Search results for: (ANFIS) Adaptive Neuro Fuzzy Inference System
8238 Human Action Recognition Using Variational Bayesian HMM with Dirichlet Process Mixture of Gaussian Wishart Emission Model
Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park
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In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.
Keywords: Human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, Prior distribution and approximate posterior distribution, KTH dataset.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10148237 Adaptive and Personalizing Learning Sequence Using Modified Roulette Wheel Selection Algorithm
Authors: Melvin A. Ballera
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Prior literature in the field of adaptive and personalized learning sequence in e-learning have proposed and implemented various mechanisms to improve the learning process such as individualization and personalization, but complex to implement due to expensive algorithmic programming and need of extensive and prior data. The main objective of personalizing learning sequence is to maximize learning by dynamically selecting the closest teaching operation in order to achieve the learning competency of learner. In this paper, a revolutionary technique has been proposed and tested to perform individualization and personalization using modified reversed roulette wheel selection algorithm that runs at O(n). The technique is simpler to implement and is algorithmically less expensive compared to other revolutionary algorithms since it collects the dynamic real time performance matrix such as examinations, reviews, and study to form the RWSA single numerical fitness value. Results show that the implemented system is capable of recommending new learning sequences that lessens time of study based on student's prior knowledge and real performance matrix.Keywords: E-learning, fitness value, personalized learning sequence, reversed roulette wheel selection algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20318236 A Complexity-Based Approach in Image Compression using Neural Networks
Authors: Hadi Veisi, Mansour Jamzad
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In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation are evaluated and compared. In training and evaluation, each image block is assigned to a network based on its complexity value. Best-SNR is another alternative in selecting compressor network for image blocks in evolution phase which chooses one of the trained networks such that results best SNR in compressing the input image block. In our evaluations, best results are obtained when overlapping the blocks is allowed and choosing the networks in compressor is based on the Best-SNR. In this case, the results demonstrate superiority of this method comparing with previous similar works and JPEG standard coding.Keywords: Adaptive image compression, Image complexity, Multi-layer perceptron neural network, JPEG Standard, PSNR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22318235 Development of a Speed Sensorless IM Drives
Authors: Dj. Cherifi, Y. Miloud, A. Tahri
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The primary objective of this paper is to elimination of the problem of sensitivity to parameter variation of induction motor drive. The proposed sensorless strategy is based on an algorithm permitting a better simultaneous estimation of the rotor speed and the stator resistance including an adaptive mechanism based on the lyaponov theory. To study the reliability and the robustness of the sensorless technique to abnormal operations, some simulation tests have been performed under several cases.
The proposed sensorless vector control scheme showed a good performance behavior in the transient and steady states, with an excellent disturbance rejection of the load torque.
Keywords: Induction Motor Drive, field-oriented control, adaptive speed observer, stator resistance estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20308234 The Estimation of Semi Elliptical Surface Cracks Advancement via Fuzzy Logic
Authors: Gürol Önal, Ahmet Avcı
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This paper presented the results of an experimental investigation into the axial fatigue behavior of a 5086 aluminum alloy which have several notch-aspect ratios a0/c0 and notch thickness ratio a/t with semi-elliptical surface cracks. Tests were conducted in la b air for stress levels of 50 % of their yield strength. Experiments were carried out for various notch to thickness ratios. Crack growth rates of test specimens both in surface and depth directions were determined by using die penetration method. Fuzzy Logic method was used to predict the deep direction crack growth because the dept of the crack is considerably difficult to measure.Keywords: Axial fatigue, Crack growth rate, surface crack, Al-Mg alloy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16908233 Cognitive SATP for Airborne Radar Based on Slow-Time Coding
Authors: Fanqiang Kong, Jindong Zhang, Daiyin Zhu
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Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, the notion of cognitive radar is extended to STAP technique, and cognitive STAP is discussed. The principle for improving signal-to-clutter ratio (SCNR) based on slow-time coding is given, and the corresponding optimization algorithm based on cyclic and power-like algorithms is presented. Numerical examples show the effectiveness of the proposed method.Keywords: Space-time adaptive processing (STAP), signal-to-clutter ratio, slow-time coding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8568232 Parking Space Detection and Trajectory Tracking Control for Vehicle Auto-Parking
Authors: Shiuh-Jer Huang, Yu-Sheng Hsu
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On-board available parking space detecting system, parking trajectory planning and tracking control mechanism are the key components of vehicle backward auto-parking system. Firstly, pair of ultrasonic sensors is installed on each side of vehicle body surface to detect the relative distance between ego-car and surrounding obstacle. The dimension of a found empty space can be calculated based on vehicle speed and the time history of ultrasonic sensor detecting information. This result can be used for constructing the 2D vehicle environmental map and available parking type judgment. Finally, the auto-parking controller executes the on-line optimal parking trajectory planning based on this 2D environmental map, and monitors the real-time vehicle parking trajectory tracking control. This low cost auto-parking system was tested on a model car.Keywords: Vehicle auto-parking, parking space detection, parking path tracking, intelligent fuzzy controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14708231 Satellite Beam Handoff Detection Algorithm Based On RCST Mobility Information
Authors: Ji Nyong Jang, Min Woo Lee, Eun Kyung Kim, Ki Keun Kim, Jae Sung Lim
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Since DVB-RCS has been successively implemented, the mobile communication on the multi-beam satellite communication is attractive attention. And the DVB-RCS standard sets up to support mobility of a RCST. In the case of the spot-beam satellite system, the received signal strength does not differ largely between the center and the boundary of the beam. Thus, the RSS based handoff detection algorithm is not benefit to the satellite system as a terrestrial system. Therefore we propose an Adaptive handoff detection algorithm based on RCST mobility information. Our handoff detection algorithm not only can be used as centralized handoff detection algorithm but also removes uncertainties of handoff due to the variation of RSS. Performances were compared with RSS based handoff algorithm. Simulation results show that the proposed handoff detection algorithm not only achieved better handoff and link degradation rate, but also achieved better forward link spectral efficiency.
Keywords: DVB-RCS, satellite multi-beam handoff, mobility information, handover.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17168230 Matching-Based Cercospora Leaf Spot Detection in Sugar Beet
Authors: Rong Zhou, Shun’ich Kaneko, Fumio Tanaka, Miyuki Kayamori, Motoshige Shimizu
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In this paper, we propose a robust disease detection method, called adaptive orientation code matching (Adaptive OCM), which is developed from a robust image registration algorithm: orientation code matching (OCM), to achieve continuous and site-specific detection of changes in plant disease. We use two-stage framework for realizing our research purpose; in the first stage, adaptive OCM was employed which could not only realize the continuous and site-specific observation of disease development, but also shows its excellent robustness for non-rigid plant object searching in scene illumination, translation, small rotation and occlusion changes and then in the second stage, a machine learning method of support vector machine (SVM) based on a feature of two dimensional (2D) xy-color histogram is further utilized for pixel-wise disease classification and quantification. The indoor experiment results demonstrate the feasibility and potential of our proposed algorithm, which could be implemented in real field situation for better observation of plant disease development.
Keywords: Cercospora Leaf Spot (CLS), Disease detection, Image processing, Orientation Code Matching (OCM), Support Vector Machine (SVM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22018229 Temporal Analysis of Magnetic Nerve Stimulation–Towards Enhanced Systems via Virtualisation
Authors: Stefan M. Goetz, Thomas Weyh, Hans-Georg Herzog
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The triumph of inductive neuro-stimulation since its rediscovery in the 1980s has been quite spectacular. In lots of branches ranging from clinical applications to basic research this system is absolutely indispensable. Nevertheless, the basic knowledge about the processes underlying the stimulation effect is still very rough and rarely refined in a quantitative way. This seems to be not only an inexcusable blank spot in biophysics and for stimulation prediction, but also a fundamental hindrance for technological progress. The already very sophisticated devices have reached a stage where further optimization requires better strategies than provided by simple linear membrane models of integrate-and-fire style. Addressing this problem for the first time, we suggest in the following text a way for virtual quantitative analysis of a stimulation system. Concomitantly, this ansatz seems to provide a route towards a better understanding by using nonlinear signal processing and taking the nerve as a filter that is adapted for neuronal magnetic stimulation. The model is compact and easy to adjust. The whole setup behaved very robustly during all performed tests. Exemplarily a recent innovative stimulator design known as cTMS is analyzed and dimensioned with this approach in the following. The results show hitherto unforeseen potentials.
Keywords: Theory of magnetic stimulation, inversion, optimization, high voltage oscillator, TMS, cTMS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13838228 Energy Recovery from Swell with a Height Inferior to 1.5 m
Authors: A. Errasti, F. Doffagne, O. Foucrier, S. Kao, A. Meigne, H. Pellae, T. Rouland
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Renewable energy recovery is an important domain of research in past few years in view of protection of our ecosystem. Several industrial companies are setting up widespread recovery systems to exploit wave energy. Most of them have a large size, are implanted near the shores and exploit current flows. However, as oceans represent 70% of Earth surface, a huge space is still unexploited to produce energy. Present analysis focuses on surface small scale wave energy recovery. The principle is exactly the opposite of wheel damper for a car on a road. Instead of maintaining the car body as non-oscillatory as possible by adapted control, a system is designed so that its oscillation amplitude under wave action will be maximized with respect to a boat carrying it in view of differential potential energy recuperation. From parametric analysis of system equations, interesting domains have been selected and expected energy output has been evaluated.
Keywords: Small scale wave, potential energy, optimized energy recovery, auto-adaptive system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11988227 Power System Security Constrained Economic Dispatch Using Real Coded Quantum Inspired Evolution Algorithm
Authors: A. K. Al-Othman, F. S. Al-Fares, K. M. EL-Nagger
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This paper presents a new optimization technique based on quantum computing principles to solve a security constrained power system economic dispatch problem (SCED). The proposed technique is a population-based algorithm, which uses some quantum computing elements in coding and evolving groups of potential solutions to reach the optimum following a partially directed random approach. The SCED problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Real Coded Quantum-Inspired Evolution Algorithm (RQIEA) is then applied to solve the constrained optimization formulation. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that RQIEA is very applicable for solving security constrained power system economic dispatch problem (SCED).Keywords: State Estimation, Fuzzy Linear Regression, FuzzyLinear State Estimator (FLSE) and Measurements Uncertainty.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17198226 Intelligent Vision System for Human-Robot Interface
Authors: Al-Amin Bhuiyan, Chang Hong Liu
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This paper addresses the development of an intelligent vision system for human-robot interaction. The two novel contributions of this paper are 1) Detection of human faces and 2) Localizing the eye. The method is based on visual attributes of human skin colors and geometrical analysis of face skeleton. This paper introduces a spatial domain filtering method named ?Fuzzily skewed filter' which incorporates Fuzzy rules for deciding the gray level of pixels in the image in their neighborhoods and takes advantages of both the median and averaging filters. The effectiveness of the method has been justified over implementing the eye tracking commands to an entertainment robot, named ''AIBO''.Keywords: Fuzzily skewed filter, human-robot interface, rmscontrast, skin color segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14428225 Automated Segmentation of ECG Signals using Piecewise Derivative Dynamic Time Warping
Authors: Ali Zifan, Mohammad Hassan Moradi, Sohrab Saberi, Farzad Towhidkhah
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Electrocardiogram (ECG) segmentation is necessary to help reduce the time consuming task of manually annotating ECG-s. Several algorithms have been developed to segment the ECG automatically. We first review several of such methods, and then present a new single lead segmentation method based on Adaptive piecewise constant approximation (APCA) and Piecewise derivative dynamic time warping (PDDTW). The results are tested on the QT database. We compared our results to Laguna-s two lead method. Our proposed approach has a comparable mean error, but yields a slightly higher standard deviation than Laguna-s method.Keywords: Adaptive Piecewise Constant Approximation, Dynamic programming, ECG segmentation, Piecewise DerivativeDynamic Time Warping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20748224 Design Neural Network Controller for Mechatronic System
Authors: Ismail Algelli Sassi Ehtiwesh, Mohamed Ali Elhaj
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The main goal of the study is to analyze all relevant properties of the electro hydraulic systems and based on that to make a proper choice of the neural network control strategy that may be used for the control of the mechatronic system. A combination of electronic and hydraulic systems is widely used since it combines the advantages of both. Hydraulic systems are widely spread because of their properties as accuracy, flexibility, high horsepower-to-weight ratio, fast starting, stopping and reversal with smoothness and precision, and simplicity of operations. On the other hand, the modern control of hydraulic systems is based on control of the circuit fed to the inductive solenoid that controls the position of the hydraulic valve. Since this circuit may be easily handled by PWM (Pulse Width Modulation) signal with a proper frequency, the combination of electrical and hydraulic systems became very fruitful and usable in specific areas as airplane and military industry. The study shows and discusses the experimental results obtained by the control strategy of neural network control using MATLAB and SIMULINK [1]. Finally, the special attention was paid to the possibility of neuro-controller design and its application to control of electro-hydraulic systems and to make comparative with other kinds of control.
Keywords: Neural-Network controller, Mechatronic, electrohydraulic
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21878223 Pectoral Muscles Suppression in Digital Mammograms Using Hybridization of Soft Computing Methods
Authors: I. Laurence Aroquiaraj, K. Thangavel
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Breast region segmentation is an essential prerequisite in computerized analysis of mammograms. It aims at separating the breast tissue from the background of the mammogram and it includes two independent segmentations. The first segments the background region which usually contains annotations, labels and frames from the whole breast region, while the second removes the pectoral muscle portion (present in Medio Lateral Oblique (MLO) views) from the rest of the breast tissue. In this paper we propose hybridization of Connected Component Labeling (CCL), Fuzzy, and Straight line methods. Our proposed methods worked good for separating pectoral region. After removal pectoral muscle from the mammogram, further processing is confined to the breast region alone. To demonstrate the validity of our segmentation algorithm, it is extensively tested using over 322 mammographic images from the Mammographic Image Analysis Society (MIAS) database. The segmentation results were evaluated using a Mean Absolute Error (MAE), Hausdroff Distance (HD), Probabilistic Rand Index (PRI), Local Consistency Error (LCE) and Tanimoto Coefficient (TC). The hybridization of fuzzy with straight line method is given more than 96% of the curve segmentations to be adequate or better. In addition a comparison with similar approaches from the state of the art has been given, obtaining slightly improved results. Experimental results demonstrate the effectiveness of the proposed approach.
Keywords: X-ray Mammography, CCL, Fuzzy, Straight line.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17628222 Automated ECG Segmentation Using Piecewise Derivative Dynamic Time Warping
Authors: Ali Zifan, Sohrab Saberi, Mohammad Hassan Moradi, Farzad Towhidkhah
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Electrocardiogram (ECG) segmentation is necessary to help reduce the time consuming task of manually annotating ECG's. Several algorithms have been developed to segment the ECG automatically. We first review several of such methods, and then present a new single lead segmentation method based on Adaptive piecewise constant approximation (APCA) and Piecewise derivative dynamic time warping (PDDTW). The results are tested on the QT database. We compared our results to Laguna's two lead method. Our proposed approach has a comparable mean error, but yields a slightly higher standard deviation than Laguna's method.
Keywords: Adaptive Piecewise Constant Approximation, Dynamic programming, ECG segmentation, Piecewise Derivative Dynamic Time Warping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24008221 GCM Based Fuzzy Clustering to Identify Homogeneous Climatic Regions of North-East India
Authors: Arup K. Sarma, Jayshree Hazarika
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The North-eastern part of India, which receives heavier rainfall than other parts of the subcontinent, is of great concern now-a-days with regard to climate change. High intensity rainfall for short duration and longer dry spell, occurring due to impact of climate change, affects river morphology too. In the present study, an attempt is made to delineate the North-eastern region of India into some homogeneous clusters based on the Fuzzy Clustering concept and to compare the resulting clusters obtained by using conventional methods and nonconventional methods of clustering. The concept of clustering is adapted in view of the fact that, impact of climate change can be studied in a homogeneous region without much variation, which can be helpful in studies related to water resources planning and management. 10 IMD (Indian Meteorological Department) stations, situated in various regions of the North-east, have been selected for making the clusters. The results of the Fuzzy C-Means (FCM) analysis show different clustering patterns for different conditions. From the analysis and comparison it can be concluded that nonconventional method of using GCM data is somehow giving better results than the others. However, further analysis can be done by taking daily data instead of monthly means to reduce the effect of standardization.
Keywords: Climate change, conventional and nonconventional methods of clustering, FCM analysis, homogeneous regions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22138220 Soft Computing based Retrieval System for Medical Applications
Authors: Pardeep Singh, Sanjay Sharma
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With increasing data in medical databases, medical data retrieval is growing in popularity. Some of this analysis including inducing propositional rules from databases using many soft techniques, and then using these rules in an expert system. Diagnostic rules and information on features are extracted from clinical databases on diseases of congenital anomaly. This paper explain the latest soft computing techniques and some of the adaptive techniques encompasses an extensive group of methods that have been applied in the medical domain and that are used for the discovery of data dependencies, importance of features, patterns in sample data, and feature space dimensionality reduction. These approaches pave the way for new and interesting avenues of research in medical imaging and represent an important challenge for researchers.Keywords: CBIR, GA, Rough sets, CBMIR, SVM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17398219 Animal-Assisted Therapy for Persons with Disabilities Based on Canine Tail Language Interpretation via Gaussian-Trapezoidal Fuzzy Emotional Behavior Model
Authors: W. Phanwanich, O. Kumdee, P. Ritthipravat, Y. Wongsawat
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In order to alleviate the mental and physical problems of persons with disabilities, animal-assisted therapy (AAT) is one of the possible modalities that employs the merit of the human-animal interaction. Nevertheless, to achieve the purpose of AAT for persons with severe disabilities (e.g. spinal cord injury, stroke, and amyotrophic lateral sclerosis), real-time animal language interpretation is desirable. Since canine behaviors can be visually notable from its tail, this paper proposes the automatic real-time interpretation of canine tail language for human-canine interaction in the case of persons with severe disabilities. Canine tail language is captured via two 3-axis accelerometers. Directions and frequencies are selected as our features of interests. The novel fuzzy rules based on Gaussian-Trapezoidal model and center of gravity (COG)-based defuzzification method are proposed in order to interpret the features into four canine emotional behaviors, i.e., agitate, happy, scare and neutral as well as its blended emotional behaviors. The emotional behavior model is performed in the simulated dog and has also been evaluated in the real dog with the perfect recognition rate.Keywords: Animal-assisted therapy (AAT), Persons with disabilities, Canine tail language, Fuzzy emotional behavior model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20228218 Robust Adaptive ELS-QR Algorithm for Linear Discrete Time Stochastic Systems Identification
Authors: Ginalber L. O. Serra
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This work proposes a recursive weighted ELS algorithm for system identification by applying numerically robust orthogonal Householder transformations. The properties of the proposed algorithm show it obtains acceptable results in a noisy environment: fast convergence and asymptotically unbiased estimates. Comparative analysis with others robust methods well known from literature are also presented.Keywords: Stochastic Systems, Robust Identification, Parameter Estimation, Systems Identification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14968217 MARTI and MRSD: Newly Developed Isolation-Damping Devices with Adaptive Hardening for Seismic Protection of Structures
Authors: Murat Dicleli, Ali Salem Milani
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In this paper, a summary of analytical and experimental studies into the behavior of a new hysteretic damper, designed for seismic protection of structures is presented. The Multidirectional Torsional Hysteretic Damper (MRSD) is a patented invention in which a symmetrical arrangement of identical cylindrical steel cores is so configured as to yield in torsion while the structure experiences planar movements due to earthquake shakings. The new device has certain desirable properties. Notably, it is characterized by a variable and controllable-via-design post-elastic stiffness. The mentioned property is a result of MRSD’s kinematic configuration which produces this geometric hardening, rather than being a secondary large-displacement effect. Additionally, the new system is capable of reaching high force and displacement capacities, shows high levels of damping, and very stable cyclic response. The device has gone through many stages of design refinement, multiple prototype verification tests and development of design guide-lines and computer codes to facilitate its implementation in practice. Practicality of the new device, as offspring of an academic sphere, is assured through extensive collaboration with industry in its final design stages, prototyping and verification test programs.Keywords: Seismic, isolation, damper, adaptive stiffness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20068216 Climate Adaptive Building Shells for Plus-Energy-Buildings, Designed on Bionic Principles
Authors: Andreas Hammer
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Six peculiar architecture designs from the Frankfurt University will be discussed within this paper and their future potential of the adaptable and solar thin-film sheets implemented facades will be shown acting and reacting on climate/solar changes of their specific sites. The different aspects, as well as limitations with regard to technical and functional restrictions, will be named. The design process for a “multi-purpose building”, a “high-rise building refurbishment” and a “biker’s lodge” on the river Rheine valley, has been critically outlined and developed step by step from an international studentship towards an overall energy strategy, that firstly had to push the design to a plus-energy building and secondly had to incorporate bionic aspects into the building skins design. Both main parameters needed to be reviewed and refined during the whole design process. Various basic bionic approaches have been given [e.g. solar ivy TM, flectofin TM or hygroskin TM, which were to experiment with, regarding the use of bendable photovoltaic thin film elements being parts of a hybrid, kinetic façade system.
Keywords: Energy-strategy, photovoltaic in building skins, bionic and bioclimatic design, plus-energy-buildings, solar gain, the harvesting façade, sustainable building concept, high-efficiency building skin, climate adaptive Building Shells (CABS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27918215 Image Thresholding for Weld Defect Extraction in Industrial Radiographic Testing
Authors: Nafaâ Nacereddine, Latifa Hamami, Djemel Ziou
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In non destructive testing by radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptability or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of thresholding methods must be done judiciously. In this paper, performance criteria are used to conduct a comparative study of thresholding methods based on gray level histogram, 2-D histogram and locally adaptive approach for weld defect extraction in radiographic images.
Keywords: 1D and 2D histogram, locally adaptive approach, performance criteria, radiographic image, thresholding, weld defect.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23498214 Information Technologies in Automotive Assembly Industry in Thailand
Authors: Jirarat Teeravaraprug, Usawadee Inklay
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This paper gave an attempt in prioritizing information technologies that organizations should give concentration. The case study was organizations in the automotive assembly industry in Thailand. Data were first collected to gather all information technologies known and used in the automotive assembly industry in Thailand. Five experts from the industries were surveyed based on the concept of fuzzy DEMATEL. The information technologies were categorized into six groups, which were communication, transaction, planning, organization management, warehouse management, and transportation. The cause groups of information technologies for each group were analyzed and presented. Moreover, the relationship between the used and the significant information technologies was given. Discussions based on the used information technologies and the research results are given.
Keywords: Information technology, automotive assembly industry, fuzzy DEMATEL.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17228213 Adaptive Kernel Filtering Used in Video Processing
Authors: Rasmus Engholm, Eva B. Vedel Jensen, Henrik Karstoft
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In this paper we present a noise reduction filter for video processing. It is based on the recently proposed two dimensional steering kernel, extended to three dimensions and further augmented to suit the spatial-temporal domain of video processing. Two alternative filters are proposed - the time symmetric kernel and the time asymmetric kernel. The first reduces the noise on single sequences, but to handle the problems at scene shift the asymmetric kernel is introduced. The performance of both are tested on simulated data and on a real video sequence together with the existing steering kernel. The proposed kernels improves the Rooted Mean Squared Error (RMSE) compared to the original steering kernel method on video material.
Keywords: Adaptive image filtering, noise reduction, kernel methods, video processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14788212 Adaptive Dynamic Time Warping for Variable Structure Pattern Recognition
Authors: S. V. Yendiyarov
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Pattern discovery from time series is of fundamental importance. Particularly, when information about the structure of a pattern is not complete, an algorithm to discover specific patterns or shapes automatically from the time series data is necessary. The dynamic time warping is a technique that allows local flexibility in aligning time series. Because of this, it is widely used in many fields such as science, medicine, industry, finance and others. However, a major problem of the dynamic time warping is that it is not able to work with structural changes of a pattern. This problem arises when the structure is influenced by noise, which is a common thing in practice for almost every application. This paper addresses this problem by means of developing a novel technique called adaptive dynamic time warping.
Keywords: Pattern recognition, optimal control, quadratic programming, dynamic programming, dynamic time warping, sintering control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20508211 An Induction Motor Drive System with Intelligent Supervisory Control for Water Networks Including Storage Tank
Authors: O. S. Ebrahim, K. O. Shawky, M. A. Badr, P. K. Jain
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This paper describes an efficient; low-cost; high-availability; induction motor (IM) drive system with intelligent supervisory control for water distribution networks including storage tank. To increase the operational efficiency and reduce cost, the IM drive system includes main pumping unit and an auxiliary voltage source inverter (VSI) fed unit. The main unit comprises smart star/delta starter, regenerative fluid clutch, switched VAR compensator, and hysteresis liquid-level controller. Three-state energy saving mode (ESM) is defined at no-load and a logic algorithm is developed for best energetic cost reduction. To reduce voltage sag, the supervisory controller operates the switched VAR compensator upon motor starting. To provide smart star/delta starter at low cost, a method based on current sensing is developed for interlocking, malfunction detection, and life–cycles counting and used to synthesize an improved fuzzy logic (FL) based availability assessment scheme. Furthermore, a recurrent neural network (RNN) full state estimator is proposed to provide sensor fault-tolerant algorithm for the feedback control. The auxiliary unit is working at low flow rates and improves the system efficiency and flexibility for distributed generation during islanding mode. Compared with doubly-fed IM, the proposed one ensures 30% working throughput under main motor/pump fault conditions, higher efficiency, and marginal cost difference. This is critically important in case of water networks. Theoretical analysis, computer simulations, cost study, as well as efficiency evaluation, using timely cascaded energy-conservative systems, are performed on IM experimental setup to demonstrate the validity and effectiveness of the proposed drive and control.
Keywords: Artificial Neural Network, ANN, Availability Assessment, Cloud Computing, Energy Saving, Induction Machine, IM, Supervisory Control, Fuzzy Logic, FL, Pumped Storage.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6548210 Investigating Determinants of Medical User Expectations from Hospital Information System
Authors: G. Gürsel, K. H. Gülkesen, N. Zayim, A. Arifoğlu, O. Saka
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User satisfaction is one of the most used success indicators in the research of information system (IS). Literature shows user expectations have great influence on user satisfaction. Both expectation and satisfaction of users are important for Hospital Information Systems (HIS). Education, IS experience, age, attitude towards change, business title, sex and working unit of the hospital, are examined as the potential determinant of the medical users’ expectations. Data about medical user expectations are collected by the “Expectation Questionnaire” developed for this study. Expectation data are used for calculating the Expectation Meeting Ratio (EMR) with the evaluation framework also developed for this study. The internal consistencies of the answers to the questionnaire are measured by Cronbach´s Alpha coefficient. The multivariate analysis of medical user’s EMRs of HIS is performed by forward stepwise binary logistic regression analysis. Education and business title is appeared to be the determinants of expectations from HIS.Keywords: Evaluation, Fuzzy Logic, Hospital Information System, User Expectation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19528209 A Decision Support Model for Bank Branch Location Selection
Authors: Nihan Cinar
Abstract:
Location selection is one of the most important decision making process which requires to consider several criteria based on the mission and the strategy. This study-s object is to provide a decision support model in order to help the bank selecting the most appropriate location for a bank-s branch considering a case study in Turkey. The object of the bank is to select the most appropriate city for opening a branch among six alternatives in the South-Eastern of Turkey. The model in this study was consisted of five main criteria which are Demographic, Socio-Economic, Sectoral Employment, Banking and Trade Potential and twenty one subcriteria which represent the bank-s mission and strategy. Because of the multi-criteria structure of the problem and the fuzziness in the comparisons of the criteria, fuzzy AHP is used and for the ranking of the alternatives, TOPSIS method is used.Keywords: MCDM, bank branch location, fuzzy AHP, TOPSIS.
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