Search results for: computational model(s)

Authors: Maziar Ahmad Sharbafi, Caro Lucas, Abolfazel Toroghi Haghighat, Omid AmirGhiasvand, Omid Aghazade

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RoboCup Rescue simulation as a large-scale Multi agent system (MAS) is one of the challenging environments for keeping coordination between agents to achieve the objectives despite sensing and communication limitations. The dynamicity of the environment and intensive dependency between actions of different kinds of agents make the problem more complex. This point encouraged us to use learning-based methods to adapt our decision making to different situations. Our approach is utilizing reinforcement leaning. Using learning in rescue simulation is one of the current ways which has been the subject of several researches in recent years. In this paper we present an innovative learning method implemented for Police Force (PF) Agent. This method can cope with the main difficulties that exist in other learning approaches. Different methods used in the literature have been examined. Their drawbacks and possible improvements have led us to the method proposed in this paper which is fast and accurate. The Brain Emotional Learning Based Intelligent Controller (BELBIC) is our solution for learning in this environment. BELBIC is a physiologically motivated approach based on a computational model of amygdale and limbic system. The paper presents the results obtained by the proposed approach, showing the power of BELBIC as a decision making tool in complex and dynamic situation.

Keywords: Emotional learning, rescue, simulation environment, RoboCup, multi-agent system.

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Authors: Fatemeh Afsharnia, Mohammad Amin Asoodar, Abbas Abdeshahi

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In economical evaluation literature, although the combination of some variables such as repair and maintenance costs and accumulated use hours has been widely considered in determining of optimum life for tractor, no investigation has indicated the influence of failure rate on repair and maintenance costs. In this study, the owners of three hundred tractors, which include Massey Ferguson, John Deere and Universal, were interviewed, from five regions of Khouzestan Province. A regression model was used to predict the tractors annual repair and maintenance costs based on failure rate. Results showed that the maximum percentage of annual repair and maintenance costs occurred in engine parts for MF285, JD3140 and U650 tractors while these costs for tire, ring, ball bearing and operator seat were higher compared to other MF399 tractor systems. According to the results of the regression, the failure rate increase would lead to annual repair and maintenance costs increase for all tractors. But, of all the tractors, repair and maintenance costs of JD3140 tractors extremely affected by the failure rate increase.

Keywords: Failure rate, tractor, annual repair and maintenance costs, regression model, Khouzestan.

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Authors: Kyoungwoo Park, Chol-Ho Hong, Ji-Won Han, Byeong-Sam Kim, Cha-Sik Park, Oh Kyung Kwon

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Numerical analysis of flow characteristics and separation efficiency in a high-efficiency cyclone has been performed. Several models based on the experimental observation for a design purpose were proposed. However, the model is only estimated the cyclone's performance under the limited environments; it is difficult to obtain a general model for all types of cyclones. The purpose of this study is to find out the flow characteristics and separation efficiency numerically. The Reynolds stress model (RSM) was employed instead of a standard k-ε or a k-ω model which was suitable for isotropic turbulence and it could predict the pressure drop and the Rankine vortex very well. For small particles, there were three significant components (entrance of vortex finder, cone, and dust collector) for the particle separation. In the present work, the particle re-entraining phenomenon from the dust collector to the cyclone body was observed after considerable time. This re-entrainment degraded the separation efficiency and was one of the significant factors for the separation efficiency of the cyclone.

Keywords: CFD, High-efficiency cyclone, Pressure drop, Rankine vortex, Reynolds stress model (RSM), Separation efficiency.

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Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar

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Several meteorological parameters were used for the  prediction of monthly average daily global solar radiation on  horizontal using recurrent neural networks (RNNs). Climatological  data and measures, mainly air temperature, humidity, sunshine  duration, and wind speed between 1995 and 2007 were used to design  and validate a feed forward and recurrent neural network based  prediction systems. In this paper we present our reference system  based on a feed-forward multilayer perceptron (MLP) as well as the  proposed approach based on an RNN model. The obtained results  were promising and comparable to those obtained by other existing  empirical and neural models. The experimental results showed the  advantage of RNNs over simple MLPs when we deal with time series  solar radiation predictions based on daily climatological data.

Keywords: Recurrent Neural Networks, Global Solar Radiation, Multi-layer perceptron, gradient, Root Mean Square Error.

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Authors: Md R. Bashar, Yan Li, Peng Wen

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This study is to investigate the electroencephalogram (EEG) differences generated from a normal and Alzheimer-s disease (AD) sources. We also investigate the effects of brain tissue distortions due to AD on EEG. We develop a realistic head model from T1 weighted magnetic resonance imaging (MRI) using finite element method (FEM) for normal source (somatosensory cortex (SC) in parietal lobe) and AD sources (right amygdala (RA) and left amygdala (LA) in medial temporal lobe). Then, we compare the AD sourced EEGs to the SC sourced EEG for studying the nature of potential changes due to sources and 5% to 20% brain tissue distortions. We find an average of 0.15 magnification errors produced by AD sourced EEGs. Different brain tissue distortion models also generate the maximum 0.07 magnification. EEGs obtained from AD sources and different brain tissue distortion levels vary scalp potentials from normal source, and the electrodes residing in parietal and temporal lobes are more sensitive than other electrodes for AD sourced EEG.

Keywords: Alzheimer's disease (AD), brain tissue distortion, electroencephalogram, finite element method.

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Authors: C. Ardil

Abstract:

The paper presents a multiple criteria decision making analysis process to determine the most suitable regional aircraft type according to a set of evaluation criteria. The main purpose of this study is to use different decision making methods to determine the most suitable regional aircraft for aviation operators. In this context, the nine regional aircraft types were analyzed using multiple criteria decision making analysis methods. Preference analysis for reference ideal solution (PARIS) was used in regional aircraft selection process. The findings of the proposed model show that the ranking results of the multiple criteria decision making models are consistent with each other, and the proposed method is efficient, and the results are valid. Finally, the Embraer E195-E2 model regional aircraft is chosen as the most suitable aircraft type.

Keywords: aircraft, regional aircraft selection, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS

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Authors: Amr Almaddah, Sadi Vural, Yasushi Mae, Kenichi Ohara, Tatsuo Arai

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In this paper, we propose a robust face relighting technique by using spherical space properties. The proposed method is done for reducing the illumination effects on face recognition. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients. First, an internal training illumination database is generated by computing face albedo and face normal from 2D images under different lighting conditions. Based on the generated database, we analyze the target face pixels and compare them with the training bootstrap by using pre-generated tiles. In this work, practical real time processing speed and small image size were considered when designing the framework. In contrast to other works, our technique requires no 3D face models for the training process and takes a single 2D image as an input. Experimental results on publicly available databases show that the proposed technique works well under severe lighting conditions with significant improvements on the face recognition rates.

Keywords: Face synthesis and recognition, Face illumination recovery, 2D spherical spaces, Vision for graphics.

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Authors: Noor Asma Husain, Mohd Shafry Mohd Rahim, Abdullah Bade

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Subdivision surfaces were applied to the entire meshes in order to produce smooth surfaces refinement from coarse mesh. Several schemes had been introduced in this area to provide a set of rules to converge smooth surfaces. However, to compute and render all the vertices are really inconvenient in terms of memory consumption and runtime during the subdivision process. It will lead to a heavy computational load especially at a higher level of subdivision. Adaptive subdivision is a method that subdivides only at certain areas of the meshes while the rest were maintained less polygons. Although adaptive subdivision occurs at the selected areas, the quality of produced surfaces which is their smoothness can be preserved similar as well as regular subdivision. Nevertheless, adaptive subdivision process burdened from two causes; calculations need to be done to define areas that are required to be subdivided and to remove cracks created from the subdivision depth difference between the selected and unselected areas. Unfortunately, the result of adaptive subdivision when it reaches to the higher level of subdivision, it still brings the problem with memory consumption. This research brings to iterative process of adaptive subdivision to improve the previous adaptive method that will reduce memory consumption applied on triangular mesh. The result of this iterative process was acceptable better in memory and appearance in order to produce fewer polygons while it preserves smooth surfaces.

Keywords: Subdivision surfaces, adaptive subdivision, selectioncriteria, handle cracks, smooth surface

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: Intrusion prevention, network security, optimal policy, Q-learning.

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Authors: A. J. Al-Shareef, E. A. Mohamed, E. Al-Judaibi

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Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.

Keywords: Artificial neural networks, short-term load forecasting, back propagation.

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Authors: S. Dan'azumi, S. Shamsudin, A. A. Rahman

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Rainfall data at fine resolution and knowledge of its characteristics plays a major role in the efficient design and operation of agricultural, telecommunication, runoff and erosion control as well as water quality control systems. The paper is aimed to study the statistical distribution of hourly rainfall depth for 12 representative stations spread across Peninsular Malaysia. Hourly rainfall data of 10 to 22 years period were collected and its statistical characteristics were estimated. Three probability distributions namely, Generalized Pareto, Exponential and Gamma distributions were proposed to model the hourly rainfall depth, and three goodness-of-fit tests, namely, Kolmogorov-Sminov, Anderson-Darling and Chi-Squared tests were used to evaluate their fitness. Result indicates that the east cost of the Peninsular receives higher depth of rainfall as compared to west coast. However, the rainfall frequency is found to be irregular. Also result from the goodness-of-fit tests show that all the three models fit the rainfall data at 1% level of significance. However, Generalized Pareto fits better than Exponential and Gamma distributions and is therefore recommended as the best fit.

Keywords: Goodness-of-fit test, Hourly rainfall, Malaysia, Probability distribution.

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Authors: Evgeniia V. Mekhonoshina, Vladimir Ya. Modorskii, Vasilii Yu. Petrov

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At present, vibrations of rotors of gas transmittal unit evade sustainable forecasting. This paper describes elastic oscillation modes in resilient supports and rotor impellers modeled during computational experiments with regard to interference in the system of gas-dynamic flow and compressor rotor. Verification of aeroelastic approach was done on model problem of interaction between supersonic jet in shock tube with deformed plate. ANSYS 15.0 engineering analysis system was used as a modeling tool of numerical simulation in this paper. Finite volume method for gas dynamics and finite elements method for assessment of the strain stress state (SSS) components were used as research methods. Rotation speed and material’s elasticity modulus varied during calculations, and SSS components and gas-dynamic parameters in the dynamic system of gas-dynamic flow and compressor rotor were evaluated. The analysis of time dependence demonstrated that gas-dynamic parameters near the rotor blades oscillate at 200 Hz, and SSS parameters at the upper blade edge oscillate four times higher, i.e. with blade frequency. It has been detected that vibration amplitudes correction in the test points at magnetic bearings by aeroelasticity may correspond up to 50%, and about -π/4 for phases.

Keywords: Centrifugal compressor, aeroelasticity, interdisciplinary calculation, oscillation phase displacement, vibration, nonstationarity.

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Authors: A.H.M.A.Rahim

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The impact of fixed speed squirrel cage type as well as variable speed doubly fed induction generators (DFIG) on dynamic performance of a multimachine power system has been investigated. Detailed models of the various components have been presented and the integration of asynchronous and synchronous generators has been carried out through a rotor angle based transform. Simulation studies carried out considering the conventional dynamic model of squirrel cage asynchronous generators show that integration, as such, could degrade to the AC system performance transiently. This article proposes a frequency or power controller which can effectively control the transients and restore normal operation of fixed speed induction generator quickly. Comparison of simulation results between classical cage and doubly-fed induction generators indicate that the doubly fed induction machine is more adaptable to multimachine AC system. Frequency controller installed in the DFIG system can also improve its transient profile.

Keywords: Doubly-fed generator, Induction generator, Multimachine system modeling, Wind energy systems

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Authors: Dimitrios Zarpalas, Anastasios Zafeiropoulos, Petros Daras, Nicos Maglaveras

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Segmentation techniques based on Active Contour Models have been strongly benefited from the use of prior information during their evolution. Shape prior information is captured from a training set and is introduced in the optimization procedure to restrict the evolution into allowable shapes. In this way, the evolution converges onto regions even with weak boundaries. Although significant effort has been devoted on different ways of capturing and analyzing prior information, very little thought has been devoted on the way of combining image information with prior information. This paper focuses on a more natural way of incorporating the prior information in the level set framework. For proof of concept the method is applied on hippocampus segmentation in T1-MR images. Hippocampus segmentation is a very challenging task, due to the multivariate surrounding region and the missing boundary with the neighboring amygdala, whose intensities are identical. The proposed method, mimics the human segmentation way and thus shows enhancements in the segmentation accuracy.

Keywords: Medical imaging & processing, Brain MRI segmentation, hippocampus segmentation, hippocampus-amygdala missingboundary, weak boundary segmentation, region based segmentation, prior information, local weighting scheme in level sets, spatialdistribution of labels, gradient distribution on boundary.

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Authors: Mussa I. Mgwatu, Reuben R. M. Kainkwa

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Wind is among the potential energy resources which can be harnessed to generate wind energy for conversion into electrical power. Due to the variability of wind speed with time and height, it becomes difficult to predict the generated wind energy more optimally. In this paper, an attempt is made to establish a probabilistic model fitting the wind speed data recorded at Makambako site in Tanzania. Wind speeds and direction were respectively measured using anemometer (type AN1) and wind Vane (type WD1) both supplied by Delta-T-Devices at a measurement height of 2 m. Wind speeds were then extrapolated for the height of 10 m using power law equation with an exponent of 0.47. Data were analysed using MINITAB statistical software to show the variability of wind speeds with time and height, and to determine the underlying probability model of the extrapolated wind speed data. The results show that wind speeds at Makambako site vary cyclically over time; and they conform to the Weibull probability distribution. From these results, Weibull probability density function can be used to predict the wind energy.

Keywords: Probabilistic models, wind speed, wind energy

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Authors: Mohamed Hafez, Georg Hausner

Abstract:

The full length mitochondrial small subunit ribosomal (mt-rns) gene has been characterized for Ophiostoma novo-ulmi subspecies americana. The gene was also characterized for Ophiostoma ulmi and a group II intron was noted in the mt-rns gene of O. ulmi. The insertion in the mt-rns gene is at position S952 and it is a group IIB1 intron that encodes a double motif LAGLIDADG homing endonuclease from an open reading frame located within a loop of domain III. Secondary structure models for the mt-rns RNA of O. novo-ulmi subsp. americana and O. ulmi were generated to place the intron within the context of the ribosomal RNA. The in vivo splicing of the O.ul-mS952 group II intron was confirmed with reverse transcription-PCR. A survey of 182 strains of Dutch Elm Diseases causing agents showed that the mS952 intron was absent in what is considered to be the more aggressive species O. novo-ulmi but present in strains of the less aggressive O. ulmi. This observation suggests that the O.ul-mS952 intron can be used as a PCR-based molecular marker to discriminate between O. ulmi and O. novo-ulmi subsp. americana.

Keywords: Dutch Elm Disease, group II introns, mtDNA, species identification

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Authors: Pradeep Singh, Shrish Verma

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Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. Earlier we predicted the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven datasets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: Software Metrics, Fault prediction, Cross project, Within project.

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Authors: T. Yilmaz, N. Kirac

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Beam-column elements are defined as structural members subjected to a combination of axial and bending forces. Lateral torsional buckling is one of the major failure modes in which beam-columns that are bent about its strong axis may buckle out of the plane by deflecting laterally and twisting. This study presents a compact closed-form equation that it can be used for calculating critical lateral torsional-buckling load of beam-columns with monosymmetric sections in the presence of a known axial load. Lateral-torsional buckling behavior of beam-columns subjected to constant axial force and various transverse load cases are investigated by using Ritz method in order to establish proposed equation. Lateral-torsional buckling loads calculated by presented formula are compared to finite element model results. ABAQUS software is utilized to generate finite element models of beam-columns. It is found out that lateral-torsional buckling load of beam-columns with monosymmetric sections can be determined by proposed equation and can be safely used in design.

Keywords: Lateral-torsional buckling, stability, beam-column, monosymmetric section.

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Authors: Morteza Zahedi, Philippe Dreuw, Thomas Deselaers, Hermann Ney

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Sign language is used by the deaf and hard of hearing people for communication. Automatic sign language recognition is a challenging research area since sign language often is the only way of communication for the deaf people. Sign language includes different components of visual actions made by the signer using the hands, the face, and the torso, to convey his/her meaning. To use different aspects of signs, we combine the different groups of features which have been extracted from the image frames recorded directly by a stationary camera. We combine the features in two levels by employing three techniques. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, or by concatenating feature groups over time and using LDA to choose the most discriminant elements. At the model level, a late fusion of differently trained models can be carried out by a log-linear model combination. In this paper, we investigate these three combination techniques in an automatic sign language recognition system and show that the recognition rate can be significantly improved.

Keywords: American sign language, appearance-based features, Feature combination, Sign language recognition

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Authors: Antoni Grau, Yolanda Bolea, Alberto Sanfeliu

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Embedding Sustainability in technological curricula has become a crucial factor for educating engineers with competences in sustainability. The Technical University of Catalonia UPC, in 2008, designed the Sustainable Technology Excellence Program STEP 2015 in order to assure a successful Sustainability Embedding. This Program takes advantage of the opportunity that the redesign of all Bachelor and Master Degrees in Spain by 2010 under the European Higher Education Area framework offered. The STEP program goals are: to design compulsory courses in each degree; to develop the conceptual base and identify reference models in sustainability for all specialties at UPC; to create an internal interdisciplinary network of faculty from all the schools; to initiate new transdisciplinary research activities in technology-sustainability-education; to spread the know/how attained; to achieve international scientific excellence in technology-sustainability-education and to graduate the first engineers/architects of the new EHEA bachelors with sustainability as a generic competence. Specifically, in this paper authors explain their experience in leading the STEP program, and two examples are presented: Industrial Robotics subject and the curriculum for the School of Architecture.

Keywords: Sustainability, curricula improvement, robotics.

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Authors: Peter Odero Akuon

Abstract:

A rain cell ratio model is proposed that computes attenuation of the smallest rain cell which represents the maximum rain rate value i.e. the cell size when rainfall rate is exceeded 0.01% of the time, R_0.01 and predicts attenuation for other cells as the ratio with this maximum. This model incorporates the dependence of the path factor r on the ellipsoidal path variation of the Fresnel zone at different frequencies. In addition, the inhomogeneity of rainfall is modeled by a rain drop packing density factor. In order to derive the model, two empirical methods that can be used to find rain cell size distribution D_c are presented. Subsequently, attenuation measurements from different climatic zones for terrestrial radio links with frequencies F in the range 7-38 GHz are used to test the proposed model. Prediction results show that the path factor computed from the rain cell ratio technique has improved reliability when compared with other path factor and effective rain rate models, including the current ITU-R 530-15 model of 2013.

Keywords: Packing density of rain drops, prediction model, rain attenuation, rain cell ratio technique.

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Authors: Israt Jahan Eshita

Abstract:

Flows developed between two parallel disks have many engineering applications. Two types of non-swirling flows can be generated in such a domain. One is purely source flow in disc type domain (outward flow). Other is purely sink flow in disc type domain (inward flow). This situation often appears in some turbo machinery components such as air bearings, heat exchanger, radial diffuser, vortex gyroscope, disc valves, and viscosity meters. The main goal of this paper is to show the mesh convergence, because mesh convergence saves time, and economical to run and increase the efficiency of modeling for both sink and source flow. Then flow field is resolved using a very fine mesh near-wall, using enhanced wall treatment. After that we are going to compare this flow using standard k-epsilon, RNG k-epsilon turbulence models. Lastly compare some experimental data with numerical solution for sink flow. The good agreement of numerical solution with the experimental works validates the current modeling.

Keywords: Hydraulic diameter, k-epsilon model, meshes convergence, Reynolds number, RNG model, sink flow, source flow and wall y+.

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Authors: Nada Azhar

Abstract:

As a developing country, The Kingdom of Saudi Arabia (KSA) needs to make the best possible use of its workforce for social and economic reasons. The workforce is diverse, calling for appropriate diversity management (DM). The thesis focuses on the banking sector in KSA. To date, there have been no studies on DM in the banking sector in this country. Many organizations have introduced specific policies and programmes to improve the recruitment, inclusion, promotion, and retention of diverse employees, in addition to the legal requirements existing in many countries. However, Western-centric models of DM may not be applicable, at least not in their entirety, in other regions.

The aim of the study is to devise a framework for understanding gender, age and disability DM in the banking sector in KSA in order to enhance DM in this sector. A sample of 24 managers, 2 from each of the 12 banks, was interviewed to obtain their views on DM in the banking sector in KSA. Thematic analysis was used to analyze the data. These themes were used to develop the questionnaire, which was administered to 10 managers in each of the 12 banks. After analysis of these data, and completion of the study, the research will make a theoretical contribution to the knowledge on DM and a practical contribution to the management of diversity in Saudi banks. This paper concerns a work in progress.

Keywords: Age, disability, diversity, gender, Kingdom of Saudi Arabia.

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Authors: U. Amin, A. Talib, S. A. Qureshi, M. J. Hossain, G. Ahmad

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The choice evaluation between oil-immersed and dry-type transformers is often controlled by cost, location, and application. This paper compares the electrical performance of liquid- filled and dry-type transformers, which will assist the customer to choose the right and efficient ones for particular applications. An accurate assessment of the time-average flux density, electric field intensity and voltage distribution in an oil-insulated and a dry-type transformer have been computed and investigated. The detailed transformer modeling and analysis has been carried out to determine electrical parameter distributions. The models of oil-immersed and dry-type transformers are developed and solved by using the finite element method (FEM) to compare the electrical parameters. The effects of non-uniform and non-coherent voltage gradient, flux density and electric field distribution on the power losses and insulation properties of transformers are studied in detail. The results show that, for the same voltage and kilo-volt-ampere (kVA) rating, oil-immersed transformers have better insulation properties and less hysteresis losses than the dry-type.

Keywords: Finite element method, flux density, transformer, voltage gradient.

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Authors: A. Maddi, A. Guessoum, D. Berkani

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The purpose of this paper is to provide a practical example to the Linear Quadratic Gaussian (LQG) controller. This method includes a description and some discussion of the discrete Kalman state estimator. One aspect of this optimality is that the estimator incorporates all information that can be provided to it. It processes all available measurements, regardless of their precision, to estimate the current value of the variables of interest, with use of knowledge of the system and measurement device dynamics, the statistical description of the system noises, measurement errors, and uncertainty in the dynamics models. Since the time of its introduction, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation. For example, to determine the velocity of an aircraft or sideslip angle, one could use a Doppler radar, the velocity indications of an inertial navigation system, or the relative wind information in the air data system. Rather than ignore any of these outputs, a Kalman filter could be built to combine all of this data and knowledge of the various systems- dynamics to generate an overall best estimate of velocity and sideslip angle.

Keywords: Aircraft motion, Kalman filter, LQG control, Lateral stability, State estimator.

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Authors: N. Guru Prasath, Sangjin Ma, Chang-Wan Kim

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A butterfly valve is a quarter turn valve which is used to control the flow of a fluid through a section of pipe. Generally, butterfly valve is used in wide range of applications such as water distribution, sewage, oil and gas plants. In particular, butterfly valve with larger diameter finds its immense applications in hydro power plants to control the fluid flow. In-lieu with the constraints in cost and size to run laboratory setup, analysis of large diameter values will be mostly studied by computational method which is the best and inexpensive solution. For fluid and structural analysis, CFD and FEM software is used to perform large scale valve analyses, respectively. In order to perform above analysis in butterfly valve, the CAD model has to recreate and perform mesh in conventional software’s for various dimensions of valve. Therefore, its limitation is time consuming process. In-order to overcome that issue, python code was created to outcome complete pre-processing setup automatically in Salome software. Applying dimensions of the model clearly in the python code makes the running time comparatively lower and easier way to perform analysis of the valve. Hence, in this paper, an attempt was made to study the fluid-structure interaction (FSI) of butterfly valves by varying the valve angles and dimensions using python code in pre-processing software, and results are produced.

Keywords: Butterfly valve, fluid-structure interaction, automatic CFD analysis, flow coefficient.

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Authors: Thanh-Duoc Phan, Saden H. Zahiri, S. H. Masood, Mahnaz Jahedi

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In this article, using finite element analysis (FEA) and an X-ray diffractometer (XRD), cold-sprayed titanium particles on a steel substrate is investigated in term of cooling time and the development of residual strains. Three cooling-down models of sprayed particles after deposition stage are simulated and discussed: the first model (m1) considers conduction effect to the substrate only, the second model (m2) considers both conduction as well as convection effect to the environment, and the third model (m3) which is the same as the second model but with the substrate heated to a near particle temperature before spraying. Thereafter, residual strains developed in the third model is compared with the experimental measurement of residual strains, which involved a Bruker D8 Advance Diffractometer using CuKa radiation (40kV, 40mA) monochromatised with a graphite sample monochromator. For deposition conditions of this study, a good correlation was found to exist between the FEA results and XRD measurements of residual strains.

Keywords: cold gas dynamic spray, X-ray diffraction, explicit finite element analysis, residual strain, titanium, particle impact, deformation behavior.

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Authors: Ronal Muresano, Andrea Pagano

Abstract:

Nowadays, the mathematical/statistical applications are developed with more complexity and accuracy. However, these precisions and complexities have brought as result that applications need more computational power in order to be executed faster. In this sense, the multicore environments are playing an important role to improve and to optimize the execution time of these applications. These environments allow us the inclusion of more parallelism inside the node. However, to take advantage of this parallelism is not an easy task, because we have to deal with some problems such as: cores communications, data locality, memory sizes (cache and RAM), synchronizations, data dependencies on the model, etc. These issues are becoming more important when we wish to improve the application’s performance and scalability. Hence, this paper describes an optimization method developed for Systemic Model of Banking Originated Losses (SYMBOL) tool developed by the European Commission, which is based on analyzing the application's weakness in order to exploit the advantages of the multicore. All these improvements are done in an automatic and transparent manner with the aim of improving the performance metrics of our tool. Finally, experimental evaluations show the effectiveness of our new optimized version, in which we have achieved a considerable improvement on the execution time. The time has been reduced around 96% for the best case tested, between the original serial version and the automatic parallel version.

Keywords: Algorithm optimization, Bank Failures, OpenMP, Parallel Techniques, Statistical tool.

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Authors: Josua K. Junias, Fillemon N. Nangolo, Petrina T. Johaness

Abstract:

The deterioration of pavement can lead to the formation of potholes, which cause the wheels of a vehicle to experience unusual and uneven movement. In addition, improper loading practices of heavy vehicles can result in dynamic loading of the pavement due to the vehicle's response to the irregular movement caused by the potholes. The combined effects of asymmetrical vehicle loading and uneven road surfaces has an effect on pavement dynamic loading. This study aimed to model the pavement's dynamic response to heavy vehicles under different loading configurations and wheel movements. A sample of 225 cases with symmetrical and asymmetrical loading and kinematic movements was used, and 27 validated 3D pavement-vehicle interactive models were developed using SIMWISE 4D. The study found that the type of kinematic movement experienced by the heavy vehicle affects the pavement's dynamic loading, with eccentrically loaded, asymmetrically kinematic heavy vehicles having a statistically significant impact. The study also suggests that the mass of the vehicle's suspension system plays a role in the pavement's dynamic loading.

Keywords: Eccentricities, pavement dynamic loading, vertical displacement dynamic response, heavy vehicles.

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Authors: Walter Hussak, John Keane

Abstract:

The usual correctness condition for a schedule of concurrent database transactions is some form of serializability of the transactions. For general forms, the problem of deciding whether a schedule is serializable is NP-complete. In those cases other approaches to proving correctness, using proof rules that allow the steps of the proof of serializability to be guided manually, are desirable. Such an approach is possible in the case of conflict serializability which is proved algebraically by deriving serial schedules using commutativity of non-conflicting operations. However, conflict serializability can be an unnecessarily strong form of serializability restricting concurrency and thereby reducing performance. In practice, weaker, more general, forms of serializability for extended models of transactions are used. Currently, there are no known methods using proof rules for proving those general forms of serializability. In this paper, we define serializability for an extended model of partitioned transactions, which we show to be as expressive as serializability for general partitioned transactions. An algebraic method for proving general serializability is obtained by giving an initial-algebra specification of serializable schedules of concurrent transactions in the model. This demonstrates that it is possible to conduct algebraic proofs of correctness of concurrent transactions in general cases.

Keywords: Algebraic Specification, Partitioned Transactions, Serializability.

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