Search results for: optimal estimation

Authors: Victor A. Naumenko, Yuriy A. Tyulenev, Alla A. Kushch

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The objective of current issue was to develop a model of testicular herpes simplex virus (HSV) type I infection for assessment of viral effect on fertility. 56 male mice were inoculated intraperitoneally with different concentrations of HSV on 8 day post partum. It was revealed that the optimal dose was 100 plaque forming units per mice as it provided testicular infection in 100% of survivors. HSV proteins were detected both in somatic and germ cells (spermatogonia, spermatocytes, spermatides). Although DNA load in testis was descending from 3 to 28 days post infection only 12.5% of infected males had offspring after mating with uninfected females comparing to 87.5% in control (p=0.012). These results are the first direct evidence for HSV impact in male sterility. Prepuberal mice appeared to be a suitable model for investigation of pathogenesis of virus-associated fertility disorders.

Keywords: Herpes simplex virus type I, male fertility, prepuberal mice, spermatogenesis.

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Authors: H.S. Kim

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In this study, control performance of a smart base isolation system consisting of a friction pendulum system (FPS) and a magnetorheological (MR) damper has been investigated. A fuzzy logic controller (FLC) is used to modulate the MR damper so as to minimize structural acceleration while maintaining acceptable base displacement levels. To this end, a multi-objective optimization scheme is used to optimize parameters of membership functions and find appropriate fuzzy rules. To demonstrate effectiveness of the proposed multi-objective genetic algorithm for FLC, a numerical study of a smart base isolation system is conducted using several historical earthquakes. It is shown that the proposed method can find optimal fuzzy rules and that the optimized FLC outperforms not only a passive control strategy but also a human-designed FLC and a conventional semi-active control algorithm.

Keywords: Fuzzy logic controller, genetic algorithm, MR damper, smart base isolation system

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Authors: Zhengkun Guo, Yanbin Li, Wenqing Wang, Bo Zou

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Active radar and sonar systems often report Doppler measurements in addition to the position measurements such as range and bearing. The tracker can perform better by making full use of the Doppler measurements. However, due to the high nonlinearity of the Doppler measurements with respect to the target state in the Cartesian coordinate systems, those measurements are not always fully exploited. This paper mainly focuses on dealing with the Doppler measurements as well as the position measurements in Polar coordinates. The Statically Fused Converted Position and Doppler Measurements Kalman Filter (SF-CMKF) with additive debiased measurement conversion has been presented. However, the exact compensation for the bias of the measurement conversion are multiplicative and depend on the statistics of the cosine of the angle measurement errors. As a result, the consistency and performance of the SF-CMKF may be suboptimal in the large angle error situations. In this paper, the multiplicative unbiased position and Doppler measurement conversion for two-dimensional (Polar-to-Cartesian) tracking are derived, and the SF-CMKF is improved by using those conversion. Monte Carlo simulations are presented to demonstrate the statistic consistency of the multiplicative unbiased conversion and the superior performance of the modified SF-CMKF (SF-UCMKF).

Keywords: Measurement conversion, Doppler, Kalman filter, estimation, tracking.

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Authors: Sukrit Shankar, Chetana Shanta Patsa, K. Pardha Saradhi, Jaydev Sharma

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Fractional Fourier Transform is a powerful tool, which is a generalization of the classical Fourier Transform. This paper provides a mathematical relation relating the span in Fractional Fourier domain with the amplitude and phase functions of the signal, which is further used to study the variation of quality factor with different values of the transform order. It is seen that with the increase in the number of transients in the signal, the deviation of average Fractional Fourier span from the frequency bandwidth increases. Also, with the increase in the transient nature of the signal, the optimum value of transform order can be estimated based on the quality factor variation, and this value is found to be very close to that for which one can obtain the most compact representation. With the entire mathematical analysis and experimentation, we consolidate the fact that Fractional Fourier Transform gives more optimal representations for a number of transform orders than Fourier transform.

Keywords: Fractional Fourier Transform, Quality Factor, Fractional Fourier span, transient signals.

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Authors: Mohammad Reza Ghanbari, Parham Azimi, Farrokh Abdollahi

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Since the last two decades, container transportation system has been faced under increasing development. This fact shows the importance of container transportation system as a key role of container terminals to link between sea and land. Therefore, there is a continuous need for the optimal use of equipment and facilities in the ports. Regarding the complex structure of container ports, this paper presents a simulation model that compares tow storage strategies for storing containers in the yard. For this purpose, we considered loading and unloading norm as an important criterion to evaluate the performance of Shahid Rajaee container port. By analysing the results of the model, it will be shown that using marshalling yard policy instead of current storage system has a significant effect on the performance level of the port and can increase the loading and unloading norm up to 14%.

Keywords: Simulation Modeling, Container Port, Marshaling Yard, Storage Policy

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Authors: Nurhani Kasuan, Zakariah Yusuf, Mohd Nasir Taib, Mohd Hezri Fazalul Rahiman, Nazurah Tajuddin, Mohd Azri Abdul Aziz

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This paper presents a hybrid fuzzy-PD plus PID (HFPP) controller and its application to steam distillation process for essential oil extraction system. Steam temperature is one of the most significant parameters that can influence the composition of essential oil yield. Due to parameter variations and changes in operation conditions during distillation, a robust steam temperature controller becomes nontrivial to avoid the degradation of essential oil quality. Initially, the PRBS input is triggered to the system and output of steam temperature is modeled using ARX model structure. The parameter estimation and tuning method is adopted by simulation using HFPP controller scheme. The effectiveness and robustness of proposed controller technique is validated by real time implementation to the system. The performance of HFPP using 25 and 49 fuzzy rules is compared. The experimental result demonstrates the proposed HFPP using 49 fuzzy rules achieves a better, consistent and robust controller compared to PID when considering the test on tracking the set point and the effects due to disturbance.

Keywords: Fuzzy Logic controller, steam temperature, steam distillation, real time control.

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Authors: Mahmoud Saeidi, Ali Nazemipour

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In this paper, we propose a novel adaptive spatiotemporal filter that utilizes image sequences in order to remove noise. The consecutive frames include: current, previous and next noisy frames. The filter proposed in this paper is based upon the weighted averaging pixels intensity and noise variance in image sequences. It utilizes the Appropriate Number of Consecutive Frames (ANCF) based on the noisy pixels intensity among the frames. The number of consecutive frames is adaptively calculated for each region in image and its value may change from one region to another region depending on the pixels intensity within the region. The weights are determined by a well-defined mathematical criterion, which is adaptive to the feature of spatiotemporal pixels of the consecutive frames. It is experimentally shown that the proposed filter can preserve image structures and edges under motion while suppressing noise, and thus can be effectively used in image sequences filtering. In addition, the AWA filter using ANCF is particularly well suited for filtering sequences that contain segments with abruptly changing scene content due to, for example, rapid zooming and changes in the view of the camera.

Keywords: Appropriate Number of Consecutive Frames, Adaptive Weighted Averaging, Motion Estimation, Noise Variance, Motion Compensation

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Authors: Ipak Torkpour

Abstract:

In order to convert natural rubber or related polymers to material with varying physical properties such as elastic modulus or durability, a chemical process named sulfur vulcanization is needed. This can be either done by heating sulfur or sulfur-containing compounds. The main goal of this process is to produce untreated natural rubber latex that can be the main source of manufacturing for several rubber producers. Temperature, pressure, and time are considered as three crucial factors in the tire vulcanization process. The present study is an attempt to optimize these crucial parameters, with the aim of achieving maximum tire modulus using Taguchi experimental design. The results revealed that the optimal parameter values are as follows: a temperature of 170 °C, a pressure of 110 bar, and a time duration of 230 seconds. Under these optimized conditions, the obtained tire modulus reached 8.8 kgf.

Keywords: Rubber vulcanization, experimental design, Taguchi, polymers.

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Authors: Hadi Veisi, Mansour Jamzad

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In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation are evaluated and compared. In training and evaluation, each image block is assigned to a network based on its complexity value. Best-SNR is another alternative in selecting compressor network for image blocks in evolution phase which chooses one of the trained networks such that results best SNR in compressing the input image block. In our evaluations, best results are obtained when overlapping the blocks is allowed and choosing the networks in compressor is based on the Best-SNR. In this case, the results demonstrate superiority of this method comparing with previous similar works and JPEG standard coding.

Keywords: Adaptive image compression, Image complexity, Multi-layer perceptron neural network, JPEG Standard, PSNR.

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Authors: S. Areerachakul

Abstract:

Nowadays, several techniques such as; Fuzzy Inference System (FIS) and Neural Network (NN) are employed for developing of the predictive models to estimate parameters of water quality. The main objective of this study is to compare between the predictive ability of the Adaptive Neuro-Fuzzy Inference System (ANFIS) model and Artificial Neural Network (ANN) model to estimate the Biochemical Oxygen Demand (BOD) on data from 11 sampling sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2004-2011. The five parameters of water quality namely Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen (NO3N), and Total Coliform bacteria (T-coliform) are used as the input of the models. These water quality indices affect the biochemical oxygen demand. The experimental results indicate that the ANN model provides a higher correlation coefficient (R=0.73) and a lower root mean square error (RMSE=4.53) than the corresponding ANFIS model.

Keywords: adaptive neuro-fuzzy inference system, artificial neural network, biochemical oxygen demand, surface water.

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Authors: Hyung Jong Ko, Kyoung Hoon Kim

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In this study thermodynamic performance analysis of a combined organic Rankine cycle and ejector refrigeration cycle is carried out for use of low-grade heat source in the form of sensible energy. Special attention is paid to the effects of system parameters including the turbine inlet temperature and turbine inlet pressure on the characteristics of the system such as ratios of mass flow rate, net work production, and refrigeration capacity as well as the coefficient of performance and exergy efficiency of the system. Results show that for a given source the coefficient of performance increases with increasing of the turbine inlet pressure. However, the exergy efficiency has an optimal condition with respect to the turbine inlet pressure.

Keywords: Coefficient of performance, ejector refrigeration cycle, exergy efficiency, low-grade energy, organic rankine cycle.

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Authors: N. Massoum, A. Guen. Bouazza, B. Bouazza, A. El Ouchdi

Abstract:

The progress of industry integrated circuits in recent years has been pushed by continuous miniaturization of transistors. With the reduction of dimensions of components at 0.1 micron and below, new physical effects come into play as the standard simulators of two dimensions (2D) do not consider. In fact the third dimension comes into play because the transverse and longitudinal dimensions of the components are of the same order of magnitude. To describe the operation of such components with greater fidelity, we must refine simulation tools and adapted to take into account these phenomena. After an analytical study of the static characteristics of the component, according to the different operating modes, a numerical simulation is performed of field-effect transistor with submicron gate MESFET GaInP. The influence of the dimensions of the gate length is studied. The results are used to determine the optimal geometric and physical parameters of the component for their specific applications and uses.

Keywords: Monte Carlo simulation, transient electron transport, MESFET device.

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Authors: Andre A. Keller

Abstract:

The optimal control is one of the possible controllers for a dynamic system, having a linear quadratic regulator and using the Pontryagin-s principle or the dynamic programming method . Stochastic disturbances may affect the coefficients (multiplicative disturbances) or the equations (additive disturbances), provided that the shocks are not too great . Nevertheless, this approach encounters difficulties when uncertainties are very important or when the probability calculus is of no help with very imprecise data. The fuzzy logic contributes to a pragmatic solution of such a problem since it operates on fuzzy numbers. A fuzzy controller acts as an artificial decision maker that operates in a closed-loop system in real time. This contribution seeks to explore the tracking problem and control of dynamic macroeconomic models using a fuzzy learning algorithm. A two inputs - single output (TISO) fuzzy model is applied to the linear fluctuation model of Phillips and to the nonlinear growth model of Goodwin.

Keywords: fuzzy control, macroeconomic model, multiplier - accelerator, nonlinear accelerator, stabilization policy.

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Authors: San Nah Sze, Wei King Tiong

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The multiple traveling salesman problem (mTSP) can be used to model many practical problems. The mTSP is more complicated than the traveling salesman problem (TSP) because it requires determining which cities to assign to each salesman, as well as the optimal ordering of the cities within each salesman's tour. Previous studies proposed that Genetic Algorithm (GA), Integer Programming (IP) and several neural network (NN) approaches could be used to solve mTSP. This paper compared the results for mTSP, solved with Genetic Algorithm (GA) and Nearest Neighbor Algorithm (NNA). The number of cities is clustered into a few groups using k-means clustering technique. The number of groups depends on the number of salesman. Then, each group is solved with NNA and GA as an independent TSP. It is found that k-means clustering and NNA are superior to GA in terms of performance (evaluated by fitness function) and computing time.

Keywords: Multiple Traveling Salesman Problem, GeneticAlgorithm, Nearest Neighbor Algorithm, k-Means Clustering.

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Authors: Boubekeur Dokkar, Nasreddine Chennouf, Noureddine Settou, Belkhir Negrou, Abdesslam Benmhidi

Abstract:

The optimal operation of proton exchange membrane fuel cell (PEMFC) requires good water management which is presented under two forms vapor and liquid. Moreover, fuel cells have to reach higher output require integration of some accessories which need electrical power. In order to analyze fuel cells operation and different species transport phenomena a biphasic mathematical model is presented by governing equations set. The numerical solution of these conservation equations is calculated by Matlab program. A multi-criteria optimization with weighting between two opposite objectives is used to determine the compromise solutions between maximum output and minimal stack size. The obtained results are in good agreement with available literature data.

Keywords: Biphasic model, PEM fuel cell, optimization, simulation, specie transport.

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Authors: Yung-Chuan Lee, Shahram Rahimi, Bidyut Gupta

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In this paper, we introduce an mobile agent framework with proactive load balancing for ambient intelligence (AmI) environments. One of the main obstacles of AmI is the scalability in which the openness of AmI environment introduces dynamic resource requirements on agencies. To mediate this scalability problem, our framework proposes a load balancing module to proactively analyze the resource consumption of network bandwidth and preferred agencies to suggest the optimal communication method to its user. The framework generally formulates an AmI environment that consists of three main components: (1) mobile devices, (2) hosts or agencies, and (3) directory service center (DSC). A preliminary implementation was conducted with NetLogo and the experimental results show that the proposed approach provides enhanced system performance by minimizing the network utilization to provide users with responsive services.

Keywords: Ambient intelligence, load balancing, multiagent systems, ubiquitous computing.

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Authors: Yahya H. Zweiri

Abstract:

The back-propagation algorithm calculates the weight changes of an artificial neural network, and a two-term algorithm with a dynamically optimal learning rate and a momentum factor is commonly used. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third term increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and optimization approaches for evaluating the learning parameters are required to facilitate the application of the three terms BP algorithm. This paper considers the optimization of the new back-propagation algorithm by using derivative information. A family of approaches exploiting the derivatives with respect to the learning rate, momentum factor and proportional factor is presented. These autonomously compute the derivatives in the weight space, by using information gathered from the forward and backward procedures. The three-term BP algorithm and the optimization approaches are evaluated using the benchmark XOR problem.

Keywords: Neural Networks, Backpropagation, Optimization.

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Authors: Hossein Ali Akbarpour, Fatemeh Dadkhah

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This paper considers a multi criteria cell formation problem in Cellular Manufacturing System (CMS). Minimizing the number of voids and exceptional elements in cells simultaneously are two proposed objective functions. This problem is an Np-hard problem according to the literature, and therefore, we can-t find the optimal solution by an exact method. In this paper we developed two ant algorithms, Ant Colony Optimization (ACO) and Max-Min Ant System (MMAS), based on Data Envelopment Analysis (DEA). Both of them try to find the efficient solutions based on efficiency concept in DEA. Each artificial ant is considered as a Decision Making Unit (DMU). For each DMU we considered two inputs, the values of objective functions, and one output, the value of one for all of them. In order to evaluate performance of proposed methods we provided an experimental design with some empirical problem in three different sizes, small, medium and large. We defined three different criteria that show which algorithm has the best performance.

Keywords: Ant algorithm, Cellular manufacturing system, Data envelopment analysis, Efficiency

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Authors: M. Farshbaf, M. R. Feizi-Derakhshi

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Graph partitioning is a NP-hard problem with multiple conflicting objectives. The graph partitioning should minimize the inter-partition relationship while maximizing the intra-partition relationship. Furthermore, the partition load should be evenly distributed over the respective partitions. Therefore this is a multiobjective optimization problem (MOO). One of the approaches to MOO is Pareto optimization which has been used in this paper. The proposed methods of this paper used to improve the performance are injecting best solutions of previous runs into the first generation of next runs and also storing the non-dominated set of previous generations to combine with later generation's non-dominated set. These improvements prevent the GA from getting stuck in the local optima and increase the probability of finding more optimal solutions. Finally, a simulation research is carried out to investigate the effectiveness of the proposed algorithm. The simulation results confirm the effectiveness of the proposed method.

Keywords: Graph partitioning, Genetic algorithm, Multiobjective optimization, Pareto front.

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Authors: Sajeena Beevi. B, Jose P. P., G. Madhu

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The aim of this study was to obtain the optimal conditions for biogas production from anaerobic digestion of organic fraction of municipal solid waste (OFMSW) using response surface methodology (RSM). The parameters studied were initial pH, substrate concentration and total organic carbon (TOC). The experimental results showed that the linear model terms of initial pH and substrate concentration and the quadratic model terms of the substrate concentration and TOC had significant individual effect (p < 0.05) on biogas yield. However, there was no interactive effect between these variables (p > 0.05). The highest level of biogas produced was 53.4 L/Kg VS at optimum pH, substrate concentration and total organic carbon of 6.5, 99gTS/L and 20.32 g/L respectively.

Keywords: Anaerobic Digestion, Biogas, Optimization, Response Surface Methodology.

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Authors: Jung-Eun Park, Kyung-Whan Oh

Abstract:

Intelligent systems are required in order to quickly and accurately analyze enormous quantities of data in the Internet environment. In intelligent systems, information extracting processes can be divided into supervised learning and unsupervised learning. This paper investigates intelligent clustering by unsupervised learning. Intelligent clustering is the clustering system which determines the clustering model for data analysis and evaluates results by itself. This system can make a clustering model more rapidly, objectively and accurately than an analyzer. The methodology for the automatic clustering intelligent system is a multi-agent system that comprises a clustering agent and a cluster performance evaluation agent. An agent exchanges information about clusters with another agent and the system determines the optimal cluster number through this information. Experiments using data sets in the UCI Machine Repository are performed in order to prove the validity of the system.

Keywords: Intelligent Clustering, Multi-Agent System, PCA, SOM, VC(Variance Criterion)

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Authors: Mihai Caramihai, Irina Severin, Ana Aurelia Chirvase, Adrian Onu, Cristina Tanase, Camelia Ungureanu

Abstract:

An immunomodulator bioproduct is prepared in a batch bioprocess with a modified bacterium Pseudomonas aeruginosa. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The optimal bioprocess parameters were determined: temperature – 37 0C, agitation speed - 300 rpm, aeration rate – 40 L/min, pressure – 0.5 bar, Dow Corning Antifoam M-max. 4 % of the medium volume, duration - 6 hours. This kind of bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying. The aim of the paper is to present (by comparison) different models based on experimental data. The analysis criteria were modeling error and convergence rate. The estimated values and the modeling analysis were done by using the Table Curve 2D. The preliminary conclusions indicate Andrews-s model with a maximum specific growth rate of the bacterium in the range of 0.8 h-1.

Keywords: bioprocess modeling, Pseudomonas aeruginosa, kinetic models,

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Authors: T. Sopapirm, K-N. Areerak, K-L. Areerak, A. Srikaew

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The paper presents the applications of artificial intelligence technique called adaptive tabu search to design the controller of a buck converter. The averaging model derived from the DQ and generalized state-space averaging methods is applied to simulate the system during a searching process. The simulations using such averaging model require the faster computational time compared with that of the full topology model from the software packages. The reported model is suitable for the work in the paper in which the repeating calculation is needed for searching the best solution. The results will show that the proposed design technique can provide the better output waveforms compared with those designed from the classical method.

Keywords: Buck converter, adaptive tabu search, DQ method, generalized state-space averaging method, modeling and simulation

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Authors: T. Vigneswari, M. A. Maluk Mohamed

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Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Heterogeneous Earliest First Min- Min Artificial Bee Colony (CHMM-ABC), to optimally schedule jobs for the available resources. The proposed model utilizes a novel Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm along with Min-Min algorithm to identify the initial food source. Simulation results show the performance improvement of the proposed algorithm over other swarm intelligence techniques.

Keywords: Grid Computing, Grid Scheduling, Heterogeneous Earliest Finish Time (HEFT), Artificial Bee colony (ABC) Algorithm, Resource Management.

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Authors: Ismail I. Fasfous, Nedal Abu Farha

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The purpose of this research is to establish the experimental conditions for removal of Cibacron Brilliant Yellow 3G-P dye (CBY) from aqueous solutions by sorption onto coffee husks as a low-cost sorbent. The effects of various experimental parameters (e.g. initial CBY dye concentration, sorbent mass, pH, temperature) were examined and the optimal experimental conditions were determined. The results indicated that the removal of the dye was pH dependent and at initial pH of 2, the dye was removed effectively. The CBY dye sorption data were fitted to Langmuir, Freundlich, Temkin and Dubinin-Radushkevich equilibrium models. The maximum sorption capacity of CBY dye ions onto coffee husks increased from 24.04 to 35.04 mg g-1 when the temperature was increased from 293 to 313 K. The calculated sorption thermodynamic parameters including ΔG°, ΔH°, and ΔS° indicated that the CBY dye sorption onto coffee husks is a spontaneous, endothermic and mainly physical in nature.

Keywords: Coffee husks, equilibrium, reactive dyes, sorption.

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Authors: Dana Kristalova, Jan Mazal

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This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the Army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms etc., have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is the surface of a terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for the commander`s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: Movement in a terrain, geographical factors, surface of a field, mathematical evaluation, optimization and searching paths.

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Authors: Hoda Zolfagharnejad, Behnam Kamkar, Omid Abdi

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Crop coefficient (Kc) is an important factor contributing to estimation of evapotranspiration, and is also used to determine the irrigation schedule. This study investigated and determined the monthly Kc of winter wheat (Triticum aestivum L.) using five vegetation indices (VIs): Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI), Soil Adjusted Vegetation Index (SAVI), Infrared Percentage Vegetation Index (IPVI), and Ratio Vegetation Index (RVI) of four basins in Golestan province, Iran. 14 Landsat-8 images according to crop growth stage were used to estimate monthly Kc of wheat. VIs were calculated based on infrared and near infrared bands of Landsat 8 images using Geographical Information System (GIS) software. The best VIs were chosen after establishing a regression relationship among these VIs with FAO Kc and Kc that was modified for the study area by the previous research based on R² and Root Mean Square Error (RMSE). The result showed that local modified SAVI with R²= 0.767 and RMSE= 0.174 was the best index to produce monthly wheat Kc maps.

Keywords: Crop coefficient, remote sensing, vegetation indices, wheat.

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Authors: Whee Yen Wong, Chan Wai Lee, Kim Yeow Tshai

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Producing IT products/services required carefully designed. IT development process is intangible and labour intensive. Making optimal use of available resources, both soft (knowledge, skill-set etc.) and hard (computer system, ancillary equipment etc.), is vital if IT development is to achieve sensible economical advantages. Apart from the norm of Project Life Cycle and System Development Life Cycle (SDLC), there is an urgent need to establish a general yet widely acceptable guideline on the most effective and efficient way to precede an IT project in the broader view of Product Life Cycle. The current paper proposes such a framework with two major areas of concern: (1) an integration of IT Products and IT Services within an existing IT Process architecture and; (2) how IT Product and IT Services are built into the framework of Product Life Cycle, Project Life Cycle and SDLC.

Keywords: Mapping of Quality Relationship, IT Processes/IT Products/IT Services, Product Life Cycle, System Development Life Cycle.

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Authors: Liping Li, Changchun Liu, Ke Li, Chengyu Liu

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Non-stationary trend in R-R interval series is considered as a main factor that could highly influence the evaluation of spectral analysis. It is suggested to remove trends in order to obtain reliable results. In this study, three detrending methods, the smoothness prior approach, the wavelet and the empirical mode decomposition, were compared on artificial R-R interval series with four types of simulated trends. The Lomb-Scargle periodogram was used for spectral analysis of R-R interval series. Results indicated that the wavelet method showed a better overall performance than the other two methods, and more time-saving, too. Therefore it was selected for spectral analysis of real R-R interval series of thirty-seven healthy subjects. Significant decreases (19.94±5.87% in the low frequency band and 18.97±5.78% in the ratio (p<0.001)) were found. Thus the wavelet method is recommended as an optimal choice for use.

Keywords: empirical mode decomposition, heart rate variability, signal detrending, smoothness priors, wavelet

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Authors: H. Nikzad, S. Yoshitomi

Abstract:

In this paper, an optimization procedure is applied for 3D Reinforced concrete building structure with shear wall.  In the optimization problem, cross sections of beams, columns and shear wall dimensions are considered as design variables and the optimal cross sections can be derived to minimize the total cost of the structure. As for final design application, the most suitable sections are selected to satisfy ACI 318-14 code provision based on static linear analysis. The validity of the method is examined through numerical example of 15 storied 3D RC building with shear wall.  This optimization method is expected to assist in providing a useful reference in design early stage, and to be an effective and powerful tool for structural design of RC shear wall structures.

Keywords: Structural optimization, linear static analysis, ETABS, MATLAB, RC moment frame, RC shear wall structures.

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