A Force-directed Graph Drawing based on the Hierarchical Individual Timestep Method

In this paper, we propose a fast and efficient method for drawing very large-scale graph data. The conventional force-directed method proposed by Fruchterman and Rheingold (FR method) is well-known. It defines repulsive forces between every pair of nodes and attractive forces between connected nodes on a edge and calculates corresponding potential energy. An optimal layout is obtained by iteratively updating node positions to minimize the potential energy. Here, the positions of the nodes are updated every global timestep at the same time. In the proposed method, each node has its own individual time and time step, and nodes are updated at different frequencies depending on the local situation. The proposed method is inspired by the hierarchical individual time step method used for the high accuracy calculations for dense particle fields such as star clusters in astrophysical dynamics. Experiments show that the proposed method outperforms the original FR method in both speed and accuracy. We implement the proposed method on the MDGRAPE-3 PCI-X special purpose parallel computer and realize a speed enhancement of several hundred times.

Analysis of Genotype Size for an Evolvable Hardware System

The evolution of logic circuits, which falls under the heading of evolvable hardware, is carried out by evolutionary algorithms. These algorithms are able to automatically configure reconfigurable devices. One of main difficulties in developing evolvable hardware with the ability to design functional electrical circuits is to choose the most favourable EA features such as fitness function, chromosome representations, population size, genetic operators and individual selection. Until now several researchers from the evolvable hardware community have used and tuned these parameters and various rules on how to select the value of a particular parameter have been proposed. However, to date, no one has presented a study regarding the size of the chromosome representation (circuit layout) to be used as a platform for the evolution in order to increase the evolvability, reduce the number of generations and optimize the digital logic circuits through reducing the number of logic gates. In this paper this topic has been thoroughly investigated and the optimal parameters for these EA features have been proposed. The evolution of logic circuits has been carried out by an extrinsic evolvable hardware system which uses (1+λ) evolution strategy as the core of the evolution.

Numerical Analysis of Turbulent Natural Convection in a Square Cavity using Large- Eddy Simulation in Lattice Boltzmann Method

In this paper Lattice Boltzmann simulation of turbulent natural convection with large-eddy simulations (LES) in a square cavity which is filled by water has been investigated. The present results are validated by finds of other investigations which have been done with different numerical methods. Calculations were performed for high Rayleigh numbers of Ra=108 and 109. The results confirm that this method is in acceptable agreement with other verifications of such a flow. In this investigation is tried to present Large-eddy turbulence flow model by Lattice Boltzmann Method (LBM) with a clear and simple statement. Effects of increase in Rayleigh number are displayed on streamlines, isotherm counters and average Nusselt number. Result shows that the average Nusselt number enhances with growth of the Rayleigh numbers.

Improved C-Fuzzy Decision Tree for Intrusion Detection

As the number of networked computers grows, intrusion detection is an essential component in keeping networks secure. Various approaches for intrusion detection are currently being in use with each one has its own merits and demerits. This paper presents our work to test and improve the performance of a new class of decision tree c-fuzzy decision tree to detect intrusion. The work also includes identifying best candidate feature sub set to build the efficient c-fuzzy decision tree based Intrusion Detection System (IDS). We investigated the usefulness of c-fuzzy decision tree for developing IDS with a data partition based on horizontal fragmentation. Empirical results indicate the usefulness of our approach in developing the efficient IDS.

Environmental Friendly Polyurethane Coatings Based On Hyperbranched Resin

Water borne polyurethane (PU) based on newly prepared hyperbranched poly (amine-ester) (HBPAE) was applied and evaluated as organic coating material. HBPAE was prepared through one-pot synthesis between trimethylol propane as a core and AB2 branched monomer which was obtained via Michal addition of methyl methacrylate (MMA) and diethanol amine (DEA). PU was prepared from HBPAE using different ratios of toluene diisocyanate (TDI) to form cured coating film. The prepared HBPAE was characterized using; GPC, FT-IR and 1H-NMR. The mechanical properties (impact, hardness, adhesion, and flexibility), thermal properties (DSC and TGA) and chemical resistance of the applied film were estimated. The results indicated 50% of TDI is the selected ratio. This formulation represents a promising candidate to be used as coating material.

Video-based Face Recognition: A Survey

During the past several years, face recognition in video has received significant attention. Not only the wide range of commercial and law enforcement applications, but also the availability of feasible technologies after several decades of research contributes to the trend. Although current face recognition systems have reached a certain level of maturity, their development is still limited by the conditions brought about by many real applications. For example, recognition images of video sequence acquired in an open environment with changes in illumination and/or pose and/or facial occlusion and/or low resolution of acquired image remains a largely unsolved problem. In other words, current algorithms are yet to be developed. This paper provides an up-to-date survey of video-based face recognition research. To present a comprehensive survey, we categorize existing video based recognition approaches and present detailed descriptions of representative methods within each category. In addition, relevant topics such as real time detection, real time tracking for video, issues such as illumination, pose, 3D and low resolution are covered.

Forecasting of Flash Floods over Wadi Watier –Sinai Peninsula Using the Weather Research and Forecasting (WRF) Model

Flash floods are considered natural disasters that can cause casualties and demolishing of infra structures. The problem is that flash floods, particularly in arid and semi arid zones, take place in very short time. So, it is important to forecast flash floods earlier to its events with a lead time up to 48 hours to give early warning alert to avoid or minimize disasters. The flash flood took place over Wadi Watier - Sinai Peninsula, in October 24th, 2008, has been simulated, investigated and analyzed using the state of the art regional weather model. The Weather Research and Forecast (WRF) model, which is a reliable short term forecasting tool for precipitation events, has been utilized over the study area. The model results have been calibrated with the real data, for the same date and time, of the rainfall measurements recorded at Sorah gauging station. The WRF model forecasted total rainfall of 11.6 mm while the real measured one was 10.8 mm. The calibration shows significant consistency between WRF model and real measurements results.

GPI Observer-based Tracking Control and Synchronization of Chaotic Systems

Based on general proportional integral (GPI) observers and sliding mode control technique, a robust control method is proposed for the master-slave synchronization of chaotic systems in the presence of parameter uncertainty and with partially measurable output signal. By using GPI observer, the master dynamics are reconstructed by the observations from a measurable output under the differential algebraic framework. Driven by the signals provided by GPI observer, a sliding mode control technique is used for the tracking control and synchronization of the master-slave dynamics. The convincing numerical results reveal the proposed method is effective, and successfully accommodate the system uncertainties, disturbances, and noisy corruptions.

Game-Tree Simplification by Pattern Matching and Its Acceleration Approach using an FPGA

In this paper, we propose a Connect6 solver which adopts a hybrid approach based on a tree-search algorithm and image processing techniques. The solver must deal with the complicated computation and provide high performance in order to make real-time decisions. The proposed approach enables the solver to be implemented on a single Spartan-6 XC6SLX45 FPGA produced by XILINX without using any external devices. The compact implementation is achieved through image processing techniques to optimize a tree-search algorithm of the Connect6 game. The tree search is widely used in computer games and the optimal search brings the best move in every turn of a computer game. Thus, many tree-search algorithms such as Minimax algorithm and artificial intelligence approaches have been widely proposed in this field. However, there is one fundamental problem in this area; the computation time increases rapidly in response to the growth of the game tree. It means the larger the game tree is, the bigger the circuit size is because of their highly parallel computation characteristics. Here, this paper aims to reduce the size of a Connect6 game tree using image processing techniques and its position symmetric property. The proposed solver is composed of four computational modules: a two-dimensional checkmate strategy checker, a template matching module, a skilful-line predictor, and a next-move selector. These modules work well together in selecting next moves from some candidates and the total amount of their circuits is small. The details of the hardware design for an FPGA implementation are described and the performance of this design is also shown in this paper.

Optimal All-to-All Personalized Communication in All-Port Tori

All-to-all personalized communication, also known as complete exchange, is one of the most dense communication patterns in parallel computing. In this paper, we propose new indirect algorithms for complete exchange on all-port ring and torus. The new algorithms fully utilize all communication links and transmit messages along shortest paths to completely achieve the theoretical lower bounds on message transmission, which have not be achieved among other existing indirect algorithms. For 2D r × c ( r % c ) all-port torus, the algorithm has time complexities of optimal transmission cost and O(c) message startup cost. In addition, the proposed algorithms accommodate non-power-of-two tori where the number of nodes in each dimension needs not be power-of-two or square. Finally, the algorithms are conceptually simple and symmetrical for every message and every node so that they can be easily implemented and achieve the optimum in practice.

Medical Image Segmentation Based On Vigorous Smoothing and Edge Detection Ideology

Medical image segmentation based on image smoothing followed by edge detection assumes a great degree of importance in the field of Image Processing. In this regard, this paper proposes a novel algorithm for medical image segmentation based on vigorous smoothening by identifying the type of noise and edge diction ideology which seems to be a boom in medical image diagnosis. The main objective of this algorithm is to consider a particular medical image as input and make the preprocessing to remove the noise content by employing suitable filter after identifying the type of noise and finally carrying out edge detection for image segmentation. The algorithm consists of three parts. First, identifying the type of noise present in the medical image as additive, multiplicative or impulsive by analysis of local histograms and denoising it by employing Median, Gaussian or Frost filter. Second, edge detection of the filtered medical image is carried out using Canny edge detection technique. And third part is about the segmentation of edge detected medical image by the method of Normalized Cut Eigen Vectors. The method is validated through experiments on real images. The proposed algorithm has been simulated on MATLAB platform. The results obtained by the simulation shows that the proposed algorithm is very effective which can deal with low quality or marginal vague images which has high spatial redundancy, low contrast and biggish noise, and has a potential of certain practical use of medical image diagnosis.

The Effects of Work Values, Work-Value Congruence and Work Centrality on Organizational Citizenship Behavior

The aim of this study is to test the “work values" inventory developed by Tevruz and Turgut and to utilize the concept in a model, which aims to create a greater understanding of the work experience. In the study multiple effects of work values, work-value congruence and work centrality on organizational citizenship behavior are examined. In this respect, it is hypothesized that work values and work-value congruence predict organizational citizenship behavior through work centrality. Work-goal congruence test, Tevruz and Turgut-s work values inventory are administered along with Kanungo-s work centrality and Podsakoff et al.-s [47] organizational citizenship behavior test to employees working in Turkish SME-s. The study validated that Tevruz and Turgut-s work values inventory and the work-value congruence test were reliable and could be used for future research. The study revealed the mediating role of work centrality only for the relationship of work values and the responsibility dimension of citizenship behavior. Most important, this study brought in an important concept, work-value congruence, which enables a better understanding of work values and their relation to various attitudinal variables.

An Automatic Tool for Checking Consistency between Data Flow Diagrams (DFDs)

System development life cycle (SDLC) is a process uses during the development of any system. SDLC consists of four main phases: analysis, design, implement and testing. During analysis phase, context diagram and data flow diagrams are used to produce the process model of a system. A consistency of the context diagram to lower-level data flow diagrams is very important in smoothing up developing process of a system. However, manual consistency check from context diagram to lower-level data flow diagrams by using a checklist is time-consuming process. At the same time, the limitation of human ability to validate the errors is one of the factors that influence the correctness and balancing of the diagrams. This paper presents a tool that automates the consistency check between Data Flow Diagrams (DFDs) based on the rules of DFDs. The tool serves two purposes: as an editor to draw the diagrams and as a checker to check the correctness of the diagrams drawn. The consistency check from context diagram to lower-level data flow diagrams is embedded inside the tool to overcome the manual checking problem.

Trajectory-Based Modified Policy Iteration

This paper presents a new problem solving approach that is able to generate optimal policy solution for finite-state stochastic sequential decision-making problems with high data efficiency. The proposed algorithm iteratively builds and improves an approximate Markov Decision Process (MDP) model along with cost-to-go value approximates by generating finite length trajectories through the state-space. The approach creates a synergy between an approximate evolving model and approximate cost-to-go values to produce a sequence of improving policies finally converging to the optimal policy through an intelligent and structured search of the policy space. The approach modifies the policy update step of the policy iteration so as to result in a speedy and stable convergence to the optimal policy. We apply the algorithm to a non-holonomic mobile robot control problem and compare its performance with other Reinforcement Learning (RL) approaches, e.g., a) Q-learning, b) Watkins Q(λ), c) SARSA(λ).

Evaluating the Standards of Hospital Pharmacies in Therapeutic Centers Affiliated with Kermanshah University of Medical Sciences, Iran

Nowadays pharmaceutical care departments located in hospitals are amongst the important pillars of the healthcare system. The aim of this study was to evaluate quality of hospital drugstores affiliated with Kermanshah University of Medical Sciences. In this cross-sectional study a validated questionnaire was used. The questionnaire was filled in by the one of the researchers in all seventeen hospital drugstores located in the teaching and nonteaching hospitals affiliated with Kermanshah University of Medical Sciences. The results shows that in observed hospitals,24% of pharmacy environments, 25% of pharmacy store and storage conditions, 49% of storage procedure, 25% of ordering drugs and supplies, 73% of receiving supplies (proper procedure are fallowed for receiving supplies), 35% of receiving supplies (prompt action taken if deterioration of drugs received is suspected), 23.35% of drugs delivery to patients and finally 0% of stock cards are used for proper inventory control have full compliance with standards.

Power Distance and Knowledge Management from a Post-Taylorist Perspective

Contact centres have been exemplars of scientific management in the discipline of operations management for more than a decade now. With the movement of industries from a resource based economy to knowledge based economy businesses have started to realize the customer eccentricity being the key to sustainability amidst high velocity of the market. However, as technologies have converged and advanced, so have the contact centres. Contact Centres have redirected the supply chains and the concept of retailing is highly diminished due to over exaggeration of cost reduction strategies. In conditions of high environmental velocity together with services featuring considerable information intensity contact centres will require up to date and enlightened agents to satisfy the demands placed upon them by those requesting their services. In this paper we examine salient factors such as Power Distance, Knowledge structures and the dynamics of job specialisation and enlargement to suggest critical success factors in the domain of contact centres.

Numerical Investigation of Wave Interaction with Double Vertical Slotted Walls

Recently, permeable breakwaters have been suggested to overcome the disadvantages of fully protection breakwaters. These protection structures have minor impacts on the coastal environment and neighboring beaches where they provide a more economical protection from waves and currents. For regular waves, a numerical model is used (FLOW-3D, VOF) to investigate the hydraulic performance of a permeable breakwater. The model of permeable breakwater consists of a pair of identical vertical slotted walls with an impermeable upper and lower part, where the draft is a decimal multiple of the total depth. The middle part is permeable with a porosity of 50%. The second barrier is located at distant of 0.5 and 1.5 of the water depth from the first one. The numerical model is validated by comparisons with previous laboratory data and semi-analytical results of the same model. A good agreement between the numerical results and both laboratory data and semi-analytical results has been shown and the results indicate the applicability of the numerical model to reproduce most of the important features of the interaction. Through the numerical investigation, the friction factor of the model is carefully discussed.

Inelastic Strength of Laterally Unsupported Top- Loaded Built-Up Slender Beams

Lateral-torsional buckling (LTB) is one of the phenomenae controlling the ultimate bending strength of steel Ibeams carrying distributed loads on top flange. Built-up I-sections are used as main beams and distributors. This study investigates the ultimate bending strength of such beams with sections of different classes including slender elements. The nominal strengths of the selected beams are calculated for different unsupported lengths according to the Provisions of the American Institute of Steel Constructions (AISC-LRFD). These calculations are compared with results of a nonlinear inelastic study using accurate FE model for this type of loading. The goal is to investigate the performance of the provisions for the selected sections. Continuous distributed load at the top flange of the beams was applied at the FE model. Imperfections of different values are implemented to the FE model to examine their effect on the LTB of beams at failure, and hence, their effect on the ultimate strength of beams. The study also introduces a procedure for evaluating the performance of the provisions compared with the accurate FEA results of the selected sections. A simplified design procedure is given and recommendations for future code updates are made.

Generating High-Accuracy Tool Path for 5-axis Flank Milling of Globoidal Spatial Cam

A new tool path planning method for 5-axis flank milling of a globoidal indexing cam is developed in this paper. The globoidal indexing cam is a practical transmission mechanism due to its high transmission speed, accuracy and dynamic performance. Machining the cam profile is a complex and precise task. The profile surface of the globoidal cam is generated by the conjugate contact motion of the roller. The generated complex profile surface is usually machined by 5-axis point-milling method. The point-milling method is time-consuming compared with flank milling. The tool path for 5-axis flank milling of globoidal cam is developed to improve the cutting efficiency. The flank milling tool path is globally optimized according to the minimum zone criterion, and high accuracy is guaranteed. The computational example and cutting simulation finally validate the developed method.

Multi-Label Hierarchical Classification for Protein Function Prediction

Hierarchical classification is a problem with applications in many areas as protein function prediction where the dates are hierarchically structured. Therefore, it is necessary the development of algorithms able to induce hierarchical classification models. This paper presents experimenters using the algorithm for hierarchical classification called Multi-label Hierarchical Classification using a Competitive Neural Network (MHC-CNN). It was tested in ten datasets the Gene Ontology (GO) Cellular Component Domain. The results are compared with the Clus-HMC and Clus-HSC using the hF-Measure.