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6th World Symposium on Communication engineering, WSCE 2023

作者： Stergiou, Konstantinos D. Ishibashi, Yutaka Goudos, Sotirios K. Lagkas, Thomas Sarigiannidis, Panagiotis Psannis, Konstantinos E. University of Macedonia Department of Applied Informatics Thessaloniki Greece Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan Aristotle University of Thessaloniki Department of Physics Thessaloniki Greece International Hellenic University Department of Computer Science Kavala Greece University of Western Macedonia Department of Informatics and Telecommunications Engineering Kozani Greece

ISBN: (纸本)9798350339505

This paper discusses the use of federated learning as a method for optimizing decision-making in communication systems. Federated learning is a machine learning technique that enables the training of models on decentralized data, allowing for the collection and analysis of data from multiple sources while maintaining the privacy and security of the data. This approach is particularly useful in communication systems, as it allows for the optimization of decision-making across a wide range of devices and networks. The paper examines the advantages of federated learning, including the ability to collect a large amount of data from a diverse range of devices, the protection of sensitive data, and the ability to adapt to changing conditions in real-time. The paper also provides specific examples of how federated learning can be used in the optimization of mobile networks and content delivery. The conclusion highlights the growing importance of federated learning in improving communication systems. © 2023 IEEE.

关键词： Learning systems

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Handwriting recognition on mobile devices - State of the art technology, usability and business analysis

Handwriting recognition on mobile devices - State of the art...

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作者： Holzinger, Andreas Basic, Lamija Peischl, Bernhard Debevc, Matjaz Research Unit Human-Computer Interaction Institute for Medical Informatics Medical University of Graz Graz Austria Softnet Graz Austria Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia

ISBN: (纸本)9789898425706

The software company FERK-Systems has been providing mobile health care information systems for various German medical services (e.g. Red Cross) for many years. Since handwriting is an issue in the medical and health care domain, a system for handwriting recognition on mobile devices has been developed within the last few years. While we have been continually improving the degree of recognition within the system, there are still changes necessary to ensure the reliability that is imperative in this critical domain. In this paper, we present the major improvements made since our presentation at the ICE-B 2010, along with a recent real-life usability evaluation. Moreover, we discuss some of the advantages and disadvantages of current systems, along with some business aspects of the vast, and growing, mobile handwriting recognition market.

关键词： Usability engineering

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On Min-Max Graph Balancing with Strict Negative Correlation Constraints 34

On Min-Max Graph Balancing with Strict Negative Correlation ...

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34th International Symposium on Algorithms and Computation, ISAAC 2023

作者： Kuo, Ting-Yu Chen, Yu-Han Frosini, Andrea Hsieh, Sun-Yuan Tsai, Shi-Chun Kao, Mong-Jen Dept. of Computer Science National Yang-Ming Chiao-Tung University Hsinchu Taiwan Dept. of Computer Science and Information Engineering National Cheng-Kung University Tainan Taiwan Dept. of Mathematics and Informatics University of Florence Italy Dept. of Computer Science and Information Engineering National Chi-Nan University Puli Taiwan

ISBN: (纸本)9783959772891

We consider the min-max graph balancing problem with strict negative correlation (SNC) constraints. The graph balancing problem arises as an equivalent formulation of the classic unrelated machine scheduling problem, where we are given a hypergraph G = (V, E) with vertex-dependent edge weight function p: E × V 7→ Z≥0 that represents the processing time of the edges (jobs). The SNC constraints, which are given as edge subsets C1, C2, . . ., Ck, require that the edges in the same subset cannot be assigned to the same vertex at the same time. Under these constraints, the goal is to compute an edge orientation (assignment) that minimizes the maximum workload of the vertices. In this paper, we conduct a general study on the approximability of this problem. First, we show that, in the presence of SNC constraints, the case with maxe∈E |e| = maxi |Ci| = 2 is the only case for which approximation solutions can be obtained. Further generalization on either direction, e.g., maxe∈E |e| or maxi |Ci|, will directly make computing a feasible solution an NP-complete problem to solve. Then, we present a 2-approximation algorithm for the case with maxe∈E |e| = maxi |Ci| = 2, based on a set of structural simplifications and a tailored assignment LP for this problem. We note that our approach is general and can be applied to similar settings, e.g., scheduling with SNC constraints to minimize the weighted completion time, to obtain similar approximation guarantees. Further cases are discussed to describe the landscape of the approximability of this prbolem. For the case with |V | ≤ 2, which is already known to be NP-hard, we present a fully-polynomial time approximation scheme (FPTAS). On the other hand, we show that the problem is at least as hard as vertex cover to approximate when |V | ≥ 3. © Ting-Yu Kuo, Yu-Han Chen, Andrea Frosini, Sun-Yuan Hsieh, Shi-Chun Tsai, and Mong-Jen Kao;licensed under Creative Commons License CC-BY 4.0.

关键词： Computational complexity

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Towards High-Performance and Power-Efficient Optical NoCs Using Silicon-in-Silica Photonic Components

Towards High-Performance and Power-Efficient Optical NoCs Us...

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International Workshop on Interconnection Network Architectures: On-Chip, Multi-Chip (INA-OCMC)

作者： Elena Kakoulli Vassos Soteriou Charalambos Koutsides Kyriacos Kalli Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9781479918713

Networks-on-Chips (NoCs) are meeting the growing inter-tile communication needs of multicore chips. However, achieving system scalability by utilizing hundreds of cores on-chip requires high performance, yet energy-efficient on-chip interconnects. As electrical interconnects are marred by high energy-to-bandwidth costs, threatening multicore scalability, on-chip nanophotonics, which offer high throughput, yet energy-efficient communication, are an alternative attractive solution. In this paper we consider silicon nanophotonic components that are embedded completely within the silica (SiO 2 ) substrate as opposed to prior-art that utilizes die on-surface silicon nanophotonics. As nanophotonic components now reside in the silica substrate's subsurface, a greater portion of a chip's real estate can be utilized by cores and routers, while non-obstructive interconnect geometries offering higher network throughput can be implemented. First, we show using detailed simulations based on commercial tools that such silicon-in-silica (SiS) structures are feasible, and then demonstrate our proof of concept by utilizing a hybrid SiS-based photonic mesh-diagonal links topology that provides both higher effective throughput and throughput-to-power ratio versus prior-art.

关键词： Optical waveguides Ports (computers) Topology Nanophotonics Silicon computer architecture

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Structure and magnetism of LSMO/BTO/MgO/LSMO multilayers

Structure and magnetism of LSMO/BTO/MgO/LSMO multilayers

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作者： Pawlak, J. Zywczak, A. Szwachta, G. Kanak, J. Gajewska, M. Przybylski, M. Faculty of Physics and Applied Computer Science Faculty of Informatics Electronics and Telecommunications AGH University of Science and Technology Kraków Poland Academic Centre for Materials and Nanotechnology Faculty of Informatics Electronics and Telecommunications AGH University of Science and Technology Kraków Poland Faculty of Metals Engineering and Industrial Computer Science Faculty of Informatics Electronics and Telecommunications AGH University of Science and Technology Kraków Poland Department of Electronics Faculty of Informatics Electronics and Telecommunications AGH University of Science and Technology Kraków Poland

A multiferroic tunnel junction (MFTJ) is a promising device for future memory systems with discrete and different logic states which are controlled by a combination of electric and magnetic fields. The goal of ongoing research is to present ferroelectric and ferromagnetic properties, especially at room temperature (RT), represented as high values of tunnel electroresistance (TER) and tunnel magnetoresistance (TMR). A key aspect is the appropriate preparation of a sample allowing epitaxial growth. The thin layers were prepared by pulsed laser deposition on atomically smooth monocrystalline SrTiO3 (STO) substrates. The ferromagnetic metal layers La0.67Sr0.33MnO3 (LSMO) are separated by a layer of a ferroelectric insulator - BaTiO3 (BTO). The same structure of LSMO, BTO and STO (perovskite) and a similar lattice constant make it possible to obtain high-quality heterostructures. Magnetic measurements confirm differences in the magnetic coercivity of the top and bottom LSMO layer, which allows to obtain their parallel and antiparallel magnetization orientation. A modification of the interfaces of BTO by thin MgO layer enables an increase in the value of the TER effect. © 2018 Polish Academy of Sciences. All rights reserved.

关键词： Magnesia

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Equipment Parameter Investigation for a Proposed Power Conductor Hot Spot Identification system

Equipment Parameter Investigation for a Proposed Power Condu...

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International Conference on Modern Power Systems (MPS)

作者： Alexis Polycarpou Michael Komodromos Kyriacos Kalli Maria C. Argyrou Andreas Ioannou Deparment of Electrical Computer Engineering and Informatics Frederick University Frederick Research Center Nicosia Cyprus Department of Electrical Engineering / Computer Engineering and Informatics PhOSLab Cyprus University of Technology Limassol Cyprus

Reliability, efficiency and continuity of power energy supplied is an area which receives increasing attention as the main infrastructure of power transmission and distribution systems in many countries is ageing. Hot spot related cable failures and power interruptions have a big financial impact on the power provider. The operational parameters of a method to identify in real time hot spots on cables is investigated in this paper, which can result to timely fault prevention. This can be achieved through exploiting the optical sensing capabilities of the existing optical fibre on-grid network. The resulting parameters aim to be advantageous for the system as they increase accuracy and will enable the Remote, automated, continuous, and real time monitoring of the grid infrastructure integrity.

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Self-Correcting Time Synchronization Support for Wireless Sensor Networks Targeting Applications on Internet of Things

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IFAC-PapersOnLine 2016年第30期49卷 355-360页

作者： Bruscato, Leandro T. Freitas, Edison P. Heimfarth, Tales Federal University of Rio Grande do Sul Porto AlegreRS Brazil Federal University of Rio Grande do Sul School of Engineering and Informatics Institute Porto AlegreRS Brazil Federal University of Lavras Computer Science Department LavrasMG Brazil

The Internet of Things is a collection of devices that communicate by exchanging a variety of data among them, in which time synchronization is needed for meaningful information creation and transmission. The robustness of the data transmissions becomes an issue, since most of these devices use wireless communication. This paper focuses in proposing and implementing a time synchronization service for low-power wireless sensor networks using low frequency real-time clocks in each node. This work presents the design, implementation and test of an adaptive algorithm, making the timing of the clocks converge as quickly as possible and after this convergence, keeping them most similar as possible. The goal is to achieve the best method that ensures right timing and still having low energy consumption. Experimental results provide evidence of the success in meeting this goal. © 2016

关键词： Low power electronics Adaptive algorithms Clocks Energy utilization Information services Internet of things Sensor nodes Synchronization Wireless sensor networks Wireless telecommunication systems Latency Low Power Real time Self Correcting Time synchronization

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Insurance Fraud Detection using Machine Learning

Insurance Fraud Detection using Machine Learning

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Information and Communication Technologies (ZCICT), Zimbabwe Conference of

作者： Machinya Tongesai Godfrey Mbizo Kudakwashe Zvarevashe Champion Analytics & Informatics Department Faculty of Computer Engineering Informatics and Communication University of Zimbabwe Harare Zimbabwe

ISBN: (纸本)9781665475778

Many insurance companies today deal with the issue of fraudulent insurance claims, which results in significant yearly financial loss. Since the losses are covered by raising policyholders’ premium costs, these frauds have a negative impact on society. The traditional claim investigation procedure has also been blamed for producing unreliable conclusions because it is time-consuming and laborious. Therefore, using machine learning and the XGBoost method, we construct an automated fraud detection application framework in this study. Accurately identifying fraud claims in a shorter amount of time is the goal. Data analysis is utilized throughout the process to validate, sanitize, and extract the pertinent data. As a result, the insurance firm can retain its reputation outside by employing this structure and has a reliable relationship with clients that they can share.

关键词： Machine learning algorithms Data analysis Costs Insurance Machine learning Fraud Information and communication technology

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Information gain as a feature selection method for the efficient classification of influenza based on viral hosts

Information gain as a feature selection method for the effic...

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World Congress on engineering, WCE 2014

作者： Shaltout, Nermeen A. El-Hefnawi, Mahmoud Rafea, Ahmed Moustafa, Ahmed Computer Science and Engineering Department School of Sciences and Engineering American University of Cairo New Cairo 11835 Cairo Egypt Informatics and Systems Department Biomedical Informatics and Chemoinformatics Group Centre of Excellence for Advanced Sciences Tahrir Street 12311 Cairo Egypt Biology Department School of Sciences and Engineering American University of Cairo New Cairo 11835 Cairo Egypt

ISBN: (纸本)9789881925275

The paper demonstrates the improvement in Influenza A classification based on viral host when applying feature selection on classical machine learning techniques. The impact of using the most informative DNA positions on classifier efficiency and performance was measured. Both decision trees (DTs) and neural networks (NNs) were used. The experiments were conducted on DNA sequences belonging to the PB1 and HA segments of subtypes H1 and H5 respectively. Sequences from each segment were further divided into human and nonhuman hosts prior to classification analysis. Accuracy, sensitivity, specificity, precision and time were used as performance measures. Extracting the best hundred informative positions with information gain increased classification efficiency by 90% for both classifiers, without compromising performance significantly. NNs performed better on both DNA segments than DTs, when decreasing the number of informative positions below a hundred. The classification speed of NNs was improved vastly compared to DTs, when classifying the H1, PB1 segment.

关键词： Feature Selection

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Big Data Bot with a Special Reference to Bioinformatics

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computers, Materials & Continua 2023年第5期75卷 4155-4173页

作者： Ahmad M.Al-Omari Shefa M.Tawalbeh Yazan H.Akkam Mohammad Al-Tawalbeh Shima’a Younis Abdullah A.Mustafa Jonathan Arnold Biomedical Systems and Informatics Engineering Department Yarmouk UniversityIrbid21163Jordan Department of Medicinal Chemistry and Pharmacognosy Yarmouk UniversityIrbid21163Jordan Department of Electrical Computer and Software EngineeringUniversity of Ontario Institute of TechnologyOshawaL1H7K4Canada Department of Mechanical Engineering University of MosulMosul41001Iraq Genetics Department University of GeorgiaAthens30602GAUSA

There are quintillions of data on deoxyribonucleic acid(DNA)and protein in publicly accessible data banks,and that number is expanding at an exponential *** scientific fields,such as bioinformatics and drug discovery,rely on such data;nevertheless,gathering and extracting data from these resources is a tough *** data should go through several processes,including mining,data processing,analysis,and *** study proposes software that extracts data from big data repositories automatically and with the particular ability to repeat data extraction phases as many times as needed without human *** software simulates the extraction of data from web-based(point-and-click)resources or graphical user interfaces that cannot be accessed using command-line *** software was evaluated by creating a novel database of 34 parameters for 1360 physicochemical properties of antimicrobial peptides(AMP)sequences(46240 hits)from various MARVIN software panels,which can be later utilized to develop novel ***,for machine learning research,the program was validated by extracting 10,000 protein tertiary structures from the Protein Data *** a result,data collection from the web will become faster and less expensive,with no need for manual data *** software is critical as a first step to preparing large datasets for subsequent stages of analysis,such as those using machine and deep-learning applications.

关键词： Bioinformatics big data data extraction bot drug design

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