Difference between Structured and Unstructured Observation

Difference between Structured and Un structure ObservationAt the first trample of this assessment I essential to outline what is involved in structured manifestation. The two main strategies that seekers notify commonly utilization to record their postings of events ar the structured and unstructured observation. The former involves the recording of events of pre delineate types emitring at bumpicular dooms in time, or within particular intervals. Structured observation typically produces duodecimal entropy (information close to(predicate) the frequency of versatile sorts of events or of the proportion of time spent on disparate types of action at law). This form of observation typically involves different threats to validity. Among the dangers with structured observation is that the predefined categories employ, exit turn out not to be clearly defined, so that there is uncertainty in particular instances about which category is appropriate. at that place may alike be relevant events that do not seem to fit into any of the categories. This, however, is only gained at the cost of the information being collected on different cases or at different quantify often not being compar fitted (Research Methods in Education, Handbook, p. 44).Further more than, structured observation is swooning to be described unless difficult to be appreciated without actually engaging in the process. Very simply, it involves placing an observer in a kindly setting to observe all activities defined as of interest to the interrogation. In essence, the method acting is derived from short-changeer observation in social anthropology and the eminence which is sometimes made between participant and non-participant observation does not fully induce in practice some degree of participation is inevitable. As William Howard Russell, the Victorian war correspondent for the Times said I base of operations and look around, and say thus does it appear to me and thus I seem to see so does the structured observation. The structure of structured observation is imposed by the aims of the search in the same air as such aims impose structure upon any method of data-collection. Just as is the case when open questions be used in interviews or self-completed questionnaires the tec using structured observation recognizes that not all of the structure discharge be determined in pass and that some structure must be imposed on the data after they have been collected (Roberts, 1975, p. 309).Researchers undertaking structured observational research usually look to use low-inference categories in an other(a)(prenominal) words, categories that can be applied to instances with a minimum of contestable judgement on the part of the observer in the hope of incurring only small elements of error and uncertainty. For precedent, low-inference categories for observing a meeting cleverness include such things as Asks a question, Expresses agreement and Makes a proposal (E891 Educational Enquiry, film Guide, p. 145). Furthermore, it is almost sure that some data obtained from structured observation contain errors, especially if observation is carried out under coarse pressure of time, leading the candidate to make wrong judgement in wrong boxes. However structured observation as a quantitative research has as well as been guided by at least some of the assumptions of favorableness from laboratory experiments, through structured observational studies of classroom teaching, to large-scale social surveys of the attitudes of teachers, students, p arents, reading managers and others. Indeed, all over the build of the twentieth century, a great deal of educational research was settled by a positive(p) approach restoreed, for example, with identifying the relative effectiveness of different teaching strategies and techniques (Dunkin, 1974, p. 6).Coming to the mo part of the assignment, I will try to lay in according to the best of my knowledge, the methodo limpid philosophy of incontrovertibility. In concern to the tenets of logical empiricism, scientific progress in any discipline begins with the untainted observation of reality. This fact is expected to stand the researcher with an image of the real world from which cognitively generates an a priori model of the process to be investigated. The word incontrovertibility is nowadays used in such a wide range of ways that it has perplex almost think aboutingless, except that it is usually employed desperately to dismiss views or forms of research of which the speaker disapproves. The original meaning of the term contained some important elements. Widely, positivism can be characterised historically as a way of thinking about knowledge and enquiry that takes natural science, as it developed after the seventeenth century, as the model, and which seeks to apply the scientific method to new fields. Even though the term positivism was not invented until the nine teenth century, this thinking was a central anchor of eighteenth-century Enlightenment thinking, although it was by no means the only one and was certainly not recognised by all Enlightenment thinkers (E891 Educational Enquiry, carry Guide, p. 78). mavin of the main elements of positivism is the fancy that it is the assess of research to identify standard repeatable patterns between cause and effect, identifying particular pedagogical strategies that reliably bring about a desirable educational outcome. However, there are questions about whether such patterns dwell, what character they have if they do, and how we can know them. Another feature of positivism is the idea that research must follow an explicit procedure, so that the idiosyncratic effects of who is doing the research can be eliminated and the replicability of the findings checked. Trying to build on this, the concept of evidence- found policy-making and practice is often promoted on the grounds that it is transpare nt, since it is guided by explicitly specified knowledge whose validity is open to inspection even though this idea is subjected to dispute.In contrast, the positivist philosophy, suffers from several limitations, especially when applied to social sciences. First, this approach, generalizes a universal statement of truth from observations of a certain number of positive instances. The grim inductionist approach is often inappropriate because speculation and creation of an a priori hypothesis are essential for a systematic procedure of theory building. Furthermore, the empiricist approach is based on the notion of pure observation, which is impossible in research, especially in social sciences, since observations are always subject to measurement errors. Finally, this approach assumes that knowledge is derived from an verifiable interpretation of assumptions, without any of the subjective biases or a priori knowledge of the scientist coming into play.Furthermore, positivists have t ended to believe that the success of natural science in modern times has stemmed from scientists refusal to go beyond what can be supported by empirical evidence. It is easy to forget how radical an orientation this was in earlier centuries, and maybe shut up is in some quarters. It challenges religious claims to knowledge about the world, various kinds of speculative philosophy that do not pay close attention to what is warranted by empirical evidence, and even any appeal to what is obvious to common sense. (E891 Educational Enquiry, Study Guide, p. 79).The third component of my essay is the strengths and weaknesses of structured observation in concern of positivism. Although positivism has been a recurrent theme in the memoir of western thought from the Ancient Greeks to the present day, it is historically associated with the nineteenth-century French philosopher, Auguste Comte, who was the first thinker to use the word for a philosophical military post. In his study of the fib of the philosophy and methodology of science, Oldroyd (1986) says It was Comte who consciously invented the new science of society and gave it the name to which we are accustomed. He thought that it would be possible to establish it on a positive basis, just like the other sciences, which served as necessary preliminaries to it. For social phenomena were to be viewed in the light of physiological (or biological) laws and theories and investigated empirically, just like physical phenomena. Likewise, biological phenomena were to be viewed in the light of chemical laws and theories and so on down the line (Silverman et al, (2000), p.18). Furthermore, Comtes position was to lead to a general doctrine of positivism which held that all genuine knowledge is based on sense experience and can only be advanced by means of observation and experiment. Firstly, Positivism here implies a particular stance concerning the social scientist as an observer of social reality and second the end-prod uct of investigations by social scientists can be formulated in terms parallel to those of natural science. This means that their analyses must be expressed in laws or law-like generalizations of the same kind that have been established in relation to natural.Positivists often had high hopes that science, and especially a science of human social breeding, would pave the way for substantial social and political progress, by undermining beliefs and practices that were based solely on superstition or tradition, and replacing them wherever possible with ones founded on scientific evidence. To a large extent, positivists have, adopted experimental physics as their model. As a result to this, it has been a strong tendency for them to insist that it is essential to use the experimental method, and the forms of statistical outline modelled on it, to engage in the careful measurement of phenomena, and to look for causal or statistical relationships among variables. These commitments stron gly imply the use of quantitative data (E891 Educational Enquiry, Study Guide, p. 89). Another characteristic of positivist philosophy is the view that, to develop knowledge, it is essential to follow special or transparent procedures or methods. The logic behind this is that it helps to eliminate the biases that can arise through the influence of the personal and social characteristics of the researcher. In addition, can achieve what is sometimes referred to as adjectival objectivity. It also allows others to replicate the research, which in some regard is necessary in order to test whether the knowledge produced is sound, or whether it has been distorted by error or bias by the researcher.Furthermore, positivism is the idea that research should follow a set of explicit procedures, so that the idiosyncratic effects of who is doing the research can be eliminated and the replicability of the findings checked. Building on this, the concept of structured observation policy-making and practice is often promoted on the grounds that it is transparent, since it is guided by explicitly specified knowledge whose validity is open to inspection. The link between positivism and the notion of structured observation does not necessarily mean that the idea that educational research can and should be designed to make a significant contri thation to educational policy-making and/or practice. Indeed, one sign that the positivists impose on this commitment is that positivism has influenced various forms of action research. This often requires enquiry to be integrated into educational practice, rather than being detached from it in the way that much ordinary research is (E891 Educational Enquiry, Study Guide, p. 219). However, as in all methods so in this one strengths and weakness can be distinguished. Structured observation can provide good insights into how the different participants are behaving and interacting. In addition, may enable you to see things that are taken for gr anted by participants in the learning and teaching context. Their perceived lack of importance by participants may mean that they would not be picked up by other methods that explore participant perceptions.In addition to the above, the task of the educational investigator often explains the means by which an orderly social world is established and maintained in terms of its shared meanings and how do participant observation techniques assist the researcher in this task. As Bailey put forward some inherent advantages in the participant observation approachObservation studies are greatest to experiments and surveys when data are being collected on non-verbal behaviour.In observation studies, investigators are able to discern ongoing behaviour as it occurs and are able to make appropriate notes about its salient features.Because case study observations take place over an extended period of time, researchers can develop more inside and informal relationships with those they are obse rving, loosely in more natural environments than those in which experiments and surveys are conducted.Case study observations are less reactive than other types of data-gathering methods. For example, in laboratory-based experiments and in surveys that depend upon verbal solutions to structured questions, bias can be introduced in the very data that researchers are attempting to study.(Silverman et al, (2000), p.18).In contrast to the above, firstly, structured observation neglects the deduction of contexts-temporal and spatial-thereby overlooking the fact those behaviours may be context specific. In their concern for the overt and the observable, researchers may overlook unintended outcomes which may have significance they may be unable to show how significant are the behaviours of the participants being observed in their own terms. Furthermore, structured observations as a quantitative method in concern with positivism can be time consuming. Getting a representative picture of t he implementation over the duration of a buffer or embedding phase of a change in learning and teaching will involve attending more than one learning and teaching activity or event. Continuing, its activities may affect the behaviour of those involved in it and hence what you observe. Participants may be concerned about what you are actually evaluating. Academic round may be concerned the quality of their teaching is being evaluated and students may be concerned their academic performance is being assessed. The thinking that underlies participants observed actions cannot be observed. Finally, structured observations are therefore used with other methods that seek insight into this thinking. Being able to make sense of the context of evaluation in a limited amount of time with limited resources may require some knowledge of the academic discipline and its culture.At this part of my assignment, I will introduce the methodological philosophy of interpretivism. Interpretivism was intr oduced from German philosopher Max Weber. According to Max Weber from whom the interpretivist tradition is derived, the enterprise of social science could not be treated as similar to that of the natural science. He stressed on social action which means the study of meaning which the individual attaches to his/her actions. Interpretivisms starting point is its insistence on differentiating between the nature of the phenomena investigated by the natural sciences and the nature of those studied by historians, social scientists and educational researchers. Mainly, it argues that lot in contrast atoms, chemicals or most non-human forms of life interpret their environment and themselves in ways that are shaped by the particular cultures in which they live. These distinctive hea and soish orientations shape what they do, and when and how they do it (E891 Educational Enquiry, Study Guide, p. 81).Interpretivist does not reject the idea of scientific or objective knowledge, but they questi on the notion that the methods employed by natural science used also in the study of society or social sciences. He stressed on social action which means the study of meaning which the individual attaches to his or her actions. Furthermore Interpretivist criticize Positivists for neglecting the fact that they are studying people who need to be explored in the ways they really think and act in different kinds of situations. Social institutions cannot be treated as separate entities or divorced from the subjective discovering or meaning that people have of them and society cannot be studied on the principle of causality as positivists stress, may make a great deal of sense in the natural world but according to the interpretivist, cannot be rigidly applied in the social world. People do not just react to external stimuli like biologically programmed living(a) organisms. They actively interpret and control the situation and control their behavior, acting on the basis of their interpre tations of what is going on, what is the best course of action. Many different responses are possible. There are three different interpretations of a single event, e.g. there is no consistent cause and effect relationship. Whatever the response, an observer cannot make sense of your response without interpreting the meaning you attributed to your teachers behavior, for it is this meaning that explains your response, not the observable event on its own.Interpretivists argue that all research methods involve complex forms of communication therefore, coming to understand other people necessarily relies two on researchers background, cultural knowledge and skills, and on their willingness to suspend prior assumptions and allow understanding of other peoples orientations to emerge over the course of enquiry. Thus quite different ways of life and associated beliefs about the world can be located at different points in history and also coexist (peacefully or in divergence) at any time. F urthermore, this is not just a matter of differences between societies there is also significant cultural variation within the large, complex societies in which most of us now live. Interpretivists argue that we cannot understand why people do what they do, why particular institutions exist and operate in characteristic ways, without grasping how people interpret and make sense of their world in other words, the distinctive nature of their beliefs, attitudes and thoughts.Coming to this part of my assignment I need to mention the strengths and weaknesses of structured observation within the context of interpretivism. As we know, structured observation involves a researcher watching and sense of hearing to actions and events within a particular context over a period of time, and then making a record of what he or she has witnessed. A distinction is sometimes drawn between participant and non-participant structured observation, indicating that the role of an observer may vary a good deal. He or she may play a participant role in the setting or the events being observed, or may play no such role other than observer. The patriarchal concern behind this distinction is reactivity in other words, the extent to which, and the ways in which, the behaviour of the people studied is shaped both by the fact that they are being studied in a given way and by the particular characteristics and participant role of the researcher (E891 Educational Enquiry, Study Guide, p. 121). Generally speaking, qualitative researchers use relatively structured observation as a supplement to other sources of data. Furthermore, researchers undertaking structured observational research generally seek to use low-inference categories in other words, categories that can be applied to instances with a minimum of contestable judgement on the part of the observer in the hope of incurring only small elements of error and uncertainty. For example, low-inference categories for observing a meeting m ight include such things as Asks a question, Expresses agreement and Makes a proposal. As a result, this is one of the reasons why interpretivism has encouraged a shift towards qualitative method. soft methods are usually taken to mean unstructured or structured observation, ethnography, focus groups, and etc. that involve researchers in actively listening to what the researched say. The popularity of the term paradigm is traceable to Kuhns work on The Structure of Scientific Revolutions 7 it can be defined as a total matrix of beliefs about theories, research questions and research data (Oakley, 1999, p.155). These observations and experiences are one way of representing the conflict between different ways of achieving knowledge about the world that amongst social researchers are known as qualitative and quantitative methods. A commonly accepted alliance has developed between research method and research subject, according to which qualitative methods are often used to privilege th e experiences of oppressed social groups. What I argue is that this division of methodological labour is, firstly, socially and historically constructed and secondly is problematic in terms of the potential of qualitative methods to produce an emancipator social science with trustworthy knowledge claims. However, this qualitative method as all the other research methods has strengths and weaknesses points. Taking the advantages strengths at the beginning, I can definitely mention that usually the data is based on the participants own categories of meaning and the research is only useful for studying a limited number of cases in depth. not only that, another major advantage of the method is that the researcher can describe complex phenomena something that you can ra deposit find in any other method.Structured observation is one of the most straightforward ways to gather information via the school or classroom having a strong connection with the researcher of interpretivism and get a picture of what happens. It is often a good way to begin to explore a situation you want to know more about. It can also be useful to add information to other sources of data you may be collecting for your action enquiry. However, it is important to be aware that as an observer you can often affect the situation you are trying to observe. Generally the role of the observer can be pure (unnoticed, part of the wallpaper) or participatory (e.g. participate in what is going on in the situation observed). The latter use qualitative, structured approaches of observation the former might use a mixture of both quantitative and qualitative approaches. Whilst the pure observer uses an instrument (e.g. proforma) for the observation, the participant-observer is the instrument. One very common example could be the finding of the class teacher in finding out how children solve a multiplication problem. As a pure observer she or he will use an observation checklist, ticking boxes as she or he obse rves the pupil on a pre-determined problem-solving activity. Then, as the instrument himself or herself, she or he may ask the pupil what he or she did, why he did it, and may even set him another, but similar, task, to see if he uses the same strategy. By doing so, the teacher will influence the outcome, but in the context of teaching and learning this may be a valid method of structured observation.Taking the above simple example into consideration someone can definitely determine not only the strengths but also the weaknesses of the method used. From the point of strength, the researcher Can conduct cross-case comparisons and analysis and provides understanding and description of peoples personal experiences of the phenomena. Furthermore, the researcher can study dynamic processes, and determine how participants interpret constructs. In addition, qualitative researchers are especially responsive to changes that occur during the conduct of a study and may shift the focus of their studies. In contrast, biases can be developed. Data analysis is often time consuming and the results are more easily influenced by the researchers personal biases and idiosyncrasies. Meaning that all perceptual processes involving the taking in of information by observation and its subsequent internal process are subject to bias. Our own interests, experiences, and expectations are likely to influence what we pay attention to and do make a conscious effort to distribute your attention widely and evenly. Finally, It is more difficult to test hypotheses and theories with large participant pools but knowledge produced might not generalize to other people or other settings (i.e., findings might be unique to the relatively few people included in the research study.Part six, is the last part of my assignment. The searching question in this part has to do with all of the discussion done on the previous sections. Up to now, structured observation was the core of our assignment and the way researchers develop their task. As a result, I have discussed the structured observation from the point of positivism and the quantity method on the one hand and the structured observation from the point of interpretivism and the qualitative method on the other hand. However since Gage wrote his fictional history, what has actually happened is in fact quite complex and varies across countries. The trend against positivism continued, and what we have called constructionism emerged as an important influence alongside interpretivism and critical research. However, in the early years of the twenty-first century, there have been signs of a second phase, the re-emergence of positivist ideas, partly as a result of calls for practice to become evidence-based. Nevertheless, at present, much educational research continues to take a qualitative approach. Alongside, the revival in support for quantitative methods in some quarters, there have also been increasing calls for mixed methods or trian gulation research that is, research that combines quantitative and qualitative approaches and more methods. The justification for this is often the kind of pragmatism to which Gage appealed. It is suggested that, by combining quantitative and qualitative methods, it is possible to gain the benefits of both and avoid the weaknesses of each when used on its own (E891 Educational Enquiry, Study Guide, p. 89).Coming to the point, the difference between positivism and interpretivism is rather subtle than a difference in focus, but it is still important. Examine the situation historically, the conflict between positivism and interpretivism dates from at least the middle of the nineteenth century, although it only arose clearly within the field of educational research during the second half of the twentieth century. Usually, positivists researchers have generally assumed that it is possible to scroll recurrent and standard patterns of relationship. At first between peoples background exp eriences and their attitudes, and then between their attitudes and their behaviour. On the other side of the coin, interpretivists researchers have suggested that these relationships are much more contingent and diverse, as the historians have emphasised the uncertain course of history and this is not simply the playing out of a set of universal laws. This is what Gage means when he says that interpretivists reject the assumption of the uniformity of nature and elongate causal models (E891 Educational Enquiry, Study Guide, p. 81). It is worth to mention an example at this point to raise the difference among them. Positivists assume that it is possible to document attitudes by acquiring people to respond to a standard structured questionnaire. Interpretivists, however, argue that all research methods involve complex forms of communication therefore, coming to understand other people necessarily relies both on researchers background cultural knowledge and skills, and on their willing ness to suspend prior assumptions and allow understanding of other peoples orientations to emerge over the course of enquiry.Further to the point I have raised concerning the two other methods, i.e., the mixed method or triangulation, I have the feeling I need to elaborate on at least at one of them. The triangulation, in social science, is defined as the mixing of data or methods so that diverse viewpoints or standpoints cast light upon a topic. The mixing of data types, known as data triangulation, is often thought to help in validating the claims that might arise from an initial pilot study. The mixing of methodologies, e.g. mixing the use of survey data with interviews, is a more profound form of triangulation. Denzin wrote a justification for triangulation in 1970 and is credited by some with initiating the move toward integrated research that mixes methods. However other authors in other contexts have used mixed methods research both before and after Denzins summary was writte n. For instance, Lenin used a mixture of quantitative data tables along with a political-economy analysis of charged words used in his classic research monograph, The Development of Capitalism in Russia (1898). We would today say that his work used methodological triangulation of discourse analysis (a qualitative methodology), and survey data (a quantitative methodology), to study the end of the Russian peasantry and the early beginnings of working class conflict with employers in Russia (Wendy O., 2004, p.3).Continuing the above and according to researchers from case studies to econometric analysis, educational research has a long tradition of employing both qualitative and quantitative methods, but the usual juxtaposition of qualitative research against quantitative research makes it easy to miss the fact that qualitative research itself encompasses a multitude of different approaches. Qualitative work can be positivist It can attempt to document practices that lead consistently t o one set of outcomes rather than another, to identify characteristics that commonly are related to some policy problem, or to find strategic patterns that hold across different venues and with different actors. Qualitative work also can be interpretivist It attempts to understand what general concepts like poverty or race mean in their specific operation, to uncover the conscious and unconscious explanations people have for what they do or believe, or to capture and reproduce a particular time, culture, or place so that actions people take become intelligible.In conclusion, observation methods are powerful tools for gaining insight into situations. As with other data collection techniques, they are beset by issues of validity and reliability. Even low inference observation, perhaps the safest form of observation, is itself highly selective, just as perception is selective. Higher forms of inference, whilst moving towards establishing causality, rely on greater levels of interpretat ion by the observer, wherein the observer makes judgements about intentionality and motivation. In this respect it has been suggested that additional methods of gathering data might be employed, to provide documentation and triangulation, in short, to ensure that reliable inferences are derived from reliable data.ReferencesDunkin, M.J. and Biddle, B.J. (1974) The Study of Teaching, New York, Holt, Rinehart and Winston.E891 Educational Enquiry, Study Guide, (2007), The Open University.Oakley, A., Peoples way of knowing gender and methodology. In comminuted issues in social research, Hood, S, Mayall, B. Oliver, S., pp.154-170. Open University Press, 1999.Research Methods in Education, Handbook, (2003), The Open University.Silverman, David (2000). Doing Qualitative Research A Practical Handbook. SageWendy, O. (2004) Triangulation in Social Research Qualitative and Quantitative Methods Can Really Be Mixed, Causeway Press.

Experiment for Plant Recognition

Experiment for Plant RecognitionAbstractIn crystalizeical sparse theatrical performance base classification (SRC) and weighted SRC (WSRC) algorithms, the screen types be sp atomic number 18ly correspond by any fosterage takes. They emphasize the leanness of the coding coefficients but without considering the topical anaesthetic structure of the input data. Although the more training smacks, the repair the sparse bureau, it is time consuming to find a global sparse representation for the test savour on the cosmic-scale database. To overcome the shortcoming, aiming at the rough problem of bring leaf recognition on the large-scale database, a two-stage local similitude based classification learning (LSCL) regularity is proposed by feature local mean-based classification (LMC) method and local WSRC (LWSRC). In the prototypic stage, LMC is applied to coarsely classifying the test sample. k nearby neighbours of the test sample, as a dwell subset, is selected fro m to individu all in ally one training class, then the local geometric center of each class is calculated. S prognosis neighbor subsets of the test sample are goaded with the first S smallest distances amid the test sample and each local geometric center. In the succor stage, LWSRC is proposed to count only represent the test sample by means of and through a linear weighted sum of all k-S samples of the S view neighbor subsets. The rationale of the proposed method is as follows (1) the first stage aims to cash in ones chips the training samples that are outlying(prenominal) from the test sample and assume that these samples run through no effects on the ultimate classification decision, then select the candidate neighbor subsets of the test sample. Thus the classification problem becomes mere(a) with fewer subsets (2) the second stage pays more precaution to those training samples of the candidate neighbor subsets in weighted representing the test sample. This is helpf ul to accurately represent the test sample. Experimental results on the leaf image database demonstrate that the proposed method non only has a high accuracy and low time damage, but also can be clearly interpreted.Keywords Local similarity-based-classification learning (LSCL) Local mean-based classification method (LMC) burden sparse representation based classification (WSRC) Local WSRC (LWSRC) Two-stage LSCL.1. IntroductionSimilarity-based-classification learning (SCL) methods make use of the pair-wise similarities or dissimilarities mingled with a test sample and each training sample to design the classification problem. K-nearest neighbor (K-NN) is a non-parametric, simple, attractive, relatively mature pattern SCL method, and is easy to be quickly achieved 1,2. It has been widely applied to umpteen applications, including computer vision, pattern recognition and machine learning 3,4. Its basic processes are calculating the distance (as dissimilarity or similarity) between the test sample y and each training sample, selecting k samples with k minimum distances as the nearest k neighbors of y, finally determining the category of y that most of the nearest k neighbors belong to. In weighted K-NN, it is useful to assign weight to the contributions of the neighbors, so that the nearer neighbors contribute more to the classification method than the more dissimilarity ones. angiotensin-converting enzyme of the disadvantages of K-NN is that, when the distribution of the training set is uneven, K-NN may cause misjudgment, because K-NN only cares the order of the first k nearest neighbor samples but does non consider the sample density. Moreover, the performance of K-NN is seriously influenced by the existing outliers and noise samples. To overcome these problems, a number of local SCL (LSCL) methods have been proposed recently. The local mean-based nonparametric classifier (LMC) is said to be an alter K-NN, which can resist the noise influences and classif y the unbalanced data 5,6. Its main idea is to calculate the local mean-based vector of each class as the nearest k neighbor of the test sample, and the test sample can be classified into the category that the nearest local mean-based vector belongs to. One disadvantage of LMC is that it cannot nearly represent the similarity between multidimensional vectors. To reform the performance of LMC, Mitani et al. 5 proposed a reliable local mean-based K-NN algorithm (LMKNN), which employs the local mean vector of each class to classify the test sample. LMKNN has been already successfully applied to the group-based classification, discriminant analytic thinking and distance metric learning. Zhang et al. 6 further improved the performance of LMC by utilizing the romaine distance alternatively of Euclidean distance to select the k nearest neighbors. It is proved to be better suitable for the classification of multidimensional data.Above SCL, LMC and LSCL algorithms are often not stiff wh en the data patterns of opposite classes overlap in the regions in feature space. Recently, sparse representation based classification (SRC) 8, a SCL modified manner, has attracted much attention in dissimilar areas. It can achieve better classification performance than other typical clustering and classification methods much(prenominal) as SCL, LSCL, linear discriminant analysis (LDA) and principal component analysis (PCA) 7 in roughly cases. In SRC 9, a test image is encoded over the original training set with sparse simpleness imposed on the encoding vector. The training set acts as a dictionary to linearly represent the test samples. SRC emphasizes the sparsity of the coding coefficients but without considering the local structure of the input data 10,11. However, the local structure of the data is proven to be important for the classification tasks. To make use of the local structure of the data, both(prenominal) weighted SRC (WSRC) and local SCR (LSRC) algorithms have b een proposed. Guo et al. 12 proposed a similarity WSRC algorithm, in which, the similarity matrix between the test samples and the training samples can be constructed by various distance or similarity measurements. Lu et al. 13 proposed a WSRC algorithm to represent the test sample by exploiting the weighted training samples based on l1-norm. Li et al. 14 proposed a LSRC algorithm to perform the sparse decomposition in local neighborhood. In LSRC, instead of solving the l1-norm constrained to the lowest degree square problem for all of training samples, they solved a similar problem in the local neighborhood of each test sample.SRC, WSRC, similarity WSRC and LSRChave roundthing in common, such as, the individual sparsity and local similarity between the test sample and the training samples are considered to ensure that the neighbor coding vectors are similar to each other if they have strong correlation, and the weighted matrix is constructed by incorporating the similarity inform ation, the similarity weighted l1-norm minimisation problem is constructed and solved, and the obtained coding coefficients tend to be local and robust.Leaf based position species recognition is one of the most important branches in pattern recognition and artificial intelligence 15-18. It is useful for agricultural producers, botanists, industrialists, food engineers and physicians, but it is a NP-hard problem and a challenging research 19-21, because appoint leaves are quite irregular, it is difficult to accurately describe their shapes compared with the industrial work pieces, and some between-species leaves are different from each other, as shown in Fig1.A and B, while within-species leaves are similar to each other, as shown in Fig.1C 22.test sample training 1 training 2 training 3 training 4 training 5 training 6 training 7(A) Four different species leaves (B) Four different species leaves(C) decade same species leavesFig.1 plant leaf examplesSRC can be applied to leaf based plant species recognition 23,24. In theory, in SRC and modified SRC, it is well to sparsely represent the test sample by too many training samples. In practice, however, it is time consuming to find a global sparse representation on the large-scale leaf image database, because leaf images are quite complex than face images. To overcome this problem, in the paper, motivated by the recent supercharge and success in LMC 6, modified SRC 12-14, two-stage SR 25 and SR based coarse-to-fine face recognition 26, by creatively integrating LMC and WSRC into the leaf classification, a novel plant recognition method is proposed and verified on the large-scale dataset. Different from the classical plant classification methods and the modified SRC algorithms, in the proposed method, the plant species recognition is implemented through a coarse recognition process and a fine recognition process.The major contributions of the proposed method are (1) a two-stage plant species recognition method, fo r the first time, is proposed (2) a local WSRC algorithm is proposed to sparsely represent the test sample (3) the experimental results indicate that the proposed method is very competitive in plant species recognition on large-scale database.The remainder of this paper is arranged as follows in Section 2, we briefly review LMC, SRC and WSRC. In Section 3, we describe the proposed method and provide some rationale and rendition. Section 4 presents experimental results. Section 5 offers conclusion and future work.2. Related worksIn this section, some related works are introduced. Suppose n training samples,, from different classes X1, X2,,XC. is the sample number of the ith class, then.2.1 LMCLocal mean-based nonparametric classification (LMC) is an improved K-NN method 6. It uses Euclidean distance or cosine distance to select nearest neighbors and measure the similarity between the test sample and its neighbors. In general, the cosine distance is more suitable to describe the simi larity of the multi-dimensional data.LMC is described as follows, for each test sample y, smell 1 Select k nearest neighbors of y from the jth class, as a neighbor subset represented by clapperclaw 2 Calculate the local mean-based vector for each classby, (1) feeling 3 Calculate the distance between y and.Step 4 if Euclidean distance metric is adopted while if cosine distance metric is adopted.2.2 SRCSRC relies on a distance metric to penalize the dissimilar samples and pillage the similar samples. Its main idea is to sparsely represent and classify the test sample by a linear combination of all the training samples. The test sample is assigned into the class that produces the minimum resi cod.SRC is described as follows,Input n training samples, a test sample.Output the class mark off of y.Step 1 Construct the dictionary matrixby n training samples. Each column of A is a training sample called basis vector or atom. mollify each column of A to unit l2-norm.A is required to be uni t l2-norm (or bounded norm) in order to avoid the trivial dissolvers that are due to the ambiguity of the linear reconstruction.Step 2 Construct and solve an l1-norm minimization problem, (2)where x is called as spare representation coefficients of y.Eq. (2) can be usually approximate by an l1-norm minimization problem, (3)whereis the threshold of the residue.Eq.(3) can be generalized as a constrained least square problem, (4)where 0 is a scalar regularization statement which balances the tradeoff between the sparsity of the solution and the reconstruction error.Eq.(4) is a constrained LASSO problem, its detail solution is found in Ref. 27.Step 3 solve residue, whereis the characteristic function that selects the coefficients associated with the ith classStep 4 the class label of, y, is identified as.2.3 WSRCWSRC integrates both sparsity and locality structure of the data to further improve the classification performance of SRC. It aims to impose larger weight to the training sam ples that are farer from the test sample. Different from SRC, WSRC solves a weighted l1-norm minimization problem, (5)where W is a chance event weighted matrix, and its diagonal elements are.Eq.(5) makes sure that the coding coefficients of WSRC tend to be not only sparse but also local in linear representation 13, which can represent the test sample more robustly.2.4 LSRCThough a lot of instances have been reported that WSRC performs better than SRC in various classification problems, WSRC forms the dictionary by use all the training samples, thus the size of the generated dictionary may be large, which will make adverse effect to solving the l1-norm minimization problem. To overcome this drawback, a local sparse representation based classification (LSRC) is proposed to perform sparse decomposition in a local manner. In LSRC, K-NN bill is exploited to find the nearest k neighbors for the test samples, and the selected samples are utilized to construct the over-complete dictionar y. Different from SRC, LSRC solves a weighted l1 minimization problem, (6)wherestands for data matrix which consists of the k nearest neighbors of y.Compared with the original SRC and WSRC, although the computational cost of LSRC will be saved remarkably when, LSRC does not assign different weight to the different training samples.3. Two-stage LSCLFrom the preceding(prenominal) analysis, it is found that each of LMC, WSRC and LSRC has its advantages and disadvantages. To overcome the difficult problem of plant recognition on the large-scale leaf image database, a two-stage LSCL leaf recognition method is proposed in the section. It is a sparse decomposition problem in a local manner to obtain an approximate solution. Compared with WSRC and LSRC, LSCL solves a weighted l1-norm constrain least square problem in the candidate local neighborhoods of each test sample, instead of solving the same problem for all the training samples. Suppose on that point are a test sampleand n training samples from C classes, andis the sample number of ith class,is jth sample of the ith class. Each sample is assumed to be a unidimensional column vector. The proposed method is described in detail as follows.3.1 First stage of LSCLCalculate the Euclidean distancebetween y and, and select k nearest neighbors of y fromwith the first k smallest distances, the selected neighbor subset noted as, .Calculate the average of, (7)Calculate the Euclidean distancebetween y and.From C neighbor subsets, selectneighbor subsets with the firstsmallest distancesas the candidate subsets for the test sample, in simple terms, denoted as.The training samples fromare reserved as the candidate training samples for the test sample, and the other training samples are eliminated from the training set.3.2 Second step of LSCLFrom the first stage, it is noted that at that place aretraining samples from all the candidate subsets. For simplify, we just as well express the jth training sample ofis. The second st age first represents the test sample as a linear combination of all the training samples of, and then exploits this linear combination to classify the test sample.From the first stage, we have obtained the Euclidean distancebetween y and each candidate sample. By, a new local WSRC is proposed to solve the same weighted l1-norm minimization problem as Eq.(5), (8)where is the dictionary constructed bytraining samples of,is the weighted diagonal matrix, is the Euclidean distance between y and.In Eq.(8), the weighted matrix is a locality adaptor to penalize the distance between y and. In the above SRC, WSRC, LSRC and LSCL, the l1norm coldness least square minimization problem is solved by the approach proposed in 28, which is a specialized interior-point method for solving the large scale problem. The solution of Eq.(8) can be expressed as (9)From Eq.(9), is expressed as the sparse representation of the test sample. In representing the test sample, the sum of the contribution of the it h candidate neighbor subset is calculated by (10)whereis the jth sparse coefficient corresponding to the ith candidate nearest neighbor subset.Then we calculate the residue of the ith candidate neighbor subset corresponding to test sample y, (11)In Eq.(11), for the ith class (), a smalleraverages the greater contribution to representing y. Thus, y is finally classified into the class that produces the smallest residue.3.3 Summary of two-stage LSCLFrom the above analysis, the main steps of the proposed method are summarized as follows.Suppose n training samples from Cdifferent classes, a test sample y, the number k of the nearest neighbors of y, the number S of the candidate neighbor subsets.Step 1. Compute the Euclidean distance between the test sample y and every training sample, respectively.Step 2. Through K-NN rules, find k nearest neighbors from each training class as the neighbor subset for y, calculate the neighbor average of the neighbor subset of each class, and calculate t he distance between y and the neighbor average.Step 3. Determine S neighbor subsets with the first S smallest distances, as the candidate neighbor subsets for y.Step 4. Construct the dictionary by all training samples of the S candidate neighbor subsets and then construct the weighted l1-norm minimization optimization problem as Eq.(8).Step 5. Solve Eq.(8) and obtain the sparse coefficients.Step 6. For each candidate neighbor subset, compute the residue between yand its estimationby Eq.(11).Step 7. Identify the class labelthat has the minimum ultimate residue and classify y into this class.3.4 Rationale and interpretation of LSCLIn practical, some between-species leaves are very different from the other leaves, as shown in Fig.1A. They can be easily classified by the Euclidean distances between the leaf digital image matrices. However, some between-species leaves are very similar to each other, as shown in Fig.1B. They cannot be easily classified by some simple classification method s. In Figs.1A and B, suppose the first leaf is the test sample, while other seven leaves are training samples. It is difficult to identify the label of the test leaf by the simple classification method, because the test leaf is very similar to Nos. 4,5,6 and 7 in Fig.1B. However, it is sure that the test sample is not Nos.1, 2 and 3. So, we can naturally firstly exclude these three leaves. This exclusion method example is the purpose of the first stage of LSCL. From Fig.1C, it is found that there is large difference between the leaves of the same species. Therefore, in plant recognition, an optimal scheme is to select some training samples that are relatively similar to the test sample as the candidate training samples, such as Nos. 2 and 9 in Fig.1C are similar to the test sample in Fig.1C, instead of considering all training samples. The average neighbor distance is used to coarsely recognize the test sample. The average neighbor distance as dissimilarity is more effective and rob ust than the original distance between the test and each training leaf, especially in the case of existing noise and outliers.From the above analysis, in the first stage of LSCL, it is reasonable to assume that the leaf close to the test sample has great effect, on the contrary, if a leaf is far enough from the test sample it will have little effect and even have side-effect on the classification decision of the test sample. These leaves should be discarded firstly, and then the later plant recognition task will be clear and simple. In the same way, we can use the similarity between the test sample and the average of its nearest neighbors to select some neighbor subsets as the candidate training subsets of the test sample. If we do so, we can eliminate the side-effect on the classification decision of the neighbor subset that is far from the test sample. Usually, for the classification problem, the more the classes, the lower the classification accuracy, so the first stage is very u seful.In the second stage of LSCL, there are S nearest neighbor subsets as candidate class labels of the test sample, thus it is indeed faced with a problem simpler than the original classification problem, becauseand, i.e., few training samples are reserved to match the test sample. Thus, the computational cost is mostly reduced and the recognition rate will be improved greatly. We analyze the computational cost of LSCL in theory as follows.There are n samples from C classes, and every sample is an m-1 column vector, the first stage study to calculate the Euclidean distance, select k nearest neighbors from each class, and calculate the average of the k nearest neighbors, then the computational cost is about. In second stage, there aretraining samples to construct the dictionary A, the cost ofis, the cost ofis, and the cost ofis. The second stage has computational cost of+. The computational cost of LSCL is ++in total. The computational cost of the classical SRC algorithm is8,9. Co mpared with SRC, it is found that the computational cost of LSCL will be saved remarkably when.4. Experiments and result analysisIn this section, the proposed method is validated on a plant species leaf database and compared with the state-of-the-art methods.4.1 Leaf image data and experiment preparationTo validate the proposed method, we apply it to the leaf classification task using the ICL dataset. All leaf images of the dataset were collected at the Botanical Garden of Hefei, Anhui Province of China by Intelligent Computing Laboratory (ICL), Chinese Academy of Sciences. The ICL dataset contains 6000 plant leaf images from 200 species, in which each class has 30 leaf images. Some examples are shown in Fig.2. In the database, some leaves could be distinguished easily, such as the first 6 leaves in Fig.2A, while some leaves could be distinguished difficultly, such as the last 6 leaves in Fig.2A. We verify the proposed method by two situations, (1) two-fold cocker validation, i.e., 15 leaf images of each class are randomly selected for training, and the rest 15 samples are used for testing (2) leave-one-out cross validation, i.e., one of each class are randomly selected for testing and the rest 29 leaf images per class are used for training.(A) Original leaf images(B) Gray-scale images(C) binary star texture imagesFig.2 Samples of different species from ICL database

Imagery of Disease and Decay in Hamlet Essay -- GCSE English Literatur

Imagery of Disease and Decay in crossroads William Shakespeare found that tomography was a useful tool to micturate his works greater impact and hidden meaning. In village, Shakespeare use imagery to present ideas about the atmosphere, Hamlets character, and the major theme of the play. He used imagery of change integrity to give the reader a feel of the changing atmosphere. He used imagery of disease to hint how some of the different characters perceived Hamlet as he put on his antic disposition. And finally, he used imagery of poison to emphasize the main theme of the play everybody receives rightful requital in the end. Early in Hamlet, Shakespeares first use of imagery was of decay. Marcellus says, Something is rotten in the state of Denmark (I iv 90), to Horatio after Hamlet leaves to talk with the ghost of his father. The imagery of decay used here gives the reader a background understanding of a few things. First, it foreshadows that the kings throne (the state of Den mark) is on shaky ground because Hamlet will shortly find out that his father was murdered and not bitten by a snake as was originally thought. Also, it reveals the building atmosphere of hunch (something is rotten) which would play a role for a big part of the play. Then, two scenes later, imagery of decay was used a second time when Hamlet says, For if the fair weather breed maggots in a dead dog, being a good kissing carrion, (II i 182-183) to Polonius during their first conversation in the play. The imagery of decay used here subtly gets across information of a few things. First, it foreshadows that Hamlet (the sun) will kill Polonius (breed maggots in a dead dog). And secondly, at this point in the scene, Hamlet goes on to talk about his own ... ...mastery of imagery that helped Shakespeare lift himself in the world of literature and to give him a solid place as one of the greatest playwrights of all time. Works Cited and Consulted Bodkin, Maud. Death and Decay in Hamlet Ox ford Oxford University Press. 1934. Burnett, Mark, ed. New Essays on Hamlet. New York AMS Press, 1994. Levin, Richard. 1990. The Poetics and Politics of Bardicide. PMLA 105 491-504. Vickers, Brian. Appropriating Shakespeare Contemporary captious Quarrels. New Haven and London Yale University Press. 1993. Watson, Robert N. 1990. Giving up the Ghost in a World of Decay Hamlet, Revenge and Denial. Renaissance Drama 21199-223. Wright, George T. 1981. Hendiadys and Hamlet. PMLA 96168-193. Shakespeare, William. The Tradegy of Hamlet Prince of Denmark. New York Washington Square Press, 1992

William Shakespeares A Midsummer Nights Dream :: William Shakespeare Midsummer Dream Essays

William Shakespeares A Midsummer wickednesss intakeThe stage production of William Arden Shakespeares A Midsummer Nights Dream, by a British director Tim Supple was one in a million-that everyone talked around it and questions rode questions, on how the performance went. It is the best production I comport ever seen. What grapples me most, is the cast, ravaging with a rich choreography, this was said by the British Ambassador to India in a chat with Times of India.The cleric dramatist melt down was sponsored for production by the British Council, India. Staged at Indira Gandhi National Centre for the Arts, on Rajendra Prasad Road, New Delhi, on the 3 of March, the old, but became-new play was performed by what Mr. Supple described as an all Indian and Sri Lankan cast, spoken in many languages, from English to Hindi and Bengali.It was free. But one has to institute a pass to be admitted in. All and sundry came for this mesmerizing production-and all came and went, but only one p erson never went from my memory. The one and only Arundhati Roy-the population acclaimed author of The God of Small Things. She was there. She was there for good and praises poured on her. Her presence sweetened the sweet production, as well as heightened emotions.A Midsummer Nights Dream is a romantic comedy by William Shakespeare, written sometime in the mid-1590s. It depicts the adventures of four young lovers and a group of amateur actors in a woolgathering forest, and their interactions with the fairies who inhabit it. Today, the play is one of Shakespeares most popular and is performed across the world.When the production came to an end with a big coctail and wide applauds, I realised that I have never read this acclaimed bestseller. And so, I wobbled into a bookshop around and got a copy. It is cheap here in India. Everything is cheap. And I read this book in lead days. Unbelievable? That is the truth. Because the story line is straight and sweet. But before then, the writer -activist who lives in New Delhi spoke about life as a writer. You have to be yourself. No pretence. And if any pretence, that should be embedded in your characters. Think like your characters and see what this life is all about, Ms Roy said, intoned.There is something surreal about her. Her benevolence and non-descriminative wit and candour. India has bestselling authors like Salman Rushdie (Satanic Verses), Amitav Ghosh, Jhumpa Lahiri (Interpreter of Maladies), Chetan Bhagat (One Night the Call Centre), the Nobel Laureates and more.

One Evil Summer :: essays research papers

One Evil SummerIt&8217s finally summer and a time to do what you want and have as much fun as you can. Well that&8217s not the case with Amanda Conklin&8217s who lives in a cruel and crazy townsfolk on a very scary street, Fear Street.Amanda was going threw a lot of bad tuff times, like when the town accused her of lighting an old mans house on fire, or the time when she was accused of stealing from her drill gym. Amanda was also doing fairly bad in school and especially at the end of her school year. Amanda was so frustrated that she told everyone she would soon run away and a few nights that exactly what she did and on that night she was mangle by car and the next morning she was sent to a mental hospital nearby her home. She then came out of the mental hospital a calendar month later and went back to school. The bad thing was tat she didn&8217t know every of the stuff they were studying and there was only one week left wing of school. She was doing terrible in school and on l ast day of school she got her report card and it was terrible. When she came home he showed it to her mother and it was recommended that she should go to summer school.So the summer that Amanda thought would be the greatest summer yet was turned into the worst. Amanda&8217s family decided to move the family to a nearby beach in Seahaven. In Saehaven Amanda was sent to summer school and hated it. Amanda&8217s parents aid that they wer going on a 3week trip and already have everything planned. Amanda&8217s brother and sister were going to be baby sat by who was said to be the town&8217s dress hat baby sitter, her name was Chrissy Meleings. Chrissy was known as the best baby sitter Amandas sister and brother loved her and so did the rest of the town but Amanda had a feeling there was something wrong with her.So Amanda started request or so to see if Chrissie was bad or not. It took long but she found out about her reacent babysitttings from her friend heather and found out that Aman da would kill any animals of yours steal toys and it is rumored that she killed some of the kids she babysat. Amanda was going crazy and it was the second week since Christie has been babysitting her sister and brother and Amanda noticed her cat was missing she then searched all around for it.

To Build A Fire Essay -- essays research papers

To Build a FireIn Jack Londons, To Build a Fire, it is obvious to see that as the story progresses, the domain becomes more bestial. However at the homogeneous time the dog seems to gain the human quality of good sense. This quality of good sense, which the dog acquires, allows it to away from the same fate of the man. There are many examples of how this is portrayed as the story makes headway.The first example of how the man becomes more bestial occurs after his first stimulate fails. After his fire fails, his hands are too cold to allow him to pick up matches. He was trying everything in order to warm up his hands, but nothing was working. Then he came up with a crazy and savage idea to warm them up. The story reads, He would kill the dog, and bury his hands in the warm body until the numbness went out of them. Then he could build another fire... That idea is a perfect example of his turn to bestiality. When the man tries to convey out this insane idea, the dog demonstrates hi s lean towards human characteristics.Another example how the man is beginning to move and act like an animal. It reads, After some manipulation he managed to get the bunch between the heels of his mittened hands. In this fashion he carried it to his mouth... At this point, the mans hands are so cold that he can no all-night grasp objects, such as matches. In order to get the matches he has to use the heels of his ...

Sir Gawain And The Green Knight: The Role Of Women :: essays research papers

In the fourteenth century, knightliness was in decline due to drastic social and economic changes. Although feudalism-along with chivalry-would eventually diminution for other reasons, including a decrease in cheap human resources due to a drop in population caused by plague epidemics and the emergence of a mercantile middle class, the Gawain author perceived a breathing out of religious values as the cause of its decline. Gawain and the park Knight presents both a tin of the old feudal hierarchies and an implicit criticism of changes by recalling chivalry in its idealized state in the courtroom of King Arthur. The women in the story be the poets primary instruments in this critique and reinforcement of feudalism. The poet uses the contrast between the Virgin Mary with Lady Bertilaks wife to degree out the conflict between courtly and spiritual love that he felt had weakened the religious values behind chivalry. The poem warns that a loss of the religious values behind chiv alry would lead to its ultimate destruction. Although superficially Sir Gawain and the thou Knight appears to be a romantic celebration of chivalry, it contains wide-ranging solid criticism of the system. The poet is showing Gawains reliance on chivalrys outside form and substance at the expense of the original values of the Christian religion from which it sprang. The first knights were monastic ones, vowing chastity, poverty and service to God, and undertaking crusades for the corking of their faith. The divergence between this early model and the fourteenth century knight came with the rise of courtly love in which the knights were led to their great deeds by devotion to a mistress rather than God. The discrepancy between this and the churchs mistrust of women and desires of the flesh is obvious, and the poet uses women in the story to sky this message. In contrast to reality at the time, women in the story are given great power Mary, when properly worshiped, gives Gawain hi s power, Lady Bertilak operates alone in the chamber and singlehandedly taints the chevalier, and Morgan the Fay instigates the entire plot, wielding enough power. The author is victimisation them as a metaphor for other anti-social forces and dangers outside the control of feudalism and chivalry, drawing upon biblical and classical examples in his audiences minds of where femininity is linked with subversiveness. Lady Bertilak is intelligibly seen in the Biblical role of the temptress, the Eve who led Adam astray--in Gawain, she represents the traditional female archetypes of courtly love, disobedience, lust and death.Sir Gawain And The Green Knight The Role Of Women essays research papers In the fourteenth century, chivalry was in decline due to drastic social and economic changes. Although feudalism-along with chivalry-would eventually fall for other reasons, including a decrease in cheap human resources due to a drop in population caused by plague epidemics and the emergen ce of a mercantile middle class, the Gawain author perceived a loss of religious values as the cause of its decline. Gawain and the Green Knight presents both a support of the old feudal hierarchies and an implicit criticism of changes by recalling chivalry in its idealized state in the court of King Arthur. The women in the story are the poets primary instruments in this critique and reinforcement of feudalism. The poet uses the contrast between the Virgin Mary with Lady Bertilaks wife to point out the conflict between courtly and spiritual love that he felt had weakened the religious values behind chivalry. The poem warns that a loss of the religious values behind chivalry would lead to its ultimate destruction. Although superficially Sir Gawain and the Green Knight appears to be a romantic celebration of chivalry, it contains wide-ranging serious criticism of the system. The poet is showing Gawains reliance on chivalrys outside form and substance at the expense of the original va lues of the Christian religion from which it sprang. The first knights were monastic ones, vowing chastity, poverty and service to God, and undertaking crusades for the good of their faith. The divergence between this early model and the fourteenth century knight came with the rise of courtly love in which the knights were led to their great deeds by devotion to a mistress rather than God. The discrepancy between this and the churchs mistrust of women and desires of the flesh is obvious, and the poet uses women in the story to deliver this message. In contrast to reality at the time, women in the story are given great power Mary, when properly worshiped, gives Gawain his power, Lady Bertilak operates alone in the bedroom and singlehandedly taints the chevalier, and Morgan the Fay instigates the entire plot, wielding enough power. The author is using them as a metaphor for other anti-social forces and dangers outside the control of feudalism and chivalry, drawing upon biblical and cl assical examples in his audiences minds of where femininity is linked with subversiveness. Lady Bertilak is clearly seen in the Biblical role of the temptress, the Eve who led Adam astray--in Gawain, she represents the traditional female archetypes of courtly love, disobedience, lust and death.