Our Babies, Ourselves Essay

Dependence during infancy is unique amongst hominids compared to other beings. However, different cultures in the world differ on how they cater to this dependency. For example, the American culture is influenced by individualism, therefore they tend to rear their children in such a way that they will grow up as an independent individual. On the other hand, Japanese are likely to be more affectionate in their child upbringing culture. And on both instances, infants who were reared up the American or Japanese way, their anticipated adult traits remain to be visible. As the article â€Å"Our Babies, Ourselves† suggests, the care given to an infant during his most dependent stage is reflected when the infant grows up and he develops his own sense of independence and survival skills. The rearing up process, whether an individual is being given over adequate attention or being least assisted during infancy is reflected by his developed reflexes and skills in his grown up stage. For the Gusii child-rearing practices, infants were held closer to their parents compared to other cultures. Here, infants develop a closer bond to their mothers, and later on towards other children to develop their interpersonal skills better. Moreover, apart from the physical and emotional aspects of development, neurological and genetic developments of infants are also being attributed to their rearing up practices. Thus, the uniqueness developed by an individual regarding his skills, competencies and survival instincts is defined by infant care that was rendered to him by his parents. However, the rearing up process is highly shaped and influenced by traditions within a culture, thus creating cross-cultural differences when it comes to child development across different nations and races.

Miranda Priestly OB

Locus of control: It can be observed throughout the movie how Miranda tried to control ever thing around her. Every decision taken by her was considered to be final. There is a dialogue â€Å"Her opinion is the only opinion that matters†, it show how she controlled everything around her. Self Esteem: (Tendency to rate one very high) Miranda rated herself above everyone. She likes to believe that, if it's for her then anything is possible. She never allows anyone to ever ride lift with her. A person leaves lift as soon as Miranda enters lift for her and waits for the other en to arrive.Lack of emotional Intelligence: Miranda lacks emotional intelligence. During many of the incidences she tends to ignore the emotions of the people around her. For instance when her assistant fails to book flight for her, she makes her feel very bad even though it was not her mistake. In one of the incidences even though she knew her first assistant was looking forward for the trip to Paris, and h as been dieting and planning for over months, even though she neglects her and takes a new assistant with her. She never cared to learn the name of her employee and called by any name she felt .Job Fit: She is the most job fit for her job. She has knowledge of her domain and she makes sure job is done at all cost. A famous designer displays his designs before Paris show to Miranda. He thinks it was his best work but Miranda directly rejects the collection and the designer changes his collection to receive applaud during the main show. Pygmalion Effect: The process of bringing the best out of others. Miranda always expected the best out of each and every of her employee. When a new assistant joins, Miranda pushes her to extreme always expecting the result out of her.She sometimes gave impossible task to her employee like booking flight during storm or procuring an unpublished Harry potter book. Due to her constant supervision she always brings out the best in people. Andrea â€Å"An dy' Cash land an interview with an fashion industry magazine which is names as a job â€Å"a million girls would kill for†. The job is as junior personal assistant for editor of Runway fashion magazine. Andrea is a fresh out of college and is looking for a job to jump start her career, even though he dislikes fashion industry, she accepts the job.

An overview of Civil disobedience

An overview of Civil disobedience At the beginning of â€Å"Civil Disobedience,† Thoreau expresses agreement with the idea â€Å"that government is best which governs least†. When carried to its logical conclusion, this concept leads to the realization â€Å"that government is best which governs not at all†. Thoreau believes government is the mode people have chosen to affect their will and is apt to be exploited before the people can act through it. Whatever the government assumes or promises, Thoreau argues, it does not keep a country free and it does not educate. He claims that all good that has been accomplished in America has been done not by the government, but by the people. He also argues that further accomplishments may have been reached if the government had not interfered. Thoreau states that as a reasonable citizen, he does not ask for no government at all, but an improved government. The first step in improving a government is for the people to identify what kind of government would earn their respect and loyalty. The problem is that not every individual has a say in how the government should perform, and many do not have the respect or even acknowledgement from the government. The majority can rule simply because it is more physically powerful, and the minority has essentially no say in shaping law. To Thoreau, a government based on majority rule is not based on justice. He asks, â€Å"Should an individual citizen have to resign his conscience to the legislator?† If this is so, why would a person even have a conscience? Thoreau states that we should be men first and subjects later. It is not desirable to develop a high opinion of the law, so much as for justice and right. For an individual to do what he thinks is right is the only duty which one has the right to assume. Thoreau makes a good argument; a group on its own has no conscience. However, a group of conscientious people is a conscientious group. Thoreau claims that when the people have respect for an undeserving government, the only natural result is that the people will be following the law against their wills, against their common sense, and against their conscience. So, Thoreau asks, are these people men at all? He states, â€Å"A wise man will only be useful as a man, and will not submit to be clay†. Thoreau states that most men do recognize the right of revolution when a government’s tyranny or inefficiency are sufficiently great and unendurable. When most of a country is unjustly overrun, then this is the time for honest individuals to rebel and revolt. Thoreau refers to voting as â€Å"a game†. He states that a person votes as he thinks is right, but that he is not necessarily bothered by whether or not his belief – his vote – is successful. The people, he believes, seem to be willing to leave this to the majority. Thoreau argues that a real wise man would not take the risk of what is right not prevailing and would also realize that there is not much virtue in the action of the mass. But as far as real men go, Thoreau believes that they are few and rare. He makes this clear in this essay; â€Å"How many men are there to a square thousand miles in the country? Hardly one.† Thoreau believes that there are few real people, it seems, because we are hypocritical, inconsistent, and weak in our beliefs. He claims that many disapprove of the nature of the government but continue to support it. Such people, he argues, should be resisting the government. An individual cannot genuinely be content when he knows he is consciously being cheated or deceived. Thoreau believes that instead of obeying rules one knows to be unjust, the individual should attempt to alter those laws. He suggests that the power of governmental control is what causes people to perceive resistance as worse than obedience. The government and the mass do not seem to be aware of or appreciate the wise minority who would push for reform, and those who choose to resist are punished and humiliated. Most people would rather wait until the majority agrees that laws should be revised via traditional process than to resist. Thoreau argues that if a government expects an individual to follow and carry out injustice, then that government is not one that should be followed. He makes a very good claim by saying that when one is under a government which unjustly imprisons people, then prison would be the appropriate place for a true, just individual. Thoreau evidently believes that an individual should not follow laws which he or she believes to be unjust. He states, â€Å"Know all men by these presents, that I, Henry Thoreau, do not wish to be regarded as a member of any society which I have not joined.† He declares that a real man would find it less confining to be locked up in a prison cell knowing that he was doing what is right, rather than living â€Å"free† in a society while obeying laws he believes to be wrong. Thoreau tries to make it clear at the end of the essay that he does not hate the idea of government, but that it is in dire need of major improvement, and that it should only be followed if it is just and if it has the consent of those who it governs. He states that the state will never be progressive and free until it recognizes the individuals, rather than the mass, and respects them accordingly.

Communication Essay Example | Topics and Well Written Essays - 1000 words - 2

Communication - Essay Example The first organization that was observed was Wal-Mart. This research recognizes that most individuals are at least cursorily familiar with Wal-Mart, however insights can be gained from in-depth observational investigation. One of the most overarching considerations is Wal-Mart’s organizational model. In these regards, the organization is the country’s largest retailer, selling both household items as well as groceries. There are large numbers of employees working at Wal-Mart. There is a management level of employees, another group of employees who work the cash registers, other groups of employees who work in specific department – for instance electronics or the seafood departments -- finally other groups of employees work stocking the shelves. The specific observation of these employees revealed a number of elements. While the employees are easy to locate oftentimes they operate in a very business environment and as such their roles are less defined as customer service, than in the service of their specific tasks. I observed one interaction where a customer asked an employee where measuring tape was. Rather than bring the customer to the location the employee vaguely pointed at an area and said they believe it was in that direction. While one could attribute such a communication approach to the specific employee, this behavior was also witnessed in the electronics department. In this situation a customer asked about what the specific figures on one of the computer advertisements meant. The employee responded that they weren’t sure about the specific elements on that computer. It seems that to a great degree these employees’ verbal communication skills were a necessary byproduct of the organizational culture that had been established at Wal-Mart. Namely, the commitment to low-cost goods has necessitated that customer service be sacrificed. As I was checking out of the store I waited in line for five minutes. Suddenly the cashi er looked to the others in the line and informed them that this line was closed. While she could have informed the customers waiting earlier, he non-verbal communication carried on as normal. The situation demonstrated that the employee had a lack of pride in her job. Ultimately, it seems that such actions may also be a product of necessary sacrifice for low prices. The next retailer that was observed was Best Buy. Best Buy is a large-scale electronics retailer specializing in virtually all major electronics and games. Upon entering the store I immediately recognized a number of disparate elements between this organizational model and that of Wal-Mart. While both retailers are large-scale chains Best Buy’s focuses on electronics, as well as their subsequent approach to customer service. While Wal-Mart’s employee communication styles are very detached, Best Buy’s approach is almost overly helpful. Employees were both verbally and non-verbally approachable through body language. In walking around the store I was approached numerous times by employees asking if I needed help or had any questions. While it seems to a degree this was motivated out of the need to help customers with the complexity of the electronics it is seems a comprehensively different approach to the organizational model. The specific breakdown of employees was the same as Wal-Mart’s with individuals stocking shelves, cashiers, and managers; however,

Report on Religious Field Research Term Paper Example | Topics and Well Written Essays - 1500 words

Report on Religious Field Research - Term Paper Example (Jungman, 2012) During the first 280 years in Christian history, Christianity was ruled out in the Roman Empire and Christians were heavily persecuted. This arbitrary changed after the â€Å"conversion† of the Roman Emperor Constantine. He allowed Christians to worship and made Christianity legal with the Milan’s Edicit in A.D 313. In A.D 325, Constantine summoned the council of Nicaea in an attempt popularize Christianity. Constantine postulated that Christianity would unite the Roman Empire which at that time was fragmenting gradually. This generated positive results towards the development of Christianity at the time. (Jungman, 2012) However Constantine did not fully accept Christianity, instead he mixed some Roman pagan beliefs which are still intact up to date. The impetuous behind Constantine’s action of blending Christianity and Roman paganism was that Christian was a foreign religion and Romans could not have just left their religion and embrace a foreign one fully. Some of the Christianized beliefs include: (i) Cult of Isis was a mother –goddess from Egyptian religion. It was absorbed and harmonized with Christianity and it was replaced by the Virgin Mary. Many titles that were meant for Isis were attached to Mary, i.e., â€Å"Queen of Heaven†, â€Å"Mother of God†, theotokas (â€Å"God –bearer†) among other adoration names. Mary was given supreme positions as the roles far much ahead than the bible ascribes to her. This was done in order to attract the Isis worshippers to Christianity. Failure to do this, any efforts would lead to frustration. (George, 2009) (ii) Mithraism was a renowned religion in the Roman Empire which was practiced in the 5th century A.D .It was popular among the Roman soldiers sand also the Roman Emperors. Mithraism lacked the â€Å"official â€Å"status in the Roman Empire, it was accepted as the de facto official religion not until the Roman Emperors replaced Mithraism w ith Christianity. The key aspects of Mithraism was sacrificial meal (theophagy, eating ones god), sacraments among other conspicuous features. Constantine and the successors found it easy to substitute Mithraism with the Lords supper /Holy Communion which unfortunately prompted some early Christians to attach mysticism to the lords supper, rejecting the biblical idea of remembrance worship and meditation of Christ’s sacrificial death and the blood He shed. (Charles, 1982) (iii) Henoticism is a distinguishing feature of roman pagan religion. It involves believing in the existence of many gods but focuses primarily on one particular god which is considered to be the most superior god. For instance, Jupiter was the supreme Roman god. The Roman sailors normally worshipped Neptune, which was the god of the oceans. Christianization of Roman paganism involved the replacing of Roman gods with saints just as the Roman chain of gods had a god of love, god of peace, god of war, god of s trength among other gods which were claimed to exist(Charles, 1982.) The â€Å"Papacy† that exists in the hierarchy of Catholic Church is a continuation of what was created by the Roman Emperors,

Economics for Business and Management Essay Example | Topics and Well Written Essays - 2750 words - 2

Economics for Business and Management - Essay Example Market is a distributed system and can be effectively used in taking decisions. These people think so because they believe that the market based system can really attend to the features of new world system. The following issues are addressed by market system: The market system is responsible for supporting a dense set of social goals. Social goals of people also include taking resource allocation decisions by people. The participants take their investment decisions by quantifying the benefits perceived on each of the investment options. It is the market that provides its participants initiatives to take the decisions wisely. Thus market system is such that it helps the investors maximise the overall value and take efficient investment decision. The prevalence of a currency in the market helps the participants express value for the decision variables. The currency is used as a medium of exchange between the economies of the world. For example if the currency is open, it is generally assumed as a mean to acquire huge amount of goods and services. In such situation, it can be used as an incentive for resource providers to increase their services and vice versa. Thus currency can be used as a medium that allows market to admire those who provide valuable resources to the market. Market system is a platform that provides the investors the set where they can express their desires and holdings. Markets are broadly used to take complex resource allocation decisions. The examples of difficult decision situations can be the wireless spectrum auctions, energy market and airline landing slot exchanges. These are the situations of extreme intricacies where market system has worked effectively in resolving problems. The market system provides scope for those systems that run in parallel and help offer various access to unique resources such as many scientific tools. For example, a situation can be imagined where a physics researcher

Black Segregation Essay Example | Topics and Well Written Essays - 1250 words

Black Segregation - Essay Example In the year 1954 the Court of United States pronounced its verdict as concerns the landmark case of Brown v. Board where it provided that the racial segregation of children based on the rule of â€Å"separate but equal† as directed by the provision of the 1896 Plessy v. Ferguson that was later overturned was considered as an infringement of the Equal Protection Clause of the Fourteenth Amendment. The Supreme Court hence declared the separate educational facilities as essentially unequal and unconstitutional. The ruling on Brown v. Board of Education case helped to combat the activities of the state in funding and facilitating aspects of segregation that had been corroding the ethical codes of the society. It also served to give the civil movement groups a voice and motivation to fight for the rights and privileges of the discriminated groups (Renzulli, 2006). In history, the root cause for the segregation of blacks and whites in America dates back to the mid 19th century. It primarily began with the passage of Jim Crow laws after the Reconstruction Era ended. These laws were largely common among the southern states but later spread to regions of the Southwest. The separation was primarily ascribed to various aspects of public life as well as in learning institutions and other public facilities and resources. Jim Crow laws hence prohibited blacks from sharing schools, churches, restaurants and other public amenities with their white counterparts. The Supreme Court of America in the ruling on Plessy v consequently upheld this law.

Reflective Leadership Essay Example | Topics and Well Written Essays - 5500 words

Reflective Leadership - Essay Example dents enabling them to understand the ways in which particular theories can be applied and put into practice as well as to identify the practices which are in complete alignment with theories and concepts (The higher education academy, 2009). The reflective learning process has been of great help to me over the 10 week sessions. The reflective log helped me to identify my own self in the best possible way. I was able to have a better understanding of the strengths and weaknesses that I possessed. The self reflections allowed me to realize as well as question my underlying beliefs and values. In addition, the learning process enabled me to acknowledge and argue probable assumptions as well as theories over which my feelings, ideas and actions were based. Most importantly, I was able to recognize the key areas of improvement that needs to be brought about in me. The sessions that I attended made me concur to the ideas on leadership set forth by empirical researchers. Leadership according to me is a key determinant of the success of any entity be it a business organization or a sports team. Being a project lead of the company that I currently work for has made me understand about various aspects and dimensions of leadership. Although my experience was relatively lesser than my cohorts who were present along with me in the session but my lob position was unbelievably unique among all the job mentioned job positions mentioned by various holders who attended the session. This enabled me to provide as well as gain a different perspective of leadership.

Kraiger and Holton and Kirkpatricks models' investigation Essay

Kraiger and Holton and Kirkpatricks models' investigation - Essay Example Kirkpatrick's four stages of criterion, including the responses, knowledge, behavior, as well as results, all have been utilized to steer the training assessments in addition to the measurement of training performance for more than 40 years. The recent belief within the training assessment literature expands Kirkpatrick's agenda. The measurement of knowledge criterion characteristically explained with reference to an alteration within declarative information or else expertise has developed beyond the theory within stage two of Kirkpatrick's model. Kraiger along with his colleagues extrapolated the fact that knowledge within training can be categorized into three groups of criterion, cognitive, expertise based moreover sentimental learning. The multidimensional model of training routine is the one, within which disparate the modeling demeanoured with the job performance criterion. This condition is altering as additional researchers take up the Kraiger model within their training investigation. When presenting the training criterion, a lot of diverse provisions appear to be used in exchange of each other: such as the training assessment, training efficiency, substantiation, or appraisal. Time and again, these provisions have extremely dissimilar meanings. In terms of Kraiger and Colleagues, this kind of assessment is carried out to resolve whether the training objectives were accomplished and whether achievement of those objectives ended in improved performance on the post, and training efficiency seeks to learn why training did or did not realize its proposed outcomes. Training efficiency is a much expansive notion moreover encompasses training assessment as well as its criterion. Q2) Identify and describe three potential problems with using self-report measures in HRD evolution. How can these problems be minimizing Answer)The faction of self report Measures is decisive for accomplishment; however it is an unsatisfactory art, as adept by nearly all corporations. Moreover time and again, the spotlight is on established, technological measures, rather than on the explicit wants of the individuals concerned in addition to the preferred outcomes. This becomes even more stressed within the time and again unclear region of self report measures. If we take a much closer look within this segment we would discover that in addition to challenging those inked with the self report measurement to toil towards knowledge and development can guide to measures that are additionally straightforward as well as more precious to all. The foremost, and most elemental, dilemma with the utilization of self report measures is the exploitation of two comparable provisions: assessment and assessing efficiency. The word assessment is a noun that explains a compound business procedure of shaping value or else merit, plus the expression assessing efficiency is a verb idiom. Assessment is a much bigger progression than assessing efficiency. The next trouble is its malfunction to clearly deal with the disparate reasons for assessing the job. Present-day business requirements may perhaps adjoin a fourth rationale to

Women in the Workforce Essay Example for Free

Women in the Workforce Essay As a young a woman living in the 21st century I can only believe that women have every reason to be part of the workforce. In today’s world advancement we have all the technology needed to be able to create balances between our family and work life. In the old days women were viewed to be weak compared to men, because jobs required more physical abilities then mental and critical thinking abilities. Therefore, men were given the working part of the family’s establishment and women were given the care giving for the children part. Today, things are different. Jobs have turned from being only physically oriented to rather more problem solving and thinking oriented. And this makes more opportunities for women to join the workforce. Moreover, I think women should join the labor force because it is proven that when a woman in a family is working it is more likely that the family will rise above the poverty line. Studies done in Bangladesh by Mohammad Yunus, the founder of the micro financing Grameen Bank, show that when the woman in a family is given a chance to generate income for her household she always does a better job with helping her family out of poverty. Women are care givers in nature, and when given the chance to improve the living standard of their children’s lives they will do a better job managing the money and finances. My final reason is that I think in the end, woman or man, we as humans should be given equal opportunities to explore our full potential. No matter what kind of job or craft or hobby we might be doing, we should all be given the chance to thrive and prosper in this life with no restrictions. No matter what race gender or ethnicity we should all be able to do what we love.

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

Marijuana Should Be Legal :: Argument for Medical Marijuana

The purpose of this paper is to illustrate the importance of marijuana as a medicine and to propose a possible change in the federal laws prohibiting the medical use of marijuana. At the present time, thirty-four states ha ve laws that recognize the medical properties of marijuana and allow for its use when prescribed by a doctor. In fact, USA Today polls have shown that there is anywhere from 65% to 78% voter support for marijuana's medicinal use. (1) However, these laws cannot be implemented until there is a change in the federal laws. So why have these federal laws not been changed? First, there is a great misunderstanding of marijuana. There is also a significant lack of funding for marijuana research which could p rove its efficacy as a therapeutic drug. With proper funding, studies could help people understand marijuana so the long awaited and needed change can take place. Background Information on Marijuana What is Marijuana? Marijuana comes from the dried leaves and buds of the cannabis plant. (7) Although there are three varieties of the cannabis plant, cannabis sativa (the least potent of the three) is the most common form of the plant and is the mai n source of marijuana in the United States. Marijuana contains over 400 chemicals, although less than 100 are considered psychoactive. (7) Sixty-one of the chemicals found in marijuana are of the cannabinoid family and are only found in cannabis plants. The main active ingredient in marijuana is the cannabinoid delta-9 tetrahydrocannibinol, or THC. (7) THC has been shown to have many effects such as slowed reactions, increased appetite, released inhibitions, and impaired judgments and motor skills. M any of these effects are similar to the effects of alcohol, except that while alcohol causes a short temper and a propensity towards violence, marijuana does exactly the opposite. Marijuana induces a mellow state of relaxation. History of Marijuana as Medicine Marijuana has been used for thousands of years for its therapeutic value. The first known reference to the medical use of marijuana is contained in the 15th century BC Chinese Pharmacopoeia , the Ry-Ya. While there have been m any other reports on the value of medical marijuana throughout written history, the most noteworthy are the articles contained in many 18th century U.S. medical journals. Between 1840 and 1900, over 100 articles were published detailing the th erapeutic benefits and the safety of the drug. In fact, the federal government has used many references to these articles in health reports.

The Los Angeles Riots of 1992 Essay examples -- Exploratory Essays Res

The Los Angeles Riots of 1992 The Los Angeles riots were a release of pressure that had build up from the innocent charging of Officer Laurence M. Powell and other Police officers that "Used excessive force" on Rodney King on March 3, 1991, but that was not the only reason.(8) In the words of a singer singing about the riots "They said it was for the black man, they said it was for the Mexican, but not for the white man, but if you look at the streets it wasn't about Rodney King, It's bout this f****d up situation and the f****n' police."(9) Did the riots even have anything to do with King? Was King a minor reason for this to happen, or did King put the level of pressure right over the top? Whatever way you see it, the fact is that on April 29, 1992, anarchy was set free in Los Angeles and before the papers could write about the happenings in this city of angels, the writing on the walls could tell it all. Reginald Denny, a truck driver that was driving through the area of hate, stopped his truck and was pulled from his seat only to be beaten by a group of African Americans, was smiled at for his stupidity. Did Reginald Denny deserve to be beaten as much as King did? Many people that participated in the riot believed so, even though those were the same people that felt that that King was wrongly treated. Was this feeling of revenge produced by racism or fair 'take a hit, leave a hit' that would be forgotten once the pain was the same for everyone? Unfortunately, revenge never finds its own way to normal, humankind always wants to be 'one up' on the competition. The system of LA seemed to be falling apart at the thought of "Blacks" getting unfair treatment under the same conditions. The fact that "Blacks" were the ones tha... ... of black doctors helped save life of LA riot victim Reginald Denny. Jet, 51, v82 n6 O'Brien, Maureen, (1992, May 11) Bookstores, libraries destroyed in LA riot. Publishers Weekly, 9, v239 n22 Marlow, Michel, (1992, May 5) LA aftermath WWD, p21, v163 n88 Wojcik, Joanne, (1992, May 4) LA riot damage costliest in history: losses to top $200 million; most damage in likely insured. Business Insurance, 1, v26 n18 Shoemaker, A., James, C., King, L., Hardin, E., Ordog G. (1993, Dec 15) Urban violence in Los Angeles in the aftermath of the riots: a perspective from health care professionals, with implications for social reconstruction. JAMA, The Journal of the American Medical Association, 2833, v270 n23 National Review Magazine, (1993, Nov 15) Crime without punishment. National Review, 14, v45 n22 "April 29, 1992," Sublime, Sublime MCA Records, 1995

how come Essay -- essays research papers

Grazing ecosystems support more herbivore biomass than any other terrestrial habitat (Sinclair 1975, Detling 1988, McNaughton et al. 1989, 1991, Huntly 1991). A functional consequence of this disparity in trophic structure emerges by comparing the relationship between aboveground production and herbivore consumption in the Serengeti and Yellowstone ecosystems with that in other terrestrial ecosystems [ILLUSTRATION FOR FIGURE 3 OMITTED]. For consumption measurements, we included plant material removed by all important herbivores, both vertebrates and invertebrates. All values were energy equivalents (kJ), converted from biomass measurements using standard conversion factors (Golley 1968). For productivity measurements, we considered only the nonwoody fraction of aboveground productivity - that is, net foliage production (NFP) - because woody production is largely unavailable to herbivores. Plotting plant production against consumption revealed that terrestrial ecosystems fall into two groups that are distinguished by the intensity of herbivory ([F.sub.1,78] = 88.2, P [less than] 0.0001; [ILLUSTRATION FOR FIGURE 3 OMITTED]). The first group includes low-herbivory habitats: desert, tundra, temperate forest, tropical forest, [TABULAR DATA FOR TABLE 1 OMITTED] and small grassland sites lacking large herbivores. The second includes the Serengeti and Yellowstone, which exhibit high herbivory rates. On average, herbivores removed 57% (SE = 3.4, n = 40) of NFP in the Serengeti and Yellowstone, whereas they removed only 9% (SE = 1.4, n = 40) of NFP in other terrestrial ecosystems. For example, only 10% (SE = 2.1, n = 14) of the aboveground production was consumed in temperate grasslands that lack large herbivores, showing that the removal of migratory grazers dramatically affects the energy dynamics of grasslands. Slopes of the relationships did not differ statistically between the two groups (P [greater than] 0.10) and were greater than 1, indicating that the proportion of available primary production consumed increased as NFP increased for both groups of habitats. The low level of dispersion of samples around the regression line characterizing plant productivity and consumption in the Serengeti and Yellowstone grasslands suggests that the relationship describes a continuum from cool, temperate to warm, tropical grazing ecosystems. Primary production is greater in... ...erlag. McNaughton SJ, Milchunas DG, Frank DA. 1996. How can net primary productivity be measured in grazing ecosystems? Ecology 77: 974-977. Meagher M. 1973. The Bison of Yellowstone National Park. National Park Service Scientific Monograph Series 1. Washington (DC): United States Department of Interior. Meagher M, Meyer ME. 1994. On the origin of brucellosis in bison of Yellowstone National Park: A review Conservation Biology 8: 645-653. Milchunas DG, Lauenroth WK. 1993. Quantitative effects of grazing on vegetation and soils over a global range of environments. Ecology 63: 327-366. Morton JK. 1972. Phytogeography of the west African mountains. Pages 221-236 in Valentine DH, ed. Taxonomy, Phytogeography, and Evolution. New York: Academic Press. Oesterheld, M, Sala OE, McNaughton SJ. 1992. Effect of animal husbandry on herbivore carrying capacity at the regional scale. Nature 356: 234-236. Peters RH. 1983. The Ecological Implications of Body Size. Cambridge (UK): Cambridge University Press. Prins HHT. 1996. Ecology and Behavior of the African Buffalo: Social Inequality and Decision Making London: Chapman & Hall. Senft RL, Coughenour MB, Bailey DW, Rittenhouse LR, Sala

Play Macbeth

Macbeth – Fair is Foul â€Å"Fair is foul and fouls is fair: Hover through the fog and filthy air. † The paradox â€Å"Fair is foul, and foul is fair,† expresses some of the many themes of Macbeth. There are several different ways in which these words can be interpreted.The first time we hear the statement is in the opening scene when the witches say the exact line â€Å"Fair is foul, and foul is fair† and Macbeth himself repeats it later almost precisely in Act 1 Scene 3: â€Å"So fair and foul a day I have not seen† Act 1 Scene 1, line 48 Which suggests a link between Macbeth and the sisters, though the interesting thing is that he hasn't even met them yet, although they have already conspired to meet with him. They lure him with fair means, by telling him a small truth, to a foul end. Banquo suspects this, but Macbeth ignores his warnings.The witches themselves seem to be the embodiment of the foul part of the phrase. At the time, people were ver y superstitious about witches, believing they were evil and should be burned. They would obviously assume the witches to be evil and untrustworthy. During this time, Guy Fawkes had tried to overthrow the English king, but had failed. However, Macbeth succeeded in acquiring the throne. Perhaps it was only because of the evil witches that he managed to do so. It is possible that he wouldn't have even attempted to become king if the witches had not enticed him with their predictions.The witches also have an eerie atmosphere about them because they always speak in rhyme. When they were first introduced, they were meeting in a storm and by the darkness and turbulence; the audience can tell straight away that they are going to be evil characters in the play. Also the ingredients they use for their spells and charms are unnatural and disgusting. â€Å"Fair is foul, and foul is fair† can be related to the The witches delight in confusion, always speaking in rhyme and often contradict ing themselves in what they say, â€Å"Lesser than Macbeth, and greater.Not so happy, yet much happier. Thou shalt get kings, though thou be none:† Act 1 Scene 3, lines 65-67 Their exact meanings are never clear and even their appearances are confusing, as Banquo states: â€Å"You should be women, And yet your beards forbid me to interpret That you are so. † Act 1 Scene 3, lines 45-47 Characters can sometimes appear to be under the influence of the witches at crucial points in the play, such as when Lady Macbeth calls upon evil spirits, it is very similar to a spell: â€Å"Come, you spirits That tend on mortal thoughts!Unsex me here, And fill me from the crown to the toe top-full Of direst cruelty ;make thick my blood, Stop up the access and passage to remorse, That no compunctious visitings of nature Shake my fell purpose, nor keep peace between Th'effect and it! † Act 1 Scene 5, lines 39-46 However, by the end of the play, it is more like Macbeth has recited t his incantation, as he has become cold and destroyed everything that was ever good about himself. He cannot even find it in his heart to grieve for his wife, saying simply that she should have picked a better time to die.During the play, we see certain character's personalities changing from fair to foul, or foul to fair. For example, at the beginning of the play Macbeth is shown as a brave and noble warrior, perhaps the fairest man in the whole of Scotland. However, his ambition is stirred by the foul predictions of the witches: â€Å"All hail Macbeth! That shalt be King hereafter. † Act 1 Scene 3, line 50 He tries to reject his â€Å"dark desires† to kill, but eventually at the cajoling of his wife he is driven to murder Duncan.Before the deed is done, Macbeth's soliloquy reveals his confusion as he considers all angles, reminding us of the chaos the witches bring. Everything is stacked against the murder, apart from his ambition which he knows can only lead to a fal l. Even then, he is still convinced by Lady Macbeth to murder Duncan. After the murder, Macbeth begins a downward spiral, needing no more encouragement to kill and becoming so obsessed with his pursuit of glory that he doesn't even notice Lady Macbeth slipping into insanity.When she commits suicide, he finds he has lost the capacity for grief. At the start of the play Macbeth appeared to be a fair man, receiving nothing but praise from the wounded sergeant. He had great trouble bringing himself to murder Duncan, and afterwards is burdened with guilt and regret. He believed he was not fit to pray, and when he murdered Duncan, he murdered sleep at the same, time, so he will never be allowed to rest again. â€Å"What hands are here! Ha! They pluck out mine eyes. Will all great Neptune's ocean wash this blood Clean from my hands? Act 2 Scene 2, lines 59-61 However by the end of the play he is so foul he is almost inhuman. This is shown when he has Lady Macduff and her children massacre d in cold blood, and he cannot possibly justify this crime in any way, as it was completely unnecessary. The relationship between Macbeth and Lady Macbeth also turns from fair to foul. At first they share everything, and Macbeth calls his wife â€Å"my dearest partner of greatness. â€Å". When Lady Macbeth assesses her husband's character, it is clear that she knows him very well.