The State of Discord

The debate between Thomas Friedman and Robert Kaplan can throw light on various aspects of globalization, especially its effects on individuals and societies. In particular, one should focus on the role of different states and governments or the factors that increase the integration of different markets, technologies, and finance.Advertising We will write a custom essay sample on The State of Discord specifically for you for only $16.05 $11/page Learn More Moreover, the authors pay attention to such an issue as personal rights and freedoms in the globalized world. These are the main questions that should be discussed more closely. On the whole, this debate is both interesting and thought-provoking because it can enable readers to understand how different communities can evolve in the environment when people from countries can easily interact with one another. Certainly, one cannot tell that the arguments of Thomas Friedman and Robert Kaplan are always su bstantiated with empirical data. This is one of the limitations that should be taken into account. However, this shortcoming does not undermine the value of this discussion since Thomas Friedman and Robert Kaplan illustrate different pathways of globalization. First of all, Thomas Friedman is quite right in pointing out that the process of globalization is driven by the development of technologies, rather than political changes within various communities. For instance, information and communication technologies make the world more interconnected. They create many opportunities for entrepreneurs. Therefore, one should not suppose that the efforts of different states can stop the process of the integration of markets. Such efforts are not likely to be effective because modern people can communicate with one another through a great number of channels. This is one of the main arguments that can be put forward. It seems that this comment is important for understanding the reasons why eco nomic and cultural relations between various countries intensify. Still, one should not forget about availability of natural resources, since this factor affects the patterns of immigration. The availability of natural resources is vital for explaining the origins of conflicts between states. It is possible to argue that the scholars underline the complexities of globalization. This is one of the details that can be important for understanding the changes in the international relations. One of the central questions examined by Thomas Friedman and Robert Kaplan is the role of governments in the world in which the borders become more blurred. On the one hand, the process of globalization is possible when the government decreases its interference into the lives of citizens. Furthermore, this institution does not erect any barriers for businesses.Advertising Looking for essay on international relations? Let's see if we can help you! Get your first paper with 15% OFF Learn Mo re So, one can say that the role of the state can weaken However, the authors also note that under such circumstances, countries are exposed to a great number of economic or ecological risks. Thus, the skills of policy-makers and legislators can profoundly shape the long-term development of a country. They should make sure that a country can derive benefits from new trade agreements or technological innovations. Therefore, one should not disregard the role of governmental institutions. This discussion is important for showing that it is difficult to predict the role of the state in the globalized world of the future. This is one of the main issues that can be singled out. In my view, this question is relevant to modern political leaders who have to safeguard their countries against various threats. Apart from that, it is critical to focus on the impacts of globalization on the identities of individuals. Both authors argue that it is not possible to disregard a person’s atta chment toward a certain region, country, or city. This situation can be observed in various parts of the European Union. For instance, one can mention the development of the nationalist movement in the modern Catalonia. Moreover, one should not suppose that people lose their attachment to the customs, values, or traditions which are familiar to them since childhood. In my opinion, the scholars explain people’s resistance to complete eradication of borders and the domination of only one culture. To a great extent, the scholars show the integration of cultures and regional identities of people can co-exist. Additionally, researchers identify some important risks associated with globalization. For instance, Robert Kaplan notes that the economic development within a country results in political instability. In many cases, one can speak about the change of political regime and open violence that are usually preceded by transformation of the society. This is one of the most importa nt claims that Robert Kaplan makes. In particular, one should focus on countries as Egypt or Libya. Yet, the development of a state is dependent on the political culture of a country and its historical legacy. These questions are of great interest to Robert Kaplan and Thomas Friedman. On the whole, one can say that this issue should be taken into account by the readers, especially if they take interest in political science or geopolitics. Admittedly, one cannot say that the globalization is process that can be easily analyzed or predicted with the help of existing methods. However, it is possible to single out some patterns of its development in the future.Advertising We will write a custom essay sample on The State of Discord specifically for you for only $16.05 $11/page Learn More Another important question that should be discussed is the protection of civic and human rights. The scholars agree the process of globalization increases the role played by middle classes. This layer of the population can limit the authority of the state and its ability to infringe upon the rights of citizens. Robert Kaplan and Thomas Friedman can show how communities may evolve in the future. Certainly, this debate does not contain the reference to any empirical data or models which can explain how societies can adjust to the process of globalization. Therefore, one should not suppose that the predictions made by these scholars will necessarily come true. However, these authors examine hypothetical scenarios that can eventually unfold in various states that can be both advanced and developing economies. This is why their discussion should not be overlooked by readers. Furthermore, this debate can be used by policy-makers who have to reduce the risks of globalization. On the whole, Thomas Friedman and Robert Kaplan can give readers a better idea about different implications of globalization. The scholars do not debate one particular point or thesis st atement. Instead, they attempt to gain a better understanding of this economic, political, and cultural process which affects many people and organizations. It seems that this approach is very productive. The reading can show how various societies can influenced by the integration of various markets and the blurring of national borders. The debate between Thomas Friedman and Robert Kaplan can be used as a starting point for the study of globalization. These are the main issues that can be singled out. This essay on The State of Discord was written and submitted by user Elvis Hayes to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly. You can donate your paper here.

buy custom The Canadian Tourism Human Resource essay

buy custom The Canadian Tourism Human Resource essay In any part of the world tourism is a very dynamic sector that needs a lot of staff to succeed. Tourism needs people in all aspects of the tourist circuit and this poses an insatiable demand for the well trained personnel. In British Columbia, the human resource challenge brought about by dynamism is the fact that not many people working in the tourism sector have been specially trained. One may find a professional waiter taking on the duties of an usher when the demand arises. Some professionals are only needed when the demand arises and as such they result in taking on other jobs to fend for their families. According to Tourism Industry advisory council. (2006) most of the tourists visiting British Columbia are people who have prior experience in tourism having visited other parts of the world. They tend to compare the services offered in British Columbia with those they experienced elsewhere. This comes in total disregard to the numerous new opportunities and experiences that the country has to offer. The human resource well conversant with the country is thus found to be wanting in the eyes of the frequent traveler. Most of the people that work in the tourist attraction areas, in British Columbia have had no prior training in professional colleges. Rather, they have been trained on the job in the relevant institutions where they work. The human resource is rich in experience but lacks the fine touch that professional school training can offer. More and more establishments are beginning to value the training that comes with attending one of the few approved tourism colleges in the country. There are a couple of internationa training colleges that offer various courses covering the hospitality and tourism sectors present in British Columbia that train students. However, due to the dependability on seasons of the tourism sector in the country, most of them end up finding work in foreign countries. This is because competition is more dynamic in foreign countries leading to better pay for the graduates. This is not good for the long run since the tourism sector will end up lacking professionally trained staff (Propel Industry Credentials, 2008). There is also a large discrepancy in the employment numbers through the different sectors in the tourism industry. For instance, according to Canadian Tourism Human Resource Council (2011) the accommodation services required more than 66,000 members of staff as compared to 43,500 in 2001. The problem with this growth pattern is that it is unstable and as such it can record substantial increases in some years and steep declines in the following years. Another factor affecting the human resource in British Columbia is the inability for the sector to attract large numbers of talented individual to pursue careers in tourism and hospitality. This is mainly because the sector is still struggling and people look into pursuing strongly cemented careers that will guarantee success in both monetary and career growth aspects (McCallum, 2009). The food and beverage sector attracts more employees than any other sector in the tourism circle. Preliminary data for 2001 shows that tourism related employment in British Columbia stood at 14% of the overall employment in British Columbia. The rates have increased over the years to stand at 18% in the year 20099 (Canadian Tourism Human Resource Council, 2011 and The Canadian Tourism Human Resource Council and Capilano College, 2001)). This is evidence of the growth in the tourism thus it is important for the industry players to ensure that their establishments are ready to cater for the growing numbers. Tourism has also continued to attract tourists into British Columbia increasing at a rate of 11% in the last decade (BCJobs.ca , 2010). The larger numbers of these tourists are those who are attracted into the country for adventure tourism activities like skiing and golf. These are occasional adventurers who in turn require part time staff to take care of their needs during these ti mes. The tourism sector thus has to be flexible enough to accommodate these needs (Industry Canada, n.d). Projections have shown that employment in this sector is likely to reach 37,700 by 2012 and increase by a further 10,600 through to the year 2020. The annual employment growth rate is projected at 4.2%, though this figure is slightly below the growth rate experienced in this sector during much of the early 2000 (Go2, n.d.). The projections show numbers well above employment growth rates for other areas of tourism related industries. In conclusion, it is important for the industry players to take into account the different needs of tourists who frequent British Columbia and adjust accordingly (Kootenay Rockies, 2007). This will ensure that the current human resource remains employed and relevant in the sector if the tourists keep coming. Tourism is a very viable sector the world over and the staff in this sector need to be well taken care of to ensure that they remain in British Columbia to serve within it own boundaries (Victoria, 2006). Buy custom The Canadian Tourism Human Resource essay

Impact of age diversity Essay Example | Topics and Well Written Essays - 1750 words

Impact of age diversity - Essay Example Specifically, these aspects will be examined in the context of the impact of age in the labor force and how this will affect the roles of the managers in the labor organizations as a recent study reported that by 2020, individuals of 50 years old and up will take up a third of the region’s workforce population. Article Analysis The age of the workers is recognized as a relevant determinant of their performance at work. Some employers prefer the old ones for their developed skills from experience, while the others choose the younger for their flexibility and other characteristics. Such assumptions have rooted from a number of research findings pointing out how workers of specific age ranges easily adapt to changes implemented in the work places (e.g., technology, roles and responsibilities, and etc.) while others can or do not (Morris & Venkatesh, 2000; Morris, Venkatesh, & Ackerman, 2005). Other studies also suggest that an employee’s age can tell employers his or her p robable productivity rate. Specifically, groups of researchers have previously proposed that valuable attitudes and behaviors of the workers decline as one ages (Ferris, et al., 1985; McEvoy & Cascio, 1989; Salthouse & Babcock, 1991; Lawrence, 1988); others, on the other hand, cannot particularly point out concrete evidences of the existence of such relationships in â€Å"different age categories of employees† (Duncan & Loretto, 2004). ... Specifically, groups of researchers have previously proposed that valuable attitudes and behaviors of the workers decline as one ages (Ferris, et al., 1985; McEvoy & Cascio, 1989; Salthouse & Babcock, 1991; Lawrence, 1988); others, on the other hand, cannot particularly point out concrete evidences of the existence of such relationships in â€Å"different age categories of employees† (Duncan & Loretto, 2004). Nevertheless, because of prior assumptions related to these, age discrimination has been inevitable (Ferris & King, 1992; Issacharoff & Harris, 1997; Taylor & Walker, 1997); putting the welfare of the members of the workforce -- especially the old ones -- in line while necessitating further management reorganization and implementation from those with higher positions in the workplace. As such dilemmas coexist, it is then important to consider several aspects that affect and, likewise, become affected by the consequences of the age of the employees by the overall performan ce of the workforce as well as the management of the organization. This is particularly true as an unexpected shift of the age of the workforce is to be anticipated after nine years; that is, more than 30% of the members of the United Kingdom workforce â€Å"will be over 50 by 2020† (Snowdon, 2010). In Snowdon’s article, it was noted that the Chartered Management Institute (CMI) and the Chartered Institute of Personnel and Development (CIPD) reported in a research that majority of the managers in the work organizations in UK are still unprepared for this shift. Although the author seems to lack the efficiency of properly addressing the audience that he intends to tap with his article, it is without a doubt that

Describe urban blight Essay Example | Topics and Well Written Essays - 500 words

Describe urban blight - Essay Example The main reason which can be identified for the phenomenon of urban blight includes the neglect from the respective governments of the particular region. Lack of economic support towards the proper maintenance of the areas can also result in the deterioration of the older buildings and portions of the cities. Effects of urban blight can be of high significance. Urban Blight has the possibility of causing hazard to other buildings and also is threatening for the lives of human beings. The buildings in the city with poor conditions are very much prone to fire and also have the high probability of collapsing down at any times which may cause considerable damage to the society. (What is urban blight, n. d). Another significant cause of urban blight can refer to the process of urban renewal scheme, where the government focuses on the development of the cities in areas near to the highways. As a result of such projects they fail to concentrate on the older parts of the city which leads to their deterioration. The increase in tax in The United states property improvement gave rise to the urban Blight in the area. (Soares, et al, p.675, 2011) Shanty town refers to the settlement of people in slums. The presence of shanty town is mostly observed in the developing and the partially developed nations where unequal distribution of wealth prevails. The people in shanty town lead a treacherous life and their primary needs are often not fulfilled. They lack a proper shelter as their dwellings are made up of scrap materials which may collapse easily under any sort of environmental calamity. People living in shanty town lack proper sanitation facility and leads an unhygienic lifestyle (Clark, 2003, p.122). The slums in which they live are generally one room and are shared by many people who make it clumsy and suffocating. There is no facility of electricity in the

Question of risk assessment Essay Example | Topics and Well Written Essays - 250 words

Question of risk assessment - Essay Example In case of an accident, there are possibilities of planning errors, storage errors, and execution errors in the management field. For example, if the employees of an organization went on strike demanding better remuneration and working conditions. The planning error can occur in this case where the management uses a wrong approach to the problem hence accelerating the problem. This can happen where the managements plans to fire the striking workers instead of addressing their grievances. The storage error that can happen in this scenario may involve how the management will try to contain the strike. Where the management decides to ignore the demands of the striking employees this amounts to a storage error. An execution error in this case may involve how the management makes the ultimate address to the strike. Where the management fires the striking employees, this will jeopardize the operations and performance of the organization. All these errors question the reliability of the sys tematic procedures adopted by the management as stipulated under the SHARP

Wavelet Packet Feature Extraction And Support Vector Machine Psychology Essay

Wavelet Packet Feature Extraction And Support Vector Machine Psychology Essay ABSTRACT- The aim of this work is an automatic classification of the electroencephalogram (EEG) signals by using statistical features extraction and support vector machine. From a real database, two sets of EEG signals are used: EEG recorded from a healthy person and from an epileptic person during epileptic seizures. Three important statistical features are computed at different sub-bands discrete wavelet and wavelet packet decomposition of EEG recordings. In this study, to select the best wavelet for our application, five wavelet basis functions are considered for processing EEG signals. After reducing the dimension of the obtained data by linear discriminant analysis and principal component analysis, feature vectors are used to model and to train the efficient support vector machine classifier. In order to show the efficiency of this approach, the statistical classification performances are evaluated, and a rate of 100% for the best classification accuracy is obtained and is compa red with those obtained in other studies for the same data set. Keywords- EEG; Discrete Wavelet Transform, Wavelet Packet Transform, Support Vector Machine, Statistical analysis, classification. 1. Introduction In neurology, the electroencephalogram (EEG) is a non-invasive test of brain function that is mostly used for the diagnosis and classification of epilepsy. The epilepsy episodes are a result of excessive electrical discharges in a group of brain cells. Epilepsy is a chronic neurological disorder of the brain that affects over 50 million people worldwide and in developing countries, three fourths of people with epilepsy may not receive the treatment they need [1]. In clinical decisions, the EEG is related to initiation of therapy to improve quality of epileptic patients life. However, EEG signals occupy a huge volume and the scoring of long-term EEG recordings by visual inspection, in order to classify epilepsy, is usually a time consuming task. Therefore, many researchers have addressed the problem of automatic detection and classification of epileptic EEG signals [2, 3]. Different studies have shown that EEG signal is a non-stationary process and non-linear features are extracted fr om brain activity recordings in order to specific signal characteristics [2, 4, 5, 6]. Then these features are used as input of classifiers [11]. Subasi in [7] used the discrete wavelet transform (DWT) coefficient of normal and epileptic EEG segments in a modular neural network called mixture of expert. For the same EEG data set, Polat and Gà ¼nes [8] used the feature reduction methods including DWT, autoregressive and discrete Fourier transform. In Subasi and Gursoy [9], the dimensionality of the DWT features was reduced using principal component analysis (PCA), independent component analysis (ICA) and linear discriminant analysis (LDA). The resultant features were used to classify normal and epilepsy EEG signals using support vector machine. Jahankhani, Kodogiannis and Revett [10] have obtained feature vectors from EEG signals by DWT and performed the classification by multilayer perceptron (MLP) and radial basis function network. Wavelet packet transform (WPT) appears as one of most promising methods as shown by a great number of works in the literature [11] particularly for ECG signals and relatively fewer, for EEG signals. In [12], Wang, Miao and Xie used wavelet packet entropy method to extract features and K-nearest neighbor (K-NN) classifier. In this work, both DWT and WPT split non stationary EEG signals into frequency sub-bands. Then a set of statistical features such as standard deviation, energy and entropy from real database EEG recordings were computed from e ach decomposition level to represent time-frequency distribution of wavelet coefficients. LDA and PCA are applied to these various parameters allowing a data reduction. These features were used as an input to efficient SVM classifier with two discrete outputs: normal person and epileptic subject. A measure of the performances of these methods is presented. The remaining of this paper is organized as follows: Section 2 describes the data set of EEG signals used in our work. In Section 3, preliminaries are presented for immediate reference. This is followed by the step up of our experiments and the results in section 4. Finally, some concluding remarks are given in Section 5. 2. DATA SELECTION We have used the EEG data taken from the artifact free EEG time series database available at the Department of Epileptology, University of Bonn [23]. The complete dataset consists of five sets (denoted A-B-C-D-E). Each set contains100 single-channel EEG signals of 23,6s. The normal EEG data was obtained from five healthy volunteers who were in the relaxed awake state with their eyes open (set A). These signals were obtained from extra-cranially surface EEG recordings in accordance with a standardized electrode placement. Set E contains seizure activity, selected from all recording sites exhibiting ictal activity. All EEG signals were recorded with the same 128 channel amplifier system and digitized at 173.61Hz sampling. 12 bit analog-to-digital conversion and band-pass (0.53-40 Hz) filter settings were used. For a more detailed description, the reader can refer to [13]. In our study, we used set A and set E from the complete dataset. Raw EEG signal Feature extraction: Energy, Entropy and Standard deviation from DWT and WPT decom-position coefficients Dimensionality reduction by LDA and PCA Classification and Performance measure Healthy Epileptic Figure 1 The flow chart of the proposed system 3. methods The proposed method consists of three main parts: (i) statistical feature extraction from DWT and from WPT decomposition coefficients, (ii) dimensionality reduction using PCA and LDA, and (iii) EEG classification using SVM. The flow chart of the proposed method is given in figure 1. Details of the pre-processing and classification steps are examined in the following subsections. 3.1 Analysis using DWT and WPT Since the EEG is a highly non-stationary signal, it has been recently recommended the use of time-frequency domain methods [14]. Wavelet transform can be used to decompose a signal into sub-bands with low frequency (approximate coefficients) and sub-bands with high frequency (detailed coefficients) [15, 16, 17]. Under discrete wavelet transform (DWT), only approximation coefficients are decomposed iteratively by two filters and then down-sampled by 2. The first filter h[.] is a high-pass filter which is the mirror of the second low pass filter l[.]. DWT gives a left recursive binary tree structure. We processed 16 DWT coefficients. Wavelet packet transform (WPT) is an extension of DWT that gives a more informative signal analysis. By using WPT, the lower, as well as the higher frequency bands are decomposed giving a balanced tree structure. The wavelet packet transform generates a full decomposition tree, as shown in figure 2. In this work, we performed five-level wavelet packet deco mposition. The two wavelet packet orthogonal bases at a parent node (i, p) are obtained from the following recursive relationships Eq. (1) and (2), where l[n] and h[n] are low (scale) and high (wavelet) pass filter, respectively; i is the index of a subspaces depth and p is the number of subspaces [15]. The wavelet packet coefficients corresponding to the signal x(t) can be obtained from Eq. (3), l (3,0) (3,1)†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦(3,6) (3,7) h l h l h l h h l h l h l SIGNAL (0,0) (1,0) (1,1) (2,0) (2,1) (2,2) (2,3) Figure 2 Third level wavelet packet decomposition of EEG signal Table 1 gives the frequency bands for each level of WPT decomposition. Figures 3 and 4 show the fifth level wavelet packet decomposition of EEG segments, according to figure 2. We processed 32 WPT coefficients. Therefore, in this study, three statistical parameters: energy feature (En), the measure of Shannon entropy (Ent) and standard deviation (Std) are computed, (4) (5) (6) 3.2 Principal component analysis To make a classifier system more effective, we use principal component analysis (PCA) for dimensionality reduction. The purpose of its implementation is to derive a small number of uncorrelated principal components from a larger set of zero-mean variables, retaining the maximum possible amount of information from the original data. Formally, the most common derivation of PCA is in terms of standardized linear projection, which maximizes the variance in the projected space [18, 19]. For a given p-dimensional data set X, the m principal axes W1,†¦,Wm where 1≠¤ m≠¤ p, are orthogonal axes onto which the retained variance is maximum in the projected space. Generally, W1,†¦,Wm can be given by the m leading eigenvectors of the sample Table1 Frequency band of each wavelet decomposition level. Decomposition level Frequency band (Hz) 1 2 3 4 5 0-86.8; 86.8-173.6 0-43.5; 43.5-86.8; 86.3-130.2 ;130.2-173.6 0-21.75; 21.75-43.5; 43.5-54.375; 54.375-86.3; 86.3-108.05; 108.05-130.2; 130.2 130.2-151.95; 151.95-173.6; 0-10.875; 10.875-21.75; 21.75-32.625; 32.625-43.5; 43.5-54.375; 54.375-65.25; 65.25-76.125; 76.125-87; 87-97.875; 97.875-108.75; 108.75-119.625; 119.625-130.5; 130.5-141.375; 141.375-152.25; 152.25-163.125; 163.125-173.6 0-5.44; 5.44-10.875; 10.875-16.31; 16.31-21.75: 21.75-27.19; 27.19-32.625; 32.625-38.06; 38.06-43.5; 43.5-48.94; 48.94-54.375; 54.375-59.81; 59.81-65.25; 65.25-70.69; 70.69-76.125; 76.125-81.56;81.56-87; 87-92.44; 92.44-97.87; 97.87-103.3; 103.3-108.75; 108.75-114.19; 114.19-119.625; 119.625-125.06; 125.06-130.5; 130.5-135.94; 135.94-141.38; 141.38-146.81; 146.81-152.25; 152.25-157.69; 157.69-163.125; 163.125-168.56; 168.56-173.6 covariance matrix where is the sample mean and N is the number of samples, so that SWi= ÃŽ »iWi, where ÃŽ »i is the ith largest eigenvalue of S. The m principal components of a given observation vector xi are given by the reduced feature vector . 3.3 Linear discriminant analysis Linear discriminant analysis (LDA) projects high-dimensional data onto a low-dimensional space where the data can achieve maximum class separability [19]. The aim of LDA is to create a new variable that is a combination of the original predictors, i.e. the derived features in LDA are linear combinations of the original variables, where the coefficients are from the transformation matrix i.e. LDA utilizes a transformation matrix W, which can maximizes the ratio of the between-class scatter matrix SB to the within-class scatter matrix SW, to transform the original feature vectors into lower dimensional feature space by linear transformation. The linear function y= WTx maximizes the Fisher criterion J(W) [19], where xj(i) represents the jth sample of the ith of total c classes. k is the dimension of the feature space, and  µi is the Figure 3 Fifth level wavelet packet decomposition of healthy EEG signal (set A). Figure 4 Fifth level wavelet packet decomposition of epileptic EEG signal (set E). mean of the ith class. Mi is the number of samples within classes i in total number of classes. where is the mean of the entire data set. As a dimensionality reduction method, LDA has also been adopted in this work. 3.4 SVM classifier In this work, SVM [20] has been employed as a learning algorithm due to its superior classification ability. Let n examples S={xi,yi}i=1n, yià Ã‚ µ{-1,+1}, where xi represent the input vectors, yi is the class label. The decision hyperplane of SVM can be defined as (w, b); where w is a weight vector and b a bias. The optimal hyperplane can be written as, where w0 and b0 denote the optimal values of the weight vector and bias. Then, after training, test vector is classified by decision function, To find the optimum values of w and b, it is required to solve the following optimization problem: subject to where ÃŽ ¾i is the slack variable, C is the user-specified penalty parameter of the error term (C>0), and φ the kernel function [21]. A radial basis function (RBF) kernel defined as, was used, where ÏÆ' is kernel parameter defined by the user. 4. results and discussion Before we give the experimental results and discuss our observations, we present three performance measures used to evaluate the proposed classification method. (i) Sensitivity, represented by the true positive ratio (TPR), is defined as (ii) Specificity, represented by the true negative ratio (TNR), is given by, (iii) and average classification accuracy is defined as, (16) where FP and FN represent false positive and false negative, respectively. All the experiments in this work were undertaken over 100 segments EEG time series of 4096 samples for each class set A and set E. There were two diagnosis classes: Normal person and epileptic patient. To estimate the reliability of the proposed model, we utilize ten-fold cross validation method. The data is split into ten parts such that each part contains approximately the same proportion of class samples as in the classification dataset. Nine parts (i.e. 90%) are used for training the classifier, and the remaining part (i.e. 10%) for testing. This procedure is repeated ten times using a different part for testing in each case. As illustrated in Fig.3 and 4, feature vectors were computed from coefficient of EEG signals. Taking energy as feature vector, figure 5 shows that the features of both normal and epileptic EEG signals are mixed. The proposed analysis using wavelets was carried out using MATLAB R2011b. In literature, there is no common suggestion to select a particular wavelet. Therefore, a very important step before classifying EEG signals is to select an appropriate wavelet for our application. Then, five wavelet functions namely Daubechies, Coiflets, Biorthogonal, Symlets and Discrete Meyer wavelets are examined and compared, in order to evaluate the performance of various types of wavelets. Figure 6 shows accuracy, sensitivity and specificity from different wavelets. We see that the best wavelet giving good correct rate is the Db2, Db4, coif3 and Bior1.1.The choice of the mother wavelet is focused on daubechies where the length of the filter is 2N, while coifflet wavelet filter is 6N and biorthogonal wavelet (2N +2). After EEG signal Db2 wavelet decomposition and dimensionality reduction, results of correct rate classification are showed in Table 2. The classification accuracy varies from the optimum value (100%) to a lowest value (87%). The results using standard deviation are the best results obtained and using entropy is better than using energy in EEG signals classification. In this study, experimental results show that linear discriminant analysis based on wavelet packet decomposition improves classification and the optimum SVM results are obtained by using standard deviation feature computed from wavelet packet coefficient and LDA reduction method. For this proposed scheme, the accuracy of the classification is 100%. This method presents a novel contribution and has not yet been presented in the literature. Figure 7 shows the average rate of classification (accuracy, sensitivity, specificity) obtained with different methods of decomposition (DWT or WPT), two reduction methods (LDA or PCA) and three characteristic features (standard deviation, energy, entropy) using the four best wavelet (Db2, Db4, coif3 and Bior1.1). We see that the combination of LDA with standard deviation have an optimum average accuracy rate of 99.90% and combination of standard deviation with PCA reaches 99.50 %. Table 3 gives a summary of the accuracy results obtained by other studies from the same dataset (set A and set E) using extraction of features from EEG signal and their classification. 5. conclusion In this paper, EEG signals were decomposed into time-frequency representations using discrete wavelet transform, wavelet packet transform and statistical features were Figure 5 Energy feature vector coefficient D3versus D2 (adapted from [22]). Table 3 Epilepsy classification accuracies evaluation obtained in literature from the same data sets Authors Method Accuracy (%) [7] Subasi DWT + Mixture of Expert 94.50 [8] Polat and Gà ¼nes DWT+DFT+ Auto-regres-sive model + Decision Tree 99.32 [9] Subasi and Gursoy DWT+PCA+ LDA+ICA +SVM 98.75(PCA) 100(LDA) 99.5(ICA) [12] Wang, Miao and Xie WPT+ Entropy-hierarchical K-NN classification 99,44 [14] ÃÅ"beylà ¯ Burg autoregressive + LS-SVM 99.56 Our method WPT + Standard deviation+ LDA + SVM 100 computed to represent their distribution. The most suitable mother wavelets for feature extraction and classification were found. The selection of the suitable mother wavelet and using reduction methods lead to the improvement of performance of EEG signal classification. It has been shown by experiments that for the SVM and the combination of the standard deviation with LDA have the highest correct classification rate of 100% in comparison with other techniques. The interest in expert systems for detection and classification of epileptic EEG signal is expected to grow more and more in order to assist and strengthen the neurologist in numerous tasks, especially, to reduce the number of selection for classification performance. These promising results encourage us to continue with more depth our study and to apply it to other databases recorded with other diseases.

Images and Imagery within Shakespeares Macbeth :: GCSE English Literature Coursework

The Reinforcing Imagery Within Macbeth      Ã‚  Ã‚  Ã‚  Ã‚   In the classic Shakespearean drama Macbeth it seems that every scene is laden with copious imagery - and for a purpose. Its intended purpose is to play a supporting role for more important facets of the play, for example theme.    In his book, On the Design of Shakespearean Tragedy, H. S. Wilson interprets the imagery of Macbeth:    Macbeth is a play in which the poetic atmosphere is very important; so important, indeed, that some recent commentators give the impression that this atmosphere, as created by the imagery of the play, is its determining quality. For those who pay most attention to these powerful atmospheric suggestions, this is doubtless true. Mr. Kenneth Muir, in his introduction to the play - which does not, by the way, interpret it simply from this point of view - aptly describes the cumulative effect of the imagery: "The contrast between light and darkness is part of a general antithesis between good and evil, devils and angels, evil and grace, hell and heaven . . . and the disease images of IV, iii and in the last act clearly reflect both the evil which is a disease, and Macbeth himself who is the disease from which his country suffers."(67-68)    Roger Warren comments in Shakespeare Survey 30 , regarding Trervor Nunn's direction of Macbeth at Stratford-upon-Avon in 1974-75, on opposing imagery used to support the opposing notions of purity and black magic:    Much of the approach and detail was carried over, particularly the clash between religious purity and black magic. Purity was embodied by Duncan, very infirm (in 1974 he was blind), dressed in white and accompanied by church organ music, set against the black magic of the witches, who even chanted 'Double, double to the Dies Irae. (283)    L.C. Knights in the essay "Macbeth" explains the supporting role which imagery plays in Macbeth's descent into darkness:    To listen to the witches, it is suggested, is like eating "the insane root, That takes the reason prisoner" (I.iii.84-5); for Macbeth, in the moment of temptation, "function," or intellectual activity, is "smother'd in surmise"; and everywhere the imagery of darkness suggests not only the absence or withdrawal of light but - "light thickens" - the presence of something positively oppressive and impeding.   (101)    In Fools of Time: Studies in Shakespearean Tragedy, Northrop Frye shows how the playwright uses imagery to reinforce the theme: