Search results for: Radial Distribution network
4334 Monitoring and Prediction of Intra-Crosstalk in All-Optical Network
Authors: Ahmed Jedidi, Mesfer Mohammed Alshamrani, Alwi Mohammad A. Bamhdi
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Optical performance monitoring and optical network management are essential in building a reliable, high-capacity, and service-differentiation enabled all-optical network. One of the serious problems in this network is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole AON may be more nefarious than a single point of crosstalk. As results, we note a huge degradation of the Quality of Service (QoS) in our network. For that, it is necessary to identify and monitor the impairments in whole network. In this way, this paper presents new system to identify and monitor crosstalk in AONs in real-time fashion. particular, it proposes a new technique to manage intra-crosstalk in objective to relax QoS of the network.Keywords: All-optical networks, optical crosstalk, optical cross-connect, crosstalk, monitoring crosstalk.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17084333 An ACO Based Algorithm for Distribution Networks Including Dispersed Generations
Authors: B. Bahmani Firouzi, T. Niknam, M. Nayeripour
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With Power system movement toward restructuring along with factors such as life environment pollution, problems of transmission expansion and with advancement in construction technology of small generation units, it is expected that small units like wind turbines, fuel cells, photovoltaic, ... that most of the time connect to the distribution networks play a very essential role in electric power industry. With increase in developing usage of small generation units, management of distribution networks should be reviewed. The target of this paper is to present a new method for optimal management of active and reactive power in distribution networks with regard to costs pertaining to various types of dispersed generations, capacitors and cost of electric energy achieved from network. In other words, in this method it-s endeavored to select optimal sources of active and reactive power generation and controlling equipments such as dispersed generations, capacitors, under load tapchanger transformers and substations in a way that firstly costs in relation to them are minimized and secondly technical and physical constraints are regarded. Because the optimal management of distribution networks is an optimization problem with continuous and discrete variables, the new evolutionary method based on Ant Colony Algorithm has been applied. The simulation results of the method tested on two cases containing 23 and 34 buses exist and will be shown at later sections.
Keywords: Distributed Generation, Optimal Operation Management of distribution networks, Ant Colony Optimization(ACO).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16944332 Domain-based Key Management Scheme for Active Network
Authors: Jong-Whoi Shin, Soon-Tai Park, Chong-Sun Hwang
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Active network was developed to solve the problem of the current sharing-based network–difficulty in applying new technology, service or standard, and duplicated operation at several protocol layers. Active network can transport the packet loaded with the executable codes, which enables to change the state of the network node. However, if the network node is placed in the sharing-based network, security and safety issues should be resolved. To satisfy this requirement, various security aspects are required such as authentication, authorization, confidentiality and integrity. Among these security components, the core factor is the encryption key. As a result, this study is designed to propose the scheme that manages the encryption key, which is used to provide security of the comprehensive active directory, based on the domain.Keywords: Active Network, Domain-based Key Management, Security Components.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16644331 Application of Functional Network to Solving Classification Problems
Authors: Yong-Quan Zhou, Deng-Xu He, Zheng Nong
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In this paper two models using a functional network were employed to solving classification problem. Functional networks are generalized neural networks, which permit the specification of their initial topology using knowledge about the problem at hand. In this case, and after analyzing the available data and their relations, we systematically discuss a numerical analysis method used for functional network, and apply two functional network models to solving XOR problem. The XOR problem that cannot be solved with two-layered neural network can be solved by two-layered functional network, which reveals a potent computational power of functional networks, and the performance of the proposed model was validated using classification problems.Keywords: Functional network, neural network, XOR problem, classification, numerical analysis method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12994330 A Novel Technique for Ferroresonance Identification in Distribution Networks
Authors: G. Mokryani, M. R. Haghifam, J. Esmaeilpoor
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Happening of Ferroresonance phenomenon is one of the reasons of consuming and ruining transformers, so recognition of Ferroresonance phenomenon has a special importance. A novel method for classification of Ferroresonance presented in this paper. Using this method Ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Competitive Neural Network used for classification. Ferroresonance data and other transients was obtained by simulation using EMTP program. Using Daubechies wavelet transform signals has been decomposed till six levels. The energy of six detailed signals that obtained by wavelet transform are used for training and trailing Competitive Neural Network. Results show that the proposed procedure is efficient in identifying Ferroresonance from other events.
Keywords: Competitive Neural Network, Ferroresonance, EMTP program, Wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14154329 Optimal Allocation of PHEV Parking Lots to Minimize Distribution System Losses
Authors: Mahmud Fotuhi-Firuzabad, Ali Abbaspour, Mohsen Mazidi, Mohamamd Rastegar
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To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.Keywords: Plug-in Hybrid Electric Vehicle (PHEV), PHEV parking lot, V2G.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22874328 Spreading Dynamics of a Viral Infection in a Complex Network
Authors: Khemanand Moheeput, Smita S. D. Goorah, Satish K. Ramchurn
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We report a computational study of the spreading dynamics of a viral infection in a complex (scale-free) network. The final epidemic size distribution (FESD) was found to be unimodal or bimodal depending on the value of the basic reproductive number R0 . The FESDs occurred on time-scales long enough for intermediate-time epidemic size distributions (IESDs) to be important for control measures. The usefulness of R0 for deciding on the timeliness and intensity of control measures was found to be limited by the multimodal nature of the IESDs and by its inability to inform on the speed at which the infection spreads through the population. A reduction of the transmission probability at the hubs of the scale-free network decreased the occurrence of the larger-sized epidemic events of the multimodal distributions. For effective epidemic control, an early reduction in transmission at the index cell and its neighbors was essential.
Keywords: Basic reproductive number, epidemic control, scalefree network, viral infection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17114327 Avoiding Catastrophic Forgetting by a Dual-Network Memory Model Using a Chaotic Neural Network
Authors: Motonobu Hattori
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In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.
Keywords: catastrophic forgetting, chaotic neural network, complementary learning systems, dual-network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20844326 Implementation of an Associative Memory Using a Restricted Hopfield Network
Authors: Tet H. Yeap
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An analog restricted Hopfield Network is presented in this paper. It consists of two layers of nodes, visible and hidden nodes, connected by directional weighted paths forming a bipartite graph with no intralayer connection. An energy or Lyapunov function was derived to show that the proposed network will converge to stable states. By introducing hidden nodes, the proposed network can be trained to store patterns and has increased memory capacity. Training to be an associative memory, simulation results show that the associative memory performs better than a classical Hopfield network by being able to perform better memory recall when the input is noisy.Keywords: Associative memory, Hopfield network, Lyapunov function, Restricted Hopfield network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4744325 RBF- based Meshless Method for Free Vibration Analysis of Laminated Composite Plates
Authors: Jeeoot Singh, Sandeep Singh, K. K. Shukla
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The governing differential equations of laminated plate utilizing trigonometric shear deformation theory are derived using energy approach. The governing differential equations discretized by different radial basis functions are used to predict the free vibration behavior of symmetric laminated composite plates. Effect of orthotropy and span to thickness ratio on frequency parameter of simply supported laminated plate is presented. Numerical results show the accuracy and good convergence of radial basis functions.Keywords: Composite plates, Meshfree method, free vibration, Shear deformation, RBFs
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21154324 Adaptive Fuzzy Routing in Opportunistic Network (AFRON)
Authors: Payam Nabhani, Sima Radmanesh
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Opportunistic network is a kind of Delay Tolerant Networks (DTN) where the nodes in this network come into contact with each other opportunistically and communicate wirelessly and, an end-to-end path between source and destination may have never existed, and disconnection and reconnection is common in the network. In such a network, because of the nature of opportunistic network, perhaps there is no a complete path from source to destination for most of the time and even if there is a path; the path can be very unstable and may change or break quickly. Therefore, routing is one of the main challenges in this environment and, in order to make communication possible in an opportunistic network, the intermediate nodes have to play important role in the opportunistic routing protocols. In this paper we proposed an Adaptive Fuzzy Routing in opportunistic network (AFRON). This protocol is using the simple parameters as input parameters to find the path to the destination node. Using Message Transmission Count, Message Size and Time To Live parameters as input fuzzy to increase delivery ratio and decrease the buffer consumption in the all nodes of network.
Keywords: Opportunistic Routing, Fuzzy Routing, Opportunistic Network, Message Routing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15274323 Neural Network Based Determination of Splice Junctions by ROC Analysis
Authors: S. Makal, L. Ozyilmaz, S. Palavaroglu
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Gene, principal unit of inheritance, is an ordered sequence of nucleotides. The genes of eukaryotic organisms include alternating segments of exons and introns. The region of Deoxyribonucleic acid (DNA) within a gene containing instructions for coding a protein is called exon. On the other hand, non-coding regions called introns are another part of DNA that regulates gene expression by removing from the messenger Ribonucleic acid (RNA) in a splicing process. This paper proposes to determine splice junctions that are exon-intron boundaries by analyzing DNA sequences. A splice junction can be either exon-intron (EI) or intron exon (IE). Because of the popularity and compatibility of the artificial neural network (ANN) in genetic fields; various ANN models are applied in this research. Multi-layer Perceptron (MLP), Radial Basis Function (RBF) and Generalized Regression Neural Networks (GRNN) are used to analyze and detect the splice junctions of gene sequences. 10-fold cross validation is used to demonstrate the accuracy of networks. The real performances of these networks are found by applying Receiver Operating Characteristic (ROC) analysis.Keywords: Gene, neural networks, ROC analysis, splice junctions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16494322 Landslide and Debris Flow Characteristics during Extreme Rainfall in Taiwan
Authors: C. Y. Chen
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As the global climate changes, the threat from landslides and debris flows increases. Learning how a watershed initiates landslides under abnormal rainfall conditions and predicting landslide magnitude and frequency distribution is thus important. Landslides show a power-law distribution in the frequency-area distribution. The distribution curve shows an exponent gradient 1.0 in the Sandpile model test. Will the landslide frequency-area statistics show a distribution similar to the Sandpile model under extreme rainfall conditions? The purpose of the study is to identify the extreme rainfall-induced landslide frequency-area distribution in the Laonong River Basin in southern Taiwan. Results of the analysis show that a lower gradient of landslide frequency-area distribution could be attributed to the transportation and deposition of debris flow areas that are included in the landslide area.Keywords: Landslide, power-law distribution, GIS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19324321 Role of Acoustic Pressure on the Dynamics of Moving Single-Bubble Sonoluminescence
Authors: Reza Rezaei-Nasirabad, Zeinab Galavani, Rasoul Sadighi-Bonabi, Mohammad Asgarian
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Role of acoustic driving pressure on the translational-radial dynamics of a moving single bubble sonoluminescence (m-SBSL) has been numerically investigated. The results indicate that increase in the amplitude of the driving pressure leads to increase in the bubble peak temperature. The length and the shape of the trajectory of the bubble depends on the acoustic pressure and because of the spatially dependence of the radial dynamics of the moving bubble, its peak temperature varies during the acoustical pulses. The results are in good agreement with the experimental reports on m-SBSL.Keywords: Bubble dynamics, Equation of the gas state, Hydrodynamic force, Moving sonoluminescence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17654320 Simulation Study for Performance Comparison of Routing Protocols in Mobile Adhoc Network
Authors: Ahmad Anzaar, Husain Shahnawaz, Chand Mukesh, S. C. Gupta, R. Gowri, H. L. Mandoria
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Due to insufficient frequency band and tremendous growth of the mobile users, complex computation is needed for the use of resources. Long distance communication began with the introduction of telegraphs and simple coded pulses, which were used to transmit short messages. Since then numerous advances have rendered reliable transfer of information both easier and quicker. Wireless network refers to any type of computer network that is wireless, and is commonly associated with a telecommunications network whose interconnections between nodes is implemented without the use of wires. Wireless network can be broadly categorized in infrastructure network and infrastructure less network. Infrastructure network is one in which we have a base station to serve the mobile users and in the infrastructure less network is one in which no infrastructure is available to serve the mobile users this kind of networks are also known as mobile Adhoc networks. In this paper we have simulated the result for different scenarios with protocols like AODV and DSR; we simulated the result for throughput, delay and receiving traffic in the given scenario.
Keywords: Adhoc network, AODV, DSR. mobility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20944319 An Agent-based Model for Analyzing Interaction of Two Stable Social Networks
Authors: Masatora Daito, Hisashi Kojima
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In this research, the authors analyze network stability using agent-based simulation. Firstly, the authors focus on analyzing large networks (eight agents) by connecting different two stable small social networks (A small stable network is consisted on four agents.). Secondly, the authors analyze the network (eight agents) shape which is added one agent to a stable network (seven agents). Thirdly, the authors analyze interpersonal comparison of utility. The “star-network "was not found on the result of interaction among stable two small networks. On the other hand, “decentralized network" was formed from several combination. In case of added one agent to a stable network (seven agents), if the value of “c"(maintenance cost of per a link) was larger, the number of patterns of stable network was also larger. In this case, the authors identified the characteristics of a large stable network. The authors discovered the cases of decreasing personal utility under condition increasing total utility.Keywords: Social Network, Symmetric Situation, Network Stability, Agent-Based Modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15224318 The Empirical Survey on the Effect of Using Media in Explosive Forming of Tubular Shells
Authors: V. Hadavi, J. Zamani, R. Hosseini
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The special and unique advantages of explosive forming, has developed its use in different industries. Considering the important influence of improving the current explosive forming techniques on increasing the efficiency and control over the explosive forming procedure, the effects of air and water as the energy-conveying medium, and also their differences will be illustrated in this paper. Hence, a large number of explosive forming tests have been conducted on two sizes of thin walled cylindrical shells by using air and water as the working medium. Comparative diagrams of the maximum radial deflection of work-pieces of the same size, as a function of the scaled distance, show that for the points with the same values of scaled distance, the maximum radial deformation caused by the under water explosive loading is 4 to 5 times more than the deflection of the shells under explosive forming, while using air. Results of this experimental research have also been compared with other studies which show that using water as the energy conveying media increases the efficiency up to 4.8 times. The effect of the media on failure modes of the shells, and the necking mechanism of the walls of the specimens, while being explosively loaded, are also discussed in this issue. Measuring the tested specimens shows that, the increase in the internal volume has been accompanied by necking of the walls, which finally results in the radial rupture of the structure.Keywords: Explosive Forming, Energy Conveying Medium, Tubular Shell
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13374317 Techniques for Reliability Evaluation in Distribution System Planning
Authors: T. Lantharthong, N. Phanthuna
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This paper presents reliability evaluation techniques which are applied in distribution system planning studies and operation. Reliability of distribution systems is an important issue in power engineering for both utilities and customers. Reliability is a key issue in the design and operation of electric power distribution systems and load. Reliability evaluation of distribution systems has been the subject of many recent papers and the modeling and evaluation techniques have improved considerably.Keywords: Reliability Evaluation, Optimization Technique, Reliability Indices
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 45524316 A Research on DC Voltage Offsets Generated by PWM-Controlled Inverters
Authors: Marios N. Moschakis
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The increasing penetration of Distributed Generation and storage connected to the distribution network via PWM converters increases the possibility of a DC-component (offset) in voltage or current flowing into the grid. This occurs when even harmonics are present in the network voltage. DC-components can affect the operation and safety of several grid components. Therefore, an investigation of the way they are produced is important in order to take appropriate measures for their elimination. Further research on DC-components that appear on output voltage of converters is performed for different parameters of PWM technique and characteristics of even harmonics.
Keywords: Asymmetric even harmonics, DC-offsets, distributed generation, electric machine drive systems, power quality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36754315 Reliability Improvement with Optimal Placement of Distributed Generation in Distribution System
Authors: N. Rugthaicharoencheep, T. Langtharthong
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This paper presents the optimal placement and sizing of distributed generation (DG) in a distribution system. The problem is to reliability improvement of distribution system with distributed generations. The technique employed to solve the minimization problem is based on a developed Tabu search algorithm and reliability worth analysis. The developed methodology is tested with a distribution system of Roy Billinton Test System (RBTS) bus 2. It can be seen from the case study that distributed generation can reduce the customer interruption cost and therefore improve the reliability of the system. It is expected that our proposed method will be utilized effectively for distribution system operator.
Keywords: Distributed generation Optimization technique Reliability improvement, Distribution system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30024314 Using Mixed Methods in Studying Classroom Social Network Dynamics
Authors: Nashrawan N. Taha, Andrew M. Cox
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In a multi-cultural learning context, where ties are weak and dynamic, combining qualitative with quantitative research methods may be more effective. Such a combination may also allow us to answer different types of question, such as about people’s perception of the network. In this study the use of observation, interviews and photos were explored as ways of enhancing data from social network questionnaires. Integrating all of these methods was found to enhance the quality of data collected and its accuracy, also providing a richer story of the network dynamics and the factors that shaped these changes over time.
Keywords: Mixed Methods, Social Network Analysis, multi-cultural learning, Social Network Dynamics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17954313 VoIP Source Model based on the Hyperexponential Distribution
Authors: Arkadiusz Biernacki
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In this paper we present a statistical analysis of Voice over IP (VoIP) packet streams produced by the G.711 voice coder with voice activity detection (VAD). During telephone conversation, depending whether the interlocutor speaks (ON) or remains silent (OFF), packets are produced or not by a voice coder. As index of dispersion for both ON and OFF times distribution was greater than one, we used hyperexponential distribution for approximation of streams duration. For each stage of the hyperexponential distribution, we tested goodness of our fits using graphical methods, we calculated estimation errors, and performed Kolmogorov-Smirnov test. Obtained results showed that the precise VoIP source model can be based on the five-state Markov process.Keywords: VoIP source modelling, distribution approximation, hyperexponential distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16994312 Dual-Network Memory Model for Temporal Sequences
Authors: Motonobu Hattori, Rina Suzuki
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In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudopatterns. Because temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.
Keywords: Catastrophic forgetting, dual-network, temporal sequences.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14164311 Chilean Wines Classification based only on Aroma Information
Authors: Nicolás H. Beltrán, Manuel A. Duarte-Mermoud, Víctor A. Soto, Sebastián A. Salah, and Matías A. Bustos
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Results of Chilean wine classification based on the information provided by an electronic nose are reported in this paper. The classification scheme consists of two parts; in the first stage, Principal Component Analysis is used as feature extraction method to reduce the dimensionality of the original information. Then, Radial Basis Functions Neural Networks is used as pattern recognition technique to perform the classification. The objective of this study is to classify different Cabernet Sauvignon, Merlot and Carménère wine samples from different years, valleys and vineyards of Chile.Keywords: Feature extraction techniques, Pattern recognitiontechniques, Principal component analysis, Radial basis functionsneural networks, Wine classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15394310 Fault Detection of Pipeline in Water Distribution Network System
Authors: Shin Je Lee, Go Bong Choi, Jeong Cheol Seo, Jong Min Lee, Gibaek Lee
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Water pipe network is installed underground and once equipped, it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate or pressure. The transient model describing water flow in pipelines is presented and simulated using MATLAB. The fault situations such as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the better fault detection performance.Keywords: fault detection, water pipeline model, fast Fourier transform, discrete wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23304309 Simulation Study of Radial Heat and Mass Transfer Inside a Fixed Bed Catalytic Reactor
Authors: K. Vakhshouri, M.M. Y. Motamed Hashemi
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A rigorous two-dimensional model is developed for simulating the operation of a less-investigated type steam reformer having a considerably lower operating Reynolds number, higher tube diameter, and non-availability of extra steam in the feed compared with conventional steam reformers. Simulation results show that reasonable predictions can only be achieved when certain correlations for wall to fluid heat transfer equations are applied. Due to severe operating conditions, in all cases, strong radial temperature gradients inside the reformer tubes have been found. Furthermore, the results show how a certain catalyst loading profile will affect the operation of the reformer.
Keywords: Steam reforming, direct reduction, heat transfer, two-dimensional model, simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36334308 Derivation of Monotone Likelihood Ratio Using Two Sided Uniformly Normal Distribution Techniques
Authors: D. A. Farinde
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In this paper, two-sided uniformly normal distribution techniques were used in the derivation of monotone likelihood ratio. The approach mainly employed the parameters of the distribution for a class of all size a. The derivation technique is fast, direct and less burdensome when compared to some existing methods.
Keywords: Neyman-Pearson Lemma, Normal distribution
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31934307 Improving RBF Networks Classification Performance by using K-Harmonic Means
Authors: Z. Zainuddin, W. K. Lye
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In this paper, a clustering algorithm named KHarmonic means (KHM) was employed in the training of Radial Basis Function Networks (RBFNs). KHM organized the data in clusters and determined the centres of the basis function. The popular clustering algorithms, namely K-means (KM) and Fuzzy c-means (FCM), are highly dependent on the initial identification of elements that represent the cluster well. In KHM, the problem can be avoided. This leads to improvement in the classification performance when compared to other clustering algorithms. A comparison of the classification accuracy was performed between KM, FCM and KHM. The classification performance is based on the benchmark data sets: Iris Plant, Diabetes and Breast Cancer. RBFN training with the KHM algorithm shows better accuracy in classification problem.Keywords: Neural networks, Radial basis functions, Clusteringmethod, K-harmonic means.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18414306 Optimizing the Probabilistic Neural Network Training Algorithm for Multi-Class Identification
Authors: Abdelhadi Lotfi, Abdelkader Benyettou
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In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.
Keywords: Classification, probabilistic neural networks, network optimization, pattern recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12074305 Low-Latency and Low-Overhead Path Planning for In-band Network-Wide Telemetry
Authors: Penghui Zhang, Hua Zhang, Jun-Bo Wang, Cheng Zeng, Zijian Cao
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With the development of software-defined networks and programmable data planes, in-band network telemetry (INT) has become an emerging technology in communications because it can get accurate and real-time network information. However, due to the expansion of the network scale, existing telemetry systems, to the best of the authors’ knowledge, have difficulty in meeting the common requirements of low overhead, low latency and full coverage for traffic measurement. This paper proposes a network-wide telemetry system with a low-latency low-overhead path planning (INT-LLPP). This paper builds a mathematical model to analyze the telemetry overhead and latency of INT systems. Then, we adopt a greedy-based path planning algorithm to reduce the overhead and latency of the network telemetry with the full network coverage. The simulation results show that network-wide telemetry is achieved and the telemetry overhead can be reduced significantly compared with existing INT systems. INT-LLPP can control the system latency to get real-time network information.
Keywords: Network telemetry, network monitoring, path planning, low latency.
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