Search results for: context based coordination

Authors: Vishal Raj, Noorhan Abbas

Abstract:

Ambiguity in NLP (Natural Language Processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a method to create an affinity matrix to calculate the affinity between any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an algorithm to create the sense clusters of tokens using affinity matrix under hierarchy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contextual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and challenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: Word Sense Disambiguation, WSD, Contextual SenSe Model, Most Frequent Sense, part of speech, POS, Natural Language Processing, NLP, OOV, out of vocabulary, ELMo, Embeddings from Language Model, BERT, Bidirectional Encoder Representations from Transformers, Word2Vec, lemma_POS, Algorithm.

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Authors: J. K. Alhassan, S. A. Lawal

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This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.

Keywords: Decision tree, classification, data mining, scholarship.

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Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Inderpreet Kaur, Birinderjit S. Kalyan

Abstract:

This work is a proposed model of CMOS for which the algorithm has been created and then the performance evaluation of this proposition has been done. In this context, another commonly used model called ZSTT (Zero Switching Time Transient) model is chosen to compare all the vital features and the results for the Proposed Equivalent CMOS are promising. In the end, the excerpts of the created algorithm are also included

Keywords: Dual Capacitor Model, ZSTT, CMOS, SPICEMacro-Model.

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Authors: Kyoung-jae Kim

Abstract:

Recommender systems are usually regarded as an important marketing tool in the e-commerce. They use important information about users to facilitate accurate recommendation. The information includes user context such as location, time and interest for personalization of mobile users. We can easily collect information about location and time because mobile devices communicate with the base station of the service provider. However, information about user interest can-t be easily collected because user interest can not be captured automatically without user-s approval process. User interest usually represented as a need. In this study, we classify needs into two types according to prior research. This study investigates the usefulness of data mining techniques for classifying user need type for recommendation systems. We employ several data mining techniques including artificial neural networks, decision trees, case-based reasoning, and multivariate discriminant analysis. Experimental results show that CHAID algorithm outperforms other models for classifying user need type. This study performs McNemar test to examine the statistical significance of the differences of classification results. The results of McNemar test also show that CHAID performs better than the other models with statistical significance.

Keywords: Customer need type, Data mining techniques, Recommender system, Personalization, Mobile user.

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Authors: Susmitha Vekkot, Pancham Shukla

Abstract:

In this paper, we focus on the fusion of images from different sources using multiresolution wavelet transforms. Based on reviews of popular image fusion techniques used in data analysis, different pixel and energy based methods are experimented. A novel architecture with a hybrid algorithm is proposed which applies pixel based maximum selection rule to low frequency approximations and filter mask based fusion to high frequency details of wavelet decomposition. The key feature of hybrid architecture is the combination of advantages of pixel and region based fusion in a single image which can help the development of sophisticated algorithms enhancing the edges and structural details. A Graphical User Interface is developed for image fusion to make the research outcomes available to the end user. To utilize GUI capabilities for medical, industrial and commercial activities without MATLAB installation, a standalone executable application is also developed using Matlab Compiler Runtime.

Keywords: Filter mask, GUI, hybrid architecture, image fusion, Matlab Compiler Runtime, wavelet transform.

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Authors: K. Prasertwong, N. Mithulananthan

Abstract:

This paper investigates and compares performance of various conventional and fuzzy logic based controllers at generator locations for oscillation damping. Performance of combination of conventional and fuzzy logic based controllers also studied by comparing overshoot on the active power deviation response for a small disturbance and damping ratio of the critical mode. Fuzzy logic based controllers can not be modeled in the state space form to get the eigenvalues and corresponding damping ratios of various modes of generators and controllers. Hence, a new method based on tracing envelop of time domain waveform is also presented and used in the paper for comparing performance of controllers. The paper also shows that if the fuzzy based controllers designed separately combining them could not lead to a better performance.

Keywords: Automatic voltage regulator, damping ratio, fuzzylogic controller, power system stabilizer.

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Authors: Lai-Man Po, Chi-Wang Ting, Ka-Ho Ng

Abstract:

Recently, an enhanced hexagon-based search (EHS) algorithm was proposed to speedup the original hexagon-based search (HS) by exploiting the group-distortion information of some evaluated points. In this paper, a second version of the EHS is proposed with a new point-oriented inner search technique which can further speedup the HS in both large and small motion environments. Experimental results show that the enhanced hexagon-based search version-2 (EHS2) is faster than the HS up to 34% with negligible PSNR degradation.

Keywords: Inner search, fast motion estimation, block-matching, hexagon search

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Authors: Sevil Igit, Merve Meric, Sarp Erturk

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In this paper, it is proposed to improve Daisy Descriptor based face recognition using a novel One-Bit Transform (1BT) based pre-registration approach. The 1BT based pre-registration procedure is fast and has low computational complexity. It is shown that the face recognition accuracy is improved with the proposed approach. The proposed approach can facilitate highly accurate face recognition using DAISY descriptor with simple matching and thereby facilitate a low-complexity approach.

Keywords: Face Recognition, Daisy Descriptor, One-Bit Transform, Image Registration.

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Authors: Chein-Shung Hwang, Ruei-Siang Fong

Abstract:

User-based Collaborative filtering (CF), one of the most prevailing and efficient recommendation techniques, provides personalized recommendations to users based on the opinions of other users. Although the CF technique has been successfully applied in various applications, it suffers from serious sparsity problems. The cloud-model approach addresses the sparsity problems by constructing the user-s global preference represented by a cloud eigenvector. The user-based CF approach works well with dense datasets while the cloud-model CF approach has a greater performance when the dataset is sparse. In this paper, we present a hybrid approach that integrates the predictions from both the user-based CF and the cloud-model CF approaches. The experimental results show that the proposed hybrid approach can ameliorate the sparsity problem and provide an improved prediction quality.

Keywords: Cloud model, Collaborative filtering, Hybridrecommender system

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Authors: Wernhuar Tarng, Weichian Tsai

Abstract:

The major purpose of this study is to use network and multimedia technologies to build a game-based learning system for junior high school students to apply in learning “World Geography" through the “role-playing" game approaches. This study first investigated the motivation and habits of junior high school students to use the Internet and online games, and then designed a game-based learning system according to situated and game-based learning theories. A teaching experiment was conducted to analyze the learning effectiveness of students on the game-based learning system and the major factors affecting their learning. A questionnaire survey was used to understand the students- attitudes towards game-based learning. The results showed that the game-based learning system can enhance students- learning, but the gender of students and their habits in using the Internet have no significant impact on learning. Game experience has a significant impact on students- learning, and the higher the experience value the better the effectiveness of their learning. The results of questionnaire survey also revealed that the system can increase students- motivation and interest in learning "World Geography".

Keywords: Game-based learning, situated learning, role playing, learning effectiveness, learning motivation.

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Authors: Renkai Wang, Tingcun Wei

Abstract:

In this paper, a digital control algorithm based on delta-operator is presented for high-frequency digitally-controlled DC-DC switching converters. The stability and the controlling accuracy of the DC-DC switching converters are improved by using the digital control algorithm based on delta-operator without increasing the hardware circuit scale. The design method of voltage compensator in delta-domain using PID (Proportion-Integration- Differentiation) control is given in this paper, and the simulation results based on Simulink platform are provided, which have verified the theoretical analysis results very well. It can be concluded that, the presented control algorithm based on delta-operator has better stability and controlling accuracy, and easier hardware implementation than the existed control algorithms based on z-operator, therefore it can be used for the voltage compensator design in high-frequency digitally- controlled DC-DC switching converters.

Keywords: Digitally-controlled DC-DC switching converter, finite word length, control algorithm based on delta-operator, high-frequency, stability.

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Authors: Hamed Rafiei, Masoud Rabbani

Abstract:

This paper addresses one of the most important issues have been considered in hybrid MTS/MTO production environments. To cope with the problem, a mathematical programming model is applied from a tactical point of view. The model is converted to a fuzzy goal programming model, because a degree of uncertainty is involved in hybrid MTS/MTO context. Finally, application of the proposed model in an industrial center is reported and the results prove the validity of the model.

Keywords: Fuzzy sets theory, Hybrid MTS/MTO, Order penetration point, Quadratic programming.

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Authors: Nureni O. Adeboye, Dawud A. Agunbiade

Abstract:

This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.

Keywords: Audit fee, heteroscedasticity, Lagrange multiplier test, periodicity.

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Authors: Mohammad Darzi, Ali AsgharLiaei, Mahdi Hosseini, HabibollahAsghari

Abstract:

This article addresses feature selection for breast cancer diagnosis. The present process contains a wrapper approach based on Genetic Algorithm (GA) and case-based reasoning (CBR). GA is used for searching the problem space to find all of the possible subsets of features and CBR is employed to estimate the evaluation result of each subset. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer (WDBC) dataset.

Keywords: Case-based reasoning; Breast cancer diagnosis; Genetic algorithm; Wrapper feature selection

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Authors: Chiung-Hui Chen

Abstract:

With advancements in science and technology, the concept of the Internet of Things (IoT) has gradually developed. The development of the intelligent environment adds intelligence to objects in the living space by using the IoT. In the smart environment, when multiple users share the living space, if different service requirements from different users arise, then the context-aware system will have conflicting situations for making decisions about providing services. Therefore, the purpose of establishing a communication and negotiation mechanism among objects in the intelligent environment is to resolve those service conflicts among users. This study proposes developing a decision-making methodology that uses “Event Agents” as its core. When the sensor system receives information, it evaluates a user’s current events and conditions; analyses object, location, time, and environmental information; calculates the priority of the object; and provides the user services based on the event. Moreover, when the event is not single but overlaps with another, conflicts arise. This study adopts the “Multiple Events Correlation Matrix” in order to calculate the degree values of incidents and support values for each object. The matrix uses these values as the basis for making inferences for system service, and to further determine appropriate services when there is a conflict.

Keywords: Internet of things, intelligent object, event agents, negotiation mechanism, degree of similarity.

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Authors: Mohamed Ali AlShaari, Khalid M. ElFitori

Abstract:

In the field of Quran Studies known as GHAREEB AL QURAN (The study of the meanings of strange words and structures in Holy Quran), it is difficult to distinguish some pragmatic meanings from conceptual meanings. One who wants to study this subject may need to look for a common usage between any two words or more; to understand general meaning, and sometimes may need to look for common differences between them, even if there are synonyms (word sisters).

Some of the distinguished scholars of Arabic linguistics believe that there are no synonym words, they believe in varieties of meaning and multi-context usage. Based on this viewpoint, our method was designedto look for synonyms of a word, then the differences that distinct the word and their synonyms.

There are many available books that use such a method e.g. synonyms books, dictionaries, glossaries, and some books on the interpretations of strange vocabulary of the Holy Quran, but it is difficult to look up words in these written works.

For that reason, we proposed a logical entity, which we called Differences Matrix (DM).

DM groups the synonyms words to extract the relations between them and to know the general meaning, which defines the skeleton of all word synonyms; this meaning is expressed by a word of its sisters.

In Differences Matrix, we used  the sisters(words) as titles for rows and columns, and in the obtained  cells we tried to define the row title (word) by using column title (her sister), so the relations between sisters appear, the expected result is well defined groups of sisters for each word. We represented the obtained results formally, and used the defined groups as a base for building the ontology of the Holy Quran synonyms.

Keywords: Quran, synonyms, Differences Matrix, ontology

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Authors: A. Knezović

Abstract:

21st century has transformed the labor market landscape in a way of posing new and different demands on university graduates as well as university lecturers, which means that the knowledge and academic skills students acquire in the course of their studies should be applicable and transferable from the higher education context to their future professional careers. Given the context of the Languages for Specific Purposes (LSP) classroom, the teachers’ objective is not only to teach the language itself, but also to prepare students to use that language as a medium to develop generic skills and competences. These include media and information literacy, critical and creative thinking, problem-solving and analytical skills, effective written and oral communication, as well as collaborative work and social skills, all of which are necessary to make university graduates more competitive in everyday professional environments. On the other hand, due to limitations of time and large numbers of students in classes, the frequently topic-centered syllabus of LSP courses places considerable focus on acquiring the subject matter and specialist vocabulary instead of sufficient development of skills and competences required by students’ prospective employers. This paper intends to explore some of those issues as viewed both by LSP lecturers and by business professionals in their respective surveys. The surveys were conducted among more than 50 LSP lecturers at higher education institutions in Croatia, more than 40 HR professionals and more than 60 university graduates with degrees in economics and/or business working in management positions in mainly large and medium-sized companies in Croatia. Various elements of LSP course content have been taken into consideration in this research, including reading and listening comprehension of specialist texts, acquisition of specialist vocabulary and grammatical structures, as well as presentation and negotiation skills. The ability to hold meetings, conduct business correspondence, write reports, academic texts, case studies and take part in debates were also taken into consideration, as well as informal business communication, business etiquette and core courses delivered in a foreign language. The results of the surveys conducted among LSP lecturers will be analyzed with reference to what extent those elements are included in their courses and how consistently and thoroughly they are evaluated according to their course requirements. Their opinions will be compared to the results of the surveys conducted among professionals from a range of industries in Croatia so as to examine how useful and important they perceive the same elements of the LSP course content in their working environments. Such comparative analysis will thus show to what extent the syllabi of LSP courses meet the demands of the employment market when it comes to the students’ language skills and competences, as well as transferable skills. Finally, the findings will also be compared to the observations based on practical teaching experience and the relevant sources that have been used in this research. In conclusion, the ideas and observations in this paper are merely open-ended questions that do not have conclusive answers, but might prompt LSP lecturers to re-evaluate the content and objectives of their course syllabi.

Keywords: Languages for specific purposes (LSP), language skills, topic-centered syllabus, transferable skills.

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Authors: Rohit Gupta, Ruchika

Abstract:

In this paper, a PSO based fractional order PID (FOPID) controller is proposed for concentration control of an isothermal Continuous Stirred Tank Reactor (CSTR) problem. CSTR is used to carry out chemical reactions in industries, which possesses complex nonlinear dynamic characteristics. Particle Swarm Optimization algorithm technique, which is an evolutionary optimization technique based on the movement and intelligence of swarm is proposed for tuning of the controller for this system. Comparisons of proposed controller with conventional and fuzzy based controller illustrate the superiority of proposed PSO-FOPID controller.

Keywords: CSTR, Fractional Order PID Controller, Partical Swarm Optimization.

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Authors: D. Geringswald, B. Hintze

Abstract:

The miniaturization of circuits is advancing. During chip manufacturing, structures are filled for example by metal organic chemical vapor deposition (MOCVD). Since this process reaches its limits in case of very high aspect ratios, the use of alternatives such as the atomic layer deposition (ALD) is possible, requiring the extension of existing coating systems. However, it is an unsolved question to what extent MOCVD can achieve results similar as an ALD process. In this context, this work addresses the characterization of a metal organic vapor deposition of titanium nitride. Based on the current state of the art, the film properties coating thickness, sheet resistance, resistivity, stress and chemical composition are considered. The used setting parameters are temperature, plasma gas ratio, plasma power, plasma treatment time, deposition time, deposition pressure, number of cycles and TDMAT flow. The derived process instructions for unstructured wafers and inside a structure with high aspect ratio include lowering the process temperature and increasing the number of cycles, the deposition and the plasma treatment time as well as the plasma gas ratio of hydrogen to nitrogen (H₂:N₂). In contrast to the current process configuration, the deposited titanium nitride (TiN) layer is more uniform inside the entire test structure. Consequently, this paper provides approaches to employ the MOCVD for structures with increasing aspect ratios.

Keywords: ALD, high aspect ratio, PE-MOCVD, TiN.

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Authors: Mussarat Abdullah, Fazal Wahab

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Data hiding into text documents itself involves pretty complexities due to the nature of text documents. A robust text watermarking scheme targeting an object based environment is presented in this research. The heart of the proposed solution describes the concept of watermarking an object based text document where each and every text string is entertained as a separate object having its own set of properties. Taking advantage of the z-ordering of objects watermark is applied with the z-axis letting zero fidelity disturbances to the text. Watermark sequence of bits generated against user key is hashed with selected properties of given document, to determine the bit sequence to embed. Bits are embedded along z-axis and the document has no fidelity issues when printed, scanned or photocopied.

Keywords: Digital Watermarking, Object Based Environment, Watermark, z-ordering.

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Authors: Mohammed Nafie

Abstract:

Decision Feedback equalizers (DFEs) usually outperform linear equalizers for channels with intersymbol interference. However, the DFE performance is highly dependent on the availability of reliable past decisions. Hence, in coded systems, where reliable decisions are only available after decoding the full block, the performance of the DFE will be affected. A symbol based DFE is a DFE that only uses the decision after the block is decoded. In this paper we derive the optimal settings of both the feedforward and feedback taps of the symbol based equalizer. We present a novel symbol based DFE filterbank, and derive its taps optimal settings. We also show that it outperforms the classic DFE in terms of complexity and/or performance.

Keywords: Coding, DFE, Equalization, Exponential Channelmodels.

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Authors: O. F. Elkommos

Abstract:

“Humour studies” is an interdisciplinary research area that is relatively recent. It interests researchers from the disciplines of psychology, sociology, medicine, nursing, in the work place, gender studies, among others, and certainly teaching, language learning, linguistics, and literature. Linguistic theories of humour research are numerous; some of which are of interest to the present study. In spite of the fact that humour courses are now taught in universities around the world in the Egyptian context it is not included. The purpose of the present study is two-fold: to review the state of arts and to show how linguistic theories of humour can be possibly used as an art and craft of teaching and of learning in EFL literature classes. In the present study linguistic theories of humour were applied to selected literary texts to interpret humour as an intrinsic artistic communicative competence challenge. Humour in the area of linguistics was seen as a fifth component of communicative competence of the second language leaner. In literature it was studied as satire, irony, wit, or comedy. Linguistic theories of humour now describe its linguistic structure, mechanism, function, and linguistic deviance. Semantic Script Theory of Verbal Humor (SSTH), General Theory of Verbal Humor (GTVH), Audience Based Theory of Humor (ABTH), and their extensions and subcategories as well as the pragmatic perspective were employed in the analyses. This research analysed the linguistic semantic structure of humour, its mechanism, and how the audience reader (teacher or learner) becomes an interactive interpreter of the humour. This promotes humour competence together with the linguistic, social, cultural, and discourse communicative competence. Studying humour as part of the literary texts and the perception of its function in the work also brings its positive association in class for educational purposes. Humour is by default a provoking/laughter-generated device. Incongruity recognition, perception and resolving it, is a cognitive mastery. This cognitive process involves a humour experience that lightens up the classroom and the mind. It establishes connections necessary for the learning process. In this context the study examined selected narratives to exemplify the application of the theories. It is, therefore, recommended that the theories would be taught and applied to literary texts for a better understanding of the language. Students will then develop their language competence. Teachers in EFL/ESL classes will teach the theories, assist students apply them and interpret text and in the process will also use humour. This is thus easing students' acquisition of the second language, making the classroom an enjoyable, cheerful, self-assuring, and self-illuminating experience for both themselves and their students. It is further recommended that courses of humour research studies should become an integral part of higher education curricula in Egypt.

Keywords: ABTH, deviance, disjuncture, episodic, GTVH, humour competence, humour comprehension, humour in the classroom, humour in the literary texts, humour research linguistic theories, incongruity- resolution, isotopy-disjunction, jab line, longer text joke, narrative story line (macro-micro), punch line, six knowledge resource, SSTH, stacks, strands, teaching linguistics, teaching literature, TEFL, TESL.

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Authors: Zeinab Ghasemi, S. Amirhassan Monadjemi, Abbas Vafaei

Abstract:

This paper presents a comparative analysis of a new unsupervised PCA-based technique for steel plates texture segmentation towards defect detection. The proposed scheme called Variance Based Component Analysis or VBCA employs PCA for feature extraction, applies a feature reduction algorithm based on variance of eigenpictures and classifies the pixels as defective and normal. While the classic PCA uses a clusterer like Kmeans for pixel clustering, VBCA employs thresholding and some post processing operations to label pixels as defective and normal. The experimental results show that proposed algorithm called VBCA is 12.46% more accurate and 78.85% faster than the classic PCA.

Keywords: Principal Component Analysis; Variance Based Component Analysis; Defect Detection; Texture Segmentation.

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Authors: D. Hassell, D. De Focatiis

Abstract:

This paper presents work on the application of wiki based coursework for a fourth-year engineering module delivered as part of both a MEng and MSc programme in Chemical Engineering. The module was taught with an equivalent structure simultaneously on two separate campuses, one in the United Kingdom (UK) and one in Malaysia, and the subsequent results were compared. Student feedback was sought via questionnaires, with 45 respondents from the UK and 49 from Malaysia. Results include discussion on; perceived difficulty; student enjoyment and experiences; differences between MEng and MSc students; differences between cohorts on different campuses. The response of students to the use of wiki-based coursework was found to vary based on their experiences and background, with UK students being generally more positive on its application than those in Malaysia.

Keywords: Engineering education, student differences, student learning, web-based coursework.

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Authors: Omair Ghori, Anton Stadler, Stefan Wilk, Wolfgang Effelsberg

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Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection.

Keywords: Contrast analysis, early fire detection, video smoke detection, video surveillance.

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Authors: A.Muthuramalingam, S.Himavathi

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Space Vector Modulation (SVM) is an optimum Pulse Width Modulation (PWM) technique for an inverter used in a variable frequency drive applications. It is computationally rigorous and hence limits the inverter switching frequency. Increase in switching frequency can be achieved using Neural Network (NN) based SVM, implemented on application specific chips. This paper proposes a neural network based SVM technique for a Voltage Source Inverter (VSI). The network proposed is independent of switching frequency. Different architectures are investigated keeping the total number of neurons constant. The performance of the inverter is compared for various switching frequencies for different architectures of NN based SVM. From the results obtained, the network with minimum resource and appropriate word length is identified. The bit precision required for this application is identified. The network with 8-bit precision is implemented in the IC XCV 400 and the results are presented. The performance of NN based general purpose SVM with higher bit precision is discussed.

Keywords: NN based SVM, FPGA Implementation, LayerMultiplexing, NN structure and Resource Reduction, PerformanceEvaluation

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: Feature selection, multi-objective evolutionary computation, unsupervised classification, behavior assessment system for children.

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Authors: Costin Badica, Maria Ganzha, Maciej Gawinecki, Pawel Kobzdej, Marcin Paprzycki

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Recently, we have presented an initial implementation of a model agent-based e-commerce system, which utilized a simple price negotiation mechanism–English Auction. In this note we discuss how a Dutch Auction involving multiple units of a product can be included in our system. We present UML diagrams of agents involved in price negotiations and briefly discuss rule-based mechanism exemplifying Dutch Auction.

Keywords: e-commerce, rule-based price negotiation mechanism, Dutch Auction, agent system.

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Authors: T. N. Sindhu, M. Aslam

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A comprehensive Bayesian analysis has been carried out in the context of informative and non-informative priors for the shape parameter of the Burr type X distribution under different symmetric and asymmetric loss functions. Elicitation of hyperparameter through prior predictive approach is also discussed. Also we derive the expression for posterior predictive distributions, predictive intervals and the credible Intervals. As an illustration, comparisons of these estimators are made through simulation study.

Keywords: Credible Intervals, Loss Functions, Posterior Predictive Distributions, Predictive Intervals.

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Authors: Aurelie Aurilla Bechina Arntzen

Abstract:

The last decade has seen an early majority of people The last decade, the role of the of the information communication technologies has increased in improving the social and business life of people. Today, it is recognized that game could contribute to enhance virtual rehabilitation by better engaging patients. Our research study aims to develop a game based system enhancing cognitive and physical capabilities of elderly people. To this end, the project aims to develop a low cost hand held system based on existing game such as Wii, PSP, or Xbox. This paper discusses the concepts and requirements for developing such game for elderly people. Based on the requirement elicitation, we intend to develop a prototype related to sport and dance activities.

Keywords: Elderly people, Game based learning system, Health systems, rehabilitation

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