Agent Decision using Granular Computing in Traffic System

In recent years multi-agent systems have emerged as one of the interesting architectures facilitating distributed collaboration and distributed problem solving. Each node (agent) of the network might pursue its own agenda, exploit its environment, develop its own problem solving strategy and establish required communication strategies. Within each node of the network, one could encounter a diversity of problem-solving approaches. Quite commonly the agents can realize their processing at the level of information granules that is the most suitable from their local points of view. Information granules can come at various levels of granularity. Each agent could exploit a certain formalism of information granulation engaging a machinery of fuzzy sets, interval analysis, rough sets, just to name a few dominant technologies of granular computing. Having this in mind, arises a fundamental issue of forming effective interaction linkages between the agents so that they fully broadcast their findings and benefit from interacting with others.

Exploiting Global Self Similarity for Head-Shoulder Detection

People detection from images has a variety of applications such as video surveillance and driver assistance system, but is still a challenging task and more difficult in crowded environments such as shopping malls in which occlusion of lower parts of human body often occurs. Lack of the full-body information requires more effective features than common features such as HOG. In this paper, new features are introduced that exploits global self-symmetry (GSS) characteristic in head-shoulder patterns. The features encode the similarity or difference of color histograms and oriented gradient histograms between two vertically symmetric blocks. The domain-specific features are rapid to compute from the integral images in Viola-Jones cascade-of-rejecters framework. The proposed features are evaluated with our own head-shoulder dataset that, in part, consists of a well-known INRIA pedestrian dataset. Experimental results show that the GSS features are effective in reduction of false alarmsmarginally and the gradient GSS features are preferred more often than the color GSS ones in the feature selection.

Compensation Method Eliminating Voltage Distortions in PWM Inverter

The switching lag-time and the voltage drop across the power devices cause serious waveform distortions and fundamental voltage drop in pulse width-modulated inverter output. These phenomenons are conspicuous when both the output frequency and voltage are low. To estimate the output voltage from the PWM reference signal it is essential to take account of these imperfections and to correct them. In this paper, on-line compensation method is presented. It needs three simple blocs to add at the ideal reference voltages. This method does not require any additional hardware circuit and off- line experimental measurement. The paper includes experimental results to demonstrate the validity of the proposed method. It is applied, finally, in case of indirect vector controlled induction machine and implemented using dSpace card.

Bin Bloom Filter Using Heuristic Optimization Techniques for Spam Detection

Bloom filter is a probabilistic and memory efficient data structure designed to answer rapidly whether an element is present in a set. It tells that the element is definitely not in the set but its presence is with certain probability. The trade-off to use Bloom filter is a certain configurable risk of false positives. The odds of a false positive can be made very low if the number of hash function is sufficiently large. For spam detection, weight is attached to each set of elements. The spam weight for a word is a measure used to rate the e-mail. Each word is assigned to a Bloom filter based on its weight. The proposed work introduces an enhanced concept in Bloom filter called Bin Bloom Filter (BBF). The performance of BBF over conventional Bloom filter is evaluated under various optimization techniques. Real time data set and synthetic data sets are used for experimental analysis and the results are demonstrated for bin sizes 4, 5, 6 and 7. Finally analyzing the results, it is found that the BBF which uses heuristic techniques performs better than the traditional Bloom filter in spam detection.

Propagation of Electron-Acoustic Solitary Waves in Weakly Relativistically Degenerate Fermi Plasma

Using one dimensional Quantum hydrodynamic (QHD) model Korteweg de Vries (KdV) solitary excitations of electron-acoustic waves (EAWs) have been examined in twoelectron- populated relativistically degenerate super dense plasma. It is found that relativistic degeneracy parameter influences the conditions of formation and properties of solitary structures.

An Assessment of Technological Competencies on Professional Service Firms Business Performance

This study was initiated with a three prong objective. One, to identify the relationship between Technological Competencies factors (Technical Capability, Firm Innovativeness and E-Business Practices and professional service firms- business performance. To investigate the predictors of professional service firms business performance and finally to evaluate the predictors of business performance according to the type of professional service firms, a survey questionnaire was deployed to collect empirical data. The questionnaire was distributed to the owners of the professional small medium size enterprises services in the Accounting, Legal, Engineering and Architecture sectors. Analysis showed that all three Technology Competency factors have moderate effect on business performance. In addition, the regression models indicate that technical capability is the most highly influential that could determine business performance, followed by e-business practices and firm innovativeness. Subsequently, the main predictor of business performance for all types of firms is Technical capability.

Separation of Manganese and Cadmium from Cobalt Electrolyte Solution by Solvent Extraction

Impurity metals such as manganese and cadmium from high-tenor cobalt electrolyte solution were selectively removed by solvent extraction method using Co-D2EHPA after converting the functional group of D2EHPA with Co2+ ions. The process parameters such as pH, organic concentration, O/A ratio, kinetics etc. were investigated and the experiments were conducted by batch tests in the laboratory bench scale. Results showed that a significant amount of manganese and cadmium can be extracted using Co-D2EHPA for the optimum processing of cobalt electrolyte solution at equilibrium pH about 3.5. The McCabe-Thiele diagram, constructed from the extraction studies showed that 100% impurities can be extracted through four stages for manganese and three stages for cadmium using O/A ratio of 0.65 and 1.0, respectively. From the stripping study, it was found that 100% manganese and cadmium can be stripped from the loaded organic using 0.4 M H2SO4 in a single contact. The loading capacity of Co-D2EHPA by manganese and cadmium were also investigated with different O/A ratio as well as with number of stages of contact of aqueous and organic phases. Valuable information was obtained for the designing of an impurities removal process for the production of pure cobalt with less trouble in the electrowinning circuit.

High Order Accurate Runge Kutta Nodal Discontinuous Galerkin Method for Numerical Solution of Linear Convection Equation

This paper deals with a high-order accurate Runge Kutta Discontinuous Galerkin (RKDG) method for the numerical solution of the wave equation, which is one of the simple case of a linear hyperbolic partial differential equation. Nodal DG method is used for a finite element space discretization in 'x' by discontinuous approximations. This method combines mainly two key ideas which are based on the finite volume and finite element methods. The physics of wave propagation being accounted for by means of Riemann problems and accuracy is obtained by means of high-order polynomial approximations within the elements. High order accurate Low Storage Explicit Runge Kutta (LSERK) method is used for temporal discretization in 't' that allows the method to be nonlinearly stable regardless of its accuracy. The resulting RKDG methods are stable and high-order accurate. The L1 ,L2 and L∞ error norm analysis shows that the scheme is highly accurate and effective. Hence, the method is well suited to achieve high order accurate solution for the scalar wave equation and other hyperbolic equations.

Characteristics of Hemodynamics in a Bileaflet Mechanical Heart Valve using an Implicit FSI Method

Human heart valves diseased by congenital heart defects, rheumatic fever, bacterial infection, cancer may cause stenosis or insufficiency in the valves. Treatment may be with medication but often involves valve repair or replacement (insertion of an artificial heart valve). Bileaflet mechanical heart valves (BMHVs) are widely implanted to replace the diseased heart valves, but still suffer from complications such as hemolysis, platelet activation, tissue overgrowth and device failure. These complications are closely related to both flow characteristics through the valves and leaflet dynamics. In this study, the physiological flow interacting with the moving leaflets in a bileaflet mechanical heart valve (BMHV) is simulated with a strongly coupled implicit fluid-structure interaction (FSI) method which is newly organized based on the Arbitrary-Lagrangian-Eulerian (ALE) approach and the dynamic mesh method (remeshing) of FLUENT. The simulated results are in good agreement with previous experimental studies. This study shows the applicability of the present FSI model to the complicated physics interacting between fluid flow and moving boundary.

The Framework of BeeBot: Binus Multi-Client of Intelligent Telepresence Robot

We present a BeeBot, Binus Multi-client Intelligent Telepresence Robot, a custom-build robot system specifically designed for teleconference with multiple person using omni directional actuator. The robot is controlled using a computer networks, so the manager/supervisor can direct the robot to the intended person to start a discussion/inspection. People tracking and autonomous navigation are intelligent features of this robot. We build a web application for controlling the multi-client telepresence robot and open-source teleconference system used. Experimental result presented and we evaluated its performance.

A Third Drop Level For TCP-RED Congestion Control Strategy

This work presents the Risk Threshold RED (RTRED) congestion control strategy for TCP networks. In addition to the maximum and minimum thresholds in existing RED-based strategies, we add a third dropping level. This new dropping level is the risk threshold which works with the actual and average queue sizes to detect the immediate congestion in gateways. Congestion reaction by RTRED is on time. The reaction to congestion is neither too early, to avoid unfair packet losses, nor too late to avoid packet dropping from time-outs. We compared our novel strategy with RED and ARED strategies for TCP congestion handling using a NS-2 simulation script. We found that the RTRED strategy outperformed RED and ARED.

Dry Sliding Wear Behavior of Epoxy-Rubber Dust Composites

Composite pins of rubber dust collected from tyre retreading centres of trucks, cars and buses etc.and epoxy with weight percentages of 10. 15, and 20 % of rubber (weight fractions of 9, 13 and 17 % respectively) have been prepared in house with the help of a split wooden mould. The pins were tested in a pin-on-disc wear monitor to determine the co-efficient of friction and weight losses with varying speeds, loads and time. The wear volume and wear rates have also been found out for all these three specimens.. It is observed that all the specimens have exhibited very low coefficient of friction and low wear rates under dry sliding condition. Out of the above three samples tested, the specimen with 10 % rubber dust by weight has shown lowest wear rates. However a peculiar result i.e decreasing trend has been obtained with 20% reinforcement of rubber in epoxy while rubbed against steel at varying speeds. This might have occurred due to high surface finish of the disc and formation of a thin transfer layer from the composite

MIMO Antenna Selections using CSI from Reciprocal Channel

It is well known that the channel capacity of Multiple- Input-Multiple-Output (MIMO) system increases as the number of antenna pairs between transmitter and receiver increases but it suffers from multiple expensive RF chains. To reduce the cost of RF chains, Antenna Selection (AS) method can offer a good tradeoff between expense and performance. In a transmitting AS system, Channel State Information (CSI) feedback is necessarily required to choose the best subset of antennas in which the effects of delays and errors occurred in feedback channels are the most dominant factors degrading the performance of the AS method. This paper presents the concept of AS method using CSI from channel reciprocity instead of feedback method. Reciprocity technique can easily archive CSI by utilizing a reverse channel where the forward and reverse channels are symmetrically considered in time, frequency and location. In this work, the capacity performance of MIMO system when using AS method at transmitter with reciprocity channels is investigated by own developing Testbed. The obtained results show that reciprocity technique offers capacity close to a system with a perfect CSI and gains a higher capacity than a system without AS method from 0.9 to 2.2 bps/Hz at SNR 10 dB.

Hybrid Neural Network Methods for Lithology Identification in the Algerian Sahara

In this paper, we combine a probabilistic neural method with radial-bias functions in order to construct the lithofacies of the wells DF01, DF02 and DF03 situated in the Triassic province of Algeria (Sahara). Lithofacies is a crucial problem in reservoir characterization. Our objective is to facilitate the experts' work in geological domain and to allow them to obtain quickly the structure and the nature of lands around the drilling. This study intends to design a tool that helps automatic deduction from numerical data. We used a probabilistic formalism to enhance the classification process initiated by a Self-Organized Map procedure. Our system gives lithofacies, from well-log data, of the concerned reservoir wells in an aspect easy to read by a geology expert who identifies the potential for oil production at a given source and so forms the basis for estimating the financial returns and economic benefits.

Gender Differences in Entrepreneurship: Situation, Characteristics, Motivation and Entrepreneurial Behavior of Women Entrepreneurs in Switzerland

Entrepreneurs are important for national labour markets and economies in that they contribute significantly to economic growth as well as provide the majority of jobs and create new ones. According to the Global Entrepreneurship Monitor’s “Report on Women and Entrepreneurship”, investment in women’s entrepreneurship is an important way to exponentially increase the impact of new venture creation finding ways to empower women’s participation and success in entrepreneurship are critical for more sustainable and successful economic development. Our results confirm that they are still differences between men and women entrepreneurs The reasons seems to be the lack of specific business skills, the less extensive social network, and the lack of identification patterns among women. Those differences can be explained by the fact that women still have fewer opportunities to make a career. If this is correct, we can predict an increasing proportion of women among entrepreneurs in the next years. Concerning the development of a favorable environment for developing and enhancing women entrepreneurship activities, our results show the insertion in a network and the role of a model doubtless represent elements determining in the choice to launch an entrepreneurship activity, as well as a precious resource for the success of her company.

Preparation of Size Controlled Silver on Carbon from E-waste by Chemical and Electro-Kinetic Processes

Preparation of size controlled nano-particles of silver catalyst on carbon substrate from e-waste has been investigated. Chemical route was developed by extraction of the metals available in nitric acid followed by treatment with hydrofluoric acid. Silver metal particles deposited with an average size 4-10 nm. A stabilizer concentration of 10- 40 g/l was used. The average size of the prepared silver decreased with increase of the anode current density. Size uniformity of the silver nano-particles was improved distinctly at higher current density no more than 20mA... Grain size increased with EK time whereby aggregation of particles was observed after 6 h of reaction.. The chemical method involves adsorption of silver nitrate on the carbon substrate. Adsorbed silver ions were directly reduced to metal particles using hydrazine hydrate. Another alternative method is by treatment with ammonia followed by heating the carbon loaded-silver hydroxide at 980°C. The product was characterized with the help of XRD, XRF, ICP, SEM and TEM techniques.

Mercury Removal Techniques for Industrial Waste Water

The current work focuses on rephrasing the harmful effects of mercury that is being released from a number of sources. Most of the sources are from the industrial waste water. Different techniques of mercury removal have been discussed and a brief comparison among these has been made. The experimental work has been conducted for two most widely used methods of mercury removal and comparison in terms of their efficiency has been made.

Factors Related to Working Behavior

This paper aimed to study the factors that relate to working behavior of employees at Pakkred Municipality, Nonthaburi Province. A questionnaire was utilized as the tool in collecting information. Descriptive statistics included frequency, percentage, mean and standard deviation. Independent- sample t- test, analysis of variance and Pearson Correlation were also used. The findings of this research revealed that the majority of the respondents were female, between 25- 35 years old, married, with a Bachelor degree. The average monthly salary of respondents was between 8,001- 12,000 Baht, and having about 4-7 years of working experience. Regarding the overall working motivation factors, the findings showed that interrelationship, respect, and acceptance were ranked as highly important factors, whereas motivation, remunerations & welfare, career growth, and working conditions were ranked as moderately important factors. Also, overall working behavior was ranked as high. The hypotheses testing revealed that different genders had a different working behavior and had a different way of working as a team, which was significant at the 0.05 confidence level, Moreover, there was a difference among employees with different monthly salary in working behavior, problem- solving and decision making, which all were significant at the 0.05 confidence level. Employees with different years of working experience were found to have work working behavior both individual and as a team at the statistical significance level of 0.01 and 0.05. The result of testing the relationship between motivation in overall working revealed that interrelationship, respect and acceptance from others, career growth, and working conditions related to working behavior at a moderate level, while motivation in performing duties and remunerations and welfares related to working behavior towards the same direction at a low level, with a statistical significance of 0.01.

Cross-Industry Innovations–Systematic Identification of Ideas for Radical Problem Solving

Creativity is often based on an unorthodox recombination of knowledge; in fact: 80% of all innovations use given knowledge and put it into a new combination. Cross-industry innovations follow this way of thinking and bring together problems and solution ideas from different industries. Therefore analogies and search strategies have to be developed. Taking this path, the questions where to search, what to search and how to search have to be answered. Afterwards, the gathered information can be used within a planned search process. Identified solution ideas have to be assessed and analyzed in detail for the success promising adaption planning.

Facial Expressions Animation and Lip Tracking Using Facial Characteristic Points and Deformable Model

Face and facial expressions play essential roles in interpersonal communication. Most of the current works on the facial expression recognition attempt to recognize a small set of the prototypic expressions such as happy, surprise, anger, sad, disgust and fear. However the most of the human emotions are communicated by changes in one or two of discrete features. In this paper, we develop a facial expressions synthesis system, based on the facial characteristic points (FCP's) tracking in the frontal image sequences. Selected FCP's are automatically tracked using a crosscorrelation based optical flow. The proposed synthesis system uses a simple deformable facial features model with a few set of control points that can be tracked in original facial image sequences.