349 research outputs found

    ICSNC 1: Mobility and Ad Hoc

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    Page 1. Page 2. ICSNC 1: Mobility and Ad Hoc Energy Aware Topology Management in Ad Hoc Wireless Networks T. Shiv Prakash, GS Badrinath, KR Venugopal and LM Patnaik T Hybrid Agents for Power-Aware Intrusion Detection in Highly Mobile Ad Hoc Networks T. Srinivasan, V. Mahadevan, A. Meyyappan, A. Manikandan, M. Nivedita and N. Pavithra T An Enhanced Gnutella for Ad-Hoc Networks Hyun-Duk Choi, Ho-Hyun Park and Miae Woo T A New EAAODV Routing Protocol Based on Mobile Agent Chenchen Zhao and Zhen Yang T The Case of Multi-Hop Peer-to-Peer Implementation of Mobile Social Applications Panayotis Antoniadis and Costas Courcoubetis T Mobile Agent Communication Scheme: An Evolving Canvas Mâamoun Bernich and Fabrice Mourlin T Page 3. ICSNC 2: High Speed Building High-Performance and Reconfigurable Bandwidth Controllers with Adaptive Clustering

    ACADEMIC HANDBOOK (UNDERGRADUATE) COLLEGE OF ENGINEERING (CoE)

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    Mobile Ad-Hoc Networks

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    Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

    Intelligent Computational Transportation

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    Transportation is commonplace around our world. Numerous researchers dedicate great efforts to vast transportation research topics. The purpose of this dissertation is to investigate and address a couple of transportation problems with respect to geographic discretization, pavement surface automatic examination, and traffic ow simulation, using advanced computational technologies. Many applications require a discretized 2D geographic map such that local information can be accessed efficiently. For example, map matching, which aligns a sequence of observed positions to a real-world road network, needs to find all the nearby road segments to the individual positions. To this end, the map is discretized by cells and each cell retains a list of road segments coincident with this cell. An efficient method is proposed to form such lists for the cells without costly overlapping tests. Furthermore, the method can be easily extended to 3D scenarios for fast triangle mesh voxelization. Pavement surface distress conditions are critical inputs for quantifying roadway infrastructure serviceability. Existing computer-aided automatic examination techniques are mainly based on 2D image analysis or 3D georeferenced data set. The disadvantage of information losses or extremely high costs impedes their effectiveness iv and applicability. In this study, a cost-effective Kinect-based approach is proposed for 3D pavement surface reconstruction and cracking recognition. Various cracking measurements such as alligator cracking, traverse cracking, longitudinal cracking, etc., are identified and recognized for their severity examinations based on associated geometrical features. Smart transportation is one of the core components in modern urbanization processes. Under this context, the Connected Autonomous Vehicle (CAV) system presents a promising solution towards the enhanced traffic safety and mobility through state-of-the-art wireless communications and autonomous driving techniques. Due to the different nature between the CAVs and the conventional Human- Driven-Vehicles (HDVs), it is believed that CAV-enabled transportation systems will revolutionize the existing understanding of network-wide traffic operations and re-establish traffic ow theory. This study presents a new continuum dynamics model for the future CAV-enabled traffic system, realized by encapsulating mutually-coupled vehicle interactions using virtual internal and external forces. A Smoothed Particle Hydrodynamics (SPH)-based numerical simulation and an interactive traffic visualization framework are also developed

    Quality-Oriented Mobility Management for Multimedia Content Delivery to Mobile Users

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    The heterogeneous wireless networking environment determined by the latest developments in wireless access technologies promises a high level of communication resources for mobile computational devices. Although the communication resources provided, especially referring to bandwidth, enable multimedia streaming to mobile users, maintaining a high user perceived quality is still a challenging task. The main factors which affect quality in multimedia streaming over wireless networks are mainly the error-prone nature of the wireless channels and the user mobility. These factors determine a high level of dynamics of wireless communication resources, namely variations in throughput and packet loss as well as network availability and delays in delivering the data packets. Under these conditions maintaining a high level of quality, as perceived by the user, requires a quality oriented mobility management scheme. Consequently we propose the Smooth Adaptive Soft-Handover Algorithm, a novel quality oriented handover management scheme which unlike other similar solutions, smoothly transfer the data traffic from one network to another using multiple simultaneous connections. To estimate the capacity of each connection the novel Quality of Multimedia Streaming (QMS) metric is proposed. The QMS metric aims at offering maximum flexibility and efficiency allowing the applications to fine tune the behavior of the handover algorithm. The current simulation-based performance evaluation clearly shows the better performance of the proposed Smooth Adaptive Soft-Handover Algorithm as compared with other handover solutions. The evaluation was performed in various scenarios including multiple mobile hosts performing handover simultaneously, wireless networks with variable overlapping areas, and various network congestion levels

    Evolving to Digital and Programmable Value Based Economy: General Prospect and Specific Applications over Sustainability

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    [eng] In the fields of economics, business and management, how could Digital Transformation (DT) advance value creation and reliably encourage value capture, exchange and distribution? This thesis aim to fill that gap with a novel framework to support policy-makers, countries, cities and businesses address the potential value that can be generated and captured by digitalization combining DT and Internet of Value theoretical perspectives and practical applications of them over concrete issues such as sustainability in cities, as an example. For this, it is proposed to make new contributions related to DT and Internet of Value in two main aspects: to explore DT countries’ mindsets when it relates to their value progress through Digital Ecosystems and to advance with the potential digital value applications through Programmable Economy advantages when it focus on concrete aspect such as sustainability in cities. Both perspectives, although it will be applied on different dimensions and on different purposes, have in common that they are focus on digital and programable value based economy and management and want to explore the best way to maximize and capture the DT potential in terms of value for organizations and society. Thus, first, it will be analysed the importance of knowing clearly the digital ecosystem in which the agents are operating in order to reinforce the value creation by promoting the inclusivity and connectivity of the endpoints involved in it. Secondly, it will be analysed how the digital value can be captured, exchanged and redistributed in a complex issues such as sustainability by deploying concrete digital applications that include human reinforcement aspects to, finally, closing the circle combining both perspectives in a single framework. To achieve these objectives in this thesis, own models are proposed, inspired by other theoretical models already contrasted, and some proven methodologies are used related to Conditional Probability, Forgotten Effects and Fuzzy Sets. As a main conclusion, Digital Transformation has the potential to generate immense value for economy and society. Although currently the capture of the vast majority of it is not guaranteed and its distribution between agents is no clear, new formulas are being explored supported by the Internet of Value. This thesis defends that if agents want to advance value creation and encourage value capture, they should consider to make their own Digital and Programmable Value Based Economy and Management framework through: - Allowing all functional agents work in a Digital Ecosystem embracing new relationships and ways of collaborating pursuing the same purpose. - Deploying Programmable Economy applications advantages, mixing digital's and analogue's world that can be interlinked and programmed by the blockchain allowing monetization and exploring new human and machine alliances. - Adopting strong and inclusive agents’ commitment in order to exploit the advantages that this smart economy system has from a human centric vision, discovering new forms of value, considering that, although tech can be everywhere, value not

    Advances in Computer Science and Engineering

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    The book Advances in Computer Science and Engineering constitutes the revised selection of 23 chapters written by scientists and researchers from all over the world. The chapters cover topics in the scientific fields of Applied Computing Techniques, Innovations in Mechanical Engineering, Electrical Engineering and Applications and Advances in Applied Modeling

    Personality Identification from Social Media Using Deep Learning: A Review

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    Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed
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