Effect of Conjugate Heat and Mass Transfer on MHD Mixed Convective Flow past Inclined Porous Plate in Porous Medium

This analysis is performed to study the momentum, heat and mass transfer characteristics of MHD mixed convective flow past inclined porous plate in porous medium, including the effect of fluid suction. The fluid is assumed to be steady, incompressible and dense. Similarity solution is used to transform the problem under consideration into coupled nonlinear boundary layer equations which are then solved numerically by using the Runge-Kutta sixth-order integration scheme together with Nachtsheim-Swigert shooting iteration technique. Numerical results for the various types of parameters entering into the problem for velocity, temperature and concentration distributions are presented graphically and analyzed thereafter. Moreover, expressions for the skin-friction, heat transfer co-efficient and mass transfer co-efficient are discussed with graphs against streamwise distance for various governing parameters.

Motion Planning and Posture Control of the General 3-Trailer System

This paper presents a set of artificial potential field functions that improves upon, in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of the general3-trailer system in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. Simulations are provided to demonstrate the effectiveness of the controls laws.

Comparative Study on Swarm Intelligence Techniques for Biclustering of Microarray Gene Expression Data

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

Potential Field Functions for Motion Planning and Posture of the Standard 3-Trailer System

This paper presents a set of artificial potential field functions that improves upon, in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of 3-trailer systems in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. The effectiveness of the proposed control laws were demonstrated via simulations of two traffic scenarios.

A Model-Reference Sliding Mode for Dual-Stage Actuator Servo Control in HDD

This paper presents a method of sliding mode control (SMC) designing and developing for the servo system in a dual-stage actuator (DSA) hard disk drive. Mathematical modeling of hard disk drive actuators is obtained, extracted from measuring frequency response of the voice-coil motor (VCM) and PZT micro-actuator separately. Matlab software tools are used for mathematical model estimation and also for controller design and simulation. A model-reference approach for tracking requirement is selected as a proposed technique. The simulation results show that performance of a model-reference SMC controller design in DSA servo control can be satisfied in the tracking error, as well as keeping the positioning of the head within the boundary of +/-5% of track width under the presence of internal and external disturbance. The overall results of model-reference SMC design in DSA are met per requirement specifications and significant reduction in %off track is found when compared to the single-state actuator (SSA).

H∞ State Estimation of Neural Networks with Discrete and Distributed Delays

In this paper, together with some improved Lyapunov-Krasovskii functional and effective mathematical techniques, several sufficient conditions are derived to guarantee the error system is globally asymptotically stable with H∞ performance, in which both the time-delay and its time variation can be fully considered. In order to get less conservative results of the state estimation condition, zero equalities and reciprocally convex approach are employed. The estimator gain matrix can be obtained in terms of the solution to linear matrix inequalities. A numerical example is provided to illustrate the usefulness and effectiveness of the obtained results.

Dynamic Self-Scheduling of Pumped-Storage Power Plant in Energy and Ancillary Service Markets Using Sliding Window Technique

In the competitive electricity market environment, the profit of the pumped-storage plant in the energy market can be maximized by operating it as a generator, when market clearing price is high and as a pump, to pump water from lower reservoir to upper reservoir, when the price is low. An optimal self-scheduling plan has been developed for a pumped-storage plant, carried out on weekly basis in order to maximize the profit of the plant, keeping into account of all the major uncertainties such as the sudden ancillary service delivery request and the price forecasting errors. For a pumped storage power plant to operate in a real time market successive self scheduling has to be done by considering the forecast of the day-ahead market and the modified reservoir storage due to the ancillary service request of the previous day. Sliding Window Technique has been used for successive self scheduling to ensure profit for the plant.

A New Proof on the Growth Factor in Gaussian Elimination for Generalized Higham Matrices

The generalized Higham matrix is a complex symmetric matrix A = B + iC, where both B ∈ Cn×n and C ∈ Cn×n are Hermitian positive definite, and i = √−1 is the imaginary unit. The growth factor in Gaussian elimination is less than 3√2 for this kind of matrices. In this paper, we give a new brief proof on this result by different techniques, which can be understood very easily, and obtain some new findings.

Semantically Enriched Web Usage Mining for Personalization

The continuous growth in the size of the World Wide Web has resulted in intricate Web sites, demanding enhanced user skills and more sophisticated tools to help the Web user to find the desired information. In order to make Web more user friendly, it is necessary to provide personalized services and recommendations to the Web user. For discovering interesting and frequent navigation patterns from Web server logs many Web usage mining techniques have been applied. The recommendation accuracy of usage based techniques can be improved by integrating Web site content and site structure in the personalization process. Herein, we propose semantically enriched Web Usage Mining method for Personalization (SWUMP), an extension to solely usage based technique. This approach is a combination of the fields of Web Usage Mining and Semantic Web. In the proposed method, we envisage enriching the undirected graph derived from usage data with rich semantic information extracted from the Web pages and the Web site structure. The experimental results show that the SWUMP generates accurate recommendations and is able to achieve 10-20% better accuracy than the solely usage based model. The SWUMP addresses the new item problem inherent to solely usage based techniques.

Design and Realization of an Electronic Load for a PEM Fuel Cell

In order to further understand the behavior of PEM fuel cell and optimize their performance, it is necessary to perform measurements in real time. The internal impedance measurement by electrochemical impedance spectroscopy (EIS) is of great importance. In this work, we present the impedance measurement method of a PEM fuel cell by electrochemical impedance spectroscopy method and the realization steps of electronic load for this measuring technique implementation. The theoretical results are obtained from the simulation of software PSPICE® and experimental tests are carried out using the Ballard Nexa™ PEM fuel cell system.

Internal Node Stabilization for Voltage Sense Amplifiers in Multi-Channel Systems

This paper discusses the undesirable charge transfer by the parasitic capacitances of the input transistors in a voltage sense amplifier. Due to its intrinsic rail-to-rail voltage transition, the input sides are inevitably disturbed. It can possible disturb the stabilities of the reference voltage levels. Moreover, it becomes serious in multi-channel systems by altering them for other channels, and so degrades the linearity of the systems. In order to alleviate the internal node voltage transition, the internal node stabilization technique is proposed by utilizing an additional biasing circuit. It achieves 47% and 43% improvements for node stabilization and input referred disturbance, respectively.

Comparative Analysis of DTC Based Switched Reluctance Motor Drive Using Torque Equation and FEA Models

Since torque ripple is the main cause of noise and vibrations, the performance of Switched Reluctance Motor (SRM) can be improved by minimizing its torque ripple using a novel control technique called Direct Torque Control (DTC). In DTC technique, torque is controlled directly through control of magnitude of the flux and change in speed of the stator flux vector. The flux and torque are maintained within set hysteresis bands. The DTC of SRM is analyzed by two methods. In one method, the actual torque is computed by conducting Finite Element Analysis (FEA) on the design specifications of the motor. In the other method, the torque is computed by Simplified Torque Equation. The variation of peak current, average current, torque ripple and speed settling time with Simplified Torque Equation model is compared with FEA based model.

Model-Based Control for Piezoelectric-Actuated Systems Using Inverse Prandtl-Ishlinskii Model and Particle Swarm Optimization

In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller. 

Production of Size-Selected Tin Nanoclusters for Device Applications

This work reports on the fabrication of tin nanoclusters by sputtering and inert-gas condensation inside an ultra-high vacuum compatible system. This technique allows to fine tune the size and yield of nanoclusters by controlling the nanocluster source parameters. The produced nanoclusters are deposited on SiO2/Si substrate with pre-formed electrical electrodes to produce a nanocluster device. Those devices can be potentially used for gas sensor applications.

Incidence of Disasters and Coping Mechanism among Farming Households in South West Nigeria

Farming households faces lots of disaster which contribute to endemic poverty. Anticipated increases in extreme weather events will exacerbate this. Primary data was administered to farming household using multi-stage random sampling technique. The result of the analysis shows that majority of the respondents (69.9%) are male, have mean household size, years of formal education and age of 5±1.14, 6±3.41, and 51.06±10.43 respectively. The major (48.9%) type of disaster experienced is flooding. Major coping mechanism adopted is sourcing for support from family and friends. Age, education, experience, access to extension agent, and mitigation control method contribute significantly to vulnerability to disaster. The major adaptation method (62.3%) is construction of drainage. The study revealed that the coping mechanisms employed may become less effective as increasingly fragile livelihood systems struggle to withstand disaster shocks. Thus there is need for training of the farmers on measures to adapt to mitigate the shock from disasters

Computer Software for Calculating Electron Mobility of Semiconductors Compounds; Case Study for N-Gan

Computer software to calculate electron mobility with respect to different scattering mechanism has been developed. This software is adopted completely Graphical User Interface (GUI) technique and its interface has been designed by Microsoft Visual basic 6.0. As a case study the electron mobility of n-GaN was performed using this software. The behavior of the mobility for n-GaN due to elastic scattering processes and its relation to temperature and doping concentration were discussed. The results agree with other available theoretical and experimental data.

TiO2/Clay Minerals (Palygorskite/Halloysite) Nanocomposite Coatings for Water Disinfection

Microfibrous palygorskite and tubular halloysite clay mineral combined with nanocrystalline TiO2 are incorporating in the preparation of nanocomposite films on glass substrates via sol-gel route at 450oC. The synthesis is employing nonionic surfactant molecule as pore directing agent along with acetic acid-based sol-gel route without addition of water molecules. Drying and thermal treatment of composite films ensure elimination of organic material lead to the formation of TiO2 nanoparticles homogeneously distributed on the palygorskite or halloysite surfaces. Nanocomposite films without cracks of active anatase crystal phase on palygorskite and halloysite surfaces are characterized by microscopy techniques, UV-Vis spectroscopy, and porosimetry methods in order to examine their structural properties. The composite palygorskite-TiO2 and halloysite-TiO2 films with variable quantities of palygorskite and halloysite were tested as photocatalysts in the photo-oxidation of Basic Blue 41 azo dye in water. These nanocomposite films proved to be most promising photocatalysts and highly effective to dye’s decoloration in spite of small amount of palygorskite-TiO2 or halloysite-TiO2 catalyst immobilized onto glass substrates mainly due to the high surface area and uniform distribution of TiO2 on clay minerals avoiding aggregation.

Software Vulnerability Markets: Discoverers and Buyers

Some of the key aspects of vulnerability—discovery, dissemination, and disclosure—have received some attention recently. However, the role of interaction among the vulnerability discoverers and vulnerability acquirers has not yet been adequately addressed. Our study suggests that a major percentage of discoverers, a majority in some cases, are unaffiliated with the software developers and thus are free to disseminate the vulnerabilities they discover in any way they like. As a result, multiple vulnerability markets have emerged. In some of these markets, the exchange is regulated, but in others, there is little or no regulation. In recent vulnerability discovery literature, the vulnerability discoverers have remained anonymous individuals. Although there has been an attempt to model the level of their efforts, information regarding their identities, modes of operation, and what they are doing with the discovered vulnerabilities has not been explored. Reports of buying and selling of the vulnerabilities are now appearing in the press; however, the existence of such markets requires validation, and the natures of the markets need to be analyzed. To address this need, we have attempted to collect detailed information. We have identified the most prolific vulnerability discoverers throughout the past decade and examined their motivation and methods. A large percentage of these discoverers are located in Eastern and Western Europe and in the Far East. We have contacted several of them in order to collect firsthand information regarding their techniques, motivations, and involvement in the vulnerability markets. We examine why many of the discoverers appear to retire after a highly successful vulnerability-finding career. The paper identifies the actual vulnerability markets, rather than the hypothetical ideal markets that are often examined. The emergence of worldwide government agencies as vulnerability buyers has significant implications. We discuss potential factors that can impact the risk to society and the need for detailed exploration.

Ranking of Performance Measures of GSCM towards Sustainability: Using Analytic Hierarchy Process

During recent years, the natural environment has become a challenging topic that business organizations must consider due to the economic and ecological impacts and increasing awareness of environment protection among society. Organizations are trying to achieve the goals of improvement in environment, low cost, high quality, flexibility and more customer satisfaction. Performance measurement frameworks are very useful to monitor the performance of any organization. The basic goal of this paper is to identify performance measures and ranking of these performance measures of GSCM performance measurement towards sustainability framework. Five perspectives (Environment, Economic, Social, Operational and Cost performances) and nineteen performance measures of GSCM performance towards sustainability have been have been identified from extensive literature review. Analytical Hierarchy Process (AHP) technique has been utilized for ranking of these performance perspectives and measures. All pair comparisons in AHP have been made on the basis on the experts’ opinions (selected from academia and industry). Ranking of these performance perspectives and measures will help to understand the importance of environmental, economic, social, operational performances and cost performances in the supply chain.

Rapid Detection System of Airborne Pathogens

We developed new processes which can collect and detect rapidly airborne pathogens such as the avian flu virus for the pandemic prevention. The fluorescence antibody technique is known as one of high-sensitive detection methods for viruses, but this needs up to a few hours to bind sufficient fluorescence dyes to viruses for detection. In this paper, we developed a mist-labeling can detect substitution viruses in a short time to improve the binding rate of fluorescent dyes and substitution viruses by the micro reaction process. Moreover, we developed the rapid detection system with the above “mist labeling”. The detection system set with a sampling bag collecting patient’s breath and a cartridge can detect automatically pathogens within 10 minutes.