Search results for: Wireless Sensor Networks
1980 The Parameters Analysis for the Intersection Collision Avoidance Systems Based on Radar Sensors
Authors: Jieh-Shian Young, Chan Wei Hsu
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This paper mainly studies the analyses of parameters in the intersection collision avoidance (ICA) system based on the radar sensors. The parameters include the positioning errors, the repeat period of the radar sensor, the conditions of potential collisions of two cross-path vehicles, etc. The analyses of the parameters can provide the requirements, limitations, or specifications of this ICA system. In these analyses, the positioning errors will be increased as the measured vehicle approach the intersection. In addition, it is not necessary to implement the radar sensor in higher position since the positioning sensitivities become serious as the height of the radar sensor increases. A concept of the safety buffer distances for front and rear of the measured vehicle is also proposed. The conditions for potential collisions of two cross-path vehicles are also presented to facilitate the computation algorithm.Keywords: Intersection Collision Avoidance (ICA), Positioning Errors, Radar Sensors, Sensitivity of Positioning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15641979 Solving Partially Monotone Problems with Neural Networks
Authors: Marina Velikova, Hennie Daniels, Ad Feelders
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In many applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. Here we consider partially monotone problems, where the target variable depends monotonically on some of the predictor variables but not all. We propose an approach to build partially monotone models based on the convolution of monotone neural networks and kernel functions. The results from simulations and a real case study on house pricing show that our approach has significantly better performance than partially monotone linear models. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.Keywords: Mixture models, monotone neural networks, partially monotone models, partially monotone problems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16111978 Comparison between Beta Wavelets Neural Networks, RBF Neural Networks and Polynomial Approximation for 1D, 2DFunctions Approximation
Authors: Wajdi Bellil, Chokri Ben Amar, Adel M. Alimi
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This paper proposes a comparison between wavelet neural networks (WNN), RBF neural network and polynomial approximation in term of 1-D and 2-D functions approximation. We present a novel wavelet neural network, based on Beta wavelets, for 1-D and 2-D functions approximation. Our purpose is to approximate an unknown function f: Rn - R from scattered samples (xi; y = f(xi)) i=1....n, where first, we have little a priori knowledge on the unknown function f: it lives in some infinite dimensional smooth function space and second the function approximation process is performed iteratively: each new measure on the function (xi; f(xi)) is used to compute a new estimate f as an approximation of the function f. Simulation results are demonstrated to validate the generalization ability and efficiency of the proposed Beta wavelet network.
Keywords: Beta wavelets networks, RBF neural network, training algorithms, MSE, 1-D, 2D function approximation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19041977 Uplink Throughput Prediction in Cellular Mobile Networks
Authors: Engin Eyceyurt, Josko Zec
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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.Keywords: Drive test, LTE, machine learning, uplink throughput prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8701976 Percolation Transition with Hidden Variables in Complex Networks
Authors: Zhanli Zhang, Wei Chen, Xin Jiang, Lili Ma, Shaoting Tang, Zhiming Zheng
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A new class of percolation model in complex networks, in which nodes are characterized by hidden variables reflecting the properties of nodes and the occupied probability of each link is determined by the hidden variables of the end nodes, is studied in this paper. By the mean field theory, the analytical expressions for the phase of percolation transition is deduced. It is determined by the distribution of the hidden variables for the nodes and the occupied probability between pairs of them. Moreover, the analytical expressions obtained are checked by means of numerical simulations on a particular model. Besides, the general model can be applied to describe and control practical diffusion models, such as disease diffusion model, scientists cooperation networks, and so on.Keywords: complex networks, percolation transition, hidden variable, occupied probability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16001975 Stability Analysis of Impulsive Stochastic Fuzzy Cellular Neural Networks with Time-varying Delays and Reaction-diffusion Terms
Authors: Xinhua Zhang, Kelin Li
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In this paper, the problem of stability analysis for a class of impulsive stochastic fuzzy neural networks with timevarying delays and reaction-diffusion is considered. By utilizing suitable Lyapunov-Krasovskii funcational, the inequality technique and stochastic analysis technique, some sufficient conditions ensuring global exponential stability of equilibrium point for impulsive stochastic fuzzy cellular neural networks with time-varying delays and diffusion are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters, diffusion effect and impulsive disturbed intention. It is believed that these results are significant and useful for the design and applications of fuzzy neural networks. An example is given to show the effectiveness of the obtained results.
Keywords: Exponential stability, stochastic fuzzy cellular neural networks, time-varying delays, impulses, reaction-diffusion terms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13651974 A Study of Structural Damage Detection for Spacecraft In-Orbit Based on Acoustic Sensor Array
Authors: Lei Qi, Rongxin Yan, Lichen Sun
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With the increasing of human space activities, the number of space debris has increased dramatically, and the possibility that spacecrafts on orbit are impacted by space debris is growing. A method is of the vital significance to real-time detect and assess spacecraft damage, determine of gas leak accurately, guarantee the life safety of the astronaut effectively. In this paper, acoustic sensor array is used to detect the acoustic signal which emits from the damage of the spacecraft on orbit. Then, we apply the time difference of arrival and beam forming algorithm to locate the damage and leakage. Finally, the extent of the spacecraft damage is evaluated according to the nonlinear ultrasonic method. The result shows that this method can detect the debris impact and the structural damage, locate the damage position, and identify the damage degree effectively. This method can meet the needs of structural damage detection for the spacecraft in-orbit.
Keywords: Acoustic sensor array, spacecraft, damage assessment, leakage location.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11111973 Development of a System for Measuring the Three-Axis Pedal Force in Cycling and Its Applications
Authors: Joo-Hack Lee, Jin-Seung Choi, Dong-Won Kang, Jeong-Woo Seo, Ju-Young Kim, Dae-Hyeok Kim, Seung-Tae Yang, Gye-Rae Tack
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For cycling, the analysis of the pedal force is one of the important factors in the study of exercise ability assessment and overuse injuries. In past studies, a two-axis measurement sensor was used at the sagittal plane to measure the force only in the anterior, posterior, and vertical directions and to analyze the loss of force and the injury on the frontal plane due to the forces in the right and left directions. In this study, which is a basic study on diverse analyses of the pedal force that consider the forces on the sagittal plane and the frontal plane, a three-axis pedal force measurement sensor was developed to measure the anterior-posterior (Fx), medio-lateral (Fz), and vertical (Fy) forces. The sensor was fabricated with a size and shape similar to those of the general flat pedal, and had a 550g weight that allowed smooth pedaling. Its measurement range was ±1000 N for Fx and Fz and ±2000 N for Fy, and its non-linearity, hysteresis, and repeatability were approximately 0.5%. The data were sampled at 1000 Hz using a signal collector. To use the developed sensor, the pedaling efficiency (index of efficiency, IE) and the range of left and right (medio-lateral, ML) forces were measured with two seat heights (low and high). The results of the measurement showed that the IE was higher and the force range in the ML direction was lower with the high position than with the low position. The developed measurement sensor and its application results will be useful in understanding and explaining the complicated pedaling technique, and will enable diverse kinematic analyses of the pedal force on the sagittal plane and the frontal plane.
Keywords: Cycling, Index of effectiveness, Pedal force.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25671972 Problems of Innovation Development of Wireless Data Transfer Branch in the Cellular Market of Kazakhstan
Authors: Yessengeldy Kuanyshpayev
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Now in some countries of the world the cellular market is on the point of saturation, in others - positive dynamics of development kept on. The reasons for it are also different, but there are united by their general susceptibility to innovation changes, if they are really innovative. If to take as an example the cellular market of Kazakhstan it is defined by the low percent of smart phones at consumers, the low population density, undercapacity of the 3G channel, and absence of universal access to the LTE technology that limits dynamical growth of this branch. These moments are aggravated by failures of starting commercial projects by private companies which prevent to be implemented and widely adopted to a new product among consumers. The object of the research is possible integration of wireless and program technologies at which introduction the idea can regenerate in an innovation. The analysis of existing projects in the market and the possible union of the technologies through a prism of theoretical bases of innovative activity shows that efficiency of the company by development and introduction of innovations is possible only thanks to strict observance of all terms and conditions of the innovative process which main term is profit. Despite that fact that on a global scale the innovativeness issue of companies is very popular, there are no researches about possibility of innovative breaks in the field of wireless access to the Internet in the cellular market of Kazakhstan.
Keywords: Cellular market, commercialization, innovation, the effectiveness of company.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20641971 Realization of Autonomous Guidance Service by Integrating Information from NFC and MEMS
Authors: Dawei Cai
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In this paper, we present an autonomous guidance service by combinating the position information from NFC and the orientation information from 6 a 6 axis acceleration and terrestrial magnetism sensor. We developed an algorithm to calculate the device orientation based on the data from acceleration and terrestrial magnetism sensor.With this function, a autonomous guidance service can be provided, according the visitors's position and orientation. This service may be convient for old people or disables or children.
Keywords: NFC, Ubiquitous Computing, Guide Sysem, MEMS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16421970 Mean Square Exponential Synchronization of Stochastic Neutral Type Chaotic Neural Networks with Mixed Delay
Authors: Zixin Liu, Huawei Yang, Fangwei Chen
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This paper studies the mean square exponential synchronization problem of a class of stochastic neutral type chaotic neural networks with mixed delay. On the Basis of Lyapunov stability theory, some sufficient conditions ensuring the mean square exponential synchronization of two identical chaotic neural networks are obtained by using stochastic analysis and inequality technique. These conditions are expressed in the form of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. The feedback controller used in this paper is more general than those used in previous literatures. One simulation example is presented to demonstrate the effectiveness of the derived results.
Keywords: Exponential synchronization, stochastic analysis, chaotic neural networks, neutral type system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15511969 Autonomous Underwater Vehicle (AUV) Dynamics Modeling and Performance Evaluation
Authors: K. M. Tan, A. Anvar, T.F. Lu
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A sophisticated simulator provides a cost-effective measure to carry out preliminary mission testing and diagnostic while reducing potential failures for real life at sea trials. The presented simulation framework covers three key areas: AUV modeling, sensor modeling, and environment modeling. AUV modeling mainly covers the area of AUV dynamics. Sensor modeling deals with physics and mathematical models that govern each sensor installed onto the AUV. Environment model incorporates the hydrostatic, hydrodynamics, and ocean currents that will affect the AUV in a real-time mission. Based on this designed simulation framework, custom scenarios provided by the user can be modeled and its corresponding behaviors can be observed. This paper focuses on the accuracy of the simulated data from AUV model and environmental model derived from a developed AUV test-bed which was jointly upgraded by DSTO and the University of Adelaide. The main contribution of this paper is to experimentally verify the accuracy of the proposed simulation framework.
Keywords: Autonomous Underwater Vehicle (AUV), simulator, framework, robotics, maritime robot, modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47151968 Estimating Reaction Rate Constants with Neural Networks
Authors: Benedek Kovacs, Janos Toth
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Solutions are proposed for the central problem of estimating the reaction rate coefficients in homogeneous kinetics. The first is based upon the fact that the right hand side of a kinetic differential equation is linear in the rate constants, whereas the second one uses the technique of neural networks. This second one is discussed deeply and its advantages, disadvantages and conditions of applicability are analyzed in the mirror of the first one. Numerical analysis carried out on practical models using simulated data, and our programs written in Mathematica.
Keywords: Neural networks, parameter estimation, linear regression, kinetic models, reaction rate coefficients.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19801967 Modeling and Analysis of Concrete Slump Using Hybrid Artificial Neural Networks
Authors: Vinay Chandwani, Vinay Agrawal, Ravindra Nagar
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Artificial Neural Networks (ANN) trained using backpropagation (BP) algorithm are commonly used for modeling material behavior associated with non-linear, complex or unknown interactions among the material constituents. Despite multidisciplinary applications of back-propagation neural networks (BPNN), the BP algorithm possesses the inherent drawback of getting trapped in local minima and slowly converging to a global optimum. The paper present a hybrid artificial neural networks and genetic algorithm approach for modeling slump of ready mix concrete based on its design mix constituents. Genetic algorithms (GA) global search is employed for evolving the initial weights and biases for training of neural networks, which are further fine tuned using the BP algorithm. The study showed that, hybrid ANN-GA model provided consistent predictions in comparison to commonly used BPNN model. In comparison to BPNN model, the hybrid ANNGA model was able to reach the desired performance goal quickly. Apart from the modeling slump of ready mix concrete, the synaptic weights of neural networks were harnessed for analyzing the relative importance of concrete design mix constituents on the slump value. The sand and water constituents of the concrete design mix were found to exhibit maximum importance on the concrete slump value.
Keywords: Artificial neural networks, Genetic algorithms, Back-propagation algorithm, Ready Mix Concrete, Slump value.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28911966 Cooperative CDD Scheme Based On Adaptive Modulation in Wireless Communication System
Authors: Seung-Jun Yu, Hwan-Jun Choi, Hyoung-Kyu Song
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Among spatial diversity scheme, orthogonal space-time block code (OSTBC) and cyclic delay diversity (CDD) have been widely studied for the cooperative wireless relaying system. However, conventional OSTBC and CDD cannot cope with change in the number of relays owing to low throughput or error performance. In this paper, we propose a cooperative cyclic delay diversity (CDD) scheme that use hierarchical modulation at the source and adaptive modulation based on cyclic redundancy check (CRC) code at the relays.
Keywords: Adaptive modulation, Cooperative communication, CDD, OSTBC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17471965 Sparse Networks-Based Speedup Technique for Proteins Betweenness Centrality Computation
Authors: Razvan Bocu, Dr Sabin Tabirca
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The study of proteomics reached unexpected levels of interest, as a direct consequence of its discovered influence over some complex biological phenomena, such as problematic diseases like cancer. This paper presents the latest authors- achievements regarding the analysis of the networks of proteins (interactome networks), by computing more efficiently the betweenness centrality measure. The paper introduces the concept of betweenness centrality, and then describes how betweenness computation can help the interactome net- work analysis. Current sequential implementations for the between- ness computation do not perform satisfactory in terms of execution times. The paper-s main contribution is centered towards introducing a speedup technique for the betweenness computation, based on modified shortest path algorithms for sparse graphs. Three optimized generic algorithms for betweenness computation are described and implemented, and their performance tested against real biological data, which is part of the IntAct dataset.Keywords: Betweenness centrality, interactome networks, protein-protein interactions, sub-communities, sparse networks, speedup tech-nique, IntAct.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14981964 Power Forecasting of Photovoltaic Generation
Authors: S. H. Oudjana, A. Hellal, I. Hadj Mahammed
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Photovoltaic power generation forecasting is an important task in renewable energy power system planning and operating. This paper explores the application of neural networks (NN) to study the design of photovoltaic power generation forecasting systems for one week ahead using weather databases include the global irradiance, and temperature of Ghardaia city (south of Algeria) using a data acquisition system. Simulations were run and the results are discussed showing that neural networks Technique is capable to decrease the photovoltaic power generation forecasting error.Keywords: Photovoltaic Power Forecasting, Regression, Neural Networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37481963 Loop-free Local Path Repair Strategy for Directed Diffusion
Authors: Basma M. Mohammad El-Basioni, Sherine M. Abd El-kader, Hussein S. Eissa
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This paper proposes an implementation for the directed diffusion paradigm aids in studying this paradigm-s operations and evaluates its behavior according to this implementation. The directed diffusion is evaluated with respect to the loss percentage, lifetime, end-to-end delay, and throughput. From these evaluations some suggestions and modifications are proposed to improve the directed diffusion behavior according to this implementation with respect to these metrics. The proposed modifications reflect the effect of local path repair by introducing a technique called Loop-free Local Path Repair (LLPR) which improves the directed diffusion behavior especially with respect to packet loss percentage by about 92.69%. Also LLPR improves the throughput and end-to-end delay by about 55.31% and 14.06% respectively, while the lifetime decreases by about 29.79%.Keywords: Attribute-value based naming scheme, data gathering, data-centric routing, energy-efficiency, locality, wireless sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14181962 Multi-Sensor Target Tracking Using Ensemble Learning
Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana
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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfil requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.
Keywords: Single classifier, machine learning, ensemble learning, multi-sensor target tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5811961 Efficient Solution for a Class of Markov Chain Models of Tandem Queueing Networks
Authors: Chun Wen, Tingzhu Huang
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We present a new numerical method for the computation of the steady-state solution of Markov chains. Theoretical analyses show that the proposed method, with a contraction factor α, converges to the one-dimensional null space of singular linear systems of the form Ax = 0. Numerical experiments are used to illustrate the effectiveness of the proposed method, with applications to a class of interesting models in the domain of tandem queueing networks.
Keywords: Markov chains, tandem queueing networks, convergence, effectiveness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13201960 Hardware Description Language Design of Σ-Δ Fractional-N Phase-Locked Loop for Wireless Applications
Authors: Ahmed El Oualkadi, Abdellah Ait Ouahman
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This paper discusses a systematic design of a Σ-Δ fractional-N Phase-Locked Loop based on HDL behavioral modeling. The proposed design consists in describing the mixed behavior of this PLL architecture starting from the specifications of each building block. The HDL models of critical PLL blocks have been described in VHDL-AMS to predict the different specifications of the PLL. The effect of different noise sources has been efficiently introduced to study the PLL system performances. The obtained results are compared with transistor-level simulations to validate the effectiveness of the proposed models for wireless applications in the frequency range around 2.45 GHz.
Keywords: Phase-locked loop, frequency synthesizer, fractional-N PLL, Σ-Δ modulator, HDL models
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37711959 Survey on Energy Efficient Routing Protocols in Mobile Ad Hoc Networks
Authors: Swapnil Singh, Sanjoy Das
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Mobile Ad-Hoc Network (MANET) is a network without infrastructure dynamically formed by autonomous system of mobile nodes that are connected via wireless links. Mobile nodes communicate with each other on the fly. In this network each node also acts as a router. The battery power and the bandwidth are very scarce resources in this network. The network lifetime and connectivity of nodes depend on battery power. Therefore, energy is a valuable constraint which should be efficiently used. In this paper we survey various energy efficient routing protocols. The energy efficient routing protocols are classified on the basis of approaches they use to minimize the energy consumption. The purpose of this paper is to facilitate the research work and combine the existing solution and to develop a more energy efficient routing mechanism.
Keywords: Delaunay Triangulation, deployment, energy efficiency, MANET.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30281958 Delay-Dependent Stability Analysis for Neural Networks with Distributed Delays
Authors: Qingqing Wang, Shouming Zhong
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This paper deals with the problem of delay-dependent stability for neural networks with distributed delays. Some new sufficient condition are derived by constructing a novel Lyapunov-Krasovskii functional approach. The criteria are formulated in terms of a set of linear matrix inequalities, this is convenient for numerically checking the system stability using the powerful MATLAB LMI Toolbox. Moreover, in order to show the stability condition in this paper gives much less conservative results than those in the literature, numerical examples are considered.
Keywords: Neural networks, Globally asymptotic stability , LMI approach, Distributed delays.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15591957 Fabrication and Characterization of Al2O3 Based Electrical Insulation Coatings Around SiC Fibers
Authors: S. Palaniyappan, P. K. Chennam, M. Trautmann, H. Ahmad, T. Mehner, T. Lampke, G. Wagner
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In structural-health monitoring of fiber reinforced plastics (FRPs), every single inorganic fiber sensor that are integrated into the bulk material requires an electrical insulation around itself, when the surrounding reinforcing fibers are electrically conductive. This results in a more accurate data acquisition only from the sensor fiber without any electrical interventions. For this purpose, thin nano-films of aluminium oxide (Al2O3)-based electrical-insulation coatings have been fabricated around the Silicon Carbide (SiC) single fiber sensors through reactive DC magnetron sputtering technique. The sputtered coatings were amorphous in nature and the thickness of the coatings increased with an increase in the sputter time. Microstructural characterization of the coated fibers performed using scanning electron microscopy (SEM) confirmed a homogeneous circumferential coating with no detectable defects or cracks on the surface. X-ray diffraction (XRD) analyses of the as-sputtered and 2 hours annealed coatings (825 & 1125 ˚C) revealed the amorphous and crystalline phases of Al2O3 respectively. Raman spectroscopic analyses produced no characteristic bands of Al2O3, as the thickness of the films was in the nanometer (nm) range, which is too small to overcome the actual penetration depth of the laser used. In addition, the influence of the insulation coatings on the mechanical properties of the SiC sensor fibers has been analyzed.
Keywords: Al2O3 insulation coating, reactive sputtering, SiC single fiber sensor, single fiber tensile test.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8981956 Analysis of S.P.O Techniques for Prediction of Dynamic Behavior of the Plate
Authors: Byung-kyoo Jung, Weui-bong Jeong
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In most cases, it is considerably difficult to directly measure structural vibration with a lot of sensors because of complex geometry, time and equipment cost. For this reason, this paper deals with the problem of locating sensors on a plate model by four advanced sensor placement optimization (S.P.O) techniques. It also suggests the evaluation index representing the characteristic of orthogonal between each of natural modes. The index value provides the assistance to selecting of proper S.P.O technique and optimal positions for monitoring of dynamic systems without the experiment.Keywords: Genetic algorithm, Modal assurance criterion, Sensor placement optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16691955 Research on Development and Accuracy Improvement of an Explosion Proof Combustible Gas Leak Detector Using an IR Sensor
Authors: Gyoutae Park, Seungho Han, Byungduk Kim, Youngdo Jo, Yongsop Shim, Yeonjae Lee, Sangguk Ahn, Hiesik Kim, Jungil Park
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In this paper, we presented not only development technology of an explosion proof type and portable combustible gas leak detector but also algorithm to improve accuracy for measuring gas concentrations. The presented techniques are to apply the flame-proof enclosure and intrinsic safe explosion proof to an infrared gas leak detector at first in Korea and to improve accuracy using linearization recursion equation and Lagrange interpolation polynomial. Together, we tested sensor characteristics and calibrated suitable input gases and output voltages. Then, we advanced the performances of combustible gaseous detectors through reflecting demands of gas safety management fields. To check performances of two company's detectors, we achieved the measurement tests with eight standard gases made by Korea Gas Safety Corporation. We demonstrated our instruments better in detecting accuracy other than detectors through experimental results.
Keywords: Gas sensor, leak, detector, accuracy, interpolation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13881954 Taxonomy of Threats and Vulnerabilities in Smart Grid Networks
Authors: Faisal Al Yahmadi, Muhammad R. Ahmed
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Electric power is a fundamental necessity in the 21st century. Consequently, any break in electric power is probably going to affect the general activity. To make the power supply smooth and efficient, a smart grid network is introduced which uses communication technology. In any communication network, security is essential. It has been observed from several recent incidents that adversary causes an interruption to the operation of networks. In order to resolve the issues, it is vital to understand the threats and vulnerabilities associated with the smart grid networks. In this paper, we have investigated the threats and vulnerabilities in Smart Grid Networks (SGN) and the few solutions in the literature. Proposed solutions showed developments in electricity theft countermeasures, Denial of services attacks (DoS) and malicious injection attacks detection model, as well as malicious nodes detection using watchdog like techniques and other solutions.
Keywords: Smart grid network, security, threats, vulnerabilities.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5741953 Prediction of Bath Temperature Using Neural Networks
Authors: H. Meradi, S. Bouhouche, M. Lahreche
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In this work, we consider an application of neural networks in LD converter. Application of this approach assumes a reliable prediction of steel temperature and reduces a reblow ratio in steel work. It has been applied a conventional model to charge calculation, the obtained results by this technique are not always good, this is due to the process complexity. Difficulties are mainly generated by the noisy measurement and the process non linearities. Artificial Neural Networks (ANNs) have become a powerful tool for these complex applications. It is used a backpropagation algorithm to learn the neural nets. (ANNs) is used to predict the steel bath temperature in oxygen converter process for the end condition. This model has 11 inputs process variables and one output. The model was tested in steel work, the obtained results by neural approach are better than the conventional model.
Keywords: LD converter, bath temperature, neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18281952 New PTH Moment Stable Criteria of Stochastic Neural Networks
Authors: Zixin Liu, Huawei Yang, Fangwei Chen
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In this paper, the issue of pth moment stability of a class of stochastic neural networks with mixed delays is investigated. By establishing two integro-differential inequalities, some new sufficient conditions ensuring pth moment exponential stability are obtained. Compared with some previous publications, our results generalize some earlier works reported in the literature, and remove some strict constraints of time delays and kernel functions. Two numerical examples are presented to illustrate the validity of the main results.
Keywords: Neural networks, stochastic, PTH moment stable, time varying delays, distributed delays.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14581951 Exponential Stability and Periodicity of a Class of Cellular Neural Networks with Time-Varying Delays
Authors: Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye
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The problem of exponential stability and periodicity for a class of cellular neural networks (DCNNs) with time-varying delays is investigated. By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions for exponential stability and periodicity are derived via the methods of variation parameters and inequality techniques. These conditions are represented by some blocks of the interconnection matrices. Compared with some previous methods, the method used in this paper does not resort to any Lyapunov function, and the results derived in this paper improve and generalize some earlier criteria established in the literature cited therein. Two examples are discussed to illustrate the main results.
Keywords: Cellular neural networks, exponential stability, time varying delays, partitioned matrices, periodic solution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1513