Search results for: Baseline networks
1164 Reliability-Based Maintenance Management Methodology to Minimise Life Cycle Cost of Water Supply Networks
Authors: Mojtaba Mahmoodian, Joshua Phelan, Mehdi Shahparvari
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With a large percentage of countries’ total infrastructure expenditure attributed to water network maintenance, it is essential to optimise maintenance strategies to rehabilitate or replace underground pipes before failure occurs. The aim of this paper is to provide water utility managers with a maintenance management approach for underground water pipes, subject to external loading and material corrosion, to give the lowest life cycle cost over a predetermined time period. This reliability-based maintenance management methodology details the optimal years for intervention, the ideal number of maintenance activities to perform before replacement and specifies feasible renewal options and intervention prioritisation to minimise the life cycle cost. The study was then extended to include feasible renewal methods by determining the structural condition index and potential for soil loss, then obtaining the failure impact rating to assist in prioritising pipe replacement. A case study on optimisation of maintenance plans for the Melbourne water pipe network is considered in this paper to evaluate the practicality of the proposed methodology. The results confirm that the suggested methodology can provide water utility managers with a reliable systematic approach to determining optimum maintenance plans for pipe networks.Keywords: Water pipe networks, maintenance management, reliability analysis, optimum maintenance plan.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12441163 Issues in Deploying Smart Antennas in Mobile Radio Networks
Authors: Rameshwar Kawitkar
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With the exponentially increasing demand for wireless communications the capacity of current cellular systems will soon become incapable of handling the growing traffic. Since radio frequencies are diminishing natural resources, there seems to be a fundamental barrier to further capacity increase. The solution can be found in smart antenna systems. Smart or adaptive antenna arrays consist of an array of antenna elements with signal processing capability, that optimize the radiation and reception of a desired signal, dynamically. Smart antennas can place nulls in the direction of interferers via adaptive updating of weights linked to each antenna element. They thus cancel out most of the co-channel interference resulting in better quality of reception and lower dropped calls. Smart antennas can also track the user within a cell via direction of arrival algorithms. This implies that they are more advantageous than other antenna systems. This paper focuses on few issues about the smart antennas in mobile radio networks.Keywords: Smart/Adaptive Antenna, Multipath fading, Beamforming, Radio propagation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26571162 Identification of Impact Loads and Partial System Parameters Using 1D-CNN
Authors: Xuewen Yu, Danhui Dan
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The identification of impact loads and some hard-to-obtain system parameters is crucial for analysis, validation, and evaluation activities in the engineering field. This paper proposes a method based on 1D-CNN to identify impact loads and partial system parameters from the measured responses. To this end, forward computations are conducted to provide datasets consisting of triples (parameter θ, input u, output y). Two neural networks are then trained: one to learn the mapping from output y to input u and another to learn the mapping from input and output (u, y) to parameter θ. Subsequently, by feeding the measured output response into the trained neural networks, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameter.
Keywords: Convolutional neural network, impact load identification, system parameter identification, inverse problem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 591161 Eco-Connectivity: Sustainable Practices in Telecom Networks Using Big Data
Authors: Tharunika Sridhar
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This paper addresses sustainable eco-connectivity within the telecommunications sector studying its importance to tackle the contemporary challenges and data regulation issues. The paper also investigates the role of Big Data and its integration in this context, specific to telecom industry. One of the major focus areas in this paper is studying and examining the pathways explored, that are state-of-the-art ecological infrastructure solutions and sector-led measures derived from expert analyses and reviews. Additionally, the paper analyses critical factors involving cost-effective route planning, and the development of green telecommunications infrastructure that adds qualitative reasoning to the research idea. Furthermore, the study discusses in detail a potential green roadmap towards sustainability by exploring green routing software, eco-friendly infrastructure and other eco-focused initiatives. The paper is also directed at the special linguistic needs of the telecommunications sector by focusing on targeted select range of telecom environment.
Keywords: Big Data, telecom, sustainable telecom sector, telecom networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 411160 Opinion Mining and Sentiment Analysis on DEFT
Authors: Najiba Ouled Omar, Azza Harbaoui, Henda Ben Ghezala
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Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte (DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.
Keywords: Opinion mining, sentiment analysis, emotion, polarity, annotation, OSEE, figurative language, DEFT, Twitter, Tweet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8051159 Optical Multicast over OBS Networks: An Approach Based On Code-Words and Tunable Decoders
Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga
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In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.
Keywords: Optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16711158 Optical Multicast over OBS Networks: An Approach Based On Code-Words and Tunable Decoders
Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga
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In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.
Keywords: Optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17491157 Modeling of Normal and Atherosclerotic Blood Vessels using Finite Element Methods and Artificial Neural Networks
Authors: K. Kamalanand, S. Srinivasan
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Analysis of blood vessel mechanics in normal and diseased conditions is essential for disease research, medical device design and treatment planning. In this work, 3D finite element models of normal vessel and atherosclerotic vessel with 50% plaque deposition were developed. The developed models were meshed using finite number of tetrahedral elements. The developed models were simulated using actual blood pressure signals. Based on the transient analysis performed on the developed models, the parameters such as total displacement, strain energy density and entropy per unit volume were obtained. Further, the obtained parameters were used to develop artificial neural network models for analyzing normal and atherosclerotic blood vessels. In this paper, the objectives of the study, methodology and significant observations are presented.Keywords: Blood vessel, atherosclerosis, finite element model, artificial neural networks
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22951156 Bandwidth Optimization through Dynamic Routing in ATM Networks: Genetic Algorithm and Tabu Search Approach
Authors: Susmi Routray, A. M. Sherry, B. V. R. Reddy
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Asynchronous Transfer Mode (ATM) is widely used in telecommunications systems to send data, video and voice at a very high speed. In ATM network optimizing the bandwidth through dynamic routing is an important consideration. Previous research work shows that traditional optimization heuristics result in suboptimal solution. In this paper we have explored non-traditional optimization technique. We propose comparison of two such algorithms - Genetic Algorithm (GA) and Tabu search (TS), based on non-traditional Optimization approach, for solving the dynamic routing problem in ATM networks which in return will optimize the bandwidth. The optimized bandwidth could mean that some attractive business applications would become feasible such as high speed LAN interconnection, teleconferencing etc. We have also performed a comparative study of the selection mechanisms in GA and listed the best selection mechanism and a new initialization technique which improves the efficiency of the GA.Keywords: Asynchronous Transfer Mode(ATM), GeneticAlgorithm(GA), Tabu Search(TS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17581155 Hybrid Machine Learning Approach for Text Categorization
Authors: Nerijus Remeikis, Ignas Skucas, Vida Melninkaite
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Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.
Keywords: Text categorization, decision trees, neural networks, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17961154 A New Method for Image Classification Based on Multi-level Neural Networks
Authors: Samy Sadek, Ayoub Al-Hamadi, Bernd Michaelis, Usama Sayed
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In this paper, we propose a supervised method for color image classification based on a multilevel sigmoidal neural network (MSNN) model. In this method, images are classified into five categories, i.e., “Car", “Building", “Mountain", “Farm" and “Coast". This classification is performed without any segmentation processes. To verify the learning capabilities of the proposed method, we compare our MSNN model with the traditional Sigmoidal Neural Network (SNN) model. Results of comparison have shown that the MSNN model performs better than the traditional SNN model in the context of training run time and classification rate. Both color moments and multi-level wavelets decomposition technique are used to extract features from images. The proposed method has been tested on a variety of real and synthetic images.Keywords: Image classification, multi-level neural networks, feature extraction, wavelets decomposition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16361153 Mamdani Model based Adaptive Neural Fuzzy Inference System and its Application
Authors: Yuanyuan Chai, Limin Jia, Zundong Zhang
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Hybrid algorithm is the hot issue in Computational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classification method and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy Inference System (M-ANFIS) and weight updating formula in consideration with qualitative representation of inference consequent parts in fuzzy neural networks. M-ANFIS model adopts Mamdani fuzzy inference system which has advantages in consequent part. Experiment results of applying M-ANFIS to evaluate traffic Level of service show that M-ANFIS, as a new hybrid algorithm in computational intelligence, has great advantages in non-linear modeling, membership functions in consequent parts, scale of training data and amount of adjusted parameters.Keywords: Fuzzy neural networks, Mamdani fuzzy inference, M-ANFIS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 52301152 A Study of Behaviors in Using Social Networks of Corporate Personnel of Suan Sunandha Rajabhat University
Authors: Wipada Chiawchan
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This study found that most corporate personnel are using social media to communicate with colleagues to make the process of working more efficient. Complete satisfaction occurred on the use of security within the University’s computer network. The social network usage for communication, collaboration, entertainment and demonstrating concerns accounted for fifty percent of variance to predict interpersonal relationships of corporate personnel. This evaluation on the effectiveness of social networking involved 213 corporate personnel’s. The data was collected by questionnaires. This data was analyzed by using percentage, mean, and standard deviation. The results from the analysis and the effectiveness of using online social networks were derived from the attitude of private users and safety data within the security system. The results showed that the effectiveness on the use of an online social network for corporate personnel of Suan Sunandha Rajabhat University was specifically at a good level, and the overall effects of each aspect was (Ẋ=3.11).Keywords: Behaviors, Social Media, Social Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13841151 Analysis of the Omnichannel Delivery Network with Application to Last Mile Delivery
Authors: Colette Malyack, Pius Egbelu
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Business-to-Customer (B2C) delivery options have improved to meet increased demand in recent years. The change in end users has forced logistics networks to focus on customer service and sentiment that would have previously been the priority of the company or organization of origin. This has led to increased pressure on logistics companies to extend traditional B2B networks into a B2C solution while accommodating additional costs, roadblocks, and customer sentiment; the result has been the creation of the omnichannel delivery network encompassing a number of traditional and modern methods of package delivery. In this paper the many solutions within the omnichannel delivery network are defined and discussed. It can be seen through this analysis that the omnichannel delivery network can be applied to reduce the complexity of package delivery and provide customers with more options. Applied correctly the result is a reduction in cost to the logistics company over time, even with an initial increase in cost to obtain the technology.Keywords: Network planning, Last Mile Delivery, LMD, omnichannel delivery network, omnichannel logistics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6511150 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 20941149 An Empirical Model of Correlated Traffics in LTE-Advanced System through an Innovative Simulation Tool
Authors: Ghassan A. Abed, Mahamod Ismail, Samir I. Badrawi, Bayan M. Sabbar
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Long Term Evolution Advanced (LTE-Advanced) LTE-Advanced is not new as a radio access technology, but it is an evolution of LTE to enhance the performance. This generation is the continuation of 3GPP-LTE (3GPP: 3rd Generation Partnership Project) and it is targeted for advanced development of the requirements of LTE in terms of throughput and coverage. The performance evaluation process of any network should be based on many models and simulations to investigate the network layers and functions and monitor the employment of the new technologies especially when this network includes large-bandwidth and low-latency links such as LTE and LTE-Advanced networks. Therefore, it’s necessary to enhance the proposed models of high-speed and high-congested link networks to make these links and traffics fulfill the needs of the huge data which transferred over the congested links. This article offered an innovative model of the most correlated links of LTE-Advanced system using the Network Simulator 2 (NS-2) with investigation of the link parameters.
Keywords: 3GPP, LTE, LTE-Advanced, NS-2.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24171148 T-Wave Detection Based on an Adjusted Wavelet Transform Modulus Maxima
Authors: Samar Krimi, Kaïs Ouni, Noureddine Ellouze
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The method described in this paper deals with the problems of T-wave detection in an ECG. Determining the position of a T-wave is complicated due to the low amplitude, the ambiguous and changing form of the complex. A wavelet transform approach handles these complications therefore a method based on this concept was developed. In this way we developed a detection method that is able to detect T-waves with a sensitivity of 93% and a correct-detection ratio of 93% even with a serious amount of baseline drift and noise.Keywords: ECG, Modulus Maxima Wavelet Transform, Performance, T-wave detection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18411147 Soft Computing Based Cluster Head Selection in Wireless Sensor Network Using Bacterial Foraging Optimization Algorithm
Authors: A. Rajagopal, S. Somasundaram, B. Sowmya, T. Suguna
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Wireless Sensor Networks (WSNs) enable new applications and need non-conventional paradigms for the protocol because of energy and bandwidth constraints, In WSN, sensor node’s life is a critical parameter. Research on life extension is based on Low-Energy Adaptive Clustering Hierarchy (LEACH) scheme, which rotates Cluster Head (CH) among sensor nodes to distribute energy consumption over all network nodes. CH selection in WSN affects network energy efficiency greatly. This study proposes an improved CH selection for efficient data aggregation in sensor networks. This new algorithm is based on Bacterial Foraging Optimization (BFO) incorporated in LEACH.Keywords: Bacterial Foraging Optimization (BFO), Cluster Head (CH), Data-aggregation protocols, Low-Energy Adaptive Clustering Hierarchy (LEACH).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34711146 An Autonomous Collaborative Forecasting System Implementation – The First Step towards Successful CPFR System
Authors: Chi-Fang Huang, Yun-Shiow Chen, Yun-Kung Chung
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In the past decade, artificial neural networks (ANNs) have been regarded as an instrument for problem-solving and decision-making; indeed, they have already done with a substantial efficiency and effectiveness improvement in industries and businesses. In this paper, the Back-Propagation neural Networks (BPNs) will be modulated to demonstrate the performance of the collaborative forecasting (CF) function of a Collaborative Planning, Forecasting and Replenishment (CPFR®) system. CPFR functions the balance between the sufficient product supply and the necessary customer demand in a Supply and Demand Chain (SDC). Several classical standard BPN will be grouped, collaborated and exploited for the easy implementation of the proposed modular ANN framework based on the topology of a SDC. Each individual BPN is applied as a modular tool to perform the task of forecasting SKUs (Stock-Keeping Units) levels that are managed and supervised at a POS (point of sale), a wholesaler, and a manufacturer in an SDC. The proposed modular BPN-based CF system will be exemplified and experimentally verified using lots of datasets of the simulated SDC. The experimental results showed that a complex CF problem can be divided into a group of simpler sub-problems based on the single independent trading partners distributed over SDC, and its SKU forecasting accuracy was satisfied when the system forecasted values compared to the original simulated SDC data. The primary task of implementing an autonomous CF involves the study of supervised ANN learning methodology which aims at making “knowledgeable" decision for the best SKU sales plan and stocks management.Keywords: CPFR, artificial neural networks, global logistics, supply and demand chain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19791145 Markov Chain Based QoS Support for Wireless Body Area Network Communication in Health Monitoring Services
Authors: R. A. Isabel, E. Baburaj
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Wireless Body Area Networks (WBANs) are essential for real-time health monitoring of patients and in diagnosing of many diseases. WBANs comprise many sensors to monitor a large range of ambient conditions. Quality of Service (QoS) is a key challenge in WBAN, because the different state information of the neighboring nodes has to be monitored in an accurate manner. However, energy consumption gets increased while predicting and maintaining the exact information in highly dynamic environments. In order to reduce energy consumption and end to end delay, Markov Chain Based Quality of Service Support (MC-QoSS) method is designed in the health monitoring services of WBAN communication. The energy consumption gets reduced by forming a Markov chain with high energy nodes in the sensor networks communication path. The low energy level sensor nodes are removed using transitional probability in order to reduce end to end delay. High energy nodes are formed in the chain structure of its corresponding path to enhance communication. After choosing the communication path through high energy nodes, the packets are sent to the sink node from the source node with a higher Packet Delivery Ratio. The simulation result shows that MC-QoSS method improves the packet delivery ratio and reduces energy consumption with minimum end to end delay, compared to existing methods.
Keywords: Wireless body area networks, quality of service, Markov chain, health monitoring services.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14341144 Fuzzy Based Particle Swarm Optimization Routing Technique for Load Balancing in Wireless Sensor Networks
Authors: S. Balaji, E. Golden Julie, M. Rajaram, Y. Harold Robinson
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Network lifetime improvement and uncertainty in multiple systems are the issues of wireless sensor network routing. This paper presents fuzzy based particle swarm optimization routing technique to improve the network scalability. Significantly, in the cluster formation procedure, fuzzy based system is used to solve the uncertainty and network balancing. Cluster heads play an important role to reduce the energy consumption using particle swarm optimization algorithm, the cluster head sends its information along data packets to the heads with link. The simulation results show that the presented routing protocol can perform load balancing effectively and reduce the energy consumption of cluster heads.
Keywords: Wireless sensor networks, fuzzy logic, PSO, LEACH.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12761143 Future Logistics - Challenges, Requirements and Solutions for Logistics Networks
Authors: Martin Roth, Axel Klarmann, Bogdan Franczyk
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The importance of logistics has changed enormously in the last few decades. While logistics was formerly one of the core functions of most companies, logistics or at least parts of their functions are nowadays outsourced to external logistic service providers in terms of contracts. As a result of this shift new business models like the fourth party logistics provider emerged, which designs, plans and monitors the resulting logistics networks. This new business model and topics such as Synchromodality or Big Data impose new requirements on the underlying IT, which cannot be met with conventional concepts and approaches. In this paper, the challenges of logistics network monitoring are outlined by using a scenario. The most common layers in a logical multilayered architecture for an information system are used to point out the arising challenges for IT. In addition, first appropriate solution approaches are introduced.
Keywords: Complex Event Processing, Fourth Party Logistics Service Provider, Logistics monitoring, Synchromodality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33651142 Validity Domains of Beams Behavioural Models: Efficiency and Reduction with Artificial Neural Networks
Authors: Keny Ordaz-Hernandez, Xavier Fischer, Fouad Bennis
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In a particular case of behavioural model reduction by ANNs, a validity domain shortening has been found. In mechanics, as in other domains, the notion of validity domain allows the engineer to choose a valid model for a particular analysis or simulation. In the study of mechanical behaviour for a cantilever beam (using linear and non-linear models), Multi-Layer Perceptron (MLP) Backpropagation (BP) networks have been applied as model reduction technique. This reduced model is constructed to be more efficient than the non-reduced model. Within a less extended domain, the ANN reduced model estimates correctly the non-linear response, with a lower computational cost. It has been found that the neural network model is not able to approximate the linear behaviour while it does approximate the non-linear behaviour very well. The details of the case are provided with an example of the cantilever beam behaviour modelling.
Keywords: artificial neural network, validity domain, cantileverbeam, non-linear behaviour, model reduction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14201141 An Evaluation of Neural Network Efficacies for Image Recognition on Edge-AI Computer Vision Platform
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Image recognition enables machine-like robotics to understand a scene and plays an important role in computer vision applications. Computer vision platforms as physical infrastructure, supporting Neural Networks for image recognition, are deterministic to leverage the performance of different Neural Networks. In this paper, three different computer vision platforms – edge AI (Jetson Nano, with 4GB), a standalone laptop (with RTX 3000s, using CUDA), and a web-based device (Google Colab, using GPU) are investigated. In the case study, four prominent neural network architectures (including AlexNet, VGG16, GoogleNet, and ResNet (34/50)), are deployed. By using public ImageNets (Cifar-10), our findings provide a nuanced perspective on optimizing image recognition tasks across Edge-AI platforms, offering guidance on selecting appropriate neural network structures to maximize performance under hardware constraints.
Keywords: AlexNet, VGG, GoogleNet, ResNet, ImageNet, Cifar-10, Edge AI, Jetson Nano, CUDA, GPU.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1781140 Apoptosis Inspired Intrusion Detection System
Authors: R. Sridevi, G. Jagajothi
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Artificial Immune Systems (AIS), inspired by the human immune system, are algorithms and mechanisms which are self-adaptive and self-learning classifiers capable of recognizing and classifying by learning, long-term memory and association. Unlike other human system inspired techniques like genetic algorithms and neural networks, AIS includes a range of algorithms modeling on different immune mechanism of the body. In this paper, a mechanism of a human immune system based on apoptosis is adopted to build an Intrusion Detection System (IDS) to protect computer networks. Features are selected from network traffic using Fisher Score. Based on the selected features, the record/connection is classified as either an attack or normal traffic by the proposed methodology. Simulation results demonstrates that the proposed AIS based on apoptosis performs better than existing AIS for intrusion detection.
Keywords: Apoptosis, Artificial Immune System (AIS), Fisher Score, KDD dataset, Network intrusion detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21821139 Formal Verification of a Multicast Protocol in Mobile Networks
Authors: M. Matash Borujerdi, S.M. Mirzababaei
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As computer network technology becomes increasingly complex, it becomes necessary to place greater requirements on the validity of developing standards and the resulting technology. Communication networks are based on large amounts of protocols. The validity of these protocols have to be proved either individually or in an integral fashion. One strategy for achieving this is to apply the growing field of formal methods. Formal methods research defines systems in high order logic so that automated reasoning can be applied for verification. In this research we represent and implement a formerly announced multicast protocol in Prolog language so that certain properties of the protocol can be verified. It is shown that by using this approach some minor faults in the protocol were found and repaired. Describing the protocol as facts and rules also have other benefits i.e. leads to a process-able knowledge. This knowledge can be transferred as ontology between systems in KQML format. Since the Prolog language can increase its knowledge base every time, this method can also be used to learn an intelligent network.Keywords: Formal methods, MobiCast, Mobile Network, Multicast.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13691138 Handling Mobility using Virtual Grid in Static Wireless Sensor Networks
Authors: T.P. Sharma
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Querying a data source and routing data towards sink becomes a serious challenge in static wireless sensor networks if sink and/or data source are mobile. Many a times the event to be observed either moves or spreads across wide area making maintenance of continuous path between source and sink a challenge. Also, sink can move while query is being issued or data is on its way towards sink. In this paper, we extend our already proposed Grid Based Data Dissemination (GBDD) scheme which is a virtual grid based topology management scheme restricting impact of movement of sink(s) and event(s) to some specific cells of a grid. This obviates the need for frequent path modifications and hence maintains continuous flow of data while minimizing the network energy consumptions. Simulation experiments show significant improvements in network energy savings and average packet delay for a packet to reach at sink.Keywords: Mobility in WSNs, virtual grid, GBDD, clustering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15411137 MCDM Spectrum Handover Models for Cognitive Wireless Networks
Authors: Cesar Hernández, Diego Giral, Fernando Santa
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Spectrum handover is a significant topic in the cognitive radio networks to assure an efficient data transmission in the cognitive radio user’s communications. This paper proposes a comparison between three spectrum handover models: VIKOR, SAW and MEW. Four evaluation metrics are used. These metrics are, accumulative average of failed handover, accumulative average of handover performed, accumulative average of transmission bandwidth and, accumulative average of the transmission delay. As a difference with related work, the performance of the three spectrum handover models was validated with captured data of spectrum occupancy in experiments performed at the GSM frequency band (824 MHz - 849 MHz). These data represent the actual behavior of the licensed users for this wireless frequency band. The results of the comparison show that VIKOR Algorithm provides a 15.8% performance improvement compared to SAW Algorithm and, it is 12.1% better than the MEW Algorithm.Keywords: Cognitive radio, decision making, MEW, SAW, spectrum handover, VIKOR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21441136 An Integrated Software Architecture for Bandwidth Adaptive Video Streaming
Authors: T. Arsan
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Video streaming over lossy IP networks is very important issues, due to the heterogeneous structure of networks. Infrastructure of the Internet exhibits variable bandwidths, delays, congestions and time-varying packet losses. Because of variable attributes of the Internet, video streaming applications should not only have a good end-to-end transport performance but also have a robust rate control, furthermore multipath rate allocation mechanism. So for providing the video streaming service quality, some other components such as Bandwidth Estimation and Adaptive Rate Controller should be taken into consideration. This paper gives an overview of video streaming concept and bandwidth estimation tools and then introduces special architectures for bandwidth adaptive video streaming. A bandwidth estimation algorithm – pathChirp, Optimized Rate Controllers and Multipath Rate Allocation Algorithm are considered as all-in-one solution for video streaming problem. This solution is directed and optimized by a decision center which is designed for obtaining the maximum quality at the receiving side.Keywords: Adaptive Video Streaming, Bandwidth Estimation, QoS, Software Architecture.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14181135 Definition of Foot Size Model using Kohonen Network
Authors: Khawla Ben Abderrahim
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In order to define a new model of Tunisian foot sizes and for building the most comfortable shoes, Tunisian industrialists must be able to offer for their customers products able to put on and adjust the majority of the target population concerned. Moreover, the use of models of shoes, mainly from others country, causes a mismatch between the foot and comfort of the Tunisian shoes. But every foot is unique; these models become uncomfortable for the Tunisian foot. We have a set of measures produced from a 3D scan of the feet of a diverse population (women, men ...) and we try to analyze this data to define a model of foot specific to the Tunisian footwear design. In this paper we propose tow new approaches to modeling a new foot sizes model. We used, indeed, the neural networks, and specially the Kohonen network. Next, we combine neural networks with the concept of half-foot size to improve the models already found. Finally, it was necessary to compare the results obtained by applying each approach and we decide what-s the best approach that give us the most model of foot improving more comfortable shoes.Keywords: Morphology of the foot, foot size, half foot size, neural network, Kohonen network, model of foot size.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1546