Search results for: Finite Difference methods

Authors: C. F. Ocoleanu, A. I. Dolan, G. Cividjian, S. Teodorescu

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In this paper we make a temperature investigations in two type of superposed crimped connections using experimental determinations. All the samples use 8 copper wire 7.1 x 3 mm2 crimped by two methods: the first method uses one crimp indents and the second is a proposed method with two crimp indents. The ferrule is a parallel one. We study the influence of number and position of crimp indents. The samples are heated in A.C. current at different current values until steady state heating regime. After obtaining of temperature values, we compare them and present the conclusion.

Keywords: Crimped connections, experimental determinations, heat transfer temperature.

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Authors: Todor Bačkalić, Marinko Maslarić, Milosav Georgijević, Sanja Bojić

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Presented article outlines a rationale, why it is necessary to develop competence about infrastructure risk in water transport. Climate changes are evident and require special attention and global monitoring. Current risk assessment methods for Inland waterway transport just consider some dramatic events. We present a new method for the assessment of risk and vulnerability of inland waterway transport where river depth represents a crucial part. The analysis of water level changes in the lower Danube was done for two significant periods (1965-1979 and 1998-2012).

Keywords: Container ship, draught, probability, the Danube.

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Authors: Radek Fisera, Petr Stluka

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This paper describes a methodology for remote performance monitoring of retail refrigeration systems. The proposed framework starts with monitoring of the whole refrigeration circuit which allows detecting deviations from expected behavior caused by various faults and degradations. The subsequent diagnostics methods drill down deeper in the equipment hierarchy to more specifically determine root causes. An important feature of the proposed concept is that it does not require any additional sensors, and thus, the performance monitoring solution can be deployed at a low installation cost. Moreover only a minimum of contextual information is required, which also substantially reduces time and cost of the deployment process.

Keywords: Condition monitoring, energy baselining, fault detection and diagnostics, commercial refrigeration.

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Authors: A. M. Pashaev, R. A. Sadihov, A. S. Samedov, C. Ardil

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A mathematical model and a numerical method for computing the temperature field of the profile part of convectionally cooled blades are developed. The theoretical substantiation of the method is proved by corresponding theorems. To this end, convergent quadrature processes were developed and error estimates were obtained in terms of the Zygmund continuity moduli. The boundary conditions for heat exchange are determined from the solution of the corresponding integral equations and empirical relations. The reliability of the developed methods is confirmed by calculation and experimental studies of the thermohydraulic characteristics of the nozzle apparatus of the first stage of the gas turbine.

Keywords: Aviation gas turbine, temperature field, cooled blades, numerical modeling.

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Authors: B. Zatwarnicka-Madura

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The objective of the article was to identify the impacts of gamification on customers' behaviour. The most important applications of games in marketing and mechanisms of gamification are presented in the article. A detailed analysis of the influence of gamification on customers using two brands, Foursquare and Nike, was also presented. Research studies using auditory survey methods were carried out among 176 young respondents, who are potential targets of gamification. The studies confirmed a huge participation of young people in customer loyalty programs with relatively low participation in other gamificationbased marketing activities. The research findings clearly indicate that gamification mechanisms are the most attractive.

Keywords: Customer loyalty, games, gamification, social aspects.

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Authors: S. A. Gayvoronsky, T. A. Ezangina

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The robust control system objects with interval- undermined parameters is considers in this paper. Initial information about the system is its characteristic polynomial with interval coefficients. On the basis of coefficient estimations of quality indices and criterion of the maximum stability degree, the methods of synthesis of a robust regulator parametric is developed. The example of the robust stabilization system synthesis of the rope tension is given in this article.

Keywords: An interval polynomial, controller synthesis, analysis of quality factors, maximum degree of stability, robust degree of stability, robust oscillation, system accuracy.

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Authors: K. A. D. N. K Wimalawarne

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In this paper we introduce a novel kernel classifier based on a iterative shrinkage algorithm developed for compressive sensing. We have adopted Bregman iteration with soft and hard shrinkage functions and generalized hinge loss for solving l1 norm minimization problem for classification. Our experimental results with face recognition and digit classification using SVM as the benchmark have shown that our method has a close error rate compared to SVM but do not perform better than SVM. We have found that the soft shrinkage method give more accuracy and in some situations more sparseness than hard shrinkage methods.

Keywords: Compressive sensing, Bregman iteration, Generalisedhinge loss, sparse, kernels, shrinkage functions

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Authors: Modreck Gomo

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The evolution of groundwater chemistry and its quality is largely controlled by hydrogeochemical processes and their understanding is therefore important for groundwater quality assessments and protection of the water resources. A study was conducted in Bloemfontein town of South Africa to assess and compare the groundwater chemistry and quality characteristics in an alluvial aquifer and single-plane fractured-rock aquifers. 9 groundwater samples were collected from monitoring boreholes drilled into the two aquifer systems during a once-off sampling exercise. Samples were collected through low-flow purging technique and analysed for major ions and trace elements. In order to describe the hydrochemical facies and identify dominant hydrogeochemical processes, the groundwater chemistry data are interpreted using stiff diagrams and principal component analysis (PCA), as complimentary tools. The fitness of the groundwater quality for domestic and irrigation uses is also assessed. Results show that the alluvial aquifer is characterised by a Na-HCO₃ hydrochemical facie while fractured-rock aquifer has a Ca-HCO₃ facie. The groundwater in both aquifers originally evolved from the dissolution of calcite rocks that are common on land surface environments. However the groundwater in the alluvial aquifer further goes through another evolution as driven by cation exchange process in which Na in the sediments exchanges with Ca²⁺ in the Ca-HCO₃ hydrochemical type to result in the Na-HCO₃ hydrochemical type. Despite the difference in the hydrogeochemical processes between the alluvial aquifer and single-plane fractured-rock aquifer, this did not influence the groundwater quality. The groundwater in the two aquifers is very hard as influenced by the elevated magnesium and calcium ions that evolve from dissolution of carbonate minerals which typically occurs in surface environments. Based on total dissolved levels (600-900 mg/L), groundwater quality of the two aquifer systems is classified to be of fair quality. The negative potential impacts of the groundwater quality for domestic uses are highlighted.

Keywords: Alluvial aquifer, fractured-rock aquifer, groundwater quality, hydrogeochemical processes.

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Authors: Mounira RouaÐùnia, Noureddine Doghmane

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In this paper we consider the problem of change detection and non stationary signals tracking. Using parametric estimation of signals based on least square lattice adaptive filters we consider for change detection statistical parametric methods using likelihood ratio and hypothesis tests. In order to track signals dynamics, we introduce a compensation procedure in the adaptive estimation. This will improve the adaptive estimation performances and fasten it-s convergence after changes detection.

Keywords: Change detection, Hypothesis test, likelihood ratioleast square lattice adaptive filters.

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Authors: A. Nour Eddine, D. Chalet, L. Aixala, P. Chessé, X. Faure, N. Hatat

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Thermal power technology such as the TEG (Thermo-Electric Generator) arouses significant attention worldwide for waste heat recovery. Despite the potential benefits of marine application due to the permanent heat sink from sea water, no significant studies on this application were to be found. In this study, a test rig has been designed and built to test the performance of the TEG on engine operating points. The TEG device is built from commercially available materials for the sake of possible economical application. Two types of commercial TEM (thermo electric module) have been studied separately on the test rig. The engine data were extracted from a commercial Diesel engine since it shares the same principle in terms of engine efficiency and exhaust with the marine Diesel engine. An open circuit water cooling system is used to replicate the sea water cold source. The characterization tests showed that the silicium-germanium alloys TEM proved a remarkable reliability on all engine operating points, with no significant deterioration of performance even under sever variation in the hot source conditions. The performance of the bismuth-telluride alloys was 100% better than the first type of TEM but it showed a deterioration in power generation when the air temperature exceeds 300 °C. The temperature distribution on the heat exchange surfaces revealed no useful combination of these two types of TEM with this tube length, since the surface temperature difference between both ends is no more than 10 °C. This study exposed the perspective of use of TEG technology for marine engine exhaust heat recovery. Although the results suggested non-sufficient power generation from the low cost commercial TEM used, it provides valuable information about TEG device optimization, including the design of heat exchanger and the types of thermo-electric materials.

Keywords: Internal combustion engine application, Seebeck, thermo-electricity, waste heat recovery.

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Authors: Noura Meshaan Al-Otaibi, Amin Yousef Noaman

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Nowadays scientific data is inevitably digital and stored in a wide variety of formats in heterogeneous systems. Scientists need to access an integrated view of remote or local heterogeneous data sources with advanced data accessing, analyzing, and visualization tools. This research suggests the use of Service Oriented Architecture (SOA) to integrate biological data from different data sources. This work shows SOA will solve the problems that facing integration process and if the biologist scientists can access the biological data in easier way. There are several methods to implement SOA but web service is the most popular method. The Microsoft .Net Framework used to implement proposed architecture.

Keywords: Bioinformatics, Biological data, Data Integration, SOA and Web Services.

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Authors: Wojciech Rejchel

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The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0-1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U-processes as well as empirical processes.

Keywords: Convex loss function, empirical risk minimization, empirical process, U-process, boosting, euclidean family.

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Authors: M. M. Seif, F. A. Khalil, A. A. K. Abou Arab, A. S. Abdel- Aziz, M. A. Abou Donia, Sh. R. Mohamed

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Malathion (ML) is a well known pesticide commonly used in many agricultural and non-agricultural processes. Its toxicity has been attributed primarily to the accumulation of acetylcholine (Ach) at nerve junctions, due to the inhibition of acetylcholinesterase (AChE). The aim of the current research was to study the protective effect of the melissa plant extract against reproductive impairment induced by malathion in 32 male albino rats, and the biological experiment was divided into four groups (8 in each) that given malathion (27 mg/kg; 1/50 of the LD50 for an oral dose) and/or Melissa officinalis (MO) extract (200mg/kg/day) by gavages technique. The sperm counts, sperm motility, sperm morphology, FSH, LH, and testosterone levels had been determined in testes homogenate at the end of the experiment. It is worthy to report that, rats treated with melissa extract did not show a significant difference when compared with the control group, while rats given malathion alone had significantly lower sperm count, sperm motility, and significantly higher abnormal sperm numbers, than the untreated control rats as well as having significantly lower serum FSH, LH, and testosterone levels compared with the control group. Administrations of melissa extract restore all mentioned histological parameters towards the control group and the melissa extract had a strong positive protective effect against malathion toxicity. Results the of biological parameters were confirmed by the histological examination of rat testes and indicated that, both control and melissa groups showing normal seminiferous tubules, while malathion group testicular tissues had necrosis, edema in the seminiferous tubules and degeneration of spermatogonial cells lining the seminiferous tubules with incomplete spermatogenesis. The use of melissa against malathion improved the histological picture and showing normal seminiferous tubules with complete spermatogenesis and almost there was no histopathological changes could be noted.

Keywords: Malathion, Melissa officinalis L., Reproductive toxicity, Rats.

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Authors: S. Balaji, V. Swaminathan, K. Kannan

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The Minimum Vertex Cover (MVC) problem is a classic graph optimization NP - complete problem. In this paper a competent algorithm, called Vertex Support Algorithm (VSA), is designed to find the smallest vertex cover of a graph. The VSA is tested on a large number of random graphs and DIMACS benchmark graphs. Comparative study of this algorithm with the other existing methods has been carried out. Extensive simulation results show that the VSA can yield better solutions than other existing algorithms found in the literature for solving the minimum vertex cover problem.

Keywords: vertex cover, vertex support, approximation algorithms, NP - complete problem.

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Authors: Laila Salah Seada, Ashraf Ibrahim, Fawaz Al Rashid, Ihab Abdo, Hassan Kasim, Waleed Al Mansi, Saud Al Shabli

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Background and Objectives: Colorectal carcinoma is increasing among both men and women worldwide. It has a multifactorial etiology including genetic factors, environmental factors and inflammatory conditions of the digestive tract. A clinicopathologic assessment of colorectal carcinoma in Hail region is done, considering any changing patterns in two 5-year periods from 2005-2009 (A) and from 2012 to 2017 (B). All data had been retrieved from histopathology files of King Khalid Hospital, Hail. Results: During period (A), 75 cases were diagnosed as colorectal carcinoma. Male patients comprised 56/75 (74.7%) of the study, with a mean age of 58.4 (36-97), while females were 19/75 (25.3%) with a mean age of 50.3(30-85) and the difference was significant (p = 0.05). M:F ratio was 2.9:1. Most common histological type was adenocarcioma in 68/75 (90.7%) patients mostly well differentiated in 44/68 (64.7%). Mucinous neoplasms comprised only 7/75 (9.3%) of cases and tended to have a higher stage (p = 0.04). During period (B), 115 cases were diagnosed with an increase of 53.3% in number of cases than period (A). Male to female ratio also decreased to 1.35:1, females being 44.83% more affected. Adenocarcinoma remained the prevalent type (93.9%), while mucinous type was still rare (5.2%). No distal metastases found at time of presentation. Localization of tumors was rectosigmoid in group (A) in 41.4%, which increased to 56.6% in group (B), with an increase of 15.2%. Iliocecal location also decreased from 8% to 3.5%, being 56.25% less. Other proximal areas of the colon were decreased by 25.75%, from 53.9% in group (A) to 40% in group (B). Conclusion: Colorectal carcinoma in Hail region has increased by 53.3% in the past 5 years, with more females being diagnosed. Localization has also shifted distally by 15.2%. These findings are different from Western world patterns which experienced a decrease in incidence and proximal shift of the colon cancer localization. This might be due to better diagnostic tools, population awareness of the disease, as well as changing of life style and/or food habits in the region.

Keywords: Colorectal cancer, Hail Region, changing pattern, distal shift.

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Authors: Liton Jude Rozario, Mohammad Reduanul Haque, Md. Ziarul Islam, Mohammad Shorif Uddin

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Face recognition is a technique to automatically identify or verify individuals. It receives great attention in identification, authentication, security and many more applications. Diverse methods had been proposed for this purpose and also a lot of comparative studies were performed. However, researchers could not reach unified conclusion. In this paper, we are reporting an extensive quantitative accuracy analysis of four most widely used face recognition algorithms: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) using AT&T, Sheffield and Bangladeshi people face databases under diverse situations such as illumination, alignment and pose variations.

Keywords: PCA, ICA, LDA, SVM, face recognition, noise.

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: Metagenomics, phenotype prediction, deep learning, embeddings, multiple instance learning.

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Authors: Maria V. Morozova, Zoya A. Mikhaylovskaya, Elena S. Buyanova, Sofia A. Petrova, Ksenia V. Arishina, Robert G. Zaharov

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The present work is devoted to the investigation of two series of doped bismuth molybdates: Bi_26-2xMn_2xMo₁₀O_69-d and Bi₂₆Mo_10-2yMn_2yO_69-d. Complex oxides were synthesized by conventional solid state technology and by co-precipitation method. The products were identified by powder diffraction. The powders and ceramic samples were examined by means of densitometry, laser diffraction, and electron microscopic methods. Porosity of the ceramic materials was estimated using the hydrostatic method. The electrical conductivity measurements were carried out using impedance spectroscopy method.

Keywords: Bismuth molybdate, columnar structures, impedance spectroscopy, oxygen ionic conductors.

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Authors: YuLung Wu

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In Knowledge Structure Graph, each course unit represents a phase of learning activities. Both learning portfolios and Knowledge Structure Graphs contain learning information of students and let teachers know which content are difficulties and fails. The study purposes "Dual Mode On-line Learning Diagnosis System" that integrates two search methods: learning portfolio and knowledge structure. Teachers can operate the proposed system and obtain the information of specific students without any computer science background. The teachers can find out failed students in advance and provide remedial learning resources.

Keywords: Knowledge Structure Graph, On-line LearningDiagnosis

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Authors: Kelechi E. Ezeji

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Instruction towards acquiring skills in the use of Computer Aided Design technologies has become a vital part of architectural education curriculum in the digital era. Its implementation, however, requires deployment of extra resources to build new infrastructure, acquisition and maintenance of new equipment, retraining of staff and recruitment of new ones who are knowledgeable in this area. This study sought to examine the impact that ownership structure of Nigerian universities had on provision of staff and infrastructure for implementing computer aided design curriculum with a view to developing a framework for the evaluation for appropriate implementation by the institutions. Survey research design was employed. The focus was on departments of architecture in universities in south-east Nigeria accredited by the National Universities Commission. Data were obtained in the areas of infrastructure and personnel for CAD implementation. A multi-stage stratified random sampling method was adopted. The first stage of stratification involved the accredited departments. Random sampling by balloting was then carried out. At the second stage, sampling size formulae was applied to obtain respondents’ number. For data analysis, analysis of variance tool for testing differences of means was used. With ρ < 0.5, the study found that there was significant difference between private-funded, state-funded and federal-funded departments of architecture in the provision of personnel and infrastructure. The implications of these findings were that for successful implementation leading to attainment of CAD proficiency to occur in every institution regardless of ownership structure, minimum evaluation guidelines needed to be set. A regular comparison of implementation in institutions was recommended as a means of rating performance. This will inform better interaction with those who consistently show weakness to challenge them towards improvement.

Keywords: Computer-aided design, curriculum, funding, infrastructure.

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Authors: Dávid Csercsik, Péter Kádár

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In the case of the proposed method, the problem is parallelized by considering multiple possible mode of operation profiles, which determine the range in which the generators operate in each period. For each of these profiles, the optimization is carried out independently, and the best resulting dispatch is chosen. For each such profile, the resulting problem is a quadratic programming (QP) problem with a potentially negative definite Q quadratic term, and constraints depending on the actual operation profile. In this paper we analyze the performance of available MATLAB optimization methods and solvers for the corresponding QP.

Keywords: Economic dispatch, optimization, quadratic programming, MATLAB.

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Authors: Noor Atinah Ahmad

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The Minimal Residual (MR) is modified for adaptive filtering application. Three forms of MR based algorithm are presented: i) the low complexity SPCG, ii) MREDSI, and iii) MREDSII. The low complexity is a reduced complexity version of a previously proposed SPCG algorithm. Approximations introduced reduce the algorithm to an LMS type algorithm, but, maintain the superior convergence of the SPCG algorithm. Both MREDSI and MREDSII are MR based methods with Euclidean direction of search. The choice of Euclidean directions is shown via simulation to give better misadjustment compared to their gradient search counterparts.

Keywords: Adaptive filtering, Adaptive least square, Minimalresidual method.

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Authors: Grzegorz Ulacha, Ryszard Stasiński

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In the paper an effective context based lossless coding technique is presented. Three principal and few auxiliary contexts are defined. The predictor adaptation technique is an improved CoBALP algorithm, denoted CoBALP+. Cumulated predictor error combining 8 bias estimators is calculated. It is shown experimentally that indeed, the new technique is time-effective while it outperforms the well known methods having reasonable time complexity, and is inferior only to extremely computationally complex ones.

Keywords: Adaptive prediction, context coding, image losslesscoding, prediction error bias correction.

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Authors: Y. Harold Robinson, M. Rajaram, E. Golden Julie, S. Balaji

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A mobile ad hoc network (MANET) is a wireless communication network where nodes that are not within direct transmission range establish their communication via the help of other nodes to forward data. Routing protocols in MANETs are usually categorized as proactive. Tree Based Opportunistic Routing (TBOR) finds a multipath link based on maximum probability of the throughput. The simulation results show that the presented method is performed very well compared to the existing methods in terms of throughput, delay and routing overhead.

Keywords: Mobile ad hoc networks, opportunistic data forwarding, proactive Source routing, BFS.

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Authors: Amin Milani Fard, Mohsen Kahani, Reza Ghaemi, Hamid Tabatabaee

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In this paper we propose a multi-agent architecture for web information retrieval using fuzzy logic based result fusion mechanism. The model is designed in JADE framework and takes advantage of JXTA agent communication method to allow agent communication through firewalls and network address translators. This approach enables developers to build and deploy P2P applications through a unified medium to manage agent-based document retrieval from multiple sources.

Keywords: Information retrieval systems, list fusion methods, document score, multi-agent systems.

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Authors: Seongsoo Lee, Jong-Bae Lee, Wookkang Lee, Duyen Hai Pham

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In the image sensors, the acquired image often differs from the real image in luminance or chrominance due to fabrication defects or nonlinear characteristics, which often lead to pixel defects or sensor failure. Therefore, the image acquisition characteristics of image sensors should be measured and tested before they are mounted on the target product. In this paper, the standardized test and measurement methods of image sensors are introduced. It applies standard light source to the image sensor under test, and the characteristics of the acquired image is compared with ideal values.

Keywords: Image Sensor, Image Acquisition Characteristics, Defect, Failure, Standard, Test, Measurement.

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Authors: Hamed Vahdat Nejad, Hossein Deldari

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Wavelet transforms are multiresolution decompositions that can be used to analyze signals and images. Image compression is one of major applications of wavelet transforms in image processing. It is considered as one of the most powerful methods that provides a high compression ratio. However, its implementation is very time-consuming. At the other hand, parallel computing technologies are an efficient method for image compression using wavelets. In this paper, we propose a parallel wavelet compression algorithm based on quadtrees. We implement the algorithm using MatlabMPI (a parallel, message passing version of Matlab), and compute its isoefficiency function, and show that it is scalable. Our experimental results confirm the efficiency of the algorithm also.

Keywords: Image compression, MPI, Parallel computing, Wavelets.

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Authors: Adriana Alexandru, Ovidiu Bica, Eleonora Tudora, Cristina Simona Alecu, Cristina-Adriana Alexandru, Ioan Covalcic

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This paper presents the results of the authors in designing, experimenting, assessing and transferring an innovative approach to energy education in secondary schools, aimed to enhance the quality of learning in terms of didactic curricula and pedagogic methods. The training is online delivered to youngsters via e-Books and portals specially designed for this purpose or by learning by doing via interactive games. An online educational methodology is available teachers.

Keywords: Education, eLearning, Energy Efficiency, InternetMethodology, Renewable Energy Sources.

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Authors: Ranjan Kumar Dash, Chita Ranjan Tripathy

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The evaluation of residual reliability of large sized parallel computer interconnection systems is not practicable with the existing methods. Under such conditions, one must go for approximation techniques which provide the upper bound and lower bound on this reliability. In this context, a new approximation method for providing bounds on residual reliability is proposed here. The proposed method is well supported by two algorithms for simulation purpose. The bounds on residual reliability of three different categories of interconnection topologies are efficiently found by using the proposed method

Keywords: Parallel computer network, reliability, probabilisticgraph, interconnection networks.

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Authors: Pavel Zikmund, Robert Popela

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Extreme formation is a theoretical concept of selfsustain flight when a big airliner is followed by a small UAV glider flying in the airliner wake vortex. The paper presents results of a climb analysis with the goal to lift the gliding UAV to airliners cruise altitude. Wake vortex models, the UAV drag polar and basic parameters and airliner’s climb profile are introduced at first. Afterwards, flight performance of the UAV in a wake vortex is evaluated by analytical methods. Time history of optimal distance between an airliner and the UAV during a climb is determined. The results are encouraging. Therefore available UAV drag margin for electricity generation is figured out for different vortex models.

Keywords: Flight in formation, self-sustained flight, UAV, wake vortex.

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