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Weighted Sum Rate Enhancement by Using Dual-Side IOS-Assisted Full-Duplex for Multi-User MIMO Systems

IEEE Internet of Things Journal 2025年

作者： Fang, Sisai Chen, Gaojie Huang, Chong Gao, Yue Li, Yonghui Wong, Kai-Kit Chambers, Jonathon A. State Key Laboratory of Optoelectronic Materials and Technologies Guangdong510220 China GuildfordGU2 7XH United Kingdom Fudan University School of Computer Science Shanghai200433 China University of Sydney School of Electrical and Information Engineering SydneyNSW2006 Australia University College London Department of Electronic and Electrical Engineering LondonWC1E 7JE United Kingdom University of Leicester School of Engineering LeicesterLE1 7RH United Kingdom

This paper established a novel multi-input multi-output (MIMO) communication network, in the presence of full-duplex (FD) transmitters and receivers with the assistance of dual-side intelligent omni surface (IOS). Compared with the traditional IOS, the dual-side IOS allows signals from both sides to reflect and refract simultaneously, which further exploits the potential of metasurfaces to avoid frequency dependence, and size, weight, and power (SWaP) limitations. By considering both the downlink and uplink transmissions, we aim to maximize the weighted sum rate, subject to the transmit power constraints of the transmitter, the users and the dual-side reflecting and refracting phase shifts constraints. However, the formulated sum rate maximization problem is not convex, hence we exploit the weighted minimum mean square error (WMMSE) approach, and tackle the original problem iteratively by solving two sub-problems. For the beamforming matrices optimization of the downlink and uplink, we resort to the Lagrangian dual method combined with a bisection search to obtain the results. Furthermore, we resort to the quadratically constrained quadratic programming (QCQP) method to optimize the reflecting and refracting phase shifts of both sides of the IOS. Simulation results validate the efficacy of the proposed algorithm and demonstrate the superiority of the dual-side IOS. © 2014 IEEE.

关键词： Mean square error

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K+ concentration-based NMR-fluorescence dual-functional senescence sensing using graphene quantum dots with crown ether structure

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Sensors and Actuators B: Chemical 2025年 431卷

作者： Chen, Xiaojing Tao, Quan Yang, Siwei Wang, Hang Wang, Xuelian Ding, Guqiao Gao, Xiumin Dong, Hui Rong, Liangliang School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Shanghai Key Laboratory of Superconductor Integrated Circuit Technology & National Key Laboratory of Materials for Integrated Circuits Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing100049 China Shanghai Jiaotong University School of Medicine Shanghai200025 China

Aging allows the occurrence and progression of cerebrovascular diseases, highlighting the importance of detecting senescent cells and tissues in the nervous system. Detecting senescent cells/tissues using nanoparticles as probes in the nervous system is desired with high sensitivity, high accuracy, and penetration of the blood-brain barrier. In response, we designed crown ether-based graphene quantum dots with fast proton transport channels to sense potassium ions, a significant differential indicator between healthy and senescent cells. Using the probe, we have achieved MRI-fluorescence dual-functional monitoring of potassium ion concentration in cells via fluorescent intensity and magnetic relaxation time. Importantly, we have further demonstrated the advantages of the crown ether-based graphene quantum dots in penetrating the blood-brain barrier, revealing their potential for diagnosing aging in the nervous system. © 2025 Elsevier B.V.

关键词： Graphene quantum dots

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Utilization of Quality of Service in Basic Wireline Telecom Services for enhancing Consumer Satisfaction in Assam region

Utilization of Quality of Service in Basic Wireline Telecom ...

引用

Devices for Integrated Circuit (DevIC)

作者： Arshi Naim Anshul Mahajan Dr Rakesh Kolluri Amanjot Singh Neeti Misra Jaypal Lande Business Management European Institute of Innovation and Technology Malta School of Electronics and Electrical Engineering Lovely Professional University Phagwara Punjab India Department of ECE Malla Reddy Engineering College for Women Hyderabad Department of Management Uttaranchal Institute of Management Uttaranchal University Dehradun Uttarakhand India School of Computer Science & Artificial Intelligence SR University Warangal

ISBN: (数字)9798350391107

ISBN: (纸本)9798350391114

This study explores the impact of Quality of Service (QoS) on consumer satisfaction in basic wireline telecom services in Assam, India. The aim of this research is to identify key QoS indicators that influence consumer satisfaction in the region. A qualitative research method is adopted, utilizing secondary data available for public disclosure, including government reports, telecom regulatory authority publications, and consumer feedback from various platforms. The study focuses on understanding how these indicators such as call quality, internet connectivity, customer support response time, and pricing transparency affect the satisfaction levels of consumers in Assam. The findings indicate that call quality and internet reliability are the most critical factors for consumers, followed by effective customer service and pricing fairness. These results highlight the need for telecom providers in Assam to prioritize service improvements in these areas to enhance consumer satisfaction and loyalty. This study offers valuable insights for policy makers and telecom companies to improve service delivery.

关键词： Surveys Measurement Integrated circuits Urban areas Quality of service Pricing Time factors Reliability Interviews Telecommunication services

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Analysis of the opportunities for reducing energy intensity in construction site operations in Germany

Civil Engineering Design

引用

Civil engineering Design 2025年第0期

作者： Krištofič, Štefan Harborth, Thomas Antošová, Naďa Kalická, Jana Department of Building Technology Faculty of Civil Engineering Slovak University of Technology in Bratislava Bratislava Slovakia Hochschule Magdeburg-Stendal Baubetrieb—Bauwirtschaft und Bautechnologie Fachbereich Wasser Umwelt Bau und Sicherheit Magdeburg Germany Institute of Computer Science and Mathematics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Bratislava Bratislava Slovakia

The paper presents a detailed assessment of the energy performance of a construction site in Germany, where realistic electricity consumption patterns are obtained using metering devices installed in the site switchgear. The paper analyzes the current operations on construction sites and suggests innovative strategies to improve energy efficiency. The results reveal potential electricity savings of nearly 44% in temporary construction offices. Moreover, the paper discusses various strategies, technological innovations, and management practices that could help reduce electricity consumption while ensuring sustainable and environmentally friendly construction practices. © 2025 Ernst & Sohn GmbH.

关键词： electricity consumption innovation optimization site operation

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Better Rates for Random Task Orderings in Continual Linear Models

arXiv

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arXiv 2025年

作者： Evron, Itay Levinstein, Ran Schliserman, Matan Sherman, Uri Koren, Tomer Soudry, Daniel Srebro, Nathan Department of Electrical and Computer Engineering Technion Department of Computer Science Technion Blavatnik School of Computer Science and AI Tel Aviv University Blavatnik School of Computer Science and AI Tel Aviv University Google Research Toyota Technological Institute Chicago United States

We study the common continual learning setup where an overparameterized model is sequentially fitted to a set of jointly realizable tasks. We analyze the forgetting—loss on previously seen tasks—after k iterations. For linear models, we prove that fitting a task is equivalent to a single stochastic gradient descent (SGD) step on a modified objective. We develop novel last-iterate SGD upper bounds in the realizable least squares setup, and apply them to derive new results for continual learning. Focusing on random orderings over T tasks, we establish universal forgetting rates, whereas existing rates depend on the problem dimensionality or complexity. Specifically, in continual regression with replacement, we improve the best existing rate from O((d − r¯)/k) to O(min(1/√4 k, √d − r¯/k, √Tr¯/k)), where d is the dimensionality and r¯ the average task rank. Furthermore, we establish the first rates for random task orderings without replacement. The obtained rate of O(min(1/√4T, (d − r)/T)) proves for the first time that randomization alone—with no task repetition—can _prevent catastrophic forgetting in sufficiently long task sequences. Finally, we prove a similar O(1/√4 k) universal rate for the forgetting in continual linear classification on separable data. Our universal rates apply for broader projection methods, such as block Kaczmarz and POCS, illuminating their loss convergence under i.i.d. and one-pass orderings. © 2025, CC BY.

关键词： Least squares approximations

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Bifurcation analysis of an opinion dynamics model coupled with an environmental dynamics

arXiv

引用

arXiv 2025年

作者： Couthures, Anthony Bizyaeva, Anastasia Varma, Vineeth S. Franci, Alessio Morărescu, Irinel-Constantin Université de Lorraine CNRS CRAN NancyF-54000 France Automation Department Technical University of Cluj-Napoca Memorandumului 28 Cluj-Napoca400114 Romania Sibley School of Mechanical and Aerospace Engineering Cornell University United States Department of Electrical Engineering and Computer Science University of Liege WEL Research Institute Wavre Belgium

We consider an opinion dynamics model coupled with an environmental dynamics. Based on a forward invariance argument, we can simplify the analysis of the asymptotic behavior to the case when all the opinions in the social network are synchronized. Our goal is to emphasize the role of the trust given to the environmental signal in the asymptotic behavior of the opinion dynamics and implicitly of the coupled system. To do that, we conduct a bifurcation analysis of the system around the origin when the trust parameter is varying. Specific conditions are presented for both pitchfork and Hopf bifurcation. Numerical illustration completes the theoretical findings. © 2025, CC BY-SA.

关键词： Bifurcation (mathematics)

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Enhancing Sales Forecasting in E-Commerce Through Advanced Predictive Analytics and Deep Neural Networks

Enhancing Sales Forecasting in E-Commerce Through Advanced P...

引用

Automation and Computation (AUTOCOM), International Conference on

作者： Mahesh Kotha Gnanajeyaraman Rajaram K. Sathishkumar Mohammed Hussein Fallah J. Karpagam Anil P S Department of CSE (AI&ML) CMR Technical Campus Hyderabad India Department of CSE SIMATS Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical sciences Chennai India Dept. of Computer Science Erode Arts and Science College Erode Tamilnadu India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore India Department of Management Gnanam School of Business Thanjavur Tamilnadu

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Within this context, this research is aimed at enhancing the sales forecasting in e-commerce using the newer approaches of predictive analytics and deep neural networks. There usually is significant variability of results as compared to traditional approaches that are based on historical data and simple econometric models. This research evaluates how deep learning approaches, LSTM and Transformer models, improve precisely the forecast by noticing the behaviour dynamics and more complex patterns in the business environment. The actual approach includes sales history data, understanding customers, trends, and related promotions to train as well as test neural networks. The basic hybrid approach integrates deep learning and statistical methods to forecast the maximum potential outcomes. The performance of models in this study is evaluated by Mean Absolute Error (MAE), Root Mean Squared Error(RMSE) and R-Squared to compare the forecasted sales values with the actual ones. It is established that incorporating the deep learning models that have been described enhances the forecast precision concerning the baseline and conventional methods of approach significantly, especially the hybrid model. The precise accuracy, and factors that cause it to fluctuate from one product category to another, and the impact of promotional activities on the forecast's precision, are addressed. Thus, the study contributes to the knowledge that adopting innovative techniques such as advanced predictive analytics and deep learning to improve sales forecasting can potentiate strategic business courses of action and the firm's performance in today's cut-throat e-commerce marketplace.

关键词： Deep learning Biological system modeling Predictive models Transformers Market research Data models Electronic commerce Forecasting Predictive analytics Long short term memory

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AI-Powered Object Detection for Autonomous Vehicles: A Comparative Study of Machine Learning Models

AI-Powered Object Detection for Autonomous Vehicles: A Compa...

引用

Computational, Communication and Information Technology (ICCCIT), International Conference on

作者： Anurag Shrivastava Vipashi Kansal Amandeep Nagpal Manjunatha Krishna Kant Dixit K. Varada Rajkumar Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamilnadu India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Lovely Professional University Phagwara India Department of Mechanical Engineering New Horizon College of Engineering Bangalore India Department of Electrical Engineering GLA University Mathura India Department of CSE-AI&ML MLR Institute of Technology Hyderabad Telangana India

ISBN: (数字)9798331512965

ISBN: (纸本)9798331512972

Object detection is an integral piece of autonomous cars learning their surroundings and making safe judgements about where and how to drive in real time. This research compares and contrasts multiple machine learning models for object identification in autonomous cars in order to assess accuracy, computational economy, and real time performance. Then, we present how various well known proposed models (CNN, YOLO, SSD, R-CNN) perform in changing driving conditions. It researches the models capabilities to run real time applications within autonomous cars, as well as the trade off of speed and accuracy between different models. We also study how hyperparameter adjustment, data augmentation and transfer learning impact these models’ performance. Through thorough research on benchmark datasets, this work shows the benefits of the adoption of hybrid models, which mix speed and accuracy, to increase item recognition in real world contexts. This study contributes to the expanding corpus of knowledge on AI driven solutions for autonomous systems by having useful insights regarding the improvement of autonomous vehicle object identification algorithms.

关键词： YOLO Accuracy Biological system modeling Computational modeling Transfer learning Real-time systems Sensors Automobiles Object recognition Autonomous vehicles

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NLOS Identification and Machine Learning Methods for Predicting the Outcome of 60GHz Ranging System

引用

Chinese Journal of Electronics 2018年第1期27卷 175-182页

作者： LIANG Xiaolin JIN Yiheng ZHANG Hao LYU Tingting College of Information Science and Engineering Ocean University of China Department of Electrical Computer Engineering University of Victoria

Millimeter-wave(MMW) signals in 60 GHz band have shown immense potential for accurate range estimation with precise time and multipath resolution. Nonline of sight(NLOS) propagation is a primary factor affecting the range precision. To improve range estimation,an Energy detector(ED) based normalized threshold algorithm which employs a Neural network(NN) is developed on the basis of NLOS identification. The maximum curl and standard deviation of the received energy block values are used to determine NLOS environment and the normalized thresholds for different Signal-to-noise ratios(SNRs). The effects of the channel and integration period are *** results are presented which show that the proposed approach provides better precision and is more robust than other solutions over a wide range of SNRs for the CM1.1 and CM2.1 channel models in the IEEE802.15.3 c standard.

关键词： Non-line of sight(NLOS) identification Curl Standard deviation IEEE 802.15.3c Machine learning

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Force-Aware Autonomous Robotic Surgery

arXiv

引用

arXiv 2025年

作者： Abdelaal, Alaa Eldin Fang, Jiaying Reinhart, Tim N. Mejia, Jacob A. Zhao, Tony Z. Bohg, Jeannette Okamura, Allison M. Mechanical Engineering Department Stanford University 440 Escondido Mall Building 530 StanfordCA94305 United States Electrical Engineering Department Stanford University 350 Jane Stanford Way StanfordCA94305 United States Department of Computer Science Stanford University 353 Jane Stanford Way StanfordCA94305 United States

This work demonstrates the benefits of using tool-tissue interaction forces in the design of autonomous systems in robot-assisted surgery (RAS). Autonomous systems in surgery must manipulate tissues of different stiffness levels and hence should apply different levels of forces accordingly. We hypothesize that this ability is enabled by using force measurements as input to policies learned from human demonstrations. To test this hypothesis, we use Action-Chunking Transformers (ACT) to train two policies through imitation learning for automated tissue retraction with the da Vinci Research Kit (dVRK). To quantify the effects of using tool-tissue interaction force data, we trained a "no force policy" that uses the vision and robot kinematic data, and compared it to a "force policy" that uses force, vision and robot kinematic data. When tested on a previously seen tissue sample, the force policy is 3 times more successful in autonomously performing the task compared with the no force policy. In addition, the force policy is more gentle with the tissue compared with the no force policy, exerting on average 62% less force on the tissue. When tested on a previously unseen tissue sample, the force policy is 3.5 times more successful in autonomously performing the task, exerting an order of magnitude less forces on the tissue, compared with the no force policy. These results open the door to design force-aware autonomous systems that can meet the surgical guidelines for tissue handling, especially using the newly released RAS systems with force feedback capabilities such as the da Vinci 5. © 2025, CC BY.

关键词： Medical robotics

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