Search results for: numerical analysis method.

Authors: M.R. Safizadeh, M. Hussein, K. F. Samat, M.S. Che Kob, M.S. Yaacob, M.Z. Md Zain

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The aim of this paper is to present the kinematic analysis and mechanism design of an assistive robotic leg for hemiplegic and hemiparetic patients. In this work, the priority is to design and develop the lightweight, effective and single driver mechanism on the basis of experimental hip and knee angles- data for walking speed of 1 km/h. A mechanism of cam-follower with three links is suggested for this purpose. The kinematic analysis is carried out and analysed using commercialized MATLAB software based on the prototype-s links sizes and kinematic relationships. In order to verify the kinematic analysis of the prototype, kinematic analysis data are compared with the experimental data. A good agreement between them proves that the anthropomorphic design of the lower extremity exoskeleton follows the human walking gait.

Keywords: Kinematic analysis, assistive robotic leg, lower extremity exoskeleton, cam-follower mechanism.

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Authors: Bin Mu, Site Li, Shijin Yuan

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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model.

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Authors: Seema Biday, Udhav Bhosle

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Repeated observation of a given area over time yields potential for many forms of change detection analysis. These repeated observations are confounded in terms of radiometric consistency due to changes in sensor calibration over time, differences in illumination, observation angles and variation in atmospheric effects. This paper demonstrates applicability of an empirical relative radiometric normalization method to a set of multitemporal cloudy images acquired by Resourcesat1 LISS III sensor. Objective of this study is to detect and remove cloud cover and normalize an image radiometrically. Cloud detection is achieved by using Average Brightness Threshold (ABT) algorithm. The detected cloud is removed and replaced with data from another images of the same area. After cloud removal, the proposed normalization method is applied to reduce the radiometric influence caused by non surface factors. This process identifies landscape elements whose reflectance values are nearly constant over time, i.e. the subset of non-changing pixels are identified using frequency based correlation technique. The quality of radiometric normalization is statistically assessed by R2 value and mean square error (MSE) between each pair of analogous band.

Keywords: Correlation, Frequency domain, Multitemporal, Relative Radiometric Correction

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Authors: Gye-rok Jeon, Jae-hee Jung, In-cheol Kim, Ah-young Jeon, Sang-hwa Yoon, Jung-man Son, Jae-hyung Kim, Soo-young Ye, Jung-hoon Ro, Dong-hyun Kim, Chul-han Kim

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A analysis on the conventional the blood pressure estimation method using an oscillometric sphygmomanometer was performed through a computer simulation using an arterial pressure-volume (APV) model. Traditionally, the maximum amplitude algorithm (MAP) was applied on the oscillation waveforms of the APV model to obtain the mean arterial pressure and the characteristic ratio. The estimation of mean arterial pressure and characteristic ratio was significantly affected with the shape of the blood pressure waveforms and the cutoff frequency of high-pass filter (HPL) circuitry. Experimental errors are due to these effects when estimating blood pressure. To find out an algorithm independent from the influence of waveform shapes and parameters of HPL, the volume oscillation of the APV model and the phase shift of the oscillation with fast fourier transform (FFT) were testified while increasing the cuff pressure from 1 mmHg to 200 mmHg (1 mmHg per second). The phase shift between the ranges of volume oscillation was then only observed between the systolic and the diastolic blood pressures. The same results were also obtained from the simulations performed on two different the arterial blood pressure waveforms and one hyperthermia waveform.

Keywords: Arterial blood pressure, oscillometric method

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Authors: Amir. AL-Haddad, Hisham. Ettouney, Samiya. Saqer

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The main objectives of this paper are to measure pollutants concentrations in the oil refinery area in Kuwait over three periods during one year, obtain recent emission inventory for the three refineries of Kuwait, use AERMOD and the emission inventory to predict pollutants concentrations and distribution, compare model predictions against measured data, and perform numerical experiments to determine conditions at which emission rates and the resulting pollutant dispersion is below maximum allowable limits.

Keywords: Emissions, ISCST3 model, Modeling, Pollutants, Refinery

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Authors: Zongqing Lu

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It has proved that nonlinear diffusion and bilateral filtering (BF) have a closed connection. Early effort and contribution are to find a generalized representation to link them by using adaptive filtering. In this paper a new further relationship between nonlinear diffusion and bilateral filtering is explored which pays more attention to numerical calculus. We give a fresh idea that bilateral filtering can be accelerated by multigrid (MG) scheme which likes the nonlinear diffusion, and show that a bilateral filtering process with large kernel size can be approximated by a nonlinear diffusion process based on full multigrid (FMG) scheme.

Keywords: Bilateral filter, multigrid

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Authors: Nur Atiqah Rochin Demong, Jie Lu, Farookh Khadeer Hussain

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Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expert-s opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of experts- experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper.

Keywords: Uncertainty factors, data mining, multidimensional data model, risk analysis.

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Authors: George Yungchih Wang

Abstract:

Real options theory suggests that managerial flexibility embedded within irreversible investments can account for a significant value in project valuation. Although the argument has become the dominant focus of capital investment theory over decades, yet recent survey literature in capital budgeting indicates that corporate practitioners still do not explicitly apply real options in investment decisions. In this paper, we explore how real options decision criteria can be transformed into equivalent capital budgeting criteria under the consideration of uncertainty, assuming that underlying stochastic process follows a geometric Brownian motion (GBM), a mixed diffusion-jump (MX), or a mean-reverting process (MR). These equivalent valuation techniques can be readily decomposed into conventional investment rules and “option impacts", the latter of which describe the impacts on optimal investment rules with the option value considered. Based on numerical analysis and Monte Carlo simulation, three major findings are derived. First, it is shown that real options could be successfully integrated into the mindset of conventional capital budgeting. Second, the inclusion of option impacts tends to delay investment. It is indicated that the delay effect is the most significant under a GBM process and the least significant under a MR process. Third, it is optimal to adopt the new capital budgeting criteria in investment decision-making and adopting a suboptimal investment rule without considering real options could lead to a substantial loss in value.

Keywords: real options, capital budgeting, geometric Brownianmotion, mixed diffusion-jump, mean-reverting process

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Authors: Natalia Polkanova, Sergey Kazakov

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In the second decade of the XXI century the role of tourism destination attractiveness is becoming increasingly important for destination management. Competition in tourism market moves from ordinary service quality to provision of unforgettable emotional experience for tourists. The main purpose of the present study is to identify the perception of the tourism destinations based on the number of factors related to its tourist attractiveness. The content analysis method was used to analyze the on-line tourist feedback data immensely available in Social Media and in travel related sites. The collected data made it possible to procure the information which is necessary to understand the perceived attractiveness of the destinations and key destination appeal factors that are important for Russian leisure travelers. Results of the present study demonstrate key attractiveness factors or destination ‘properties’ that were unveiled as the most important for Russian leisure tourists. The study targeted five main Spanish tourism destinations that initially were determined by in-depth interview with a number of Russian nationals who had visited Spain at least once. The research results can be useful for Spanish Tourism Organization Representation office in Russia as well as for the other national tourism organizations in order to promote their respective destinations for Russian travelers focusing on main attractiveness factors identified in this study.

Keywords: Tourism destination, destination attractiveness, destination competitiveness, content analysis, unstructured image.

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Authors: Mohanad Alhabo, Naveed Nawaz

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The ongoing call or data session must be maintained to ensure a good quality of service. This can be accomplished by performing handover procedure while the user is on the move. However, dense deployment of small cells in 5G networks is a challenging issue due to the extensive number of handovers. In this paper, a neighbour cell list method is proposed to reduce the number of target small cells and hence minimizing the number of handovers. The neighbour cell list is built by omitting cells that could cause an unnecessary handover and/or handover failure because of short time of stay of a user in these cells. A multi-attribute decision making technique, simple additive weighting, is then applied to the optimized neighbour cell list. The performance of the proposed method is analysed and compared with that of the existing methods. Results disclose that our method decreases the candidate small cell list, unnecessary handovers, handover failure and short time of stay cells compared to the competitive method.

Keywords: Handover, HetNets, MADM, small cells.

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Authors: H. El Fadili, K. Zenkouar, H. Qjidaa

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This paper proposes a neural network weights and topology optimization using genetic evolution and the backpropagation training algorithm. The proposed crossover and mutation operators aims to adapt the networks architectures and weights during the evolution process. Through a specific inheritance procedure, the weights are transmitted from the parents to their offsprings, which allows re-exploitation of the already trained networks and hence the acceleration of the global convergence of the algorithm. In the preprocessing phase, a new feature extraction method is proposed based on Legendre moments with the Maximum entropy principle MEP as a selection criterion. This allows a global search space reduction in the design of the networks. The proposed method has been applied and tested on the well known MNIST database of handwritten digits.

Keywords: Genetic algorithm, Legendre Moments, MEP, Neural Network.

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Authors: Promise A. Azor, Avievie Igodo, Esabai M. Ase

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The paper merged the return of premium clause and voluntary contributions to investigate retirees’ investment plan in a defined contributory (DC) pension scheme with a portfolio comprising of a risk-free asset and a risky asset whose price process is described by geometric Brownian motion (GBM). The paper considers additional voluntary contributions paid by members, charge on balance by pension fund administrators and the mortality risk of members of the scheme during the accumulation period by introducing return of premium clause. To achieve this, the Weilbull mortality force function is used to establish the mortality rate of members during accumulation phase. Furthermore, an optimization problem from the Hamilton Jacobi Bellman (HJB) equation is obtained using dynamic programming approach. Also, the Legendre transformation method is used to transform the HJB equation which is a nonlinear partial differential equation to a linear partial differential equation and solves the resultant equation for the value function and the optimal distribution plan under logarithm utility function. Finally, numerical simulations of the impact of some important parameters on the optimal distribution plan were obtained and it was observed that the optimal distribution plan is inversely proportional to the initial fund size, predetermined interest rate, additional voluntary contributions, charge on balance and instantaneous volatility.

Keywords: Legendre transform, logarithm utility, optimal distribution plan, return clause of premium, charge on balance, Weibull mortality function.

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Authors: Jafar Abbaszadeh Chekan, Kaveh Merat, Hassan Zohoor

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In this study the regional stability of a rotor system which is supported on rolling bearings with radial clearance is studied. The rotor is assumed to be rigid. Due to radial clearance of bearings and dynamic configuration of system, each rolling elements of bearings has the possibility to be in contact with both of the races (under compression) or lose its contact. As a result, this change in dynamic of the system makes it to be known as switching system which is a type of Hybrid systems. In this investigation by adopting Multiple Lyapunov Function theorem and using Hamiltonian function as a candidate Lyapunov function, the stability of the system is studied. The purpose of this study is to inspect the regional stability of rotor-roller bearing and rotor-ball bearing systems.

Keywords: Stability analysis, Rotor-rolling bearing systems, Switching systems, Multiple Lyapunov Function Method

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Authors: Iva Košek Bartošová, Andrea Jokešová, Eva Kozlová, Helena Matějová

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The paper presents results of a research team from Faculty of Education, University of Hradec Králové in the Czech Republic. It introduces with the most reading methods used in the 1^st classes of a primary school and presents results of a pilot research focused on mastering reading techniques and the quality of reading comprehension of pupils in the first half of a school year during training in teaching reading by an analytic-synthetic method and by a genetic method. These methods of practicing reading skills are the most used ones in the Czech Republic. During the school year 2015/16 there has been a measurement made of two groups of pupils of the 1^st year and monitoring of quantitative and qualitative parameters of reading pupils’ outputs by several methods. Both of these methods are based on different theoretical basis and each of them has a specific educational and methodical procedure. This contribution represents results during a piloting project and draws pilot conclusions which will be verified in the subsequent broader research at the end of the school year of the first class of primary school.

Keywords: Analytic-synthetic method of reading, genetic method of reading, reading comprehension, reading literacy, reading methods, reading speed.

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Authors: Yang Liu, Hong Li, Siriguleng He, Wei Gao, Zhichao Fang

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In this paper, the C1-conforming finite element method is analyzed for a class of nonlinear fourth-order hyperbolic partial differential equation. Some a priori bounds are derived using Lyapunov functional, and existence, uniqueness and regularity for the weak solutions are proved. Optimal error estimates are derived for both semidiscrete and fully discrete schemes.

Keywords: Nonlinear fourth-order hyperbolic equation, Lyapunov functional, existence, uniqueness and regularity, conforming finite element method, optimal error estimates.

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Authors: M. A. Beisenbi, N. M. Kissikova, S. E. Beisembina, S. T. Suleimenova, S. A. Kaliyeva

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The paper proposes a method for constructing a self-organizing control system for unstable and deterministic chaotic processes in the class of catastrophe “hyperbolic umbilic” for objects with m-inputs and n-outputs. The self-organizing control system is investigated by the universal gradient-velocity method of Lyapunov vector-functions. The conditions for self-organization of the control system in the class of catastrophes “hyperbolic umbilic” are shown in the form of a system of algebraic inequalities that characterize the aperiodic robust stability in the stationary states of the system.

Keywords: Gradient-velocity method of Lyapunov vector-functions, hyperbolic umbilic, self-organizing control system, stability.

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Authors: M. Amir Abas, M. Dahlui

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This paper presents the development of analysis tools for Home Agriculture project. The tools are required for monitoring the condition of greenhouse which involves two components: measurement hardware and data analysis engine. Measurement hardware is functioned to measure environment parameters such as temperature, humidity, air quality, dust and etc while analysis tool is used to analyse and interpret the integrated data against the condition of weather, quality of health, irradiance, quality of soil and etc. The current development of the tools is completed for off-line data recorded technique. The data is saved in MMC and transferred via ZigBee to Environment Data Manager (EDM) for data analysis. EDM converts the raw data and plot three combination graphs. It has been applied in monitoring three months data measurement for irradiance, temperature and humidity of the greenhouse..

Keywords: Monitoring, Environment, Greenhouse, Analysis tools

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Authors: S. H. Yahaya, J. M. Ali, M. R. Arham

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This paper presents the analysis of duct design using static and dynamic approaches. The static approach is used to find out applicability between the design and material applied. The material used in this paper is Thermoplastic Olefins (TPO). For the dynamic approach, the focusing is only on the CFD simulations. The fatigue life in this design and material applied also covered.

Keywords: CFD, structural analysis, fluid analysis, duct design, fatigue life

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Authors: Nurfirdawati Muhamad Hanafi, Azmanirah Ab Rahman, Marina Ibrahim Mukhtar, Jamil Ahmad, Sarebah Warman

Abstract:

This study was conducted to generate empirical evidence on validity and reliability of the item of Competency Assessment Implementation (CAI) Instrument using Rasch Model for polythomous data aided by Winstep software version 3.68. The construct validity was examined by analyzing the point-measure correlation index (PTMEA), infit and outfit MNSQ values; meanwhile the reliability was examined by analyzing item reliability index. A survey technique was used as the major method with the CAI instrument on 156 teachers from vocational schools. The results have shown that the reliability of CAI Instrument items were between 0.80 and 0.98. PTMEA Correlation is in positive values, in which the item is able to distinguish between the ability of the respondent. Statistical data obtained show that out of 154 items, 12 items from the instrument suggested to be omitted. This study is hoped could bring a new direction to the process of data analysis in educational research.

Keywords: Competency Assessment, Reliability, Validity, Item Analysis.

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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: A. Ouanane, A. Serir

Abstract:

In this paper, a novel algorithm based on Ridgelet Transform and support vector machine is proposed for human action recognition. The Ridgelet transform is a directional multi-resolution transform and it is more suitable for describing the human action by performing its directional information to form spatial features vectors. The dynamic transition between the spatial features is carried out using both the Principal Component Analysis and clustering algorithm K-means. First, the Principal Component Analysis is used to reduce the dimensionality of the obtained vectors. Then, the kmeans algorithm is then used to perform the obtained vectors to form the spatio-temporal pattern, called set-of-labels, according to given periodicity of human action. Finally, a Support Machine classifier is used to discriminate between the different human actions. Different tests are conducted on popular Datasets, such as Weizmann and KTH. The obtained results show that the proposed method provides more significant accuracy rate and it drives more robustness in very challenging situations such as lighting changes, scaling and dynamic environment

Keywords: Human action, Ridgelet Transform, PCA, K-means, SVM.

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Authors: Aresh Vikram Singh, Sarika Nagar

Abstract:

The tamarind based resin containing hydroxypropane sulphonic acid groups has been synthesized and their adsorption behavior for heavy metal ions has been investigated using batch and column experiments. The hydroxypropane sulphonic acid group has been incorporated onto tamarind by a modified Porath's method of functionalisation of polysaccharides. The tamarind hydroxypropane sulphonic acid (THPSA) resin can selectively remove of heavy metal ions, which are contained in industrial wastewater. The THPSA resin was characterized by FTIR and thermogravimetric analysis. The effects of various adsorption conditions, such as pH, treatment time and adsorbent dose were also investigated. The optimum adsorption condition was found at pH 6, 120 minutes of equilibrium time and 0.1 gram of resin dose. The orders of distribution coefficient values were determined.

Keywords: Distribution coefficient, industrial wastewater, polysaccharides, tamarind hydroxypropane sulphonic acid resin, thermogravimetric analysis.

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Authors: Stephen Karungaru, Minoru Fukumi, Norio Akamatsu

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In this paper, we propose a morphing method by which face color images can be freely transformed. The main focus of this work is the transformation of one face image to another. This method is fully automatic in that it can morph two face images by automatically detecting all the control points necessary to perform the morph. A face detection neural network, edge detection and medium filters are employed to detect the face position and features. Five control points, for both the source and target images, are then extracted based on the facial features. Triangulation method is then used to match and warp the source image to the target image using the control points. Finally color interpolation is done using a color Gaussian model that calculates the color for each particular frame depending on the number of frames used. A real coded Genetic algorithm is used in both the image warping and color blending steps to assist in step size decisions and speed up the morphing. This method results in ''very smooth'' morphs and is fast to process.

Keywords: color transition, genetic algorithms morphing, warping

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Authors: Congmin Z. Xie, Terry Healy, Peter Robinson, Kevin Stewart

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An HPLC-UV analytical method was developed to determine ethylenediaminetetraacetic acid (EDTA) in dairy wastewater and surface water. The optimizing separation was achieved by reversed–phase ion-pair liquid chromatography on a C18 column using methanol as mobile phase solvent, tetrabutylammonium bromide as the ion-pair reagent in pH 3.3 formate buffer solution at a flow rate of 0.9 mL min-1 with a UV detector at 265 nm. No interference of Ca, Mg or NO3 - was detected. Method performance was evaluated in terms of linearity, repeatability and reproducibility. The method detection limit was 5 μg L-1. The contents of EDTA in dairy effluents were 72 ~ 261 μg L-1 at a large dairy site. A change of EDTA concentration was observed downstream of the dairy effluent discharge, but this was well under the predicted no effect concentration for aquatic ecosystem.

Keywords: Dairy wastewater, EDTA, HPLC, surface water.

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Authors: Loay A. Altamimi

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Collaborative technologies or software known as groupware are key enabling tools for communication, collaboration and co-ordination among individuals, work groups and businesses. Available reviews of the groupware literature are very few, and mostly neither systematic nor recent. This paper is an effort to fill this gap, and to provide researchers, with a more up-to-date and wide systematic literature review. For this purpose, 1087 scholarly articles, published from 1990 to 2013, on the topic of groupware, were collected by the literature search. The study here adopted the systematic approach of lexical analysis for the analysis of those articles.

Keywords: Lexical Analysis, Literature review, Groupware, collaborative Software.

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Authors: Kang-Gyu Park, Sun-Jong Park, Hong Jae Yim, Hyo-Gyung Kwak

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This paper attempts to evaluate the effect of fire damage on concrete by using nonlinear resonance vibration method, one of the nonlinear nondestructive method. Concrete exhibits not only nonlinear stress-strain relation but also hysteresis and discrete memory effect which are contained in consolidated materials. Hysteretic materials typically show the linear resonance frequency shift. Also, the shift of resonance frequency is changed according to the degree of micro damage. The degree of the shift can be obtained through nonlinear resonance vibration method. Five exposure scenarios were considered in order to make different internal micro damage. Also, the effect of post-fire-curing on fire-damaged concrete was taken into account to conform the change in internal damage. Hysteretic nonlinearity parameter was obtained by amplitudedependent resonance frequency shift after specific curing periods. In addition, splitting tensile strength was measured on each sample to characterize the variation of residual strength. Then, a correlation between the hysteretic nonlinearity parameter and residual strength was proposed from each test result.

Keywords: Fire damaged concrete, nonlinear resonance vibration method, nonlinearity parameter, post-fire-curing, splitting tensile strength.

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Authors: S. Pattanapairoj, D. Chetchotsak

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This paper proposed classification models that would be used as a proxy for hard disk drive (HDD) functional test equitant which required approximately more than two weeks to perform the HDD status classification in either “Pass" or “Fail". These models were constructed by using committee network which consisted of a number of single neural networks. This paper also included the method to solve the problem of sparseness data in failed part, which was called “enforce learning method". Our results reveal that the constructed classification models with the proposed method could perform well in the sparse data conditions and thus the models, which used a few seconds for HDD classification, could be used to substitute the HDD functional tests.

Keywords: Sparse data, Classifications, Committee network

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Authors: Weizhi Xu, Zhiyong Liu, Dongrui Fan, Shuai Jiao, Xiaochun Ye, Fenglong Song, Chenggang Yan

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Many-core GPUs provide high computing ability and substantial bandwidth; however, optimizing irregular applications like SpMV on GPUs becomes a difficult but meaningful task. In this paper, we propose a novel method to improve the performance of SpMV on GPUs. A new storage format called HYB-R is proposed to exploit GPU architecture more efficiently. The COO portion of the matrix is partitioned recursively into a ELL portion and a COO portion in the process of creating HYB-R format to ensure that there are as many non-zeros as possible in ELL format. The method of partitioning the matrix is an important problem for HYB-R kernel, so we also try to tune the parameters to partition the matrix for higher performance. Experimental results show that our method can get better performance than the fastest kernel (HYB) in NVIDIA-s SpMV library with as high as 17% speedup.

Keywords: GPU, HYB-R, Many-core, Performance Tuning, SpMV

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Authors: P. Wlodarczak, J. Soar, M. Ally

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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: Social Media, text mining, knowledge discovery, predictive analysis, machine learning.

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Authors: Choon Ki Ahn, Jung Hun Park, Wook Hyun Kwon

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CEMTool is a command style design and analyzing package for scientific and technological algorithm and a matrix based computation language. In this paper, we present new 2D & 3D finite element method (FEM) packages for CEMTool. We discuss the detailed structures and the important features of pre-processor, solver, and post-processor of CEMTool 2D & 3D FEM packages. In contrast to the existing MATLAB PDE Toolbox, our proposed FEM packages can deal with the combination of the reserved words. Also, we can control the mesh in a very effective way. With the introduction of new mesh generation algorithm and fast solving technique, our FEM packages can guarantee the shorter computational time than MATLAB PDE Toolbox. Consequently, with our new FEM packages, we can overcome some disadvantages or limitations of the existing MATLAB PDE Toolbox.

Keywords: CEMTool, Finite element method (FEM), Numericalanalysis, Partial differential equation (PDE)

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