Mergers and Acquisitions: American Airlines Merges With Rival US Airways Essay

Effective organizations in business are continually looking for changed approaches to improve their situation in their particular regions of activity. Mergers and acquisitions have been demonstrated to be an approach to do only that. A merger is essentially characterized as two organizations joining to make another organization, while a securing happens when one organization inside and out buys another organization. Mergers and Acquisitions are considered as the significant development technique for organizations to fulfill the expanding requests of different partners (Krishnamurti and Vishwanath, 2010). Why Merge? AMR Corporation, the parent organization of American Airlines, declared designs to converge with US Airways Group in February, 2013. This came after the company had recently petitioned for Chapter 11 liquidation security in November 2011. (Isidore, Chris) The subsequent merger made the biggest carrier on the planet. The organizations formally shaped the new American Airlines Group Inc. on December 9, 2013. (Air Transport World, Jan 2014) Doug Parker, beforehand the CEO of US Airways, and now CEO of the new American, expressed: â€Å"We are taking the best of both US Airways and American Airlines to make a considerable contender, better situated to convey for the entirety of our partners. We anticipate incorporating our organizations rapidly and productively so the huge advantages of the merger can be realized.† (Air Transport World, Jan 2014) That announcement demonstrates that the merger was shaped for two reasons: cash, and force. The two organizations were losing in the traveler air transportation field to different organizations that had as of late consolidated. Consolidating would permit the two organizations to grow their assets and gather courses and terminals into a single unit that were recently held to each independently preceding the blend. US Airways bringsâ access to littler US urban areas, while American Airlines has an enormous nearness universally, especially London and Latin America (What the American Airlines/US Airways Merger Will Mean for You, 2013). American Airlines indicated the need and requirement for cash after it nearly crumbled in chapter 11. The merger of the two organizations was a case of an even joining. This is characterized by Investopedia.com as a merger or procurement of extra business exercises on a similar degree of the worth chain in comparative or various enterprises, and can be ac complished by inner or outside development. The carrier business has changed radically over the previous decade with mergers of pretty much every significant aircraft: Delta and Northwest; United and Continental; and Southwest and AirTran. These mergers made another scene in which the tables were inclined against both US Airways and American Airlines. It was a need that the two unite so as to remain be serious and remain above water against the other as of late shaped super carriers. Those mergers additionally made an open door for income development in the ticket evaluating field. The cost of a household ticket to go full circle costs has climbed about 15% since 2009 because of expansion. The merger will enable American and US Airways to build passages with the expansion of the two organizations previous courses and terminals. What were the huge impacts of the merger? So as to be a triumph, a merger must give all gatherings included some huge increment in advantage. This merger isn't excluded from that announcement. Dailyfinance.com (2013) states that a key explanation behind the merger among American and US Airways is to interface both airlines’ systems, making a framework comparable to Delta Air Lines and United. The mix of the two outcomes in excess of 6,700 every day trips to 336 goals in 56 nations. This system will permit travelers to fly the world over without the need to make the regularly debilitating associations that they were exposed to pre-merger. The merger additionally made a moment increment in stock costs. Portions of the consolidated organization rose 2.7%. This in itself is a decent beginning for an organization in the post-chapter 11 period. The rebuilding and blending will reimburse AMR’s lenders with intrigue and give its associations and regular holders a huge portion of value in the new organization. (Susan Ca rey and Jack Nicas, 2013) Coming about Organizational Structure of the Post-Merger Company By consolidating two beforehand completely operational organizations, the hierarchical structure will be progressively mind boggling, at any rate, than it was previously. Because of the merger, American Airlines Group, Inc. presently has consolidated workforce of 110,000 individuals close by an armada of 1,511 airplane (Bohemer, 2013). Arranging such a huge workforce makes a test that requires a pioneer equipped for taking care of that task. The organization is presently lead by Chief Executive Officer W. Douglas Parker, the previous CEO and administrator of US Airways. Parker has demonstrated authority capacity, managing the merger of US Airways and America West Airlines in 2005. He likewise administered the organization during a period of record income development and expanded net revenues. Active CEO Tom Horton was in that position from 2011 through 2013, driving the organization through the merger before giving co ntrol over to Parker. Parker seems to have an edge on driving and group building, having experiencing a carrier merger beforehand. His capacity to build benefit and friends riches settles on him the undeniable decision to lead the new organization. Despite the fact that the merger has gotten last, the two organizations will even now work as discrete substances for a long time to come. This will permit the organizations more opportunity to assemble the huge structure and settle on appropriate choices to guarantee for smooth tasks later on. They profit by not being the principal aircrafts of their sizes to make this progress, as the mergers of Delta and Northwest and United and Continental have kind of made a way of what should be done so as to be an effective merger. The structure joined workers from the two aircrafts, which manufactures solidarity and shows that the organization is focused on pushing ahead together, not simply to come in and dominate. This is a decent method that more organizations ought to embrace. Alongside the physical structure change of the new American Airlines Group, there will likewise be changes that influence the buyers. Preferred customer credits will have the option to be utilized reciprocally with either American Airlines or US Airways flights. Clients will be permitted to accumulate mileage from either carriers. AA.com (n.d.) records a few advantages that AAdvantage individuals will be managed with US Airlines, and the other way around. There are likewise entryway changes that influence clients and workers, as observed with the end of US Airways Pittsburgh Terminal. In a meeting with the Pittsburgh Post Gazette, Spokesman Todd Lehmacher said â€Å"US Airways says the greater part of the 600 representatives at the Pittsburgh community will be given the choice toâ relocate to Texas, however it recognized it doesn’t anticipate that every one of them should do as such. The individuals who decide d not to go will be given a severance package.†(Mutzabaugh, 2014) Having lived in the Pittsburgh region for quite a long time, very a couple of miles of the air terminal, I realize that the pullback will enormously influence the nearby economy. HR Management Practices Whenever you consolidate two separate organizations into one, there will be contrasts to resolve. Corporate culture will without a doubt be one of the numerous Human asset challenges that the merger should survive. Hierarchical social contrasts have been contrarily connected with different bookkeeping measures and securities exchange esteem following household M&As. (Webber and Drori, 2011) Being that the organizations have comparable obligations and duties, it ought not be too hard to even think about working through these issues. There might be past practices at each organization that should be balanced so as to make the change smooth. Combining additionally introduced the chance to expand worker pay and support agreement, which would be in accordance with the other huge carriers. With the normal expanded income, there would be more assets to share among the representatives and investors. In the background gatherings, Parker furtively arranged arrangements with American’ s three primary associations, making â€Å"provisional contracts† that would give American’s laborers much better compensation and work rules. (Tully, 2013) These exchanges gave the union’s motivation to get tied up with and advance the merger. End While the merger between these two carrier mammoths didn't abandon hiccup, they were in a superior situation to make the change because of a need to by American Airlines and a need to by US Airways. American seems, by all accounts, to be the champ of the merger by coming out of chapter 11, keeping up their organization, and growing their courses and terminals. The merger was concluded on December 9, 2013 References Krishnamurti, C., and Vishwanath, S. R. (2010). Mergers, Acquisitions, and Corporate Restructuring. South Asian Journal of Management, 17(2), 169-171. American Airlines, US Airways close merger to make world’s biggest aircraft. (2014). Air Transport World, 51(1), 8. Boehmer, J. (2013). Merger Planning Underway As American, US Airways Embark On Long Journey. Business Travel News, 30(7), 28. What the American Airlines/US Airways Merger Will Mean For You. (2013, November 12). Every day Finance. Recovered from http://www.dailyfinance.com/2013/12/12/us-aviation routes american-carriers merger-purchaser sway American Airlines, US Airways Complete Merger (2013.). The Wall Street Journal. Recovered from http://online.wsj.com/news/articles/W. Douglas Parker. (n.d.). US Airways. Recovered from http://www.usairways.com/EN-US/ABOUTUS/PRESSROOM/BIOS/PARKER.HTML Weber, Y., and Drori, I. (2011). Incorporating Organizational and Human Behavior Perspectives on Mergers and Acquisitions. Universal Studies of Management and Organization, 41(3), 76-95. Tully, S. (2013, March 18). Inside the World’s Biggest Airline Merger. Fortune, 167, 169.

Types of Budget Free Essays

History of Indian Budget India’s first Finance Minister Sir R. K. Shanmugham Chetty, introduced the principal Finance Budget of free India on November 26, 1947. We will compose a custom paper test on Sorts of Budget or on the other hand any comparable subject just for you Request Now From that point forward, 28 differentUnion Finance Ministers have been introducing the spending quite a long time after year. At first, significant consideration was paid towards the horticulture area however as the economy developed, the center moved from agribusiness to different parts like mechanical, money related and so on. During the early the fifties, Indian spending features spun around the open segment and open money and thus, in those days †tax assessment, expansion, open reserve funds and so on were tremendously discussed themes. This pattern proceeded till the account financial plan 1985-86. The adjustment in the methodology started with Mr. Manmohan Singh who filled in as the Union Finance Minister under the administration of Mr. P. V. Narsimha Rao. Mr. Singh was instrumental in headstarting the new period of financial progression. He diminished the control of Government over open division units through disinvestment. The progression procedure which he began a long time back is despite everything followed and is found in interval financial plan and Indianâ budgetâ announcementsâ every year. This year additionally live association financial plan 2011 will be declared by Pranab Mukherjee. Realities Bite * First Finance Minister: Shanmugham Chetty * Number of Finance Minister Since Independence: 28 * Maximum Number of Budgets Presented by: Morarji Desai * Economic Liberalization Started by: Mr. Manmohan Singh ( Finance Minister 1991) * Current Finance Minister: Mr. P. Chidambaram Explain the various kinds of spending plans in detail, with the assistance of reasonable models. In each business arranging is the most significant capacity to perform. Arranging of various firms relies on such a significant number of variables. Arranging is accomplished for contrasting the genuine exhibition and standard execution. Spending plans are likewise arranged ahead of time. Spending plans are set up to check the accessibility of account as per the interest of task. So budgetary control is additionally fundamental instrument of the board to control cost and augments benefits. Which means of spending plan: A financial plan is a detail plan of activities for a particular timeframe. In the current time everybody is with the term financial plan since it fundamental throughout everyday life. A spending plan is set up for the successful usage of assets, which will help in accomplishing the set targets. Financial plans are additionally significant in singular life, as it is significant in business firms. Coming up next are the basic of spending plan: (an) It is set up ahead of time and depends on tentative arrangement of activity. (b) It identifies with a future period and depends on destinations to be accomplished. (c) It is an announcement communicated in fiscal or physical unit arranged for the definition of strategy. Sorts of financial plans. 1. Practical premise of spending plans. a. Deals spending plan: Sales financial plan is the essential financial plan. It is the most significant financial plan to get ready and different spending plans are set up based on deals spending plan. In this spending plan the in control or master conjecture the future anticipated deals of the firm. The project supervisor is liable for the exactness of the spending plan. The business spending plans may get ready on premise of item, sort of clients, sales rep, territory and so on for the planning of deals financial plan the accompanying things ought to be take under consideration like past deals, sales rep gauges, plant limit, crude material, arranges close by, occasional vacillations, rivalry and so forth. Utilizations: Sales spending plan is the most significant financial plan while making the general financial plan for the association for a monetary year. It is significant in this feeling how might anyone make monetary spending plan for association in the event that he don’t think about the amount to deal or what are the organization’s deal would be. On the off chance that you know the business volume of units of item you need to deal in a monetary year then you will make creation financial plan as indicated by that business prerequisite as a primary concern you will have creation data as a top priority you will buy crude material, recruit work as indicated by necessities. So on the off chance that you don’t think about the amount you need to deal, at that point how might you financial plan different things and how might you look at your presentation toward the finish of monetary year. . Creation spending plan: After getting ready deals financial plan the following spending will be creation spending plan. In this spending works administrator get ready calendar of creation by breaking enormous creation in little un its to satisfy the objective creation. An appropriately worked financial plans prompts stock control, improved support of creation calendars and creation targets. Assume, if the evaluated opening stock is 5000 units and assessed deals are 25000 units and shutting load of the item is 3000 units the evaluated creation will be 25000 + 3000 †5000 =23000 units (deals + shutting stock †opening stock). Utilizations: A creation financial plan is a bookkeeping strategy used to both record and propose fabricating flexibly costs. Keeping a sorted out creation spending plan guarantees that the gracefully of crude materials to the creation line proceeds with continuous and fulfills buyer need. Keeping up a point by point post-buying creation spending plan additionally assists with representing material misfortunes because of shrinkage. b. Material spending plan: In the creation spending material is the principal prerequisite to be thought of. Materials are fundamentally isolated into two classes as immediate and roundabout material. It incorporates the planning of evaluations of various sorts of the crude material required for different items and buying crude material in required number at a necessary time. There are scarcely any variables which ought to be taken under consideration like prerequisite of crude material; company’s loading strategies, value pattern, and cost of crude material. Utilizations: Schedule indicating how much material will be required for creation and how much material must be purchased to meet this creation prerequisite. The buy relies upon both expected use of materials and stock levels. For instance, accept anticipated creation of 790 units, 3 lbs. of material required per unit, wanted completion stock of material 216 lbs. , starting stock of material 237 lbs. , and unit cost per lb. of $2. At that point lbs. of material to be bought and buy cost follow: Labor financial plan: work is a significant factor in each creation association. Work assumes a significant job in changing over crude material into completed item. The work prerequisite spending plans arranged on premise of creation financial plan. Work might be of two sorts immediate and backhanded work. In this spending organization needs to financial plan the necessary number of hours and the normal compensation sizes of the representatives. This spending gives data about staff details for the activity for which laborers are to be selected, the level of expertise and experience required and paces of pay. Utilizations: The immediate work spending plan is normally introduced in either a month to month or quarterly organization. The fundamental computation utilized by the immediate work financial plan is to import the quantity of units of creation from the creation spending plan, and to increase this by the standard number of work hours for every unit. This yields a subtotal of the immediate work hours expected to meet the creation target. You can likewise add more hours to represent creation wasteful aspects, which builds the measure of direct work hours. At that point increase the all out number of direct work hours by the fullyâ burdenedâ direct work cost every hour, to show up at the complete expense of direct work. e. Assembling Overhead financial plans: this spending gives the works overhead costs to be acquired in a spending period to accomplish the creation target. The expense of backhanded material, aberrant work and so on can be determined with the assistance of this financial plan. For causing appropriate control it to can be partitioned into departmental overhead financial plan. Variable costs are assessed based on the planned yield in light of the fact that these costs will undoubtedly change with the adjustment in yield. Utilizations: The assembling overhead spending show the normal assembling over head costs for the spending time frame. The spending plan recognizes variable and fixed overhead expenses. Organizations change with creation volume based on the accompanying rates per direct work hour: circuitous materials $1. 00, aberrant work $1. 0, utilities $0. 40, and upkeep $0. 20. Hence, for 6,200 direct work hours planned circuitous materials are $6,200 (6,200 x $1), and planned aberrant work is $8,680 (6,200 x $1. 40). The organization perceives that some support is fixed. The sums announced for fixed expense are expected. f. Organization Expenses spending plan: The spending covers the costs caused in encircling strategies, coordinating the association a nd controlling the business activities. In financial plan a gauge of costs is readied with respect to focal office and of the executives pay rates. The financial plan might be set up at division level for viability in planning framework. The financial plan can be set up with the past experience and foreseen changes. Utilizations: The selling and managerial cost financial plan is contained the spending plans of all non-producing offices, for example, the business, advertising, bookkeeping, designing, and offices. In total, this financial plan can equal the size of theâ production spending plan, as is deserving of significant consideration. The selling and regulatory cost spending plan is regularly introduced in either a month to month or quarterly organization. It might likewise be separated into sections for a different deals and showcasing spending plan and a different organization financial plan. G. Selling and Distribution spending plans: This cost is identified with the selling and circulation of material. In this spending specialists need to get ready for the normal selling and dispersion costs of the firm. Certain things of selling and dissemination costs as cost of transportation, sales rep pay rates and so forth. Utilizations: The selling and regulatory cost financial plan is involved the spending plans of all non-

What Makes You Tick

What Makes You Tick Seeing all the parents converge on MIT campus for Family Weekend reminded me of my parents, who are one continent and one ocean away. So, on a side note, really take the time to appreciate your parents while youre still with them. This is especially true for all you high school seniors who are leaving for college a year from now. Your parents might be nagging at you about your SAT scores now and theres still technically one year left before you have to say goodbye, but theyll be gone before you know it (really.) Anyways, all this reminded me of all you Early Action applicants, who are probably cranking out application essays, having interviews, and/or worrying whether your SAT scores are high enough right now (or, at least, I hope you are just not the worrying part). Therefore, I decided to tell you my ED story. Last year, around this same time, I was pretty much in your shoes. Ive identified a college that I was very passionate about way back in August, and knew I wanted to ED it, no questions asked. I was done with the testing and other requirements fairly early, so I spent the majority of my time re-reading and re-examining my applications (while wondering why in the world my interviewer hasnt bothered to call me yet). I wrote out my essays, I polished them, and I fine-tuned them to a point that I was able to recite it backwards (Im serious). I had several of my teachers read over my essays, and I actually wrote 13 drafts for my main essay. This is like a world record for me, since I am basically the master of churning out pointless fluff insightful essays for AP testing. Simply, I just hate writing multiple drafts for a single essay. Predictably, l became paranoid about my application very quickly. I wanted it to be totally perfect. 100% perfect not 99%, or even 99.99% 100. At one point, I actually went online and searched for the right orientation of stapling pieces of paper together (the staple should ideally make a 45 degree angle to the left side of the paper, so its basically slanted, sloping up to the right) because I didnt think I should staple my papers together recklessly (afterwards, I discovered that its generally not a good idea to staple any part of your college application, actually. Many colleges scan additional sheets of paper that come in, and staples are a huge hassle.). When I clicked submit online 2 hours before the deadline, I felt I had the complete package. I had the stats, I had the essays, I had the recs I am going to college. A month and a half later, I was shocked when I received a deferral letter in the mail and this is not due to blind confidence either, as I really felt that my application was strong enough in terms of academic merit to get into the college I was applying to. I started asking myself these questions were my SAT scores not high enough? Did I not do enough activities? Was my essay too boring? Finding no answers to my queries, I plunged myself headfirst into Regular Action applications. Not to sound corny, but it was after doing the MIT application that I realized what was wrong in my Early application. I was trying too hard to be different. I was trying too hard to be the person that adcoms like. I wasnt being myself. I re-read my Early application, and I realized that I sounded like a cookie-cutter student that was trying too hard to flaunt his academic abilities. I was trying hard to impress, trying hard to be unique, but I hardly recognized the person that the application tried to convey. Realizing this, I completely took out the 13-draft essay that took me three solid weeks of revision and wrote an essay on the same topic, using the tone I liked and the angle I wanted to convey it from, not the tone and the angle that my teachers had suggested. After proofreading it carefully for grammatical errors multiple times, I sent it in without consulting another adult. I wanted this new essay to be mine, I wanted it to be from myself not from my GC, not from my teachers. The biggest piece of advice I want to give you guys as you guys approach not only the EA application, but all the future applications that you might encounter is to just be yourself in whatever you do. When you write your essay, dont write with a specific audience in mind. Dont say the things that you think the admissions officers want to hear. When you do the interview, dont try to second-guess your interviewers questions and remarks. When you describe your activities, convey your true passions. Dont say that you totally loved Student Government when you hated all the lunch meetings, and dont be shy to share the ups and downs in your life even if it may be something as simple as loving the fresh smell of grass after a spring rain. These things are what makes you different from the thousands of people applying to the same school as you are. Its not just about the four digits in your SAT score or the numbers after the decimal point in your GPA. Even a robot can be trained to take tes ts or do algebra, but what is it that makes you different from a test-taking machine? Quite simply, what tickles your heart and motivates you to overcome the challenges that youve faced in your life? I wish you guys the best of luck in your college application experience. And for those really committed to coming here, I hope MIT is a wonderful fit for you :) Im still discovering reasons to love MIT each day. Take a look: Amazing Guest Lecturers Dr. Harish Hande is a pioneer in bringing light and electricity to rural locations in India through affordable solar panel systems. iHouse had the honor of inviting him to dinner and learning about his developmental solutions for underprivileged countries. Diverse Talents Last Saturday I went with my friends to Sigma Kappas Late Night an annual charity talent show hosted by the sorority to promote research for Alzheimers Disease and saw some really amazing acts One of the most incredible things about MIT is the wealth of talents that is represented in the student body. Everyone comes here with a story to share, and it is very rewarding to discover the stories of your fellow peers. We may hail from the different corners of the world, but we are all connected by a love of learning and a deep conviction for our passions be it playing the guitar, acting in a circus, or inventing robots. Explore the stories of those people around you you will be pleasantly surprised (I still am, almost on a day-to-day basis). Unity MIT is United. We may be taking classes from Course 1 to Course 24, but we are never too busy to help the person beside us in a pset that dragged on for too long or help him study for a test that seems too difficult. I went on a retreat with my fraternity, SigEp, last weekend, and we played this game in which the objective is to lower a stick propped up by the index fingers of all the players to the ground, with the catch that no one can lose contact of the stick in the process. A couple of days after we returned from the retreat, some of the older brothers volunteered to host a study session for the froshies in anticipation for the 8.01 midterm. It is interesting to note that one of the key points in the Helium Stick activity is to constantly look out for one another, especially the people who are about to lose contact with the stick. In the same way, the people at MIT offering help to one another is in tune with the same spirit. Im not referring to just my fraternity brothers offering to prep me in 8.01, but also the guy in my 18.02 recitation that patiently explained the concept of directional vectors to me, the girl that offered to sub in for my SAT class when I have to be gone for the SigEp retreatthe list goes on and on. Anyways, this entry could quite viably be two entries, so I think I will pause here. Before I sign off though, check out this cool picture from our retreat and some excellent food. So best wishes from George 10 and me to all the Early applicants! Share your stories, explore your options, and dare to dream. George and I have every confidence in you. Right, George? Right. Heres to you all. Cheers!

Definition of Sfumato Art History Glossary

Sfumato (pronounced sfoo ·mah ·toe) is the word art historians use to describe a painting technique taken to dizzying heights by the Italian Renaissance polymath Leonardo da Vinci. The visual result of the technique is that there are no harsh outlines present (as in a coloring book). Instead, areas of dark and light blend into one another through miniscule brushstrokes, making for a rather hazy, albeit more realistic, depiction of light and color. The word sfumato means shaded, and it is the past participle of the Italian verb sfumare or shade. Fumare means smoke in Italian, and the combination of smoke and shade perfectly describes the barely perceptible gradation of tones and colors of the technique from light to dark, particularly used in flesh tones. An early, wonderful example of sfumato can be seen in Leonardos Mona Lisa. Inventing the Technique According to the art historian Giorgio Vasari (1511–1574), the technique was first invented by the Primitive Flemish school, including perhaps Jan Van Eyck and Rogier Van Der Weyden. Da Vincis first work incorporating sfumato is known as the Madonna of the Rocks, a triptych designed for the chapel in San Francesco Grande, painted between 1483 and 1485. Madonna of the Rocks was commissioned by the Franciscan Confraternity of the Immaculate Conception which, at the time, was still the object of some controversy. The Franciscans believed that the Virgin Mary was conceived immaculately (without sex); the Dominicans argued that would deny the need for Christs universal redemption of mankind. The contracted painting needed to show Mary as crowned in the living light and free from shadow, reflecting the plenitude of grace while humanity functioned in the orbit of the shadow. The final painting included a cave backdrop, which art historian Edward Olszewski says helped to define and signify Marys immaculacy—expressed by the sfumato technique applied to her face as emerging from the shadow of sin. Layers and Layers of Glazes Art historians have suggested that the technique was created by the careful application of multiple translucent layers of paint layers. In 2008, physicists Mady Elias and Pascal Cotte used a spectral technique to (virtually) strip away the thick layer of varnish from the Mona Lisa. Using a multi-spectral camera, they found that the sfumato effect was created by layers of a single pigment combining 1 percent vermillion and 99 percent lead white. Quantitative research was conducted by de Viguerie and colleagues (2010) using non-invasive advanced X-ray fluorescence spectrometry on nine faces painted by or attributed to da Vinci. Their results suggest that he constantly revised and improved the technique, culminating in the Mona Lisa. In his later paintings, da Vinci developed translucent glazes from an organic medium and laid them on the canvases in very thin films, some of which were only a micron (.00004 inches) in scale. Direct optical microscopy has shown that da Vinci achieved flesh tones by superimposing four layers: a priming layer of lead white; a pink layer of mixed lead white, vermillion, and earth; a shadow layer made with a translucent glaze with some opaque paint with dark pigments; and a varnish.  The thickness of each colored layer was found to range between 10-50 microns. A Patient Art The de Viguerie study identified those glazes on the faces of four of Leonardos paintings: Mona Lisa, Saint John the Baptist, Bacchus, and Saint Anne, the Virgin, and the Child. Glaze thicknesses increase on the faces from a few micrometers in the light areas to 30–55 microns in the dark areas, which are made of up to 20–30 distinct layers. The thickness of the paint on da Vincis canvases—not counting the varnish—is never more than 80 microns. That on St. John the Baptist is under 50. But those layers must have been laid down in a slow and deliberate fashion. The drying time between layers may have lasted from several days to several months, depending on the amount of resin and oil that was used in the glaze. That might well explain why da Vincis Mona Lisa took four years, and it was still not completed at da Vincis death in 1915. Sources: de Viguerie L, Walter P, Laval E, Mottin B, and Solà © VA. 2010. Revealing the sfumato Technique of Leonardo da Vinci by X-Ray Fluorescence Spectroscopy. Angewandte Chemie International Edition 49(35):6125-6128.Elias M, and Cotte P. 2008. Multispectral camera and radiative transfer equation used to depict Leonardos sfumato in Mona Lisa. Applied Optics 47(12):2146-2154.Olszewski EJ. 2011. How Leonardo invented sfumato. Source: Notes in the History of Art 31(1):4-9.Queiros-Conde D. 2004. The Turbulent Structure of Sfumato within Mona Lisa. Leonardo 37(3):223-228.

Pros and Cons of a Dry Campus - 809 Words

Every year, universities always have the same issue regarding alcohol. Students are constantly getting in trouble for possession or consumption. Here at Eastern Connecticut State University, the policy is a dry campus. This means that alcohol is completely prohibited on campus. There are many opinions when it comes to this choice, as there are also many pros and cons to it. One pro of having a dry campus is that students can find other events to go to. Eastern often offers other events where students can do and socialize, promoting a night without alcohol. Students can also join clubs, intramurals, sports, etc. All of these clubs and events offer a positive influence on the students by keeping them busy. According to a friend and†¦show more content†¦We are making these choices; therefore we should learn to live with the consequences. Personally, I feel that although all these deaths and injuries that occur because of alcohol, is actually the person. Yes there are more alcoh ol related incidents for college students, but that’s also because these students have no self-control and are not responsible for what they are doing. However, it’s not just happening in college. It’s happening everywhere, regardless of location. I do believe, however, that students who are underage should get punished when caught because they are breaking a law, not just a rule. In conclusion, I am not completely sure whether or not it is better to have dry campus. There are a lot of cons but there are also a lot of pros to it too. I think that it depends on the students and geography of theShow MoreRelatedSolar Panel Pros And Cons986 Words   |  4 PagesSolar Panel Pros and Cons Solar energy is the energy from the sun. It uses sunlight to produce electricity. These panels are usually installed on the roof and positioned to face the sun. 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Should Public High School Students Have Access to “The Kite Runner”‘s Content Free Essays

Should Public High School students have access to â€Å"The Kite Runner†Ã¢â‚¬Ëœs content? Khaled Hosseni’s famous novel, â€Å"The Kite Runner† is one of the most popular books of the decade. It is #1 New York Bestseller with sold more than 10 million copies. Even though the book has immense popularity, the book is banned in several countries including Afghanistan, Hosseni’s mother land because of its sexual orientation and the use of vulgar language. We will write a custom essay sample on Should Public High School Students Have Access to â€Å"The Kite Runner†Ã¢â‚¬Ëœs Content or any similar topic only for you Order Now The government believes the novel will outrage the Afghan community and may lead to chaotic situation. Even though some advocates of banning the novel for education curriculum may argue that, the book contains rapes in graphic detail, the use of vulgar language, offensive language and ethnic tensions, these romantic critics are too dogmatic in their provincial ideology. Hosseni’s novel, â€Å"The Kite Runner† shouldn’t be banned from high school students because of its teaching about loyalty, forgiveness, sacrifice and also provides an insight of real world alongside its immense popularity. Khaled Hosseni’s best-seller book, â€Å"The Kite Runner† shouldn’t be banned from high school curriculum. The book demonstrates different incidents which provide important lessons for the reader through its quotes. For example, when Amir talked about sin, Baba said, â€Å"No matter what the mullah teaches, there is only one sin, only one. And that is theft† (Hosseni, 17). Baba believed stealing is the only sin a person can commit; other crimes are just different form of crime. This demonstrates the discouragement of vice, exists in the novel, which has great impact on reader’s mind. Additionally, the book provides a depth insight of the real world. It demonstrates the depravity of the war, the importance of kinship and also encourages people to stand up for the truth and demolish the false. So that’s why the book shouldn’t be banned. On the other hand, the opponents of the idea argue to deny the access of book to public high school students for various reasons. The book contains a sodomy rape scene in graphic detail which is arguably inappropriate for high school students. †(Green, Tracy. It’s Banned Book of the Week? Why Kite Runner? www. authorexposure. com . Sept 30, 2009. Web. April 13, 2013. http://www. authorexposure. com/2009/09/its-banned-book-week-why-kite-runner. html) As Assef tries to teach Hassan a lesson, â€Å"Assef knelt behind Hassan, put his hand on Hassan’s hips and lifted his bare buttocks. He k ept one hand on Hassan’s back and undid his own belt buckle with his free hand. He unzipped How to cite Should Public High School Students Have Access to â€Å"The Kite Runner†Ã¢â‚¬Ëœs Content, Essays

Lamb to the Slaughter vs Speckled Band Essay Thesis Example For Students

Lamb to the Slaughter vs Speckled Band Essay Thesis The murder mystery genre was first recognised as a major genre during the 19th century. Pioneers of this genre include the Norwegian writer Mauritz Hansen as his novel The murder of machine operator Rolfsen, published in 1839 is considered to be the earliest known novel of this genre. Another pioneer of the genre includes Edgar Allan Poe. Many of the conventions associated with the murder mystery genre prior to Doyle arriving onto the murder mystery scene, would have been invented by Hansen and Poe and would have influenced Doyle in his stories (Its fairly well known that Doyle was a very keen reader of Poes works). However, Sir Arthur Conan Doyle, unlike Hansen or Poe, is believed to have popularised the genre with his Sherlock Holmes stories. There are various conventions associated with the genre. The most well known conventions of this genre include: a typically vulnerable female victim, the use of a sinister weapon for the murder, dark and horrific setting(s) for the scene of the crime(s). Other conventions of this genre include the motives behind the murder(s) generally being of vengeance, jealousy or financial gain. Yet another convention is the method used to kill the victim: poison, strangulation, stabbing, gunshot. There are conventions also in the way the crimes are uncovered and solved: the crimes were typically solved by a detective who is sharp, intellectual and fervent about their job; never failing to inspect even the most diminutive details. Another conventions attached to this genre is the author using fairly vague but convincing details, clues to mislead the readers (red-herrings) and of course the perpetrator eventually being brought to justice. In Lamb to the Slaughter Dahl subverts the conventions of the genre from the very first beginning as he names the book Lamb to the Slaughter; giving the reader an impression that something rather sinister is going to take place or that an innocent lamb is going to be lead to the slaughter. The title however juxtaposes with the beginning of the story; setting a very inviting and clean atmosphere for the crime scene instead of the conventionally dark and gloomy setting. Dahl also subverts the conventions by being meticulously detailed about simple, everyday objects, surroundings and actions e.g. instead of mentioning that Mr. Maloney drank the whiskey, Dahl gives particular attention to the fact that he unusually drained half of the drink in one go.  This builds tension by making Mr. Maloney look like the to be perpetrator; describing his actions an ominous slant prior to revealing the plaintive news to his wife, e.g. keeping his head down to avoid light hitting the lower part of his face and the slight twitch in the corner of his left eye. This also builds tension as it makes Mr. Maloney look villainous and creating anticipation within the reader for the crime to take place. Here onwards Dahl simply writes about Mrs. Maloneys feelings to the lamenting news revealed by her husband. This was done to ease the tension and for the readers to sympathise and understand her before they find out about the real perpetrator.  However, tensions start rising again in the paragraph that contains a mere four words; A leg of lamb. This sentence is left alone as a paragraph to help the readers realise the fact that this is the point where the titles meaning is going to be revealed (this builds up tensions amongst the readers making them anxious to know what takes place next). Dahl cleverly gets across the message that Mrs. Maloneys act of violence was unplanned in a few different ways. Firstly, as the narrator he ridicules her choice of weapon (the leg of lamb) saying: She might just as well have hit him with the steel club. Secondly he uses dialogue to further the point that it was unplanned; All right, so Ive killed him. Thirdly Dahl points out the fact that she rehearsed what to say to the grocer several times (something that isnt required if the murder was planned).  Another convention that gets subverted is that the murderer (Mary Maloney) calls the police herself. She also knows most of the policemen that came that night to investigate the crime scene and affectionately calls the Sergeant (Jack Noonan) by his name, instead of calling him Sergeant. Also worth noting is the fact that the investigators (detectives) know the murderer and the victim. .u40893de83a0a987da2d6a20371f97b00 , .u40893de83a0a987da2d6a20371f97b00 .postImageUrl , .u40893de83a0a987da2d6a20371f97b00 .centered-text-area { min-height: 80px; position: relative; } .u40893de83a0a987da2d6a20371f97b00 , .u40893de83a0a987da2d6a20371f97b00:hover , .u40893de83a0a987da2d6a20371f97b00:visited , .u40893de83a0a987da2d6a20371f97b00:active { border:0!important; } .u40893de83a0a987da2d6a20371f97b00 .clearfix:after { content: ""; display: table; clear: both; } .u40893de83a0a987da2d6a20371f97b00 { display: block; transition: background-color 250ms; webkit-transition: background-color 250ms; width: 100%; opacity: 1; transition: opacity 250ms; webkit-transition: opacity 250ms; background-color: #95A5A6; } .u40893de83a0a987da2d6a20371f97b00:active , .u40893de83a0a987da2d6a20371f97b00:hover { opacity: 1; transition: opacity 250ms; webkit-transition: opacity 250ms; background-color: #2C3E50; } .u40893de83a0a987da2d6a20371f97b00 .centered-text-area { width: 100%; position: relative ; } .u40893de83a0a987da2d6a20371f97b00 .ctaText { border-bottom: 0 solid #fff; color: #2980B9; font-size: 16px; font-weight: bold; margin: 0; padding: 0; text-decoration: underline; } .u40893de83a0a987da2d6a20371f97b00 .postTitle { color: #FFFFFF; font-size: 16px; font-weight: 600; margin: 0; padding: 0; width: 100%; } .u40893de83a0a987da2d6a20371f97b00 .ctaButton { background-color: #7F8C8D!important; color: #2980B9; border: none; border-radius: 3px; box-shadow: none; font-size: 14px; font-weight: bold; line-height: 26px; moz-border-radius: 3px; text-align: center; text-decoration: none; text-shadow: none; width: 80px; min-height: 80px; background: url(https://artscolumbia.org/wp-content/plugins/intelly-related-posts/assets/images/simple-arrow.png)no-repeat; position: absolute; right: 0; top: 0; } .u40893de83a0a987da2d6a20371f97b00:hover .ctaButton { background-color: #34495E!important; } .u40893de83a0a987da2d6a20371f97b00 .centered-text { display: table; height: 80px; padding-left : 18px; top: 0; } .u40893de83a0a987da2d6a20371f97b00 .u40893de83a0a987da2d6a20371f97b00-content { display: table-cell; margin: 0; padding: 0; padding-right: 108px; position: relative; vertical-align: middle; width: 100%; } .u40893de83a0a987da2d6a20371f97b00:after { content: ""; display: block; clear: both; } READ: A Personal Experience In The Arts EssayYet another convention that gets broken is the fact that all the policeman are extremely kind towards Mary Maloney and after arriving on the scene, rule out her involvement in the murder completely, not something a dedicated but emotionless detective would do. They are also later found to be negligent when it came to their work guidelines i.e. consuming alcoholic drinks.  Peculiarly the police officers dont bother asking her to go vacate the house to some other place instead to search the property. They also failed to decline Mary Maloneys request of eating up the lamb.

Electronic Banking Essays - Payment Systems, E-commerce, Banking

Electronic Banking The Electronic Banking Association (EBA) is a non-profit organization established to do one simple thing-help more people get started with electronic banking. Here's why. Who taught you how to write paper checks? Probably your parent's right? Well, who's going to teach you how to write electronic checks? Probably NOT your parents. That's where they come in. E-banking is so much more convenient and so much quicker that everyone should know about it. The EBA was established as an independent source of helpful information about electronic banking for consumers and businesses. Financial institutions, merchants, and other financial service firms actually provide financial e-commerce services, but the Electronic Banking Association (EBA) monitors progress in the financial e-commerce industry and provides information that will enable users of those services to become better informed and to locate providers of the services they seek. Everyone hates paying bills. It's time-consuming, frustrating, and you have to lick that awful envelope glue. But not with e-banking. You'll spend less time paying bills, and more time doing fun stuff. Here are some advantages to e-banking: - No more paper checks. Your computer remembers who you write checks to. You simply enter an amount then point-and-click. You'll never run out of checks again. - No more hassles. You can schedule your payments in advance, so they'll get paid while you're on vacation or away on business. Electronic payments are processed quickly, in as little as 24 hours to 5 days (unlike a paper check sent in the mail, which takes an average of 10 days to post). - No more envelopes to lick. No envelope glue. No paper cuts on your tongue. And you can stop writing your return address again, and again, and again. - No more writer's cramp. It takes forever to write checks and addresses every month. E-banking cuts that time to practically nothing. - No more stamps. With e-banking, there's no postage and your bills are processed quickly - whenever you want them paid. You can pay your bills online, so it only makes sense to receive them that way, too. This is called "Electronic Bill Presentment," and more and more businesses are going to offer it. - No more lost bills. Your dog can't eat electronic bills. Your kids can't misplace them. And you can't lose them under a stack of catalogs. - Pay bills when you want to. Not when the post office decides to deliver them. Click to see it. Click to pay it. Your bills appear right on your computer screen and look much like the printed bills you are used to getting. But the difference is you can pay them with just the click of a mouse. - Better record keeping. All your billing and payment information is kept in one convenient location, not in messy cardboard boxes or goodness only knows where else. You can pay your bills online, so it only makes sense to receive them that way, too. This is called "Electronic Bill Presentment," and more and more businesses are going to offer it. In addition to paying bills online, you can get current information any time you want it. So you can get up-to-date account balances, transfer funds, obtain information about check clearing; all sorts of things. You can import this information directly into today's popular financial management programs such as Quicken? without having to re-enter it. You buy things all the time with credit cards, right? Well then, those are electronic transactions just like these. Today's latest Web browsers have sophisticated encryption that's very secure. What's more, electronic checks are safer than having paper checks lying around where anyone can obtain and misuse your account information. Experts predict it would take a hacker over 2,000 years to crack 56-bit encryption. Yet many financial institutions today require a browser that supports 128-bit encryption, which would take about 12,710,204,652,610,000,000,000,000 years to crack. Now that's secure. (Source: Byte Magazine) When you're ready to open an e-banking account, you can receive more information on security, as well as a recent browser that supports 128-bit encryption, through your financial institution or at the Netscape and Microsoft Web sites. In the time it takes you to pay your bills the old-fashioned way, you can be up and running with e-banking. Best of all, once you enter who you pay bills to, you'll never have to re-enter that information. Your financial institution may offer e-banking via the Web or a personal financial manager or both. Web-based e-banking is generally easier and quicker to set up. All you'll need is a recent

Sample Autobiography Translated to Spanish Essays

Sample Autobiography Translated to Spanish Essays Sample Autobiography Translated to Spanish Essay Sample Autobiography Translated to Spanish Essay Essay Topic: Autobiography of My Mother I am Mark Alexis Alaban, 18 years young. I currently live in Tanza Gua, Roxas City. I’m a third year student of the College of Business Management and Accountancy, taking Bachelor of Science in Information Technology, studying in Colegio de la Purisima Concepcion. I was born in a small town of Tanza Gua and was a farm field behind my house. I spent most of my time playing outside with the neighborhood children. In my family, I have one brother who is eleven years older than me. I really appreciate the fact that I have a stay at home mother and father. It was nice to come home to a house that was not empty. My dad is a government employee and my mom is a plain house wife. For over 18 years I have been passionate about taking pictures. It’s been my hobby and pastime. Now, I have decided to create my own corner of cyberspace to share my love of photography. My childhood consisted of a fascination of watching the environment and thats how I love to spend my time to take a snapshots. Photography is my complete existence. I spend countless hours looking at every book and image. There is nothing in my life except photography. We all have creative abilities; I was raised with no exposure to art and grew up believing that I had no talent. As for processing, I spend hours on each image until I am happy with the results. ?I didnt set out to be a photographer. It just kind of happened. ?What I can tell you are that I really love what I do and I spend a lot of time refining, perfecting and even obsessing over my work. It is a passion. ?I relish the opportunity of being at one with my surroundings and aim to capture the wonderful world around me. I love nature, I find beauty in everyday things and I enjoy. I think a photography class should be a requirement in all educational programs because it makes you see the world rather than just look at it. To capture memories that will last a lifetime even if you may not. ? ?I spent half of my life thinking that a camera was just for capturing family snapshots or recording events. Then came the day when I realized that some people use it to create art. I spent the other half of my life admiring hose people’s work, convinced that photography as an art was something beyond my reach. At the end of the day, I know my passion for this activity comes from my joy of â€Å"being one with nature† and being able to escape the daily worries and hassles of work and life. I believe a great photograph can share the experience and a great photo can â€Å"tell a thousand words† if taken properly. I suppose this is my immodest goal that I strive to reach each time I pick up my cam era and head out the door. Soy Marcos Alexis Alaban, 18 anos joven. Actualmente vivo en Tanza Gua, de Roxas City. Soy un estudiante de tercer ano de la Facultad de Administracion de Empresas y Contabilidad, teniendo Licenciatura en Ciencias en Tecnologia de la Informacion, estudiando en el Colegio de la Purisima Concepcion. Naci en un pequeno pueblo de Tanza Gua y era un campo de cultivo detras de mi casa. Pase la mayor parte de mi tiempo jugando afuera con los ninos del barrio. En mi familia, tengo un hermano que es once anos mayor que. Realmente aprecio el hecho de que tengo una estancia en la casa madre y el padre. Fue agradable volver a casa a una casa que no estaba vacio. Mi padre es un empleado del gobierno y mi madre es ama de casa normal. Desde hace mas de 18 anos he sido un apasionado de la toma de fotografias. Ha sido mi hobby y pasatiempo. Ahora, he decidido crear mi propio rincon del ciberespacio para compartir mi amor por la fotografia. Mi infancia consistio en una fascinacion de ver el medio ambiente y asi es como me gusta pasar mi tiempo para tomar unas instantaneas. La fotografia es mi existencia completa. Me paso horas y horas mirando a todos los libros y la imagen. No hay nada en mi vida, excepto la fotografia. Todos tenemos capacidades creativas; me crie sin exposicion al arte y crecio creyendo que no tenia talento. En cuanto a la transformacion, me paso horas en cada imagen hasta que este satisfecho con los resultados. Yo no tenia la intencion de ser un fotografo. Esto solo sucedio. Lo que puedo decir es que me encanta lo que hago y yo pasamos mucho tiempo refinacion, perfeccionando y hasta obsesionado con mi trabajo. Es una pasion. Me entusiasma la oportunidad de estar en armonia con mi entorno y tratar de capturar el maravilloso mundo que me rodea. Me encanta la naturaleza, encuentro la belleza en las cosas cotidianas y disfrutar yo. Creo que una clase de fotografia deberia ser un requisito en todos los programas educativos, ya que te hace ver el mundo en lugar de solo mirarlo. Para capturar recuerdos que duraran toda la vida, incluso si usted no puede. Pase la mitad de mi vida pensando que una camara era solo para la captura de instantaneas familiares o eventos de grabacion. Entonces llego el dia en que me di cuenta de que algunas personas lo utilizan para crear arte. Me pase la otra mitad de mi vida admirando el trabajo de esa gente, convencida de que la fotografia como arte era algo fuera de mi alcance. Al final del dia, se que mi pasion por esta actividad proviene de mi alegria de ser uno con la naturaleza y ser capaz de escapar de las preocupaciones diarias y los problemas de trabajo y de vida. Creo que una gran fotografia pueden compartir la experiencia y una gran foto se puede decir mas que mil palabras, si se toma correctamente. Supongo que es mi objetivo inmodesto que me esfuerzo para llegar a cada vez que cojo mi camara y la cabeza por la puerta.

Economic development of India and China Essay Example | Topics and Well Written Essays - 1750 words

Economic development of India and China - Essay Example In the case of China, there is consensus that, in the past three decades, the country’s leadership adopted policies aimed at accumulation of wealth for rapid industrialisation and export of industrial goods (Zhijun and Jing, 2011). Prior to 1979, the country’s national planning was a catastrophe. This led to poor showing on economic scales. In India’s case, poor economic performance in the 1960s throughout 1970s has been associated with several issues including poor policies, and license-permits (Kshetri, 2011). Yet India’s poor infrastructure and lack of demand also contributed to the country’s industrial growth. The two countries adopted policies aimed at addressing their challenges, which have effectively turned around their economies since 1980s. Overview of both economies On the key economic developments in recent times, China and India occupy the first and second positions in Asia respectively (Dong et al, 2013). The two nations are by their b ig population size, global economic powerhouses. Whereas they develop the industries, it is clear that their growth will have deep impacts, not just within the countries but for the better part of the global economy. Such impacts which are already on record include; new market opportunities, stemming from improved purchasing power and higher competitiveness of the two greatest economies in Asia known for particular industrial commodities (Zhou et al, 2010; Prime et al, 2012). China and India have had very rapid economic development which has led to significant achievements, especially on poverty reduction. The two countries also experience problems arising from rapid economic development such as the increasing gap between rural and urban income earners and pollution of the environment (Das, 2012). Afan (2013) indicated that increasing incomes trigger structural transformation in the agricultural sector and food industry as the economy encounters changes in demand and consumer prefer ences. Concomitantly the effects will impact on trade, business and investment. Both global economic giants have undergone positive growth in the agricultural sector, followed by fast-developing industrial sectors and a huge slump in relative poverty. Das (2012) pointed to the difference in the preconditions and the triggering economic factors behind growth in the two countries. Massive agricultural production Both China and India have massively invested in agriculture (Dorn, 2013). The Chinese economy manifests the significant impact of agriculture on the country’s economic mix, especially in the 1980s and 1990s, when major economic reform took effect in the country (Liu, Liu, and Wei, 2005). In India, the lesser industrialized power of the two, agricultural production continues to occupy a very important part of the economy. While agriculture's portion in the Gross Domestic Product (GDP) has been on a downward trend, the industry still provides massive employment opportunit ies for the locals (Agrawal, and Khan, 2011; Bensidoun, Lemoine, and Unal, 2009). Economic contribution in this sector is undeniably of tremendous significance for prospective policies and measures aimed at the realization of the Millennium Development Goals (MDGs). This is especially true for the need to alleviate abject poverty and food insecurity in the economy by 2015 (Winters, and Yusuf, 2007; Gupta, and Wang, 2009). Appropriate economic responses China’s and India’s economic growth can be attributed to the tactful manner in which they have responded to new global adjustments such as free trade, globalization, agricultural production, rural growth and poverty alleviation (Das, 2012). The two countries

Personal statement Essay Example | Topics and Well Written Essays - 250 words - 8

Personal statement - Essay Example I am deeply aware that any interest in life can best translate into a real-time success only through impeccable academic credentials. My father himself built his military career on the foundation of his study at Sandhurst Academy in the UK. In line with this belief, I chose to pursue my Bachelor of Science in International Business Management at Lynn University. As a senior, I can confidently say that this is indeed what I want to do with my life. I have enjoyed all my undergraduate courses, particularly Operations, Management, Marketing and Finance. I perceive that Masters in Information Technology from a reputed university like Pace is the logical next step to open the doors to my entry into the tech industry. Right from High School, I have grabbed every opportunity to gain computer related knowledge. My internship with the Gardeniya Ladies Centre at Alkhobar, Saudi Arabia, gave me valuable exposure to customer relations. I learned that interpersonal communication is the bedrock of any commercial venture. I went on to another internship at the Click Travel Agency in Jeddah, Saudi Arabia, where I scheduled flight arrivals and departures, and honed my organizational prowess. I am confident that my internships have given me valuable skills in time management, dispute resolution and innovative packages design. At Lynn, I am a faithful and interested participant in the numerous CEO presentations on campus, absorbing the invaluable, first-hand inputs of professional businessmen and entrepreneurs. I also made use of the opportunity to be a part of the preparation for the 2012 Presidential Debate hosted at Lynn. What a learning experience that was! I believe that volunteer work is the ideal way to self-fulfillment. One of the most enriching periods of my life is the time I spent as a student volunteer at the Senior Nursing Home/ Orphanage Facility for Children at Dammam, Saudi Arabia. I was part of a social media campaign to

Modelling of Meromorphic Retina

Modelling of Meromorphic Retina CHAPTER 1 INTRODUCTION and literature review 1. INTRODUCTION The world depends on how we sense it; perceive it and how we act is according to our perception of this world. But where from this perception comes? Leaving the psychological part, we perceive by what we sense and act by what we perceive. The senses in humans and other animals are the faculties by which outside information is received for evaluation and response. Thus the actions of humans depend on what they sense. Aristotle divided the senses into five, namely: Hearing, Sight, Smell, Taste and Touch. These have continued to be regarded as the classical five senses, although scientists have determined the existence of as many as 15 additional senses. Sense organs buried deep in the tissues of muscles, tendons, and joints, for example, give rise to sensations of weight, position of the body, and amount of bending of the various joints; these organs are called proprioceptors. Within the semicircular canal of the ear is the organ of equilibrium, concerned with the sense of balance. General senses, which produce information concerning bodily needs (hunger, thirst, fatigue, and pain), are also recognized. But the foundation of all these is still the list of five that was given by Aristotle. Our world is a visual world. Visual perception is by far the most important sensory process by which we gather and extract information from our environment. Vision is the ability to see the features of objects we look at, such as color, shape, size, details, depth, and contrast. Vision is achieved when the eyes and brain work together to form pictures of the world around us. Vision begins with light rays bouncing off the surface of objects. Light reflected from objects in our world forms a very rich source of information and data. The light reflected has a short wavelength and high transmission speed that allow us a spatially accurate and fast localization of reflecting surfaces. The spectral variations in wavelength and intensity in the reflected light resemble the physical properties of object surfaces, and provide means to recognize them. The sources that light our world are usually inhomogeneous. The sun, our natural light source, for example, is in good approximation a point sou rce. Inhomogeneous light sources cause shadows and reflections that are highly correlated with the shape of objects. Thus, knowledge of the spatial position and extent of the light source enables further extraction of information about our environment. Our world is also a world of motion. We and most other animals are moving creatures. We navigate successfully through a dynamic environment, and we use predominantly visual information to do so. A sense of motion is crucial for the perception of our own motion in relation to other moving and static objects in the environment. We must predict accurately the relative dynamics of objects in the environment in order to plan appropriate actions. Take for example the following situation that illustrates the nature of such a perceptual task: the batsman a cricket team is facing a bowler. In order to get the boundary on the ball, he needs an accurate estimate of the real motion trajectory of the ball such that he can precisely plan and orchestrate his body movements to hit the ball. There is little more than just visual information available to him in order to solve the task. And once he is in motion the situation becomes much more complicated because visual motion information now represents the relative motion between him and the ball while the important coordinate frame remains static. Yet, despite its difficulty, with appropriate training some of us become astonishingly good at performing this task. High performance is important because we live in a highly competitive world. The survival of the fittest applies to us as to any other living organism, although the fields of competition might have slightly shifted and diverted during recent evolutionary trends. This competitive pressure not only promotes a visual motion perception system that can determine quickly what is moving where, in which direction, and at what speed; but it also forces this system to be efficient. Efficiency is crucial in biological systems. It encourages solutions that consume the smallest amount of resources of time, substrate, and energy. The requirement for efficiency is advantageous because it drives the system to be quicker, to go further, to last longer, and to have more resources left to solve and perform other tasks at the same time. Thus, being the complex sensory-motor system as the batsman is, he cannot dedicate all of the resources available to solve a single task. Compared to human perceptual abilities, nature provides us with even more astonishing examples of efficient visual motion perception. Consider the various flying insects that navigate by visual perception. They weigh only fractions of grams, yet they are able to navigate successfully at high speeds through complicated environments in which they must resolve visual motions up to 2000 deg/s. 1.1 ARTIFICIAL SYSTEMS What applies to biological systems applies also to a large extent to any artificial autonomous system that behaves freely in a real-world environment. When humankind started to build artificial autonomous systems, it was commonly accepted that such systems would become part of our everyday life by the year 2001. Numberless science-fiction stories and movies have encouraged visions of how such agents should behave and interfere with human society. And many of these scenarios seem realistic and desirable. Briefly, we have a rather good sense of what these agents should be capable of. But the construction is still eluding. The semi- autonomous rover of NASAs recent Mars missions or demonstrations of artificial pets are the few examples. Remarkably the progress in this field is slow than the other fields of electronics. Unlike transistor technology in which explosion of density is defined by the Moores law and also in terms of the computational powers the performance of autonomous systems is still not to the par. To find out the reason behind it we have to understand the limitation of traditional approaches. The autonomous system is the one that perceives, takes decision and plans action at a cognitive level, in doing so it must show some degree of intelligence. Returning back to the batsman example, he knows exactly what he has to do to dispatch the ball to the boundary, he has to get into a right position and then hit the ball with a precise timing. In this process, the photons hit the retina and then muscle force is applied. The batsman is not aware that this much is going on into his body. The batsman has a nervous system, and one of its many functions is to instantiate a transformation layerbetween the environme nt and his cognitive mind. The brain reduces and preprocesses the huge amount of noisy sensory data, categorizes and extracts the relevant information, and translates it into a form that is accessible to cognitive reasoning. Thus it is clear here that the there is cluster of process that takes place in a biological cognitive system in a very short time duration. And also that an important part of this whole process is transduction although it is not the one that can solely perform the whole complex task. Thus perception is the interpretationof sensory information with respect to the perceptual goal. The process is shown in the fig-1. 1.2 DIFFERENCE BETWEEN BIOLOGICAL SYSTEMS AND COMPUTERS The brain is fundamentally differently organized than a computer and science is still a long way from understanding how the whole thing works. A computer is really easy to understand by comparison. Features (or organization principles) that clearly distinguish a brain from a computer are: Massive parallelism, Distributed storage, Asynchronous processing, and Self organization. The computer is still a basically serially driven machine with a centralized storage and minimal self organization. The table 1.1 enlists these differences. Table 1.1 Differences in the organization principles and operation of computer and brain The digital computation may become so fast that it may solve the present problems and also it may become possible that the autonomous systems are made by digital components that are as powerful as efficient and as intelligent as we may imagine in our wildest dreams. However there are doubts in it and so we have to switch to an implementation framework that can realize all these things. 1.3 NEURAL COMPUTATIONS WITH THE HELP OF ANALOG INTEGRATED CIRCUITS It was Carver Mead who, inspired by the course â€Å"The Physics of Computation† he jointly taught with John Hopfield and Richard Feynman at Caltech in 1982, first proposed the idea of embodying neural computation in silicon analog very large-scale integrated (aVLSI) circuits. Biological neural networks are examples of wonderfully engineered and efficient computational systems. When researchers first began to develop mathematical models for how nervous systems actually compute and process information, they very soon realized that one of the main reasons for the impressive computational power and efficiency of neural networks is the collective computation that takes place among their highly connected neurons. And in researches, it is also well established that these computations are not undertaken digitally although the digital way is much simpler. Real neurons have a cell membrane with a capacitance that acts as a low-pass filter to the incoming signal through its dendrites; they have dendritic trees that non-linearly add signals from other neurons, and so forth. Network structure and analog processing seem to be two key properties of nervous systems providing them with efficiency and computational power, but nonetheless two properties that digital compute rs typically do not share or exploit. 1.4 LITERATURE REVIEW 1. Biological information-processing systems operate on completely different principles from those with which most engineers are familiar. For many problems, particularly those in which the input data are ill-conditioned and the computation can be specified in a relative manner, biological solutions are many orders of magnitude more effective than those we have been able to implement using digital methods. This advantage can be attributed principally to the use of elementary physical phenomena as computational primitives, and to the representation of information by the relative values of analog signals, rather than by the absolute values of digital signals. This approach requires adaptive techniques to mitigate the effects of component differences. This kind of adaptation leads naturally to systems that learn about their environment. Large-scale adaptive analog systems are more robust to component degradation and failure than are more conventional systems, and they use far less power . For this reason, adaptive analog technology can be expected to utilize the full potential of wafer scale silicon fabrication 2. The architecture and realization of microelectronic components for a retina-implant system that will provide visual sensations to patients suffering from photoreceptor degeneration. Special circuitry has been developed for a fast single-chip CMOS image sensor system, which provides high dynamic range of more than seven decades (without any electronic or mechanical shutter) corresponding to the performance of the human eye. This image sensor system is directly coupled to a digital filter and a signal processor that compute the so-called receptive-field function for generation of the stimulation data. These external components are wireless, linked to an implanted flexible silicon multielectrode stimulator, which generates electrical signals for electro stimulation of the intact ganglion cells. All components, including additional hardware for digital signal processing and wireless data and power transmission, have been fabricated using in-house standard CMOS technology 3. The circuits inspired by the nervous system that either help verifying neuron physiological models, or that are useful components in artificial perception/action systems. Research also aims at using them in implants. These circuits are computational devices and intelligent sensors that are very differently organized than digital processors. Their storage and processing capacity is distributed. They are asynchronous and use no clock signal. They are often purely analog and operate time continuous. They are adaptive or can even learn on a basic level instead of being programmed. A short introduction into the area of brain research is also included in the course. The students will learn to exploit mechanisms employed by the nervous system for compact energy efficient analog integrated circuits. They will get insight into a multidisciplinary research area. The students will learn to analyze analog CMOS circuits and acquire basic knowledge in brain research methods. 4. Smart vision systems will be an inevitable component of future intelligent systems. Conventional vision systems, based on the system level integration (or even chip level integration) of an image (usually a CCD) camera and a digital processor, do not have the potential for application in general purpose consumer electronic products. This is simply due to the cost, size, and complexity of these systems. Because of these factors conventional vision systems have mainly been limited to specific industrial and military applications. Vision chips, which include both the photo sensors and parallel processing elements (analog or digital), have been under research for more than a decade and illustrate promising capabilities. 5. Dr. Carver Mead, professor emeritus of California Institute of Technology (Caltech), Pasadena pioneered this field. He reasoned that biological evolutionary trends over millions of years have produced organisms that engineers can study to develop better artificial systems. By giving senses and sensory-based behavior to machines, these systems can possibly compete with human senses and brings an intersection between biology, computer science and electrical engineering. Analog circuits, electrical circuits operated with continuous varying signals, are used to implement these algorithmic processes with transistors operated in the sub-threshold or weak inversion region (a region of operation in which transistors are designed to conduct current though the gate voltage is slightly lower than the minimum voltage, called threshold voltage, required for normal conduction to take place) where they exhibit exponential current voltage characteristics and low currents. This circuit paradigm pr oduces high density and low power implementations of some functions that are computationally intensive when compared with other paradigms (triode and saturation operational regions). {A triode region is operating transistor with gate voltage above the threshold voltage but with the drain-source voltage lower than the difference between the gate-source voltage and threshold voltage. For saturation region, the gate voltage is still above the threshold voltage but with the drain-source voltage above the difference between the gate-source voltage and threshold voltage. Transistor has four terminals: drain, gate, source and bulk. Current flows between the drain and the source when enough voltage is applied through the gate that enables conduction. The bulk is the body of the transistor.}. As the systems mature, human parts replacements would become a major application area of the Neuromorphic electronics. The fundamental principle is by observing how biological systems perform these func tions robust artificial systems are designed. 6. In This proposed work a circuit level model of Neuromorphic Retina, this is a crude electronic model of biologically inspired smart visual sensors. These visual sensors have integrated image acquisition and parallel processing. Having these features neuromorphic retina mimics the neural circuitry of bionic eye. The proposed electronic model contains adaptive photoreceptors as light sensors and other circuit components such as averaging circuits, circuits representing ganglion cells, neuronal firing circuits etc that junction to sense brightness, size, orientation and shape to distinguish objects in closer proximity. Although image-processing features are available with modern robots but most of the issues related to image processing are taken care by software resources. Whereas machine vision with the help of neuromorphic retina is empowered with image processing at the front end. With added hardware resources, processing at the front end can reduce a lot of engineering resources for making electronic devices with sense of vision. 1.5 OBJECTIVES OF THE PRESENT WORK This project work describes a circuit level model of Neuromorphic Retina, which is a crude electronic model of biologically inspired smart visual sensors. These visual sensors have integrated image acquisition and parallel processing. Having these features neuromorphic retina mimics the neural circuitry of bionic eye. The proposed electronic model contains adaptive photoreceptors as light sensors and other neural firing circuits etc at junction to sense brightness, size, orientation and shape to distinguish objects in closer proximity. Although, image processing features are available with modern robots but most of the issues related to image processing are taken care by software resources. Whereas, machine vision with the help of neuromorphic retina is empowered with image processing at the front end. In this paper it has been shown that with added hardware resources, processing at the front end it can reduce a lot of engineering resources as well as time for making electronic devic es with sense of vision. . The objectives of present work are: Modelling of Neuromorphic Retina The photoreceptor block The horrizontal cell block The transistor mesh implemented with cmos technology The integerated block The integrated block of prs, horizontal cells and bipolar cells The spike generation circuit 1.6 Concluding Remarks In this chapter, the function of the artificial system, difference between brain and computer work is described. The present work is focused on designing of neuromorphic retina layer circuits. Many successful studies have been carried out by the researchers to study the behavior and failure of neuromorphic retina. Some investigators have performed the experimental work to study the phenomenon of the neuromorphic retina. Chapter 2 conations the biological neurons and the electronics of neuromorphic retina in this the descriptions of silicon neurons, electrical nodes as neurons, perceptrons, integrate fire neurons, biological significance of neuromorphic systems, neuromorphic electronics engineering methods, process of developing a neuromorphic chip. Chapter 3 describes the artificial silicon retina, physiology of vision, the retina, photon to electrons, why we require the neuromorphic retina?, the equivalent electronic structure, visual path to brain. In chapter 4 designing and implementation of neuromorphic retina in this the description of the photoreceptor block, the horrizontal cell block, the integerated block, the integrated block of photoreceptors, horizontal cells and bipolar cells, the spike generation circuit. In chapter 5 the design analyses and test results of neuromorphic retina layers. The results are summarized in the form of conclusion in Chapter 6 CHAPTER-2 BIOLOGICAL neurons AND neuromorphic electronics 2.1 INTRODUCTION Neuromorphic systems are inspired by the structure, function and plasticity of biological nervous systems. They are artificial neural systems that mimic algorithmic behavior of the biological animal systems through efficient adaptive and intelligent control techniques. They are designed to adapt, learn from their environments, and make decisions like biological systems and not to perform better than them. There are no efforts to eliminate deficiencies inherent in biological systems. This field, called Neuromorphic engineering, is evolving a new era in computing with a great promise for future medicine, healthcare delivery and industry. It relies on plenty of experiences which nature offers to develop functional, reliable and effective artificial systems. Neuromorphic computational circuits, designed to mimic biological neurons, are primitives based on the optical and electronic properties of semiconductor materials 2.1 BIOLOGICAL NEURONS Biological neurons have a fairly simple large-scale structure, although their operation and small-scale structure is immensely complex. Neurons have three main parts: a central cell body, called the soma, and two different types of branched, treelike structures that extend from the soma, called dendrites and axons. Information from other neurons, in the form of electrical impulses, enters the dendrites at connection points called synapses. The information flows from the dendrites to the soma, where it is processed. The output signal, a train of impulses, is then sent down the axon to the synapses of other neurons. The dendrites send impulses to the soma while the axon sends impulses away from the soma. Functionally, there are three different types of neurons: Sensory neurons They carry information from sense receptors (nerves that help us see, smell, hear taste and feel) to the central nervous system which includes the brain and the spinal cord. Motor neurons They carry information from the CNS to effectors (muscles or glands that release all kind of stuff, from water to hormones to ear wax) Interneuron They connect sensory neurons and motor neurons. It has a cell body (or soma) and root-like extensions called mygdale. Amongst the mygdale, one major outgoing trunk is the axon, and the others are dendrites. The signal processing capabilities of a neuron is its ability to vary its intrinsic electrical potential (membrane potential) through special electro-physical and chemical processes. The portion of axon immediately adjacent to the cell body is called axon hillock. This is the point at which action potentials are usually generated. The branches that leave the main axon are often called collaterals. Certain types of neurons have axons or dendrites coated with a fatty insulating substance called myelin. The coating is called the myelin sheath and the fiber is said to be myelinated. In some cases, the myelin sheath is surrounded by another insulating layer, sometimes called neurilemma. This layer, thinner than the myelin sheath and continuous over the nodes of Ranvier, is made up o thin cells called Schwann cells. Now, how do these things work? Inside and just outside of the neurons are sodium ions (Na+) and potassium ions (K+). Normally, when the neuron is just sitting not sending any messages, K+ accumulate inside the neuron while Na+ is kicked out to the area just outside the neuron. Thus, there is a lot of K+ in the neuron and a lot of Na+ just outside of it. This is called the resting potential. Keeping the K+ in and the Na+ is not easy; it requires energy from the body to work. An impulse coming in from the dendrites, reverses this balance, causing K+ to leave the neuron and Na+ to come in. This is known as depolarization. As K+ leave Na+ enter the neuron, energy is released, as the neuron no longer is doing any work to keep K+ in and Na+ out. This energycreates an electrical impulse or action potential that is transmitted from the soma to axon. As the impulse leaves the axon, the neuron repolarizes, that is it takes K+ back in and kicks Na+ out and restores itself to resting potential, ready to send another impulse. This process occurs extremely quickly. A neuron theoretically can send roughly 266 messages in one second. The electrical impulse may stimulate other neurons from its synaptic knobs to propagate the message. Experiments have shown that the membrane voltage variation during the generation of an action potential is generally in a form of a spike (a short pulse figure 2.2), and the shape of this pulse in neurons is rather stereotype and mathematically predictable. 2.2 SILICON NEURONS Neuromorphic engineers are more interested in the physiological rather than the anatomical model of a neuron though, which is concerned with the functionality rather than only classifying its parts. And their preference lies with models that can be realized in aVLSI circuits. Luckily many of the models of neurons have always been formulated as electronic circuits since many of the varying observables in biological neurons are voltages and currents. So it was relatively straight forward to implement them in VLSI electronic circuits. There exist now many aVLSI models of neurons which can be classified by their level of detail that is represented in them. A summary can be found in table 3.1. The most detailed ones are known as ‘silicon neurons. A bit cruder on the level of detail are ‘integrate and fire neurons and even more simplifying are ‘Perceptrons also known as ‘Mc Culloch Pitts neurons. The simplest way however of representing a neuron in electronics is to represent neurons as electrical nodes. Table 2.1 VLSI models of neurons 2.2.1 Electrical Nodesasneurons The most simple of all neuronal models is to just represent a neurons activity by a voltage or a current in an electrical circuit, and input and output are identical, with no transfer function in-between. If a voltage node represents a neuron, excitatory bidirectional connections can be realized simply by resistive elements between the neurons. If you want to add the possibility for inhibitory and mono directional connections, followers can be used instead of resistors. Or if a current represents neuronal activity then a simple current mirror can implement a synapse. Many useful processing networks can be implemented in this manner or in similar ways. For example a resistive network can compute local averages of current inputs. 2.2.2 Perceptrons A perceptron is a simple mathematical model of a neuron. As real neurons it is an entity that is connected to others of its kind by one output and several inputs. Simple signals pass through these connections. In the case of the perceptron these signals are not action potentials but real numbers. To draw the analogy to real neurons these numbers may represent average frequencies of action potentials. The output of a perceptron is a monotonic function (referred to as activation function) of the weighted sum of its inputs (see figure 3.3). Perceptrons are not so much implemented in analog hardware. They have originally been formulated as a mathematical rather than an electronic model and traditional computers are good at those whereas it is not so straight forward to implement simple mathematics into aVLSI. Still there exist aVLSI implementations of perceptrons since they still promise the advantage of a real fully parallel, energy and space conservative implementation. A simple aVLSI implementation of a perceptron is given in the schematics in figure 3.4. This particular implementation works well enough in theory, in practice however it is on one hand not flexible enough (particularly the activation function), on the other already difficult to tune by its bias voltages and prone to noise on the a chip. Circuits that have really been used are based on this one but were more extensive to deal with the problems. 2.2.3 Integrate Fire Neurons This model of a neuron sticks closer to the original in terms of its signals. Its output and its inputs are pulse signals. In terms of frequencies it actually can be modeled by a perceptron and vice versa. It is however much better suited to be implemented in aVLSI. And the spike communication also has distinct advantages in noise robustness. That is also thought to be a reason, why the nervous system uses that kind of communication. An integrate and fire neuron integrates weighted charge inputs triggered by presynaptic action potentials. If the integrated voltage reaches a threshold, the neuron fires a short output pulse and the integrator is reset. These basic properties are depicted in figure 2.5. 2.3 BIOLOGICAL SIGNIFICANCE OF NEUROMORPHIC SYSTEMS The fundamental philosophy of neuromorphic engineering is to utilize algorithmic inspiration of biological systems to engineer artificial systems. It is a kind of technology transfer from biology to engineering that involves the understanding of the functions and forms of the biological systems and consequent morphinginto silicon chips. The fundamental biological unit mimicked in the design of neuromorphic systems is the neurons. Animal brain is composed of these individual units of computation, called neurons and the neurons are the elementary signaling parts of the nervous systems. By examining the retina for instance, artificial neurons that mimic the retinal neurons and chemistry are fabricated on silicon (most common material), gallium arsenide (GaAs) or possibly prospective organic semiconductor materials. 2.4 NEUROMORPHIC ELECTRONICS ENGINEERING METHODS Neuromorphic systems design methods involves the mapping of models of perfection and sensory processing in biological systems onto analog VLSI systems which emulate the biological functions at the same time resembling their structural architecture. These systems are mainly designed with complementary metal oxide semiconductors (CMOS) transistors that enable low power consumption, higher chip density and integration, lower cost. These transistors are biased to operate in the sub-threshold region to enable the realizations of high dynamic range of currents which are very important for neural systems design. Elements of adaptation and learning (a sort of higher level of adaptation in which past experience is used to effectively readjust the response of a system to previously unseen input stimuli) are incorporated into neuromorphic systems since they are expected to emulate the behavior of the biological systems and compensate for imperfections in t Modelling of Meromorphic Retina Modelling of Meromorphic Retina CHAPTER 1 INTRODUCTION and literature review 1. INTRODUCTION The world depends on how we sense it; perceive it and how we act is according to our perception of this world. But where from this perception comes? Leaving the psychological part, we perceive by what we sense and act by what we perceive. The senses in humans and other animals are the faculties by which outside information is received for evaluation and response. Thus the actions of humans depend on what they sense. Aristotle divided the senses into five, namely: Hearing, Sight, Smell, Taste and Touch. These have continued to be regarded as the classical five senses, although scientists have determined the existence of as many as 15 additional senses. Sense organs buried deep in the tissues of muscles, tendons, and joints, for example, give rise to sensations of weight, position of the body, and amount of bending of the various joints; these organs are called proprioceptors. Within the semicircular canal of the ear is the organ of equilibrium, concerned with the sense of balance. General senses, which produce information concerning bodily needs (hunger, thirst, fatigue, and pain), are also recognized. But the foundation of all these is still the list of five that was given by Aristotle. Our world is a visual world. Visual perception is by far the most important sensory process by which we gather and extract information from our environment. Vision is the ability to see the features of objects we look at, such as color, shape, size, details, depth, and contrast. Vision is achieved when the eyes and brain work together to form pictures of the world around us. Vision begins with light rays bouncing off the surface of objects. Light reflected from objects in our world forms a very rich source of information and data. The light reflected has a short wavelength and high transmission speed that allow us a spatially accurate and fast localization of reflecting surfaces. The spectral variations in wavelength and intensity in the reflected light resemble the physical properties of object surfaces, and provide means to recognize them. The sources that light our world are usually inhomogeneous. The sun, our natural light source, for example, is in good approximation a point sou rce. Inhomogeneous light sources cause shadows and reflections that are highly correlated with the shape of objects. Thus, knowledge of the spatial position and extent of the light source enables further extraction of information about our environment. Our world is also a world of motion. We and most other animals are moving creatures. We navigate successfully through a dynamic environment, and we use predominantly visual information to do so. A sense of motion is crucial for the perception of our own motion in relation to other moving and static objects in the environment. We must predict accurately the relative dynamics of objects in the environment in order to plan appropriate actions. Take for example the following situation that illustrates the nature of such a perceptual task: the batsman a cricket team is facing a bowler. In order to get the boundary on the ball, he needs an accurate estimate of the real motion trajectory of the ball such that he can precisely plan and orchestrate his body movements to hit the ball. There is little more than just visual information available to him in order to solve the task. And once he is in motion the situation becomes much more complicated because visual motion information now represents the relative motion between him and the ball while the important coordinate frame remains static. Yet, despite its difficulty, with appropriate training some of us become astonishingly good at performing this task. High performance is important because we live in a highly competitive world. The survival of the fittest applies to us as to any other living organism, although the fields of competition might have slightly shifted and diverted during recent evolutionary trends. This competitive pressure not only promotes a visual motion perception system that can determine quickly what is moving where, in which direction, and at what speed; but it also forces this system to be efficient. Efficiency is crucial in biological systems. It encourages solutions that consume the smallest amount of resources of time, substrate, and energy. The requirement for efficiency is advantageous because it drives the system to be quicker, to go further, to last longer, and to have more resources left to solve and perform other tasks at the same time. Thus, being the complex sensory-motor system as the batsman is, he cannot dedicate all of the resources available to solve a single task. Compared to human perceptual abilities, nature provides us with even more astonishing examples of efficient visual motion perception. Consider the various flying insects that navigate by visual perception. They weigh only fractions of grams, yet they are able to navigate successfully at high speeds through complicated environments in which they must resolve visual motions up to 2000 deg/s. 1.1 ARTIFICIAL SYSTEMS What applies to biological systems applies also to a large extent to any artificial autonomous system that behaves freely in a real-world environment. When humankind started to build artificial autonomous systems, it was commonly accepted that such systems would become part of our everyday life by the year 2001. Numberless science-fiction stories and movies have encouraged visions of how such agents should behave and interfere with human society. And many of these scenarios seem realistic and desirable. Briefly, we have a rather good sense of what these agents should be capable of. But the construction is still eluding. The semi- autonomous rover of NASAs recent Mars missions or demonstrations of artificial pets are the few examples. Remarkably the progress in this field is slow than the other fields of electronics. Unlike transistor technology in which explosion of density is defined by the Moores law and also in terms of the computational powers the performance of autonomous systems is still not to the par. To find out the reason behind it we have to understand the limitation of traditional approaches. The autonomous system is the one that perceives, takes decision and plans action at a cognitive level, in doing so it must show some degree of intelligence. Returning back to the batsman example, he knows exactly what he has to do to dispatch the ball to the boundary, he has to get into a right position and then hit the ball with a precise timing. In this process, the photons hit the retina and then muscle force is applied. The batsman is not aware that this much is going on into his body. The batsman has a nervous system, and one of its many functions is to instantiate a transformation layerbetween the environme nt and his cognitive mind. The brain reduces and preprocesses the huge amount of noisy sensory data, categorizes and extracts the relevant information, and translates it into a form that is accessible to cognitive reasoning. Thus it is clear here that the there is cluster of process that takes place in a biological cognitive system in a very short time duration. And also that an important part of this whole process is transduction although it is not the one that can solely perform the whole complex task. Thus perception is the interpretationof sensory information with respect to the perceptual goal. The process is shown in the fig-1. 1.2 DIFFERENCE BETWEEN BIOLOGICAL SYSTEMS AND COMPUTERS The brain is fundamentally differently organized than a computer and science is still a long way from understanding how the whole thing works. A computer is really easy to understand by comparison. Features (or organization principles) that clearly distinguish a brain from a computer are: Massive parallelism, Distributed storage, Asynchronous processing, and Self organization. The computer is still a basically serially driven machine with a centralized storage and minimal self organization. The table 1.1 enlists these differences. Table 1.1 Differences in the organization principles and operation of computer and brain The digital computation may become so fast that it may solve the present problems and also it may become possible that the autonomous systems are made by digital components that are as powerful as efficient and as intelligent as we may imagine in our wildest dreams. However there are doubts in it and so we have to switch to an implementation framework that can realize all these things. 1.3 NEURAL COMPUTATIONS WITH THE HELP OF ANALOG INTEGRATED CIRCUITS It was Carver Mead who, inspired by the course â€Å"The Physics of Computation† he jointly taught with John Hopfield and Richard Feynman at Caltech in 1982, first proposed the idea of embodying neural computation in silicon analog very large-scale integrated (aVLSI) circuits. Biological neural networks are examples of wonderfully engineered and efficient computational systems. When researchers first began to develop mathematical models for how nervous systems actually compute and process information, they very soon realized that one of the main reasons for the impressive computational power and efficiency of neural networks is the collective computation that takes place among their highly connected neurons. And in researches, it is also well established that these computations are not undertaken digitally although the digital way is much simpler. Real neurons have a cell membrane with a capacitance that acts as a low-pass filter to the incoming signal through its dendrites; they have dendritic trees that non-linearly add signals from other neurons, and so forth. Network structure and analog processing seem to be two key properties of nervous systems providing them with efficiency and computational power, but nonetheless two properties that digital compute rs typically do not share or exploit. 1.4 LITERATURE REVIEW 1. Biological information-processing systems operate on completely different principles from those with which most engineers are familiar. For many problems, particularly those in which the input data are ill-conditioned and the computation can be specified in a relative manner, biological solutions are many orders of magnitude more effective than those we have been able to implement using digital methods. This advantage can be attributed principally to the use of elementary physical phenomena as computational primitives, and to the representation of information by the relative values of analog signals, rather than by the absolute values of digital signals. This approach requires adaptive techniques to mitigate the effects of component differences. This kind of adaptation leads naturally to systems that learn about their environment. Large-scale adaptive analog systems are more robust to component degradation and failure than are more conventional systems, and they use far less power . For this reason, adaptive analog technology can be expected to utilize the full potential of wafer scale silicon fabrication 2. The architecture and realization of microelectronic components for a retina-implant system that will provide visual sensations to patients suffering from photoreceptor degeneration. Special circuitry has been developed for a fast single-chip CMOS image sensor system, which provides high dynamic range of more than seven decades (without any electronic or mechanical shutter) corresponding to the performance of the human eye. This image sensor system is directly coupled to a digital filter and a signal processor that compute the so-called receptive-field function for generation of the stimulation data. These external components are wireless, linked to an implanted flexible silicon multielectrode stimulator, which generates electrical signals for electro stimulation of the intact ganglion cells. All components, including additional hardware for digital signal processing and wireless data and power transmission, have been fabricated using in-house standard CMOS technology 3. The circuits inspired by the nervous system that either help verifying neuron physiological models, or that are useful components in artificial perception/action systems. Research also aims at using them in implants. These circuits are computational devices and intelligent sensors that are very differently organized than digital processors. Their storage and processing capacity is distributed. They are asynchronous and use no clock signal. They are often purely analog and operate time continuous. They are adaptive or can even learn on a basic level instead of being programmed. A short introduction into the area of brain research is also included in the course. The students will learn to exploit mechanisms employed by the nervous system for compact energy efficient analog integrated circuits. They will get insight into a multidisciplinary research area. The students will learn to analyze analog CMOS circuits and acquire basic knowledge in brain research methods. 4. Smart vision systems will be an inevitable component of future intelligent systems. Conventional vision systems, based on the system level integration (or even chip level integration) of an image (usually a CCD) camera and a digital processor, do not have the potential for application in general purpose consumer electronic products. This is simply due to the cost, size, and complexity of these systems. Because of these factors conventional vision systems have mainly been limited to specific industrial and military applications. Vision chips, which include both the photo sensors and parallel processing elements (analog or digital), have been under research for more than a decade and illustrate promising capabilities. 5. Dr. Carver Mead, professor emeritus of California Institute of Technology (Caltech), Pasadena pioneered this field. He reasoned that biological evolutionary trends over millions of years have produced organisms that engineers can study to develop better artificial systems. By giving senses and sensory-based behavior to machines, these systems can possibly compete with human senses and brings an intersection between biology, computer science and electrical engineering. Analog circuits, electrical circuits operated with continuous varying signals, are used to implement these algorithmic processes with transistors operated in the sub-threshold or weak inversion region (a region of operation in which transistors are designed to conduct current though the gate voltage is slightly lower than the minimum voltage, called threshold voltage, required for normal conduction to take place) where they exhibit exponential current voltage characteristics and low currents. This circuit paradigm pr oduces high density and low power implementations of some functions that are computationally intensive when compared with other paradigms (triode and saturation operational regions). {A triode region is operating transistor with gate voltage above the threshold voltage but with the drain-source voltage lower than the difference between the gate-source voltage and threshold voltage. For saturation region, the gate voltage is still above the threshold voltage but with the drain-source voltage above the difference between the gate-source voltage and threshold voltage. Transistor has four terminals: drain, gate, source and bulk. Current flows between the drain and the source when enough voltage is applied through the gate that enables conduction. The bulk is the body of the transistor.}. As the systems mature, human parts replacements would become a major application area of the Neuromorphic electronics. The fundamental principle is by observing how biological systems perform these func tions robust artificial systems are designed. 6. In This proposed work a circuit level model of Neuromorphic Retina, this is a crude electronic model of biologically inspired smart visual sensors. These visual sensors have integrated image acquisition and parallel processing. Having these features neuromorphic retina mimics the neural circuitry of bionic eye. The proposed electronic model contains adaptive photoreceptors as light sensors and other circuit components such as averaging circuits, circuits representing ganglion cells, neuronal firing circuits etc that junction to sense brightness, size, orientation and shape to distinguish objects in closer proximity. Although image-processing features are available with modern robots but most of the issues related to image processing are taken care by software resources. Whereas machine vision with the help of neuromorphic retina is empowered with image processing at the front end. With added hardware resources, processing at the front end can reduce a lot of engineering resources for making electronic devices with sense of vision. 1.5 OBJECTIVES OF THE PRESENT WORK This project work describes a circuit level model of Neuromorphic Retina, which is a crude electronic model of biologically inspired smart visual sensors. These visual sensors have integrated image acquisition and parallel processing. Having these features neuromorphic retina mimics the neural circuitry of bionic eye. The proposed electronic model contains adaptive photoreceptors as light sensors and other neural firing circuits etc at junction to sense brightness, size, orientation and shape to distinguish objects in closer proximity. Although, image processing features are available with modern robots but most of the issues related to image processing are taken care by software resources. Whereas, machine vision with the help of neuromorphic retina is empowered with image processing at the front end. In this paper it has been shown that with added hardware resources, processing at the front end it can reduce a lot of engineering resources as well as time for making electronic devic es with sense of vision. . The objectives of present work are: Modelling of Neuromorphic Retina The photoreceptor block The horrizontal cell block The transistor mesh implemented with cmos technology The integerated block The integrated block of prs, horizontal cells and bipolar cells The spike generation circuit 1.6 Concluding Remarks In this chapter, the function of the artificial system, difference between brain and computer work is described. The present work is focused on designing of neuromorphic retina layer circuits. Many successful studies have been carried out by the researchers to study the behavior and failure of neuromorphic retina. Some investigators have performed the experimental work to study the phenomenon of the neuromorphic retina. Chapter 2 conations the biological neurons and the electronics of neuromorphic retina in this the descriptions of silicon neurons, electrical nodes as neurons, perceptrons, integrate fire neurons, biological significance of neuromorphic systems, neuromorphic electronics engineering methods, process of developing a neuromorphic chip. Chapter 3 describes the artificial silicon retina, physiology of vision, the retina, photon to electrons, why we require the neuromorphic retina?, the equivalent electronic structure, visual path to brain. In chapter 4 designing and implementation of neuromorphic retina in this the description of the photoreceptor block, the horrizontal cell block, the integerated block, the integrated block of photoreceptors, horizontal cells and bipolar cells, the spike generation circuit. In chapter 5 the design analyses and test results of neuromorphic retina layers. The results are summarized in the form of conclusion in Chapter 6 CHAPTER-2 BIOLOGICAL neurons AND neuromorphic electronics 2.1 INTRODUCTION Neuromorphic systems are inspired by the structure, function and plasticity of biological nervous systems. They are artificial neural systems that mimic algorithmic behavior of the biological animal systems through efficient adaptive and intelligent control techniques. They are designed to adapt, learn from their environments, and make decisions like biological systems and not to perform better than them. There are no efforts to eliminate deficiencies inherent in biological systems. This field, called Neuromorphic engineering, is evolving a new era in computing with a great promise for future medicine, healthcare delivery and industry. It relies on plenty of experiences which nature offers to develop functional, reliable and effective artificial systems. Neuromorphic computational circuits, designed to mimic biological neurons, are primitives based on the optical and electronic properties of semiconductor materials 2.1 BIOLOGICAL NEURONS Biological neurons have a fairly simple large-scale structure, although their operation and small-scale structure is immensely complex. Neurons have three main parts: a central cell body, called the soma, and two different types of branched, treelike structures that extend from the soma, called dendrites and axons. Information from other neurons, in the form of electrical impulses, enters the dendrites at connection points called synapses. The information flows from the dendrites to the soma, where it is processed. The output signal, a train of impulses, is then sent down the axon to the synapses of other neurons. The dendrites send impulses to the soma while the axon sends impulses away from the soma. Functionally, there are three different types of neurons: Sensory neurons They carry information from sense receptors (nerves that help us see, smell, hear taste and feel) to the central nervous system which includes the brain and the spinal cord. Motor neurons They carry information from the CNS to effectors (muscles or glands that release all kind of stuff, from water to hormones to ear wax) Interneuron They connect sensory neurons and motor neurons. It has a cell body (or soma) and root-like extensions called mygdale. Amongst the mygdale, one major outgoing trunk is the axon, and the others are dendrites. The signal processing capabilities of a neuron is its ability to vary its intrinsic electrical potential (membrane potential) through special electro-physical and chemical processes. The portion of axon immediately adjacent to the cell body is called axon hillock. This is the point at which action potentials are usually generated. The branches that leave the main axon are often called collaterals. Certain types of neurons have axons or dendrites coated with a fatty insulating substance called myelin. The coating is called the myelin sheath and the fiber is said to be myelinated. In some cases, the myelin sheath is surrounded by another insulating layer, sometimes called neurilemma. This layer, thinner than the myelin sheath and continuous over the nodes of Ranvier, is made up o thin cells called Schwann cells. Now, how do these things work? Inside and just outside of the neurons are sodium ions (Na+) and potassium ions (K+). Normally, when the neuron is just sitting not sending any messages, K+ accumulate inside the neuron while Na+ is kicked out to the area just outside the neuron. Thus, there is a lot of K+ in the neuron and a lot of Na+ just outside of it. This is called the resting potential. Keeping the K+ in and the Na+ is not easy; it requires energy from the body to work. An impulse coming in from the dendrites, reverses this balance, causing K+ to leave the neuron and Na+ to come in. This is known as depolarization. As K+ leave Na+ enter the neuron, energy is released, as the neuron no longer is doing any work to keep K+ in and Na+ out. This energycreates an electrical impulse or action potential that is transmitted from the soma to axon. As the impulse leaves the axon, the neuron repolarizes, that is it takes K+ back in and kicks Na+ out and restores itself to resting potential, ready to send another impulse. This process occurs extremely quickly. A neuron theoretically can send roughly 266 messages in one second. The electrical impulse may stimulate other neurons from its synaptic knobs to propagate the message. Experiments have shown that the membrane voltage variation during the generation of an action potential is generally in a form of a spike (a short pulse figure 2.2), and the shape of this pulse in neurons is rather stereotype and mathematically predictable. 2.2 SILICON NEURONS Neuromorphic engineers are more interested in the physiological rather than the anatomical model of a neuron though, which is concerned with the functionality rather than only classifying its parts. And their preference lies with models that can be realized in aVLSI circuits. Luckily many of the models of neurons have always been formulated as electronic circuits since many of the varying observables in biological neurons are voltages and currents. So it was relatively straight forward to implement them in VLSI electronic circuits. There exist now many aVLSI models of neurons which can be classified by their level of detail that is represented in them. A summary can be found in table 3.1. The most detailed ones are known as ‘silicon neurons. A bit cruder on the level of detail are ‘integrate and fire neurons and even more simplifying are ‘Perceptrons also known as ‘Mc Culloch Pitts neurons. The simplest way however of representing a neuron in electronics is to represent neurons as electrical nodes. Table 2.1 VLSI models of neurons 2.2.1 Electrical Nodesasneurons The most simple of all neuronal models is to just represent a neurons activity by a voltage or a current in an electrical circuit, and input and output are identical, with no transfer function in-between. If a voltage node represents a neuron, excitatory bidirectional connections can be realized simply by resistive elements between the neurons. If you want to add the possibility for inhibitory and mono directional connections, followers can be used instead of resistors. Or if a current represents neuronal activity then a simple current mirror can implement a synapse. Many useful processing networks can be implemented in this manner or in similar ways. For example a resistive network can compute local averages of current inputs. 2.2.2 Perceptrons A perceptron is a simple mathematical model of a neuron. As real neurons it is an entity that is connected to others of its kind by one output and several inputs. Simple signals pass through these connections. In the case of the perceptron these signals are not action potentials but real numbers. To draw the analogy to real neurons these numbers may represent average frequencies of action potentials. The output of a perceptron is a monotonic function (referred to as activation function) of the weighted sum of its inputs (see figure 3.3). Perceptrons are not so much implemented in analog hardware. They have originally been formulated as a mathematical rather than an electronic model and traditional computers are good at those whereas it is not so straight forward to implement simple mathematics into aVLSI. Still there exist aVLSI implementations of perceptrons since they still promise the advantage of a real fully parallel, energy and space conservative implementation. A simple aVLSI implementation of a perceptron is given in the schematics in figure 3.4. This particular implementation works well enough in theory, in practice however it is on one hand not flexible enough (particularly the activation function), on the other already difficult to tune by its bias voltages and prone to noise on the a chip. Circuits that have really been used are based on this one but were more extensive to deal with the problems. 2.2.3 Integrate Fire Neurons This model of a neuron sticks closer to the original in terms of its signals. Its output and its inputs are pulse signals. In terms of frequencies it actually can be modeled by a perceptron and vice versa. It is however much better suited to be implemented in aVLSI. And the spike communication also has distinct advantages in noise robustness. That is also thought to be a reason, why the nervous system uses that kind of communication. An integrate and fire neuron integrates weighted charge inputs triggered by presynaptic action potentials. If the integrated voltage reaches a threshold, the neuron fires a short output pulse and the integrator is reset. These basic properties are depicted in figure 2.5. 2.3 BIOLOGICAL SIGNIFICANCE OF NEUROMORPHIC SYSTEMS The fundamental philosophy of neuromorphic engineering is to utilize algorithmic inspiration of biological systems to engineer artificial systems. It is a kind of technology transfer from biology to engineering that involves the understanding of the functions and forms of the biological systems and consequent morphinginto silicon chips. The fundamental biological unit mimicked in the design of neuromorphic systems is the neurons. Animal brain is composed of these individual units of computation, called neurons and the neurons are the elementary signaling parts of the nervous systems. By examining the retina for instance, artificial neurons that mimic the retinal neurons and chemistry are fabricated on silicon (most common material), gallium arsenide (GaAs) or possibly prospective organic semiconductor materials. 2.4 NEUROMORPHIC ELECTRONICS ENGINEERING METHODS Neuromorphic systems design methods involves the mapping of models of perfection and sensory processing in biological systems onto analog VLSI systems which emulate the biological functions at the same time resembling their structural architecture. These systems are mainly designed with complementary metal oxide semiconductors (CMOS) transistors that enable low power consumption, higher chip density and integration, lower cost. These transistors are biased to operate in the sub-threshold region to enable the realizations of high dynamic range of currents which are very important for neural systems design. Elements of adaptation and learning (a sort of higher level of adaptation in which past experience is used to effectively readjust the response of a system to previously unseen input stimuli) are incorporated into neuromorphic systems since they are expected to emulate the behavior of the biological systems and compensate for imperfections in t