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International Conference on Advanced Communication Technologies and Networking (CommNet)

作者： Tsachrelias Konstantinos Chrisostomos-Athanasios Katsigiannis Vasileios Kokkinos Apostolos Gkamas Christos Bouras Philippos Pougioutas Computer Engineering and Informatics Department University of Patras Patras Greece Department of Chemistry University of Ioannina Ioannina Greece Computer Science Department University of Cyprus Nicosia Cyprus

ISBN: (数字)9798350367027

ISBN: (纸本)9798350367034

The evolution of 5G networks is driving advancements in data rates, latency reduction, and connectivity, with adaptive beamforming emerging as a core technology to enhance spectral efficiency. This study demonstrates how integrating beamforming with spatial filtering can effectively optimize signal quality in 5G MIMO networks. Through simulations, we show that our approach achieves significant improvements in Signal-to-Noise Ratio (SNR) by optimizing beam directions. Specifically, results indicate that optimal beamforming angles can yield SNR values as high as 78 dB, substantially outperforming lower SNRs observed at less favorable angles. These findings underscore the potential of combined beamforming and spatial filtering to enhance communication reliability and network performance, particularly in high-density settings.

关键词： Adaptation models Adaptive systems Array signal processing 5G mobile communication Spectral efficiency Filtering Communications technology Reliability Signal to noise ratio

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Competing Mutual Information Constraints with Stochastic Competition-based Activations for Learning Diversified Representations

arXiv

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arXiv 2022年

作者： Panousis, Konstantinos P. Antoniadis, Anastasios Chatzis, Sotirios Department of Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

This work aims to address the long-established problem of learning diversified representations. To this end, we combine information-theoretic arguments with stochastic competition-based activations, namely Stochastic Local Winner-Takes-All (LWTA) units. In this context, we ditch the conventional deep architectures commonly used in Representation Learning, that rely on non-linear activations;instead, we replace them with sets of locally and stochastically competing linear units. In this setting, each network layer yields sparse outputs, determined by the outcome of the competition between units that are organized into blocks of competitors. We adopt stochastic arguments for the competition mechanism, which perform posterior sampling to determine the winner of each block. We further endow the considered networks with the ability to infer the sub-part of the network that is essential for modeling the data at hand;we impose appropriate stick-breaking priors to this end. To further enrich the information of the emerging representations, we resort to information-theoretic principles, namely the Information Competing Process (ICP). Then, all the components are tied together under the stochastic Variational Bayes framework for inference. We perform a thorough experimental investigation for our approach using benchmark datasets on image classification. As we experimentally show, the resulting networks yield significant discriminative representation learning abilities. In addition, the introduced paradigm allows for a principled investigation mechanism of the emerging intermediate network representations. © 2022, CC BY.

关键词： Stochastic systems

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Parameter Tuned Deep Learning Based Traffic Critical Prediction Model on Remote Sensing Imaging

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computers, Materials & Continua 2023年第5期75卷 3993-4008页

作者： Sarkar Hasan Ahmed Adel Al-Zebari Rizgar R.Zebari Subhi R.M.Zeebaree Computer Networks Department Sulaimani Polytechnic UniversitySulaimaniIraq Information Technology Department Technical College of Informatics-AkreDuhok Polytechnic UniversityIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Remote sensing(RS)presents laser scanning measurements,aerial photos,and high-resolution satellite images,which are utilized for extracting a range of traffic-related and road-related *** has a weakness,such as traffic fluctuations on small time scales that could distort the accuracy of predicted road and traffic *** article introduces an Optimal Deep Learning for Traffic Critical Prediction Model on High-Resolution Remote Sensing Images(ODLTCP-HRRSI)to resolve these *** presented ODLTCP-HRRSI technique majorly aims to forecast the critical traffic in smart *** attain this,the presented ODLTCP-HRRSI model performs two major *** the initial stage,the ODLTCP-HRRSI technique employs a convolutional neural network with an auto-encoder(CNN-AE)model for productive and accurate traffic ***,the hyperparameter adjustment of the CNN-AE model is performed via the Bayesian adaptive direct search optimization(BADSO)*** experimental outcomes demonstrate the enhanced performance of the ODLTCP-HRRSI technique over recent approaches with maximum accuracy of 98.23%.

关键词： Remote sensing images traffic prediction deep learning smart cities intelligent transportation systems

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Penetration of Distributed Generation in Microgrids: Characteristics and Challenges

Penetration of Distributed Generation in Microgrids: Charact...

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International Universities Power engineering Conference (UPEC)

作者： Kypros Tillyros Nicholas G. Christofides Michael Komodromos Department of Electrical Engineering Computer Engineering and Informatics Frederick University Nicosia Cyprus

The exploitation of sustainable distributed energy sources is associated with the energy resilience and power optimisation of power grids. This study divides the energy sector of urban areas into isolated and non-isolated topologies and attempts to review the application of microgrids within the two. In addition, it investigates methods to optimise power quality with the integration of multi-renewable generation to the system and discusses on the feasibility towards islanded operating microgrids. The proposed work is a result of a careful evaluation of the current literature on the topic. Consequently, the outcome of the given study is anticipated to facilitate future work on Microgrid implementation functioning in islanded mode.

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Feasibility of direct quantum communications between the UK and Ireland via 224 km of underwater fibre

Feasibility of direct quantum communications between the UK ...

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British and Irish Conference on Optics and Photonics, BICOP 2023

作者： Amies-Kin, Ben Schatz, Karolina P. Duan, Haofan Biswas, Ayan Bailey, Jack Felvinti, Adrian Winward, Jaimes Dixon, Mike Minder, Mariella Kumar, Rupesh Albosh, Sophie Lucamarini, Marco School of Physics Engineering and Technology York Centre for Quantum Technologies Institute for Safe Autonomy University of York YorkYO10 5FT United Kingdom EuNetworks Fiber UK Limited 5 Churchill Place LondonE14 5HU United Kingdom Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol3036 Cyprus

Quantum key distribution is required for unconditionally secure communications against an eavesdropper with a powerful quantum computer. We present the first QKD feasibility study over long-haul submarine fibre, betwe... 详细信息

关键词： Quantum cryptography

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Assessing the Maturity of Blockchain-based Supply Chain Management and Logistics: Comprehensive Examination of the Current Situation 6

Assessing the Maturity of Blockchain-based Supply Chain Mana...

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6th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Sener, Umut Çaldag, Murat Tahir Gökalp, Ebru Graduate School of Informatics Middle East Technical University Ankara Turkey Department of Technology and Knowledge Management Baskent University Ankara Turkey Department of Computer Engineering Hacettepe University Ankara Turkey

Blockchain technology, a transformative force in digital transactions, has emerged as a significant enabler of secure, transparent, and traceable operations within supply chain management and logistics (SCML). Its immutable nature facilitates enhanced management of SCML activities by seamlessly integrating information flow throughout the value chain, and substantially increasing data integrity and operational reliability. While organizations are attracted to these capabilities, they still lack comprehensive guidelines to fully benefit from blockchain in SCML. There is a fundamental need to assist organizations in assessing and enhancing their blockchain-based SCML capabilities. Maturity models (MMs) are tools that help organizations assess and improve their processes, providing step-by-step guidelines from basic to advanced levels of maturity. Therefore, this study aims to identify and analyze MMs focused on blockchain-based SCML. An extensive systematic literature review (SLR) was conducted, and thirteen relevant studies were identified and evaluated against a comprehensive set of quality criteria. The analysis revealed that none of the existing MMs fully satisfied all criteria, highlighting a significant gap in the field. This research provides a thorough systematic analysis of MMs for blockchain-based SCML, offering an in-depth view of their levels, dimensions, research focuses, domains, industry targets, and their quality evaluation. The significance of this study lies in identifying the necessity for an MM specifically designed for blockchain-based SCML, addressing a critical gap in the current literature. These findings contribute to the growing body of knowledge on blockchain integration in SCML and provide a foundation for future research. © 2024 The Authors. Published by Elsevier B.V.

关键词： Data integrity

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Multifunctional Switchable Filter Using Shorted Coupled-Line Sections 52

Multifunctional Switchable Filter Using Shorted Coupled-Line...

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52nd European Microwave Conference, EuMC 2022

作者： Shirazi, Minahil Chatzichristodoulou, David Quddious, Abdul Shoaib, Nosherwan Psychogiou, Dimitra Nikolaou, Symeon Vryonides, Photos Frederick Research Center Cyprus Pakistan Rf and Microwave Solutions Ltd Cyprus Kios Research and Innovation Center of Excellence University of Cyprus Cyprus School of Engineering University College Cork Ireland Tyndall National Institute Ireland Frederick University Dept. of Electrical and Computer Engineering and Informatics Cyprus

ISBN: (数字)9782874870699

ISBN: (纸本)9782874870699

This paper presents a novel multifunctional RF filter based on RF-switched parallel-coupled line sections. It demonstrates three different reconfigurable responses namely a bandpass filter (BPF) response, a bandstop filter (BSF) response and a dual-band (DBPF) response. Reconfigurability is realized by turning on and off four p-i-n diodes that are placed at specific locations and either connect or disconnect a uniform transmission line and shorted parallel coupled-line sections to the main RF signal path. To verify the validity of the proposed design, a switchable filter prototype is fabricated and measured. For the BPF response, the measured 3-dB fractional bandwidth (FBW) is 43.48 % (1.75-2.75 GHz) with a passband insertion loss of 0.8 dB. For the BSF response the measured 3-dB FBW is 36.52 % (1.90-2.74 GHz) with an in-band suppression level above 12 dB. Finally for the dual-band BPF response, the measured 3-dB FBWs of the two bands are 18.2% and 18.5% respectively. © 2022 European Microwave Association (EuMA).

关键词： Notch filters

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SNR and RSSI Based an Optimized Machine Learning Based Indoor Localization Approach:Multistory Round Building Scenario over LoRa Network

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computers, Materials & Continua 2024年第8期80卷 1927-1945页

作者： Muhammad Ayoub Kamal Muhammad Mansoor Alam Aznida Abu Bakar Sajak Mazliham Mohd Su’ud Malaysian Institute of Information Technology(MIIT) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Computing and Informatics Multimedia UniversityCyberjaya63100Malaysia Depertment of Computer Science DHA Suffa UniversityKarachiSindh75500Pakistan Riphah Institute of System Engineering(RISE) Faculty of ComputingRiphah International UniversityIslamabad46000Pakistan Malaysian France Institute(MFI) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneyUltimoNSW 2007Australia

In situations when the precise position of a machine is unknown,localization becomes *** research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-based *** order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over LoRa technology,this study proposed an optimized machine learning(ML)based *** signal strength indicator(RSSI)data from the sensors at different positions was first gathered via an experiment through the LoRa network in a multistory round layout *** noise factor is also taken into account,and the signal-to-noise ratio(SNR)value is recorded for every RSSI *** study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference *** findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.

关键词： Indoor localization MKNN LoRa machine learning classification RSSI SNR localization

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High-Performance and Low-Cost Approximation of ANN Sigmoid Activation Functions on FPGAs

High-Performance and Low-Cost Approximation of ANN Sigmoid A...

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International Conference on Modern Circuits and Systems Technologies (MOCAST)

作者： Kostantinos Tatas Michalis Gemenaris Department of Electrical Engineering Computer Engineering and Informatics Frederick University Nicosia Cyprus

Neural network implementations on FPGAs have received significant attention from the research community due to their superior performance in tasks such as computer vision and the need to perform them on edge devices. Most efforts have focused on architecture optimizations such as pruning and operations such as the multiplications and additions with less attention on the ANN activation function. In this paper a hardware implementation of an artificial neural network on Field Programmable Gate Arrays (FPGA) is presented. A digital system architecture is designed with the purpose of reducing the delay of implementation and minimizing the LUTs in the FPGA. The designed architecture is described using Very High-Speed Integrated Circuits Hardware Description Language (VHDL). The proposed method utilizes a known piecewise linear approximation of the sigmoid function, and additionally exploits properties of fixed-point binary number representation to efficiently reduce delay and the amount of LUTS required Compared with previously published implementations of the same function and FPGA technology, the proposed method is shown to achieve a reduction between 33% and 95% in LUTs with no reduction in accuracy.

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To Risk Analyse, or Not to Risk Analyse: That’s the Question 18th

To Risk Analyse, or Not to Risk Analyse: That’s the Ques...

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18th IFIP WG 11.12 International Symposium on Human Aspects of Information Security and Assurance, HAISA 2024

作者： Bergström, Erik Andersson, Simon Lundgren, Martin School of Engineering Jönköping University Jönköping Sweden Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden School of Informatics University of Skövde Skövde Sweden

ISBN: (纸本)9783031725586

Risk analysis is a key activity for organisations that are looking to protect their valuable information assets against threats, such as malicious actors. It is one of the essential parts of risk management and is used to justify and prioritise what assets require the attention of which potential security controls. Risk management, and more specifically, risk analysis, is an activity that should be performed continuously. However, recent studies indicate that this is not always the case. As such, this paper investigates risk analysis as it is performed in practice in different Swedish public sector organisations. The results are based on semi-structured interviews with 17 senior security experts, an analysis of standards, and a national method support aiming to fill the gap between standard and practice. The results are presented in three themes: how, when and why risk analysis is performed. Of note, we identify that there is an issue of overlooking specific assets or systems when establishing an organisational-wide risk profile and a general recognition of the necessity for risk analysis, albeit not always in alignment with a classic risk analysis. © IFIP International Federation for Information Processing 2025.

关键词： Cybersecurity Information security Risk analysis

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