Design of a Permanent Magnet Synchronous Machine for the Hybrid Electric Vehicle

Permanent magnet synchronous machines are known as a good candidate for hybrid electric vehicles due to their unique merits. However they have two major drawbacks i.e. high cost and small speed range. In this paper an optimal design of a permanent magnet machine is presented. A reduction of permanent magnet material for a constant torque and an extension in speed and torque ranges are chosen as the optimization aims. For this purpose the analytical model of the permanent magnet synchronous machine is derived and the appropriate design algorithm is devised. The genetic algorithm is then employed to optimize some machine specifications. Finally the finite element method is used to validate the designed machine.

Promoting Electric Vehicles for Sustainable Urban Transport: How to Do It This Time Right

In recent years various types of electric vehicles has gained again increasing attention as an environmentally benign technology in transport. Especially for urban areas with high local pollution this Zero-emission technology (at the point of use) is considered to provide proper solutions. Yet, the bad economics and the limited driving ranges are still major barriers for a broader market penetration of battery electric vehicles (BEV) and of fuel cell vehicles (FCV). The major result of our analyses is that the most important precondition for a further dissemination of BEV in urban areas are emission-free zones. This is an instrument which allows the promotion of BEV without providing excessive subsidies. In addition, it is important to note that the full benefits of EV can only be harvested if the electricity used is produced from renewable energy sources. That is to say, it has to be ensured that the use of BEV in urban areas is clearly linked to a green electricity purchase model. And moreover, the introduction of a CO2- emission-based tax system would support this requirement.

Elaboration and Optimization of Pellets Used for Precise Glass Grinding

In this work, grinding or microcutting tools in the form of pellets were manufactured using a bounded alumina abrasive grains. The bound used is a vitreous material containing quartz feldspars, kaolinite and a quantity of hematite. The pellets were used in glass grinding process to replace the free abrasive grains lapping process. The study of the elaborated pellets were done to define their effectiveness in the grinding process and to optimize the influence of the pellets elaboration parameters. The obtained results show the existence of an optimal combination of the pellets elaboration parameters for each glass grinding phase (coarse to fine grinding). The final roughness (rms) reached by the elaborated pellets on a BK7 glass surface was about 0.392 μm.

Unsupervised Texture Classification and Segmentation

An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of independent non-Gaussian densities. The algorithm estimates the data density in each class by using parametric nonlinear functions that fit to the non-Gaussian structure of the data. This improves classification accuracy compared with standard Gaussian mixture models. When applied to textures, the algorithm can learn basis functions for images that capture the statistically significant structure intrinsic in the images. We apply this technique to the problem of unsupervised texture classification and segmentation.

Shift Invariant Support Vector Machines Face Recognition System

In this paper, we present a new method for incorporating global shift invariance in support vector machines. Unlike other approaches which incorporate a feature extraction stage, we first scale the image and then classify it by using the modified support vector machines classifier. Shift invariance is achieved by replacing dot products between patterns used by the SVM classifier with the maximum cross-correlation value between them. Unlike the normal approach, in which the patterns are treated as vectors, in our approach the patterns are treated as matrices (or images). Crosscorrelation is computed by using computationally efficient techniques such as the fast Fourier transform. The method has been tested on the ORL face database. The tests indicate that this method can improve the recognition rate of an SVM classifier.

Numerical Simulation of a Conventional Heat Pipe

The steady incompressible flow has been solved in cylindrical coordinates in both vapour region and wick structure. The governing equations in vapour region are continuity, Navier-Stokes and energy equations. These equations have been solved using SIMPLE algorithm. For study of parameters variation on heat pipe operation, a benchmark has been chosen and the effect of changing one parameter has been analyzed when the others have been fixed.

A New Approaches for Seismic Signals Discrimination

The automatic discrimination of seismic signals is an important practical goal for the earth-science observatories due to the large amount of information that they receive continuously. An essential discrimination task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present new techniques for seismic signals classification: local, regional and global discrimination. These techniques were tested on seismic signals from the data base of the National Geophysical Institute of the Centre National pour la Recherche Scientifique et Technique (Morocco) by using the Moroccan software for seismic signals analysis.

Induction of Apoptosis by Newcastle Disease Virus Strains AF220 and V4-UPM in Human Promyelocytic Leukemia (HL60) and Human T-Lymphoblastic Leukemia (CEM-SS) Cells

Newcastle Disease Virus (NDV), an avian paramyxovirus, is a highly contagious, generalised virus disease of domestic poultry and wild birds characterized by gastro-intestinal, respiratory and nervous signs. In this study, it was shown that NDV strain AF2240 and V4-UPM are cytolytic to Human Promyelocytic Leukemia, HL60 and Human T-lymphoblastic Leukemia, CEM-SS cells. Results from MTT cytolytic assay showed that CD50 for NDV AF2240 against HL60 was 130 HAU and NDV V4-UPM against HL60 and CEM-SS were 110.6 and 150.9 HAU respectively. Besides, both strains were found to inhibit the proliferation of cells in a dose dependent manner. The mode of cell death either by apoptosis or necrosis was further analyzed using acridine orange and propidium iodide (AO/PI) staining. Our results showed that both NDV strains induced primarily apoptosis in treated cells at CD50 concentration. In conclusion, both NDV strains caused cytolytic effects primarily via apoptosis in leukemia cells.

New Hybrid Algorithm for Task Scheduling in Grid Computing to Decrease missed Task

The purpose of Grid computing is to utilize computational power of idle resources which are distributed in different areas. Given the grid dynamism and its decentralize resources, there is a need for an efficient scheduler for scheduling applications. Since task scheduling includes in the NP-hard problems various researches have focused on invented algorithms especially the genetic ones. But since genetic is an inherent algorithm which searches the problem space globally and does not have the efficiency required for local searching, therefore, its combination with local searching algorithms can compensate for this shortcomings. The aim of this paper is to combine the genetic algorithm and GELS (GAGELS) as a method to solve scheduling problem by which simultaneously pay attention to two factors of time and number of missed tasks. Results show that the proposed algorithm can decrease makespan while minimizing the number of missed tasks compared with the traditional methods.

Enhancing Human-Computer Interaction and Feedback in Touchscreen Icon

In order to enhance the usability of the human computer interface (HCI) on the touchscreen, this study explored the optimal tactile depth and effect of visual cues on the user-s tendency to touch the touchscreen icons. The experimental program was designed on the touchscreen in this study. Results indicated that the ratio of the icon size to the tactile depth was 1:0.106. There were significant effects of experienced users and novices on the tactile feedback depth (p < 0.01). In addition, the results proved that the visual cues provided a feedback that helped to guide the user-s touch icons accurately and increased the capture efficiency for a tactile recognition field. This tactile recognition field was 18.6 mm in length. There was consistency between the experienced users and novices under the visual cue effects. Finally, the study developed an applied design with touch feedback for touchscreen icons.

A Fuzzy Classifier with Evolutionary Design of Ellipsoidal Decision Regions

A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able toadapt the distance norm to the underlying distribution of the prototypedata points except that the sizes of ellipsoids need to be determined a priori. To overcome GKA's inability to determine appropriate size ofellipsoid, the genetic algorithm (GA) is applied to learn the size ofellipsoid. With GA combined with GKA, it will be shown in this paper that the proposed method outperforms the benchmark algorithms as well as algorithms in the field.

Fuzzy Logic System for Tractive Performance Prediction of an Intelligent Air-Cushion Track Vehicle

Fuzzy logic system (FLS) is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –cushion system with measuring the vehicle traction force (TF), motion resistance (MR), cushion clearance height (CH) and cushion pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, pressure control sensor, micro controller, and battery pH sensor are incorporated with the Fuzzy logic system to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively.

Aqueous Ranitidine Elimination in Photolytic Processes

The elimination of ranitidine (a pharmaceutical compound) has been carried out in the presence of UV-C radiation. After some preliminary experiments, it has been experienced the no influence of the gas nature (air or oxygen) bubbled in photolytic experiments. From simple photolysis experiments the quantum yield of this compound has been determined. Two photolytic approximation has been used, the linear source emission in parallel planes and the point source emission in spherical planes. The quantum yield obtained was in the proximity of 0.05 mol Einstein-1 regardless of the method used. Addition of free radical promoters (hydrogen peroxide) increases the ranitidine removal rate while the use of photocatalysts (TiO2) negatively affects the process.

Requirements Engineering for Enterprise Applications Development: Seven Challenges in Higher Education Environment

This paper describes the challenges on the requirements engineering for developing an enterprise applications in higher education environment. The development activities include software implementation, maintenance, and enhancement and support for online transaction processing and overnight batch processing. Generally, an enterprise application for higher education environment may include Student Information System (SIS), HR/Payroll system, Financial Systems etc. By the way, there are so many challenges in requirement engineering phases in order to provide two distinctive services that are production processing support and systems development.

Why We Are Taller in the Morning than Going to Bed at Night – An in vivo and in vitro Study

Intradiscal and intervertebral pressure transducers were developed. They were used to map the pressures in the nucleus and within the annulus of the human spinal segments. Their stressrelaxation were recorded over a period of time for nucleus pressure, applied load, and peripherial strain against time. The results show that for normal discs, pressures in the nucleus are viscoelastic in nature with the applied compressive load. Mechanical strains which develop around the periphery of the vertebral body are also viscoelastic with the applied compressive load. Applied compressive load against time also shows viscoelastic behavior. However, annulus does not respond viscoelastically with the applied load. It showed a linear response to compressive loading.

Order Partitioning in Hybrid MTS/MTO Contexts using Fuzzy ANP

A novel concept to balance and tradeoff between make-to-stock and make-to-order has been hybrid MTS/MTO production context. One of the most important decisions involved in the hybrid MTS/MTO environment is determining whether a product is manufactured to stock, to order, or hybrid MTS/MTO strategy. In this paper, a model based on analytic network process is developed to tackle the addressed decision. Since the regarded decision deals with the uncertainty and ambiguity of data as well as experts- and managers- linguistic judgments, the proposed model is equipped with fuzzy sets theory. An important attribute of the model is its generality due to diverse decision factors which are elicited from the literature and developed by the authors. Finally, the model is validated by applying to a real case study to reveal how the proposed model can actually be implemented.

Spanning Tree Transformation of Connected Graphs into Single-Row Networks

A spanning tree of a connected graph is a tree which consists the set of vertices and some or perhaps all of the edges from the connected graph. In this paper, a model for spanning tree transformation of connected graphs into single-row networks, namely Spanning Tree of Connected Graph Modeling (STCGM) will be introduced. Path-Growing Tree-Forming algorithm applied with Vertex-Prioritized is contained in the model to produce the spanning tree from the connected graph. Paths are produced by Path-Growing and they are combined into a spanning tree by Tree-Forming. The spanning tree that is produced from the connected graph is then transformed into single-row network using Tree Sequence Modeling (TSM). Finally, the single-row routing problem is solved using a method called Enhanced Simulated Annealing for Single-Row Routing (ESSR).

User Acceptance of Location-based Services

Location-based services (LBS) exploit the known location of a user to provide services dependent on their geographic context and personalized needs [1]. The development and arrival of broadband mobile data networks supported with mobile terminals equipped with new location technologies like GPS have finally created opportunities for implementation of LBS applications. But, from the other side, collecting location information data in general raises privacy concerns. This paper presents results from two surveys of LBS acceptance in Croatia. The first survey was administered on 181 students, and the second extended survey involved pattern of 180 Croatian citizens. We developed questionnaire which consists of descriptions of 15 different applications with scale which measures perceptions and attitudes of users towards these applications. We report the results to identify potential commercial applications for LBS in B2C segment. Our findings suggest that some types of applications like emergency&safety services and navigation have significantly higher rate of acceptance than other types.

The Many Faces of your Employees: Insights into the Emerging Markets Workforce

The higher compounded growth rates coupled with favourable demographics in emerging markets portend abundant opportunities for multinational organizations. With many organizations competing for talent in these growing markets, their ability to succeed will depend on their understanding of local workforce needs and aspirations. Using data from the Towers Watson 2010 Global Workforce Study, this paper highlights differences in employee engagement, turnover risks, and attraction and retention drivers between the two markets. Apart from looking at the traditional drivers of employee engagement, the study also explores the value placed by employees on elements like a strong senior leadership, managerial capabilities and career advancement opportunities. Results reveal that emerging markets employees seem to be more engaged and value the non-traditional elements more highly than the developed markets employees.

Corruption and International Business Community Is Integration into International Business ameans of Reducing Corruption?The case of Russia

The article examines an opportunity of corruption restriction exercised by international business community in Russia. Integration of Russian economy into the international business does not reduce corruption inside the country. Foreign actors investing in Russia under the condition of obtaining their required rates of returns will be reluctant to harm their investments by involving into anticorruption activities. Furthermore, many Russian firms- competitive advantage could be directly related to their corruption connections. In this case, foreign investments would only accentuate corrupt companies- success by supporting them financially