A Dynamic Filter for Removal DC - Offset In Current and Voltage Waveforms

In power systems, protective relays must filter their inputs to remove undesirable quantities and retain signal quantities of interest. This job must be performed accurate and fast. A new method for filtering the undesirable components such as DC and harmonic components associated with the fundamental system signals. The method is s based on a dynamic filtering algorithm. The filtering algorithm has many advantages over some other classical methods. It can be used as dynamic on-line filter without the need of parameters readjusting as in the case of classic filters. The proposed filter is tested using different signals. Effects of number of samples and sampling window size are discussed. Results obtained are presented and discussed to show the algorithm capabilities.

Residue and Temporal Trend of Polychlorinated Biphenyls (PCBs) in Surface Soils from Bacninh, Vietnam

An evaluation of the PCBs residues in the surface soils from Bacninh, Vietnam was carried out. Sixty representative soil samples were collected from the centre of Bacninh and three surrounding districts. The analyzed results indicated the wide extent of contamination of total PCBs in Bacninh. In industrial and urban zones, total PCBs concentrations ranged from ranged from

Estimating European Tourism Demand for Malaysia

Tourism industry is an important sector in Malaysia economy and this motivates the examination of long-run relationships between tourist arrivals from three selected European countries in Malaysia and four possible determinants; relative prices, exchange rates, transportation cost and relative prices of substitute destination. The study utilizes data from January 1999 to September 2008 and employs standard econometric techniques that include unit root test and cointegration test. The estimated demand model indicates that depreciation of local currency and increases in prices at substitute destination have positive impact on tourist arrivals while increase in transportation cost has negative impact on tourist arrivals. In addition, the model suggests that higher rate of increase in local prices relative to prices at tourist country of origin may not deter tourists from coming to Malaysia

Change Management in Business Process Modeling Based on Object Oriented Petri Net

Business Process Modeling (BPM) is the first and most important step in business process management lifecycle. Graph based formalism and rule based formalism are the two most predominant formalisms on which process modeling languages are developed. BPM technology continues to face challenges in coping with dynamic business environments where requirements and goals are constantly changing at the execution time. Graph based formalisms incur problems to react to dynamic changes in Business Process (BP) at the runtime instances. In this research, an adaptive and flexible framework based on the integration between Object Oriented diagramming technique and Petri Net modeling language is proposed in order to support change management techniques for BPM and increase the representation capability for Object Oriented modeling for the dynamic changes in the runtime instances. The proposed framework is applied in a higher education environment to achieve flexible, updatable and dynamic BP.

Analytical Solutions for Geodesic Acoustic Eigenmodes in Tokamak Plasmas

The analytical solutions for geodesic acoustic eigenmodes in tokamak plasmas with circular concentric magnetic surfaces are found. In the frame of ideal magnetohydrodynamics the dispersion relation taking into account the toroidal coupling between electrostatic perturbations and electromagnetic perturbations with poloidal mode number |m| = 2 is derived. In the absence of such a coupling the dispersion relation gives the standard continuous spectrum of geodesic acoustic modes. The analysis of the existence of global eigenmodes for plasma equilibria with both off-axis and on-axis maximum of the local geodesic acoustic frequency is performed.

Cooperative Energy Efficient Routing for Wireless Sensor Networks in Smart Grid Communications

Smart Grids employ wireless sensor networks for their control and monitoring. Sensors are characterized by limitations in the processing power, energy supply and memory spaces, which require a particular attention on the design of routing and data management algorithms. Since most routing algorithms for sensor networks, focus on finding energy efficient paths to prolong the lifetime of sensor networks, the power of sensors on efficient paths depletes quickly, and consequently sensor networks become incapable of monitoring events from some parts of their target areas. In consequence, the design of routing protocols should consider not only energy efficiency paths, but also energy efficient algorithms in general. In this paper we propose an energy efficient routing protocol for wireless sensor networks without the support of any location information system. The reliability and the efficiency of this protocol have been demonstrated by simulation studies where we compare them to the legacy protocols. Our simulation results show that these algorithms scale well with network size and density.

Process Parameter Optimization for the Production of Gentamicin using Micromonouspora Echiniospora

The process parameters, temperature, pH and substrate concentration, were optimized for the production of gentamicin using Micromonouspora echinospora. Experiments were carried out according to central composite design in response surface method. The optimum conditions for the maximum production of gentamicin were found to be: temperature – 31.7oC, pH – 6.8 and substrate concentration – 3%. At these optimized conditions the production of gentamicin was found to be – 1040 mg/L. The R2 value of 0.9465 indicates a good fitness of the model.

Discovery and Capture of Organizational Knowledge from Unstructured Information

Knowledge of an organization does not merely reside in structured form of information and data; it is also embedded in unstructured form. The discovery of such knowledge is particularly difficult as the characteristic is dynamic, scattered, massive and multiplying at high speed. Conventional methods of managing unstructured information are considered too resource demanding and time consuming to cope with the rapid information growth. In this paper, a Multi-faceted and Automatic Knowledge Elicitation System (MAKES) is introduced for the purpose of discovery and capture of organizational knowledge. A trial implementation has been conducted in a public organization to achieve the objective of decision capture and navigation from a number of meeting minutes which are autonomously organized, classified and presented in a multi-faceted taxonomy map in both document and content level. Key concepts such as critical decision made, key knowledge workers, knowledge flow and the relationship among them are elicited and displayed in predefined knowledge model and maps. Hence, the structured knowledge can be retained, shared and reused. Conducting Knowledge Management with MAKES reduces work in searching and retrieving the target decision, saves a great deal of time and manpower, and also enables an organization to keep pace with the knowledge life cycle. This is particularly important when the amount of unstructured information and data grows extremely quickly. This system approach of knowledge management can accelerate value extraction and creation cycles of organizations.

Siding Mode Control of Pitch-Rate of an F-16 Aircraft

This paper considers the control of the longitudinal flight dynamics of an F-16 aircraft. The primary design objective is model-following of the pitch rate q, which is the preferred system for aircraft approach and landing. Regulation of the aircraft velocity V (or the Mach-hold autopilot) is also considered, but as a secondary objective. The problem is challenging because the system is nonlinear, and also non-affine in the input. A sliding mode controller is designed for the pitch rate, that exploits the modal decomposition of the linearized dynamics into its short-period and phugoid approximations. The inherent robustness of the SMC design provides a convenient way to design controllers without gain scheduling, with a steady-state response that is comparable to that of a conventional polynomial based gain-scheduled approach with integral control, but with improved transient performance. Integral action is introduced in the sliding mode design using the recently developed technique of “conditional integrators", and it is shown that robust regulation is achieved with asymptotically constant exogenous signals, without degrading the transient response. Through extensive simulation on the nonlinear multiple-input multiple-output (MIMO) longitudinal model of the F-16 aircraft, it is shown that the conditional integrator design outperforms the one based on the conventional linear control, without requiring any scheduling.

Numerical Study of Vertical Wall Jets: Influence of the Prandtl Number

This paper is a numerical investigation of a laminar isothermal plane two dimensional wall jet. Special attention has been paid to the effect of the inlet conditions at the nozzle exit on the hydrodynamic and thermal characteristics of the flow. The behaviour of various fluids evolving in both forced and mixed convection regimes near a vertical plate plane is carried out. The system of governing equations is solved with an implicit finite difference scheme. For numerical stability we use a staggered non uniform grid. The obtained results show that the effect of the Prandtl number is significant in the plume region in which the jet flow is governed by buoyant forces. Further for ascending X values, the buoyancy forces become dominating, and a certain agreement between the temperature profiles are observed, which shows that the velocity profile has no longer influence on the wall temperature evolution in this region. Fluids with low Prandtl number warm up more importantly, because for such fluids the effect of heat diffusion is higher.

Detecting and Tracking Vehicles in Airborne Videos

In this work, we present an automatic vehicle detection system for airborne videos using combined features. We propose a pixel-wise classification method for vehicle detection using Dynamic Bayesian Networks. In spite of performing pixel-wise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. The main novelty of the detection scheme is that the extracted combined features comprise not only pixel-level information but also region-level information. Afterwards, tracking is performed on the detected vehicles. Tracking is performed using efficient Kalman filter with dynamic particle sampling. Experiments were conducted on a wide variety of airborne videos. We do not assume prior information of camera heights, orientation, and target object sizes in the proposed framework. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging dataset.

New Hybrid Method to Correct for Wind Tunnel Wall- and Support Interference On-line

Because support interference corrections are not properly understood, engineers mostly rely on expensive dummy measurements or CFD calculations. This paper presents a method based on uncorrected wind tunnel measurements and fast calculation techniques (it is a hybrid method) to calculate wall interference, support interference and residual interference (when e.g. a support member closely approaches the wind tunnel walls) for any type of wind tunnel and support configuration. The method provides with a simple formula for the calculation of the interference gradient. This gradient is based on the uncorrected measurements and a successive calculation of the slopes of the interference-free aerodynamic coefficients. For the latter purpose a new vortex-lattice routine is developed that corrects the slopes for viscous effects. A test case of a measurement on a wing proves the value of this hybrid method as trends and orders of magnitudes of the interference are correctly determined.

Developing a Campus Sustainability Assessment Framework for the National University of Malaysia

Campus sustainability is the goal of a university striving for sustainable development. This study found that of 17 popular approaches, two comprehensive campus sustainability assessment frameworks were developed in the context of Sustainability in Higher Education (SHE), and used by many university campuses around the world. Sustainability Tracking Assessment and Rating Systems (STARS) and the Campus Sustainability Assessment Framework (CSAF) approaches are more comprehensive than others. Therefore, the researchers examined aspects and elements used by CSAF and STARS in the approach to develop a campus sustainability assessment framework for Universiti Kebangsaan Malaysia (UKM). Documents analysis found that CSAF and STARS do not focus on physical development, especially the construction industry, as key elements of campus sustainability assessment. This finding is in accordance with the Sustainable UKM Programme which consists of three main components of sustainable community, ecosystem and physical development.

A Dynamic Time-Lagged Correlation based Method to Learn Multi-Time Delay Gene Networks

A gene network gives the knowledge of the regulatory relationships among the genes. Each gene has its activators and inhibitors that regulate its expression positively and negatively respectively. Genes themselves are believed to act as activators and inhibitors of other genes. They can even activate one set of genes and inhibit another set. Identifying gene networks is one of the most crucial and challenging problems in Bioinformatics. Most work done so far either assumes that there is no time delay in gene regulation or there is a constant time delay. We here propose a Dynamic Time- Lagged Correlation Based Method (DTCBM) to learn the gene networks, which uses time-lagged correlation to find the potential gene interactions, and then uses a post-processing stage to remove false gene interactions to common parents, and finally uses dynamic correlation thresholds for each gene to construct the gene network. DTCBM finds correlation between gene expression signals shifted in time, and therefore takes into consideration the multi time delay relationships among the genes. The implementation of our method is done in MATLAB and experimental results on Saccharomyces cerevisiae gene expression data and comparison with other methods indicate that it has a better performance.

Scene Adaptive Shadow Detection Algorithm

Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.

Physico-Chemical Characteristics of Cement Manufactured with Artificial Pozzolan (Waste Brick)

The effect of artificial pozzolan (waste brick) on the physico-chemical properties of cement manufactured was investigated. The waste brick is generated by the manufacture of bricks. It was used in the proportions of 0%, 5%, 10%, 15% and 20% by mass of cement to study its effect on the physico-chemical properties of cement incorporating artificial pozzolan. The physicochemical properties of cement at anhydrous state and the hydrated state (chemical composition, specific weight, fineness, consistency of the cement paste and setting times) were studied. The experimental results obtained show that the quantity of pozzolanic admixture (waste brick) of cement manufactured is the principal parameter who influences on the variation of the physico-chemical properties of the cement tested.

Modeling, Simulation and Monitoring of Nuclear Reactor Using Directed Graph and Bond Graph

The main objective developed in this paper is to find a graphic technique for modeling, simulation and diagnosis of the industrial systems. This importance is much apparent when it is about a complex system such as the nuclear reactor with pressurized water of several form with various several non-linearity and time scales. In this case the analytical approach is heavy and does not give a fast idea on the evolution of the system. The tool Bond Graph enabled us to transform the analytical model into graphic model and the software of simulation SYMBOLS 2000 specific to the Bond Graphs made it possible to validate and have the results given by the technical specifications. We introduce the analysis of the problem involved in the faults localization and identification in the complex industrial processes. We propose a method of fault detection applied to the diagnosis and to determine the gravity of a detected fault. We show the possibilities of application of the new diagnosis approaches to the complex system control. The industrial systems became increasingly complex with the faults diagnosis procedures in the physical systems prove to become very complex as soon as the systems considered are not elementary any more. Indeed, in front of this complexity, we chose to make recourse to Fault Detection and Isolation method (FDI) by the analysis of the problem of its control and to conceive a reliable system of diagnosis making it possible to apprehend the complex dynamic systems spatially distributed applied to the standard pressurized water nuclear reactor.

Performance Optimization of Data Mining Application Using Radial Basis Function Classifier

Text data mining is a process of exploratory data analysis. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. This paper describes proposed radial basis function Classifier that performs comparative crossvalidation for existing radial basis function Classifier. The feasibility and the benefits of the proposed approach are demonstrated by means of data mining problem: direct Marketing. Direct marketing has become an important application field of data mining. Comparative Cross-validation involves estimation of accuracy by either stratified k-fold cross-validation or equivalent repeated random subsampling. While the proposed method may have high bias; its performance (accuracy estimation in our case) may be poor due to high variance. Thus the accuracy with proposed radial basis function Classifier was less than with the existing radial basis function Classifier. However there is smaller the improvement in runtime and larger improvement in precision and recall. In the proposed method Classification accuracy and prediction accuracy are determined where the prediction accuracy is comparatively high.

University Students Awareness on M-Learning

Mobile learning (M-learning) is the current technology that is becoming more popular. It uses the current mobile and wireless computing technology to complement the effectiveness of traditional learning process. The objective of this paper is presents a survey from 90 undergraduate students of Universiti Teknologi PETRONAS (UTP), to identify the students- perception on Mlearning. From the results, the students are willing to use M-learning. The acceptance level of the students is high, and the results obtained revealed that the respondents almost accept M-learning as one method of teaching and learning process and also able to improve the educational efficiency by complementing traditional learning in UTP.

Fuzzy Control of a Quarter-Car Suspension System

An active suspension system has been proposed to improve the ride comfort. A quarter-car 2 degree-of-freedom (DOF) system is designed and constructed on the basis of the concept of a four-wheel independent suspension to simulate the actions of an active vehicle suspension system. The purpose of a suspension system is to support the vehicle body and increase ride comfort. The aim of the work described in the paper was to illustrate the application of fuzzy logic technique to the control of a continuously damping automotive suspension system. The ride comfort is improved by means of the reduction of the body acceleration caused by the car body when road disturbances from smooth road and real road roughness. The paper describes also the model and controller used in the study and discusses the vehicle response results obtained from a range of road input simulations. In the conclusion, a comparison of active suspension fuzzy control and Proportional Integration derivative (PID) control is shown using MATLAB simulations.