Search results for: experimental evaluation

Authors: Fardin Boustani, Mohammad Hosein Hojati

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Groundwater is one of the most important water resources in Fars province. Based on this study, 95 percent of the total annual water consumption in Fars is used for agriculture, whereas the percentages for domestic and industrial uses are 4 and 1 percent, respectively. Population growth, urban and industrial growth, and agricultural development in Fars have created a condition of water stress. In this province, farmers and other users are pumping groundwater faster than its natural replenishment rate, causing a continuous drop in groundwater tables and depletion of this resource. In this research variation of groundwater level, their effects and ways to help control groundwater levels in aquifer of the Niriz plains in Fars plain were evaluated .Excessive exploitation of groundwater in this aquifer caused the groundwater levels fall too fast or to unacceptable levels. The average drawdown of the groundwater level in this plain were 9.1 meters during 1997 to 2004. The purpose of this study is to evaluate water level changes in the Niriz Aquifer in the Fars province in order to determine the areas of greatest depletion, the cause of depletion, and predict the remaining life of the aquifer.

Keywords: Aquifer, ground water depletion, water table

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Authors: Su-Hyun Cho, Chang-U Chae

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Environmental impact assessment techniques have been developed as a result of the worldwide efforts to reduce the environmental impact of global warming. By using the quantification method in the construction industry, it is now possible to manage the greenhouse gas is to systematically evaluate the impact on the environment over the entire construction process. In particular, the proportion of greenhouse gas emissions at the production stage of construction material occupied is high, and efforts are needed in particular in the construction field. In this research, intended for concrete products for the construction materials, by using the LCA method, we compared the results of environmental impact assessment and carbon emissions of developing products that have been applied low-carbon technologies compared to existing products. As a results, by introducing a raw material of industrial waste, showed carbon reduction. Through a comparison of the carbon emission reduction effect of low carbon technologies, it is intended to provide academic data for the evaluation of greenhouse gases in the construction sector and the development of low carbon technologies of the future.

Keywords: CO2 Emissions, CO2 Reduction, Ready-mixed Concrete, Environmental Impact Assessment.

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Authors: Mina Alibeigi, Sattar Hashemi, Ali Hamzeh

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Since dealing with high dimensional data is computationally complex and sometimes even intractable, recently several feature reductions methods have been developed to reduce the dimensionality of the data in order to simplify the calculation analysis in various applications such as text categorization, signal processing, image retrieval, gene expressions and etc. Among feature reduction techniques, feature selection is one the most popular methods due to the preservation of the original features. In this paper, we propose a new unsupervised feature selection method which will remove redundant features from the original feature space by the use of probability density functions of various features. To show the effectiveness of the proposed method, popular feature selection methods have been implemented and compared. Experimental results on the several datasets derived from UCI repository database, illustrate the effectiveness of our proposed methods in comparison with the other compared methods in terms of both classification accuracy and the number of selected features.

Keywords: Feature, Feature Selection, Filter, Probability Density Function

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Authors: Mona A. Fouad, Fatma M. Bayoumi, Hoda M. Onsi, Mohamed G. Darwish

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Digital libraries become more and more necessary in order to support users with powerful and easy-to-use tools for searching, browsing and retrieving media information. The starting point for these tasks is the segmentation of video content into shots. To segment MPEG video streams into shots, a fully automatic procedure to detect both abrupt and gradual transitions (dissolve and fade-groups) with minimal decoding in real time is developed in this study. Each was explored through two phases: macro-block type's analysis in B-frames, and on-demand intensity information analysis. The experimental results show remarkable performance in detecting gradual transitions of some kinds of input data and comparable results of the rest of the examined video streams. Almost all abrupt transitions could be detected with very few false positive alarms.

Keywords: Adaptive threshold, abrupt transitions, gradual transitions, MPEG video streams.

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Authors: Sigita Boca, Ruta Galoburda, Inta Krasnova, Dalija Seglina, Aivars Aboltins, Imants Skrupskis

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The aim of the study was to evaluate the effect of texturizers on the rheological properties of the apple mass and desserts made from various raw materials. The apple varieties - ‘Antonovka’, ‘Baltais Dzidrais’, and ‘Zarja Alatau’ harvested in Latvia, were used for the experiment. The apples were processed in a blender unpeeled for obtaining a homogenous mass. The apple mass was analyzed fresh and after storage at –18ºC. Both fresh and thawed apple mass samples with added gelatin, xantan gum, and sodium carboxymethylcellulose were whisked obtaining dessert. Pectin, pH and soluble dry matter of the product were determined. Apparent viscosity was measured using a rotational viscometer DV–III Ultra. Pectin content in frozen apple mass decreased significantly (p<0.05) compared to the fresh sample. The viscosity of apple desserts immediately after their preparation depends on the physico-chemical properties of apples and the texturizers used in the production.

Keywords: Apple variety, apparent viscosity, hydrocolloids, pectin, texturizers.

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Authors: Shin-Shin Kao

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This paper reviews the crucial situation in higher education in Taiwan due to the rapid decline of the birth rate in the past three decades, and how the government and local colleges/universities work to face the challenge. Recruiting international students is one of the possible ways to resolve the problem, but offering enough courses in English is one of the main obstacles when the majority of learners are still Taiwanese students. In the academic year of 2012, Chung Yuan Christian University determined to make its campus international and began to enforce two required courses for freshmen taught in English. It failed in the beginning, but succeeded in the following academic year of 2013. Using the teaching evaluations accumulated in the past three years, this paper aims to clarify the myths which had been bothering most faculties. It also offers some suggestions for college/university teachers interested in giving lectures in English to English as Second Language (ESL) learners. A conclusion is presented at the end of the paper, in which the author explained why Taiwanese students could learn their profession in English.

Keywords: Calculus, English, teaching evaluation, teaching strategy, vocabulary.

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Authors: S. Anbumozhi, P. S. Manoharan

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Medical Image fusion plays a vital role in medical field to diagnose the brain tumors which can be classified as benign or malignant. It is the process of integrating multiple images of the same scene into a single fused image to reduce uncertainty and minimizing redundancy while extracting all the useful information from the source images. Fuzzy logic is used to fuse two brain MRI images with different vision. The fused image will be more informative than the source images. The texture and wavelet features are extracted from the fused image. The multilevel Adaptive Neuro Fuzzy Classifier classifies the brain tumors based on trained and tested features. The proposed method achieved 80.48% sensitivity, 99.9% specificity and 99.69% accuracy. Experimental results obtained from fusion process prove that the use of the proposed image fusion approach shows better performance while compared with conventional fusion methodologies.

Keywords: Image fusion, Fuzzy rules, Neuro-fuzzy classifier.

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Authors: R. Hosseini, A. Gholaminejad, H. Jahandar

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The present paper is an experimental investigation of roughness effects on nucleate pool boiling of refrigerant R113 on horizontal circular copper surfaces. The copper samples were treated by different sand paper grit sizes to achieve different surface roughness. The average surface roughness of the four samples was 0.901, 0.735, 0.65, and 0.09, respectively. The experiments were performed in the heat flux range of 8 to 200kW/m2. The heat transfer coefficient was calculated by measuring wall superheat of the samples and the input heat flux. The results show significant improvement of heat transfer coefficient as the surface roughness is increased. It is found that the heat transfer coefficient of the sample with Ra=0.901 is 3.4, 10.5, and 38.5% higher in comparison with surfaces with Ra of 0.735, 0.65, and 0.09 at heat flux of 170 kW/m2. Moreover, the results are compared with literature data and the well known Cooper correlation.

Keywords: Nucleate Boiling, Pool Boiling, R113, SurfaceRoughness

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Authors: Belkacem Chikhaoui, Helene Pigot, Mathieu Beaudoin, Guillaume Pratte, Philippe Bellefeuille, Fernando Laudares

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The way music is interpreted by the human brain is a very interesting topic, but also an intricate one. Although this domain has been studied for over a century, many gray areas remain in the understanding of music. Recent advances have enabled us to perform accurate measurements of the time taken by the human brain to interpret and assimilate a sound. Cognitive computing provides tools and development environments that facilitate human cognition simulation. ACT-R is a cognitive architecture which offers an environment for implementing human cognitive tasks. This project combines our understanding of the music interpretation by a human listener and the ACT-R cognitive architecture to build SINGER, a computerized simulation for listening and recalling songs. The results are similar to human experimental data. Simulation results also show how it is easier to remember short melodies than long melodies which require more trials to be recalled correctly.

Keywords: Computational model, cognitive modeling, simulation, learning, song, music.

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Authors: Manash Pratim Sarma, Kandarpa Kumar Sarma

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A set of Artificial Neural Network (ANN) based methods for the design of an effective system of speech recognition of numerals of Assamese language captured under varied recording conditions and moods is presented here. The work is related to the formulation of several ANN models configured to use Linear Predictive Code (LPC), Principal Component Analysis (PCA) and other features to tackle mood and gender variations uttering numbers as part of an Automatic Speech Recognition (ASR) system in Assamese. The ANN models are designed using a combination of Self Organizing Map (SOM) and Multi Layer Perceptron (MLP) constituting a Learning Vector Quantization (LVQ) block trained in a cooperative environment to handle male and female speech samples of numerals of Assamese- a language spoken by a sizable population in the North-Eastern part of India. The work provides a comparative evaluation of several such combinations while subjected to handle speech samples with gender based differences captured by a microphone in four different conditions viz. noiseless, noise mixed, stressed and stress-free.

Keywords: Assamese, Recognition, LPC, Spectral, ANN.

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Authors: Nur Syibrah Muhamad Naim, Mohd Lazim Abdullah, Che Mohd Imran Che Taib, Abu OsmanMd. Tap

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Decision making preferences to certain criteria usually focus on positive degrees without considering the negative degrees. However, in real life situation, evaluation becomes more comprehensive if negative degrees are considered concurrently. Preference is expected to be more effective when considering both positive and negative degrees of preference to evaluate the best selection. Therefore, the aim of this paper is to propose the conflicting bifuzzy preference relations in group decision making by utilization of a novel score function. The conflicting bifuzzy preference relation is obtained by introducing some modifications on intuitionistic fuzzy preference relations. Releasing the intuitionistic condition by taking into account positive and negative degrees simultaneously and utilizing the novel score function are the main modifications to establish the proposed preference model. The proposed model is tested with a numerical example and proved to be simple and practical. The four-step decision model shows the efficiency of obtaining preference in group decision making.

Keywords: Fuzzy preference relations, score function, conflicting bifuzzy, decision making.

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Authors: A. Golmohammadi, B. Jahandideh

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One of the determinants of a firm-s prosperity is the customers- perceived service quality and satisfaction. While service quality is wide in scope, and consists of various dimensions, there may be differences in the relative importance of these dimensions in affecting customers- overall satisfaction of service quality. Identifying the relative rank of different dimensions of service quality is very important in that it can help managers to find out which service dimensions have a greater effect on customers- overall satisfaction. Such an insight will consequently lead to more effective resource allocation which will finally end in higher levels of customer satisfaction. This issue – despite its criticality- has not received enough attention so far. Therefore, using a sample of 240 bank customers in Iran, an artificial neural network is developed to address this gap in the literature. As customers- evaluation of service quality is a subjective process, artificial neural networks –as a brain metaphor- may appear to have a potentiality to model such a complicated process. Proposing a neural network which is able to predict the customers- overall satisfaction of service quality with a promising level of accuracy is the first contribution of this study. In addition, prioritizing the service quality dimensions in affecting customers- overall satisfaction –by using sensitivity analysis of neural network- is the second important finding of this paper.

Keywords: service quality, customer satisfaction, relative importance, artificial neural network.

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Authors: Ahmad Z., Othman S. Z., Md Yunus B., Mohamed A.

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According to the masonry standard the compressive strength is basically dependent on factors such as the mortar strength and the relative values of unit and mortar strength. However interlocking brick has none or less use of mortar. Therefore there is a need to investigate the behavior of masonry walls using interlocking bricks. In this study a series of tests have been conducted; physical properties and compressive strength of brick units and masonry walls were constructed from interlocking bricks and tested under constant vertical load at different eccentricities. The purpose of the experimental investigations is to obtain the force displacement curves, analyze the behavior of masonry walls. The results showed that the brick is categorized as common brick (BS 3921:1985) and severe weathering grade (ASTM C62). The maximum compressive stress of interlocking brick wall is 3.6 N/mm2 and fulfilled the requirement of standard for residential building.

Keywords: Interlocking brick, soil-cement brick, masonry wall, compressive strength, eccentricities

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: Local nonlinear estimation, LWPR algorithm, Online training method.

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Authors: Xiaoshu Lu, Tao Lu, Matias Remes, Martti Viljanen

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As the data-driven economy is growing faster than ever and the demand for energy is being spurred, we are facing unprecedented challenges of improving energy efficiency in data centers. Effectively maximizing energy efficiency or minimising the cooling energy demand is becoming pervasive for data centers. This paper investigates overall energy consumption and the energy efficiency of cooling system for a data center in Finland as a case study. The power, cooling and energy consumption characteristics and operation condition of facilities are examined and analysed. Potential energy and cooling saving opportunities are identified and further suggestions for improving the performance of cooling system are put forward. Results are presented as a comprehensive evaluation of both the energy performance and good practices of energy efficient cooling operations for the data center. Utilization of an energy recovery concept for cooling system is proposed. The conclusion we can draw is that even though the analysed data center demonstrated relatively high energy efficiency, based on its power usage effectiveness value, there is still a significant potential for energy saving from its cooling systems.

Keywords: Data center, case study, cooling system, energyefficiency.

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Authors: Yasmin Z. Murad, Haneen M. Abdl-Jabbar

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An experimental program is conducted in this research to investigate the influence of basalt fibers and steel fibers on the flexural behavior of RC beams. Reinforced concrete beams are constructed using steel fiber concrete and basalt fiber concrete. Steel and basalt fibers are included in a percentage of 15% and 2.5% of the total cement weight, respectively. Test results have shown that basalt fibers have increased the load carrying capacity of the beams up to 30% and the maximum deflection to almost 2.4 times that measured in the control specimen. It has also shown that steel fibers have increased the load carrying capacity of the beams up to 47% and the ultimate deflection is almost duplicated compared to the control beam. Steel and basalt fibers have increased the ductility of the reinforced concrete beams.

Keywords: Basalt fiber, steel fiber, reinforced concrete beams, flexural behavior.

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Authors: Hassan Ghasemzadeh, Sepideh Mazrouee, Hassan Goldani Moghaddam, Hamid Shojaei, Mohammad Reza Kakoee

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Block replacement algorithms to increase hit ratio have been extensively used in cache memory management. Among basic replacement schemes, LRU and FIFO have been shown to be effective replacement algorithms in terms of hit rates. In this paper, we introduce a flexible stack-based circuit which can be employed in hardware implementation of both LRU and FIFO policies. We propose a simple and efficient architecture such that stack-based replacement algorithms can be implemented without the drawbacks of the traditional architectures. The stack is modular and hence, a set of stack rows can be cascaded depending on the number of blocks in each cache set. Our circuit can be implemented in conjunction with the cache controller and static/dynamic memories to form a cache system. Experimental results exhibit that our proposed circuit provides an average value of 26% improvement in storage bits and its maximum operating frequency is increased by a factor of two

Keywords: Cache Memory, Replacement Algorithms, LeastRecently Used Algorithm, First In First Out Algorithm.

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Authors: Raquel P. F. Guiné, Ana R. B. Figueiredo, Paula M. R. Correia, Fernando J. Gonçalves

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The purpose of the present work was to develop an innovative food product with nutritional properties as well as appealing organoleptic qualities. The product, a jam, was prepared with the beans’ cooking water combined with fresh apple or carrot, without the addition of any conservatives. Three different jams were produced: bean and carrot, bean and apple and bean, apple and cinnamon. The developed products underwent a sensorial analysis that revealed that the bean, apple and cinnamon jam was globally better accepted. However, with this study, the consumers determined that the bean and carrot jam had the most attractive color and the bean and apple jam the better consistency. Additionally, it was possible to analyze the jams for their chemical components, namely fat, fiber, protein, sugars and antioxidant activity. The obtained results showed that the bean and carrot jam had the highest lipid content, while the bean, apple and cinnamon jam had the highest fiber content, when compared to the other two jams. Regarding the sugar content, both jams with apple revealed similar sugar values, which were higher than the sugar content of the bean and carrot jam. The antioxidant activity was on average 10 mg TE/g.

Keywords: Bean jam, chemical composition, sensorial analysis, product acceptability.

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Authors: L. Fonseca-Géigel, M. Alvarez, G. García, R. Cox, L. Morier, L. Fonte, M. G. Guzmán

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Toxoplasma gondii is an intracellular parasite capable of infecting all nucleated cells in a diverse array of species. Toxoplasma plaque assay have been described using Bacto Agar. Because of its experimental advantages carboxymethyl cellulose overlay, medium viscosity was choosing and the aim of this work was to develop alternative method for formation of T. gondii plaques. Tachyzoites were inoculated onto monolayers of Vero cells and cultured at 37° C under 5 % CO2. The cultures were followed up by microscopy inspection. Small plaques were visible by naphtol blue stain 4 days after infection. Larger plaques could be observed by day 10 of culture. The carboxymethyl cellulose is a cheap reagent and the methodology is easier, faster than assays under agar overlay. This is the first description of the carboxymethyl cellulose overlay use for obtaining the formation of T. gondii plaques and may be useful in consequent obtaining tachyzoites for detailed studies.

Keywords: Carboxymethyl cellulose, Cell culture, Plaque assay, Toxoplasma gondii.

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Authors: Riaz A. Bhatti, Wang Yanrong

Abstract:

Particle damping is a technique to reduce the structural vibrations by means of placing small metallic particles inside a cavity that is attached to the structure at location of high vibration amplitudes. In this paper, we have presented an analytical model to simulate the particle damping of two dimensional transient vibrations in structure operating under high centrifugal loads. The simulation results show that this technique remains effective as long as the ratio of the dynamic acceleration of the structure to the applied centrifugal load is more than 0.1. Particle damping increases with the increase of particle to structure mass ratio. However, unlike to the case of particle damping in the absence of centrifugal loads where the damping efficiency strongly depends upon the size of the cavity, here this dependence becomes very weak. Despite the simplicity of the model, the simulation results are considerably in good agreement with the very scarce experimental data available in the literature for particle damping under centrifugal loads.

Keywords: Impact damping, particle damping, vibration control, vibration suppression.

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Authors: B. Medjahed, M. A. Didi, B. Guezzen

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This work concerns with the experimental study of the adsorption of the Ni(II) on bentonite. The effects of various parameters such as contact time, stirring rate, initial concentration of Ni(II), masse of clay, initial pH of aqueous solution and temperature on the adsorption yield, were carried out. The study of the effect of the ionic strength on the yield of adsorption was examined by the identification and the quantification of the present chemical species in the aqueous phase containing the metallic ion Ni(II). The adsorbed species were investigated by a calculation program using CHEAQS V. L20.1 in order to determine the relation between the percentages of the adsorbed species and the adsorption yield. The optimization process was carried out using 2³ factorial designs. The individual and combined effects of three process parameters, i.e. initial Ni(II) concentration in aqueous solution (2.10⁻³ and 5.10⁻³ mol/L), initial pH of the solution (2 and 6.5), and mass of bentonite (0.03 and 0.3 g) on Ni(II) adsorption, were studied.

Keywords: Adsorption, bentonite, factorial design, Nickel(II).

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Authors: Mukhtar H. Hassan, Muhammed A. Basher, Elhadi E. Saad, Almahdi M. Almahdi

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The aim of this study was to demonstrate the possible effect of some variables such as age, gender, blood sugar level, and duration of diabetes on the serum level of zinc in diabetic individuals from Murzuk area. Serum zinc (Zn), Fasting blood sugar (FBS), hemoglobin HbA1c (HbA1c) were evaluated in 46 type I diabetic subjects (group 1), 48 type II diabetic subjects (group 2) and 43 healthy individuals (control) of both genders aged (30-81) years. Data showed that both diabetic groups have significantly higher (P<0.05) serum levels of Zn, FBS and HbA1c compared with controls. No significant (p>0.05) differences in serum Zn levels were observed between Males and Females. Serum Zn levels were non-significantly decreased with increasing age. In type II diabetic subjects, serum Zn levels were non-significantly decreased with increasing duration of disease whereas those in type I were non-significantly increased.

Keywords: Blood sugar, diabetes, HbA1c, zinc.

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Authors: Frank Emmert Streib, Matthias Dehmer, Gökhan H. Bakır, Max Mühlhauser

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In this paper we investigate the influence of external noise on the inference of network structures. The purpose of our simulations is to gain insights in the experimental design of microarray experiments to infer, e.g., transcription regulatory networks from microarray experiments. Here external noise means, that the dynamics of the system under investigation, e.g., temporal changes of mRNA concentration, is affected by measurement errors. Additionally to external noise another problem occurs in the context of microarray experiments. Practically, it is not possible to monitor the mRNA concentration over an arbitrary long time period as demanded by the statistical methods used to learn the underlying network structure. For this reason, we use only short time series to make our simulations more biologically plausible.

Keywords: Dynamic Bayesian networks, structure learning, gene networks, Markov chain Monte Carlo, microarray data.

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Authors: Marios Poulos, Sozon Papavlasopoulos, V. S. Belesiotis

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In the proposed method for Web page-ranking, a novel theoretic model is introduced and tested by examples of order relationships among IP addresses. Ranking is induced using a convexity feature, which is learned according to these examples using a self-organizing procedure. We consider the problem of selforganizing learning from IP data to be represented by a semi-random convex polygon procedure, in which the vertices correspond to IP addresses. Based on recent developments in our regularization theory for convex polygons and corresponding Euclidean distance based methods for classification, we develop an algorithmic framework for learning ranking functions based on a Computational Geometric Theory. We show that our algorithm is generic, and present experimental results explaining the potential of our approach. In addition, we explain the generality of our approach by showing its possible use as a visualization tool for data obtained from diverse domains, such as Public Administration and Education.

Keywords: Computational Geometry, Education, e-Governance, Semantic Web.

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Authors: Rajesh S.Prasad, U. V. Kulkarni, Jayashree.R.Prasad

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As the enormous amount of on-line text grows on the World-Wide Web, the development of methods for automatically summarizing this text becomes more important. The primary goal of this research is to create an efficient tool that is able to summarize large documents automatically. We propose an Evolving connectionist System that is adaptive, incremental learning and knowledge representation system that evolves its structure and functionality. In this paper, we propose a novel approach for Part of Speech disambiguation using a recurrent neural network, a paradigm capable of dealing with sequential data. We observed that connectionist approach to text summarization has a natural way of learning grammatical structures through experience. Experimental results show that our approach achieves acceptable performance.

Keywords: Artificial Neural Networks (ANN); Computational Intelligence (CI); Connectionist Text Summarizer ECTS (ECTS); Evolving Connectionist systems; Evolving systems; Fuzzy systems (FS); Part of Speech (POS) disambiguation.

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Authors: W. Afef, A. Mohamed Ammar, G. Kamel, O. Ahmed

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In the present study, a numerical approach to describe the pyrolysis of a single solid particle of wood is used to study the influence of various conditions such as particle size, heat transfer coefficient, reactor temperature and heating rate. The influence of these parameters in the change of the duration of the pyrolysis cycle was studied. Mathematical modeling was employed to simulate the heat, mass transfer, and kinetic processes inside the reactor. The evolutions of the mass loss as well as the evolution of temperature inside the thick piece are investigated numerically. The elaborated model was also employed to study the effect of the reactor temperature and the rate of heating on the change of the temperature and the local loss of the mass inside the piece of wood. The obtained results are in good agreement with the experimental data available in the literature.

Keywords: Wood, Pyrolysis, Modeling, Convective heat transfer, Kinetic.

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Authors: Jenn-Yih Chen, Bean-Yin Lee, Yuan-Chuan Hsu, Jui-Cheng Lin, Kuang-Chyi Lee

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In this paper, a sliding mode control method based on the passivity approach is proposed to control the position of surface-mounted permanent magnet synchronous motors (PMSMs). Firstly, the dynamics of a PMSM was proved to be strictly passive. The position controller with an adaptive law was used to estimate the load torque to eliminate the chattering effects associated with the conventional sliding mode controller. The stability analysis of the overall position control system was carried out by adopting the passivity theorem instead of Lyapunov-type arguments. Finally, experimental results were provided to show that the good position tracking can be obtained, and exhibit robustness in the variations of the motor parameters and load torque disturbances.

Keywords: Adaptive law, passivity theorem, permanent magnet synchronous motor, sliding mode control.

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Authors: Jagannath Aryal, Don Kulasiri, Dishi Liu

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This paper describes the optimization of a complex dairy farm simulation model using two quite different methods of optimization, the Genetic algorithm (GA) and the Lipschitz Branch-and-Bound (LBB) algorithm. These techniques have been used to improve an agricultural system model developed by Dexcel Limited, New Zealand, which describes a detailed representation of pastoral dairying scenarios and contains an 8-dimensional parameter space. The model incorporates the sub-models of pasture growth and animal metabolism, which are themselves complex in many cases. Each evaluation of the objective function, a composite 'Farm Performance Index (FPI)', requires simulation of at least a one-year period of farm operation with a daily time-step, and is therefore computationally expensive. The problem of visualization of the objective function (response surface) in high-dimensional spaces is also considered in the context of the farm optimization problem. Adaptations of the sammon mapping and parallel coordinates visualization are described which help visualize some important properties of the model-s output topography. From this study, it is found that GA requires fewer function evaluations in optimization than the LBB algorithm.

Keywords: Genetic Algorithm, Linux Cluster, LipschitzBranch-and-Bound, Optimization

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Authors: M. Hammerton, J. Trevathan, T. Myers, W. Read

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The transfer rate of messages in distributed sensor network applications is a critical factor in a system's performance. The Sensor Abstraction Layer (SAL) is one such system. SAL is a middleware integration platform for abstracting sensor specific technology in order to integrate heterogeneous types of sensors in a network. SAL uses Java Remote Method Invocation (RMI) as its connection method, which has unsatisfying transfer rates, especially for streaming data. This paper analyses different connection methods to optimize data transmission in SAL by replacing RMI. Our results show that the most promising Java-based connections were frameworks for Java New Input/Output (NIO) including Apache MINA, JBoss Netty, and xSocket. A test environment was implemented to evaluate each respective framework based on transfer rate, resource usage, and scalability. Test results showed the most suitable connection method to improve data transmission in SAL JBoss Netty as it provides a performance enhancement of 68%.

Keywords: Wireless sensor networks, remote method invocation, transmission time.

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Authors: Mohammad Mirabi

Abstract:

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of jobs that visit a set of machines in the same order. The FSP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To meet the requirements on time and to minimize the make-span performance of large permutation flow-shop scheduling problems in which there are sequence dependent setup times on each machine, this paper develops one hybrid genetic algorithms (HGA). Proposed HGA apply a modified approach to generate population of initial chromosomes and also use an improved heuristic called the iterated swap procedure to improve initial solutions. Also the author uses three genetic operators to make good new offspring. The results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution.

Keywords: Hybrid genetic algorithm, Scheduling, Permutationflow-shop, Sequence dependent

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