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An Explainable Artificial Intelligence model in the assessment of Brain MRI Lesions in Multiple Sclerosis using Amplitude Modulation - Frequency Modulation multi-scale feature sets 24

An Explainable Artificial Intelligence model in the assessme...

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24th International Conference on Digital Signal Processing, DSP 2023

作者： Nicolaou, Andria Kakas, Antonis Pattichis, Constantinos S. Pattichis, Marios S. Fotso, Kevin Loizou, Christos P. Pantzaris, Marios Department of Computer Science University of Cyprus Nicosia Cyprus Department of Electrical Engineering and Computer Engineering University of New Mexico United States Department of Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Cyprus Institute of Neurology and Genetics Nicosia Cyprus

ISBN: (纸本)9798350339598

The objective of this study was to implement an explainable artificial intelligence (AI) model with embedded rules to assess Multiple Sclerosis (MS) disease evolution based on brain Magnetic Resonance Imaging (MRI) multi-scale lesion evaluation. Amplitude Modulation-Frequency Modulation (AM-FM) features were extracted from manually segmented brain MS lesions obtained using MRI and were labeled with the Expanded Disability Status Scale (EDSS). Machine learning models were used to classify the MS subjects with a benign course of the disease and subjects with advanced accumulating disability. Rules were extracted from the selected model with high accuracy and then were modified to perform argumentation-based reasoning. It is demonstrated that the proposed explainable AI modeling can distinguish MS subjects and give meaningful information to track the progression of the disease. Future research will examine more subjects and add new feature sets and models. © 2023 IEEE.

关键词： Frequency modulation

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XMeta-OS: A Conceptual Framework for Unified Resource Management in Distributed Edge-Cloud Environments 3rd

XMeta-OS: A Conceptual Framework for Unified Resource Manag...

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3rd International Conference on Advances in Computing Research, ACR 2025

作者： Zacharioudakis, Eleftherios Kakoulli, Elena Evripidou, Salomi Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Pafos Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9783031876462

This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is possible. This approach offer a new GPU abstraction layer and dynamic edge-cloud allocation model that offer enhanced flexibility and resource utilization over existing systems like Kubernetes and OpenStack. By using likely sensitive data, the model applied cloud-pushed deployment model. XMeta-OS manages computer resources in real-time. Therefore, fulfilling high performance various needs. It allocates CPU and GPU in real-time to workloads requiring massive parallel processing, such as machine learning, scientific simulations, real-time data analytics, and transportation tasks. Fabrication in the laboratory of an edge-cloud environment can help to assess the scalability, fault tolerance and efficiency of the system. It showcases the overall architectural design of XMeta-OS. Changes to the kernel and security solutions for safe and effective distribution are suggested. This article presents the design of the XMeta-OS. The future of XMeta-OS entails usage and testing with which we see latency, energy, computation and other such measurements in labs. XMeta-OS is a solution to cost performance, emerging application, large-scale edge-cloud deployments, and distributed GPU-enabled infrastructures. Meta-Operating System in Edge-Cloud Continuum for dynamic resource management of GPU. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cluster computing

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Adaptive 360° Video Streaming Over Wireless Communication Channels 9

Adaptive 360° Video Streaming Over Wireless Communication C...

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9th International Conference on Frontiers of Signal Processing, ICFSP 2024

作者： Valiandi, Ioanna Pattichis, Marios S. Kyriacou, Efthyvoulos Panayides, Andreas S. VIDEOMICS Group CYENS Centre of Excellence Nicosia Cyprus University of New Mexico Department of Electrical and Computer Engineering AlbuquerqueNM United States Cyprus University of Technology Department of Electrical Eng. Computer Engineering and Informatics Limassol Cyprus

ISBN: (纸本)9798350353235

360° video streaming is one of the prevalent communication technologies for enhancing user experience and has thus seen widespread adoption in virtual and mixed reality applications. However, delivering content at scale while securing the quality of wirelessly communicated 360° videos in real-time poses significant challenges. 360° videos come in ultra-high definition, necessitate unprecedented bitrate demands and involve high encoding complexity. The time-varying nature of underlying wireless channels further introduces a destabilizing factor, calling for video systems to seamlessly adjust to varying bandwidth throughput to maintain adequate quality of service and experience. To address this issue, in this study, we have developed a multi-objective optimization framework for real-time video encoding adaptation. The objective is to optimize both video quality and encoding efficiency while minimizing the required bitrate, subject to real-time application constraints. To achieve this, we relied on generating (offline) precise forward prediction models of video quality, bitrate demands, and encoding time, that can be used to select the optimum encoding configuration in real-time. To validate our methods, we implemented an adaptive video encoding controller, and ran emulations employing actual network traces from 5G mobile video streaming scenarios, using the popular open-source x264 and x265 codecs for video encoding. A dataset of 4K omnidirectional videos at 30 frames per second was used. © 2024 IEEE.

关键词： Video streaming

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Fundamental Dynamics of Popularity-Similarity Trajectories in Real Networks

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Physical Review Letters 2024年第25期132卷 257401-257401页

作者： Evangelos S. Papaefthymiou Costas Iordanou Fragkiskos Papadopoulos Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology 3036 Limassol Cyprus.

Real networks are complex dynamical systems, evolving over time with the addition and deletion of nodes and links. Currently, there exists no principled mathematical theory for their dynamics—a grand-challenge open problem. Here, we show that the popularity and similarity trajectories of nodes in hyperbolic embeddings of different real networks manifest universal self-similar properties with typical Hurst exponents H≪0.5. This means that the trajectories are predictable, displaying antipersistent or “mean-reverting” behavior, and they can be adequately captured by a fractional Brownian motion process. The observed behavior can be qualitatively reproduced in synthetic networks that possess a latent geometric space, but not in networks that lack such space, suggesting that the observed subdiffusive dynamics are inherently linked to the hidden geometry of real networks. These results set the foundations for rigorous mathematical machinery for describing and predicting real network dynamics.

关键词： Evolving networks Real world networks Evolving network models Self-similarity

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Handling of Computationally Demanding Digital Controllers in Power System Dynamic Simulations 3

Handling of Computationally Demanding Digital Controllers in...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Jafari, Mehran Bureau, Gautier Chiaramello, Marco Guironnet, Adrien Panciatici, Patrick Aristidou, Petros Cyprus University of Technology Computer Eng. & Informatics Dept. of Electrical Eng. Limassol Cyprus France

ISBN: (纸本)9798350375923

Nowadays Smart grids utilize digital controllers to guarantee the reliable and efficient operation of their components. However, the numerical simulation of these types of controllers is challenging due to the numerous discrete time events introduced. The interpolation-based method (IBM) can effectively simulate smart digital controllers alongside the differential-algebraic equations of the system under control. Compared to the traditional step-reduction method (SRM) that reduces the time step for each time event during the simulation, IBM allows the use of variable time steps and solves the system while ensuring simulation accuracy. However, in the case of computationally demanding controllers, the computational performance of IBM suffers significantly. In this paper, a modified version of IBM is introduced, which can handle computationally demanding controllers in dynamic simulation of power systems. The performance of the proposed method is assessed and compared to SRM and IBM by simulating a test system with different controllers. © 2024 IEEE.

关键词： Smart power grids

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Survey on Cryptoprocessors Advances and Technological Trends 3rd

Survey on Cryptoprocessors Advances and Technological Tren...

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3rd International Conference on Innovations in Computing Research, ICR 2024

作者： Kakoulli, Elena Zacharioudakis, Eleftherios Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Paphos Cyprus Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine

ISBN: (纸本)9783031655210

Cryptoprocessors play a pivotal role in enhancing the security of modern computing systems by accelerating cryptographic operations and fortifying data protection. This survey delves into the world of cryptoprocessors, encompassing their historical development, architectural features, and various types based on their applications. The paper explores the crucial security considerations surrounding cryptoprocessors, covering both physical and logical aspects, as well as potential threats and countermeasures. Furthermore, the survey navigates through the latest technological trends and advancements in cryptoprocessor design. This includes discussions on post-quantum cryptography, secure enclaves, and mitigating side-channel attacks, all of which are shaping the future of cryptoprocessors. Real-world use cases and applications in domains such as secure communications, the Internet of Things (IoT), and data centers are presented, showcasing the practical significance of cryptoprocessors. However, the paper also highlights the persistent challenges faced by cryptoprocessor designers and provides insights into future research directions aimed at addressing emerging security and performance issues. As the digital landscape continues to evolve, the role of cryptoprocessors becomes increasingly vital in safeguarding sensitive information and fortifying the foundations of cybersecurity. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Internet of things

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ENERGY AND COST BENEFITS OF ADVANCED LIGHTING technology APPLICATIONS IN TRAFFIC LIGHT SYSTEMS 14

ENERGY AND COST BENEFITS OF ADVANCED LIGHTING TECHNOLOGY APP...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Polycarpou, Alexis Georgiou, Marios S. Department of Electrical Computer Engineering and Informatics Frederick University Nicosia Cyprus Electromechanical Section Nicosia Municipality Nicosia Cyprus

ISBN: (纸本)9781837242689

Following a pilot project, which concluded in 2016, the replacement of old energy consuming Traffic Light Systems (TLS) of Nicosia Municipality were the subject of an investigation with regards to the energy saving potential and most importantly the payback period of the investment, through presumptions. This paper presents the results obtained of the new efficient technology implementation, with regards to the energy saving that materialised in the Nicosia Municipality. Investigation is presented in an attempt to determine whether the proposed solution and calculated capital employed had the expected energy usage reduction, return on investment, and payback period. The estimated cost benefit of the installed systems compared to the actual benefits varies significantly, after factors such as maintenance and electricity costs are considered. © The Institution of engineering & technology 2024.

关键词： Street lighting

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Optimizing Power Allocation and Beamforming in mmWave-NOMA Downlink with Deep Reinforcement Learning

Optimizing Power Allocation and Beamforming in mmWave-NOMA D...

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2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024

作者： Kasgari, Abbas Akbarpour Chrysostomou, Chrysostomos Frederick University and Frederick Research Center Computer Engineering and Informatics Department of Electrical Engineering Nicosia Cyprus

ISBN: (纸本)9798350376715

The high demand for data rates in the fifth generation (5G) and beyond of wireless communication can be met by the Non-Orthogonal Multiple Access (NOMA) approach in the millimeter-wave (mmWave) frequency band. Joint power allocation and beamforming for 5 G and beyond mmWave-NOMA systems are essential, which can be achieved through optimization approaches. To this end, we have employed a Deep Reinforcement Learning (DRL) approach for policy generation, leading to an optimized sum-rate for users. Unlike existing methods, our approach is not susceptible to channel impulse response (CIR) estimation errors. The actor-critic framework is utilized to measure the immediate reward and provide new actions to maximize the overall Q-value of the network. The immediate reward is defined based on the summation of the rates of two users, considering the minimum guaranteed rate for each user and the total consumed power as constraints. The simulation results demonstrate the superiority of the proposed approach compared to state-of-the-art counterparts, including Time-Division Multiple Access (TDMA) and NLOS-NOMA optimization strategies, in terms of sum-rate of users, while considering both perfect and imperfect channel state information (CSI) at the receiver. This work can also be beneficial for communications in vehicular networks, particularly in applications involving Collective Perception Messages (CPMs) dissemination for autonomous driving. © 2024 IEEE.

关键词： Deep reinforcement learning

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Person-Dependent Handwriting Verification for Special Education Using DeepLearning

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Intelligent Automation & Soft Computing 2023年第4期36卷 1121-1135页

作者： Umut Zeki Tolgay Karanfiller Kamil Yurtkan Department of Computer Engineering Cyprus International UniversityHaspolatNicosiaNorthern CyprusMersin 10Turkey Computer and Instructional Technology Teacher Education Cyprus International UniversityHaspolatNicosiaNorthern CyprusMersin 10Turkey

Individuals with special needs learn more slowly than their peers and they need repetitions to be ***,in crowded classrooms,it is dif-ﬁcult for a teacher to deal with each student *** problem can be overcome by using supportive education ***,the majority of such applications are not designed for special education and therefore they are not efﬁcient as *** education students differ from their peers in terms of their development,characteristics,and educational qualiﬁ*** handwriting skills of individuals with special needs are lower than their *** makes the task of Handwriting Recognition(HWR)more difﬁ*** over-come this problem,we propose a new personalized handwriting veriﬁcation sys-tem that validates digits from the handwriting of special education *** system uses a Convolutional Neural Network(CNN)created and trained from *** data set used is obtained by collecting the handwriting of the students with the help of a tablet.A special education center is visited and the handwrittenﬁgures of the students are collected under the supervision of special education *** system is designed as a person-dependent system as every student has their writing ***,the system achieves promising results,reaching a recognition accuracy of about 94%.Overall,the system can verify special educa-tion students’handwriting digits with high accuracy and is ready to integrate with a mobile application that is designed to teach digits to special education students.

关键词： Special education deep learning convolutional neural network handwriting veriﬁcation handwriting digit veriﬁcation person-dependent training handwriting recognition

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Adaptive Strategies for Enhancing Quality of Experience in 360° Video Streaming 58

Adaptive Strategies for Enhancing Quality of Experience in 3...

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58th Asilomar Conference on Signals, Systems and computers, ACSSC 2024

作者： Valiandi, Ioanna Pattichis, Marios S. Kyriacou, Efthyvoulos Panayides, Andreas S. Videomics Group Cyens Centre of Excellence Nicosia Cyprus University of New Mexico Department of Electrical and Computer Engineering AlbuquerqueNM87131-0001 United States Cyprus University of Technology Department of Electrical Eng. Computer Engineering and Informatics Limassol Cyprus

ISBN: (纸本)9798350354058

The unprecedented growth of immersive virtual and mixed reality technologies is driving the increasing demand of 360° video streaming applications. Facilitating unique opportunities, but also challenges, 360° videos require substantially higher video resolutions, and hence bandwidth demands, for a better viewing experience. This study examined four tile-based Region of Interest (ROI) encoding techniques to optimize 360° video encoding and streaming. These techniques encode the user's viewport regions with higher quality compared to the background, non-ROI areas. A dataset of ten 4K omnidirectional videos at 30 frames per second was used to evaluate the performance of four distinct tile-based ROI methods using four video encoding standards, namely hevc - nvenc, x265, h264 - nvenc, and x264. Overall, the proposed tile-based ROI encoding methods achieve substantial bitrate reductions compared to the uniform full-frame encoding while maintaining adequate subjective video quality levels, demonstrating their potential for efficient and scalable 360° video streaming. The ROI-3 method, which uses a sliding window approach to encode the user's field of view based on eye gaze movement (EM) data coordinates translated to tile regions, was found to achieve the best trade-off between bitrate demands savings and perceptual quality for all investigated video compression standards. © 2024 IEEE.

关键词： Video streaming

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