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Blockchain-Based Wi-Fi Offloading Platform for 5G

Blockchain-Based Wi-Fi Offloading Platform for 5G

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IEEE International Conference on Communications Workshops, ICC

作者： Pramitha Fernando Lasitha Gunawardhana Wishva Rajapakshe Mahesh Dananjaya Tharindu Gamage Madhusanka Liyanage Department of Electrical and Information Engineering University of Ruhuna Sri Lanka School of Informatics University of Edinburgh UK School of Computer Science University College Dublin Ireland Centre for Wireless Communications University of Oulu Finland

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

The advent of 5G has sparked interest in Wi-Fi offloading techniques that enable efficient resource sharing and congestion management of wireless communication spectrum. However, offloading data between multiple networks (i.e. service providers) requires costly inter-provider communication which has a substantial overhead as well as high offloading latency. Moreover, involvement of the profit-oriented decision making of service providers has an inherent weakness of unfair scheduling among users and networks. To overcome those problems, this research work proposes a holistic framework similar to an online data market place where existing infrastructure can be used to set up Wi-Fi zones that everyone can use from their own data plan irrespective of the network operators they belong to. First, our proposed architecture improves the efficacy of offloading by using decentralized nature of the emerging Software-Defined Networking (SDN) to set up an operator-assisted data offloading platform, resulting in efficient inter-provider communication. Second, our proposal strengthens the fair scheduling of offloading resources by using blockchain technology to initiate unbiased and independent decision making. The resulting service is a rating system for the sellers to make reliable transactions for payments.

关键词： Wireless fidelity Contracts Bandwidth Pricing Decision making

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Belief theoretic methods for soft and hard data fusion

Belief theoretic methods for soft and hard data fusion

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： T. L. Wickramarathne K. Premaratne M. N. Murthi M. Scheutz S. Kübler M. Pravia Electrical and Computer Engineering University of Miami Coral Gables FL USA Computer Science Informatics Cognitive Science Indiana University Bloomington IN USA Cognitive Science Linguistics Indiana University Bloomington IN USA BAE Systems Avionics Burlington MA USA

ISBN: (纸本)9781457705380

In many contexts, one is confronted with the problem of extract ing information from large amounts of different types soft data (e.g., text) and hard data (from e.g., physics-based sensing systems). In handling hard data, signal and data processing offers a wealth of methods related to modeling, estimation, tracking, and inference tasks. However, soft data present several challenges that necessitate the development of new data processing methods. For example, with suitable statistical natural language processing (NLP) methods, text can be converted into logic statements that are associated with various forms of associated uncertainty related to the credibility of the statement, the reliability of the text source, and so forth. In combining or fusing soft data with either soft or hard data, one must deploy methods that can suitably preserve and update the uncertainty associated with the data, thereby providing uncertainty bounds related to any inferences regarding semantics. Since standard Bayesian probabilistic approaches have problems with suitably handling uncertain logic statements, there is an emerging need for new methods for processing heterogeneous data. In this paper, we describe a framework for fusing soft and hard data based on the Dempster-Shafer (DS) belief theoretic approach which is well-suited to the task of capturing the types of models and uncertain rules that are more typical of soft data. Since the effectiveness of traditional DS methods has been hampered by high computational requirements, we base the processing framework on our new conditional approach to DS theoretic evidence updating and fusion. We address the issue of laying the foundation for a theoretically justifiable, and computationally efficient framework for fusing soft and hard data taking into account the inherent data uncertainty such as reliability and credibility. Moreover, we present an illustrative ex ample that highlights the potential for the DS conditional approach for fusing

关键词： Uncertainty Computational modeling Natural language processing Vehicles Data processing Reliability theory

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Multiscale Kernels for Enhanced U-Shaped Network to Improve 3D Neuron Tracing

Multiscale Kernels for Enhanced U-Shaped Network to Improve ...

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Heng Wang Donghao Zhang Yang Song Siqi Liu Heng Huang Mei Chen Hanchuan Peng Weidong Cai School of Computer Science University of Sydney Australia School of Computer Science and Engineering University of New South Wales Australia Digital Services Digital Technology & Innovation Siemens Healthineers USA Department of Electrical and Computer Engineering University of Pittsburgh USA Department of Informatics University of Albany State University of New York USA Allen Institute for Brain Science USA

ISBN: (数字)9781728125060

ISBN: (纸本)9781728125077

Digital neuron morphology reconstruction from three-dimensional (3D) volumetric optical microscope images is an important procedure to rebuild the connections and structures of neural circuits. Even though many approaches have been proposed to achieve precise tracing, it is still a challenging task especially when images are polluted by noise or have discontinuity in their neuron structures. In this paper, we propose a new framework to overcome these issues by performing neuron segmentation prior to tracing. Our proposed framework adopts a novel 3D U-shaped convolutional neural network (CNN) with multiscale kernel fusion and spatial fusion to perform the image segmentation. We then perform the iterative back-tracking tracing algorithm on the output of the network. Evaluated on the Janelia dataset from the BigNeuron project, our proposed framework achieves competitive tracing performance.

关键词： Neurons Three-dimensional displays Image segmentation Kernel Gold Optical imaging Standards

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Industrial decision support requirements and expectations for a sugar mill crystallisation stage

Industrial decision support requirements and expectations fo...

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Annual Conference of Industrial Electronics Society

作者： R. Dodd A. Chiou R. Broadfoot X. Yu Faculty of Arts Business Informatics and Education Central Queensland University Rockhampton QLD Australia Queensland University of Technology Brisbane QLD Australia School of Electrical and Computer Engineering RMIT University Melbourne VIC Australia

This paper describes the fundamental requirements and expectations for the development of a knowledge based supervisory support system (KBSSS), to provide industrial decision support, for a sugar mill crystallisation stage. This paper puts into context the rationale for such a system. The increasing need and importance of providing industrial decision support in the industrial sugar mill setting are also detailed. The primary topics of this paper will focus upon: (1) a review of sugar mill industrial decision support, (2) unrealized expectations, and (3) requirements for decision support; all pertaining to sugar mill crystallisation stage operations.

关键词： Crystallization Sugar industry Production facilities Predictive models Decision making Decision support systems

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Design and Development of an Autonomous Mobile Robot for Inspection of Soy and Cotton Crops

Design and Development of an Autonomous Mobile Robot for Ins...

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International Conference on Developments in eSystems engineering (DESE)

作者： William S. Barbosa Adalberto I. S. Oliveira Gustavo B. P. Barbosa Antonio C. Leite Karla T. Figueiredo Marley M. B. R. Vellasco Wouter Caarls Dept. of Electrical Engineering PUC-Rio Rio de Janeiro RJ Brazil Dept. of Informatics and Computer Science Rio de Janeiro State University Rio de Janeiro RJ Brazil

ISBN: (数字)9781728130217

ISBN: (纸本)9781728130224

In recent years, the use of mobile robots in agriculture has increased significantly because of their capability to carry out agricultural tasks in a safe and efficient manner, with limited or without human intervention. Crop monitoring and inspection have become an important part of precision agriculture, supporting farmers in the management of insect pests, weeds and diseases in order to reduce costs and losses. In this work, we present the design and development of an autonomous mobile robot, conceived to perform routine monitoring and inspection tasks on soy and cotton crops. The robot design is similar to a differential-drive vehicle due to its simplicity of construction, modeling and control. The autonomous navigation is successfully carried out via the use of odometry and cameras properly attached to the robot structure. Preliminary field tests with the prototype operating on a cotton farm are presented to show the performance and feasibility of the electro-mechanical design for navigation in row crops.

关键词： Mobile robots Wheels Robot sensing systems Cotton Inspection

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Polarization Converter Metasurface Using Machine Learning Methods for Bandwidth Enhancement

Polarization Converter Metasurface Using Machine Learning Me...

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International Conference on Modern Circuits and Systems Technologies (MOCAST)

作者： David Chatzichristodoulou Photos Vryonides Symeon Nikolaou Dimitra-Danai Varsou Maria Antoniou Dimitris Mintis Antreas Afantitis Frederick Research Center RF an Microwave Solutions LTD Nicosia Cyprus Dept. Electrical Computer Engineering and Informatics Frederick Research Center Frederick University Nicosia Cyprus NovaMechanics Ltd Nicosia Cyprus

ISBN: (数字)9798350385427

ISBN: (纸本)9798350385434

This manuscript presents the design of a polarization converter metasurface (MTS) where Machine Learning (ML) and Deep Learning (DL) methods were used, to enhance its bandwidth. The MTS is implemented with a periodic array of multi-layered cells with chiral geometry that supports asymmetric transmission. Any impingent x-polarized wave is transmitted as a y-polarized wave, and any incident y-polarized wave is effectively reflected. In order to increase the frequency range where the incident $\vert \mathbf{Ex} \vert$ field over the transmitted $\vert \mathbf{Ey} \vert$ field (Tyx) is higher than 90% and the associated Rxx which is the ratio of the incident $\vert \mathbf{Ex} \vert$ over the transmitted $\vert \mathbf{Ex} \vert$ is less than -10 dB, the Rxx plots vs frequency were used to train an artificial neural network (ANN). The trained ANN was used to optimize the cell's geometric dimensions to create a MTS response with more than 90% conversion rate (Tyx>90%), in the frequency range from 6.5 to 12.5 GHz, resulting in more than 60% fractional bandwidth.

关键词： Geometry Deep learning Circuits and systems Bandwidth Artificial neural networks Metasurfaces Frequency conversion

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Modeling and Analyzing Server System with Rejuvenation through SysML and Stochastic Reward Nets

Modeling and Analyzing Server System with Rejuvenation throu...

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International Conference on Availability, Reliability and Security, ARES

作者： Ermeson C. Andrade Fumio Machida Dong-Seong Kim Kishor S. Trivedi Informatics Center Federal University of pernambuco (UFPE) Recife Pernambuco Brazil Department of Electrical and Computer Engineering Duke University Durham NC USA Service Platforms Research Laboratories NEC Corporation Kawasaki Japan

High-availability assurance of server systems is becoming an important issue, since many mission-critical applications are implemented on server systems. To achieve high-availability, software rejuvenation is a practical technique to reduce unexpected downtime caused by software aging in software applications running on server systems. Although analytic models of software rejuvenation are well-studied, such analysis is not used in server system administration due to the complexity of modeling. In this paper, we present an availability modeling method for server system with software rejuvenation based on SysML that is used to describe system configurations and maintenance operations semi-formally. The proposed approach allows system administrators, who do not have expertise in availability modeling, to design and study the effects of different rejuvenation policies deployed in server systems. To show the applicability of the proposed modeling and evaluation process, a case study of a web application server is presented. We show the correctness of our modeling method by comparing the conventional models for condition-based and time-based software rejuvenation.

关键词： Tin Clocks Through-silicon vias Security Availability

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Multi-Objective Design of Compact Microwave Components with Data-Driven Surrogates and Pareto Front Decomposition

Multi-Objective Design of Compact Microwave Components with ...

引用

International Conference on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO)

作者： Adrian Bekasiewicz Slawomir Koziel John W. Bandler Faculty of Electronics Telecommunications and Informatics Gdansk University of Technology Gdansk Poland Engineering Optimization & Modeling Center Reykjavik University Reykjavik Iceland Department of Electrical and Computer Eng. McMaster University Hamilton ON Canada

The paper discusses low-cost multi-objective optimization of compact microwave components using variablefidelity EM simulation models and data-driven surrogates. Our approach builds upon a recently reported method where the initial approximation of the Pareto set is obtained by optimizing the kriging surrogate constructed from sampled data of the coarsediscretization EM model of the structure at hand, with selected designs further refined to obtain the high-fidelity Pareto set. The drawback of the method is a large number of training data samples required to set up the surrogate. Here, considerable savings concerning the training data set size are achieved by Pareto front decomposition based on auxiliary points identified along the front and setting up the kriging models in the corresponding subdomains. The key factor is that the total volume of the sub-domains is considerably smaller than the volume of the original domain. Our considerations are illustrated using a compact rat-race coupler with design optimization cost savings of 29- and 30-percent for two and three sub-domains, respectively.

关键词： Optimization Couplers Training data Microwave theory and techniques Radio frequency Numerical models Microwave FET integrated circuits

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The Deep Learning-based Intelligent System for Extracting Information from e-KTP

The Deep Learning-based Intelligent System for Extracting In...

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Software engineering and Information Technology (ICoSEIT), International Conference on

作者： Zaki Fuadi Kahlil Muchtar Muhammad Subianto Hammam Riza Maulisa Oktiana Nizamuddin Department of Informatics Universitas Syiah Kuala Banda Aceh Indonesia Dept. of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia National Research and Innovation Agency (BRIN) Jakarta Indonesia

This research implements an Intelligent Information System for Text Recognition on Indonesian Identity Cards (eKTP) based on Deep Learning architecture. The aim of this research is to develop a system capable of accurately and efficiently detecting and recognizing text on e-KTP images. The first phase of this research involves selecting ideal images from the e-KTP dataset. Subsequently, pre-processing is conducted to crop the image sides and merge them with background images to create a more diverse dataset and obtain the e-KTP image masks as training data. After selecting the ideal images, the total training data amounts to 144 images. The U-Net architecture is chosen as the deep learning method for image segmentation in this research, while for text detection and recognition, two neural networks, CRAFT and TRBA (TPS-ResNet-BiLSTM-Attention), are employed. The testing, based on accuracy values, Dice coefficients, and IoU for the segmentation process, results in a U-Net model accuracy of 99.52%. Text detection and recognition follow confidence values.

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Reconfigurable planar directional antennas printed on ferrimagnetic substrates

Reconfigurable planar directional antennas printed on ferrim...

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European Conference on Antennas and Propagation, EuCAP

作者： T. Zervos A. A. Alexandridis F. Lazarakis K. Dangakis C. G. Kakoyiannis E. Varouti J. C. Vardaxoglou Institute of Informatics & Telecommunications National Centre for Scientific Research “Demokritos” Athens Greece School of Electrical & Computer Engineering National Technical University of Athens Greece Institute for Adv. Materials Physicochem. Processes Nanotech. & Microsystems NCSR “Demokritos” Athens Greece School of Electronic Electrical and Systems Engineering Loughborough University UK

This paper presents two different printed directional antenna designs that use a ferrimagnetic compound (YIG) as part of their substrates. It investigates the influence of this material on the antenna radiation characteristics under the application of an external magnetic field. It was found that the proper application of the magnetic field in each design changes the antenna resonance and the radiation pattern. Especially in the second proposed design the polarization characteristics are also changed and the antenna is reconfigured from linearly to circularly polarized.

关键词： Magnetic fields Antenna radiation patterns Microstrip antennas Substrates Directive antennas

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