Search results for: wireless sensor network.
795 Analysis and Control of Camera Type Weft Straightener
Authors: Jae-Yong Lee, Gyu-Hyun Bae, Yun-Soo Chung, Dae-Sub Kim, Jae-Sung Bae
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In general, fabric is heat-treated using a stenter machine in order to dry and fix its shape. It is important to shape before the heat treatment because it is difficult to revert back once the fabric is formed. To produce the product of right shape, camera type weft straightener has been applied recently to capture and process fabric images quickly. It is more powerful in determining the final textile quality rather than photo-sensor. Positioning in front of a stenter machine, weft straightener helps to spread fabric evenly and control the angle between warp and weft constantly as right angle by handling skew and bow rollers. To process this tricky procedure, the structural analysis should be carried out in advance, based on which, its control technology can be drawn. A structural analysis is to figure out the specific contact/slippage characteristics between fabric and roller. We already examined the applicability of camera type weft straightener to plain weave fabric and found its possibility and the specific working condition of machine and rollers. In this research, we aimed to explore another applicability of camera type weft straightener. Namely, we tried to figure out camera type weft straightener can be used for fabrics. To find out the optimum condition, we increased the number of rollers. The analysis is done by ANSYS software using Finite Element Analysis method. The control function is demonstrated by experiment. In conclusion, the structural analysis of weft straightener is done to identify a specific characteristic between roller and fabrics. The control of skew and bow roller is done to decrease the error of the angle between warp and weft. Finally, it is proved that camera type straightener can also be used for the special fabrics.
Keywords: Camera type weft straightener, structure analysis, control, skew and bow roller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1439794 Musical Instrument Classification Using Embedded Hidden Markov Models
Authors: Ehsan Amid, Sina Rezaei Aghdam
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In this paper, a novel method for recognition of musical instruments in a polyphonic music is presented by using an embedded hidden Markov model (EHMM). EHMM is a doubly embedded HMM structure where each state of the external HMM is an independent HMM. The classification is accomplished for two different internal HMM structures where GMMs are used as likelihood estimators for the internal HMMs. The results are compared to those achieved by an artificial neural network with two hidden layers. Appropriate classification accuracies were achieved both for solo instrument performance and instrument combinations which demonstrates that the new approach outperforms the similar classification methods by means of the dynamic of the signal.Keywords: hidden Markov model (HMM), embedded hidden Markov models (EHMM), MFCC, musical instrument.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1877793 Intervention Targeting in Environmental Networks
Authors: Chukwudi Henry Dike
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We explore targeted subsidy in a set-up for which manufacturing firms in a waste-spillover network make endogenous production decisions. Here, games of substitution in digraphs arises where waste-producing firms internalise negative externality in a quadratic fashion. We find neutrality in intervention policies that create or reduce spillover links. Most importantly, we observe centrality distinction in asymmetric digraphs so that the dependence and power of each firm play unique roles. Here we see that in targeted subsidy, a firm with greater centrality guarantees optimal welfare improvement. This centrality however measures the weakness of each firm’s Nash-based link to other neighbourhood firms i.e., lower negative externality.
Keywords: Centrality, externality, key-player, Nash-Equilibrium.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 193792 Impact of Harmonic Resonance and V-THD in Sohar Industrial Port–C Substation
Authors: R. S. Al Abri, M. H. Albadi, M. H. Al Abri, U. K. Al Rasbi, M. H. Al Hasni, S. M. Al Shidi
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This paper presents an analysis study on the impacts of the changes of the capacitor banks, the loss of a transformer, and the installation of distributed generation on the voltage total harmonic distortion and harmonic resonance. The study is applied in a real system in Oman, Sohar Industrial Port–C Substation Network. Frequency scan method and Fourier series analysis method are used with the help of EDSA software. Moreover, the results are compared with limits specified by national Oman distribution code.Keywords: Power quality, capacitor bank, voltage total harmonics distortion, harmonic resonance, frequency scan.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2058791 Teaching Contemporary Power Distribution and Industrial Networks in Higher Education Vocational Studies
Authors: Rade M. Ciric
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The paper shows the development and implementation of the syllabus of the subject 'Distribution and Industrial Networks', attended by the vocational specialist Year 4 students of the Electric Power Engineering study programme at the Higher Education Technical School of Vocational Studies in Novi Sad. The aim of the subject is to equip students with the knowledge necessary for planning, exploitation and management of distributive and industrial electric power networks in an open electricity market environment. The results of the evaluation of educational outcomes on the subject are presented and discussed.
Keywords: Engineering education, power distribution network, syllabus implementation, outcome evaluation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 764790 Issue Reorganization Using the Measure of Relevance
Authors: William Wong Xiu Shun, Yoonjin Hyun, Mingyu Kim, Seongi Choi, Namgyu Kim
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The need to extract R&D keywords from issues and use them to retrieve R&D information is increasing rapidly. However, it is difficult to identify related issues or distinguish them. Although the similarity between issues cannot be identified, with an R&D lexicon, issues that always share the same R&D keywords can be determined. In detail, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Furthermore, the relationship among issues that share the same R&D keywords can be shown in a more systematic way by clustering them according to keywords. Thus, sharing R&D results and reusing R&D technology can be facilitated. Indirectly, redundant investment in R&D can be reduced as the relevant R&D information can be shared among corresponding issues and the reusability of related R&D can be improved. Therefore, a methodology to cluster issues from the perspective of common R&D keywords is proposed to satisfy these demands.
Keywords: Clustering, Social Network Analysis, Text Mining, Topic Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2028789 Stability Issues on an Implemented All-Pass Filter Circuitry
Authors: Ákos Pintér, István Dénes
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The so-called all-pass filter circuits are commonly used in the field of signal processing, control and measurement. Being connected to capacitive loads, these circuits tend to loose their stability; therefore the elaborate analysis of their dynamic behavior is necessary. The compensation methods intending to increase the stability of such circuits are discussed in this paper, including the socalled lead-lag compensation technique being treated in detail. For the dynamic modeling, a two-port network model of the all-pass filter is being derived. The results of the model analysis show, that effective lead-lag compensation can be achieved, alone by the optimization of the circuit parameters; therefore the application of additional electric components are not needed to fulfill the stability requirement.Keywords: all-pass filter, frequency compensation, stability, linear modeling
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2506788 Load Modeling for Power Flow and Transient Stability Computer Studies at BAKHTAR Network
Authors: M. Sedighizadeh, A. Rezazadeh
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A method has been developed for preparing load models for power flow and stability. The load modeling (LOADMOD) computer software transforms data on load class mix, composition, and characteristics into the from required for commonly–used power flow and transient stability simulation programs. Typical default data have been developed for load composition and characteristics. This paper defines LOADMOD software and describes the dynamic and static load modeling techniques used in this software and results of initial testing for BAKHTAR power system.Keywords: Load Modelling, Static, Power Flow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2047787 LIDAR Obstacle Warning and Avoidance System for Unmanned Aircraft
Authors: Roberto Sabatini, Alessandro Gardi, Mark A. Richardson
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The availability of powerful eye-safe laser sources and the recent advancements in electro-optical and mechanical beam-steering components have allowed laser-based Light Detection and Ranging (LIDAR) to become a promising technology for obstacle warning and avoidance in a variety of manned and unmanned aircraft applications. LIDAR outstanding angular resolution and accuracy characteristics are coupled to its good detection performance in a wide range of incidence angles and weather conditions, providing an ideal obstacle avoidance solution, which is especially attractive in low-level flying platforms such as helicopters and small-to-medium size Unmanned Aircraft (UA). The Laser Obstacle Avoidance Marconi (LOAM) system is one of such systems, which was jointly developed and tested by SELEX-ES and the Italian Air Force Research and Flight Test Centre. The system was originally conceived for military rotorcraft platforms and, in this paper, we briefly review the previous work and discuss in more details some of the key development activities required for integration of LOAM on UA platforms. The main hardware and software design features of this LOAM variant are presented, including a brief description of the system interfaces and sensor characteristics, together with the system performance models and data processing algorithms for obstacle detection, classification and avoidance. In particular, the paper focuses on the algorithm proposed for optimal avoidance trajectory generation in UA applications.
Keywords: LIDAR, Low-Level Flight, Nap-of-the-Earth Flight, Near Infra-Red, Obstacle Avoidance, Obstacle Detection, Obstacle Warning System, Sense and Avoid, Trajectory Optimisation, Unmanned Aircraft.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7065786 Working Mode and Key Technology of Thermal Vacuum Test Software for Spacecraft Test
Authors: Zhang Lei, Zhan Haiyang, Gu Miao
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A universal software platform is developed for improving the defects in the practical one. This software platform has distinct advantages in modularization, information management, and the interfaces. Several technologies such as computer technology, virtualization technology, network technology, etc. are combined together in this software platform, and four working modes are introduced in this article including single mode, distributed mode, cloud mode, and the centralized mode. The application area of the software platform is extended through the switch between these working modes. The software platform can arrange the thermal vacuum test process automatically. This function can improve the reliability of thermal vacuum test.
Keywords: Software platform, thermal vacuum test, control and measurement, work mode.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1288785 Low-Cost Monitoring System for Hydroponic Urban Vertical Farms
Authors: Francesco Ruscio, Paolo Paoletti, Jens Thomas, Paul Myers, Sebastiano Fichera
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This paper presents the development of a low-cost monitoring system for a hydroponic urban vertical farm, enabling its automation and a quantitative assessment of the farm performance. Urban farming has seen increasing interest in the last decade thanks to the development of energy efficient and affordable LED lights; however, the optimal configuration of such systems (i.e. amount of nutrients, light-on time, ambient temperature etc.) is mostly based on the farmers’ experience and empirical guidelines. Moreover, even if simple, the maintenance of such systems is labor intensive as it requires water to be topped-up periodically, mixing of the nutrients etc. To unlock the full potential of urban farming, a quantitative understanding of the role that each variable plays in the growth of the plants is needed, together with a higher degree of automation. The low-cost monitoring system proposed in this paper is a step toward filling this knowledge and technological gap, as it enables collection of sensor data related to water and air temperature, water level, humidity, pressure, light intensity, pH and electric conductivity without requiring any human intervention. More sensors and actuators can also easily be added thanks to the modular design of the proposed platform. Data can be accessed remotely via a simple web interface. The proposed platform can be used both for quantitatively optimizing the setup of the farms and for automating some of the most labor-intensive maintenance activities. Moreover, such monitoring system can also potentially be used for high-level decision making, once enough data are collected.
Keywords: Automation, hydroponics, internet of things, monitoring system, urban farming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1831784 A Fuzzy Approach for Delay Proportion Differentiated Service
Authors: Mehran Garmehi, Yasser Mansouri
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There are two paradigms proposed to provide QoS for Internet applications: Integrated service (IntServ) and Differentiated service (DiffServ).Intserv is not appropriate for large network like Internet. Because is very complex. Therefore, to reduce the complexity of QoS management, DiffServ was introduced to provide QoS within a domain using aggregation of flow and per- class service. In theses networks QoS between classes is constant and it allows low priority traffic to be effected from high priority traffic, which is not suitable. In this paper, we proposed a fuzzy controller, which reduced the effect of low priority class on higher priority ones. Our simulations shows that, our approach reduces the latency dependency of low priority class on higher priority ones, in an effective manner.
Keywords: QoS, Differentiated Service (DiffServ), FuzzyController, Delay.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1276783 Application of the Discrete-Event Simulation When Optimizing of Business Processes in Trading Companies
Authors: Maxat Bokambayev, Bella Tussupova, Aisha Mamyrova, Erlan Izbasarov
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Optimization of business processes in trading companies is reviewed in the report. There is the presentation of the “Wholesale Customer Order Handling Process” business process model applicable for small and medium businesses. It is proposed to apply the algorithm for automation of the customer order processing which will significantly reduce labor costs and time expenditures and increase the profitability of companies. An optimized business process is an element of the information system of accounting of spare parts trading network activity. The considered algorithm may find application in the trading industry as well.
Keywords: Business processes, discrete-event simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1556782 A Distributed Algorithm for Intrinsic Cluster Detection over Large Spatial Data
Authors: Sauravjyoti Sarmah, Rosy Das, Dhruba Kr. Bhattacharyya
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Clustering algorithms help to understand the hidden information present in datasets. A dataset may contain intrinsic and nested clusters, the detection of which is of utmost importance. This paper presents a Distributed Grid-based Density Clustering algorithm capable of identifying arbitrary shaped embedded clusters as well as multi-density clusters over large spatial datasets. For handling massive datasets, we implemented our method using a 'sharednothing' architecture where multiple computers are interconnected over a network. Experimental results are reported to establish the superiority of the technique in terms of scale-up, speedup as well as cluster quality.Keywords: Clustering, Density-based, Grid-based, Adaptive Grid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1588781 Artificial Neural Networks for Classifying Magnetic Measurements in Tokamak Reactors
Authors: A. Greco, N. Mammone, F.C. Morabito, M.Versaci
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This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compares with earlier methods.
Keywords: Tokamak, sensors, artificial neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1815780 Genetic-Fuzzy Inverse Controller for a Robot Arm Suitable for On Line Applications
Authors: Abduladheem A. Ali, Easa A. Abd
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The robot is a repeated task plant. The control of such a plant under parameter variations and load disturbances is one of the important problems. The aim of this work is to design Geno-Fuzzy controller suitable for online applications to control single link rigid robot arm plant. The genetic-fuzzy online controller (indirect controller) has two genetic-fuzzy blocks, the first as controller, the second as identifier. The identification method is based on inverse identification technique. The proposed controller it tested in normal and load disturbance conditions.Keywords: Fuzzy network, genetic algorithm, robot control, online genetic control, parameter identification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1449779 A Preemptive Link State Spanning Tree Source Routing Scheme for Opportunistic Data Forwarding in MANET
Authors: R. Poonkuzhali, M. Y. Sanavullah, A. Sabari
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Opportunistic Data Forwarding (ODF) has drawn much attention in mobile adhoc networking research in recent years. The effectiveness of ODF in MANET depends on a suitable routing protocol which provides a powerful source routing services. PLSR is featured by source routing, loop free and small routing overhead. The update messages in PLSR are integrated into a tree structure and no need to time stamp routing updates which reduces the routing overhead.
Keywords: Mobile ad hoc network (MANET), Opportunistic data forwarding (ODF), Preemptive link state spanning tree routing (PLSR), Depth First Search (DFS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1920778 An Agent-Based Approach to Immune Modelling: Priming Individual Response
Authors: Dimitri Perrin, Heather J. Ruskin, Martin Crane
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This study focuses on examining why the range of experience with respect to HIV infection is so diverse, especially in regard to the latency period. An agent-based approach in modelling the infection is used to extract high-level behaviour which cannot be obtained analytically from the set of interaction rules at the cellular level. A prototype model encompasses local variation in baseline properties, contributing to the individual disease experience, and is included in a network which mimics the chain of lymph nodes. The model also accounts for stochastic events such as viral mutations. The size and complexity of the model require major computational effort and parallelisation methods are used.Keywords: HIV, Immune modelling, Agent-based system, individual response.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1263777 Extended Set of DCT-TPLBP and DCT-FPLBP for Face Recognition
Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui
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In this paper, we describe an application for face recognition. Many studies have used local descriptors to characterize a face, the performance of these local descriptors remain low by global descriptors (working on the entire image). The application of local descriptors (cutting image into blocks) must be able to store both the advantages of global and local methods in the Discrete Cosine Transform (DCT) domain. This system uses neural network techniques. The letter method provides a good compromise between the two approaches in terms of simplifying of calculation and classifying performance. Finally, we compare our results with those obtained from other local and global conventional approaches.Keywords: Face detection, face recognition, discrete cosine transform (DCT), FPLBP, TPLBP, NN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1963776 Autonomous Robots- Visual Perception in Underground Terrains Using Statistical Region Merging
Authors: Omowunmi E. Isafiade, Isaac O. Osunmakinde, Antoine B. Bagula
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Robots- visual perception is a field that is gaining increasing attention from researchers. This is partly due to emerging trends in the commercial availability of 3D scanning systems or devices that produce a high information accuracy level for a variety of applications. In the history of mining, the mortality rate of mine workers has been alarming and robots exhibit a great deal of potentials to tackle safety issues in mines. However, an effective vision system is crucial to safe autonomous navigation in underground terrains. This work investigates robots- perception in underground terrains (mines and tunnels) using statistical region merging (SRM) model. SRM reconstructs the main structural components of an imagery by a simple but effective statistical analysis. An investigation is conducted on different regions of the mine, such as the shaft, stope and gallery, using publicly available mine frames, with a stream of locally captured mine images. An investigation is also conducted on a stream of underground tunnel image frames, using the XBOX Kinect 3D sensors. The Kinect sensors produce streams of red, green and blue (RGB) and depth images of 640 x 480 resolution at 30 frames per second. Integrating the depth information to drivability gives a strong cue to the analysis, which detects 3D results augmenting drivable and non-drivable regions in 2D. The results of the 2D and 3D experiment with different terrains, mines and tunnels, together with the qualitative and quantitative evaluation, reveal that a good drivable region can be detected in dynamic underground terrains.Keywords: Drivable Region Detection, Kinect Sensor, Robots' Perception, SRM, Underground Terrains.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1825775 Safe, Effective, and Cost-Efficient Air Cleaning for Populated Rooms and Entire Buildings Based on the Disinfecting Power of Vaporized Hypochlorous Acid
Authors: D. Boecker, R. Breves, F. Herth, Z. Zhang, C. Bulitta
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Pathogen-carrying aerosol particles are recognized as important infection carriers like those in the current Corona pandemic. This infection route is often underestimated yet represents the infection route that has been least systematically countered to date. Particularly, the transmission indoors is of the highest concern but current indoor safety measures (e.g.: distancing, masks, filters) provide only limited protection. Inhalation of hypochlorous acid (HOCl) containing aerosols may become an alternate route to attack the incubating microbes in-situ and so potentially lead to a reduction of symptoms of already infected individuals. We investigated a facility-wide air-disinfection concept utilizing the potential of vaporized HOCl to become a disinfecting agent for populated indoor atmospheres. Aerosolized bacterial microbes were used as surrogates for a viral contamination, particularly the enveloped coronavirus. For the room air purification tests we aerosolized bacterial suspensions into lab chambers preloaded with vaporized HOCl solutions. Concentration of ‘free active chlorine’ in the test chamber atmosphere was determined with a special gas sensor system (Draeger AG, Lübeck, Germany) controlling the amount of vaporized HOCl via an aerosolis® device (oji Europe GmbH, Nauen, Germany). We could confirm the disinfecting power of HOCl in suspensions and determined the high efficacy of vaporized HOCl to disinfect atmospheres of populated indoor places at safe and non-irritant levels.
Keywords: Hypochlorous acid, HOCl, indoor air cleaning, infection control, microbial air burden, protective atmosphere.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 397774 Deep Learning Based 6D Pose Estimation for Bin-Picking Using 3D Point Clouds
Authors: Hesheng Wang, Haoyu Wang, Chungang Zhuang
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Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.
Keywords: Pose estimation, deep learning, point cloud, bin-picking, 3D computer vision.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1801773 Evidence Theory Enabled Quickest Change Detection Using Big Time-Series Data from Internet of Things
Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker
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Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.Keywords: CUSUM, evidence theory, KL divergence, quickest change detection, time series data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 983772 Context Modeling and Reasoning Approach in Context-Aware Middleware for URC System
Authors: Chung-Seong Hong, Hyung-Sun Kim, Joonmyun Cho, Hyun Kyu Cho, Hyun-Chan Lee
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To realize the vision of ubiquitous computing, it is important to develop a context-aware infrastructure which can help ubiquitous agents, services, and devices become aware of their contexts because such computational entities need to adapt themselves to changing situations. A context-aware infrastructure manages the context model representing contextual information and provides appropriate information. In this paper, we introduce Context-Aware Middleware for URC System (hereafter CAMUS) as a context-aware infrastructure for a network-based intelligent robot system and discuss the ontology-based context modeling and reasoning approach which is used in that infrastructure.Keywords: CAMUS, Context-Aware, Context Model, Ontology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1906771 Active Disturbance Rejection Control for Wind System Based On a DFIG
Authors: R. Chakib, A. Essadki, M. Cherkaoui
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This paper proposes the study of a robust control of the doubly fed induction generator (DFIG) used in a wind energy production. The proposed control is based on the linear active disturbance rejection control (ADRC) and it is applied to the control currents rotor of the DFIG, the DC bus voltage and active and reactive power exchanged between the DFIG and the network. The system under study and the proposed control are simulated using MATLAB/SIMULINK.
Keywords: Doubly fed induction generator DFIG, Active disturbance rejection control ADRC, Vector control, MPPT, Extended state observer, back to back converter, Wind turbine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2499770 Research on Modern Semiconductor Converters and the Usage of SiC Devices in the Technology Centre of Ostrava
Authors: P. Vaculík, P. Kaňovský
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The following article presents Technology Centre of Ostrava (TCO) in the Czech Republic describing the structure and main research areas realized by the project ENET - Energy Units for Utilization of non Traditional Energy Sources. More details are presented from the research program dealing with transformation, accumulation and distribution of electric energy. Technology Centre has its own energy mix consisting of alternative sources of fuel sources that use of process gases from the storage part and also the energy from distribution network. The article will be focus on the properties and application possibilities SiC semiconductor devices for power semiconductor converter for photovoltaic systems.Keywords: SiC, Si, Technology Centre of Ostrava, Photovoltaic Systems, DC/DC Converter, Simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1835769 Applying Lagrangian Relaxation-Based Algorithm for the Airline Coordinated Flight Scheduling Problems
Authors: Chia-Hung Chen, Shangyao Yan
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The solution algorithm, based on Lagrangian relaxation, a sub-gradient method and a heuristic to find the upper bound of the solution, is proposed to solve the coordinated fleet routing and flight scheduling problems. Numerical tests are performed to evaluate the proposed algorithm using real operating data from two Taiwan airlines. The test results indicate that the solution algorithm is a significant improvement over those obtained with CPLEX, consequently they could be useful for allied airlines to solve coordinated fleet routing and flight scheduling problems.
Keywords: Coordinated flight scheduling, multiple commodity network flow problem, Lagrangian relaxation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1804768 Health Risk Assessment in Lead Battery Smelter Factory: A Bayesian Belief Network Method
Authors: Kevin Fong-Rey Liu, Ken Yeh, Cheng-Wu Chen, Han-Hsi Liang
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This paper proposes the use of Bayesian belief networks (BBN) as a higher level of health risk assessment for a dumping site of lead battery smelter factory. On the basis of the epidemiological studies, the actual hospital attendance records and expert experiences, the BBN is capable of capturing the probabilistic relationships between the hazardous substances and their adverse health effects, and accordingly inferring the morbidity of the adverse health effects. The provision of the morbidity rates of the related diseases is more informative and can alleviate the drawbacks of conventional methods.Keywords: Bayesian belief networks, lead battery smelter factory, health risk assessment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1712767 A Novel Web Metric for the Evaluation of Internet Trends
Authors: Radek Malinský, Ivan Jelínek
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Web 2.0 (social networking, blogging and online forums) can serve as a data source for social science research because it contains vast amount of information from many different users. The volume of that information has been growing at a very high rate and becoming a network of heterogeneous data; this makes things difficult to find and is therefore not almost useful. We have proposed a novel theoretical model for gathering and processing data from Web 2.0, which would reflect semantic content of web pages in better way. This article deals with the analysis part of the model and its usage for content analysis of blogs. The introductory part of the article describes methodology for the gathering and processing data from blogs. The next part of the article is focused on the evaluation and content analysis of blogs, which write about specific trend.Keywords: Blog, Sentiment Analysis, Web 2.0, Webometrics
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3532766 Knowledge Discovery from Production Databases for Hierarchical Process Control
Authors: Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata
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The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system thus the proposed solution has been verified. The paper documents how is possible to apply the new discovery knowledge to use in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control.
Keywords: Hierarchical process control, knowledge discovery from databases, neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1759