Tv Channels Project India in a Bad Light

TV Channels project India in a bad light Recently the rise of consumerism and a spurt in the number of satellites in the vicinity of our planet have led to rise in the number of TV Channels as well as their viewers across the country. We have specialized channels that cater to the different categories of human taste viz entertainment, music, news,sports,etc. The wider availability of channels helps the viewer to opt among them as per his or her choice. The news channels which are clubbed together in a word ‘media’ is one of the pillars of democracy. It is the moral duty of these news channels to bring the truth in front of the masses.Talking about our country,a nation which is second largest in the world in the terms of population and the largest effective electorate is truly an exemplar of democracy. Like any other nation,it is also laden with issues-both domestic as well as of international concerns. These news channels bear the social responsibility of imparting the n ews, the happenings,the incidents or accidents which should be nothing but the truth. Also the RTI Act empowers any common Indian citizen to go to the depths of affairs and have access to information povide its disclosure does not pose a grave threat to the security and integrity of the nation.The ‘truer’ picture sometimes become harsh and pretty inconvenient to be comestible but scandals and other activities of corruption need to be brought to general awareness. And, it is not only the darker side of affairs, it is also about the achievements and the milestones the country makes in the various spheres-sports, science, humanities,etc. We have several programmes on the national television that are oriented towards the cultural and economic welfare-be it related to the promotion of agriculture,tourism,industry,services,etc.Besides there are programmmes which highlight the nations prosperity, its geographical and cultural diversity and also encourage communal harmony. The consumer oriented channels which basically thrive on the TRP ratings,drama and screenplay is of prime concern to them which helps in a maintaining a certain class of audience bound to it. The audience is engrossed as the way the theme is displayed has a glamour, a pomp and show associated with it. For this, they may exaggerate certain situations or circumstances.Nonetheless,they impart a social message under the rosy spicy recipe of drama-be it child marriage,female foeticide,’honour’ killings,terrorism, etc. And, when a guy from the lower strata of society manages to win 5 crores in a game show by the dint of his knowledge and labour besides a grace of fortune,it clearly sends a strong signal to the society about the reachability of the capital to the masses. Last but not the least,the image of the news channels and the media might have been tainted over the issue of ‘paid’ news and the dubious string operations but their importance cannot be undermined a s a source of public information.There are reality shows which do not miss a opportunity to jeer at the widespread corruption but yes, one needs to appreciate them for their creativity for the ways they adopt to entertain people. It was an eminent personality of Bollywood who blogged regarding a movie getting Oscars with an acerbic response that the jury gets a kind of emotional satisfaction watching the widespread Indian poverty and the slums which the director of the movie has encashed upon. If that be the bitter truth, so be it.There are movies which highlight the unity , the cultural diversity , the celebrations in our country. It would be too early to conclude that TV Channels project our nation in a bad light. Frankly speaking, a sugar coated truth is the better word. Allowing mobile phones in class make students less serious in studies The world is getting smaller and we are living in the era of a ‘global village’ where communication and the exchange of ideas hap pens within the wink of an eye. Information is the key and the power,truly. And, there are several tools and gadgets that facilitate this flow of information.From print media to digital and electonic media, which are primarily used as means of mass communication, we have telephones and mobile phones which are important means of personal communication. Moreover, the recent splurge in the usage of gizmos and gazettes among the generation Y and the youngsters has becomea fad and a status symbol rather than a necessity and mobiles are no exception to it. Their use is not confined to a mere tete-a tete but incorporates several varied applications which diversifies their usage.And a modern day youngster would not be satisfied with a simple Nokia 3600 or1100. He or she would go for the more sophisticated or sleek designs provide there is no hole in the pocket created. Now, coming to the usage of mobile phones inside a class, there are norms which are both discipilnary and moral and make su fficient common sense,whch direct both the teacher/professor and the students who are partcipating in a lecture to put off their cells or keep them in such a mode which aviodsunnecessary distraction.But even the norms which are rarely followed in totto, and even when followed put a cap or restriction to their use as they are intended to. Ina large gatheing being addressed and lectured to,where it becomes increasingly difficult to keep track of each and every student, there are hubs created inside the class where students fail to get engrossed in the monotonous lectures and find their own ways to do away with the time to which cellphones prove to be a great aid.It may include sharing information regarding the latest cell that the neighbour has recently bought, or texting to the pal sitting at the other corner regarding the shabby outlook of the professor,to playing games like snakes,tetris or other advanced versions to listening to songs and watching videos(of all kinds) on the tiny screen. The world of SMSes ahs virtually made the students handicapped of writing anything sincerely as they still cannot help writing those abbreviations of informal chat even when they are writing an answer to aquestion which clearly indicates to their frivolous attitude.Adding to the worse of it,these students would just take a snapshot of te notes of a sincere and laborious classmate thinking that it would suffice and save my time and labour getting ‘wasted’. One may put forth the argument that even during the non mobile days there were always a section of students who were a source of nuisance and distraction by their activities . But the inadvertent entry of mobiles inside the classes provide innumerable creative ways to bolster their activities.A serious student who is trying his/her best to concentrate and attend the lecture would surely look askance at the slim mobile phone his pals are discussingabout for long. Now this seriously puts forward 2 very primary qu estions;first,why the pattern of education becomes so dread ful and tedious which call s for the students to distract and second, why cant we cater to the students interests and inclinations so that they are provided room to choose the lecture they want to attend?Mobile phones are just the present and a lame excuse for ignorance,we need to find the root cause and address it prooperly rather than to contemplate over its complete ban or usage. However, a partial ban like prohibiting its use during the class hours and allowing only after it, seems a temporary but an effective solution as per the need of the hour.

Cement Insudtry Overview Last 49 Years Essay Example

Cement Insudtry Overview Last 49 Years Essay Example Cement Insudtry Overview Last 49 Years Essay Cement Insudtry Overview Last 49 Years Essay Bangladesh 40 years on Introduction Last year Bangladesh celebrated its 40th birthday. Possibly a celebration for some but more likely, for others, the occasion brought back terrible memories of suffering and hardship. This country of fertile plains, luscious terrain, with its remarkably rich history and heritage, was born in 1971 following a bitter struggle for independence that claimed the lives of over 3  million people. The birth pains linger; there is much poverty and many challenges lie ahead, but there are also expectations for better things to come through foreign direct investment (FDI) and infrastructure development. Meeting infrastructure needs Last year, the International Monetary Fund (IMF) indicated that Bangladesh’s economy had become the 48th largest in the world. The UK Investors Chronicle has identified Bangladesh as one of the world’s seven hottest emerging markets due to its relatively stable currency with solid foreign reserves and record foreign remittances, as well as 6. 7% real growth rate in 2011. The Bangladesh government has set itself the challenge to transform into a middle income country by 2021. In line with this strategic vision, the government has undertaken massive programmes for infrastructure development in partnership with the private sector. As the government allows 100% FDI, the infrastructure sector offers an interesting mix of opportunities for overseas interests. In October 2011, Bangladesh and the ADB announced a US$4. 5 billion five-year Country Partnership Strategy (CPS), which will include an investment programme of about US$4. 5 billion for 2011 – 15. ADB’s support will be focused on six sectors: energy, transport, urban development, education, agriculture, and natural resources and finance. In the energy sector, ADB will aim to enhance access to power, to improve energy efficiency and to develop a policy and regulatory setting conducive to private sector participation. In transport, ADB’s assistance will be targeted at better road and railway infrastructure for fostering higher growth, and support for environmentally friendly modes of transport. To accelerate growth, the CPS will prioritise private sector development by addressing major infrastructure constraints and skills gaps. Building for the future In February, transport expert, M. Rahmatullah, said that Bangladesh could earn about US$44 million pa by providing a transit facility to India and its neighbours over the next five years while developing the infrastructure for this facility. If the infrastructure was ready in five years, the country could earn US$0. 5 billion from the sixth year and US$1  billion from the sixteenth. He said: â€Å"For Bangladesh, transit will open up new avenues of opportunities. It will make out a case for India and China investing in deep-sea port facilities in the country. Some 16 million t of cargo would possibly move between the northeastern Indian states and the rest of the country. Bangladesh would require US$7 billion over the next decade to develop its transport system, including roads, rails and waterways for the transit system to be in place. As might have been expected, these comments were met with a degree of derision and cynicism in some sectors, but with welc ome comments in others. Whatever the outcome of talks surrounding this and other projects, the construction industry in Bangladesh is currently booming. This is due to housing, industrial and infrastructure demand,† says Mehedy Amin, Technical Director, Development Constructions Ltd. â€Å"We expect this demand to stay on due to the high population and expanding middle class society. † Cement production increases Mehedy Amin is predicting some problems in the future, especially regarding cement prices. â€Å"The country imports most of its clinker from abroad and with the increasing value of the US$ against local currency, the price of cement is rocketing up along with most construction materials. In January 2012, Bangladesh’s Export Promotion Bureau released data confirming that cement exports had witnessed a 21% increase in the first seven months of the current fiscal year (July 2011 – January 2012). Abdul Khaleq Parvez, Vice President of the Bangladesh Cement Manufacturers Association, commenting on the export situation said: â€Å"The export market is growing slowly as the prices of local cement increased sharply following devaluation of the local currency. Cement prices have increased by at least US$17/t†. The prices rose because of the sudden rise in production costs, this being a consequence of power shortages and a rise in labour wages. Shankar Kumar Roy, General Manager, Business Development, Holcim Bangladesh, told WORLD CEMENT that in 2011 there were 45 active cement companies in the country. â€Å"Cement demand was 14 million t, while capacity reached 24 million t and exports totalled 250 000 t†. It is said that cement production has boomed in Bangladesh since the late 1980s, with many cement plants springing up across the country. New projects Shun Shing Group International Ltd (SSGIL) has developed into a successful bulk commodity trading, shipping and investment company. A landmark investment took place in 2001 when it established a 0. 5  million t cement grinding mill in Kaligoni in Bangladesh. By the end of 2012, SSGIL’s cement production will be 3. 1 million t through increased capacity at the current site and a new plant in Khulna city, to cover the southwest market. In January of this year, HeidelbergCement officially inaugurated a new cement mill at its plant at the seaport of Chittagong. The project involved the installation of a cement grinding mill with a capacity of 105 tph, and a slag dryer with a capacity of 45 tph. HeidelbergCement has been active in Bangladesh since 1998 and is one of the largest German investors in the country. In addition to the grinding plant at Chittagong, the Group operates another grinding plant in Dhaka. Bashundhara Cement, part of the major Bashundhara Group, is currently building a 7000 tpd plant in Narayaganij. Meghna Cement, also part of the Bashundhara Group, together with Bashundhara Cement will jointly manufacture 13 500 tpd of cement, equating to 15 – 18% of cement demand in the country. In July 2011, India’s Supreme Court granted permission for Lafarge Surma Cement to resume mining limestone in the East Khasi Hills in Meghalaya state in the country’s mineral-rich northeast. The limestone is transported from Meghalaya to Lafarge Umiam Mining Pvt Ltd by a 17 km conveyor belt, where it feeds the company’s cement plant at Chhatask in Bangladesh. In February 2010 the court halted Lafarge from extracting the limestone as it was mining in an environmentally sensitive zone. India’s environment ministry told the court in April that it had cleared the mining project with strict conditions. Up to then it was reported that Lafarge had been importing clinker from abroad. The original agreement between India and Bangladesh to permit the cross-border industrial project was signed in November 2000. It was financed by Lafarge, Cementos Molins, the IFC, the ADB, German Development Bank, the European Investment Bank and the Netherlands Development Co. Unique Cement Industries Ltd. : Unique cement industries ltd established in the year 2002. The factory is built with modern machinery imported from Germany and China with production capacity of 1800 M/T per day. Unique cement industries ltd. as ISO 9001:2000 Certificate. They have two brands of cement in the local market namely FRESH and MEGHNACEM. Holcim (Bangladesh) Ltd. : Holcim (Bangladesh) Ltd started its operation in this country with of the acquisition of the-then Hyundai cement. Subsequently it acquired United Cement and Saiham Cement. Holcim (Bangladesh) Ltd is affiliated with the Holcim Group worldwide and is one the lar gest multinational cement producers in the world with manufacturing in over 70 countries. The group has a produrtion capacity of mor than 120 million tones of cement per year. MTC Cement Industries Ltd. MTC Cement Industries Ltd established with the tehnical co-operation of CITIC engineering of PRC in year of 1998 is situated on the embankment of the river Meghna. There is a two unit cement plant with capacity of 1200 MT per day. TIGER BRAND Cement started its commercial voyage on july 2001. Currently MTC is on an expansion program in pagla with a small 150 MT per day capacity cement grinding plant. Lafarge Surma Cement Ltd. : Lafarge/cement mills is setting up the only modern, integrated cement manufacturing plan known as Lafarge Surma Cement Ltd. in Bangladesh at Chattak under Sunamgonj district. The majority of Lafarge Surma Cement Ltd. Shareholding (60%) is held by a 50/50 joint venture company bewteen Lafarge and cementos molins. Founded in 1833, Lafarge operates in 75 countries, employing 77,000 people. In 2002, the group generated annual sales of Euro 14. 6 billion and globally holdstop ranking positions in Cement, Aggregates amp; Concrete, Roofing and Gypsum. Cementos Molins is a renowned spanish cement company with an annual revenue of Euro 485 million and net profit of Euro 70 million. Operating in Spain, Argentina, Uruguay and Mexico, it produces Portland and Calcium-Aluminate cement, Concrete and Precast concrete, Aggregates and Special purpose ortars. Lafarge Surma Cement Ltd. will extract and procss the basic raw materials like limestone and shale from its from its own quarry in Meghalaya, India. A 17 km crossborder belt conveyor will be installed to link the quarry with the cement plant for transportation of raw materials. A massive land filling and site development has been completed on the 90 acre plan t site. The construction and erection is also. The plant will initially produce 1. 2 millions tons of cement per year. Premier Cement Mills Ltd : Started its production in March, 2004, Premier is the second largest cement manufacturer in Bangladesh. With a total installed cement capacity of almost a million tons per year at Muktarpul, Munshiganj, the Company is recognized as a leading cement producer with abundant supply of raw materials, low production cost and an energy efficient operation. The Company currently employs 216 persons and has an extensive distribution system throughout the country. Its transportation subsidiary, with three prominent transport companies in Bangladesh, operate a large fleet of trucks to distribute cement products in bags almost anywhere in the country. The Company was founded in 2001 as the private cement producer in Bangladesh, with a factory in Muktarpul, Munshiganj. The Company started production in March, 2004 with Unit 1, which had an installed capacity of 730,000 tons of cement per year, and would be followed by Unit 2, also at 730,000 tons of cement per year, by the mid of 2005. The factory is equipped with world-class European technology built in Denmark and Germany. Within the span of first 5 months, the company has achieved the ISO 9000-2001 certification from TUV, with highly skilled employees.

Research Methods Essay Example | Topics and Well Written Essays - 2250 words - 1

Research Methods - Essay Example Management must be able to lead the employees through new techniques, which are based on the current market situations. The management must use different leadership traits so that the employees are easily able to adopt different strategies, which can help in the performance of the business. Finding an innovative idea for every problem can be a difficult task for all the management but it is essential for them to implement such ideas in the operational activities so that the production level of the employees increases which directly increases the profitability of the organization. From several studies it is observed that the role of leadership can create many changes in an organization and increase the efficiency of its employees. The importance of innovative management leads to innovative ideas. Different leadership styles help to implement the innovative ideas in the organizations and can enhance the performance of the employees. At the time of economic crisis, good leadership qualities are important to increase the performance of the organization (Cristina, 2013). There are mainly four types of leadership styles that could be observed in different organizations. The choice of leadership style depends upon the nature of business or objectives of the organization. The suitability of leadership style, therefore, varies in different industries. The aim of the proposed study is to compare different leadership styles and their traits and their impact on employees’ performance. It would be an interesting study to compare different leadership styles on employee performance in different organizations as it will allow the users of the report to identify and understand traits of different leadership styles and their role in motivating and committing employees to perform better. A comprehensive study would be possible by taking case studies of four different organizations that support two types of leadership including Transactional and

Devices and Practices for Sensory Impairments Coursework

Devices and Practices for Sensory Impairments - Coursework Example There are a number of devices and associated teaching practices that may aid students with sensory impairments in the classroom. The devices include: It also gets referred to as closed-circuit television, CCTV. It uses a video camera to display enlarged images or wordings on a monitor or television screen. It gets used by people affected with partial visual impairment. It helps them overcome reading and writing difficulties caused by visual impairment. CCTV gets manufactured in different shapes and sizes to aid any low vision needs. The video magnifier gets used in the classroom by the teacher to assist the partially visually impaired students to be able to see slide displays on the white board in class. By magnifying the images and words in the slide shows, the students are able to see clearly, and follow what becomes taught in class hence realizing their full academic potential (Farrell,2005). This device gets used by visually impaired students with low vision to assist them in their class work. The students are adventitious visually impaired and can access their visual memory to develop conceptual understanding. The video magn ifier gets used by students with sensory impairments who have typical learning processes and learning modes: but whose ability to access information gets restricted in some avenues, or have a varying order of acquiring new skills. With this device, the student grasps more than 50 percent of what gets taught. As with a palm view display, their focus is on details, hence maximum absorption of the taught content. Use of effective teaching practices help in additional benefits as the students focus on the detailed description by the teacher as opposed to vague description by the teacher. Printing the reading materials in alternative formats prior to the classes also assists the student since through the use of the video magnifier, they are able to

Search Engine Optimization Research Paper Example | Topics and Well Written Essays - 750 words

Search Engine Optimization - Research Paper Example This is to mean that, white hats use terms appropriately to ensure that their websites are visible. On the other hand, black fill their websites with content or words that get plenty of hits from search engines. White hats, when compared to black hats have distinct characteristics that put them apart in favor or against one another as one of the uses unscrupulous means and makes attractive promises (Creative Momentum 1). In relation to white hat search engine optimization, it follows regulations and guidelines to the letter, as provided by search engines to ensure that websites are visible to all that require information from them. This includes careful use of words that get numerous hits from search engines such that the words used are not meant to bloat documents or articles in the website. Instead, the words used are of a unique nature in that they are informative and, at times, act as support words for the whole article and not for exploiting the abilities of search engines. As s uch, websites are designed with certain aspects in mind; these include rules and norms, as well as a code of ethics to ensure that all internet activities are conducted with transparency. Based on this, following the guidelines of search engines for optimizing visibility, ensures that the ever-changing algorithms applied by search engines (Revenuewire 2) achieve transparency. This shields legal or appropriate sites from relegation, and thus gets high ratings by following meeting the terms of use on multiple levels. The white hat optimizers or designers, therefore, apply to the intelligence and needs of internet users to deliver quality content that does not fool search engines by giving false information, including in the titles of the websites. In relation to domain naming, white hat optimizers allow the actual intent of the website to appear rather than mislead the search engine user into logging into it for irrelevant content. These are the distinct characteristics of â€Å"whit e hat† search engine optimization due to their compliant nature, which offers protection from removal and relegation. On the other hand, black hat search engine optimizers have their own code of ethics, or lack of it thereof that sees them dump the rulebook and carry the day, but only for limited moment (Smith 5). Black hat optimization in search engines involves the application of hidden content, where there are numerous links and articles, as well as documents that are spammed with keywords, which serve as crucial gateway points for search engines. This is in relation to search engines accessing the site due to its heavy saturation with such words that are mainly used by internet users to query information from the internet. Information is usually hidden in scripts and non-script parts of code in a website, where search engines only expose it as its algorithms crawl the internet. In addition black hat optimizations tends to have meta-keyword stuffing, where in the descriptio n of the website, or even in its headers, it has numerous keywords (Wilding). These words raise the flags, both red and white for search engines thus improving the ranking of a website, especially in marketing and sites that market content to generate revenue. Through this, it is evident that black hat optimizers are only

Relationship Marketing Through a Number of Pathways Research Paper

Relationship Marketing Through a Number of Pathways - Research Paper Example Citigroup’s relationship managers have realized that the Company met all these three aspects. First of all, the Company offers both investment and commercial services which means that clients have a lot of services at their disposal. Some of them include; Mortgages, priority banking for high net worth clients, loans, investment banking, telephone banking and card products. Secondly, clients in the banking sector are in continuous need of these services. Lastly, those customers who decide to do business with the Company normally select one service or product. In the case of Citigroup, some customers strictly come to obtain loans, some would like to save their money there but access it conveniently when the need arises (commercial services and care facilities). The organization has implemented relationship marketing through consumer tracking. Since Citigroup is B2B backed, then it was able to use a comprehensive database to analyze what consumer tastes and preferences are. It ha s been a leader in business communication with the client. Citigroup has been asking its clients about their thoughts on the institution. It found that certain services were preferred over others. It also realized that consumer kept coming back for certain products during definite seasons. It was able to establish a pattern and focused its energies on products that gave them maximum returns. This was also topped up by improving services that clients were dissatisfied with. One such service was the provision of housing loans. The Company found out that many clients were happy with their rate of loan processing.

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.