Search results for: pin on disc wear testing machine.

Authors: Achim Kampker, Heiner H. Heimes, Mathias Ordung, Christoph Lienemann, Ansgar Hollah, Nemanja Sarovic

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Electric cars with their fast innovation cycles and their disruptive character offer a high degree of freedom regarding innovative design for remanufacturing. Remanufacturing increases not only the resource but also the economic efficiency by a prolonged product life time. The reduced power train wear of electric cars combined with high manufacturing costs for batteries allow new business models and even second life applications. Modular and intermountable designed battery packs enable the replacement of defective or outdated battery cells, allow additional cost savings and a prolongation of life time. This paper discusses opportunities for future remanufacturing value chains of electric cars and their battery components and how to address their potentials with elaborate designs. Based on a brief overview of implemented remanufacturing structures in different industries, opportunities of transferability are evaluated. In addition to an analysis of current and upcoming challenges, promising perspectives for a sustainable electric car circular economy enabled by design for remanufacturing are deduced. Two mathematical models describe the feasibility of pursuing a circular economy of lithium ion batteries and evaluate remanufacturing in terms of sustainability and economic efficiency. Taking into consideration not only labor and material cost but also capital costs for equipment and factory facilities to support the remanufacturing process, cost benefit analysis prognosticate that a remanufacturing battery can be produced more cost-efficiently. The ecological benefits were calculated on a broad database from different research projects which focus on the recycling, the second use and the assembly of lithium ion batteries. The results of this calculations show a significant improvement by remanufacturing in all relevant factors especially in the consumption of resources and greenhouse warming potential. Exemplarily suitable design guidelines for future remanufacturing lithium ion batteries, which consider modularity, interfaces and disassembly, are used to illustrate the findings. For one guideline, potential cost improvements were calculated and upcoming challenges are pointed out.

Keywords: Circular economy, electric mobility, lithium ion batteries, remanufacturing.

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Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim

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In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.

Keywords: Artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt.

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Authors: Mohamed Moustafa Mahmoud Sedky

Abstract:

In Line start permanent magnet synchronous motor,  eccentricity is a common fault that can make it necessary to remove  the motor from the production line. However, because the motor may  be inaccessible, diagnosing the fault is not easy. This paper presents  an FEM that identifies different models, static eccentricity, dynamic  eccentricity, and mixed eccentricity, at no load and full load. The  method overcomes the difficulty of applying FEMs to transient  behavior. It simulates motor speed, torque and flux density  distribution along the air gap for SE,DE, and ME. This paper  represents the various effects of different eccentricitiestypes on the  transient performance.

Keywords: Line Start Permanent magnet, synchronous machine, Static Eccentricity, Dynamic Eccentricity, Mixed Eccentricity.

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Authors: Yasser F. Hassan

Abstract:

Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: Cellular automata, neural cellular automata, deep learning, classification.

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Authors: Anne-Margré C. Vink

Abstract:

Background. Food-related allergies and intolerances are frequently occurring in dogs. Diagnosis and monitoring according ‘Golden Standard’ of elimination efficiency is, however, time consuming, expensive, and requires expert clinical setting. In order to facilitate rapid and robust, quantitative testing of intolerance, and determining the individual offending foods, a serological test is implicated for Alimentary Induced Diseases and manifestations. Method. As we developed Medisynx IgG Human Screening Test ELISA before and the dog’ immune system is most similar to humans, we were able to develop Medisynx IgG Dog Screening Test ELISA as well. In this randomized, double-blind, split-sample, retro perspective study 47 dogs suffering from Canine Atopic Dermatitis (CAD) and several secondary induced reactions were included to participate in serological Medisynx IgG Dog Screening Test ELISA (within < 0,02 % SD). Results were expressed as titers relative to the standard OD readings to diagnose alimentary induced diseases and monitoring efficacy of an individual eliminating diet in dogs. Split sample analysis was performed by independently sending 2 times 3 ml serum under two unique codes. Results. The veterinarian monitored these dogs to check dog’ results at least at 3, 7, 21, 49, 70 days and after period of 6 and 12 months on an individual negative diet and a positive challenge (retrospectively) at 6 months. Data of each dog were recorded in a screening form and reported that a complete recovery of all clinical manifestations was observed at or less than 70 days (between 50 and 70 days) in the majority of dogs (44 out of 47 dogs =93.6%). Conclusion. Challenge results showed a significant result of 100% in specificity as well as 100% positive predicted value. On the other hand, sensitivity was 95,7% and negative predictive value was 95,7%. In conclusion, an individual diet based on IgG ELISA in dogs provides a significant improvement of atopic dermatitis and pruritus including all other non-specific defined allergic skin reactions as erythema, itching, biting and gnawing at toes, as well as to several secondary manifestations like chronic diarrhoea, chronic constipation, otitis media, obesity, laziness or inactive behaviour, pain and muscular stiffness causing a movement disorders, excessive lacrimation, hyper behaviour, nervous behaviour and not possible to stay alone at home, anxiety, biting and aggressive behaviour and disobedience behaviour. Furthermore, we conclude that a relatively more severe systemic candidiasis, as shown by relatively higher titer (class 3 and 4 IgG reactions to Candida albicans), influence the duration of recovery from clinical manifestations in affected dogs. These findings are consistent with our preliminary human clinical studies.

Keywords: Allergy, canine atopic dermatitis (CAD), food allergens, IgG-ELISA, food-incompatibility.

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Authors: Chia-Yu Yao

Abstract:

This paper presents experimental results on testing the symbol-error-rate (SER) performance of quadrature amplitude modulation (QAM) systems employing symmetric pulse-shaping square-root (SR) filters designed by minimizing the roughness function and by minimizing the peak-to-average power ratio (PAR). The device used in the experiments is the 'bladeRF' software-defined-radio platform. PAR is a well-known measurement, whereas the roughness function is a concept for measuring the jitter-induced interference. The experimental results show that the system employing minimum-roughness pulse-shaping SR filters outperforms the system employing minimum-PAR pulse-shaping SR filters in the sense of SER performance.

Keywords: Pulse-shaping filters, jitter, inter-symbol interference, symmetric FIR filters, QAM

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Authors: Kiyohiro Yamazaki

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A purpose of this study is to examine how a firm without fundamental technology is able to gain the competitive advantage. This paper examines three case studies, Sony in the flat display TV industry, Casio in the digital camera industry and Nintendo in the home game machine industry. This paper maintain the firms without fundamental technology construct two advantages, economic advantage and organizational advantage. An economic advantage involves the firm can select either high-tech or cheap devices out of several device makers, and change the alternatives cheaply and quickly. In addition, organizational advantage means that a firm without fundamental technology is not restricted by organizational inertia and cognitive restraints, and exercises the characteristic of strength.

Keywords: Firm without fundamental technology, economic advantage, organizational advantage, Sony, Casio, Nintendo.

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Authors: N. Valliammal, S.N. Geethalakshmi

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This paper describes an optimal approach for feature subset selection to classify the leaves based on Genetic Algorithm (GA) and Kernel Based Principle Component Analysis (KPCA). Due to high complexity in the selection of the optimal features, the classification has become a critical task to analyse the leaf image data. Initially the shape, texture and colour features are extracted from the leaf images. These extracted features are optimized through the separate functioning of GA and KPCA. This approach performs an intersection operation over the subsets obtained from the optimization process. Finally, the most common matching subset is forwarded to train the Support Vector Machine (SVM). Our experimental results successfully prove that the application of GA and KPCA for feature subset selection using SVM as a classifier is computationally effective and improves the accuracy of the classifier.

Keywords: Optimization, Feature extraction, Feature subset, Classification, GA, KPCA, SVM and Computation

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Authors: N. Yogal, C. Lehrmann

Abstract:

The use of permanent magnets (PM) is increasing in permanent magnet synchronous machines (PMSM) to fulfill the requirements of high efficiency machines in modern industry. PMSM are widely used in industrial applications, wind power plants and the automotive industry. Since PMSM are used in different environmental conditions, the long-term effect of NdFeB-based magnets at high temperatures and their corrosion behavior have to be studied due to the irreversible loss of magnetic properties. In this paper, the effect of magnetic properties due to corrosion and increasing temperature in a climatic chamber has been presented. The magnetic moment and magnetic field of the magnets were studied experimentally.

Keywords: Permanent magnets (PM), NdFeB, corrosion behavior, temperature effect, permanent magnet synchronous machine (PMSM).

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Authors: Barath Kumar, Oliver Niggemann, Juergen Jasperneite

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Model-based approaches have been applied successfully to a wide range of tasks such as specification, simulation, testing, and diagnosis. But one bottleneck often prevents the introduction of these ideas: Manual modeling is a non-trivial, time-consuming task. Automatically deriving models by observing and analyzing running systems is one possible way to amend this bottleneck. To derive a model automatically, some a-priori knowledge about the model structure–i.e. about the system–must exist. Such a model formalism would be used as follows: (i) By observing the network traffic, a model of the long-term system behavior could be generated automatically, (ii) Test vectors can be generated from the model, (iii) While the system is running, the model could be used to diagnose non-normal system behavior. The main contribution of this paper is the introduction of a model formalism called 'probabilistic regression automaton' suitable for the tasks mentioned above.

Keywords: Model-based approach, Probabilistic regression automata, Statistical models and Timed automata.

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Authors: Devin Atkin, Orly Yadid-Pecht

Abstract:

The continual demands for increasing resolution and dynamic range in complimentary metal-oxide semiconductor (CMOS) image sensors have resulted in exponential increases in the amount of data that need to be read out of an image sensor, and existing readouts cannot keep up with this demand. Interesting approaches such as sparse and burst readouts have been proposed and show promise, but at considerable trade-offs in other specifications. To this end, we have begun designing and evaluating various readout topologies centered around an attempt to parallelize the sensor readout. In this paper, we have designed, simulated, and started testing a light-controlled oscillator topology with dual column and row readouts. We expect the parallel readout structure to offer greater speed and alleviate the trade-off typical in this topology, where slow pixels present a major framerate bottleneck.

Keywords: CMOS image sensors, high-speed capture, wide dynamic range, light controlled oscillator.

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Authors: Tami Alghamdi, Terence Soule

Abstract:

To study how to transfer knowledge from multiple source problems to the target problem, we modeled the Transfer Learning (TL) process using Genetic Algorithms as the model solver. TL is the process that aims to transfer learned data from one problem to another problem. The TL process aims to help Machine Learning (ML) algorithms find a solution to the problems. The Genetic Algorithms (GA) give researchers access to information that we have about how the old problem is solved. In this paper, we have five different source problems, and we transfer the knowledge to the target problem. We studied different scenarios of the target problem. The results showed that combined knowledge from multiple source problems improves the GA performance. Also, the process of combining knowledge from several problems results in promoting diversity of the transferred population.

Keywords: Transfer Learning, Multiple Sources, Knowledge Transfer, Domain Adaptation, Source, Target.

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Authors: Shankar Kambhampaty, Harish Rohan Kambhampaty

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Data in IT systems in enterprises have been growing at phenomenal pace. This has provided opportunities to run analytics to gather intelligence on key business parameters that enable them to provide better products and services to customers. While there are several Artificial Intelligence/Machine Learning (AI/ML) and Business Intelligence (BI) tools and technologies available in marketplace to run analytics, there is a need for an integrated view when developing intelligent solutions in enterprises. This paper progressively elaborates a reference model for enterprise solutions, builds an integrated view of data, information and intelligence components and presents a reference architecture for intelligent enterprise solutions. Finally, it applies the reference architecture to an insurance organization. The reference architecture is the outcome of experience and insights gathered from developing intelligent solutions for several organizations.

Keywords: Architecture, model, intelligence, artificial intelligence, business intelligence, AI, BI, ML, analytics, enterprise.

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Authors: Hansung Wan, Hyungkwan Cho, Kiho Sung, Hongkyu Kim

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The amount of urban artificial heat which affects the urban temperature rise in urban meteorology was investigated in order to clarify the relationships between urbanization and urban meteorology in this study. The results of calculation to identify how urban temperate was increased through the establishment of a model for measuring the amount of urban artificial heat and theoretical testing revealed that the amount of urban artificial heat increased urban temperature by plus or minus 0.23 ˚ C in 2007 compared with 1996, statistical methods (correlation and regression analysis) to clarify the relationships between urbanization and urban weather were as follows. New design techniques and urban growth management are necessary from urban growth management point of view suggested from this research at city design phase to decrease urban temperature rise and urban torrential rain which can produce urban disaster in terms of urban meteorology by urbanization.

Keywords: The amount of urban artificial heat, Urban growth management, Urbanization, Urban meteorology

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

Abstract:

The paper discusses the main aspects involved in the development of a supply chain management system using the developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: Demand forecasting, machine learning, risk management, supply chain design.

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Authors: Ng Yee Luon, Mohd Zamri Yusoff, Norshah Hafeez Shuaib

Abstract:

Meshing is the process of discretizing problem domain into many sub domains before the numerical calculation can be performed. One of the most popular meshes among many types of meshes is tetrahedral mesh, due to their flexibility to fit into almost any domain shape. In both 2D and 3D domains, triangular and tetrahedral meshes can be generated by using Delaunay triangulation. The quality of mesh is an important factor in performing any Computational Fluid Dynamics (CFD) simulations as the results is highly affected by the mesh quality. Many efforts had been done in order to improve the quality of the mesh. The paper describes a mesh generation routine which has been developed capable of generating high quality tetrahedral cells in arbitrary complex geometry. A few test cases in CFD problems are used for testing the mesh generator. The result of the mesh is compared with the one generated by a commercial software. The results show that no sliver exists for the meshes generated, and the overall quality is acceptable since the percentage of the bad tetrahedral is relatively small. The boundary recovery was also successfully done where all the missing faces are rebuilt.

Keywords: Mesh generation, tetrahedral, CFD, Delaunay.

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Authors: Jui P. Hung, Hsia C. Chang, Yuan L. Lai

Abstract:

Introduction applicability of high-speed cutting stock problem (CSP) is presented in this paper. Due to the orders continued coming in from various on-line ways for a professional cutting company, to stay competitive, such a business has to focus on sustained production at high levels. In others words, operators have to keep the machine running to stay ahead of the pack. Therefore, the continuous stock cutting problem with setup is proposed to minimize the cutting time and pattern changing time to meet the on-line given demand. In this paper, a novel method is proposed to solve the problem directly by using cutting patterns directly. A major advantage of the proposed method in series on-line production is that the system can adjust the cutting plan according to the floating orders. Examples with multiple items are demonstrated. The results show considerable efficiency and reliability in high-speed cutting of CSP.

Keywords: Cutting stock, Optimization, Heuristics

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Authors: Praveen Boinee, Alessandro De Angelis, Gian Luca Foresti

Abstract:

Ensemble learning algorithms such as AdaBoost and Bagging have been in active research and shown improvements in classification results for several benchmarking data sets with mainly decision trees as their base classifiers. In this paper we experiment to apply these Meta learning techniques with classifiers such as random forests, neural networks and support vector machines. The data sets are from MAGIC, a Cherenkov telescope experiment. The task is to classify gamma signals from overwhelmingly hadron and muon signals representing a rare class classification problem. We compare the individual classifiers with their ensemble counterparts and discuss the results. WEKA a wonderful tool for machine learning has been used for making the experiments.

Keywords: Ensembles, WEKA, Neural networks [NN], SupportVector Machines [SVM], Random Forests [RF].

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Authors: Rui Antunes

Abstract:

This article presents a simple way to perform programmed voice commands for the interface with commercial Digital and Analogue Input/Output PCI cards, used in Robotics and Automation applications. Robots and Automation equipment can "listen" to voice commands and perform several different tasks, approaching to the human behavior, and improving the human- machine interfaces for the Automation Industry. Since most PCI Digital and Analogue Input/Output cards are sold with several DLLs included (for use with different programming languages), it is possible to add speech recognition capability, using a standard speech recognition engine, compatible with the programming languages used. It was created in this work a Visual Basic 6 (the world's most popular language) application, that listens to several voice commands, and is capable to communicate directly with several standard 128 Digital I/O PCI Cards, used to control complete Automation Systems, with up to (number of boards used) x 128 Sensors and/or Actuators.

Keywords: Speech Recognition, Automation, Robotics.

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Authors: Kiurski S. Jelena, Kecić S. Vesna, Oros B. Ivana

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Experimental results confirmed the temporal variation of carbon dioxide and carbon monoxide concentration during the working shift of the photocopying process in a small photocopying shop in Novi Sad, Serbia. The statistically significant differences of target gases were examined with two-way analysis of variance without replication followed by Scheffe's post hoc test. The existence of statistically significant differences was obtained for carbon monoxide emission which is pointed out with F-values (12.37 and 31.88) greater than F_crit (6.94) in contrary to carbon dioxide emission (F-values of 1.23 and 3.12 were less than F_crit).  Scheffe's post hoc test indicated that sampling point A (near the photocopier machine) and second time interval contribute the most on carbon monoxide emission.

Keywords: Analysis of variance, carbon dioxide, carbon monoxide, photocopying indoor, Scheffe's test

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Authors: Jung–Min Yang

Abstract:

Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the desired input/output behavior. A matrix expression is presented to address reachability of switched asynchronous sequential machines with output equivalence with respect to a model. The presented reachability condition for the controller design is validated in a simple example.

Keywords: Asynchronous sequential machines, corrective control, model matching, input/output control.

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Authors: Manpreet Singh, Parvinder Singh, Suman

Abstract:

The data is available in abundance in any business organization. It includes the records for finance, maintenance, inventory, progress reports etc. As the time progresses, the data keep on accumulating and the challenge is to extract the information from this data bank. Knowledge discovery from these large and complex databases is the key problem of this era. Data mining and machine learning techniques are needed which can scale to the size of the problems and can be customized to the application of business. For the development of accurate and required information for particular problem, business analyst needs to develop multidimensional models which give the reliable information so that they can take right decision for particular problem. If the multidimensional model does not possess the advance features, the accuracy cannot be expected. The present work involves the development of a Multidimensional data model incorporating advance features. The criterion of computation is based on the data precision and to include slowly change time dimension. The final results are displayed in graphical form.

Keywords: Multidimensional, data precision.

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Authors: René Čechmánek, Jiří Junek, Bohdan Nešpor, Pavel Šteffan

Abstract:

Regarding previous research studies it was concluded that thin-walled fiber-cement composites are able to conduct electric current under specific conditions. This property is ensured by using of various kinds of carbon materials. Though carbon fibers are less conductive than metal fibers, composites with carbon fibers were evaluated as better current conductors than the composites with metal fibers. The level of electric conductivity is monitored by the means of impedance measurement of designed samples. These composites could be used for a range of applications such as heating of trafficable surfaces or shielding of electro-magnetic fields. The aim of the present research was to design an element with the ability to monitor internal processes in building structures and prevent them from collapsing. As a typical element for laboratory testing there was chosen a concrete column, which was repeatedly subjected to load by simple pressure with continual monitoring of changes in electrical properties.

Keywords: Carbon, conductivity, loading, monitoring.

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Authors: Rauno Pääkkönen, Fabriziomaria Gobba, Leena Korpinen

Abstract:

The objective of the study is to assess the implementation of LED lighting into forest machine work in the dark. In addition, the paper includes a wide variety of important and relevant safety and health parameters. In modern, computerized work in the cab of forest machines, artificial illumination is a demanding task when performing duties, such as the visual inspections of wood and computer calculations. We interviewed entrepreneurs and gathered the following as the most pertinent themes: (1) safety, (2) practical problems, and (3) work with LED lighting. The most important comments were in regards to the practical problems of LED lighting. We found indications of technical problems in implementing LED lighting, like snow and dirt on the surfaces of lamps that dim the emission of light. Moreover, service work in the dark forest is dangerous and increases the risks of on-site accidents. We also concluded that the amount of blue light to the eyes should be assessed, especially, when the drivers are working in a semi-dark cab.

Keywords: Forest machines, health, LED, safety.

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Authors: H. Sediki, Dj. Ould Abdeslam, T. Otmane-cherif, A. Bechouche, K. Mesbah

Abstract:

This paper explores steady-state characteristics of grid-connected doubly fed induction motor (DFIM) in case of unity power factor operation. Based on the synchronized mathematical model, analytic determination of the control laws is presented and illustrated by various figures to understand the effect of the applied rotor voltage on the speed and the active power. On other hand, unlike previous works where the stator resistance was neglected, in this work, stator resistance is included such that the equations can be applied to small wind turbine generators which are becoming more popular. Finally the work is crowned by integration of the studied induction generator in a wind system where an open loop control is proposed confers a remarkable simplicity of implementation compared to the known methods.

Keywords: DFIM, equivalent circuit, induction machine, steady state

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Authors: Paula Simões, Isabel Natário

Abstract:

This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: Spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data.

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Authors: Lawrence N. Ngeh, John D. Orbell, Stephen W. Bigger, Kasup Munaweera, Peter Dann

Abstract:

This research is part of a broad program aimed at advancing the science and technology involved in the rescue and rehabilitation of oiled wildlife. One aspect of this research involves the use of oil-sequestering magnetic particles for the removal of contaminants from plumage – so-called “magnetic cleansing". This treatment offers a number of advantages over conventional detergent-based methods including portability - which offers the possibility of providing a “quick clean" to the animal upon first encounter in the field. This could be particularly advantageous when the contaminant is toxic and/or corrosive and/or where there is a delay in transporting the victim to a treatment centre. The method could also be useful as part of a stabilization protocol when large numbers of affected animals are awaiting treatment. This presentation describes the design, development and testing of a prototype field kit for providing a “quick clean" to contaminated wildlife in the field.

Keywords: Magnetic Particles, Oiled Wildlife, Quick Clean, Wildlife Rehabilitation.

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Authors: Norazah Mohd Suki, T Ramayah

Abstract:

e-Government structures permits the government to operate in a more transparent and accountable manner of which it increases the power of the individual in relation to that of the government. This paper identifies the factors that determine customer-s attitude towards e-Government services using a theoretical model based on the Technology Acceptance Model. Data relating to the constructs were collected from 200 respondents. The research model was tested using Structural Equation Modeling (SEM) techniques via the Analysis of Moment Structure (AMOS 16) computer software. SEM is a comprehensive approach to testing hypotheses about relations among observed and latent variables. The proposed model fits the data well. The results demonstrated that e- Government services acceptance can be explained in terms of compatibility and attitude towards e-Government services. The setup of the e-Government services will be compatible with the way users work and are more likely to adopt e-Government services owing to their familiarity with the Internet for various official, personal, and recreational uses. In addition, managerial implications for government policy makers, government agencies, and system developers are also discussed.

Keywords: E-government, structural equation modelling, attitude, service.

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Authors: T. Kuchukhidze, N. Jalagonia, Z. Phachulia, R. Chedia

Abstract:

Ceramic obtained on the base of aluminum oxide has wide application range, because it has unique properties, for example, wear-resistance, dielectric characteristics, and exploitation ability at high temperatures and in corrosive atmosphere. Low temperature synthesis of α-Al2O3 is energo-economical process and it is topical for developing technologies of corundum ceramics fabrication. In the present work possibilities of low temperature transformation of oxyhydroxides in α-Al2O3, during the presence of small amount of rare–earth elements compounds (also Th, Re), have been discussed. Aluminum unstable oxyhydroxides have been obtained by hydrolysis of aluminium isopropoxide, nitrates, sulphate, and chloride in alkaline environment at 80-90ºC temperatures. β-Al(OH)3 has been received from aluminum powder by ultrasonic development. Drying of oxyhydroxide sol has been conducted with presence of various types seeds, which amount reaches 0,1-0,2% (mas). Neodymium, holmium, thorium, lanthanum, cerium, gadolinium, disprosium nitrates and rhenium carbonyls have been used as seeds and they have been added to the sol specimens in amount of 0.1-0.2% (mas) calculated on metals. Annealing of obtained gels is carried out at 70– 1100ºC for 2 hrs. The same specimen transforms in α-Al2O3 at 1100ºC. At this temperature in case of presence of lanthanum and gadolinium transformation takes place by 70-85%. In case of presence of thorium stabilization of γ-and θ-phases takes place. It is established, that thorium causes inhibition of α-phase generation at 1100ºC, and at the time when in all other doped specimens α-phase is generated at lower temperatures (1000-1050ºC). Synthesis of various type compounds and simultaneous consolidation has developed in the furnace of OXY-GON. Composite materials containing oxide and non-oxide components close to theoretical data have been obtained in this furnace respectively. During the work the following devices have been used: X-ray diffractometer DRON-3M (Cu-Kα, Ni filter, 2º/min), High temperature vacuum furnace OXY-GON, electronic scanning microscopes Nikon ECLIPSE LV 150, NMM-800TRF, planetary mill Pulverisette 7 premium line, SHIMADZU Dynamic Ultra Micro Hardness Tester, DUH-211S, Analysette 12 Dyna sizer.

Keywords: α-Alumina, combustion, consolidation, phase transformation, seeding.

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Authors: Kechida Ahmed, Drai Redouane, Khelil Mohamed

Abstract:

In this paper we present a new approach to detecting a flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image based on texture features. Texture is one of the most important features used in recognizing patterns in an image. The paper describes texture features based on 2D Gabor functions, i.e., Gaussian shaped band-pass filters, with dyadic treatment of the radial spatial frequency range and multiple orientations, which represent an appropriate choice for tasks requiring simultaneous measurement in both space and frequency domains. The most relevant features are used as input data on a Fuzzy c-mean clustering classifier. The classes that exist are only two: 'defects' or 'no defects'. The proposed approach is tested on the T.O.F.D image achieved at the laboratory and on the industrial field.

Keywords: 2D Gabor Functions, flaw detection, fuzzy c-mean clustering, non destructive testing, texture analysis, T.O.F.D Image (Time of Flight Diffraction).

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