Search results for: classical extract

Authors: M. Sadighi, H. Pouriayevali, M. Saadati

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This paper deals with analysis of flexural stiffness, indentation and their energies in three point loading of sandwich beams with composite faces from Eglass/epoxy and cores from Polyurethane or PVC. Energy is consumed in three stages of indentation in laminated beam, indentation of sandwich beam and bending of sandwich beam. Theory of elasticity is chosen to present equations for indentation of laminated beam, then these equations have been corrected to offer better results. An analytical model has been used assuming an elastic-perfectly plastic compressive behavior of the foam core. Classical theory of beam is used to describe three point bending. Finite element (FE) analysis of static indentation sandwich beams is performed using the FE code ABAQUS. The foam core is modeled using the crushable foam material model and response of the foam core is experimentally characterized in uniaxial compression. Three point bending and indentation have been done experimentally in two cases of low velocity and higher velocity (quasi-impact) of loading. Results can describe response of beam in terms of core and faces thicknesses, core material, indentor diameter, energy absorbed, and length of plastic area in the testing. The experimental results are in good agreement with the analytical and FE analyses. These results can be used as an introduction for impact loading and energy absorbing of sandwich structures.

Keywords: Three point Bending, Indentation, Foams, Composite laminated beam, Sandwich beams, Finite element

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Authors: Shun Hattori

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In recent years, many researches to mine the exploding Web world, especially User Generated Content (UGC) such as weblogs, for knowledge about various phenomena and events in the physical world have been done actively, and also Web services with the Web-mined knowledge have begun to be developed for the public. However, there are few detailed investigations on how accurately Web-mined data reflect physical-world data. It must be problematic to idolatrously utilize the Web-mined data in public Web services without ensuring their accuracy sufficiently. Therefore, this paper introduces the simplest Web Sensor and spatiotemporallynormalized Web Sensor to extract spatiotemporal data about a target phenomenon from weblogs searched by keyword(s) representing the target phenomenon, and tries to validate the potential and reliability of the Web-sensed spatiotemporal data by four kinds of granularity analyses of coefficient correlation with temperature, rainfall, snowfall, and earthquake statistics per day by region of Japan Meteorological Agency as physical-world data: spatial granularity (region-s population density), temporal granularity (time period, e.g., per day vs. per week), representation granularity (e.g., “rain" vs. “heavy rain"), and media granularity (weblogs vs. microblogs such as Tweets).

Keywords: Granularity analysis, knowledge extraction, spatiotemporal data mining, Web credibility, Web mining, Web sensor.

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Authors: S. M. Seyedhosseini, A. Makui, M. Ghadami

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Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.

Keywords: Case based reasoning, Genetic algorithm, Groupdecision making, Product management.

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Authors: Imen Dhaou

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This study examines conditional Value at Risk by applying the GJR-EVT-Copula model, and finds the optimal portfolio for eight Dow Jones Islamic-conventional pairs. Our methodology consists of modeling the data by a bivariate GJR-GARCH model in which we extract the filtered residuals and then apply the Peak over threshold model (POT) to fit the residual tails in order to model marginal distributions. After that, we use pair-copula to find the optimal portfolio risk dependence structure. Finally, with Monte Carlo simulations, we estimate the Value at Risk (VaR) and the conditional Value at Risk (CVaR). The empirical results show the VaR and CVaR values for an equally weighted portfolio of Dow Jones Islamic-conventional pairs. In sum, we found that the optimal investment focuses on Islamic-conventional US Market index pairs because of high investment proportion; however, all other index pairs have low investment proportion. These results deliver some real repercussions for portfolio managers and policymakers concerning to optimal asset allocations, portfolio risk management and the diversification advantages of these markets.

Keywords: CVaR, Dow Jones Islamic index, GJR-GARCH-EVT-pair copula, portfolio optimization.

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Authors: Natural Frequency Analysis of a Porous Functionally Graded Shaft System

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The vibration characteristics of a functionally graded (FG) rotor model having porosities and micro-voids is investigated using three-dimensional finite element analysis. The FG shaft is mounted with a steel disc located at the midspan. The shaft ends are supported on isotropic bearings. The FG material is composed of a metallic (stainless-steel) and ceramic phase (zirconium oxide) as its constituent phases. The layer wise material property variation is governed by power law. Material property equations are developed for the porosity modelling. Python code is developed to assign the material properties to each layer including the effect of porosities. ANSYS commercial software is used to extract the natural frequencies and whirl frequencies for the FG shaft system. The obtained results show the influence of porosity volume fraction and power-law index, on the vibration characteristics of the ceramic-based FG shaft system.

Keywords: Finite element method, functionally graded material, porosity volume fraction, power law.

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Authors: Ahmed Kamil Hasan Al-Ali, Bouchra Senadji, Ganesh Naik

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We propose a system to real environmental noise and channel mismatch for forensic speaker verification systems. This method is based on suppressing various types of real environmental noise by using independent component analysis (ICA) algorithm. The enhanced speech signal is applied to mel frequency cepstral coefficients (MFCC) or MFCC feature warping to extract the essential characteristics of the speech signal. Channel effects are reduced using an intermediate vector (i-vector) and probabilistic linear discriminant analysis (PLDA) approach for classification. The proposed algorithm is evaluated by using an Australian forensic voice comparison database, combined with car, street and home noises from QUT-NOISE at a signal to noise ratio (SNR) ranging from -10 dB to 10 dB. Experimental results indicate that the MFCC feature warping-ICA achieves a reduction in equal error rate about (48.22%, 44.66%, and 50.07%) over using MFCC feature warping when the test speech signals are corrupted with random sessions of street, car, and home noises at -10 dB SNR.

Keywords: Noisy forensic speaker verification, ICA algorithm, MFCC, MFCC feature warping.

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Authors: Ibrahim A. Akasha, Lydia Campbell, Stephen R. Euston

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Date palm (Phoenix dactylifera L.) seeds are waste streams which are considered a major problem to the food industry. They contain potentially useful protein (10-15% of the whole date-s weight). Global production, industrialisation and utilisation of dates are increasing steadily. The worldwide production of date palm fruit has increased from 1.8 million tons in 1961 to 6.9 million tons in 2005, thus from the global production of dates are almost 800.000 tonnes of date palm seeds are not currently used [1]. The current study was carried out to convert the date palm seeds into useful protein powder. Compositional analysis showed that the seeds were rich in protein and fat 5.64 and 8.14% respectively. We used several laboratory scale methods to extract proteins from seed to produce a high protein powder. These methods included simple acid or alkali extraction, with or without ultrafiltration and phenol trichloroacetic acid with acetone precipitation (Ph/TCA method). The highest protein content powder (68%) was obtained by Ph/TCA method with yield of material (44%) whereas; the use of just alkali extraction gave the lowest protein content of 8%, and a yield of 32%.

Keywords: Date palm seed, Phoenix dactylifera L., extraction of date palm seed protein

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Authors: Jonghyun Park, Toan Nguyen Dinh, Gueesang Lee

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In this paper, we present a novel approach to accurately detect text regions including shop name in signboard images with complex background for mobile system applications. The proposed method is based on the combination of text detection using edge profile and region segmentation using fuzzy c-means method. In the first step, we perform an elaborate canny edge operator to extract all possible object edges. Then, edge profile analysis with vertical and horizontal direction is performed on these edge pixels to detect potential text region existing shop name in a signboard. The edge profile and geometrical characteristics of each object contour are carefully examined to construct candidate text regions and classify the main text region from background. Finally, the fuzzy c-means algorithm is performed to segment and detected binarize text region. Experimental results show that our proposed method is robust in text detection with respect to different character size and color and can provide reliable text binarization result.

Keywords: Text detection, edge profile, signboard image, fuzzy clustering.

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Authors: Hynek Chlup, Lukas Horny, Rudolf Zitny, Svatava Konvickova, Tomas Adamek

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Coronary artery bypass grafts (CABG) are widely studied with respect to hemodynamic conditions which play important role in presence of a restenosis. However, papers which concern with constitutive modeling of CABG are lacking in the literature. The purpose of this study is to find a constitutive model for CABG tissue. A sample of the CABG obtained within an autopsy underwent an inflation–extension test. Displacements were recoredered by CCD cameras and subsequently evaluated by digital image correlation. Pressure – radius and axial force – elongation data were used to fit material model. The tissue was modeled as onelayered composite reinforced by two families of helical fibers. The material is assumed to be locally orthotropic, nonlinear, incompressible and hyperelastic. Material parameters are estimated for two strain energy functions (SEF). The first is classical exponential. The second SEF is logarithmic which allows interpretation by means of limiting (finite) strain extensibility. Presented material parameters are estimated by optimization based on radial and axial equilibrium equation in a thick-walled tube. Both material models fit experimental data successfully. The exponential model fits significantly better relationship between axial force and axial strain than logarithmic one.

Keywords: Constitutive model, coronary artery bypass graft, digital image correlation, fiber reinforced composite, inflation test, saphenous vein.

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Authors: Cengiz Tavşan, Niloufar Akbarzadeh

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Architecture in Iran has a continuous history from at least 5000 BC to the present, and numerous Iranian pre-Islamic elements have contributed significantly to the formation of Islamic art. At first, decoration was limited to small objects and containers and then progressed in the art of plaster and brickwork. They later applied in architecture as well. The art of gypsum and brickwork, which was prevalent in the form of motifs (animals and plants) in pre-Islam, was used in the aftermath of Islam with the art of calligraphy in decorations. The splendor and beauty of Iranian architecture, especially during the Islamic era, are related to decoration and design. After the invasion of Iran by the Arabs and the introduction of Islam to Iran, the arrival of the Iranian classical architecture significantly changed, and we saw the Arabic calligraphy decoration of the mosques in Iran. The principles of aesthetics in the art of calligraphy in Iran are based precisely on the principles of the beauty of ancient Iranian and Islamic art. On the other hand, after Islam, calligraphy was one of the most important sources of Islamic art in Islam and one of the important features of Islamic culture. First, the calligraphy had no cultural meaning and was only for decoration and beautification, it had the same meaning only in the inscriptions; however, over time, it became meaningful. This article provides a summary of the history of calligraphy in the mosques (from the entrance to Islam until the Safavid period), which cannot ignore the role of the calligraphy in their decorative ideas; and also, the important role that decorative elements play in creating a public space in terms of social and aesthetic performance. This study was conducted using library studies and field studies. The purpose of this study is to show the characteristics of architecture and art of decorations in Iran, especially in the mosque's architecture, which reaches the pinnacle of progress. We will see that religious beliefs and artistic practices are merging and trying to bring a single concept.

Keywords: Islamic art, Islamic architecture, decorations in Iranian mosques, calligraphy.

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

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Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: Speech recognition, acoustic features, Mel Frequency Cepstral Coefficients.

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Authors: M. H. Syakira, L. Brenda

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Antibacterial activity of Plumeria alba (Frangipani) petals methanolic extracts were evaluated against Escherichia coli, Proteus vulgaris,Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus saprophyticus, Enterococcus faecalis and Serratia marcescens by using disk diffusion method. Concentration extracts (80 %) showed the highest inhibition zone towards Escherichia coli (14.3 mm). Frangipani extract also showed high antibacterial activity against Staphylococcus saprophyticus, Proteus vulgaris and Serratia marcescens, but not more than the zones of the positive control used. Comparison between two broad specrum antibiotics to frangipani extracts showed that the 80 % concentration extracts produce the same zone of inhibition as Streptomycin. Frangipani extracts showed no bacterial activity towards Klebsiella pneumoniae, Pseudomonas aeruginosa and Enterococcus faecalis. There are differences in the sensitivity of different bacteria to frangipani extracts, suggesting that frangipani-s potency varies between these bacteria. The present results indicate that frangipani showed significant antibacterial activity especially to Escherichia coli.

Keywords: Frangipani, Plumeria alba, anti microbial, Escherichia coli

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Authors: Barenten Suciu

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Classical matrix calculus and Routh-Hurwitz stability conditions, applied to the snake-like motion of the conical wheel axle, lead to the conclusion that the hunting mode is inherently unstable, and its natural frequency is a complex number. In order to analytically solve such a complicated vibration model, either the inertia terms were neglected, in the model designated as geometrical, or restrictions on the creep coefficients and yawing diameter were imposed, in the so-called dynamical model. Here, an alternative solution is proposed to solve the hunting mode, based on the observation that the bullet train wheel axle is equipped with cylindrical wheels. One argues that for such wheel treads, the geometrical hunting is irrelevant, since its natural frequency becomes nil, but the dynamical hunting is significant since its natural frequency reduces to a real number. Moreover, one illustrates that the geometrical simplification of the wheel causes the stabilization of the hunting mode, since the characteristic quartic equation, derived for conical wheels, reduces to a quadratic equation of positive coefficients, for cylindrical wheels. Quite simple analytical expressions for the damping ratio and natural frequency are obtained, without applying restrictions into the model of contact. Graphs of the time-depending hunting lateral perturbation, including the maximal and inflexion points, are presented both for the critically-damped and the over-damped wheel axles.

Keywords: Bullet train, dynamical hunting, cylindrical wheels, damping, stability, creep, vibration analysis.

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Authors: M. R. Mustafa, M. H. Isa, R. B. Rezaur

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The use of artificial neural network (ANN) modeling for prediction and forecasting variables in water resources engineering are being increasing rapidly. Infrastructural applications of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters in different types of neural networks used in water resources engineering have been reported. ANN modeling conducted for water resources engineering variables (river sediment and discharge) published in high impact journals since 2002 to 2011 have been examined and presented in this review. ANN is a vigorous technique to develop immense relationship between the input and output variables, and able to extract complex behavior between the water resources variables such as river sediment and discharge. It can produce robust prediction results for many of the water resources engineering problems by appropriate learning from a set of examples. It is important to have a good understanding of the input and output variables from a statistical analysis of the data before network modeling, which can facilitate to design an efficient network. An appropriate training based ANN model is able to adopt the physical understanding between the variables and may generate more effective results than conventional prediction techniques.

Keywords: ANN, discharge, modeling, prediction, sediment,

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Authors: S. Behrad, M.Y. Yusof, K. L. Goh, A.S. Baba

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Probiotic bacteria especially Lactobacillus spp. and Bifidobacterium exert suppressive effect on Helicobacter pylori. Cinnamon and licorice have been traditionally used for the treatment of gastric ulcer. The objectives of this study were to determine the effects of herbs on yogurt fermentation, the level of probiotic bacteria in yogurt during 28 days storage and the effect of herbal yogurt on the growth of H. pylori in vitro. Cinnamon or licorice was mixed with milk and the mixture was fermented with probiotic bacteria to form herbal-yogurt. Changes of pH and total titratable acids were monitored and the viability of probiotic bacteria was evaluated during and after refrigerated storage. The in vitro inhibition of H. pylori growth was determined using agar diffusion and minimum inhibitory concentration (MIC) method. The presence of herbs did not affect the probiotic population during storage. There were no significant differences in pH and TTA between herbal-yogurts and plain-yogurt during fermentation and storage. Water extract of cinnamon-yogurt showed the highest inhibition effect (13.5mm) on H. pylori growth in comparison with licorice-yogurt (11.2mm). The present findings indicate cinnamon and licorice has bioactive components to decrease the growth of H. pylori.

Keywords: Cinnamon, Helicobacter pylori, Herbal-Yogurt, Licorice, Probiotics

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Authors: J. D. D. Daniel, K. N. Goh, S. M. Yusop

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Trends in business intelligence, e-commerce and remote access make it necessary and practical to store data in different ways on multiple systems with different operating systems. As business evolve and grow, they require efficient computerized solution to perform data update and to access data from diverse enterprise business applications. The objective of this paper is to demonstrate the capability of DTS [1] as a database solution for automatic data transfer and update in solving business problem. This DTS package is developed for the sales of variety of plants and eventually expanded into commercial supply and landscaping business. Dimension data modeling is used in DTS package to extract, transform and load data from heterogeneous database systems such as MySQL, Microsoft Access and Oracle that consolidates into a Data Mart residing in SQL Server. Hence, the data transfer from various databases is scheduled to run automatically every quarter of the year to review the efficient sales analysis. Therefore, DTS is absolutely an attractive solution for automatic data transfer and update which meeting today-s business needs.

Keywords: Data Transformation Services (DTS), ObjectLinking and Embedding Database (OLEDB), Data Mart, OnlineAnalytical Processing (OLAP), Online Transactional Processing(OLTP).

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Authors: Jia-Rong Yeh, Tzu-Yu Lin, Jiann-Shing Shieh, Yun Chen

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A mammal-s body can be seen as a blood vessel with complex tunnels. When heart pumps blood periodically, blood runs through blood vessels and rebounds from walls of blood vessels. Blood pressure signals can be measured with complex but periodic patterns. When an artery is clamped during a surgical operation, the spectrum of blood pressure signals will be different from that of normal situation. In this investigation, intestinal artery clamping operations were conducted to a pig for simulating the situation of intestinal blocking during a surgical operation. Similarity theory is a convenient and easy tool to prove that patterns of blood pressure signals of intestinal artery blocking and unblocking are surely different. And, the algorithm of Hilbert Huang Transform can be applied to extract the character parameters of blood pressure pattern. In conclusion, the patterns of blood pressure signals of two different situations, intestinal artery blocking and unblocking, can be distinguished by these character parameters defined in this paper.

Keywords: Blood pressure, spectrum, intestinal artery, similarity theory and Hilbert Huang Transform.

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Authors: Michael Zimba, Darlison Nyirenda

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A novel copy-move image forgery, CMIF, detection method is proposed. The proposed method presents a new approach which relies on electrostatic field theory, EFT. Solely for the purpose of reducing the dimension of a suspicious image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of the suspicious image and extracts only the approximation subband. The extracted subband is then bijectively mapped onto a virtual electrostatic field where concepts of EFT are utilized to extract robust features. The extracted features are invariant to additive noise, JPEG compression, and affine transformation. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. SATS is a better option than the common shift vector method because SATS is insensitive to affine transformation. Consequently, the proposed CMIF algorithm is not only fast but also more robust to attacks compared to the existing related CMIF algorithms. The experimental results show high detection rates, as high as 100% in some cases.

Keywords: Affine transformation, Radix sort, SATS, Virtual electrostatic field.

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Authors: Mohammad Ali Jabraeil Jamali, Ahmad Khademzadeh

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The success of an electronic system in a System-on- Chip is highly dependent on the efficiency of its interconnection network, which is constructed from routers and channels (the routers move data across the channels between nodes). Since neither classical bus based nor point to point architectures can provide scalable solutions and satisfy the tight power and performance requirements of future applications, the Network-on-Chip (NoC) approach has recently been proposed as a promising solution. Indeed, in contrast to the traditional solutions, the NoC approach can provide large bandwidth with moderate area overhead. The selected topology of the components interconnects plays prime rule in the performance of NoC architecture as well as routing and switching techniques that can be used. In this paper, we present two generic NoC architectures that can be customized to the specific communication needs of an application in order to reduce the area with minimal degradation of the latency of the system. An experimental study is performed to compare these structures with basic NoC topologies represented by 2D mesh, Butterfly-Fat Tree (BFT) and SPIN. It is shown that Cluster mesh (CMesh) and MinRoot schemes achieves significant improvements in network latency and energy consumption with only negligible area overhead and complexity over existing architectures. In fact, in the case of basic NoC topologies, CMesh and MinRoot schemes provides substantial savings in area as well, because they requires fewer routers. The simulation results show that CMesh and MinRoot networks outperforms MESH, BFT and SPIN in main performance metrics.

Keywords: MinRoot, CMesh, NoC, Topology, Performance Evaluation

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Authors: R. Kandiah, K. Miyamoto

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In Sri Lanka, the Jaffna area is a high drought affected area and depends mainly on groundwater aquifers for water needs. Water for daily activities is extracted from wells. As households manually extract water from the wells, it is not drawn from mid evening to early morning. The water inflow at night provides the maximum water level that decreases during the daytime due to extraction. The storage volume of water in wells is limited or at its lowest level during the dry season. This study analyzes the domestic water budget during the dry season in the Jaffna area. In order to evaluate the water inflow rate into wells, storage volume and extraction volume from wells over time, water pressure is measured at the bottom of three wells, which are located in coastal area denoted as well A, in nonspecific area denoted as well B, and agricultural area denoted as well C. The water quality at the wells A, B, and C, are mostly fresh, modest fresh, and saline respectively. From the monitoring, we can find that the daily inflow amount of water into the wells and daily water extraction depend on each other, that is, higher extraction yields higher inflow. And, in the dry season, the daily inflow volume and the daily extraction volume of each well are almost in balance.

Keywords: Domestic water, water balance, water budget, ground water, shallow well.

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Authors: D. Dib, W. Guebabi, M. B. Guesmi

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The objective of this paper is a contribution to a study of power supply by solar energy system called a common Ferkène north of Algerian desert in the semi-arid area. The optimal exploitation of the system, goes through stages of study and essential design, the choice of the model of the photovoltaic panel, the study of behavior with all the parameters involved in simulation before fixing the trajectory tracking the maximum point the power to extract (MPPT), form the essential platform to shape the design of the solar system set up to supply the town Ferkène without considering the grid. The identification of the common Ferkène by the collection of geographical, meteorological, demographic and electrical provides a basis uniform and important data. The results reflect a valid fictive model for any attempt to study and design a solar system to supply an arid or semi-arid zone by electrical energy from photovoltaic panels.

Keywords: Solar power, photovoltaic panel, Boost converter, supply, design, electric power, Ferkène, Algeria.

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Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose an aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: Aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree.

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Authors: Mei Shan Ngan, Chee Wei Tan

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Due to the non-linear characteristics of photovoltaic (PV) array, PV systems typically are equipped with the capability of maximum power point tracking (MPPT) feature. Moreover, in the case of PV array under partially shaded conditions, hotspot problem will occur which could damage the PV cells. Partial shading causes multiple peaks in the P-V characteristic curves. This paper presents a hybrid algorithm of Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) MPPT algorithm for the detection of global peak among the multiple peaks in order to extract the true maximum energy from PV panel. The PV system consists of PV array, dc-dc boost converter controlled by the proposed MPPT algorithm and a resistive load. The system was simulated using MATLAB/Simulink package. The simulation results show that the proposed algorithm performs well to detect the true global peak power. The results of the simulations are analyzed and discussed.

Keywords: Photovoltaic (PV), Partial Shading, Maximum Power Point Tracking (MPPT), Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN)

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Authors: Khaled Halimi, Hassina Seridi-Bouchelaghem

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The purpose of this paper is to describe how learning analytics approaches based on social semantic web techniques can be applied to enhance the lifelong learning experiences in a connectivist perspective. For this reason, a prototype of a system called SoLearn (Social Learning Environment) that supports this approach. We observed and studied literature related to lifelong learning systems, social semantic web and ontologies, connectivism theory, learning analytics approaches and reviewed implemented systems based on these fields to extract and draw conclusions about necessary features for enhancing the lifelong learning process. The semantic analytics of learning can be used for viewing, studying and analysing the massive data generated by learners, which helps them to understand through recommendations, charts and figures their learning and behaviour, and to detect where they have weaknesses or limitations. This paper emphasises that implementing a learning analytics approach based on social semantic web representations can enhance the learning process. From one hand, the analysis process leverages the meaning expressed by semantics presented in the ontology (relationships between concepts). From the other hand, the analysis process exploits the discovery of new knowledge by means of inferring mechanism of the semantic web.

Keywords: Connectivism, data visualization, informal learning, learning analytics, semantic web, social web.

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Authors: S. Logeswari, K. Premalatha

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Search is the most obvious application of information retrieval. The variety of widely obtainable biomedical data is enormous and is expanding fast. This expansion makes the existing techniques are not enough to extract the most interesting patterns from the collection as per the user requirement. Recent researches are concentrating more on semantic based searching than the traditional term based searches. Algorithms for semantic searches are implemented based on the relations exist between the words of the documents. Ontologies are used as domain knowledge for identifying the semantic relations as well as to structure the data for effective information retrieval. Annotation of data with concepts of ontology is one of the wide-ranging practices for clustering the documents. In this paper, indexing based on concept and annotation are proposed for clustering the biomedical documents. Fuzzy c-means (FCM) clustering algorithm is used to cluster the documents. The performances of the proposed methods are analyzed with traditional term based clustering for PubMed articles in five different diseases communities. The experimental results show that the proposed methods outperform the term based fuzzy clustering.

Keywords: MeSH Ontology, Concept Indexing, Annotation, semantic relations, Fuzzy c-means.

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Authors: Seyedfateh Moradi, Abas Ali Rahbar

Abstract:

The present study focuses on investigating group psychoanalysis in the Middle East. The study uses a descriptive-analytic method and library resources have been used to collect the data. Additionally, the researcher’s observations of people’s everyday behavior have played an important role in the production and analysis of the study. Group psychoanalysis in the Middle East can be conducted through people’s daily behaviors, proverbs, poetry, mythology, etc., and some of the general characteristics of people in the Middle East include: xenophobia, revivalism, fatalism, nostalgic, wills and so on. Members of the group have often failed to achieve Libido wills and it is very important in unifying and reproduction violence. Therefore, if libidinal wills are irrationally fixed, it will be important in forming fundamentalist and racist groups, a situation that is dominant among many groups in the Middle East. Adversities, from early childhood and afterwards, in the subjects have always been influential in the political behavior of group members, and it manifests itself as counter-projections. Consequently, it affects the foreign policy of the governments. On the other hand, two kinds of subjects are identifiable in the Middle East, one; classical subject that is related to nostalgia and mythology and, two; modern subjects which is self-alienated. As a result, both subjects are seeking identity and self-expression in public in relation to forming groups. Therefore, collective unconscious in the Middle East shows itself as extreme boundaries and leads to forming groups characterized with violence. Psychoanalysis shows important aspects to identify many developments in the Middle East; totally analysis of Freud, Carl Jung and Reich about groups can be applied in the present Middle East.

Keywords: Politics, political psychoanalysis, group, Middle East.

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Authors: Samraj Andrews, Ramaswamy Palaniappan, Nidal Kamel

Abstract:

In single trial analysis, when using Principal Component Analysis (PCA) to extract Visual Evoked Potential (VEP) signals, the selection of principal components (PCs) is an important issue. We propose a new method here that selects only the appropriate PCs. We denote the method as selective eigen-rate (SER). In the method, the VEP is reconstructed based on the rate of the eigen-values of the PCs. When this technique is applied on emulated VEP signals added with background electroencephalogram (EEG), with a focus on extracting the evoked P3 parameter, it is found to be feasible. The improvement in signal to noise ratio (SNR) is superior to two other existing methods of PC selection: Kaiser (KSR) and Residual Power (RP). Though another PC selection method, Spectral Power Ratio (SPR) gives a comparable SNR with high noise factors (i.e. EEGs), SER give more impressive results in such cases. Next, we applied SER method to real VEP signals to analyse the P3 responses for matched and non-matched stimuli. The P3 parameters extracted through our proposed SER method showed higher P3 response for matched stimulus, which confirms to the existing neuroscience knowledge. Single trial PCA using KSR and RP methods failed to indicate any difference for the stimuli.

Keywords: Electroencephalogram, P3, Single trial VEP.

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Authors: Susanta Kumar Gachhayat, S. K. Dash

Abstract:

Multi objective non-convex economic dispatch problems of a thermal power plant are of grave concern for deciding the cost of generation and reduction of emission level for diminishing the global warming level for improving green-house effect. This paper deals with ramp rate constraints for achieving better inequality constraints so as to incorporate valve point loading for cost of generation in thermal power plant through ramp rate biogeography based optimization involving mutation and migration. Through 50 out of 100 trials, the cost function and emission objective function were found to have outperformed other classical methods such as lambda iteration method, quadratic programming method and many heuristic methods like particle swarm optimization method, weight improved particle swarm optimization method, constriction factor based particle swarm optimization method, moderate random particle swarm optimization method etc. Ramp rate biogeography based optimization applications prove quite advantageous in solving non convex multi objective economic dispatch problems subjected to nonlinear loads that pollute the source giving rise to third harmonic distortions and other such disturbances.

Keywords: Economic load dispatch, Biogeography based optimization, Ramp rate biogeography based optimization, Valve Point loading, Moderate random particle swarm optimization method, Weight improved particle swarm optimization method

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Authors: Qintao Shen, Lei Luo, Jun Ma, Jie Yu, Qingbo Wu, Yongqi Ma, Zhengji Liu

Abstract:

Control Flow Integrity (CFI) is one of the most promising technique to defend Code-Reuse Attacks (CRAs). Traditional CFI Systems and recent Context-Sensitive CFI use coarse control flow graphs (CFGs) to analyze whether the control flow hijack occurs, left vast space for attackers at indirect call-sites. Coarse CFGs make it difficult to decide which target to execute at indirect control-flow transfers, and weaken the existing CFI systems actually. It is an unsolved problem to extract CFGs precisely and perfectly from binaries now. In this paper, we present an algorithm to get a more precise CFG from binaries. Parameters are analyzed at indirect call-sites and functions firstly. By comparing counts of parameters prepared before call-sites and consumed by functions, targets of indirect calls are reduced. Then the control flow would be more constrained at indirect call-sites in runtime. Combined with CCFI, we implement our policy. Experimental results on some popular programs show that our approach is efficient. Further analysis show that it can mitigate COOP and other advanced attacks.

Keywords: Contex-sensitive, CFI, binary analysis, code reuse attack.

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Authors: Yun Mi, Ko, Hye Jung, Joo

Abstract:

This study develops a relation to explore the factors influencing management and technology capabilities in strategic alliances. Alliances between firms are recognizing increasingly popular as a vehicle to create and extract greater value from the market. Firm’s alliance can be described as the collaborative problem solving process to solve problems jointly. This study starts from research questions what factors of firm’s management and technology characteristics affect performance of firms which are formed alliances. In this study, we investigated the effect of strategic alliances on company performance. That is, we try to identify whether firms made an alliance with other organizations are differed by characteristics of management and technology. And we test that alliance type and alliance experiences moderate the relationship between firm’s capabilities and its performance. We employ problem-solving perspective and resource-based view perspective to shed light on this research questions. The empirical work is based on the Survey of Business Activities conducted from2006 to 2008 by Statistics Korea. We verify correlations between to point out that these results contribute new empirical evidence on the effect of strategic alliances on company performance.

Keywords: Problem solving process, strategic alliance.

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