Search results for: Aquatic training

Authors: Weidong Xia, Malgorzata Kolotylo, Xuan Tan

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This study examines the key factors that influence general practitioners’ learning and transfer of specialized arthritis knowledge and self-care techniques to patients during normal patient visits. Drawing on the theory of planed behavior and using matched survey data collected from general practitioners before and after training sessions provided by specialized orthopedic physicians, the study suggests that the general practitioner’s intention to use and transfer learned knowledge was influenced mainly by intrinsic motivation, organizational learning culture and absorptive capacity, but was not influenced by extrinsic motivation. The results provide both theoretical and practical implications.

Keywords: Empirical study, healthcare knowledge management, patient self-care, physician knowledge transfer.

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Authors: Kazunari Meguro, Shinichi Motomura, Takao Kawamura, Kazunori Sugahara

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In this paper, backup and recovery technique for Peer to Peer applications, such as a distributed asynchronous Web-Based Training system that we have previously proposed. In order to improve the scalability and robustness of this system, all contents and function are realized on mobile agents. These agents are distributed to computers, and they can obtain using a Peer to Peer network that modified Content-Addressable Network. In the proposed system, although entire services do not become impossible even if some computers break down, the problem that contents disappear occurs with an agent-s disappearance. As a solution for this issue, backups of agents are distributed to computers. If a failure of a computer is detected, other computers will continue service using backups of the agents belonged to the computer.

Keywords: Distributed Multimedia Systems, e-Learning, P2P, Mobile Agent

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Authors: Maria E. Eggink

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Innovation plays an important role in economic growth and development. Evolutionary economics has entrepreneurs at the centre of the innovation system, but includes all other participants as contributors to the performance of the innovation system. Education and training institutions, one of the participants in the innovation system, contributes in different ways to human capital. The gap in literature on the competence building as part of human capital in the analysis of innovation systems is addressed in this paper. The Mpumalanga Province of South Africa is used as a case study. It was found that the absence of a university, the level of education, the quality and performance in the education sector and the condition of the education infrastructure have not been conducive to learning.

Keywords: Education institutions, human capital, innovation systems, Mpumalanga Province.

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Authors: Z. Zainuddin, N. Mahat, Y. Abu Hassan

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Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This article focuses on two classes of acceleration techniques, one is known as Local Adaptive Techniques that are based on weightspecific only, such as the temporal behavior of the partial derivative of the current weight. The other, known as Dynamic Adaptation Methods, which dynamically adapts the momentum factors, α, and learning rate, η, with respect to the iteration number or gradient. Some of most popular learning algorithms are described. These techniques have been implemented and tested on several problems and measured in terms of gradient and error function evaluation, and percentage of success. Numerical evidence shows that these techniques improve the convergence of the Backpropagation algorithm.

Keywords: Backpropagation, Dynamic Adaptation Methods, Local Adaptive Techniques, Neural networks.

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Authors: Eric Jiang

Abstract:

As a popular rank-reduced vector space approach, Latent Semantic Indexing (LSI) has been used in information retrieval and other applications. In this paper, an LSI-based content vector model for text classification is presented, which constructs multiple augmented category LSI spaces and classifies text by their content. The model integrates the class discriminative information from the training data and is equipped with several pertinent feature selection and text classification algorithms. The proposed classifier has been applied to email classification and its experiments on a benchmark spam testing corpus (PU1) have shown that the approach represents a competitive alternative to other email classifiers based on the well-known SVM and naïve Bayes algorithms.

Keywords: Feature Selection, Latent Semantic Indexing, Text Classification, Vector Space Model.

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Authors: P. Hedbávný, M. Kalichová

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The contribution deals with problem of take-off phase of back somersault with twisting with various numbers of twists along longitudinal body axis. The aim was to evaluate the changes in angles during transition phase from back handspring to back somersault using 3D kinematic analysis of the somersaults. We used Simi Motion System for the 3D kinematic analysis of the observed gymnastic element performed by Czech Republic female representative and 2008 Summer Olympic Games participant. The results showed that the higher the number of twists, the smaller the touchdown angle in which the gymnasts lands on the pad in the beginning of take-off phase. In back somersault with one twist (180°) the average angle is 54°, in 1080° back somersault the average angle is 45.9°. These results may help to improve technical training of sports gymnasts.

Keywords: back somersault with twisting, biomechanicalanalysis, take-off

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Authors: Omid Gervei, Ahmad Ayatollahi, Navid Gervei

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In this paper we present an approach for 3D face recognition based on extracting principal components of range images by utilizing modified PCA methods namely 2DPCA and bidirectional 2DPCA also known as (2D) 2 PCA.A preprocessing stage was implemented on the images to smooth them using median and Gaussian filtering. In the normalization stage we locate the nose tip to lay it at the center of images then crop each image to a standard size of 100*100. In the face recognition stage we extract the principal component of each image using both 2DPCA and (2D) 2 PCA. Finally, we use Euclidean distance to measure the minimum distance between a given test image to the training images in the database. We also compare the result of using both methods. The best result achieved by experiments on a public face database shows that 83.3 percent is the rate of face recognition for a random facial expression.

Keywords: 3D face recognition, 2DPCA, (2D) 2 PCA, Rangeimage

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions.

Keywords: Dialogue management, response generation, reinforcement learning, deep learning, evaluation.

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Authors: R. Rajeswari, N. Kamaraj

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In this paper, Wavelet based ANFIS for finding inter turn fault of generator is proposed. The detector uniquely responds to the winding inter turn fault with remarkably high sensitivity. Discrimination of different percentage of winding affected by inter turn fault is provided via ANFIS having an Eight dimensional input vector. This input vector is obtained from features extracted from DWT of inter turn faulty current leaving the generator phase winding. Training data for ANFIS are generated via a simulation of generator with inter turn fault using MATLAB. The proposed algorithm using ANFIS is giving satisfied performance than ANN with selected statistical data of decomposed levels of faulty current.

Keywords: Winding InterTurn fault, ANN, ANFIS, and DWT.

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Authors: Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif

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In this paper, we presented our innovative way of determining the driving context for a driving assistance system. We invoke the fusion of all parameters that describe the context of the environment, the vehicle and the driver to obtain the driving context. We created a training set that stores driving situation patterns and from which the system consults to determine the driving situation. A machine-learning algorithm predicts the driving situation. The driving situation is an input to the fission process that yields the action that must be implemented when the driver needs to be informed or assisted from the given the driving situation. The action may be directed towards the driver, the vehicle or both. This is an ongoing work whose goal is to offer an alternative driving assistance system for safe driving, green driving and comfortable driving. Here, ontologies are used for knowledge representation.

Keywords: Cognitive driving, intelligent transportation system, multimodal system, ontology, machine learning.

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Authors: Lilac A. E. Al-Safadi

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This paper proposes an auto-classification algorithm of Web pages using Data mining techniques. We consider the problem of discovering association rules between terms in a set of Web pages belonging to a category in a search engine database, and present an auto-classification algorithm for solving this problem that are fundamentally based on Apriori algorithm. The proposed technique has two phases. The first phase is a training phase where human experts determines the categories of different Web pages, and the supervised Data mining algorithm will combine these categories with appropriate weighted index terms according to the highest supported rules among the most frequent words. The second phase is the categorization phase where a web crawler will crawl through the World Wide Web to build a database categorized according to the result of the data mining approach. This database contains URLs and their categories.

Keywords: Information Processing on the Web, Data Mining, Document Classification.

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Authors: B. Singh, A. Singh, R. C. Yadav

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Utmost care of human related issues are essentially required for sustainable growth of micro, small and medium enterprises (MSMEs) of India, as these MSMEs are contributing enormously to socio-economic development of country. In this research, aspects related to human factors and functioning of MSMEs of India were studied. The investigation, based on a survey of 84 MSMEs of India cited that the enterprises are mostly employing unskilled labor whose wages are less with poor training. In spite of reported minor accidents, attention towards safety is poorly paid. To meet-out the production target, MSMEs generally employ over-time and payment towards this overtime is sometimes missing. Hence, honest and humanitarian attention for better human resources is needed to improve the performance and competitiveness of MSMEs of India.

Keywords: Human factors, Small and medium enterprises, Working culture.

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Authors: Jiří Barta

Abstract:

The paper deals with simulation programs of spread of harmful substances. Air pollution has a direct impact on the quality of human life and environmental protection is currently a very hot topic. Therefore, the paper focuses on the simulation of release of harmful substances. The first part of article deals with perspectives and possibilities of implementation outputs of simulations programs into the system which is education and of practical training of the management staff during emergency events in the frame of critical infrastructure. The last part shows the practical testing and evaluation of simulation programs. Of the tested simulations software been selected Symos97. The tool offers advanced features for setting leakage. Gradually allows the user to model the terrain, location, and method of escape of harmful substances.

Keywords: Computer Simulation, Symos97, spread, simulation software, harmful substances.

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Authors: Al-bdour, A. Ali., Ellisha Nasruddin., Soh Keng Lin

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This study attempts to investigate the relationship between internal CSR practices and organizational commitment based on the social exchange theory (SET). Specifically, we examine the impact of five dimensions of internal CSR practices on organizational commitment: health and safety, human rights, training and education, work life balance and workplace diversity. The proposed model was tested on a sample of 336 frontline employees within the banking sector in Jordan. Results showed that all internal CSR dimensions are significantly and positively related to affective and normative commitment. In addition, the findings of this study indicate that all internal CSR dimensions did not have a significant relationship with continuance commitment. Limitations of the study, directions for future research, and implications of the findings are discussed.

Keywords: Internal CSR, organizational commitment, Jordan, banking sector.

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Authors: Aldrin R. Logdat

Abstract:

Philosophy offers a systematic approach to reflective, logical, and innovative thinking, which involves a thorough investigation of various concepts. On the other hand, national development encompasses a country’s ability to embrace its unique identity and take charge of its future. Education, meanwhile, provides individuals with enlightening experiences and specialized training in different fields. The aim of this paper is to demonstrate how philosophy and education can serve as catalysts for national progress. Given the Philippines' diverse socio-cultural, religious, ethnic, and political backgrounds, this study seeks to answer two crucial questions: Can the country achieve development despite its differences? If that is the case, what are the critical elements propelling this advancement? By means of historical interpretation and philosophical analysis, this article posits that philosophy and education are essential components in driving the country's progress in the era following the pandemic.

Keywords: Philosophy, national progress, educational discourse, pandemic.

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Authors: Xingyu Pan, Laure Tougne

Abstract:

For recognizing coins, the graved release date is important information to identify precisely its monetary type. However, reading characters in coins meets much more obstacles than traditional character recognition tasks in the other fields, such as reading scanned documents or license plates. To address this challenging issue in a numismatic context, we propose a training-free approach dedicated to detection and recognition of the release date of the coin. In the first step, the date zone is detected by comparing histogram features; in the second step, a topology-based algorithm is introduced to recognize coin numbers with various font types represented by binary gradient map. Our method obtained a recognition rate of 92% on synthetic data and of 44% on real noised data.

Keywords: Coin, detection, character recognition, topology.

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Authors: Wajdi Bellil, Chokri Ben Amar, Adel M. Alimi

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This paper proposes a comparison between wavelet neural networks (WNN), RBF neural network and polynomial approximation in term of 1-D and 2-D functions approximation. We present a novel wavelet neural network, based on Beta wavelets, for 1-D and 2-D functions approximation. Our purpose is to approximate an unknown function f: Rn - R from scattered samples (xi; y = f(xi)) i=1....n, where first, we have little a priori knowledge on the unknown function f: it lives in some infinite dimensional smooth function space and second the function approximation process is performed iteratively: each new measure on the function (xi; f(xi)) is used to compute a new estimate f as an approximation of the function f. Simulation results are demonstrated to validate the generalization ability and efficiency of the proposed Beta wavelet network.

Keywords: Beta wavelets networks, RBF neural network, training algorithms, MSE, 1-D, 2D function approximation.

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Authors: Reza Bazargan Lari, Mohammad H. Fattahi

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Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.

Keywords: Wavelet, de-noising, predictability, time series fractal analysis, valid length, ANN.

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Authors: Kleanthis Prekas, Maria Rangoussi, Savvas Vassiliadis, George Prekas

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Intelligent tutoring systems constitute an evolution of computer-aided educational software. We present here the modules of an intelligent tutoring system for Automatic Control, developed in our department. Through the software application developed,students can perform complete automatic control laboratory experiments, either over the departmental local area network or over the Internet. Monitoring of access to the system (local as well as international), along with student performance statistics, has yielded strongly encouraging results (as of fall 2004), despite the advanced technical content of the presented paradigm, thus showing the potential of the system developed for education and for training.

Keywords: Automatic control, tutoring system, Internet access, laboratory experiments.

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Authors: M. Aslan, A. Karaaslan, S. Selcuk

Abstract:

The research was conducted in order to determine the organizational socialization levels of nurses working in hospitals in the form of a descriptive study. The research population was composed of nurses employed in public and private sector hospitals in the province of Konya with 0-3 years of professional experience in the hospitals (N=1200); and the sample was composed of 495 nurses that accepted to take part in the study voluntarily. Statistical evaluation of data was conducted in SPSS.16 software. The results of the study revealed that the total score taken by nurses at the organizational socialization scale was 262.95; and this was close to the maximum score. Particularly the departmental socialization sub-dimension proved to be higher in comparison to the other two dimensions (organization socialization and task socialization). Statistically meaningful differences were found in the levels of organization socialization in relation to the status of organizational orientation training, level of education and age group.

Keywords: Nurses, Newcomers, Organizational Socialization.

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Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline which ensures that data mirrors real-world settings by incorporating gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification and explainability in a single pipeline called DeClEx.

Keywords: Machine learning, healthcare, classification, explainability.

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Authors: G. Mokryani, M. R. Haghifam, J. Esmaeilpoor

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Happening of Ferroresonance phenomenon is one of the reasons of consuming and ruining transformers, so recognition of Ferroresonance phenomenon has a special importance. A novel method for classification of Ferroresonance presented in this paper. Using this method Ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Competitive Neural Network used for classification. Ferroresonance data and other transients was obtained by simulation using EMTP program. Using Daubechies wavelet transform signals has been decomposed till six levels. The energy of six detailed signals that obtained by wavelet transform are used for training and trailing Competitive Neural Network. Results show that the proposed procedure is efficient in identifying Ferroresonance from other events.

Keywords: Competitive Neural Network, Ferroresonance, EMTP program, Wavelet transform.

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Authors: Ssu-Han Chen, Der-Baau Perng

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Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded,defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: Molding surface, machine vision, statistical texture, discrete Fourier transformation.

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Authors: K. M. Faraoun, A. Boukelif

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In the present work, we propose a new technique to enhance the learning capabilities and reduce the computation intensity of a competitive learning multi-layered neural network using the K-means clustering algorithm. The proposed model use multi-layered network architecture with a back propagation learning mechanism. The K-means algorithm is first applied to the training dataset to reduce the amount of samples to be presented to the neural network, by automatically selecting an optimal set of samples. The obtained results demonstrate that the proposed technique performs exceptionally in terms of both accuracy and computation time when applied to the KDD99 dataset compared to a standard learning schema that use the full dataset.

Keywords: Neural networks, Intrusion detection, learningenhancement, K-means clustering

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Authors: Mihaela Munteanu (Pila), Silvius Stanciu

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This paper presents the aspects of the official control of fishery in the Republic of Moldova. Currently, the regulations and the activity of national institutions with responsibilities in the field of food quality are in a process of harmonization with the European rules, aiming at European integration, quality improvement and providing a higher level of food safety. The National Agency for Food Safety is the main national body with responsibilities in the field of food safety. In the field of fishery products, the Agency carries out an intensive activity of informing the citizen and controlling the products marketed. The paper presents the dangers related to the consumption of fish and fishery products traded on the national market, the sanitary-veterinary inspections conducted by the profile institution and the improper situations identified. The national market of fishery products depends largely on imports, mainly focused on ocean fish. The research carried out has shown that during the period 2011-2018, following the inspections carried out on fishery products traded on the national market, a number of inconsistencies have been identified. Thus, indigenous products were frequently detected with sensory characteristics unfit for consumption, and being commercialized in inappropriate locations or contaminated with chemical pollutants. On import products controlled, the most frequent inconsistent situations have been represented by inconsistent sensory aspects and by parasite contamination. Taking into account the specific aspects of aquatic products, including the high level of alterability, special conditions of growth, marketing, culinary preparation and consumption are necessary in order to decrease the risk of disease over the population. Certificates, attestations and other documents certifying the quality of batches, completed by additional laboratory examinations, are necessary in order to increase the level of confidence on the quality of products marketed in the Republic. The implementation of various control procedures and mechanisms at national level, correlated with the focused activity of the specialized institutions, can decrease the risk of contamination and avoid cases of disease on the population due to the consumption of fishery products.

Keywords: Fishery products, food safety, insurance, inspection, Republic of Moldova.

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Authors: Tomáš Vencúrik, Jiří Nykodým

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This study compares the intensity of game load among player positions and between the 1st and the 2nd half of the games. Two guards, three forwards, and three centers (female basketball players) participated in this study. The heart rate (HR) and its development were monitored during two competitive games. Statistically insignificant differences in the intensity of game load were recorded between guards, forwards, and centers below and above 85% of the maximal heart rate (HRmax) and in the mean HR as % of HRmax (87.81±3.79%, 87.02±4.37%, and 88.76±3.54%, respectively). Moreover, when the 1st and the 2nd half of the games were compared in the mean HR (87.89±4.18% vs. 88.14±3.63% of HRmax), no statistical significance was recorded. This information can be useful for coaching staff, to manage and to precisely plan the training process.

Keywords: Game load, heart rate, player positions, the 1st and the 2nd half of the games.

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Authors: S. H. R. Lo

Abstract:

Virtual engineering technology has undergone rapid progress in recent years and is being adopted increasingly by manufacturing companies of many engineering disciplines. There is an increasing demand from industry for qualified virtual engineers. The qualified virtual engineers should have the ability of applying engineering principles and mechanical design methods within the commercial software package environment. It is a challenge to the engineering education in universities which traditionally tends to lack the integration of knowledge and skills required for solving real world problems. In this paper, a case study shows some recent development of a MSc Mechanical Engineering course at Department of Engineering and Technology in MMU, and in particular, two units Simulation of Mechanical Systems(SMS) and Computer Aided Fatigue Analysis(CAFA) that emphasize virtual engineering education and promote integration of knowledge acquisition, skill training and industrial application.

Keywords: Computational modelling and simulation, mechanical engineering education.

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Authors: Tetyana Baydyk, Ernst Kussul, Sandra Bonilla Meza

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There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.

Keywords: Face recognition, Labeled Faces in the Wild (LFW) database, Random Local Descriptor (RLD), random features.

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Authors: Chau Nguyen Viet, Ian Marshall

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This paper presents a new classification algorithm using colour and texture for obstacle detection. Colour information is computationally cheap to learn and process. However in many cases, colour alone does not provide enough information for classification. Texture information can improve classification performance but usually comes at an expensive cost. Our algorithm uses both colour and texture features but texture is only needed when colour is unreliable. During the training stage, texture features are learned specifically to improve the performance of a colour classifier. The algorithm learns a set of simple texture features and only the most effective features are used in the classification stage. Therefore our algorithm has a very good classification rate while is still fast enough to run on a limited computer platform. The proposed algorithm was tested with a challenging outdoor image set. Test result shows the algorithm achieves a much better trade-off between classification performance and efficiency than a typical colour classifier.

Keywords: Colour, texture, classification, obstacle detection.

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Authors: Glessiane de O. Almeida, Sérgio Murilo C. Messias, Iracema M. de Aragão Gomes

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This article discusses issues related to the System of Innovation: Comparing economies of Brazil and South Africa. Having as this study aimed at comparing the Innovation System of the countries mentioned. Then briefly describe the process of Venture Capital and present the industry innovation in Brazil and South Africa. The methodological approach described in this article is descriptive and the approach is qualitative, taking as a basis secondary data relating to research articles. The main results are related to the different forms of financing of Venture Capital used by countries compared, in addition to the training and economic policy. And finally, it was highlighted the importance of implementation of policy reforms for the Brazil and Africa in the innovation process.

Keywords: Innovation, Venture Capital, Economy, National Innovation System (NIS), BRICS.

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