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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Kapila W. S. Palitharathna Anna Maria Vegni Panagiotis D. Diamantoulakis Himal A. Suraweera Ioannis Krikidis Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Department of Industrial Electronic and Mechanical Engineering Roma Tre University Rome Italy Department of Applied Informatics University of Macedonia Thessaloniki Greece Department of Electrical and Electronic Engineering University of Peradeniya Peradeniya Sri Lanka

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

In this paper, we consider an indoor visible light communication (VLC) system with multiple "white" light emitting diodes serving to form overlapping wireless communication cells. In order to maintain seamless connectivity to mobile users, a handover procedure should be implemented. In particular, practical conditions such as blockages due to obstacles inside the room environment and the mobility of users can affect direct VLC connectivity. The use of reconfigurable intelligent surfaces (RISs) in optical wireless systems allows to exploit non-direct connectivity links, thus providing efficient communication links. In this paper, we present a proactive handover mechanism that exploits the presence of a RIS, in order to redirect the communication links in case of blockages. The proposed approach has been implemented both in hard and soft modes and assessed in terms of achievable data rate and handover latency for a user walking in a given reference room at different user speeds and blockage conditions. Our presented results and comparisons with conventional handover methods (i.e., without RIS) are helpful in showing the superiority of the presented algorithm.

关键词： Wireless communication Legged locomotion Circuits and systems Handover Reconfigurable intelligent surfaces Light emitting diodes Visible light communication

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Optical Wavelength Tunability of Negative Refractive Index Transmission Line Phase Shifter

Optical Wavelength Tunability of Negative Refractive Index T...

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Antennas and Propagation & USNC/URSI National Radio Science Meeting

作者： Asif Bilal Abdul Quddious Atsushi Kanno Tetsuya Kawanishi Marco A. Antoniades Stavros Iezekiel EMPHASIS Research Centre University of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Chair for RF and Photonics Engineering Technische Universität Dresden Dresden Germany Nagoya Institute of Technology Aichi Japan National Institute of Information and Communications Technology Tokyo Japan Waseda University Tokyo Japan Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto ON Canada

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

An optically reconfigurable phase shifter based on negative-refractive-index transmission line (NRI-TL) metamaterials is presented; the design is suitable for 5G antenna beam steering. Continuous tuning of the transmitted signal's phase is achieved by using varactor diodes for which the biasing is provided via an array of photodiodes placed on the back of the substrate. These are illuminated by a remote optical source whose wavelength can be tuned in the visible range, thus enabling indirect control of the varactor capacitance (and hence the phase shift) while also eliminating the need for a complex biasing network. Three different phases are achieved by illuminating the photodiode array with three different wavelengths (blue, green, and red). The compact size along with simplified biasing network introduced by the inclusion of the optical wavelength tunability has numerous applications in antenna and phased array technology, making the design a suitable candidate for 5G beam steering applications.

关键词： Phased arrays Varactors Beam steering Optical design Phase shifters Optical fiber networks Optical variables control

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The Implementation of TOGAF for Enterprise System Planning on XYZ Campus

The Implementation of TOGAF for Enterprise System Planning o...

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2023 International Conference on Networking, Electrical engineering, computer Science, and technology, IConNECT 2023

作者： Sirait, Tamsir Hasudungan Lumban Gaol, Ford Supangkat, Suhono Harso Ranti, Benny Bina Nusantara University Binus Graduate Program Computer Science Jakarta Indonesia Bina Nusantara University Computer Science Department Jakarta Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia Universitas Indonesia Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350331172

Universities can employ information technology as one means of achieving their goals and objectives. Universities can get advantages from information technology, such as effective resource management and information management for decision-making. However, don't forget that the campus must consider what technology is appropriate to assist them achieve their goals, particularly in the current industrial era 4.0 where technology is available with many different choices. The campus requires an enterprise architecture in order to design, manage, and coordinate information technology infrastructure, applications, and processes strategically and thoroughly. The adoption of enterprise information system architecture (EA) is also intended to improve the quality of services provided to internal and external stakeholders. In this case, Enterprise Architecture can help an organization to match its information technology resources with business processes and strategies to achieve their goals. This research was conducted using TOGAF ADM, also known as the Open Group Architecture Framework Architecture Development Method. This method offers best practices for creating enterprise architecture and emphasizes several steps that include creating an architectural vision, information systems, business architecture modeling to help XYZ campus manage all their information technology. © 2023 IEEE.

关键词： Information management

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Ka-Band 3D-Printed Dielectric GRIN Planar Lens Antenna with Beam Forming Capabilities

Ka-Band 3D-Printed Dielectric GRIN Planar Lens Antenna with ...

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Antennas and Propagation & USNC/URSI National Radio Science Meeting

作者： Adnan Nadeem Nosherwan Shoaib Photos Vryonides Antonis Papadakis Symeon Nikolaou Frederick Research Center Nicosia Cyprus Electrical Engineering Department Frederick University Nicosia Cyprus School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST) Islamabad Pakistan KYAMOS LTD Nicosia Cyprus

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

The manuscript describes the design of a planar dielectric graded index (GRIN) lens antenna for 5G applications operating in the 28 GHz Ka-band. The seven parallel slabs comprising the designed lens each have a distinct relative permittivity value. The required refractive indexes for each section are obtained through the arrangement of their relative permittivity values. The lens antenna demonstrates a maximum gain of 16.2 dBi in the broadside direction. The proposed lens antenna exhibits a beam-scanning capability of ± 30° and a gain exceeding 14 dBi in 60-degree scan range. The lens can be manufactured through the utilization of 3D-printing technology, employing low-loss high $\varepsilon_{r}$ dielectric filaments. In order to produce the distinct permittivity values for each slab, the infill percentage of the sections utilized during the 3D printing procedure will be varied accordingly.

关键词： Three-dimensional displays 5G mobile communication Refractive index Three-dimensional printing Dielectrics Slabs Permittivity

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Adaptive Autopilot: Constrained Drl for Diverse Driving Behaviors

Adaptive Autopilot: Constrained Drl for Diverse Driving Beha...

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International Conference on Intelligent Transportation

作者： Dinesh Cyril Selvaraj Christian Vitale Tania Panayiotou Panayiotis Kolios Carla Fabiana Chiasserini Georgios Ellinas CARS@Polito and Politecnico di Torino Torino Italy Department of Electrical and Computer Engineering KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus Department of Computer Science KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus Chalmers University of Technology Sweden

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

In pursuit of autonomous vehicles, achieving human-like driving behavior is vital. This study introduces adaptive autopilot (AA), a unique framework utilizing constrained-deep reinforcement learning (C-DRL). AA aims to safely emulate human driving to reduce the necessity for driver intervention. Focusing on the car-following scenario, the process involves (i) extracting data from the highD natural driving study and categorizing it into three driving styles using a rule-based classifier; (ii) employing deep neural network (DNN) regressors to predict human-like acceleration across styles; and (iii) using C-DRL, specifically the soft actor-critic Lagrangian technique, to learn human-like safe driving policies. Results indicate effectiveness in each step, with the rule-based classifier distinguishing driving styles, the regressor model accurately predicting acceleration, outperforming traditional car-following models, and C-DRL agents learning optimal policies for humanlike driving across styles.

关键词： Adaptation models Artificial neural networks Reinforcement learning Predictive models Semisupervised learning Autopilot Safety Driver behavior Intelligent transportation systems Vehicles

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An Effective Deep Learning Technique for Analyzing COVID - 19 Using X-Ray Images 15th

An Effective Deep Learning Technique for Analyzing COVID - 1...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Uma Maheswari, V. Aluvalu, Rajanikanth Guduri, Manisha Kantipudi, M. V. V. Prasad Department of Computer Science and Engineering Chaitanya Bharati Institute of Technology Telangana Hyderabad India Pune India School of Computing and Informatics University of Louisiana at Lafayette LafayetteLA70503 United States University Pune412115 India

ISBN: (纸本)9783031810794

The COVID - 19 disease is a extremely contagious viral infection with significant global health insinuations. COVID has a negative impact on the world economy. If positive patients are identified early, the proliferation of this pandemic infection can be slackened. COVID-19 disease prophecy is useful for finding the people with health issues who are at risk of COVID. The Deep Learning and machine learning approaches for COVID prediction using X-ray images have the possibility to be tremendously helpful in addressing the shortage of clinicians and doctors in rural areas. This research presents a deep layered Convolutional Neural Network (CNN) for recognizing the COVID-19 patients by training the system with the datasets of around 6000 chest X-ray images collected from various sources. We are categorized them as normal or COVID - impacted. Our model trained the X-ray images of chest to find these patients. And it also predicted well with the help of image analysis and deep learning by showcasing the better results comparing with the state-of-the-art methods in terms of the average accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： COVID-19

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Vessel's trim optimization using IoT data and machine learning models 13

Vessel's trim optimization using IoT data and machine learni...

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13th International Conference on Information, Intelligence, Systems and Applications, IISA 2022

作者： Panagiotakopoulos, Theodor Filippopoulos, Ioannis Filippopoulos, Christos Filippopoulos, Evangelos Lajic, Zoran Violaris, Antonis Chytas, Sotirios Panagiotis Kiouvrekis, Yiannis Hellenic Open University School of Science and Technology Greece University of Nicosia Business School Cyprus Cyprus International Institute of Management Nicosia Cyprus Infralabs Ltd Nicosia Cyprus Angelicoussis Group Athens Greece University of Thessaly Department of Electrical and Computer Engineering Greece University of Thessaly Department of Public and One Health Greece

ISBN: (数字)9781665463904

ISBN: (纸本)9781665463904

The shipping industry is an important source of greenhouse gas emissions, such as carbon dioxide, methane and nitrogen oxides. In the past few years, environmental and policy reasons dictate the immense reduction of greenhouse gas emissions in industries worldwide. Towards this direction, the shipping industry has focused on ship trim optimization in the last few years as an operational measure for better energy efficiency and thus a way to reduce consumption and energy-related emissions. In this paper, we present a machine learning solution to the problem of trim optimization. Specifically, we use Internet of Things (IoT) data for speed, draft, and trim in order to accurately predict shaft power. After our machine learning model is trained, we use its predicting capabilities to create the shaft power surface as part of the trim monitoring user interface of the maritime company infrastructure. © 2022 IEEE.

关键词： Machine learning

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Advancing general robotic manipulation with multimodal foundation models: An embodied AI paradigm

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Science China(Technological Sciences) 2025年第5期68卷 290-292页

作者： Shifeng HUANG He WANG Xing ZHOU Wenkai CHEN Haibin YANG Jianwei ZHANG Department of Mechanical and Aerospace Engineering Hong Kong University of Science and TechnologyHong Kong 999077China Foshan Institute of Intelligent Equipment Technology Foshan 528234China Foshan Huashu Robot Co. Ltd.Foshan 528234China Center on Frontiers of Computing Studies(CFCS) School of Computer SciencePeking UniversityBeijing 100871China Beijing Academy of Artificial Intelligence Beijing 100084China Department of Informatics Universität HamburgHamburg 20146Germany

Can current robotic technologies truly replicate the full scope and intricacies of human labour?In practice,the adoption of robots remains limited,especially in open,unstructured environments commonly encountered in everyday scenarios such as services,healthcare,agriculture,construction,and numerous other *** the perspective of general robotic manipulation,the challenges arise from three factors.(1)High operational barriers:human operators are obliged to master specialized robotic programming languages and gain a deep understanding of the tasks at *** tasks need to be broken down into action-level robotic programs,which results in high labour costs.(2)Limited autonomous task execution:robots lack the capability to independently plan and execute actions required to achieve the target *** limitation renders them unsuitable for deployment in open,unstructured environments that demand sophisticated interaction and seamless collaboration with humans.

关键词： multimodal foundation models autonomous task execution robotic manipulationthe general robotic manipulation robotic programming language embodied AI operational barriers robotic technologies

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Mobile Vision Transformer for Surface Defect Classification from A Tiny Dataset 14

Mobile Vision Transformer for Surface Defect Classification ...

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14th International Conference on Information and Communication technology and System, ICTS 2023

作者： Permatasari, Ghaluh Indah Pao, Hsing-Kuo Pribadi, Rudy Cahyadi Hario Iqbal, Mohammad National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei106 Taiwan University of Bhayangkara Department of Informatics Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Mathematics Surabaya60111 Indonesia

ISBN: (纸本)9798350312164

Surface defect classification is one pivotal step during the last product inspection before selling it to the market. Indeed, we want to serve our product to the customer in good condition. Speaking of smart manufacturing, existing studies on hot-rolled steel strip surface defect classification used deep learning models, which are very costly in terms of hardware, parameters, and dataset size. In this work, we propose a finetuned lightweight model from the Mobile Vision Transformer (MobileViT) to efficiently classify the surface defect of hot-rolled steel strips from a tiny data set. In this study, we experimented on a public benchmark dataset for surface defects of hot-rolled steel strip classification. The results showed that the proposed model can predict the defect accurately with fewer parameters and a smaller dataset than the SOTA ones. © 2023 IEEE.

关键词： Classification (of information)

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Comparison of *** and Spring Boot in Web Development 15

Comparison of *** and Spring Boot in Web Development

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15th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2023

作者： Novac, Ovidiu Constantin Ghiurau, David Novac, Mihaela Cornelia Gordan, Cornelia Emilia Oproescu, Mihai Bujdoso, Gyongyi Mihalca, Vlad Ovidiu University of Oradea Electrical Engineering and Information Technology Faculty Department of Computers and Information Technology Oradea Romania University of Oradea Management in Information Technology Electrical Engineering and Information Technology Faculty Oradea Romania University of Oradea Electrical Engineering and Information Technology Faculty Department of Electrical Engineering Oradea Romania University of Oradea Electrical Engineering and Information Technology Faculty Department of Electronics and Telecommunications Oradea Romania University of Pitesti Faculty of Electronics Communication and Computer Science Department of Electronics Computers and Electrical Engineering Pitesti Romania University of Debrecen Faculty of Informatics Department of Computer Science and Library and Information Science Debrecen Hungary School of Engineering Sciences University of Oradea Electrical Engineering and Information Technology Faculty Oradea Romania

ISBN: (纸本)9798350321388

In this paper we present two types of server implementation, we will look at the advantages and disadvantages of each technology. *** server application, built with ***, a single threaded server which will treat the requests in an asynchronous manner, with a non-blocking principle, whilst Spring Boot is a more robust and more common approach of a server technology with the benefits of having a strongly typed architecture and multiple threads available. These types of application will behave the same, making almost impossible to tell the difference between a *** and a Spring Boot web server. © 2023 IEEE.

关键词： Node.Js non-blocking single-multi threaded Spring Boot web server

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