Search results for: Biomechanics and ergonomic approaches

Authors: Soichi Ogishima, Takeshi Hase, So Nakagawa, Yasuhiro Suzuki, Hiroshi Tanaka

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To understand life as biological system, evolutionary understanding is indispensable. Protein interactions data are rapidly accumulating and are suitable for system-level evolutionary analysis. We have analyzed yeast protein interaction network by both mathematical and biological approaches. In this poster presentation, we inferred the evolutionary birth periods of yeast proteins by reconstructing phylogenetic profile. It has been thought that hub proteins that have high connection degree are evolutionary old. But our analysis showed that hub proteins are entirely evolutionary new. We also examined evolutionary processes of protein complexes. It showed that member proteins of complexes were tend to have appeared in the same evolutionary period. Our results suggested that protein interaction network evolved by modules that form the functional unit. We also reconstructed standardized phylogenetic trees and calculated evolutionary rates of yeast proteins. It showed that there is no obvious correlation between evolutionary rates and connection degrees of yeast proteins.

Keywords: Protein interaction network, evolution, modularity, evolutionary rate, connection degrees.

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Authors: Kritsada Khongnomnan, Wittaya Poomipak, Yong Poovorawan, Sunchai Payungporn

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In this study, three subtypes of influenza A viruses (pH1N1, H5N1 and H3N2) which naturally infected human were analyzed by bioinformatic approaches to find candidate human cellular miRNAs targeting viral genomes. There were 76 miRNAs targeting influenza A viruses. Among these candidates, 70 miRNAs were subtypes specifically targeting each subtype of influenza A virus including 21 miRNAs targeted subtype H1N1, 27 miRNAs targeted subtype H5N1 and 22 miRNAs targeted subtype H3N2. The remaining 6 miRNAs target on multiple subtypes of influenza A viruses. Uniquely, hsa-miR-3145 is the only one candidate miRNA targeting PB1 gene of all three subtypes. Obviously, most of the candidate miRNAs are targeting on polymerase complex genes (PB2, PB1 and PA) of influenza A viruses. This study predicted potential human miRNAs targeting on different subtypes of influenza A viruses which might be useful for inhibition of viral replication and for better understanding of the interaction between virus and host cell.

Keywords: Human miRNAs, Influenza A viruses, H1N1, H5N1, H3N2

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Authors: K. Kusakana

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A hybrid energy system is a combination of renewable energy sources with back up, as well as a storage system used to respond to given load energy requirements. Given that the electrical output of each renewable source is fluctuating with changes in weather conditions, and since the load demand also varies with time; one of the main attributes of hybrid systems is to be able to respond to the load demand at any time by optimally controlling each energy source, storage and back-up system. The induced optimization problem is to compute the optimal operation control of the system with the aim of minimizing operation costs while efficiently and reliably responding to the load energy requirement. Current optimization research and development on hybrid systems are mainly focusing on the sizing aspect. Thus, the aim of this paper is to report on the state-of-the-art of optimal operation control of hybrid renewable energy systems. This paper also discusses different challenges encountered, as well as future developments that can help in improving the optimal operation control of hybrid renewable energy systems.

Keywords: Renewable energies, hybrid systems, optimization, operation control.

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Authors: Hossein Kabir, Mojtaba Sadeghi

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Nowadays, high-strength concrete is an integral element of a variety of high-rise buildings. On the other hand, finding a suitable aggregate size distribution is a great concern; hence, the concrete mix proportion is presented that has no coarse aggregate, which still withstands enough desirable strength. Nano Reactive Silica sand powder concrete (NRSSPC) is a type of concrete with no coarse material in its own composition. In this concrete, the only aggregate found in the mix design is silica sand powder with a size less than 150 mm that is infinitesimally small regarding the normal concrete. The research aim is to find the compressive strength of this particular concrete under the applied different conditions of curing and consolidation to compare the approaches. In this study, the young concrete specimens were compacted with a pressing or vibrating process. It is worthwhile to mention that in order to show the influence of temperature in the curing process, the concrete specimen was cured either in 20 ⁰C lime water or autoclaved in 90 ⁰C oven.

Keywords: Nano reactive silica sand powder concrete, consolidation, compressive strength, normal curing, thermal accelerated curing.

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Authors: Nannan Zong, Manicka Dhanasekar

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The effect of the discontinuity of the rail ends and the presence of lower modulus insulation material at the gap to the variations of stresses in the insulated rail joint (IRJ) is presented. A three-dimensional wheel – rail contact model in the finite element framework is used for the analysis. It is shown that the maximum stress occurs in the subsurface of the railhead when the wheel contact occurs far away from the rail end and migrates to the railhead surface as the wheel approaches the rail end; under this condition, the interface between the rail ends and the insulation material has suffered significantly increased levels of stress concentration. The ratio of the elastic modulus of the railhead and insulation material is found to alter the levels of stress concentration. Numerical result indicates that a higher elastic modulus insulating material can reduce the stress concentration in the railhead but will generate higher stresses in the insulation material, leading to earlier failure of the insulation material

Keywords: Rail end, material interface, wheel-rail contact, stress, finite element method

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Authors: Ich Long Ngo, Dinh Tai Dang, Ngoc Tu Nguyen, Minh Duc Nguyen

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This paper describes an investigation on designing and enhancing the performance of H-Darrieus Wind Turbine (HDWT) of 10 kW at the medium wind speed. The aerodynamic characteristics of this turbine were investigated by both theoretical and numerical approaches. The optimal design procedure was first proposed to enhance the power coefficient under various effects, such as airfoil type, number of blades, solidity, aspect ratio, and tip speed ratio. As a result, the overall design of the 10 kW HDWT was well achieved, and the power characteristic of this turbine was found by numerical approach. Additionally, the maximum power coefficient predicted is up to 0.41 at the tip speed ratio of 3.7 and wind speed of 8 m/s. Particularly, a generalized correlation of power coefficient with tip speed ratio and wind speed is first proposed. These results obtained are very useful for enhancing the performance of the HDWTs placed in a country with high wind power potential like Vietnam.

Keywords: Computational Fluid Dynamics, double multiple stream tube, H-Darrieus wind turbine, renewable energy.

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Authors: Mohammed A. Gharawi, Majed M. Khoja

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This paper is a report on the findings of a study conducted at the Institute of Public Administration (IPA) in Saudi Arabia. The paper applied both qualitative and quantitative approaches to assess the levels of basic computer applications’ skills among students enrolled in the preparatory programs of the institution. Qualitative data have been collected from semi-structured interviews with the instructors who have previously been assigned to teach Introduction to information technology courses. Quantitative data were collected by executing a self-report questionnaire and a written statistical test. Three hundred eighty enrolled students responded to the questionnaire and one hundred forty two accomplished the statistical test. The results indicate the lack of necessary skills to deal with computer applications among most of the students who are enrolled in the IPA’s preparatory programs.

Keywords: Assessment, Computer Applications, Computer Literacy, Institute of Public Administration, Saudi Arabia.

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Authors: Panagiotis Kosmas, Panayiotis Zaphiris

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Embodied Cognition (EC) as a learning paradigm is based on the idea of an inseparable link between body, mind, and environment. In recent years, the advent of theoretical learning approaches around EC theory has resulted in a number of empirical studies exploring the implementation of the theory in education. This systematic literature overview identifies the mainstream of EC research and emphasizes on the implementation of the theory across learning environments. Based on a corpus of 43 manuscripts, published between 2013 and 2017, it sets out to describe the range of topics covered under the umbrella of EC and provides a holistic view of the field. The aim of the present review is to investigate the main issues in EC research related to the various learning contexts. Particularly, the study addresses the research methods and technologies that are utilized, and it also explores the integration of body into the learning context. An important finding from the overview is the potential of the theory in different educational environments and disciplines. However, there is a lack of an explicit pedagogical framework from an educational perspective for a successful implementation in various learning contexts.

Keywords: Embodied cognition, embodied learning, education, technology, schools.

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Authors: K. Khlifi, A. Haddouk, M. Hlaili, H. Mechergui

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The present paper provides a detailed analysis of prior methods and approaches for non-linear load identification in residential buildings. The main goal of this analysis is to decipher the distorted signals and to estimate the harmonics influence on power systems. We have performed an analytical study of non-linear loads behavior in the residential environment. Simulations have been performed in order to evaluate the distorted rate of the current and follow his behavior. To complete this work, an instrumental platform has been realized to carry out practical tests on single-phase non-linear loads which illustrate the current consumption of some domestic appliances supplied with single-phase sinusoidal voltage. These non-linear loads have been processed and tracked in order to limit their influence on the power grid and to reduce the Joule effect losses. As a result, the study has allowed to identify responsible circuits of harmonic pollution.

Keywords: Distortion rate, harmonic analysis, harmonic pollution, non-linear load, power factor.

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Authors: Hassan Haleh, Zohreh Nasiri, Parisa Farahpour

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During recent years, the traditional learning approaches have undergone fundamental changes due to the emergence of new technologies such as multimedia, hypermedia and telecommunication. E-learning is a modern world phenomenon that has come into existence in the information age and in a knowledgebased society. E-learning has developed significantly within a short period of time. Thus it is of a great significant to secure information, allow a confident access and prevent unauthorized accesses. Making use of individuals- physiologic or behavioral (biometric) properties is a confident method to make the information secure. Among the biometrics, fingerprint is more acceptable and most countries use it as an efficient methods of identification. This article provides a new method to compare the fingerprint comparison by pattern recognition and image processing techniques. To verify fingerprint, the shortest distance method is used together with perceptronic multilayer neural network functioning based on minutiae. This method is highly accurate in the extraction of minutiae and it accelerates comparisons due to elimination of false minutiae and is more reliable compared with methods that merely use directional images.

Keywords: Fingerprint, minutiae, extraction of properties, multilayer neural network

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Authors: Sivapalan, S., Subramaniam, G., Clifford, M.J., Balbir Singh, M.S., Abdullah, A

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Higher education has an important role to play in advocating environmentalism. Given this responsibility, the goal of higher education should therefore be to develop graduates with the knowledge, skills and values related to environmentalism. However, research indicates that there is a lack of consciousness amongst graduates on the need to be more environmentally aware, especially when it comes to applying the appropriate knowledge and skills related to environmentalism. Although institutions of higher learning do include environmental parameters within their undergraduate and postgraduate academic programme structures, the environmental boundaries are usually confined to specific engineering majors within an engineering programme. This makes environmental knowledge, skills and values exclusive to certain quarters of the higher education system. The incorporation of environmental literacy within higher education institutions as a whole is of utmost pertinence if a nation-s human capital is to be nurtured to become change agents for the preservation of environment. This paper discusses approaches that can be adapted by institutions of higher learning to include environmental literacy within the graduate-s higher learning experience.

Keywords: Higher education, engineering education, environmental literacy, Malaysia.

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Authors: Jain-Shing Liu

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In this paper, we present a matrix game-theoretic cross-layer optimization formulation to maximize the network lifetime in wireless ad hoc networks with network coding. To this end, we introduce a cross-layer formulation of general NUM (network utility maximization) that accommodates routing, scheduling, and stream control from different layers in the coded networks. Specifically, for the scheduling problem and then the objective function involved, we develop a matrix game with the strategy sets of the players corresponding to hyperlinks and transmission modes, and design the payoffs specific to the lifetime. In particular, with the inherit merit that matrix game can be solved with linear programming, our cross-layer programming formulation can benefit from both game-based and NUM-based approaches at the same time by cooperating the programming model for the matrix game with that for the other layers in a consistent framework. Finally, our numerical example demonstrates its performance results on a well-known wireless butterfly network to verify the cross-layer optimization scheme.

Keywords: Cross-layer design, Lifetime maximization, Matrix game, Network coding

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Authors: Suyoto, Tri Prasetyaningrum

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At this paper, we will present the development of mobile application Social Guidance and Counseling (GC) that called “m-NingBK: Social GC”. The application is used for GC services that run on mobile devices. The application is designed specifically for Junior High School student. The methods are a combination of interactive multimedia approaches and educational psychology. Therefore, the design process is carried out three processes, which are digitizing of material social GC services, visualizing wisely and making interactive. This method is intended to make students not only hear and see but also "do" the virtual. There are five components used in multimedia applications "m-NingBK: Social GC" i.e. text, images / graphics, audio / sound, animation and video. Four menus provided by this application is the potential self, social, Expert System and about. The application is built using the Java programming language. This application was tested using a Smartphone with Android Operating System. Based on the test, people give rating: 16.7% excellent, 61.1% good, 19.4% adequate, and 2.8% poor.

Keywords: Expert Systems, Guidance and Counseling, mobile application, multimedia.

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Authors: Rachid Ahdid, Said Safi, Bouzid Manaut

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In this paper, we present a comparative study of three methods of 2D face recognition system such as: Iso-Geodesic Curves (IGC), Geodesic Distance (GD) and Geodesic-Intensity Histogram (GIH). These approaches are based on computing of geodesic distance between points of facial surface and between facial curves. In this study we represented the image at gray level as a 2D surface in a 3D space, with the third coordinate proportional to the intensity values of pixels. In the classifying step, we use: Neural Networks (NN), K-Nearest Neighbor (KNN) and Support Vector Machines (SVM). The images used in our experiments are from two wellknown databases of face images ORL and YaleB. ORL data base was used to evaluate the performance of methods under conditions where the pose and sample size are varied, and the database YaleB was used to examine the performance of the systems when the facial expressions and lighting are varied.

Keywords: 2D face recognition, Geodesic distance, Iso-Geodesic Curves, Geodesic-Intensity Histogram, facial surface, Neural Networks, K-Nearest Neighbor, Support Vector Machines.

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Authors: Darwina Arshad, Paul Hughes

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Recent environmental turbulence including financial crisis, intensified competitive forces, rapid technological change and high market turbulence have dramatically changed the current business climate. The managers firms have to plan and decide what the best approaches that best fit their firms in order to pursue superior performance. This research aims to examine the influence of strategic reasoning and top level managers- individual characteristics on the effectiveness of organizational improvisation and firm performance. Given the lack of studies on these relationships in the previous literature, there is significant contribution to the body of knowledge as well as for managerial practices. 128 responses from top management of technology-based companies in Malaysia were used as a sample. Three hypotheses were examined and the findings confirm that (a) there is no relationship between intuitive reasoning and organizational improvisation but there is a link between rational reasoning and organizational improvisation, (b) top level managers- individual characteristics as a whole affect organizational improvisation; and (c) organizational improvisation positively affects firm performance. The theoretical and managerial implications were discussed in the conclusions.

Keywords: Organizational improvisation, strategic reasoning, firm performance.

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Authors: Levan Nadareishvili, Roland Bakuradze, Barbara Kilosanidze, Nona Topuridze, Liana Sharashidze, Ineza Pavlenishvili

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Some regularities of formation of a new structural state of the thermoplastic polymers - gradually oriented (stretched) state (GOS) are discussed. Transition into GOS is realized by the graded oriented stretching - by action of inhomogeneous mechanical field on the isotropic linear polymers or by zone stretching that is implemented on a standard tensile-testing machine with using a specially designed zone stretching device (ZSD). Both technical approaches (especially zone stretching method) allows to manage the such quantitative parameters of gradually oriented polymers as a range of change in relative elongation/orientation degree, length of this change and profile (linear, hyperbolic, parabolic, logarithmic, etc.). The possibility of obtaining functionally graded materials (FGMs) by graded orientation method is briefly discussed. Uniaxial graded stretching method should be considered as an effective technological solution to create polymer materials with a predetermined gradient of physical properties.

Keywords: Controlled graded stretching, gradually oriented state, linear polymers, zone stretching device.

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Authors: Linnea Stenliden

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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors within Actor-network theory (ANT). The learning conditions are found to be distinguished by broad complexity, characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.

Keywords: Analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation.

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Authors: Drago Jakovcevic, Mihovil Andelinovic, Igor Husak

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The aim of this paper is to explore the economic circumstances in which the selective credit policy, the least used instrument of four types of instruments on disposal to central banks, should be used. The most significant example includes the use of selective credit policies in response to the emergence of the global financial crisis by the FED. Specifics of the potential use of selective credit policies as the instigator of economic growth in Croatia, a small open economy, are determined by high euroization of financial system, fixed exchange rate and long-term trend growth of external debt that is related to the need to maintain high levels of foreign reserves. In such conditions, the classic forms of selective credit policies are unsuitable for the introduction. Several alternative approaches to implement selective credit policies are examined in this paper. Also, thorough analysis of distribution of selective monetary policy loans among economic sectors in Croatia is conducted in order to minimize the risk of investing funds and maximize the return, in order to influence the GDP growth.

Keywords: Global crisis, Selective credit policy, Small open economy.

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Authors: Nasiri Ahmadullah, Shimozato Tetsuhiro, Masayuki Tai

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This paper presents the step-by-step procedure for using Elastic Theory to calculate the internal stresses in composite bridge girders prestressed by the Preflexing Technology, called Prebeam in Japan and Preflex beam worldwide. Elastic Theory approaches preflex beams the same way as it does the conventional composite girders. Since preflex beam undergoes different stages of construction, calculations are made using different sectional and material properties. Stresses are calculated in every stage using the properties of the specific section. Stress accumulation gives the available stress in a section of interest. Concrete presence in the section implies prestress loss due to creep and shrinkage, however; more work is required to be done in this field. In addition to the graphical presentation of this application, this paper further discusses important notes of graphical comparison between the results of an experimental-only research carried out on a preflex beam, with the results of simulation based on the elastic theory approach, for an identical beam using Finite Element Modeling (FEM) by the author.

Keywords: Composite girder, elastic theory, preflex beam, prestressing.

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Authors: Omer Ishag Eldai, Ahmed Hassan M. H. Ali, S. Raviraja

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Web-based systems have become increasingly important due to the fact that the Internet and the World Wide Web have become ubiquitous, surpassing all other technological developments in our history. The Internet and especially companies websites has rapidly evolved in their scope and extent of use, from being a little more than fixed advertising material, i.e. a "web presences", which had no particular influence for the company's business, to being one of the most essential parts of the company's core business. Traditional software engineering approaches with process models such as, for example, CMM and Waterfall models, do not work very well since web system development differs from traditional development. The development differs in several ways, for example, there is a large gap between traditional software engineering designs and concepts and the low-level implementation model, many of the web based system development activities are business oriented (for example web application are sales-oriented, web application and intranets are content-oriented) and not engineering-oriented. This paper aims to introduce Increment Iterative extreme Programming (IIXP) methodology for developing web based systems. In difference to the other existence methodologies, this methodology is combination of different traditional and modern software engineering and web engineering principles.

Keywords: Web based systems, Web engineering.

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Authors: Saumyaranjan Sahoo, Sudhir Yadav

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Indian manufacturing firms operating in rapidly changing and highly competitive market, over the last few decades, have embraced organization-wide transformation to achieve cultural and operational excellence. In recent years, numerous approaches have been proposed to improve business and manufacturing performance. Lean practices in particular, Total Productive Management (TPM) and Total Quality Management (TQM) have received considerable attention, as they being adopted and adapted for raising the performance standard of Indian manufacturing firms to world class levels. The complementary nature of TPM and TQM is being practiced in many companies to achieve synergy. Specifically, this research investigates whether joint TPM-TQM implementation contribute to higher business performance when compared to individual implementation. Data from 160 manufacturing firms were analyzed that demonstrate synergetic implementation of both TPM-TQM practices over a reasonable period of time, contributed in delivering better business performance as compared to individual implementation strategy.

Keywords: Total productive management, total quality management, Indian manufacturing firms, business performance.

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Authors: Rossitza M. Setchi, Qiao Tang

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Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.

Keywords: Concepts, indexing, machine learning, ontology, tagging.

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Authors: Banashree N. P., R. Vasanta

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Recognition of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], a character or symbol to be recognized can be machine printed or handwritten characters/numerals. There are several approaches that deal with problem of recognition of numerals/character depending on the type of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent. Our work focused on a technique in feature extraction i.e. global based approach using end-points information, which is extracted from images of isolated numerals. These feature vectors are fed to neuro-memetic model [18] that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. . In proposed scheme data sets are fed to neuro-memetic algorithm, which identifies the rule with highest fitness value of nearly 100 % & template associates with this rule is nothing but identified numerals. Experimentation result shows that recognition rate is 92-97 % compared to other models.

Keywords: OCR, Global Feature, End-Points, Neuro-Memetic model.

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Authors: Almudena Konrad, Tomás Galguera

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Lack of motivation and interest is a serious obstacle to students’ learning computing skills. A need exists for a knowledge base on effective pedagogy and curricula to teach computer programming. This paper presents results from research evaluating a six-year project designed to teach complex concepts in computer programming collaboratively, while supporting students to continue developing their computer thinking and related coding skills individually. Utilizing a quasi-experimental, mixed methods design, the pedagogical approaches and methods were assessed in two contrasting groups of students with different socioeconomic status, gender, and age composition. Analyses of quantitative data from Likert-scale surveys and an evaluation rubric, combined with qualitative data from reflective writing exercises and semi-structured interviews yielded convincing evidence of the project’s success at both teaching and inspiring students.

Keywords: Computational thinking, computing education, computer programming curriculum, logic, teaching methods.

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Authors: Ahmed Elrewainy

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Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no information about the given data cube. Sparsity is one of the recent approaches used in the source recovery or unmixing techniques. The l₁-norm optimization problem “basis pursuit” could be used as a sparsity-based approach to solve this unmixing problem where the endmembers is assumed to be sparse in an appropriate domain known as dictionary. This optimization problem is solved using proximal method “iterative thresholding”. The l₁-norm basis pursuit optimization problem as a sparsity-based unmixing technique was used to unmix real and synthetic hyperspectral data cubes.

Keywords: Basis pursuit, blind source separation, hyperspectral imaging, spectral unmixing, wavelets.

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Authors: S. Qaedi, S. Seyedtabaii

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Non-Destructive evaluation of in-service power transformer condition is necessary for avoiding catastrophic failures. Dissolved Gas Analysis (DGA) is one of the important methods. Traditional, statistical and intelligent DGA approaches have been adopted for accurate classification of incipient fault sources. Unfortunately, there are not often enough faulty patterns required for sufficient training of intelligent systems. By bootstrapping the shortcoming is expected to be alleviated and algorithms with better classification success rates to be obtained. In this paper the performance of an artificial neural network, K-Nearest Neighbour and support vector machine methods using bootstrapped data are detailed and shown that while the success rate of the ANN algorithms improves remarkably, the outcome of the others do not benefit so much from the provided enlarged data space. For assessment, two databases are employed: IEC TC10 and a dataset collected from reported data in papers. High average test success rate well exhibits the remarkable outcome.

Keywords: Dissolved gas analysis, Transformer incipient fault, Artificial Neural Network, Support Vector Machine (SVM), KNearest Neighbor (KNN)

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Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: k-factor, GARMA, LLWNN, G-GARCH, electricity price, forecasting.

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Authors: M. Ovinis, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs

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The use of anatomical landmarks as a basis for image to patient registration is appealing because the registration may be performed retrospectively. We have previously proposed the use of two anatomical soft tissue landmarks of the head, the canthus (corner of the eye) and the tragus (a small, pointed, cartilaginous flap of the ear), as a registration basis for an automated CT image to patient registration system, and described their localization in patient space using close range photogrammetry. In this paper, the automatic localization of these landmarks in CT images, based on their curvature saliency and using a rule based system that incorporates prior knowledge of their characteristics, is described. Existing approaches to landmark localization in CT images are predominantly semi-automatic and primarily for localizing internal landmarks. To validate our approach, the positions of the landmarks localized automatically and manually in near isotropic CT images of 102 patients were compared. The average difference was 1.2mm (std = 0.9mm, max = 4.5mm) for the medial canthus and 0.8mm (std = 0.6mm, max = 2.6mm) for the tragus. The medial canthus and tragus can be automatically localized in CT images, with performance comparable to manual localization, based on the approach presented.

Keywords: Anatomical Landmarks, CT, Localization.

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Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob

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The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.

Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.

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Authors: M.Stella, M. Russo, D. Begušić

Abstract:

Ability of accurate and reliable location estimation in indoor environment is the key issue in developing great number of context aware applications and Location Based Services (LBS). Today, the most viable solution for localization is the Received Signal Strength (RSS) fingerprinting based approach using wireless local area network (WLAN). This paper presents two RSS fingerprinting based approaches – first we employ widely used WLAN based positioning as a reference system and then investigate the possibility of using GSM signals for positioning. To compare them, we developed a positioning system in real world environment, where realistic RSS measurements were collected. Multi-Layer Perceptron (MLP) neural network was used as the approximation function that maps RSS fingerprints and locations. Experimental results indicate advantage of WLAN based approach in the sense of lower localization error compared to GSM based approach, but GSM signal coverage by far outreaches WLAN coverage and for some LBS services requiring less precise accuracy our results indicate that GSM positioning can also be a viable solution.

Keywords: Indoor positioning, WLAN, GSM, RSS, location fingerprints, neural network.

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