Search results for: Virtual Machine Software (VMware)

Authors: Wasiu O. Ajagbe, Habeeb O. Hamzat, Waris A. Adebisi

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Structural failures occur due to a number of reasons. These may include under design, poor workmanship, substandard materials, misleading laboratory tests and lots more. Reinforcing steel bar is an important construction material, hence its properties must be accurately known before being utilized in construction. Understanding this property involves carrying out mechanical tests prior to design and during construction to ascertain correlation using steel testing machine which is usually not readily available due to the location of project. This study was conducted to determine the reliability of reinforcing steel testing machines. Reconnaissance survey was conducted to identify laboratories where yield and ultimate tensile strengths tests can be carried out. Six laboratories were identified within Ibadan and environs. However, only four were functional at the time of the study. Three steel samples were tested for yield and tensile strengths, using a steel testing machine, at each of the four laboratories (LM, LO, LP and LS). The yield and tensile strength results obtained from the laboratories were compared with the manufacturer’s specification using a reliability analysis programme. Structured questionnaire was administered to the operators in each laboratory to consider their impact on the test results. The average value of manufacturers’ tensile strength and yield strength are 673.7 N/mm² and 559.7 N/mm² respectively. The tensile strength obtained from the four laboratories LM, LO, LP and LS are given as 579.4, 652.7, 646.0 and 649.9 N/mm² respectively while their yield strengths respectively are 453.3, 597.0, 550.7 and 564.7 N/mm². Minimum tensile to yield strength ratio is 1.08 for BS 4449: 2005 and 1.15 for ASTM A615. Tensile to yield strength ratio from the four laboratories are 1.28, 1.09, 1.17 and 1.15 for LM, LO, LP and LS respectively. The tensile to yield strength ratio shows that the result obtained from all the laboratories meet the code requirements used for the test. The result of the reliability test shows varying level of reliability between the manufacturers’ specification and the result obtained from the laboratories. Three of the laboratories; LO, LS and LP have high value of reliability with the manufacturer i.e. 0.798, 0.866 and 0.712 respectively. The fourth laboratory, LM has a reliability value of 0.100. Steel test should be carried out in a laboratory using the same code in which the structural design was carried out. More emphasis should be laid on the importance of code provisions.

Keywords: Reinforcing steel bars, reliability analysis, tensile strength, universal testing machine, yield strength.

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Maryam Honarmand

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Regarding to the fast growth of computer, internet, and virtual learning in our country (Iran) and need computer-based learning systems and multimedia tools as an essential part of such education, designing and implementing such systems would help teach different field such as science. This paper describes the basic principle of multimedia. At the end, with a description of learning science to the infant students, the method of this system will be explained.

Keywords: Multimedia tools, computer based learning, science, student.

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Authors: Wang Jing, Liu Shouwen, Pei Yifei

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A satellite is being integrated and tested by BISEE (Beijing Institute of Spacecraft Environment Engineering). This paper describes the infrared lamp array simulation technology used for satellite thermal balance and thermal vacuum test. These tests were performed in KM6 space environmental simulator in Beijing, China. New software and hardware developed by BISEE, along with enhanced heat flux uniformity, provided for well accomplished thermal balance and thermal vacuum tests. The flux uniformity of lamp array was satisfied with test requirement. Monitored background radiometer offered reliable heat flux measurements with remarkable repeatability. Simulation software supplied accurate thermal flux distribution predictions.

Keywords: Satellite, Thermal test, Infrared lamp array, Heatflux

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Authors: J. P. Dubois, O. M. Abdul-Latif

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Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of SAR (synthetic aperture radar) images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to real SAR images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected SAR images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (the detection hypotheses) in the original images.

Keywords: Least Square-Support Vector Machine, SyntheticAperture Radar. Partially Developed Speckle, Multi-Look Model.

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Authors: Eduardo N. Velloso, Fernando M. N. Dantas, Luciano S. Barros

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A common complaint from power system analysis students lies in the overly complex tools they need to learn and use just to simulate very basic systems or just to check the answers to power system calculations. The most basic power system studies are power-flow solutions and short-circuit calculations. This paper presents a simple tool with an intuitive interface to perform both these studies and assess its performance in comparison with existent commercial solutions. With this in mind, Elegant is a pure Python software tool for learning power system analysis developed for undergraduate and graduate students. It solves the power-flow problem by iterative numerical methods and calculates bolted short-circuit fault currents by modeling the network in the domain of symmetrical components. Elegant can be used with a user-friendly Graphical User Interface (GUI) and automatically generates human-readable reports of the simulation results. The tool is exemplified using a typical Brazilian regional system with 18 buses. This study performs a comparative experiment with 1 undergraduate and 4 graduate students who attempted the same problem using both Elegant and a commercial tool. It was found that Elegant significantly reduces the time and labor involved in basic power system simulations while still providing some insights into real power system designs.

Keywords: Free- and open-source software, power-flow, power system analysis, Python, short-circuit.

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Authors: Waralak Vongdoiwang Siricharoen

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One of object oriented software developing problem is the difficulty of searching the appropriate and suitable objects for starting the system. In this work, ontologies appear in the part of supporting the object discovering in the initial of object oriented software developing. There are many researches try to demonstrate that there is a great potential between object model and ontologies. Constructing ontology from object model is called ontology engineering can be done; On the other hand, this research is aiming to support the idea of building object model from ontology is also promising and practical. Ontology classes are available online in any specific areas, which can be searched by semantic search engine. There are also many helping tools to do so; one of them which are used in this research is Protégé ontology editor and Visual Paradigm. To put them together give a great outcome. This research will be shown how it works efficiently with the real case study by using ontology classes in travel/tourism domain area. It needs to combine classes, properties, and relationships from more than two ontologies in order to generate the object model. In this paper presents a simple methodology framework which explains the process of discovering objects. The results show that this framework has great value while there is possible for expansion. Reusing of existing ontologies offers a much cheaper alternative than building new ones from scratch. More ontologies are becoming available on the web, and online ontologies libraries for storing and indexing ontologies are increasing in number and demand. Semantic and Ontologies search engines have also started to appear, to facilitate search and retrieval of online ontologies.

Keywords: Software Developing, Ontology, Ontology Library, Artificial Intelligent, Protégé, Object Model.

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Authors: G. Schuh, S. Aghassi

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In order to bridge the gap between research and industry, promoting technology and knowledge transfer becomes increasingly important. Especially small- and medium-sized enterprises, having only little R&D resources themselves, depend on external technology development activities for remaining innovative. Academia research on the other hand needs potential industrial partners, who are capable and willing to commercialize their technologies as most public funding programs require some sort of technology transfer or dissemination activities. Modern web technologies offer more and more “social” functionalities and open up new ways of user interaction. In the past years several technology transfer platforms were developed, making use of modern web technologies in order to enable and support technology transfer. In this paper we report on the results of a state-of-the art analyses of existing technology transfer platforms, point out their advantages and deficits and give a perspective to the development of an improved technology transfer platform.

Keywords: Knowledge transfer, social software, technology management, technology transfer.

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Authors: Marcel Chevalier, Léo Dupont, Sylvain Marié, Frédérique Roffet, Elena Stolyarova, William Templier, Costin Vasile

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Industrial end users are currently facing an increasing need to reduce the risk of unexpected failures and optimize their maintenance. This calls for both short-term analysis and long-term ageing anticipation. At Schneider Electric, we tackle those two issues using both Machine Learning and First Principles models. Machine learning models are incrementally trained from normal data to predict expected values and detect statistically significant short-term deviations. Ageing models are constructed from breaking down physical systems into sub-assemblies, then determining relevant degradation modes and associating each one to the right kinetic law. Validating such anomaly detection and maintenance models is challenging, both because actual incident and ageing data are rare and distorted by human interventions, and incremental learning depends on human feedback. To overcome these difficulties, we propose to simulate physics, systems and humans – including asset maintenance operations – in order to validate the overall approaches in accelerated time and possibly choose between algorithmic alternatives.

Keywords: Degradation models, ageing, anomaly detection, soft sensor, incremental learning.

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Authors: Muhammad Marsudi, Hani Shafeek

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The purpose of this paper is to simulate the production process of a metal stamping industry and to evaluate the utilization of the production line by using ARENA simulation software. The process time and the standard time for each process of the production line is obtained from data given by the company management. Other data are collected through direct observation of the line. There are three work stations performing ten different types of processes in order to produce a single product type. Arena simulation model is then developed based on the collected data. Verification and validation are done to the Arena model, and finally the result of Arena simulation can be analyzed. It is found that utilization at each workstation will increase if batch size is increased although throughput rate remains/is kept constant. This study is very useful for the company because the company needs to improve the efficiency and utilization of its production lines.

Keywords: Arena software, case study, production line, utilization.

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Authors: Walid S. Abd El-hamid, Sherif S. El-Etriby, Mohiy M. Hadhoud

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Regression testing is a maintenance activity applied to modified software to provide confidence that the changed parts are correct and that the unchanged parts have not been adversely affected by the modifications. Regression test selection techniques reduce the cost of regression testing, by selecting a subset of an existing test suite to use in retesting modified programs. This paper presents the first general regression-test-selection technique, which based on code and allows selecting test cases for any programs written in any programming language. Then it handles incomplete program. We also describe RTSDiff, a regression-test-selection system that implements the proposed technique. The results of the empirical studied that performed in four programming languages java, C#, Cµ and Visual basic show that the efficiency and effective in reducing the size of test suit.

Keywords: Regression testing, testing, test selection, softwareevolution, software maintenance.

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Authors: J. Palecek, R. Hajkova, A. Oulehlova, H. Malachova

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Increase of emergency incidents and crisis situations requires proactive crisis management of authorities and for its solution. Application Business Continuity Management helps the crisis management authorities to quickly and responsibly respond to threats. It also helps effectively and efficiently planning powers and resources. The main goal of this article is describing Military Continuity Management System (MCMS) based on the principles of Business Continuity Management System (BCMS) for dealing with floods in the territory of the selected municipalities. There are explained steps of loading, running and evaluating activities in the software application MCMS. Software MCMS provides complete control over the tasks, contribute a comprehensive and responsible approach solutions to solution floods in the municipality.

Keywords: Business Continuity Management, Floods Plan, Flood Activity, Level of Flood Activity.

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Authors: Marine Segui, Ruxandra Mihaela Botez

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OpenVSP is an aerodynamic solver developed by National Aeronautics and Space Administration (NASA) that allows building a reliable model of an aircraft. This software performs an aerodynamic simulation according to the angle of attack of the aircraft makes between the incoming airstream, and its speed. A reliable aerodynamic model of the Cessna Citation X was designed but it required a lot of computation time. As a consequence, a prediction method was established that allowed predicting lift and drag coefficients for all Mach numbers and for all angles of attack, exclusively for stall conditions, from a computation of three angles of attack and only one Mach number. Aerodynamic coefficients given by the prediction method for a Cessna Citation X model were finally compared with aerodynamics coefficients obtained using a complete OpenVSP study.

Keywords: Aerodynamic, coefficient, cruise, improving, longitudinal, OpenVSP, solver, time.

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Authors: Andreas Heindl, Alexander K. Seewald, Martin Schepelmann, Radu Rogojanu, Giovanna Bises, Theresia Thalhammer, Isabella Ellinger

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Bone remodeling occurs by the balanced action of bone resorbing osteoclasts (OC) and bone-building osteoblasts. Increased bone resorption by excessive OC activity contributes to malignant and non-malignant diseases including osteoporosis. To study OC differentiation and function, OC formed in in vitro cultures are currently counted manually, a tedious procedure which is prone to inter-observer differences. Aiming for an automated OC-quantification system, classification of OC and precursor cells was done on fluorescence microscope images based on the distinct appearance of fluorescent nuclei. Following ellipse fitting to nuclei, a combination of eight features enabled clustering of OC and precursor cell nuclei. After evaluating different machine-learning techniques, LOGREG achieved 74% correctly classified OC and precursor cell nuclei, outperforming human experts (best expert: 55%). In combination with the automated detection of total cell areas, this system allows to measure various cell parameters and most importantly to quantify proteins involved in osteoclastogenesis.

Keywords: osteoclasts, machine learning, ellipse fitting.

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Authors: Wei-Jong Yang, Yu-Siang Su, Pau-Choo Chung, Jar-Ferr Yang

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Moving object detection (MOD) is an important issue in advanced driver assistance systems (ADAS). There are two important moving objects, pedestrians and scooters in ADAS. In real-world systems, there exist two important challenges for MOD, including the computational complexity and the detection accuracy. The histogram of oriented gradient (HOG) features can easily detect the edge of object without invariance to changes in illumination and shadowing. However, to reduce the execution time for real-time systems, the image size should be down sampled which would lead the outlier influence to increase. For this reason, we propose the histogram of uniformly-oriented gradient (HUG) features to get better accurate description of the contour of human body. In the testing phase, the support vector machine (SVM) with linear kernel function is involved. Experimental results show the correctness and effectiveness of the proposed method. With SVM classifiers, the real testing results show the proposed HUG features achieve better than classification performance than the HOG ones.

Keywords: Moving object detection, histogram of oriented gradient histogram of oriented gradient, histogram of uniformly-oriented gradient, linear support vector machine.

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Authors: Hassan Haghighi, Sajad Ghorbani, Maryam Mohebati, Mohammad Mahdi Javanmard

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One of the most important aspects expected from ERP systems is to integrate various operations existing in administrative, financial, commercial, human resources, and production departments of the consumer organization. Also, it is often needed to integrate the new ERP system with the organization legacy systems when implementing the ERP package in the organization. Without relying on an appropriate software architecture to realize the required integration, ERP implementation processes become error prone and time consuming; in some cases, the ERP implementation may even encounters serious risks. In this paper, we propose a new architecture that is based on the agent oriented vision and supplies the integration expected from ERP systems using several independent but cooperator agents. Besides integration which is the main issue of this paper, the presented architecture will address some aspects of intelligence and learning capabilities existing in ERP systems

Keywords: enterprise resource planning, software architecture, agent oriented architecture, integration, intelligence, learning.

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Authors: R. Suresh, Pavan Kumar Nimmagadda, Ming Zo Tan, Shane Hart, Sharp Ugwuocha

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Polycrystalline diamond compact (PDC) drill bits are extensively used in the oil and gas industry as well as the mining industry. Industry engineers continually improve upon PDC drill bit designs and hydraulic conditions. Optimized injection nozzles play a key role in improving the drilling performance and efficiency of these ever changing PDC drill bits. In the first part of this study, computational fluid dynamics (CFD) modelling is performed to investigate the hydrodynamic characteristics of drilling fluid flow around the PDC drill bit. An Open-source CFD software – OpenFOAM simulates the flow around the drill bit, based on the field input data. A specifically developed console application integrates the entire CFD process including, domain extraction, meshing, and solving governing equations and post-processing. The results from the OpenFOAM solver are then compared with that of the ANSYS Fluent software. The data from both software programs agree. The second part of the paper describes the parametric study of the PDC drill bit nozzle to determine the effect of parameters such as number of nozzles, nozzle velocity, nozzle radial position and orientations on the flow field characteristics and bit washing patterns. After analyzing a series of nozzle configurations, the best configuration is identified and recommendations are made for modifying the PDC bit design.

Keywords: ANSYS Fluent, computational fluid dynamics, nozzle configuration, OpenFOAM, PDC dill bit.

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Authors: Faisal A. Aburub

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Organizations today need to invest in software in order to run their businesses, and to the organizations’ objectives, the software should be in line with the business process. This research presents an approach for linking process models and system models. Particularly, the new approach aims to synthesize sequence diagram based on role activity diagram (RAD) model. The approach includes four steps namely: Create business process model using RAD, identify computerized activities, identify entities in sequence diagram and identify messages in sequence diagram. The new approach has been validated using the process of student registration in University of Petra as a case study. Further research is required to validate the new approach using different domains.

Keywords: Business process modelling, system models, role activity diagrams, sequence diagrams.

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Authors: Li Xu, Huanbao Jiang, Zhenfei Huang, Lailai Zhang

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In recent years, as global warming, the sea-ice extent of North Arctic undergoes an evident decrease and Arctic channel has attracted the attention of shipping industry. Ice crystals existing in the seawater of Arctic channel which enter the seawater system of the ship with the seawater were found blocking the seawater pipe. The appearance of cooler paralysis, auxiliary machine error and even ship power system paralysis may be happened if seriously. In order to reduce the effect of high temperature in auxiliary equipment, seawater system will use external ice-water to participate in the cooling cycle and achieve the state of its flow. The distribution of ice crystals in seawater pipe can be achieved. As the ice slurry system is solid liquid two-phase system, the flow process of ice-water mixture is very complex and diverse. In this paper, the flow process in seawater pipe of ice slurry is simulated with fluid dynamics simulation software based on k-ε turbulence model. As the ice packing fraction is a key factor effecting the distribution of ice crystals, the influence of ice packing fraction on the flowing process of ice slurry is analyzed. In this work, the simulation results show that as the ice packing fraction is relatively large, the distribution of ice crystals is uneven in the flowing process of the seawater which has such disadvantage as increase the possibility of blocking, that will provide scientific forecasting methods for the forming of ice block in seawater piping system. It has important significance for the reliability of the operating of polar ships in the future.

Keywords: Ice slurry, seawater pipe, ice packing fraction, numerical simulation.

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Authors: Francisco J. Lopez-Jaquez, Sandra E. Ramirez-Jara

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This paper presents an implementation and performance test of a distributed motion control system based on a master-slave configuration used to move a plasma-cutting torch over a predefined trajectory. The master is a general-purpose computer running on an open source operating system platform and software developer. Software running in the master computer generates commands on real time and we measure performance based on a selected set of differences between expected and observed distances. We are testing the null hypothesis that the outcome trajectory is identical to the input against the alternative hypothesis that there is a shift to the right or left of the input one. We used the Wilcoxon signed ranks test method for the hypothesis test.

Keywords: Distributed, motion, control, real-time, contouring.

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Authors: Keyvan Shahgholian, Hamid Hajihosseini

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The significance of environmental protection is wellknown in today's world. The execution of any program depends on sufficient knowledge and required familiarity with environment and its pollutants. Taking advantage of a systematic method, as a new science, in environmental planning can solve many problems. In this article, air pollution in Tehran and its relationship with health and population growth have been analyzed using dynamic systems. Firstly, by using casual loops, the relationship between the parameters effective on air pollution in Tehran were taken into consideration, then these casual loops were turned into flow diagrams [6], and finally, they were simulated using the software Vensim [16]in order to conclude what the effect of each parameter will be on air pollution in Tehran in the next 10 years, how changing of one or more parameters influences other parameters, and which parameter among all other parameters requires to be controlled more.

Keywords: Air pollutions, Simulation, System Dynamics, Tehran, Vensim.

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Authors: A. Nusrath Unissa, Sameer Hassan, Luke Elizabeth Hanna

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Altered drug binding may be an important factor in isoniazid (INH) resistance, rather than major changes in the enzyme’s activity as a catalase or peroxidase (KatG). The identification of structural or functional defects in the mutant KatGs responsible for INH resistance remains as an area to be explored. In this connection, the differences in the binding affinity between wild-type (WT) and mutants of KatG were investigated, through the generation of three mutants of KatG, Ser315Thr [S315T], Ser315Asn [S315N], Ser315Arg [S315R] and a WT [S315]) with the help of software-MODELLER. The mutants were docked with INH using the software-GOLD. The affinity is lower for WT than mutant, suggesting the tight binding of INH with the mutant protein compared to WT type. These models provide the in silico evidence for the binding interaction of KatG with INH and implicate the basis for rationalization of INH resistance in naturally occurring KatG mutant strains of Mycobacterium tuberculosis.

Keywords: Mycobacterium tuberculosis, KatG, INH resistance, Mutants, Modeling, Docking.

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Authors: M. H. Arslan, U. K. Sahin, H. Acikgoz-Tufan, I. Gocek, I. Erdem

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Various exterior factors have perpetual effects on textile materials during wear, use and laundering in everyday life. In accordance with their frequency of use, textile materials are required to be laundered at certain intervals. The medium in which the laundering process takes place have inevitable detrimental physical and chemical effects on textile materials caused by the unique parameters of the process inherently existing. Connatural structures of various textile materials result in many different physical, chemical and mechanical characteristics. Because of their specific structures, these materials have different behaviors against several exterior factors. By modeling the behavior of commercial and test textiles as group-wise against laundering process, it is possible to disclose the relation in between these two groups of materials, which will lead to better understanding of their behaviors in terms of similarities and differences against the washing parameters of the laundering. Thus, the goal of the current research is to examine the behavior of two groups of textile materials as commercial textiles and as test textiles towards the main washing machine parameters during laundering process such as temperature, load quantity, mechanical action and level of water amount by concentrating on shrinkage, pilling, sewing defects, collar abrasion, the other defects other than sewing, whitening and overall properties of textiles. In this study, cotton fabrics were preferred as commercial textiles due to the fact that garments made of cotton are the most demanded products in the market by the textile consumers in daily life. Full factorial experimental set-up was used to design the experimental procedure. All profiles always including all of the commercial and the test textiles were laundered for 20 cycles by commercial home laundering machine to investigate the effects of the chosen parameters. For the laundering process, a modified version of ‘‘IEC 60456 Test Method’’ was utilized. The amount of detergent was altered as 0.5% gram per liter depending on varying load quantity levels. Datacolor 650®, EMPA Photographic Standards for Pilling Test and visual examination were utilized to test and characterize the textiles. Furthermore, in the current study the relation in between commercial and test textiles in terms of their performance was deeply investigated by the help of statistical analysis performed by MINITAB® package program modeling their behavior against the parameters of the laundering process. In the experimental work, the behaviors of both groups of textiles towards washing machine parameters were visually and quantitatively assessed in dry state.

Keywords: Behavior against washing machine parameters, performance evaluation of textiles, statistical analysis, commercial and test textiles.

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Authors: M. A. S. Fahim, J. Sužiedelytė Visockienė

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With the growing concern over air pollution (AP), it is clear that this has gained more prominence than ever before. The level of consciousness has increased and a sense of knowledge now has to be forwarded as a duty by those enlightened enough to disseminate it to others. This realization often comes after an understanding of how poor air quality indices (AQI) damage human health. The study focuses on assessing air pollution prediction models specifically for Lithuania, addressing a substantial need for empirical research within the region. Concentrating on Vilnius, it specifically examines particulate matter concentrations 10 micrometers or less in diameter (PM10). Utilizing Gaussian Process Regression (GPR) and Regression Tree Ensemble, and Regression Tree methodologies, predictive forecasting models are validated and tested using hourly data from January 2020 to December 2022. The study explores the classification of AP data into anthropogenic and natural sources, the impact of AP on human health, and its connection to cardiovascular diseases. The study revealed varying levels of accuracy among the models, with GPR achieving the highest accuracy, indicated by an RMSE of 4.14 in validation and 3.89 in testing.

Keywords: Air pollution, anthropogenic and natural sources, machine learning, Gaussian process regression, tree ensemble, forecasting models, particulate matter.

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Authors: M.V. Shyla, K.B. Naidu

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The objective of this paper is to develop a computational model of human nasal cavity from computed tomography (CT) scans using MIMICS software. Computational fluid dynamic techniques were employed to understand nasal airflow. Gambit and Fluent software was used to perform CFD simulation. Velocity profiles, iteration plots, pressure distribution, streamline and pathline patterns for steady, laminar airflow inside the human nasal cavity of healthy and also infected persons are presented in detail. The implications for olfaction are visualized. Results are validated with the available numerical and experimental data. The graphs reveal that airflow varies with different anatomical nasal structures and only fraction of the inspired air reaches the olfactory region. The Deviations in the results suggest that the treatment of infected volunteers will improve the olfactory function.

Keywords: CFD techniques, Finite Volume Method, Fluid dynamic sniffing, Human nasal cavity.

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Authors: Shiwei Deng, Yang Bao

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In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.

Keywords: Dependence analysis, EFSM model, greedy algorithm, regression test.

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Authors: Kyung-Jung Lee, Hyun-Sik Ahn

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This paper suggests a design methodology for the hardware and software of the electronic control unit (ECU) of safety-critical vehicle applications such as braking and steering. The architecture of the hardware is a high integrity system such thatit incorporates a high performance 32-bit CPU and a separate peripheral controlprocessor (PCP) together with an external watchdog CPU. Communication between the main CPU and the PCP is executed via a common area of RAM and events on either processor which are invoked by interrupts. Safety-related software is also implemented to provide a reliable, self-testing computing environment for safety critical and high integrity applications. The validity of the design approach is shown by using the hardware-in-the-loop simulation (HILS)for electric power steering(EPS) systemswhich consists of the EPS mechanism, the designed ECU, and monitoring tools.

Keywords: Electronic control unit, electric power steering, functional safety, hardware-in-the-loop simulation.

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Authors: Montri Phothisonothai, Masahiro Nakagawa

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The objective of this paper is to characterize the spontaneous Electroencephalogram (EEG) signals of four different motor imagery tasks and to show hereby a possible solution for the present binary communication between the brain and a machine ora Brain-Computer Interface (BCI). The processing technique used in this paper was the fractal analysis evaluated by the Critical Exponent Method (CEM). The EEG signal was registered in 5 healthy subjects,sampling 15 measuring channels at 1024 Hz.Each channel was preprocessed by the Laplacian space ltering so as to reduce the space blur and therefore increase the spaceresolution. The EEG of each channel was segmented and its Fractaldimension (FD) calculated. The FD was evaluated in the time interval corresponding to the motor imagery and averaged out for all the subjects (each channel). In order to characterize the FD distribution,the linear regression curves of FD over the electrodes position were applied. The differences FD between the proposed mental tasks are quantied and evaluated for each experimental subject. The obtained results of the proposed method are a substantial fractal dimension in the EEG signal of motor imagery tasks and can be considerably utilized as the multiple-states BCI applications.

Keywords: electroencephalogram (EEG), motor imagery tasks, mental tasks, biomedical signals processing, human-machine interface, fractal analysis, critical exponent method (CEM).

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Authors: Hyunchul Ahn, Kyoung-Jae Kim

Abstract:

Corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has been one of the attractive research topics in the literature. In recent years, multiclass classification models such as artificial neural network (ANN) or multiclass support vector machine (MSVM) have become a very appealing machine learning approaches due to their good performance. However, most of them have only focused on classifying samples into nominal categories, thus the unique characteristic of the credit rating - ordinality - has been seldom considered in their approaches. This study proposes new types of ANN and MSVM classifiers, which are named OMANN and OMSVM respectively. OMANN and OMSVM are designed to extend binary ANN or SVM classifiers by applying ordinal pairwise partitioning (OPP) strategy. These models can handle ordinal multiple classes efficiently and effectively. To validate the usefulness of these two models, we applied them to the real-world bond rating case. We compared the results of our models to those of conventional approaches. The experimental results showed that our proposed models improve classification accuracy in comparison to typical multiclass classification techniques with the reduced computation resource.

Keywords: Artificial neural network, Corporate credit rating, Support vector machines, Ordinal pairwise partitioning

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Authors: Hui-Yu Huang, Shih-Hang Hsu

Abstract:

In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.

Keywords: Gabor filter, improved active shape model (IASM), principal component analysis (PCA), face alignment, face recognition, support vector machine (SVM)

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