Search results for: nextgeneration wireless networks
440 Synthesis and Simulation of Enhanced Buffer Router vs. Virtual Channel Router in NOC ON Cadence
Authors: Bhavana Prakash Shrivastava, Kavita Khare
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This paper presents a synthesis and simulation of proposed enhanced buffer. The design provides advantages of both buffer and bufferless network for that two cross bar switches are used. The concept of virtual channel (VC) is eliminated from the previous design by using an efficient flow-control scheme that uses the storage already present in pipelined channels in place of explicit input VCBs. This can be addressed by providing enhanced buffers on the bufferless link and creating two virtual networks. With this approach, VCBs act as distributed FIFO buffers. Without VCBs or VCs, deadlock prevention is achieved by duplicating physical channels. An enhanced buffer provides a function of hand shaking by providing a ready valid handshake signal and two bit storage. Through this design the power is reduced to 15.65% and delay is reduced to 97.88% with respect to virtual channel router.
Keywords: Enhanced buffer, Gate delay, NOC, VCs, VCB.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1738439 Attention Multiple Instance Learning for Cancer Tissue Classification in Digital Histopathology Images
Authors: Afaf Alharbi, Qianni Zhang
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The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper presents a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network-based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation on an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.
Keywords: Attention Multiple Instance Learning, Multiple Instance Learning, transfer learning, histopathological slides, cancer tissue classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 171438 Design and Implementation of a Neural Network for Real-Time Object Tracking
Authors: Javed Ahmed, M. N. Jafri, J. Ahmad, Muhammad I. Khan
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Real-time object tracking is a problem which involves extraction of critical information from complex and uncertain imagedata. In this paper, we present a comprehensive methodology to design an artificial neural network (ANN) for a real-time object tracking application. The object, which is tracked for the purpose of demonstration, is a specific airplane. However, the proposed ANN can be trained to track any other object of interest. The ANN has been simulated and tested on the training and testing datasets, as well as on a real-time streaming video. The tracking error is analyzed with post-regression analysis tool, which finds the correlation among the calculated coordinates and the correct coordinates of the object in the image. The encouraging results from the computer simulation and analysis show that the proposed ANN architecture is a good candidate solution to a real-time object tracking problem.
Keywords: Image processing, machine vision, neural networks, real-time object tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3498437 Compensation of Power Quality Disturbances Using DVR
Authors: R. Rezaeipour
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One of the key aspects of power quality improvement in power system is the mitigation of voltage sags/swells and flicker. Custom power devices have been known as the best tools for voltage disturbances mitigation as well as reactive power compensation. Dynamic Voltage Restorer (DVR) which is the most efficient and effective modern custom power device can provide the most commercial solution to solve several problems of power quality in distribution networks. This paper deals with analysis and simulation technique of DVR based on instantaneous power theory which is a quick control to detect signals. The main purpose of this work is to remove three important disturbances including voltage sags/swells and flicker. Simulation of the proposed method was carried out on two sample systems by using Matlab software environment and the results of simulation show that the proposed method is able to provide desirable power quality in the presence of wide range of disturbances.Keywords: DVR, Power quality, Voltage sags, Voltage swells, Flicker.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1994436 Modeling Peer-to-Peer Networks with Interest-Based Clusters
Authors: Bertalan Forstner, Dr. Hassan Charaf
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In the world of Peer-to-Peer (P2P) networking different protocols have been developed to make the resource sharing or information retrieval more efficient. The SemPeer protocol is a new layer on Gnutella that transforms the connections of the nodes based on semantic information to make information retrieval more efficient. However, this transformation causes high clustering in the network that decreases the number of nodes reached, therefore the probability of finding a document is also decreased. In this paper we describe a mathematical model for the Gnutella and SemPeer protocols that captures clustering-related issues, followed by a proposition to modify the SemPeer protocol to achieve moderate clustering. This modification is a sort of link management for the individual nodes that allows the SemPeer protocol to be more efficient, because the probability of a successful query in the P2P network is reasonably increased. For the validation of the models, we evaluated a series of simulations that supported our results.Keywords: Peer-to-Peer, model, performance, networkmanagement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1297435 A Comparison of Image Data Representations for Local Stereo Matching
Authors: André Smith, Amr Abdel-Dayem
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The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.Keywords: Colour data, local stereo matching, stereo correspondence, disparity map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 904434 A Practical Scheme for Transmission Loss Allocation to Generators and Loads in Restructured Power Systems
Authors: M.R. Ebrahimi, M. Ehsan
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This paper presents a practical scheme that can be used for allocating the transmission loss to generators and loads. In this scheme first the share of a generator or load on the current through a branch is determined using Z-bus modified matrix. Then the current components are decomposed and the branch loss allocation is obtained. A motivation of proposed scheme is to improve the results of Z-bus method and to reach more fair allocation. The proposed scheme has been implemented and tested on several networks. To achieve practical and applicable results, the proposed scheme is simulated and compared on the transmission network (400kv) of Khorasan region in Iran and the 14-bus standard IEEE network. The results show that the proposed scheme is comprehensive and fair to allocating the energy losses of a power market to its participants.
Keywords: Transmission Loss, Loss Allocation, Z-bus modifiedmatrix, current Components Decomposition and Restructured PowerSystems
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1496433 Optimized Delay Constrained QoS Routing
Authors: P. S. Prakash, S. Selvan
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QoS Routing aims to find paths between senders and receivers satisfying the QoS requirements of the application which efficiently using the network resources and underlying routing algorithm to be able to find low-cost paths that satisfy given QoS constraints. The problem of finding least-cost routing is known to be NP-hard or complete and some algorithms have been proposed to find a near optimal solution. But these heuristics or algorithms either impose relationships among the link metrics to reduce the complexity of the problem which may limit the general applicability of the heuristic, or are too costly in terms of execution time to be applicable to large networks. In this paper, we concentrate an algorithm that finds a near-optimal solution fast and we named this algorithm as optimized Delay Constrained Routing (ODCR), which uses an adaptive path weight function together with an additional constraint imposed on the path cost, to restrict search space and hence ODCR finds near optimal solution in much quicker time.Keywords: QoS, Delay, Routing, Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1205432 Optimization of Distributed Processors for Power System: Kalman Filters using Petri Net
Authors: Anant Oonsivilai, Kenedy A. Greyson
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The growth and interconnection of power networks in many regions has invited complicated techniques for energy management services (EMS). State estimation techniques become a powerful tool in power system control centers, and that more information is required to achieve the objective of EMS. For the online state estimator, assuming the continuous time is equidistantly sampled with period Δt, processing events must be finished within this period. Advantage of Kalman Filtering (KF) algorithm in using system information to improve the estimation precision is utilized. Computational power is a major issue responsible for the achievement of the objective, i.e. estimators- solution at a small sampled period. This paper presents the optimum utilization of processors in a state estimator based on KF. The model used is presented using Petri net (PN) theory.
Keywords: Kalman filters, model, Petri Net, power system, sequential State estimator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1345431 A Reasoning Method of Cyber-Attack Attribution Based on Threat Intelligence
Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei
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With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.
Keywords: Reasoning, Bayesian networks, cyber-attack attribution, kill chain, threat intelligence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2659430 A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments
Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda
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In the context of the handwriting recognition, we propose an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods. The Distribution parameters, the centered moments of the different projections of the different segments, the centered moments of the word image coding according to the directions of Freeman, and the Barr features applied binary image of the word and on its different segments. The classification is achieved by a multi layers perceptron. A detailed experiment is carried and satisfactory recognition results are reported.Keywords: Handwritten word recognition, neural networks, image processing, pattern recognition, features extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1893429 OCR For Printed Urdu Script Using Feed Forward Neural Network
Authors: Inam Shamsher, Zaheer Ahmad, Jehanzeb Khan Orakzai, Awais Adnan
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This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. In the proposed system individual characters are recognized using our own proposed method/ algorithms. The feature detection methods are simple and robust. Supervised learning is used to train the feed forward neural network. A prototype of the system has been tested on printed Urdu characters and currently achieves 98.3% character level accuracy on average .Although the system is script/ language independent but we have designed it for Urdu characters only.Keywords: Algorithm, Feed Forward Neural Networks, Supervised learning, Pattern Matching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3019428 MITAutomatic ECG Beat Tachycardia Detection Using Artificial Neural Network
Authors: R. Amandi, A. Shahbazi, A. Mohebi, M. Bazargan, Y. Jaberi, P. Emadi, A. Valizade
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The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.Keywords: Fuzzy Logic, Probabilistic Neural Network, Tachycardia, Wavelet Transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2274427 RANFIS : Rough Adaptive Neuro-Fuzzy Inference System
Authors: Sandeep Chandana, Rene V. Mayorga
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The paper presents a new hybridization methodology involving Neural, Fuzzy and Rough Computing. A Rough Sets based approximation technique has been proposed based on a certain Neuro – Fuzzy architecture. A New Rough Neuron composition consisting of a combination of a Lower Bound neuron and a Boundary neuron has also been described. The conventional convergence of error in back propagation has been given away for a new framework based on 'Output Excitation Factor' and an inverse input transfer function. The paper also presents a brief comparison of performances, of the existing Rough Neural Networks and ANFIS architecture against the proposed methodology. It can be observed that the rough approximation based neuro-fuzzy architecture is superior to its counterparts.
Keywords: Boundary neuron, neuro-fuzzy, output excitation factor, RANFIS, rough approximation, rough neural computing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1696426 Elicitation of Requirements for a Knowledge Management Concept in Decentralized Production Planning
Authors: S. Minhas, C. Juzek, U. Berger
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The planning in manufacturing system is becoming complicated day by day due to the expanding networks and shortage of skilled people to manage change. Consequently, faster lead time and rising demands for eco-efficient evaluation of manufacturing products and processes need exploitation of new and intelligent knowledge management concepts for manufacturing planning. This paper highlights motivation for incorporation of new features in the manufacturing planning system. Furthermore, it elaborates requirements for the development of intelligent knowledge management concept to support planning related decisions. Afterwards, the derived concept is presented in this paper considering two case studies. The first case study is concerned with the automotive ramp-up planning. The second case study specifies requirements for knowledge management system to support decisions in eco-efficient evaluation of manufacturing products and processes
Keywords: Ramp-up, Environmental impact, Knowledge management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1844425 Heuristic Continuous-time Associative Memories
Authors: Truong Quang Dang Khoa, Masahiro Nakagawa
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In this paper, a novel associative memory model will be proposed and applied to memory retrievals based on the conventional continuous time model. The conventional model presents memory capacity is very low and retrieval process easily converges to an equilibrium state which is very different from the stored patterns. Genetic Algorithms is well-known with the capability of global optimal search escaping local optimum on progress to reach a global optimum. Based on the well-known idea of Genetic Algorithms, this work proposes a heuristic rule to make a mutation when the state of the network is trapped in a spurious memory. The proposal heuristic associative memory show the stored capacity does not depend on the number of stored patterns and the retrieval ability is up to ~ 1.Keywords: Artificial Intelligent, Soft Computing, NeuralNetworks, Genetic Algorithms, Hopfield Neural Networks, andAssociative Memories.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1390424 A Discrete-Event-Simulation Approach for Logistic Systems with Real Time Resource Routing and VR Integration
Authors: Gerrit Alves, Jürgen Roßmann, Roland Wischnewski
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Today, transport and logistic systems are often tightly integrated in the production. Lean production and just-in-time delivering create multiple constraints that have to be fulfilled. As transport networks often have evolved over time they are very expensive to change. This paper describes a discrete-event-simulation system which simulates transportation models using real time resource routing and collision avoidance. It allows for the specification of own control algorithms and validation of new strategies. The simulation is integrated into a virtual reality (VR) environment and can be displayed in 3-D to show the progress. Simulation elements can be selected through VR metaphors. All data gathered during the simulation can be presented as a detailed summary afterwards. The included cost-benefit calculation can help to optimize the financial outcome. The operation of this approach is shown by the example of a timber harvest simulation.Keywords: Discrete-Event-Simulation, Logistic, Simulation, Virtual Reality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1870423 Efficient and Timely Mutual Authentication Scheme for RFID Systems
Authors: Hesham A. El Zouka, Mustafa M. Hosni
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The Radio Frequency Identification (RFID) technology has a diverse base of applications, but it is also prone to security threats. There are different types of security attacks which limit the range of the RFID applications. For example, deploying the RFID networks in insecure environments could make the RFID system vulnerable to many types of attacks such as spoofing attack, location traceability attack, physical attack and many more. Therefore, security is often an important requirement for RFID systems. In this paper, RFID mutual authentication protocol is implemented based on mobile agent technology and timestamp, which are used to provide strong authentication and integrity assurances to both the RFID readers and their corresponding RFID tags. The integration of mobile agent technology and timestamp provides promising results towards achieving this goal and towards reducing the security threats in RFID systems.Keywords: RFID, security, authentication protocols, privacy, agent-based architecture, time-stamp, digital signature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1780422 Improving the Performance of Deep Learning in Facial Emotion Recognition with Image Sharpening
Authors: Ksheeraj Sai Vepuri, Nada Attar
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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.Keywords: Facial expression recognition, image pre-processing, deep learning, CNN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 528421 Multipath Routing Sensor Network for Finding Crack in Metallic Structure Using Fuzzy Logic
Authors: Dulal Acharjee, Punyaban Patel
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For collecting data from all sensor nodes, some changes in Dynamic Source Routing (DSR) protocol is proposed. At each hop level, route-ranking technique is used for distributing packets to different selected routes dynamically. For calculating rank of a route, different parameters like: delay, residual energy and probability of packet loss are used. A hybrid topology of DMPR(Disjoint Multi Path Routing) and MMPR(Meshed Multi Path Routing) is formed, where braided topology is used in different faulty zones of network. For reducing energy consumption, variant transmission ranges is used instead of fixed transmission range. For reducing number of packet drop, a fuzzy logic inference scheme is used to insert different types of delays dynamically. A rule based system infers membership function strength which is used to calculate the final delay amount to be inserted into each of the node at different clusters. In braided path, a proposed 'Dual Line ACK Link'scheme is proposed for sending ACK signal from a damaged node or link to a parent node to ensure that any error in link or any node-failure message may not be lost anyway. This paper tries to design the theoretical aspects of a model which may be applied for collecting data from any large hanging iron structure with the help of wireless sensor network. But analyzing these data is the subject of material science and civil structural construction technology, that part is out of scope of this paper.Keywords: Metallic corrosion, Multi Path Routing, DisjointMPR, Meshed MPR, braided path, dual line ACK link, route rankingand Fuzzy Logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1509420 Rejuvenate: Face and Body Retouching Using Image Inpainting
Authors: H. AbdelRahman, S. Rostom, Y. Lotfy, S. Salah Eldeen, R. Yassein, N. Awny
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People are growing more concerned with their appearance in today's society. But they are terrified of what they will look like after a plastic surgery. People's mental health suffers when they have accidents, burns, or genetic issues that cause them to cleave certain body parts, which makes them feel uncomfortable and unappreciated. The method provides an innovative deep learning-based technique for image inpainting that analyzes different picture structures and fixes damaged images. This study proposes a model based on the Stable Diffusion Inpainting method for in-painting medical images. One significant advancement made possible by deep neural networks is image inpainting, which is the process of reconstructing damaged and missing portions of an image. The patient can see the outcome more easily since the system uses the user's input of an image to identify a problem. It then modifies the image and outputs a fixed image.
Keywords: Generative Adversarial Network, GAN, Large Mask Inpainting, LAMA, Stable Diffusion Inpainting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 81419 Performance of Random Diagonal Codes for Spectral Amplitude Coding Optical CDMA Systems
Authors: Hilal A. Fadhil, Syed A. Aljunid, R. Badlishah Ahmed
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In this paper we study the use of a new code called Random Diagonal (RD) code for Spectral Amplitude Coding (SAC) optical Code Division Multiple Access (CDMA) networks, using Fiber Bragg-Grating (FBG), FBG consists of a fiber segment whose index of reflection varies periodically along its length. RD code is constructed using code level and data level, one of the important properties of this code is that the cross correlation at data level is always zero, which means that Phase intensity Induced Phase (PIIN) is reduced. We find that the performance of the RD code will be better than Modified Frequency Hopping (MFH) and Hadamard code It has been observed through experimental and theoretical simulation that BER for RD code perform significantly better than other codes. Proof –of-principle simulations of encoding with 3 channels, and 10 Gbps data transmission have been successfully demonstrated together with FBG decoding scheme for canceling the code level from SAC-signal.Keywords: FBG, MFH, OCDMA, PIIN, BER.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1735418 A New Hybrid Model with Passive Congregation for Stock Market Indices Prediction
Authors: Tarek Aboueldahab
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In this paper, we propose a new hybrid learning model for stock market indices prediction by adding a passive congregation term to the standard hybrid model comprising Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) operators in training Neural Networks (NN). This new passive congregation term is based on the cooperation between different particles in determining new positions rather than depending on the particles selfish thinking without considering other particles positions, thus it enables PSO to perform both the local and global search instead of only doing the local search. Experiment study carried out on the most famous European stock market indices in both long term and short term prediction shows significantly the influence of the passive congregation term in improving the prediction accuracy compared to standard hybrid model.
Keywords: Global Search, Hybrid Model, Passive Congregation, Stock Market Prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1494417 A Bacterial Foraging Optimization Algorithm Applied to the Synthesis of Polyacrylamide Hydrogels
Authors: Florin Leon, Silvia Curteanu
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The Bacterial Foraging Optimization (BFO) algorithm is inspired by the behavior of bacteria such as Escherichia coli or Myxococcus xanthus when searching for food, more precisely the chemotaxis behavior. Bacteria perceive chemical gradients in the environment, such as nutrients, and also other individual bacteria, and move toward or in the opposite direction to those signals. The application example considered as a case study consists in establishing the dependency between the reaction yield of hydrogels based on polyacrylamide and the working conditions such as time, temperature, monomer, initiator, crosslinking agent and inclusion polymer concentrations, as well as type of the polymer added. This process is modeled with a neural network which is included in an optimization procedure based on BFO. An experimental study of BFO parameters is performed. The results show that the algorithm is quite robust and can obtain good results for diverse combinations of parameter values.
Keywords: Bacterial foraging optimization, hydrogels, neural networks, modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 713416 Optimization of a Three-Term Backpropagation Algorithm Used for Neural Network Learning
Authors: Yahya H. Zweiri
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The back-propagation algorithm calculates the weight changes of an artificial neural network, and a two-term algorithm with a dynamically optimal learning rate and a momentum factor is commonly used. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third term increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and optimization approaches for evaluating the learning parameters are required to facilitate the application of the three terms BP algorithm. This paper considers the optimization of the new back-propagation algorithm by using derivative information. A family of approaches exploiting the derivatives with respect to the learning rate, momentum factor and proportional factor is presented. These autonomously compute the derivatives in the weight space, by using information gathered from the forward and backward procedures. The three-term BP algorithm and the optimization approaches are evaluated using the benchmark XOR problem.Keywords: Neural Networks, Backpropagation, Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1529415 Performance Evaluation of an Efficient Asynchronous Protocol for WDM Ring MANs
Authors: Peristera A. Baziana
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The idea of the asynchronous transmission in wavelength division multiplexing (WDM) ring MANs is studied in this paper. Especially, we present an efficient access technique to coordinate the collisions-free transmission of the variable sizes of IP traffic in WDM ring core networks. Each node is equipped with a tunable transmitter and a tunable receiver. In this way, all the wavelengths are exploited for both transmission and reception. In order to evaluate the performance measures of average throughput, queuing delay and packet dropping probability at the buffers, a simulation model that assumes symmetric access rights among the nodes is developed based on Poisson statistics. Extensive numerical results show that the proposed protocol achieves apart from high bandwidth exploitation for a wide range of offered load, fairness of queuing delay and dropping events among the different packets size categories.
Keywords: Asynchronous transmission, collision avoidance, wavelength division multiplexing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2083414 Distributed Coverage Control by Robot Networks in Unknown Environments Using a Modified EM Algorithm
Authors: Mohammadhosein Hasanbeig, Lacra Pavel
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In this paper, we study a distributed control algorithm for the problem of unknown area coverage by a network of robots. The coverage objective is to locate a set of targets in the area and to minimize the robots’ energy consumption. The robots have no prior knowledge about the location and also about the number of the targets in the area. One efficient approach that can be used to relax the robots’ lack of knowledge is to incorporate an auxiliary learning algorithm into the control scheme. A learning algorithm actually allows the robots to explore and study the unknown environment and to eventually overcome their lack of knowledge. The control algorithm itself is modeled based on game theory where the network of the robots use their collective information to play a non-cooperative potential game. The algorithm is tested via simulations to verify its performance and adaptability.Keywords: Distributed control, game theory, multi-agent learning, reinforcement learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 964413 Delay and Packet Loss Analysis for Handovers between MANETs and NEMO Networks
Authors: Jirawat Thaenthong, Steven Gordon
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MANEMO is the integration of Network Mobility (NEMO) and Mobile Ad Hoc Network (MANET). A MANEMO node has an interface to both a MANET and NEMO network, and therefore should choose the optimal interface for packet delivery, however such a handover between interfaces will introduce packet loss. We define the steps necessary for a MANEMO handover, using Mobile IP and NEMO to signal the new binding to the relevant Home Agent(s). The handover steps aim to minimize the packet loss by avoiding waiting for Duplicate Address Detection and Neighbour Unreachability Detection. We present expressions for handover delay and packet loss, and then use numerical examples to evaluate a MANEMO handover. The analysis shows how the packet loss depends on level of nesting within NEMO, the delay between Home Agents and the load on the MANET, and hence can be used to developing optimal MANEMO handover algorithms.Keywords: IP mobility, handover, MANET, network mobility
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2077412 User Acceptance of Location-based Services
Authors: Neven Vrček, Goran Bubaš, Neven Bosilj
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Location-based services (LBS) exploit the known location of a user to provide services dependent on their geographic context and personalized needs [1]. The development and arrival of broadband mobile data networks supported with mobile terminals equipped with new location technologies like GPS have finally created opportunities for implementation of LBS applications. But, from the other side, collecting location information data in general raises privacy concerns. This paper presents results from two surveys of LBS acceptance in Croatia. The first survey was administered on 181 students, and the second extended survey involved pattern of 180 Croatian citizens. We developed questionnaire which consists of descriptions of 15 different applications with scale which measures perceptions and attitudes of users towards these applications. We report the results to identify potential commercial applications for LBS in B2C segment. Our findings suggest that some types of applications like emergency&safety services and navigation have significantly higher rate of acceptance than other types.Keywords: Acceptance, location-based services, m-application.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1954411 Frame and Burst Acquisition in TDMA Satellite Communication Networks with Transponder Hopping
Authors: Vitalice K. Oduol, C. Ardil
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The paper presents frame and burst acquisition in a satellite communication network based on time division multiple access (TDMA) in which the transmissions may be carried on different transponders. A unique word pattern is used for the acquisition process. The search for the frame is aided by soft-decision of QPSK modulated signals in an additive white Gaussian channel. Results show that when the false alarm rate is low the probability of detection is also low, and the acquisition time is long. Conversely when the false alarm rate is high, the probability of detection is also high and the acquisition time is short. Thus the system operators can trade high false alarm rates for high detection probabilities and shorter acquisition times.
Keywords: burst acquisition, burst time plan, frame acquisition, satellite access, satellite TDMA, unique word detection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9142