Scholarly

Ageing Assessment of Insulation Systems by Absorption/Resorption Currents

Year: 2009 Volume: 3 Issue: 1 60 - 66 Pages

Abstract: Degradation of polymeric insulation systems of electrical equipments increases the space charge density and the concentration of electrical dipoles. By consequence, the maximum values and the slopes of absorption/resorption (A/R) currents can change with insulation systems ageing. In this paper, an analysis of the nature of the A/R currents and the importance of their components, especially the polarization current and the current given by the space charge, is presented. The experimental study concerns the A/R currents measurements of plane samples (made from CALMICAGLAS tapes), virgin and thermally accelerated aged. The obtained results show that the ageing process produces an increase of the values and a decrease of shapes of the A/R currents. Finally, the possibility of estimating insulations ageing state and lifetime from A/R currents measurements is discussed.

CFD Flow and Heat Transfer Simulation for Empty and Packed Fixed Bed Reactor in Catalytic Cracking of Naphtha

Year: 2007 Volume: 1 Issue: 5 49 - 52 Pages

Abstract: This work aims to test the application of computational fluid dynamics (CFD) modeling to fixed bed catalytic cracking reactors. Studies of CFD with a fixed bed design commonly use a regular packing with N=2 to define bed geometry. CFD allows us to obtain a more accurate view of the fluid flow and heat transfer mechanisms present in fixed bed equipment. Naphtha was used as feedstock and the reactor length was 80cm. It is divided in three sections that catalyst bed packed in the middle section of the reactor. The reaction scheme was involved one primary reaction and 24 secondary reactions. Because of high CPU times in these simulations, parallel processing have been used. In this study the coke formation process in fixed bed and empty tube reactor was simulated and coke in these reactors are compared. In addition, the effect of steam ratio and feed flow rate on coke formation was investigated.

Parallel Branch and Bound Model Using Logarithmic Sampling (PBLS) for Symmetric Traveling Salesman Problem

Year: 2007 Volume: 1 Issue: 6 1627 - 1630 Pages

Abstract: Very Large and/or computationally complex optimization problems sometimes require parallel or highperformance computing for achieving a reasonable time for computation. One of the most popular and most complicate problems of this family is “Traveling Salesman Problem". In this paper we have introduced a Branch & Bound based algorithm for the solution of such complicated problems. The main focus of the algorithm is to solve the “symmetric traveling salesman problem". We reviewed some of already available algorithms and felt that there is need of new algorithm which should give optimal solution or near to the optimal solution. On the basis of the use of logarithmic sampling, it was found that the proposed algorithm produced a relatively optimal solution for the problem and results excellent performance as compared with the traditional algorithms of this series.

Prediction Heating Values of Lignocellulosics from Biomass Characteristics

Year: 2013 Volume: 7 Issue: 7 522 - 525 Pages

Abstract: The paper provides biomasses characteristics by proximate analysis (volatile matter, fixed carbon and ash) and ultimate analysis (carbon, hydrogen, nitrogen and oxygen) for the prediction of the heating value equations. The heating value estimation of various biomasses can be used as an energy evaluation. Thirteen types of biomass were studied. Proximate analysis was investigated by mass loss method and infrared moisture analyzer. Ultimate analysis was analyzed by CHNO analyzer. The heating values varied from 15 to 22.4MJ kg-1. Correlations of the calculated heating value with proximate and ultimate analyses were undertaken using multiple regression analysis and summarized into three and two equations, respectively. Correlations based on proximate analysis illustrated that deviation of calculated heating values from experimental heating values was higher than the correlations based on ultimate analysis.

An Optimal Control Problem for Rigid Body Motions on Lie Group SO(2, 1)

Year: 2010 Volume: 4 Issue: 6 668 - 673 Pages

Abstract: In this paper smooth trajectories are computed in the Lie group SO(2, 1) as a motion planning problem by assigning a Frenet frame to the rigid body system to optimize the cost function of the elastic energy which is spent to track a timelike curve in Minkowski space. A method is proposed to solve a motion planning problem that minimize the integral of the square norm of Darboux vector of a timelike curve. This method uses the coordinate free Maximum Principle of Optimal control and results in the theory of integrable Hamiltonian systems. The presence of several conversed quantities inherent in these Hamiltonian systems aids in the explicit computation of the rigid body motions.

The Use of Chlorophyll Meter Readings for the Selection of Maize Inbred Lines under Drought Stress

Year: 2013 Volume: 7 Issue: 8 784 - 788 Pages

Abstract: The present study aimed to investigate whether chlorophyll meter readings (SPAD) can be used as criterion of singleplant selection in maize breeding. Experimentation was performed at the ultra-low density of 0.74 plants/m2 in order the potential yield per plant to be fully expressed. R-31 honeycomb experiments were conducted in three different areas in Greece (Thessaloniki, Giannitsa and Florina) using 30 inbred lines at well-watered and water-stressed conditions during the 2012 growing season. The chlorophyll meter readings had higher rates at dry conditions, except location of Giannitsa where differences were not significant. Genotypes of highest chlorophyll meter readings were consistent across areas, emphasizing on the character’s stability. A positive correlation between the chlorophyll meter readings and grain yield was strengthening over time and culminated at the physiological maturity stage. There was a clear sign that the chlorophyll meter readings has the potential to be used for the selection of stress-adaptive genotypes and may permit modern maize to be grown at wider range of environments addressing the climate change scenarios.

Simultaneous Tuning of Static Var Compensator and Power System Stabilizer Employing Real- Coded Genetic Algorithm

Year: 2008 Volume: 2 Issue: 5 826 - 833 Pages

Abstract: Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.

A Graph-Based Approach for Placement of No-Replicated Databases in Grid

Year: 2008 Volume: 2 Issue: 1 99 - 102 Pages

Abstract: On a such wide-area environment as a Grid, data placement is an important aspect of distributed database systems. In this paper, we address the problem of initial placement of database no-replicated fragments in Grid architecture. We propose a graph based approach that considers resource restrictions. The goal is to optimize the use of computing, storage and communication resources. The proposed approach is developed in two phases: in the first phase, we perform fragment grouping using knowledge about fragments dependency and, in the second phase, we determine an efficient placement of the fragment groups on the Grid. We also show, via experimental analysis that our approach gives solutions that are close to being optimal for different databases and Grid configurations.

Artificial Neural Network based Parameter Estimation and Design Optimization of Loop Antenna

Year: 2010 Volume: 4 Issue: 8 1143 - 1149 Pages

Abstract: Artificial Neural Network (ANN)s are best suited for prediction and optimization problems. Trained ANNs have found wide spread acceptance in several antenna design systems. Four parameters namely antenna radiation resistance, loss resistance, efficiency, and inductance can be used to design an antenna layout though there are several other parameters available. An ANN can be trained to provide the best and worst case precisions of an antenna design problem defined by these four parameters. This work describes the use of an ANN to generate the four mentioned parameters for a loop antenna for the specified frequency range. It also provides insights to the prediction of best and worst-case design problems observed in applications and thereby formulate a model for physical layout design of a loop antenna.

Robotic End-Effector Impedance Control without Expensive Torque/Force Sensor

Year: 2013 Volume: 7 Issue: 7 1475 - 1482 Pages

Abstract: A novel low-cost impedance control structure is proposed for monitoring the contact force between end-effector and environment without installing an expensive force/torque sensor. Theoretically, the end-effector contact force can be estimated from the superposition of each joint control torque. There have a nonlinear matrix mapping function between each joint motor control input and end-effector actuating force/torques vector. This new force control structure can be implemented based on this estimated mapping matrix. First, the robot end-effector is manipulated to specified positions, then the force controller is actuated based on the hall sensor current feedback of each joint motor. The model-free fuzzy sliding mode control (FSMC) strategy is employed to design the position and force controllers, respectively. All the hardware circuits and software control programs are designed on an Altera Nios II embedded development kit to constitute an embedded system structure for a retrofitted Mitsubishi 5 DOF robot. Experimental results show that PI and FSMC force control algorithms can achieve reasonable contact force monitoring objective based on this hardware control structure.

Remaining Useful Life Prediction Using Elliptical Basis Function Network and Markov Chain

Year: 2010 Volume: 4 Issue: 11 1696 - 1700 Pages

Abstract: This paper presents a novel method for remaining useful life prediction using the Elliptical Basis Function (EBF) network and a Markov chain. The EBF structure is trained by a modified Expectation-Maximization (EM) algorithm in order to take into account the missing covariate set. No explicit extrapolation is needed for internal covariates while a Markov chain is constructed to represent the evolution of external covariates in the study. The estimated external and the unknown internal covariates constitute an incomplete covariate set which are then used and analyzed by the EBF network to provide survival information of the asset. It is shown in the case study that the method slightly underestimates the remaining useful life of an asset which is a desirable result for early maintenance decision and resource planning.

The Identification of Anuran Glial Cells

Year: 2014 Volume: 8 Issue: 8 828 - 830 Pages

Authors:
Ibrahim M. S. Shnawa

Abstract: Attempts were made to identify anuran glial cells. They were found as nervous tissue resident. Having stage dependent morphotype changes, whereby, appeared as an ovoid to oval in resting state and amoeboid mrophotypes in activated state, stained fairly with methylene blue and take up Pelikane blue 10% aqueous solution, as well as having the ability to phagocytize heat killed Staphylococcus aureus. They were delineated from the migrating peripheral monocytes by morphotypic and morphometeric differences. Such criteria were consistence with glial cells. Thus, the anuran glial cells are being identified in the frog Rana ridibunda Pallas 1771 and this animal can be of use as a simple model for the immunobiology of glial cells.

Arrival and Departure Scheduling at Hub Airports Considering Airlines Level

Year: 2012 Volume: 6 Issue: 1 95 - 101 Pages

Abstract: As the air traffic increases at a hub airport, some flights cannot land or depart at their preferred target time. This event happens because the airport runways become occupied to near their capacity. It results in extra costs for both passengers and airlines because of the loss of connecting flights or more waiting, more fuel consumption, rescheduling crew members, etc. Hence, devising an appropriate scheduling method that determines a suitable runway and time for each flight in order to efficiently use the hub capacity and minimize the related costs is of great importance. In this paper, we present a mixed-integer zero-one model for scheduling a set of mixed landing and departing flights (despite of most previous studies considered only landings). According to the fact that the flight cost is strongly affected by the level of airline, we consider different airline categories in our model. This model presents a single objective minimizing the total sum of three terms, namely 1) the weighted deviation from targets, 2) the scheduled time of the last flight (i.e., makespan), and 3) the unbalancing the workload on runways. We solve 10 simulated instances of different sizes up to 30 flights and 4 runways. Optimal solutions are obtained in a reasonable time, which are satisfactory in comparison with the traditional rule, namely First- Come-First-Serve (FCFS) that is far apart from optimality in most cases.

Constructing a Simple Polygonalizations

Year: 2011 Volume: 5 Issue: 5 451 - 454 Pages

Abstract: We consider the methods of construction simple polygons for a set S of n points and applying them for searching the minimal area polygon. In this paper we propose the approximate algorithm, which generates the simple polygonalizations of a fixed set of points and finds the minimal area polygon, in O (n3) time and using O(n2) memory.

Improvement of Blood Detection Accuracy using Image Processing Techniques suitable for Capsule Endoscopy

Year: 2012 Volume: 6 Issue: 5 139 - 142 Pages

Abstract: Bleeding in the digestive duct is an important diagnostic parameter for patients. Blood in the endoscopic image can be determined by investigating the color tone of blood due to the degree of oxygenation, under- or over- illumination, food debris and secretions, etc. However, we found that how to pre-process raw images obtained from the capsule detectors was very important. We applied various image process methods suitable for the capsule endoscopic image in order to remove noises and unbalanced sensitivities for the image pixels. The results showed that much improvement was achieved by additional pre-processing techniques on the algorithm of determining bleeding areas.

Communication Behaviors as Predictors of Long-Term Dyadic Adjustment: Personality as a Moderator

Year: 2010 Volume: 4 Issue: 7 1628 - 1635 Pages

Abstract: In this longitudinal study, we examined the moderating role of personality in the relationship between communication behaviors and long-term dyadic adjustment. A sample of 82 couples completed the NEO Five-Factor Inventory and the Dyadic Adjustment Scale. These couples were also videotaped during a 15-minute problem-solving discussion. Approximately 2.5 years later, these couples completed again the Dyadic Adjustment Scale. Results show that personality of both men and women moderates the relationship between communication behaviors of the partner and long-term dyadic adjustment of the individual. Women-s openness and men-s extraversion moderate the relationship between some communication behaviors and long-term dyadic adjustment

Computational Intelligence Hybrid Learning Approach to Time Series Forecasting

Year: 2010 Volume: 4 Issue: 7 1149 - 1156 Pages

Abstract: Time series forecasting is an important and widely popular topic in the research of system modeling. This paper describes how to use the hybrid PSO-RLSE neuro-fuzzy learning approach to the problem of time series forecasting. The PSO algorithm is used to update the premise parameters of the proposed prediction system, and the RLSE is used to update the consequence parameters. Thanks to the hybrid learning (HL) approach for the neuro-fuzzy system, the prediction performance is excellent and the speed of learning convergence is much faster than other compared approaches. In the experiments, we use the well-known Mackey-Glass chaos time series. According to the experimental results, the prediction performance and accuracy in time series forecasting by the proposed approach is much better than other compared approaches, as shown in Table IV. Excellent prediction performance by the proposed approach has been observed.

Machine Learning Techniques for Short-Term Rain Forecasting System in the Northeastern Part of Thailand

Year: 2008 Volume: 2 Issue: 5 1476 - 1481 Pages

Abstract: This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Flow Visualization and Characterization of an Artery Model with Stenosis

Year: 2011 Volume: 5 Issue: 12 656 - 659 Pages

Abstract: Cardiovascular diseases, principally atherosclerosis, are responsible for 30% of world deaths. Atherosclerosis is due to the formation of plaque. The fatty plaque may be at risk of rupture, leading typically to stroke and heart attack. The plaque is usually associated with a high degree of lumen reduction, called a stenosis.It is increasingly recognized that the initiation and progression of disease and the occurrence of clinical events is a complex interplay between the local biomechanical environment and the local vascular biology. The aim of this study is to investigate the flow behavior through a stenosed artery. A physical experiment was performed using an artery model and blood analogue fluid. An axisymmetric model constructed consists of contraction and expansion region that follow a mathematical form of cosine function. A 30% diameter reduction was used in this study. The flow field was measured using particle image velocimetry (PIV). Spherical particles with 20μm diameter were seeded in a water-glycerol-NaCl mixture. Steady flow Reynolds numbers are 250. The area of interest is the region after the stenosis where the flow separation occurs. The velocity field was measured and the velocity gradient was investigated. There was high particle concentration in the recirculation zone. High velocity gradient formed immediately after the stenosis throat created a lift force that enhanced particle migration to the flow separation area.

Web Driving Performance Monitoring System

Year: 2012 Volume: 6 Issue: 10 1211 - 1215 Pages

Authors:
Ahmad Aljaafreh

Abstract: Safer driver behavior promoting is the main goal of this paper. It is a fact that drivers behavior is relatively safer when being monitored. Thus, in this paper, we propose a monitoring system to report specific driving event as well as the potentially aggressive events for estimation of the driving performance. Our driving monitoring system is composed of two parts. The first part is the in-vehicle embedded system which is composed of a GPS receiver, a two-axis accelerometer, radar sensor, OBD interface, and GPRS modem. The design considerations that led to this architecture is described in this paper. The second part is a web server where an adaptive hierarchical fuzzy system is proposed to classify the driving performance based on the data that is sent by the in-vehicle embedded system and the data that is provided by the geographical information system (GIS). Our system is robust, inexpensive and small enough to fit inside a vehicle without distracting the driver.

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