Search results for: degree of accuracy

Authors: A. Shebani, S. Iwnicki

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Understanding the nature of wheel and rail wear in the railway field is of fundamental importance to the safe and cost effective operation of the railways. Twin disc wear testing is used extensively for studying wear of wheel and rail materials. The University of Huddersfield twin disc rig was used in this paper to examine the effect of surface conditions on wheel and rail wear measurement under a range of wheel/rail contact conditions, with and without contaminants. This work focuses on an investigation of the effect of dry, wet, and lubricated conditions and the effect of contaminants such as sand on wheel and rail wear. The wheel and rail wear measurements were carried out by using a replica material and an optical profilometer that allows measurement of wear in difficult location with high accuracy. The results have demonstrated the rate at which both water and oil reduce wheel and rail wear. Scratches and other damage were seen on the wheel and rail surfaces after the addition of sand and consequently both wheel and rail wear damage rates increased under these conditions. This work introduced the replica material and an optical instrument as effective tools to study the effect of surface conditions on wheel and rail wear.

Keywords: Railway wheel/rail wear, surface conditions, twin disc test rig, replica material, Alicona profilometer.

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Authors: Anis S. Shuib, Peter R. Hoskins, William J. Easson

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Cardiovascular diseases, principally atherosclerosis, are responsible for 30% of world deaths. Atherosclerosis is due to the formation of plaque. The fatty plaque may be at risk of rupture, leading typically to stroke and heart attack. The plaque is usually associated with a high degree of lumen reduction, called a stenosis.It is increasingly recognized that the initiation and progression of disease and the occurrence of clinical events is a complex interplay between the local biomechanical environment and the local vascular biology. The aim of this study is to investigate the flow behavior through a stenosed artery. A physical experiment was performed using an artery model and blood analogue fluid. An axisymmetric model constructed consists of contraction and expansion region that follow a mathematical form of cosine function. A 30% diameter reduction was used in this study. The flow field was measured using particle image velocimetry (PIV). Spherical particles with 20μm diameter were seeded in a water-glycerol-NaCl mixture. Steady flow Reynolds numbers are 250. The area of interest is the region after the stenosis where the flow separation occurs. The velocity field was measured and the velocity gradient was investigated. There was high particle concentration in the recirculation zone. High velocity gradient formed immediately after the stenosis throat created a lift force that enhanced particle migration to the flow separation area.

Keywords: Stenosis artery, Biofluid mechanics, PIV

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Authors: T. Rashid, T. Kechadi

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This paper is a continuation of our daily energy peak load forecasting approach using our modified network which is part of the recurrent networks family and is called feed forward and feed back multi context artificial neural network (FFFB-MCANN). The inputs to the network were exogenous variables such as the previous and current change in the weather components, the previous and current status of the day and endogenous variables such as the past change in the loads. Endogenous variable such as the current change in the loads were used on the network output. Experiment shows that using endogenous and exogenous variables as inputs to the FFFBMCANN rather than either exogenous or endogenous variables as inputs to the same network produces better results. Experiments show that using the change in variables such as weather components and the change in the past load as inputs to the FFFB-MCANN rather than the absolute values for the weather components and past load as inputs to the same network has a dramatic impact and produce better accuracy.

Keywords: Daily peak load forecasting, feed forward and feedback multi-context neural network.

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of this work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. With our research and based on a feature selection in different phases, we are trying to design a neural network system with an optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each region of interest (ROI), 6 distinct sets of texture features are extracted such as: first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. When analyzing more phases, we show that the injection of liquid cause changes to the high relevant features in each region. Our results demonstrate that for detecting HCC tumor phase 3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between pathology and healthy classes, according to our method, relates to first order histogram parameters with accuracy of 85% in phase 1, 95% in phase 2, and 95% in phase 3.

Keywords: Feature selection, Multi-phasic liver images, Neural network, Texture analysis.

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Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar

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The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.

Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.

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Authors: Azli Abd. Razak, Yusli Yaakob, Mohd Nazir Ramli

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This study comprehensively simulate the use of k-ε model for predicting flow and heat transfer with measured flow field data in a stationary duct with elucidates on the detailed physics encountered in the fully developed flow region, and the sharp 180° bend region. Among the major flow features predicted with accuracy are flow transition at the entrance of the duct, the distribution of mean and turbulent quantities in the developing, fully developed, and sharp 180° bend, the development of secondary flows in the duct cross-section and the sharp 180° bend, and heat transfer augmentation. Turbulence intensities in the sharp 180° bend are found to reach high values and local heat transfer comparisons show that the heat transfer augmentation shifts towards the wall and along the duct. Therefore, understanding of the unsteady heat transfer in sharp 180° bends is important. The design and simulation are related to concept of fluid mechanics, heat transfer and thermodynamics. Simulation study has been conducted on the response of turbulent flow in a rectangular duct in order to evaluate the heat transfer rate along the small scale multiple rectangular duct

Keywords: Heat transfer, turbulence, rectangular duct, simulation.

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Authors: Gyumin Hwang, Jihong Lee

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This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.

Keywords: Chirp Spread Spectrum (CSS), Indoor Localization, Pattern-Matching, Time of Arrival (ToA), Multi-Path, Mahalanobis Distance, Reception Rate, Simultaneous Localization and Mapping (SLAM), Laser Range Finder (LRF).

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Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi

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This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.

Keywords: Land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle.

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Authors: Ramaswamy Palaniappan

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In this paper, several improvements are proposed to previous work of automated classification of alcoholics and nonalcoholics. In the previous paper, multiplayer-perceptron neural network classifying energy of gamma band Visual Evoked Potential (VEP) signals gave the best classification performance using 800 VEP signals from 10 alcoholics and 10 non-alcoholics. Here, the dataset is extended to include 3560 VEP signals from 102 subjects: 62 alcoholics and 40 non-alcoholics. Three modifications are introduced to improve the classification performance: i) increasing the gamma band spectral range by increasing the pass-band width of the used filter ii) the use of Multiple Signal Classification algorithm to obtain the power of the dominant frequency in gamma band VEP signals as features and iii) the use of the simple but effective knearest neighbour classifier. To validate that these two modifications do give improved performance, a 10-fold cross validation classification (CVC) scheme is used. Repeat experiments of the previously used methodology for the extended dataset are performed here and improvement from 94.49% to 98.71% in maximum averaged CVC accuracy is obtained using the modifications. This latest results show that VEP based classification of alcoholics is worth exploring further for system development.

Keywords: Alcoholic, Multilayer-perceptron, Nearest neighbour, Gamma band, MUSIC, Visual evoked potential.

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Authors: R. Bremananth

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Acoustic Imaging based sound localization using microphone array is a challenging task in digital-signal processing. Discrete Fourier transform (DFT) based near-field acoustical holography (NAH) is an important acoustical technique for sound source localization and provide an efficient solution to the ill-posed problem. However, in practice, due to the usage of small curtailed aperture and its consequence of significant spectral leakage, the DFT could not reconstruct the active-region-of-sound (AROS) effectively, especially near the edges of aperture. In this paper, we emphasize the fundamental problems of DFT-based NAH, provide a solution to spectral leakage effect by the extrapolation based on linear predictive coding and 2D Tukey windowing. This approach has been tested to localize the single and multi-point sound sources. We observe that incorporating extrapolation technique increases the spatial resolution, localization accuracy and reduces spectral leakage when small curtail aperture with a lower number of sensors accounts.

Keywords: Acoustic Imaging, Discrete Fourier Transform (DFT), k-space wavenumber, Near-Field Acoustical Holography (NAH), Source Localization, Spectral Leakage.

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Authors: Arkady Bolotin

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Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.

Keywords: Categorization, Uncertain medical categories, Binomial regression model, Fuzzy dependent variable, Robustness.

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Authors: M. Michael Gromiha, A. Mary Thangakani, Sandeep Kumar, D. Velmurugan

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The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson and spongiform encephalopathies is formation of amyloid fibrils and plaques in proteins. We have analyzed different sets of proteins and peptides to understand the influence of sequence based features on protein aggregation process. The comparison of 373 pairs of homologous mesophilic and thermophilic proteins showed that aggregation prone regions (APRs) are present in both. But, the thermophilic protein monomers show greater ability to ‘stow away’ the APRs in their hydrophobic cores and protect them from solvent exposure. The comparison of amyloid forming and amorphous b-aggregating hexapeptides suggested distinct preferences for specific residues at the six positions as well as all possible combinations of nine residue pairs. The compositions of residues at different positions and residue pairs have been converted into energy potentials and utilized for distinguishing between amyloid forming and amorphous b-aggregating peptides. Our method could correctly identify the amyloid forming peptides at an accuracy of 95-100% in different datasets of peptides.

Keywords: Aggregation prone regions, amyloids, thermophilic proteins, amino acid residues, machine learning.

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Authors: K. Shiba, T. Kaburagi, Y. Kurihara

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With global aging, people who require care, such as people with dementia (PwD), are increasing within many developed countries. And PwDs may wander and unconsciously set foot outdoors, it may lead serious accidents, such as, traffic accidents. Here, round-the-clock monitoring by caregivers is necessary, which can be a burden for the caregivers. Therefore, an automatic wandering detection system is required when an elderly person wanders outdoors, in which case the detection system transmits a ‘moving’ followed by an ‘absence’ state. In this paper, we focus on the transition from the ‘resting’ to the ‘absence’ state, via the ‘moving’ state as one of the wandering transitions. To capture the transition of the three states, our method based on the hidden Markov model (HMM) is built. Using our method, the restraint where the ‘resting’ state and ‘absence’ state cannot be transmitted to each other is applied. To validate our method, we conducted the experiment with 10 subjects. Our results show that the method can classify three states with 0.92 accuracy.

Keywords: Wander, microwave Doppler sensor, respiratory frequency band, the state transition, hidden Markov model.

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

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Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: Pollen recognition, logistic model tree, expectation-maximization, local binary pattern.

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Authors: K. Akilandeswari, G. M. Nasira

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Brain-Computer Interfaces (BCIs) measure brain signals activity, intentionally and unintentionally induced by users, and provides a communication channel without depending on the brain’s normal peripheral nerves and muscles output pathway. Feature Selection (FS) is a global optimization machine learning problem that reduces features, removes irrelevant and noisy data resulting in acceptable recognition accuracy. It is a vital step affecting pattern recognition system performance. This study presents a new Binary Particle Swarm Optimization (BPSO) based feature selection algorithm. Multi-layer Perceptron Neural Network (MLPNN) classifier with backpropagation training algorithm and Levenberg-Marquardt training algorithm classify selected features.

Keywords: Brain-Computer Interfaces (BCI), Feature Selection (FS), Walsh–Hadamard Transform (WHT), Binary Particle Swarm Optimization (BPSO), Multi-Layer Perceptron (MLP), Levenberg–Marquardt algorithm.

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Authors: André C. Silva, Débora N. Sousa, Elenice M. S. Silva, Thales P. Fontes, Raphael S. Tomaz

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Starches are widely used as depressant in froth flotation operations in Brazil due to their efficiency, increasing the selectivity in the inverse flotation of quartz depressing iron ore. Starches market have been growing and improving in recent years, leading to better products attending the requirements of the mineral industry. The major source of starch used for iron ore is corn starch, which needs to be gelatinized with sodium hydroxide (NaOH) prior to use. This stage has a direct impact on industrials costs, once the lowest consumption of NaOH in gelatinization provides better control of the pH in the froth flotation and reduces the amount of electrolytes present in the pulp. In order to evaluate the gelatinization degree of different starches and flour were subjected to the addiction of NaOH and temperature variation experiments. Samples of starch (corn, cassava, HIPIX 100, HIPIX 101 and HIPIX 102 commercialized by Ingredion) and flour (cassava and potato) were tested. The starch samples were characterized through Scanning Electronic Microscopy and the amylose content were determined through spectrometry, swelling and solubility tests. The gelatinization was carried out through titration with NaOH, keeping the solution temperature constant at 40 ^oC. At the end of the tests, the optimal amount of NaOH consumed to gelatinize the starch or flour from different botanical sources was established and a correlation between the content of amylopectin in the starch and the starch/NaOH ratio needed for its gelatinization.

Keywords: Froth flotation, gelatinization, sodium hydroxide, starches and flours.

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Authors: C. lo Storto

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This paper presents an approach based on the adoption of a distributed cognition framework and a non parametric multicriteria evaluation methodology (DEA) designed specifically to compare e-commerce websites from the consumer/user viewpoint. In particular, the framework considers a website relative efficiency as a measure of its quality and usability. A website is modelled as a black box capable to provide the consumer/user with a set of functionalities. When the consumer/user interacts with the website to perform a task, he/she is involved in a cognitive activity, sustaining a cognitive cost to search, interpret and process information, and experiencing a sense of satisfaction. The degree of ambiguity and uncertainty he/she perceives and the needed search time determine the effort size – and, henceforth, the cognitive cost amount – he/she has to sustain to perform his/her task. On the contrary, task performing and result achievement induce a sense of gratification, satisfaction and usefulness. In total, 9 variables are measured, classified in a set of 3 website macro-dimensions (user experience, site navigability and structure). The framework is implemented to compare 40 websites of businesses performing electronic commerce in the information technology market. A questionnaire to collect subjective judgements for the websites in the sample was purposely designed and administered to 85 university students enrolled in computer science and information systems engineering undergraduate courses.

Keywords: Website, e-commerce, DEA, distributed cognition, evaluation, comparison.

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Authors: Amon Tunwannarux, Supanunt Tunwannarux

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This paper describes the design concepts and implementation of a 5-Joint mechanical arm for a rescue robot named CEO Mission II. The multi-joint arm is a five degree of freedom mechanical arm with a four bar linkage, which can be stretched to 125 cm. long. It is controlled by a teleoperator via the user-friendly control and monitoring GUI program. With Inverse Kinematics principle, we developed the method to control the servo angles of all arm joints to get the desired tip position. By clicking the determined tip position or dragging the tip of the mechanical arm on the computer screen to the desired target point, the robot will compute and move its multi-joint arm to the pose as seen on the GUI screen. The angles of each joint are calculated and sent to all joint servos simultaneously in order to move the mechanical arm to the desired pose at once. The operator can also use a joystick to control the movement of this mechanical arm and the locomotion of the robot. Many sensors are installed at the tip of this mechanical arm for surveillance from the high level and getting the vital signs of victims easier and faster in the urban search and rescue tasks. It works very effectively and easy to control. This mechanical arm and its software were developed as a part of the CEO Mission II Rescue Robot that won the First Runner Up award and the Best Technique award from the Thailand Rescue Robot Championship 2006. It is a low cost, simple, but functioning 5-Jiont mechanical arm which is built from scratch, and controlled via wireless LAN 802.11b/g. This 5-Jiont mechanical arm hardware concept and its software can also be used as the basic mechatronics to many real applications.

Keywords: Multi-joint, mechanical arm, inverse kinematics, rescue robot, GUI control program.

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Authors: Jinho Kim, Dongik Shin, Deokwon Yun, Changsoo Han

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Rotating stages in semiconductor, display industry and many other fields require challenging accuracy to perform their functions properly. Especially, Axis of rotation error on rotary system is significant; such as the spindle error motion of the aligner, wire bonder and inspector machine which result in the poor state of manufactured goods. To evaluate and improve the performance of such precision rotary stage, unessential movements on the other 5 degrees of freedom of the rotary stage must be measured and analyzed. In this paper, we have measured the three translations and two tilt motions of a rotating stage with high precision capacitive sensors. To obtain the radial error motion from T.I.R (Total Indicated Reading) of radial direction, we have used Donaldson's reversal technique. And the axial components of the spindle tilt error motion can be obtained accurately from the axial direction outputs of sensors by Estler face motion reversal technique. Further more we have defined and measured the sensitivity of positioning error to the five error motions.

Keywords: Donaldson's reversal methods, Estler face motionreversal method, Error motion, sensitivity, T.I.R (Total IndicatedReading).

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Authors: Anis S. Shuib, Peter R. Hoskins, William J. Easson

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Cardiovascular disease mostly in the form of atherosclerosis is responsible for 30% of all world deaths amounting to 17 million people per year. Atherosclerosis is due to the formation of plaque. The fatty plaque may be at risk of rupture, leading typically to stroke and heart attack. The plaque is usually associated with a high degree of lumen reduction, called a stenosis. The initiation and progression of the disease is strongly linked to the hemodynamic environment near the vessel wall. The aim of this study is to validate the flow of blood mimic through an arterial stenosis model with computational fluid dynamics (CFD) package. In experiment, an axisymmetric model constructed consists of contraction and expansion region that follow a mathematical form of cosine function. A 30% diameter reduction was used in this study. Particle image velocimetry (PIV) was used to characterize the flow. The fluid consists of rigid spherical particles suspended in waterglycerol- NaCl mixture. The particles with 20 μm diameter were selected to follow the flow of fluid. The flow at Re=155, 270 and 390 were investigated. The experimental result is compared with FLUENT simulated flow that account for viscous laminar flow model. The results suggest that laminar flow model was sufficient to predict flow velocity at the inlet but the velocity at stenosis throat at Re =390 was overestimated. Hence, a transition to turbulent regime might have been developed at throat region as the flow rate increases.

Keywords: Atherosclerosis, Particle-laden flow, Particle imagevelocimetry, Stenosis artery

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Authors: Kalyan Deepak Kolla, Ketan Paua, Rajkumar Bhagate

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Transmission dynamics occupy major role in customer perception of the product in both senses of touch and quality of sound. The quantity and quality of sound perceived is more concerned with the whine noise of the gears engaged. Whine noise is tonal in nature and tonal noises cause fatigue and irritation to customers, which in turn affect the quality of the product. Transmission error is the usual suspect for whine noise, which can be caused due to misalignments, tolerances, manufacturing variabilities. In-cabin noise is also more sensitive to the gear design. As the details of the gear tooth design and manufacturing are in microns, anything out of the tolerance zone, either in design or manufacturing, will cause a whine noise. This will also cause high variation in stress and deformation due to change in the load and leads to the fatigue failure of the gears. Hence gear design and development take priority in the transmission development process. This paper aims to study such variability by considering five pairs of helical spur gears and their effect on the transmission error, contact pattern and vibration level on the transmission.

Keywords: Gears, whine noise, manufacturing variability, mount vibration variability.

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Authors: K. G. Firouzjah, A. Sheikholeslami

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The perfect operation of common Active Filters is depended on accuracy of identification system distortion. Also, using a suitable method in current injection and reactive power compensation, leads to increased filter performance. Due to this fact, this paper presents a method based on predictive current control theory in shunt active filter applications. The harmonics of the load current is identified by using o–d–q reference frame on load current and eliminating the DC part of d–q components. Then, the rest of these components deliver to predictive current controller as a Threephase reference current by using Park inverse transformation. System is modeled in discreet time domain. The proposed method has been tested using MATLAB model for a nonlinear load (with Total Harmonic Distortion=20%). The simulation results indicate that the proposed filter leads to flowing a sinusoidal current (THD=0.15%) through the source. In addition, the results show that the filter tracks the reference current accurately.

Keywords: Active filter, predictive current control, low pass filter, harmonic omitting, o–d–q reference frame.

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Authors: NattapongTecharattanased

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The purpose of this research was to study the factors that influenced the success of mobile phone entrepreneurs at Central Plaza. The sample group included 187 entrepreneurs at Central Plaza. A questionnaire was utilized as a tool to collect data. Statistics used in this research included frequency, percentage, mean, and standard deviation. Independent- sample t- test, one way ANOVA, and multiple regression analysis. Data were analyzed by using Statistical Package for the Social Sciences.The findings disclosed that the majority of respondents were male between 25-40 years old, and held an undergraduate degree. The average income of respondents was between 15,001-25,000 baht. The majority of respondents had less than 5 years of working experience. In terms of personality, the findings revealed that expression and agreement were ranked at the highest level. Whereas, emotion stability, consciousness, open to new experience were ranked at high. From the hypotheses testing, the findings revealed that different genders had different success in their mobile phone business with different income from the last 6 months. However, difference in age, income, level of education, and experience affected the success in terms of income, number of customers, and overall success of business. Moreover, the factors of personalities included expression, agreement, emotion stability, consciousness, open to new experience, and competitive strategy. From the findings, these factors were able to predict mobile phone business success at 66.9 percent.

Keywords: Entrepreneur, Influencing Factors, Success, Mobile Phone Business.

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Authors: Si Mon Kueh, Tom J. Kazmierski

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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks, bit-serial neural processor, FPGA, Neural Processing Element.

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Authors: Muhammad Javed, Yalemisew M. Abgaz, Claus Pahl

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Ontology-based modelling of multi-formatted software application content is a challenging area in content management. When the number of software content unit is huge and in continuous process of change, content change management is important. The management of content in this context requires targeted access and manipulation methods. We present a novel approach to deal with model-driven content-centric information systems and access to their content. At the core of our approach is an ontology-based semantic annotation technique for diversely formatted content that can improve the accuracy of access and systems evolution. Domain ontologies represent domain-specific concepts and conform to metamodels. Different ontologies - from application domain ontologies to software ontologies - capture and model the different properties and perspectives on a software content unit. Interdependencies between domain ontologies, the artifacts and the content are captured through a trace model. The annotation traces are formalised and a graph-based system is selected for the representation of the annotation traces.

Keywords: Consistent Content Management, Impact Categorisation, Trace Model, Ontology Evolution

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Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

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Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: Color overlapping windows, image stitching, leukocyte detection.

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Authors: Wang Zhan-Xi, Zhang Yi-Ming, Chen Hang, Wang Gang

Abstract:

Manual polishing has problems such as high labor intensity, low production efficiency and difficulty in guaranteeing the consistency of polishing quality. The use of robot polishing instead of manual polishing can effectively avoid these problems. Polishing force directly affects the quality of polishing, so accurate tracking and control of polishing force is one of the most important conditions for improving the accuracy of robot polishing. The traditional force control strategy is difficult to adapt to the strong coupling of force control and position control during the robot polishing process. Therefore, based on the analysis of force-based impedance control and position-based impedance control, this paper proposed a type of adaptive controller. Based on force feedback control of active compliance control, the controller can adaptively estimate the stiffness and position of the external environment and eliminate the steady-state force error produced by traditional impedance control. The simulation results of the model show that the adaptive controller has good adaptability to changing environmental positions and environmental stiffness, and can accurately track and control polishing force.

Keywords: robot polishing, force feedback, impedance control, adaptive control

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Authors: N. Shafiq, M. F. Nuruddin, S. C. Chin

Abstract:

This paper presents the experimental results of the investigation of various properties related to the durability and longterm performance of mortars made of Fly Ash blended cement, FA and Ordinary Portland cement, OPC. The properties that were investigated in an experimental program include; equilibration of specimen in different relative humidity, determination of total porosity, compressive strength, chloride permeability index, and electrical resistivity. Fly Ash blended cement mortar specimens exhibited 10% to 15% lower porosity when measured at equilibrium conditions in different relative humidities as compared to the specimens made of OPC mortar, which resulted in 6% to 8% higher compressive strength of FA blended cement mortar specimens. The effects of ambient relative humidity during sample equilibration on porosity and strength development were also studied. For specimens equilibrated in higher relative humidity conditions, such as 75%, the total porosity of different mortar specimens was between 35% to 50% less than the porosity of samples equilibrated in 12% relative humidity, consequently leading to higher compressive strengths of these specimens.A valid statistical correlation between values of compressive strength, porosity and the degree of saturation was obtained. Measured values of chloride permeability index of fly ash blended cement mortar were obtained as one fourth to one sixth of those measured for OPC mortar specimens, which indicates high resistance against chloride ion penetration in FA blended cement specimens, hence resulting in a highly durable mortar.

Keywords: chloride permeability index, equilibrium condition, electrical resistivity, fly ash

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Authors: Azeemsha Thacham Poyil, Nasimudeen KM

Abstract:

This research paper presents some methods to assess the performance of Wigner Ville Distribution for Time-Frequency representation of non-stationary signals, in comparison with the other representations like STFT, Spectrogram etc. The simultaneous timefrequency resolution of WVD is one of the important properties which makes it preferable for analysis and detection of linear FM and transient signals. There are two algorithms proposed here to assess the resolution and to compare the performance of signal detection. First method is based on the measurement of area under timefrequency plot; in case of a linear FM signal analysis. A second method is based on the instantaneous power calculation and is used in case of transient, non-stationary signals. The implementation is explained briefly for both methods with suitable diagrams. The accuracy of the measurements is validated to show the better performance of WVD representation in comparison with STFT and Spectrograms.

Keywords: WVD: Wigner Ville Distribution, STFT: Short Time Fourier Transform, FT: Fourier Transform, TFR: Time-Frequency Representation, FM: Frequency Modulation, LFM Signal: Linear FM Signal, JTFA: Joint time frequency analysis.

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Authors: Saman Ghaffarian, Ilgın Gökasar

Abstract:

This paper presents a new automatic vehicle detection method from very high resolution aerial images to measure traffic density. The proposed method starts by extracting road regions from image using road vector data. Then, the road image is divided into equal sections considering resolution of the images. Gradient vectors of the road image are computed from edge map of the corresponding image. Gradient vectors on the each boundary of the sections are divided where the gradient vectors significantly change their directions. Finally, number of vehicles in each section is carried out by calculating the standard deviation of the gradient vectors in each group and accepting the group as vehicle that has standard deviation above predefined threshold value. The proposed method was tested in four very high resolution aerial images acquired from Istanbul, Turkey which illustrate roads and vehicles with diverse characteristics. The results show the reliability of the proposed method in detecting vehicles by producing 86% overall F1 accuracy value.

Keywords: Aerial images, intelligent transportation systems, traffic density measurement, vehicle detection.

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