Search results for: Component Model

Authors: Jiqing Han, Rongchun Gao

Abstract:

One major source of performance decline in speaker recognition system is channel mismatch between training and testing. This paper focuses on improving channel robustness of speaker recognition system in two aspects of channel compensation technique and channel robust features. The system is text-independent speaker identification system based on two-stage recognition. In the aspect of channel compensation technique, this paper applies MAP (Maximum A Posterior Probability) channel compensation technique, which was used in speech recognition, to speaker recognition system. In the aspect of channel robust features, this paper introduces pitch-dependent features and pitch-dependent speaker model for the second stage recognition. Based on the first stage recognition to testing speech using GMM (Gaussian Mixture Model), the system uses GMM scores to decide if it needs to be recognized again. If it needs to, the system selects a few speakers from all of the speakers who participate in the first stage recognition for the second stage recognition. For each selected speaker, the system obtains 3 pitch-dependent results from his pitch-dependent speaker model, and then uses ANN (Artificial Neural Network) to unite the 3 pitch-dependent results and 1 GMM score for getting a fused result. The system makes the second stage recognition based on these fused results. The experiments show that the correct rate of two-stage recognition system based on MAP channel compensation technique and pitch-dependent features is 41.7% better than the baseline system for closed-set test.

Keywords: Channel Compensation, Channel Robustness, MAP, Speaker Identification

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Authors: Shun-Qi Zhang, Shu-Yang Zhang, Min Chen

Abstract:

Applying strong electric field on piezoelectric actuators, on one hand very significant electroelastic material nonlinear effects will occur, on the other hand piezo plates and shells may undergo large displacements and rotations. In order to give a precise prediction of piezolaminated smart structures under large electric field, this paper develops a finite element (FE) model accounting for both electroelastic material nonlinearity and geometric nonlinearity with large rotations based on the first order shear deformation (FSOD) hypothesis. The proposed FE model is applied to analyze a piezolaminated semicircular shell structure.

Keywords: Smart structures, piezolamintes, material nonlinearity, geometric nonlinearity, strong electric field.

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Authors: May A. Massoud

Abstract:

The availability of water in adequate quantity and quality is imperative for sustainable development. Worldwide, significant imbalance exists with regards to sustainable development particularly from a water and sanitation perspective. Water is a critical component of public health, and failure to supply safe water will place a heavy burden on the entire population. Although the 21st century has witnessed wealth and advanced development, it has not been realized everywhere. Billions of people are still striving to access the most basic human needs which are food, shelter, safe drinking water and adequate sanitation. The global picture conceals various inequalities particularly with regards to sanitation coverage in rural and urban areas. Currently, water scarcity and in particular water governance is the main challenge which will cause a threat to sustainable development goals. Within the context of water, sanitation and health, sustainable development is a confusing concept primarily when examined from the viewpoint of policy options for developing countries. This perspective paper aims to summarize and critically evaluate evidence of published studies in relation to water, sanitation and health and to identify relevant solutions to reduce public health impacts. Evidently, improving water and sanitation services will result in significant and lasting gains in health and economic development.

Keywords: developing countries, health, sanitation, sustainability, water

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Authors: A.A.Rohani, B.Hatami, L.Jokar, F.khorasheh, A.A.Safekordi

Abstract:

In industrial scale of Gas to Liquid (GTL) process in Fischer-Tropsch (FT) synthesis, a part of reactor outlet gases such as CO2 and CH4 as side reaction products, is usually recycled. In this study, the influence of CO2 and CH4 on the performance and selectivity of Co-Ru/Al2O3 catalyst is investigated by injection of these gases (0-20 vol. % of feed) to the feed stream. The effect of temperature and feed flow rate, are also inspected. The results show that low amounts of CO2 in the feed stream, doesn`t change the catalyst activity significantly but increasing the amount of CO2 (more than 10 vol. %) cause the CO conversion to decrease and the selectivity of heavy components to increase. Methane acts as an inert gas and doesn`t affect the catalyst performance. Increasing feed flow rate has negative effect on both CO conversion and heavy component selectivity. By raising the temperature, CO conversion will increase but there are more volatile components in the product. The effect of CO2 on the catalyst deactivation is also investigated carefully and a mechanism is suggested to explain the negative influence of CO2 on catalyst deactivation.

Keywords: Alumina, Carbon dioxide, Cobalt catalyst, Conversion, Fischer Tropsch, Selectivity

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Authors: A. Salsabili, M.Aghajani Mir, S.Saheri, Noor Ezlin Ahmad Basri

Abstract:

The main aims in this research are to study the solid waste generation in the Faculty of Engineering and Built Environment in the UKM and at the same time to determine composition and some of the waste characteristics likewise: moisture content, density, pH and C/N ratio. For this purpose multiple campaigns were conducted to collect the wastes produced in all hostels, faculties, offices and so on, during 24th of February till 2nd of March 2009, measure and investigate them with regard to both physical and chemical characteristics leading to highlight the necessary management policies. Research locations are Faculty of Engineering and the Canteen nearby that. From the result gained, the most suitable solid waste management solution will be proposed to UKM. The average solid waste generation rate in UKM is 203.38 kg/day. The composition of solid waste generated are glass, plastic, metal, aluminum, organic and inorganic waste and others waste. From the laboratory result, the average moisture content, density, pH and C/N ratio values from the solid waste generated are 49.74%, 165.1 kg/m3, 5.3, and 7:1 respectively. Since, the food waste (organic waste) were the most dominant component, around 62% from the total waste generated hence, the most suitable solid waste management solution is composting.

Keywords: Solid Waste, Waste Management, Characterizationand Composition

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Authors: Mikhail P. Strongin, Ragupathi Soundararajan

Abstract:

The purpose of this work is fast design optimization of the seal chamber. The study includes the mass transfer between lower and upper chamber on seal chamber for hot water application pumps. The use of Fluent 12.1 commercial code made it possible to capture complex flow with heat-mass transfer, radiation, Tailor instability, and buoyancy effect. Realizable k-epsilon model was used for turbulence modeling. Radiation heat losses were taken into account. The temperature distribution at seal region is predicted with respect to heat addition. Results show the possibilities of the model simplifications by excluding the water domain in low chamber from calculations. CFD simulations permit to improve seal chamber design to meet target water temperature around the seal. This study can be used for the analysis of different seal chamber configurations.

Keywords: CFD, heat transfer, seal chamber, high temperature water

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Authors: Tayfun Çay, Yaşar İnceyol, Abdurrahman Özbeyaz

Abstract:

Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.

Keywords: Genetic algorithm, land consolidation, landholding, land reallocation.

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Authors: Jianwei Ma, Diriba Gemechu

Abstract:

In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: Anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, Split Bregman Algorithm.

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Authors: Magdi M. Nabi, Ding-Li Yu

Abstract:

Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward and feedback control.

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Authors: Akash K. Walunj, Dipendu Bhunia, Samarth Gupta, Prabhat Gupta

Abstract:

Coupled shear walls consist of two shear walls connected intermittently by beams along the height. The behavior of coupled shear walls is mainly governed by the coupling beams. The coupling beams are designed for ductile inelastic behavior in order to dissipate energy. The base of the shear walls may be designed for elastic or ductile inelastic behavior. The amount of energy dissipation depends on the yield moment capacity and plastic rotation capacity of the coupling beams. In this paper, an analytical model of coupling beam was developed to calculate the rotations and moment capacities of coupling beam with conventional reinforcement.

Keywords: Design studies, computational model(s), case study/studies, modeling, coupling beam.

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Authors: N. A. Samat, D. F. Percy

Abstract:

The main aim of this study is to describe and introduce a method of numerical analysis in obtaining approximate solutions for the SIR-SI differential equations (susceptible-infectiverecovered for human populations; susceptible-infective for vector populations) that represent a model for dengue disease transmission. Firstly, we describe the ordinary differential equations for the SIR-SI disease transmission models. Then, we introduce the numerical analysis of solutions of this continuous time, discrete space SIR-SI model by simplifying the continuous time scale to a densely populated, discrete time scale. This is followed by the application of this numerical analysis of solutions of the SIR-SI differential equations to the estimation of relative risk using continuous time, discrete space dengue data of Kuala Lumpur, Malaysia. Finally, we present the results of the analysis, comparing and displaying the results in graphs, table and maps. Results of the numerical analysis of solutions that we implemented offers a useful and potentially superior model for estimating relative risks based on continuous time, discrete space data for vector borne infectious diseases specifically for dengue disease. 

Keywords: Dengue disease, disease mapping, numerical analysis, SIR-SI differential equations.

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Authors: D. Laiadi, A. Hasseine, A. Merzougui

Abstract:

In this work, Experimental tie-line results and solubility (binodal) curves were obtained for the ternary systems (water + acetic acid + methyl isobutyl ketone (MIBK)), (water + lactic acid+ methyl isobutyl ketone) at T = 294.15K and atmospheric pressure. The consistency of the values of the experimental tie-lines was determined through the Othmer-Tobias and Hands correlations. For the extraction effectiveness of solvents, the distribution and selectivity curves were plotted. In addition, these experimental tieline data were also correlated with NRTL model. The interaction parameters for the NRTL model were retrieved from the obtained experimental results by means of a combination of the homotopy method and the genetic algorithms.

Keywords: Liquid-liquid equilibria, homotopy methods, carboxylic acid, NRTL.

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Authors: T. C. Chu, S.H. Wu

Abstract:

This paper suggests ranking alternatives under fuzzy MCDM (multiple criteria decision making) via an centroid based ranking approach, where criteria are classified to benefit qualitative, benefit quantitative and cost quantitative ones. The ratings of alternatives versus qualitative criteria and the importance weights of all criteria are assessed in linguistic values represented by fuzzy numbers. The membership function for the final fuzzy evaluation value of each alternative can be developed through α-cuts and interval arithmetic of fuzzy numbers. The distance between the original point and the relative centroid is applied to defuzzify the final fuzzy evaluation values in order to rank alternatives. Finally a numerical example demonstrates the computation procedure of the proposed model.

Keywords: Fuzzy MCDM, Criteria, Fuzzy number, Ranking, Relative centroid.

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Authors: Dariush Jafari, Seyed Ali Jafari

Abstract:

The recommended limit for cadmium concentration in potable water is less than 0.005 mg/L. A continuous biosorption process using indigenous red seaweed, Gracilaria corticata, was performed to remove cadmium from the potable water. The process was conducted under fixed conditions and the breakthrough curves were achieved for three consecutive sorption-desorption cycles. A modeling based on Artificial Neural Network (ANN) was employed to fit the experimental breakthrough data. In addition, a simplified semi empirical model, Thomas, was employed for this purpose. It was found that ANN well described the experimental data (R2>0.99) while the Thomas prediction were a bit less successful with R2>0.97. The adjusted design parameters using the nonlinear form of Thomas model was in a good agreement with the experimentally obtained ones. The results approve the capability of ANN to predict the cadmium concentration in potable water.

Keywords: ANN, biosorption, cadmium, packed-bed, potable water.

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Authors: Wanna Saikaew, Pairat Kaewsarn, Wuthikorn Saikaew

Abstract:

The ability of pomelo peel, a natural biosorbent, to remove Cd(II) ions from aqueous solution by biosorption was investigated. The experiments were carried out by batch method at 25 °C. The influence of solution pH, initial cadmium ion concentrations and contact times were evaluated. Cadmium ion removal increased significantly as the pH of the solution increased from pH 1 to pH 5. At pH 5, the cadmium ion removal reached a maximum value. The equilibrium process was described well by the Langmuir isotherm model, with a maximum biosorption capacity of 21.83 mg/g. The biosorption was relatively quick, (approx. 20 min). Biosorption kinetics followed a pseudo-second-order model. The result showed that pomelo peel was effective as a biosorbent for removing cadmium ions from aqueous solution. It is a low cost material that shows potential to be applied in wastewater technology for remediation of heavy metal contamination.

Keywords: Pomelo peel, biosorption, Cadmium ions.

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Authors: Hatem Hajri, Mohamed-Cherif Rahal

Abstract:

Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions. Sensor fusion between Lidar and Radar aims at improving obstacle detection using advantages of the two sensors. The present paper proposes a real-time Lidar/Radar data fusion algorithm for obstacle detection and tracking based on the global nearest neighbour standard filter (GNN). This algorithm is implemented and embedded in an automative vehicle as a component generated by a real-time multisensor software. The benefits of data fusion comparing with the use of a single sensor are illustrated through several tracking scenarios (on a highway and on a bend) and using real-time kinematic sensors mounted on the ego and tracked vehicles as a ground truth.

Keywords: Ground truth, Hungarian algorithm, lidar Radar data fusion, global nearest neighbor filter.

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Authors: Jong Woo Kim, Go Bong Choi, Sang Hwan Son, Dae Shik Kim, Jung Chul Suh, Jong Min Lee

Abstract:

The Markov decision process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficulty of implementing the conventional DP approaches. The optimal schedule derived from suggested model is compared to several policies via Monte Carlo simulation. Validity of the solution and improvement in computational time are proved.

Keywords: Markov decision processes, Dynamic Programming, Monte Carlo simulation, Periodic replacement, Weibull distribution.

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

Abstract:

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: K. Cormican, G. Coppola, S. Farina

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Knowledge management is a critical component of competitive success in service organizations. Knowledge management centers on creating new knowledge and utilizing existing knowledge. While utilizing existing knowledge relates to input and control and can lead to a reduction in costs; creating new knowledge relates to output and growth and can lead to an increase in revenue. Therefore managers must ensure that they can successfully optimize the knowledge and talent in their organizations. To do this they and must try to develop an environment that promotes the generation, acquisition, transfer and use of valuable knowledge in creative ways. However knowledge management is complex and diverse. Research suggests that organizations in general and SMEs in particular are finding it difficult to implement successful knowledge management initiatives. Our research attempts to understand whether organizations are adopting best practice initiatives in their organizations. This paper presents findings from an exploratory study of 139 SMEs operating in the tourism sector across Europe. The goals of the survey is to assess the level of awareness of knowledge and talent management strategies and methodologies and to determine whether the responding companies implement best practice knowledge management initiatives in their organizations Analysis of the findings from the study are presented and discussed.

Keywords: service sector, small enterprise, success factors, survey

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Authors: Laura Lukmanto, Harya Widiputra, Lukas

Abstract:

Studies in economics domain tried to reveal the correlation between stock markets. Since the globalization era, interdependence between stock markets becomes more obvious. The Dynamic Interaction Network (DIN) algorithm, which was inspired by a Gene Regulatory Network (GRN) extraction method in the bioinformatics field, is applied to reveal important and complex dynamic relationship between stock markets. We use the data of the stock market indices from eight countries around the world in this study. Our results conclude that DIN is able to reveal and model patterns of dynamic interaction from the observed variables (i.e. stock market indices). Furthermore, it is also found that the extracted network models can be utilized to predict movement of the stock market indices with a considerably good accuracy.

Keywords: complex dynamic relationship, dynamic interaction network, interactive stock markets, stock market interdependence.

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Authors: M.R.Mansoujian, A.Rohani, N.Hedayat , M.Qamari, M. Osroosh

Abstract:

Permanent rivers are the main sources of renewable water supply for the croplands under the irrigation and drainage schemes. They are also the major source of sediment loads transport into the storage reservoirs of the hydro-electrical dams, diversion weirs and regulating dams. Sedimentation process results from soil erosion which is related to poor watershed management and human intervention ion in the hydraulic regime of the rivers. These could change the hydraulic behavior and as such, leads to riverbed and river bank scouring, the consequences of which would be sediment load transport into the dams and therefore reducing the flow discharge in water intakes. The present paper investigate sedimentation process by varying the Manning coefficient "n" by using the SHARC software along the watercourse in the Dez River. Results indicated that the optimum "n" within that river range is 0.0315 at which quantity minimum sediment loads are transported into the Eastern intake. Comparison of the model results with those obtained by those from the SSIIM software within the same river reach showed a very close proximity between them. This suggests a relative accuracy with which the model can simulate the hydraulic flow characteristics and therefore its suitability as a powerful analytical tool for project feasibility studies and project implementation.

Keywords: Sediment transport, Manning coefficient, Eastern Intake, SHARC, Dez River.

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Authors: Yu-Sheng Lu, Chung-Hsin Cheng, Shuen-Shing Jan

Abstract:

This paper presents the design and implementation of a sliding-mod controller for tracking servo of optical disk drives. The tracking servo is majorly subject to two disturbance sources: radial run-out and shock. The lateral run-out disturbance is mostly repeatable, and a model of such disturbance is incorporated into the controller design to effectively compensate for it. Meanwhile, as a shock disturbance is usually non-repeatable and unpredictable, the sliding-mode controller is employed for its robustness to abrupt perturbations. As a result, a sliding-mode controller design based on the internal model principle is tailored for tracking servo of optical disk drives in order to deal with these two major disturbances. Experimental comparative studies are conducted to investigate the effectiveness of the specially designed controller.

Keywords: Mechatronics, optical disk drive, sliding-mode control, servo systems.

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Authors: Mouna Hamed, Ammar B. Brahim

Abstract:

The objective of this work was to develop a theoretical model to study the dynamic thermal behavior of a flat plate solar collector integrated with a phase change material (PCM). The PCM acted as a heat source for the solar system during low intensity solar radiation and night. The energy balance equations for the various components of the collector as well as for the PCM were formulated and numerically solved using Matlab computational program. The effect of natural convection on heat during the melting process was taken into account by using an effective thermal conductivity. The model was used to investigate the effect of inlet water temperature, water mass flow rate, and PCM thickness on the outlet water temperature and the melt fraction during charging and discharging modes. A comparison with a collector without PCM was made. Results showed that charging and discharging processes of PCM have six stages. The adding of PCM caused a decrease in temperature during charge and an increase during discharge. The rise was most enhanced for higher inlet water temperature, PCM thickness and for lower mass flow rate. Analysis indicated that the complete melting time was shorter than the solidification time due to the high heat transfer coefficient during melting. The increases in PCM height and mass flow rate were not linear with the melting and solidification times.

Keywords: Thermal energy storage, phase change material, melting, solidification.

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Authors: Mouna Hamed, Ammar B. Brahim

Abstract:

The objective of this work was to develop a theoretical model to study the dynamic thermal behavior of a flat plate solar collector integrated with a phase change material (PCM). The PCM acted as a heat source for the solar system during low intensity solar radiation and night. The energy balance equations for the various components of the collector as well as for the PCM were formulated and numerically solved using MATLAB computational program. The effect of natural convection on heat during the melting process was taken into account by using an effective thermal conductivity. The model was used to investigate the effect of inlet water temperature, water mass flow rate, and PCM thickness on the outlet water temperature and the melt fraction during charging and discharging modes. A comparison with a collector without PCM was made. Results showed that charging and discharging processes of PCM have six stages. The adding of PCM caused a decrease in temperature during charge and an increase during discharge. The rise was most enhanced for higher inlet water temperature, PCM thickness and for lower mass flow rate. Analysis indicated that the complete melting time was shorter than the solidification time due to the high heat transfer coefficient during melting. The increases in PCM height and mass flow rate were not linear with the melting and solidification times.

Keywords: Thermal energy storage, phase change material, melting, solidification.

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Authors: W. Jay Gabbard, Saundra H. Starks, Jeremiah Jaggers, Amy C. Cappiccie

Abstract:

An ethical mandate of the social work profession in the United States is that BSW and MSW graduates are sufficiently prepared to both understand diverse cultural values and beliefs and offer services that are culturally sensitive and relevant to clients. This skill set is particularly important for social workers in the 21st Century, given the increasing globalization of the U.S. and world. The purpose of this paper is to outline a pedagogical model for teaching cultural competency that resulted in a significant increase in cultural competency for MSW graduates at Western Kentucky University (WKU). More specifically, this model is predicated on five specific culturally sensitive principles and activities that were found to be highly effective in conveying culturally relevant knowledge and skills to MSW students at WKU. Future studies can assess the effectiveness of these principles in other MSW programs across the U.S. and abroad.

Keywords: Cultural Competence, Social Work, Teaching

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Authors: Mehdi Shami Zanjani, Roshanak Rouzbehani, Hosein Dabbagh

Abstract:

Although current competitive challenges induced by today-s digital economy place their main emphasis on organizational knowledge, customer knowledge has been overlooked. On the other hand, the business community has finally begun to realize the important role customer knowledge can play in the organizational boundaries of the corporate arena. As a result, there is an emerging market for the tools and utilities whose objective is to provide the intelligence for knowledge sharing between the businesses and their customers. In this paper, we present a conceptual model of customer knowledge management by identifying and analyzing the existing tools in the market. The focus will be upon the emerging British dotcom industry whose customer based B2C behavior has been an influential part of the knowledge based intelligence tools in existence today.

Keywords: Customer knowledge, customer knowledge management, knowledge management, B2C E-commerce.

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Authors: M. M. Karkhanehchi, A. Ammani

Abstract:

A simple analytical model has been developed to optimize biasing conditions for obtaining maximum linearity among lattice-matched, pseudomorphic and metamorphic HEMT types as well as enhancement and depletion HEMT modes. A nonlinear current-voltage model has been simulated based on extracted data to study and select the most appropriate type and mode of HEMT in terms of a given gate-source biasing voltage within the device so as to employ the circuit for the highest possible output current or voltage linear swing. Simulation results can be used as a basis for the selection of optimum gate-source biasing voltage for a given type and mode of HEMT with regard to a circuit design. The consequences can also be a criterion for choosing the optimum type or mode of HEMT for a predetermined biasing condition.

Keywords: Biasing, characteristic, linearity, simulation.

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Authors: B. Selma, S. Chouraqui

Abstract:

The pancreas is an elongated organ that extends across the abdomen, below the stomach. In addition, it secretes certain enzymes that aid in food digestion. The pancreas also manufactures hormones responsible for regulating blood glucose levels. In the present paper, we propose a mathematical model to study the homeostasis of glucose and insulin in healthy human, and a simulation of this model, which depicts the physiological events after a meal, will be represented in ordinary humans. The aim of this paper is to design an algorithm which regulates the level of glucose in the blood. The algorithm applied the concept of expert system for performing an algorithm control in the form of an "active" used to prescribe the rate of insulin infusion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. The results showed a performance of the control system.

Keywords: Modeling, algorithm, regulation, glucose-insulin, blood, control system.

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Authors: Yaojun Wang, Yaoqing Wang

Abstract:

Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: Case-based reasoning, decision tree, stock selection, machine learning.

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Authors: R. Balamurugan, A. M. Natarajan, K. Premalatha

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Microarray gene expression data play a vital in biological processes, gene regulation and disease mechanism. Biclustering in gene expression data is a subset of the genes indicating consistent patterns under the subset of the conditions. Finding a biclustering is an optimization problem. In recent years, swarm intelligence techniques are popular due to the fact that many real-world problems are increasingly large, complex and dynamic. By reasons of the size and complexity of the problems, it is necessary to find an optimization technique whose efficiency is measured by finding the near optimal solution within a reasonable amount of time. In this paper, the algorithmic concepts of the Particle Swarm Optimization (PSO), Shuffled Frog Leaping (SFL) and Cuckoo Search (CS) algorithms have been analyzed for the four benchmark gene expression dataset. The experiment results show that CS outperforms PSO and SFL for 3 datasets and SFL give better performance in one dataset. Also this work determines the biological relevance of the biclusters with Gene Ontology in terms of function, process and component.

Keywords: Particle swarm optimization, Shuffled frog leaping, Cuckoo search, biclustering, gene expression data.

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