Search results for: Brain Machine Interfaces
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1573

Search results for: Brain Machine Interfaces

553 Bridging the Gap: Living Machine in Educational Nature Preserve Center

Authors: Zakeia Benmoussa

Abstract:

Pressure on freshwater systems comes from removing too much water to grow crops; contamination from economic activities, land use practices, and human waste. The paper will be focusing on how water management can influence the design, implementation, and impacts of the ecological principles of biomimicry as sustainable methods in recycling wastewater. At Texas State, United States of America, in particular the lower area of the Trinity River refuge, there is a true example of the diversity to be found in that area, whether when exploring the lands or the waterways. However, as the Trinity River supplies water to the state’s residents, the lower part of the river at Liberty County presents several problem of wastewater discharge in the river. Therefore, conservation efforts are particularly important in the Trinity River basin. Clearly, alternative ways must be considered in order to conserve water to meet future demands. As a result, there should be another system provided rather than the conventional water treatment. Mimicking ecosystem's technologies out of context is not enough, but if we incorporate plants into building architecture, in addition to their beauty, they can filter waste, absorb excess water, and purify air. By providing an architectural proposal center, a living system can be explored through several methods that influence natural resources on the micro-scale in order to impact sustainability on the macro-scale. The center consists of an ecological program of Plant and Water Biomimicry study which becomes a living organism that purifies the river water in a natural way through architecture. Consequently, a rich beautiful nature could be used as an educational destination, observation and adventure, as well as providing unpolluted fresh water to the major cities of Texas. As a result, these facts raise a couple of questions: Why is conservation so rarely practiced by those who must extract a living from the land? Are we sufficiently enlightened to realize that we must now challenge that dogma? Do architects respond to the environment and reflect on it in the correct way through their public projects? The method adopted in this paper consists of general research into careful study of the system of the living machine, in how to integrate it at architectural level, and finally, the consolidation of the all the conclusions formed into design proposal. To summarise, this paper attempts to provide a sustainable alternative perspective in bridging physical and mental interaction with biodiversity to enhance nature by using architecture.

Keywords: Biodiversity, design with nature, sustainable architecture, waste water treatment.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1956
552 Collaboration of Multi-Agent and Hyper-Heuristics Systems for Production Scheduling Problem

Authors: C. E. Nugraheni, L. Abednego

Abstract:

This paper introduces a framework based on the collaboration of multi agent and hyper-heuristics to find a solution of the real single machine production problem. There are many techniques used to solve this problem. Each of it has its own advantages and disadvantages. By the collaboration of multi agent system and hyper-heuristics, we can get more optimal solution. The hyper-heuristics approach operates on a search space of heuristics rather than directly on a search space of solutions. The proposed framework consists of some agents, i.e. problem agent, trainer agent, algorithm agent (GPHH, GAHH, and SAHH), optimizer agent, and solver agent. Some low level heuristics used in this paper are MRT, SPT, LPT, EDD, LDD, and MON

Keywords: Hyper-heuristics, multi-agent systems, scheduling problem.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2123
551 Experimental Study of the Fan Electric Drive Based on Two-Speed Motor with Pole-Changing Winding

Authors: M. Bobojanov, D. Rismukhamedov, F. Tuychiev, Kh. Shamsutdinov

Abstract:

The article presents the results of experimental study of a two-speed asynchronous motor 4A80B6/4U3 with pole-changing winding on a fan drive VSUN 160x74-0.55-4 in static and dynamic modes. A prototype of a pole-changing Motor was made based on the results of the calculation and the performance and mechanical characteristics of the Motor were removed at the experimental stand, and useful capacities and other parameters from both poles were determined. In dynamic mode, the curves of changes of torque and current of the stator were removed by direct start, constant speed operation, by switching of speeds and stopping.

Keywords: Pole-changing winding, two speed asynchronous machine, basic scheme, winding factor, differential leakage factor.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 269
550 Matlab/Simulink-Based Transient Stability Analysis Of A Sensorless Synchronous Reluctance Motor

Authors: Mostafa.A. Fellani, Daw .E. Abaid

Abstract:

This paper deals with stability analysis for synchronous reluctance motors drive. Special attention is paid to the transient performance with variations in motor's parameters such as Ld and Rs. A study of the dynamic control using d-q model is presented first in order to clarify the stability of the motor drive system. Based on the experimental parameters of the synchronous reluctance motor, this paper gives some simulation results using MATLAB/SIMULINK software packages. It is concluded that the motor parameters, especially Ld, affect the estimator stability and hence the whole drive system.

Keywords: Dynamic Simulation, MATLAB, PWM-inverter, Reluctance Machine, Sensorless Control

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3939
549 Rapid Data Acquisition System for Complex Algorithm Testing in Plastic Molding Industry

Authors: A. Tellaeche, R. Arana

Abstract:

Injection molding is a very complicated process to monitor and control. With its high complexity and many process parameters, the optimization of these systems is a very challenging problem. To meet the requirements and costs demanded by the market, there has been an intense development and research with the aim to maintain the process under control. This paper outlines the latest advances in necessary algorithms for plastic injection process and monitoring, and also a flexible data acquisition system that allows rapid implementation of complex algorithms to assess their correct performance and can be integrated in the quality control process. This is the main topic of this paper. Finally, to demonstrate the performance achieved by this combination, a real case of use is presented.

Keywords: Plastic injection, machine learning, rapid complex algorithm prototyping.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2096
548 Reciprocating Equipment Piston Rod Dynamic Elastic-Plastic Deformation Analysis

Authors: Amin Almasi

Abstract:

Analysis of reciprocating equipment piston rod leads to nonlinear elastic-plastic deformation analysis of rod with initial imperfection under axial dynamic load. In this paper a new and effective model and analytical formulations are presented to evaluate dynamic deformation and elastic-plastic stresses of reciprocating machine piston rod. This new method has capability to account for geometric nonlinearity, elastic-plastic deformation and dynamic effects. Proposed method can be used for evaluation of piston rod performance for various reciprocating machines under different operation situations. Rod load curves and maximum allowable rod load are calculated with presented method for a refinery type reciprocating compressor. Useful recommendations and guidelines for rod load, rod load reversal and rod drop monitoring are also addressed.

Keywords: Deformation, Reciprocating Equipment, Rod.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3211
547 A POX Controller Module to Collect Web Traffic Statistics in SDN Environment

Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

Abstract:

Software Defined Networking (SDN) is a new norm of networks. It is designed to facilitate the way of managing, measuring, debugging and controlling the network dynamically, and to make it suitable for the modern applications. Generally, measurement methods can be divided into two categories: Active and passive methods. Active measurement method is employed to inject test packets into the network in order to monitor their behaviour (ping tool as an example). Meanwhile the passive measurement method is used to monitor the traffic for the purpose of deriving measurement values. The measurement methods, both active and passive, are useful for the collection of traffic statistics, and monitoring of the network traffic. Although there has been a work focusing on measuring traffic statistics in SDN environment, it was only meant for measuring packets and bytes rates for non-web traffic. In this study, a feasible method will be designed to measure the number of packets and bytes in a certain time, and facilitate obtaining statistics for both web traffic and non-web traffic. Web traffic refers to HTTP requests that use application layer; while non-web traffic refers to ICMP and TCP requests. Thus, this work is going to be more comprehensive than previous works. With a developed module on POX OpenFlow controller, information will be collected from each active flow in the OpenFlow switch, and presented on Command Line Interface (CLI) and wireshark interface. Obviously, statistics that will be displayed on CLI and on wireshark interfaces include type of protocol, number of bytes and number of packets, among others. Besides, this module will show the number of flows added to the switch whenever traffic is generated from and to hosts in the same statistics list. In order to carry out this work effectively, our Python module will send a statistics request message to the switch requesting its current ports and flows statistics in every five seconds; while the switch will reply with the required information in a message called statistics reply message. Thus, POX controller will be notified and updated with any changes could happen in the entire network in a very short time. Therefore, our aim of this study is to prepare a list for the important statistics elements that are collected from the whole network, to be used for any further researches; particularly, those that are dealing with the detection of the network attacks that cause a sudden rise in the number of packets and bytes like Distributed Denial of Service (DDoS).

Keywords: Mininet, OpenFlow, POX controller, SDN.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2933
546 Study of Currents and Temperature of Induced Spur Gear using 2d Simulation

Authors: N. Barka, P. Bocher, A. Chebak, J. Brousseau, D. S. Ramdenee

Abstract:

This paper presents the study of induced currents and temperature distribution in gear heated by induction process using 2D finite element (FE) model. The model is developed by coupling Maxwell and heat transfer equations into a multi-physics model. The obtained results allow comparing the medium frequency (MF) and high frequency (HF) cases and the effect of machine parameters on the evolution of induced currents and temperature during heating. The sensitivity study of the temperature profile is conducted and the case hardness is predicted using the final temperature profile. These results are validated using tests and give a good understanding of phenomena during heating process.

Keywords: 2D model, induction heating, spur gear, induced currents, experimental validation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1586
545 Optimization of Cutting Parameters during Machining of Fine Grained Cemented Carbides

Authors: Josef Brychta, Jiri Kratochvil, Marek Pagac

Abstract:

The group of progressive cutting materials can include non-traditional, emerging and less-used materials that can be an efficient use of cutting their lead to a quantum leap in the field of machining. This is essentially a “superhard” materials (STM) based on polycrystalline diamond (PCD) and polycrystalline cubic boron nitride (PCBN) cutting performance ceramics and development is constantly "perfecting" fine coated cemented carbides. The latter cutting materials are broken down by two parameters, toughness and hardness. A variation of alloying elements is always possible to improve only one of each parameter. Reducing the size of the core on the other hand doing achieves "contradictory" properties, namely to increase both hardness and toughness.

Keywords: Grained cutting materials difficult to machine materials, optimum utilization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1552
544 Curvelet Features with Mouth and Face Edge Ratios for Facial Expression Identification

Authors: S. Kherchaoui, A. Houacine

Abstract:

This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: Facial expression identification, curvelet coefficients, support vector machine (SVM).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1822
543 Evaluating Performance of an Anomaly Detection Module with Artificial Neural Network Implementation

Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

Abstract:

Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: Network Intrusion Detection, Machine learning, Artificial Neural Network.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2053
542 A Study of Touching Characters in Degraded Gurmukhi Text

Authors: M. K. Jindal, G. S. Lehal, R. K. Sharma

Abstract:

Character segmentation is an important preprocessing step for text recognition. In degraded documents, existence of touching characters decreases recognition rate drastically, for any optical character recognition (OCR) system. In this paper a study of touching Gurmukhi characters is carried out and these characters have been divided into various categories after a careful analysis.Structural properties of the Gurmukhi characters are used for defining the categories. New algorithms have been proposed to segment the touching characters in middle zone. These algorithms have shown a reasonable improvement in segmenting the touching characters in degraded Gurmukhi script. The algorithms proposed in this paper are applicable only to machine printed text.

Keywords: Character Segmentation, Middle Zone, Touching Characters.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1816
541 Optimal Resource Configuration and Allocation Planning Problem for Bottleneck Machines and Auxiliary Tools

Authors: Yin-Yann Chen, Tzu-Ling Chen

Abstract:

This study presents the case of an actual Taiwanese semiconductor assembly and testing manufacturer. Three major bottleneck manufacturing processes, namely, die bond, wire bond, and molding, are analyzed to determine how to use finite resources to achieve the optimal capacity allocation. A medium-term capacity allocation planning model is developed by considering the optimal total profit to satisfy the promised volume demanded by customers and to obtain the best migration decision among production lines for machines and tools. Finally, sensitivity analysis based on the actual case is provided to explore the effect of various parameter levels.

Keywords: Capacity planning, capacity allocation, machine migration, resource configuration.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 979
540 Vision Based People Tracking System

Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

Abstract:

In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: Camshift Algorithm, Computer Vision, Kalman Filter, Object tracking.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1292
539 Meta Random Forests

Authors: Praveen Boinee, Alessandro De Angelis, Gian Luca Foresti

Abstract:

Leo Breimans Random Forests (RF) is a recent development in tree based classifiers and quickly proven to be one of the most important algorithms in the machine learning literature. It has shown robust and improved results of classifications on standard data sets. Ensemble learning algorithms such as AdaBoost and Bagging have been in active research and shown improvements in classification results for several benchmarking data sets with mainly decision trees as their base classifiers. In this paper we experiment to apply these Meta learning techniques to the random forests. We experiment the working of the ensembles of random forests on the standard data sets available in UCI data sets. We compare the original random forest algorithm with their ensemble counterparts and discuss the results.

Keywords: Random Forests [RF], ensembles, UCI.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2667
538 Automatic Sleep Stage Scoring with Wavelet Packets Based on Single EEG Recording

Authors: Luay A. Fraiwan, Natheer Y. Khaswaneh, Khaldon Y. Lweesy

Abstract:

Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.

Keywords: Features selection, regression trees, sleep stagescoring, wavelet packets.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2303
537 FEA- Aided Design, Optimization and Development of an Axial Flux Motor for Implantable Ventricular Assist Device

Authors: Neethu S., Shinoy K.S., A.S. Shajilal

Abstract:

This paper presents the optimal design and development of an axial flux motor for blood pump application. With the design objective of maximizing the motor efficiency and torque, different topologies of AFPM machine has been examined. Selection of optimal magnet fraction, Halbach arrangement of rotor magnets and the use of Soft Magnetic Composite (SMC) material for the stator core results in a novel motor with improved efficiency and torque profile. The results of the 3D Finite element analysis for the novel motor have been shown.

Keywords: Axial flux motor, Finite Element Methods, Halbach array, Left Ventricular Assist Device, Soft magnetic composite.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2165
536 A Similarity Measure for Clustering and its Applications

Authors: Guadalupe J. Torres, Ram B. Basnet, Andrew H. Sung, Srinivas Mukkamala, Bernardete M. Ribeiro

Abstract:

This paper introduces a measure of similarity between two clusterings of the same dataset produced by two different algorithms, or even the same algorithm (K-means, for instance, with different initializations usually produce different results in clustering the same dataset). We then apply the measure to calculate the similarity between pairs of clusterings, with special interest directed at comparing the similarity between various machine clusterings and human clustering of datasets. The similarity measure thus can be used to identify the best (in terms of most similar to human) clustering algorithm for a specific problem at hand. Experimental results pertaining to the text categorization problem of a Portuguese corpus (wherein a translation-into-English approach is used) are presented, as well as results on the well-known benchmark IRIS dataset. The significance and other potential applications of the proposed measure are discussed.

Keywords: Clustering Algorithms, Clustering Applications, Similarity Measures, Text Clustering

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1540
535 Investigation of the Tattooed Skin by OCT

Authors: Young Geun Kim, Tae Woo Lee, Changmin Yeo, Jung min Yoo, Yeo Jin Kang, Tack-Joong Kim, Byungjo Jung, Ji Hun Cha, Chan Hoi Hur, Dong-Sup Kim, Ki Jung Park, Han Sung Kim

Abstract:

The intention of this lessons is to assess the probability of optical coherence tomography (OCT) for biometric recognition. The OCT is the foundation on an optical signal acquisition and processing method and has the micrometer-resolution. In this study, we used the porcine skin for verifying the abovementioned means. The porcine tissue was sound acknowledged for structural and immunohistochemical similarity with human skin, so it could be suitable for pre-clinical trial as investigational specimen. For this reason, it was tattooed by the tattoo machine with the tattoo-pigment. We detected the pattern of the tattooed skin by the OCT according to needle speed. The result was consistent with the histology images. This result showed that the OCT was effective to examine the tattooed skin section noninvasively. It might be available to identify morphological changes inside the skin.

Keywords: mechanical skin damage, optical coherence tomography, tattooed skin

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1742
534 Automatic Threshold Search for Heat Map Based Feature Selection: A Cancer Dataset Analysis

Authors: Carlos Huertas, Reyes Juarez-Ramirez

Abstract:

Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: Feature selection, mass spectrometry, biomarker discovery, cancer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1558
533 Compensation Method Eliminating Voltage Distortions in PWM Inverter

Authors: H. Sediki, S. Djennoune

Abstract:

The switching lag-time and the voltage drop across the power devices cause serious waveform distortions and fundamental voltage drop in pulse width-modulated inverter output. These phenomenons are conspicuous when both the output frequency and voltage are low. To estimate the output voltage from the PWM reference signal it is essential to take account of these imperfections and to correct them. In this paper, on-line compensation method is presented. It needs three simple blocs to add at the ideal reference voltages. This method does not require any additional hardware circuit and off- line experimental measurement. The paper includes experimental results to demonstrate the validity of the proposed method. It is applied, finally, in case of indirect vector controlled induction machine and implemented using dSpace card.

Keywords: Dead time, field-oriented control, Induction motor, PWM inverter, voltage drop.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4558
532 Assessment of Using Wastage Steel as Welded Reinforcement

Authors: Muhammad Murtaza Nasir, Safdar Abbas Zaidi, Kamran Khan

Abstract:

This work is carried out to evaluate the possibility of using to-be-wasted steel as reinforcement after welding together pieces of reinforcing steel bars, left over during construction activities. Tests were performed on a total of nine samples. These were made by welding pieces of reinforcing steel bars purchased from the local scrap steel market. The samples were tested in uniaxial tension using a universal testing machine (UTM). It was found that the failure of the welded bars is governed by the thickness of the weld. It is concluded that suitable design of the weld is essential for achieving the desired level of ductility/elongation of these bars, if they are to be used as conventional reinforcement in reinforced concrete members.

Keywords: Ductility/elongation, low cost housing, reinforced concrete, welding, welded reinforcement, wastage steel.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 747
531 Prediction of Cardiovascular Disease by Applying Feature Extraction

Authors: Nebi Gedik

Abstract:

Heart disease threatens the lives of a great number of people every year around the world. Heart issues lead to many of all deaths; therefore, early diagnosis and treatment are critical. The diagnosis of heart disease is complicated due to several factors affecting health such as high blood pressure, raised cholesterol, an irregular pulse rhythm, and more. Artificial intelligence has the potential to assist in the early detection and treatment of diseases. Improving heart failure prediction is one of the primary goals of research on heart disease risk assessment. This study aims to determine the features that provide the most successful classification prediction in detecting cardiovascular disease. The performances of each feature are compared using the K-Nearest Neighbor machine learning method. The feature that gives the most successful performance has been identified.

Keywords: Cardiovascular disease, feature extraction, supervised learning, k-NN.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 79
530 Direct Torque Control - DTC of Induction Motor Used for Piloting a Centrifugal Pump Supplied by a Photovoltaic Generator

Authors: S. Abouda, F. Nollet, A. Chaari, N. Essounbouli, Y. Koubaa

Abstract:

In this paper we propose the study of a centrifugal pump control system driven by a three-phase induction motor, which is supplied by a PhotoVoltaic PV generator. The system includes solar panel, a DC / DC converter equipped with its MPPT control, a voltage inverter to three-phase Pulse Width Modulation - PWM and a centrifugal pump driven by a three phase induction motor. In order to control the flow of the centrifugal pump, a Direct Torque Control - DTC of the induction machine is used. To illustrate the performances of the control, simulation results are carried out using Matlab/Simulink.

Keywords: Photovoltaic generators, Maximum power point tracking (MPPT), DC/DC converters, Induction motor, Direct torque control (DTC).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3131
529 Modified Data Mining Approach for Defective Diagnosis in Hard Disk Drive Industry

Authors: S. Soommat, S. Patamatamkul, T. Prempridi, M. Sritulyachot, P. Ineure, S. Yimman

Abstract:

Currently, slider process of Hard Disk Drive Industry become more complex, defective diagnosis for yield improvement becomes more complicated and time-consumed. Manufacturing data analysis with data mining approach is widely used for solving that problem. The existing mining approach from combining of the KMean clustering, the machine oriented Kruskal-Wallis test and the multivariate chart were applied for defective diagnosis but it is still be a semiautomatic diagnosis system. This article aims to modify an algorithm to support an automatic decision for the existing approach. Based on the research framework, the new approach can do an automatic diagnosis and help engineer to find out the defective factors faster than the existing approach about 50%.

Keywords: Slider process, Defective diagnosis and Data mining.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1173
528 Intelligent Design of Reconfigurable Machines

Authors: Majid Tolouei-Rad

Abstract:

This paper presents methodologies for developing an intelligent CAD system assisting in analysis and design of reconfigurable special machines. It describes a procedure for determining feasibility of utilizing these machines for a given part and presents a model for developing an intelligent CAD system. The system analyzes geometrical and topological information of the given part to determine possibility of the part being produced by reconfigurable special machines from a technical point of view. Also feasibility of the process from a economical point of view is analyzed. Then the system determines proper positioning of the part considering details of machining features and operations needed. This involves determination of operation types, cutting tools and the number of working stations needed. Upon completion of this stage the overall layout of the machine and machining equipment required are determined.

Keywords: CAD, Knowledge based system, Reconfigurable

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1396
527 Tele-Operated Anthropomorphic Arm and Hand Design

Authors: Namal A. Senanayake, Khoo B. How, Quah W. Wai

Abstract:

In this project, a tele-operated anthropomorphic robotic arm and hand is designed and built as a versatile robotic arm system. The robot has the ability to manipulate objects such as pick and place operations. It is also able to function by itself, in standalone mode. Firstly, the robotic arm is built in order to interface with a personal computer via a serial servo controller circuit board. The circuit board enables user to completely control the robotic arm and moreover, enables feedbacks from user. The control circuit board uses a powerful integrated microcontroller, a PIC (Programmable Interface Controller). The PIC is firstly programmed using BASIC (Beginner-s All-purpose Symbolic Instruction Code) and it is used as the 'brain' of the robot. In addition a user friendly Graphical User Interface (GUI) is developed as the serial servo interface software using Microsoft-s Visual Basic 6. The second part of the project is to use speech recognition control on the robotic arm. A speech recognition circuit board is constructed with onboard components such as PIC and other integrated circuits. It replaces the computers- Graphical User Interface. The robotic arm is able to receive instructions as spoken commands through a microphone and perform operations with respect to the commands such as picking and placing operations.

Keywords: Tele-operated Anthropomorphic Robotic Arm and Hand, Robot Motion System, Serial Servo Controller, Speech Recognition Controller.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1734
526 A Practical Distributed String Matching Algorithm Architecture and Implementation

Authors: Bi Kun, Gu Nai-jie, Tu Kun, Liu Xiao-hu, Liu Gang

Abstract:

Traditional parallel single string matching algorithms are always based on PRAM computation model. Those algorithms concentrate on the cost optimal design and the theoretical speed. Based on the distributed string matching algorithm proposed by CHEN, a practical distributed string matching algorithm architecture is proposed in this paper. And also an improved single string matching algorithm based on a variant Boyer-Moore algorithm is presented. We implement our algorithm on the above architecture and the experiments prove that it is really practical and efficient on distributed memory machine. Its computation complexity is O(n/p + m), where n is the length of the text, and m is the length of the pattern, and p is the number of the processors.

Keywords: Boyer-Moore algorithm, distributed algorithm, parallel string matching, string matching.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2163
525 Automatic Detection of Suicidal Behaviors Using an RGB-D Camera: Azure Kinect

Authors: Maha Jazouli

Abstract:

Suicide is one of the leading causes of death among prisoners, both in Canada and internationally. In recent years, rates of attempts of suicide and self-harm suicide have increased, with hangings being the most frequently used method. The objective of this article is to propose a method to automatically detect suicidal behaviors in real time. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Tests show that the proposed system gives satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: Suicide detection, Kinect Azure, RGB-D camera, SVM, gesture recognition.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 409
524 Using Emotional Learning in Rescue Simulation Environment

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

Abstract:

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.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1589