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Exploring the Synergy: A Review of Dual-Functional Radar Communication Systems

IEEE Aerospace and Electronic Systems Magazine 2025年

作者： Hanif, Ali Ahmed, Sajid Alouini, Mohamed-Slim Al-Naffouri, Tareq Y. King Abdullah University of Science and Technology Department of Electrical and Computer Engineering CEMSE Division Thuwal23955 Saudi Arabia

This review paper examines the concept and advancements in the evolving landscape of Dual-functional Radar Communication (DFRC) systems. Traditionally, radar and communication systems have functioned independently, but current research is actively investigating the integration of these functionalities into a unified platform. The paper discusses the motivations behind the development of DFRC systems, the challenges involved, and the potential benefits they offer. A discussion on the performance bounds for DFRC systems is also presented. The paper provides a comprehensive review of the state-of-the-art research on DFRC systems covering various design aspects, resource allocation strategies, and future research directions. Additionally, we explore potential application scenarios for these joint communication and sensing systems, offering a comprehensive perspective on the multifaceted landscape of DFRC technology. This paper also presents a tutorial-style signal model for integrated sensing and communication tailored for newcomers to the field. © 2025 IEEE. All rights reserved.

关键词： Resource allocation

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Long-term radiofrequency electromagnetic fields exposure attenuates cognitive dysfunction in 5×FAD mice by regulating microglial function

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Neural Regeneration Research 2023年第11期18卷 2497-2503页

作者： Yeonghoon Son Hye-Jin Park Ye Ji Jeong Hyung-Do Choi Nam Kim Hae-June Lee Division of Radiation Biomedical Research Korea Institute of Radiological&Medical SciencesSeoulKorea Department of EMF Research Team Radio and Broadcasting Technology LaboratoryElectronics and Telecommunications Research InstituteDaejonKorea School of Electrical and Computer Engineering Chungbuk National UniversityCheongjuKorea

We have previously found that long-term effects of exposure to radiofrequency electromagnetic fields in 5xFAD mice with severe late-stage Alzheimer’s disease reduced both amyloid-βdeposition and glial activation,including *** examine whether this therapeutic effect is due to the regulation of activated microglia,we analyzed mic roglial gene expression profiles and the existence of microglia in the brain in this study.5xFAD mice at the age of 1.5 months were assigned to sham-and radiofrequency electromagnetic fields-exposed groups and then animals were exposed to 1950 MHz radiofrequency electromagnetic fields at a specific absorption rate of 5 W/kg for 2 hours/day and 5 days/week for 6 *** conducted behavioral tests including the object recognition and Y-maze tests and molecular and histopathological analysis of amyloid precursor protein/a myloid-beta metabolism in brain *** confirmed that radiofrequency electromagnetic field exposure for 6 months ameliorated cognitive impairment and amyloid-β*** expression levels of Iba1(pan-microglial marker)and colony-stimulating factor 1 receptor(CSF1R;regulates microglial prolife ration)in the hippocampus in 5xFAD mice treated with radiofrequency electromagnetic fields were significantly reduced compared with those of the sham-exposed ***,we analyzed the expression levels of genes related to mic rogliosis and microglial function in the radiofrequency electromagnetic fields-exposed group compared to those of a CSF1R inhibitor(PLX3397)-treated *** radiofrequency electromagnetic fields and PLX3397 suppressed the levels of genes related to microgliosis(Csf1r,CD68,and Ccl6)and pro-inflammatory cytokine interleukin-1β.N otably,the expression levels of genes related to mic roglial function,including Trem2,Fcgr1α,Ctss,and Spi1,were decreased after long-term radiofrequency electromagnetic field exposure,which was also observed in response to microglial suppression by *** res

关键词： 5×FAD Alzheimer’s disease CSF1R long term exposure microglial function neuroinflammation radiofrequency electromagnetic fields therapeutic effect

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DFRC Signaling Strategies based on MIMO Beampattern Invariance

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IEEE Transactions on Communications 2025年

作者： Mazahir, Sana Ahmed, Sajid Alouini, Mohamed-Slim King Abdullah University of Science and Technology CEMSE Division Department of Electrical and Computer Engineering Thuwal23955 Saudi Arabia

The Dual-function radar communication (DFRC) design aims to exploit the tractability and reusability of both radar and communication systems' components, parameters, and spectrum to achieve an integrated system. In this work, we propose a novel DFRC signal design by leveraging the phenomenon of the MIMO beampattern invariance, which was comprehensively explored in our previous work [1]. It is demonstrated that the flexibility afforded by this beampattern invariance can be used to construct an integrated waveform while maintaining the required beam. A beampattern-preserving unitary transformation of the MIMO weight matrix is proposed to realize a desired information-bearing symbol at the communication receiver. The proposed method has the following promising features: 1) low-complexity, closed-form solution for the transmitted signals;2) flexibility of modulation scheme;3) independence from the type of orthonormal MIMO waveforms;4) independence from the beampattern design;5) adaptability for multi-target and multi-user scenarios. Using this generic signal design method, a number of modulation schemes are implemented. Furthermore, the impact of this operation on the estimation accuracy of the target parameters is analyzed by computing their respective Cramer-Rao Lower Bounds (CRLBs). Simulation results show that modulation schemes yielding a range of symbol error rate (SER) performances can be implemented while keeping the radar parameter estimation unaffected. © 2025 IEEE.

关键词： Cramer-Rao bounds

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Adaptive Water Quality Potability Prediction and Analysis Through GEM Continual Learning Algorithm for Sustainable Resource Management

Adaptive Water Quality Potability Prediction and Analysis Th...

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International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： Jeremy David C D Shibin Computer Security Research Lab Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

Ensuring the safety of drinking water on a worldwide scale is imperative, and accurate estimation of water quality is crucial for both environmental and public health. This study leverages machine learning, evolving a novel approach with the GEM Continual Learning Algorithm to enhance sustainable resource management through water quality prediction. The research systematically evaluates GEM's effectiveness in forecasting water quality features, comparing it with diverse contemporary machine learning models like Logistic Regression, Ridge, KNeighbors Classifier, and more. Results demonstrate GEM's superiority, highlighting its adaptability and efficiency in predicting water quality attributes. Insights for customized applications are provided by discussing model selection choices that address goals and limits. Future work aims to refine feature engineering, explore ensemble methods, and address data quality concerns within the GEM framework. Conclusively, the GEM Continual Learning Algorithm emerges as a robust solution for adaptive water quality prediction, promising continuous monitoring, early detection, and compliance with water quality regulations. Its deployment holds potential for ensuring safer water supplies, contributing to sustainable water management practices worldwide.

关键词： Continuing education Adaptation models Water quality Predictive models Prediction algorithms Regulation Safety Resource management Public healthcare Water resources

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Navigating the Nexus: A systematic review of the symbiotic relationship between the metaverse and gaming

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International Journal of Cognitive Computing in engineering 2024年第1期5卷 88-103页

作者： Mohammed, Sahar Yousif Aljanabi, Mohammed Gadekallu, Thippa Reddy Translation Department Faculty of Arts Anbar University Anbar31001 Iraq Imam Ja'afar Al-Sadiq University Baghdad Iraq Department of Computer College of Education Al-Iraqia University Baghdad 10011 Iraq Division of Research and development Lovely Professional University Phagwara India Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon Centre of Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India

The advent of the metaverse has sparked profound interest in its integration within the gaming domain. Games, being intrinsic components of the metaverse, have attracted considerable attention, prompting inquiries into the transformative influence of the metaverse on the gaming industry and its communities within this immersive digital realm. This study aims to synthesize the literature by providing a comprehensive overview of recent studies on the complex interplay between video games and the metaverse, illuminating the benefits, difficulties, and uncharted territory of this field. Fifteen (15) relevant studies were reviewed in accordance with PRISMA criteria, supplemented with the LDA topic modeling to answer the developed research questions. The research showed that the metaverse has many impacts on the gaming industry;it serves as a platform for interactive games, a driver for collaborative gaming environments, a medium for immersive virtual reality (VR) experiences, and a source of useful information about the basic aspects and mechanisms that support the connected relationship between the metaverse and gaming. Furthermore, the evolution of these dimensions and processes across time was investigated. This systematic review makes a noteworthy addition to the ongoing scholarly discussion over the convergence of the metaverse and gaming. This statement highlights the significant capacity for transformation that arises from the integration of these elements, while also recognizing the intricate and demanding nature of this process. The ongoing transformation of the gaming industry and its communities by the metaverse prompts an investigation that lays the groundwork for future scholarly inquiry. This study aims to provide a detailed examination and enhanced comprehension of the intricate relationship between these two domains. © 2024 The Authors

关键词： Virtual reality

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Optimized Runge-Kutta Methods with Automatic Step Size Control for Compressible Computational Fluid Dynamics

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Communications on Applied Mathematics and Computation 2022年第4期4卷 1191-1228页

作者： Hendrik Ranocha Lisandro Dalcin Matteo Parsani David I.Ketcheson Applied Mathematics Münster University of MünsterMunsterGermany Computer Electrical and Mathematical Science and Engineering Division(CEMSE) Extreme Computing Research Center(ECRC)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Computer Electrical and Mathematical Science and Engineering Division(CEMSE) King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia

We develop error-control based time integration algorithms for compressible fluid dynam-ics(CFD)applications and show that they are efficient and robust in both the accuracy-limited and stability-limited *** on discontinuous spectral element semidis-cretizations,we design new controllers for existing methods and for some new embedded Runge-Kutta *** demonstrate the importance of choosing adequate controller parameters and provide a means to obtain these in *** compare a wide range of error-control-based methods,along with the common approach in which step size con-trol is based on the Courant-Friedrichs-Lewy(CFL)*** optimized methods give improved performance and naturally adopt a step size close to the maximum stable CFL number at loose tolerances,while additionally providing control of the temporal error at tighter *** numerical examples include challenging industrial CFD applications.

关键词： Explicit Runge-Kutta methods Step size control Compressible Euler equations Compressible Navier-Stokes equations hp-adaptive spatial discretizations

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Automated Fracture Detection and Classification Using Siamese Neural Networks

Automated Fracture Detection and Classification Using Siames...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Anderson, K.L. Engelbrecht, A.P. Birkholtz, F.F. Stellenbosch University Department of Computer Science Stellenbosch South Africa Stellenbosch University Computer Science Division Department of Industrial Engineering Stellenbosch South Africa Gulf University of Science and Technology GUST Engineering and Applied Innovation Research Centre Kuwait Institute of Orthopaedics and Rheumatology Mediclinic Winelands Orthopaedic Hospital Stellenbosch University Stellenbosch Division of Orthopaedic Surgery Department of Surgical Sciences Stellenbosch South Africa

ISBN: (纸本)9798350369106

This study aims to address the critical need for accurate and efficient fracture detection and classification in medical radiography, by leveraging recent developments in deep learning techniques. A two-stage pipeline is proposed combining a cutting-edge convolutional neural network (CNN), You only look once (YOLOv9), for wrist fracture detection using a Siamese neural network (SNN) for fracture type classification. The proposed methods aim to overcome the limitations of a single-stage approach by optimizing detection and classification stages independently. The results obtained demonstrate the efficacy of the two-stage pipeline in improving accuracy and reducing class imbalance issues, highlighting the potential of artificial intelligence (AI) driven solutions in enhancing patient care and reducing diagnosis time. © 2024 IEEE.

关键词： Convolutional neural networks

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Evaluating Different Methods for Semantic Reasoning Over Ontologies 1

Evaluating Different Methods for Semantic Reasoning Over Ont...

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1st Scholarly QALD Challenge 2023 and 4th SeMantic Answer Type, Relation and Entity Prediction Tasks Challenge, Scholarly QALD 2023 and SemREC 2023

作者： Zhapa-Camacho, Fernando Hoehndorf, Robert Computational Bioscience Research Center Computer Electrical & Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology 4700 KAUST Thuwal23955 Saudi Arabia

Reasoning over knowledge bases such as Semantic Web ontologies enables the discovery of new facts from existing knowledge. Knowledge-enhanced machine learning has motivated the development of neuro-symbolic reasoners, which enable faster but approximate computation of new facts or entailments. Neuro-symbolic methods generate vector representations (embeddings) of entities in a knowledge base. We analyze some ontology embedding methods, by implementing them as neuro-symbolic reasoners and evaluating their predictive performance on the datasets and tasks provided by the Semantic Reasoning Evaluation Challenge 2023. We explore two types of embedding methods: graph-based and model-theoretic. Regarding graph-based embeddings, we evaluated the impact of different combinations of graph representation of ontologies with knowledge graph embedding methods. For model-theoretic embeddings, which create models for theories, we evaluate the impact of using several models, enabling approximate semantic entailment. © 2023 CEUR-WS. All rights reserved.

关键词： Ontology

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Enhancing Solar PV Deployment: Land Suitability Assessment and Site Selection using AHP

Enhancing Solar PV Deployment: Land Suitability Assessment a...

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Advances in Modern Age Technologies for Health and engineering Science (AMATHE), International Conference on

作者： Blessy Tryphena Priyadharsini. C J. Vidhya Division Of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Division of Electronics and Communication Engineering IFET College of Engineering Villupuram India

ISBN: (数字)9798350371567

ISBN: (纸本)9798350371574

In response to the escalating global energy demand driven by population growth and technological advancements, solar PV emerges as a competitive and viable renewable energy source. [9] With the International Renewable Energy Agency (IRENA) projecting a significant increase in solar PV capacity by 2030 and a dramatic reduction in installation costs, the importance of strategic site selection for solar installations cannot be overstated. This paper emphasizes the necessity of conducting a thorough land suitability analysis to optimize energy output and minimize costs, taking into account environmental, economic, and social factors. To achieve this, the study employs Analytic hierarchy process within an Multicriteria decision making framework, coupled with GIS analysis, to systematically evaluate potential sites for large-scale solar power projects. This paper contributes to the field by providing a comprehensive approach to selecting optimal sites for solar PV installations, combining spatial analysis with evaluative and ranking capabilities. Through this integrated approach, the study underscores the potential of solar PV technology as a cornerstone of future energy systems, highlighting the critical role of precise site selection in realizing the full benefits of solar energy deployment.

关键词： Renewable energy sources Costs Systematics Wind speed Solar energy Analytic hierarchy process Strategic planning

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Push-Pull based Grid tied Micro inverter for Photovoltaic Applications

Push-Pull based Grid tied Micro inverter for Photovoltaic Ap...

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2023 IEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy, PESGRE 2023

作者： Paul, Preenu Jose, Babita R Shahana, T.K. Abraham, Chikku Mathew, Jimson Sandeep, J. Cochin University of Science and Technology Division of Electronics School of Engineering Cochin India Muthoot Institute of Technology and Science Department of Electrical and Electronics Engineering Ernakulam India Indian Institute of Technology Department of Computer Science and Engineering Patna India Sfo Technologies R & D Solutions Power Electronics Cochin India

ISBN: (纸本)9798350310573

This paper presents the harnessing of solar energy using a two-stage grid-tied micro inverter with an isolated high gain DC-DC converter as first stage and a single-phase grid tied inverter as second stage. High gain converter is implemented using a quasi-switched boost network, switched capacitor topology and push-pull circuit. High frequency transformer in first stage improves gain and provides isolation between solar Photovoltaic (PV) circuit and grid connection which add safety margins. Micro inverter topology, control logic for Maximum Power Point Tracking (MPPT) and H - bridge inverter is presented. The operation of a 250 V micro inverter is verified using MATLAB Simulink tool. © 2023 IEEE.

关键词： Grid tied inverter Isolated DC-DC converters MPPT One cycle control Switched boost topology Switched capacitor

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