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Energy Efficient Transmitter Creation by Consuming Free Energy in Molecular Communication

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications 2025年第2期11卷 292-303页

作者： Jing, Dongliang Li, Linjuan Cheng, Zhen Lin, Lin Eckford, Andrew W. Northwest A and F University College of Mechanical and Electronic Engineering Yangling China Ministry of Agriculture and Rural Affairs Key Laboratory of Agricultural Internet of Things Yangling China Zhejiang University of Technology School of Computer Science and Technology Hangzhou310023 China Tongji University College of Electronics and Information Engineering Shanghai China York University Department of Electrical Engineering and Computer Science TorontoON Canada

Information molecules play a crucial role in molecular communication (MC), acting as carriers for information transfer. A common approach to get information molecules in MC involves harvesting them from the environment;however, the harvested molecules are often a mixture of various environmental molecules, and the initial concentration ratios in the reservoirs are identical, which hampers high-fidelity transmission techniques such as molecular shift keying (MoSK). This paper presents a transmitter design that harvests molecules from the surrounding environment and stores them in two reservoirs. To separate the mixed molecules, energy is consumed to transfer them between reservoirs. Given limited energy resources, this work explores energy-efficient strategies to optimize transmitter performance. Through theoretical analysis and simulations, we investigate different methods for moving molecules between reservoirs. The results demonstrate that transferring higher initial concentration molecules enhances transmitter performance, while using fewer molecules per transfer further improves efficiency. These findings provide valuable insights for optimizing MC systems through energy-efficient molecule transfer techniques. © 2015 IEEE.

关键词： Transmitters

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Beam Pattern Modulation Embedded Hybrid Transceiver Optimization for Integrated Sensing and Communication

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IEEE Transactions on Wireless Communications 2025年第6期24卷 4966-4980页

作者： Liu, Boxun Gao, Shijian Yang, Zonghui Cheng, Xiang Yang, Liuqing Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Internet of Things Thrust Guangzhou511400 China Internet of Things Thrust Intelligent Transportation Thrust Guangzhou511400 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Department of Civil and Environmental Engineering SAR Hong Kong Hong Kong

Integrated sensing and communication (ISAC) emerges as a promising technology for 6G, particularly in the millimeter-wave (mmWave) band. However, the widely utilized hybrid architecture in mmWave systems compromises multiplexing gain due to the constraints of limited radio-frequency (RF) chains. Moreover, additional sensing functionalities exacerbate the impairment of spectrum efficiency (SE). In this paper, we present an optimized beam pattern modulation-embedded ISAC (BPM-ISAC) transceiver design, which spares one RF chain for sensing and uses the remaining ones for communication. To compensate for the reduced SE, index modulation across communication beams is applied. We formulate an optimization problem aimed at minimizing the mean squared error (MSE) of the sensing beampattern, subject to a symbol MSE constraint. This problem is then solved by sequentially optimizing the analog and digital parts. Both the multi-aperture structure (MAS) and the multi-beam structure (MBS) are considered in the analog part. We conduct theoretical analysis on the asymptotic pairwise error probability (APEP) and the Cramér-Rao bound (CRB) of direction of arrival (DoA) estimation. Numerical simulations validate the overall enhanced ISAC performance over existing alternatives. © 2025 IEEE. All rights reserved.

关键词： Mean square error

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Distributed quantum circuit partitioning and optimization based on combined spectral clustering and search tree strategies

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Chinese Physics B 2025年第5期34卷 237-248页

作者： Zilu Chen Zhijin Guan Shuxian Zhao Xueyun Cheng School of Artificial Intelligence and Computer Science Nantong UniversityNantong 226019China College of Engineering the Internet of Things Taihu UniversityWuxi 214063China Jiangsu Huihuan Environmental Protection Technology Co. Ltd.Nantong 226010China

In the current noisy intermediate-scale quantum(NISQ)era,a single quantum processing unit(QPU)is insufficient to implement large-scale quantum algorithms;this has driven extensive research into distributed quantum computing(DQC).DQC involves the cooperative operation of multiple QPUs but is concurrently challenged by excessive communication *** address this issue,this paper proposes a quantum circuit partitioning method based on spectral *** approach transforms quantum circuits into weighted graphs and,through computation of the Laplacian matrix and clustering techniques,identifies candidate partition schemes that minimize the total weight of the ***,a global gate search tree strategy is introduced to meticulously explore opportunities for merged transfer of global gates,thereby minimizing the transmission cost of distributed quantum circuits and selecting the optimal partition scheme from the ***,the proposed method is evaluated through various comparative *** experimental results demonstrate that spectral clustering-based partitioning exhibits robust stability and efficiency in runtime in quantum circuits of different *** experiments involving the quantum Fourier transform algorithm and Revlib quantum circuits,the transmission cost achieved by the global gate search tree strategy is significantly optimized.

关键词： NISQ era distributed quantum computing quantum circuit partitioning transmission cost

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E-Waste Management using Deep Learning 6

E-Waste Management using Deep Learning

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6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Kumar, Boddu Manoj Sujitha, Kaduru Abinaya, K. School of Computer Science Engineering with Blockchain Technology Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India School of Computer Science Engineering with Internet of Things Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India School of Computer Science and Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India

ISBN: (纸本)9798331522667

Using the YOLO v8 model and deep learning approaches, this study explores the field of e-waste management and provides effective item detection. Our research attempts to increase the accuracy and scalability of e-waste detection, simplifying its incorporation into current waste management systems. Through utilizing deep learning, our goal is to transform the way that electronic waste is categorized, from tiny parts to larger appliances, allowing for more efficient as well as environmentally friendly management techniques. When it comes to aiming for higher performance, privacy comes first. Methods of preservation guarantee the accuracy of sensitive data correlated with pictures of e-waste. By means of execution utilizing data anonymization and encryption methods, we ensure compliance with legal requirements while safeguarding against potential privacy threats and ethical issues. The YOLO v8 model achieved an average precision (Map) of 97.1% in detecting e-waste items, demonstrating its effectiveness and scalability for real-world applications. © 2025 IEEE.

关键词： Differential privacy

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Literature Review of Circulating Current of Parallel Voltage Source Converters

Literature Review of Circulating Current of Parallel Voltage...

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2023 IEEE PELS Students and Young Professionals Symposium, SYPS 2023

作者： Zhang, Haoyu Wong, Man-Chung University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering Faculty of Science and Technology China

ISBN: (纸本)9798350307832

To increase the power density of voltage source converters (VSC) usually use parallel structures. However, parallel VSC will easily introduce circulating current, which can cause a power efficiency decline. This paper gives a review of the circulating current and the solutions of it. Through the analysis of the principle of circulating current generation and the detail of the solutions, this paper gives an overview of the current research stage of circulating current. The technology can be divided into hardware solutions and software solutions are then analyzed and evaluated. © 2023 IEEE.

关键词： Power converters

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Review of Hybrid Transformer Topology

Review of Hybrid Transformer Topology

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2023 IEEE PELS Students and Young Professionals Symposium, SYPS 2023

作者： Wan, Xin Wong, Man-Chung University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering Faculty of Science and Technology China

ISBN: (纸本)9798350307832

Due to the rapid development of power electronics and new energy generation, conventional transformers cannot meet the higher requirements of intelligent grids due to a lack of controllability. While solid-state transformers (SSTs) are currently costly, making it impossible for them to be used widely in power networks. For this reason, a compromise solution of a hybrid transformer (HT) combining the traditional line frequency transformer (LFT) with power electronic devices has attracted more and more attention. Based on existing HT research, topologies of HT are classified according to installation position and connection type of power electronic devices. Rough theoretical analyses were carried out from the point of view of voltage compensation, current compensation, and power flow control. A review of HT topology in recent years is also included. © 2023 IEEE.

关键词： Topology

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Channel assignment and power allocation for throughput improvement with PPO in B5G heterogeneous edge networks

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Digital Communications and Networks 2024年第1期10卷 109-116页

作者： Xiaoming He Yingchi Mao Yinqiu Liu Ping Ping Yan Hong Han Hu The College of Computer and Information Hohai UniversityNanjingChina The Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai UniversityNanjing China The School of Computer Science and Engineering Nanyang Technological UniversitySingapore The College of Textile and Clothing Engineering Soochow UniversitySuzhouChina The College of Internet of Things Nanjing University of Posts and TelecomurunicationsNanjingChina

In Beyond the Fifth Generation(B5G)heterogeneous edge networks,numerous users are multiplexed on a channel or served on the same frequency resource block,in which case the transmitter applies coding and the receiver uses interference ***,uncoordinated radio resource allocation can reduce system throughput and lead to user inequity,for this reason,in this paper,channel allocation and power allocation problems are formulated to maximize the system sum rate and minimum user achievable *** the construction model is non-convex and the response variables are high-dimensional,a distributed Deep Reinforcement Learning(DRL)framework called distributed Proximal Policy Optimization(PPO)is proposed to allocate or assign ***,several simulated agents are trained in a heterogeneous environment to find robust behaviors that perform well in channel assignment and power ***,agents in the collection stage slow down,which hinders the learning of other ***,a preemption strategy is further proposed in this paper to optimize the distributed PPO,form DP-PPO and successfully mitigate the straggler *** experimental results show that our mechanism named DP-PPO improves the performance over other DRL methods.

关键词： B5G Heterogeneous edge networks PPO Channel assignment Power allocation Throughput

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Hierarchical Transfer Multi-task Learning Approach for Scene Classification 27th

Hierarchical Transfer Multi-task Learning Approach for Scen...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Khoshkangini, Reza Tajgardan, Mohsen Jamali, Mahtab Ljungqvist, Martin Georg Mihailescu, Radu-Casian Davidsson, Paul Internet of Things and People Research Center Department of Computer Science and Media Technology Malmö University Malmö Sweden Faculty of Electrical and Computer Engineering Qom University of Technology Qom Iran Axis Communications AB Lund Sweden

ISBN: (纸本)9783031781063

This paper presents a novel Hierarchical Transfer and Multi-task Learning (HTMTL) approach designed to substantially improve the performance of scene classification networks by leveraging the collective influence of diverse scene types. HTMTL is distinguished by its ability to capture the interaction between various scene types, recognizing how context information from one scene category can enhance the classification performance of another. Our method, when applied to the Places365 dataset, demonstrates a significant improvement in the network’s ability to accurately identify scene types. By exploiting these inter-scene interactions, HTMTL significantly enhances scene classification performance, making it a potent tool for advancing scene understanding and classification. Additionally, this study explores the contribution of individual tasks and task groupings on the performance of other tasks. To further validate the generality of HTMTL, we applied it to the Cityscapes dataset, where the results also show promise. This indicates the broad applicability and effectiveness of our approach across different datasets and scene types. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Federated learning

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Detection and Prognosis of Pulmonary Tuberculosis Using ML Classifiers with Soft Computing 5

Detection and Prognosis of Pulmonary Tuberculosis Using ML C...

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5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Bisht, Girish Singh Ganesh, D. Kumar, Santosh Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science and Information Technology Bangalore India Noida Institute of Engineering and Technology Department of Internet of Things Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350383522

Several intriguing research works on soft computing techniques have recently been presented and for the creation of a pulmonary TB diagnosis system, researchers continue to build an accurate and trustworthy intelligent decision-making approach. The current diagnostic testing system processes are cumbersome and time-consuming to analyse. Since increased sensitivity and specificity can be attained, the diagnosis of TB still has to be improved upon using new speedy and accurate diagnostic models and procedures, which will help with disease prevention and control. Therefore, this review paper's significance lies in its ability to discriminate between the many soft computing methodologies used to help the diagnosis, identification, prediction, and intelligent categorization of pulmonary TB illness. Researchers and medical professionals anticipate employing soft computing methods in the field. 'Artificial neural networks, genetic algorithms, support vector machines, fuzzy logic', and others are a few of these. The most recent diagnostic techniques involve artificial neural networks. Predictive inference accuracy and easy-to-optimize, adoptable non-linear modelling of large data sets are some additional advantages of artificial neural networks, showing that they could be an important decision support tool in a variety of industries, including medicine. © 2024 IEEE.

关键词： Artificial Neural Network Fuzzy and Fuzzy Logic Genetic Algorithm Pulmonary Tuberculosis Support Vector Machine

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A Deep Assessmen of Smart Logistics Kind of Parks with the Fog Based and Enabled Sensor Cloud Type Platforms 1

A Deep Assessmen of Smart Logistics Kind of Parks with the F...

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1st International Conference on Innovative Sustainable Technologies for Energy, Mechatronics and Smart Systems, ISTEMS 2024

作者： Yadav, Savita Gupta, Ashish Preethi, D. Noida Institute of Engineering and Technology Department of Internet of Things Uttar Pradesh Greater Noida India Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350384246

The purpose of this research is to compare, in the environment of a clever logistics park, the effectiveness of fog-enabled sensor clouds (FSC) with traditional cloud computing with fog computing models. Expanding on our earlier work, we describe the physical instrument virtualization framework and scheme that are essential to the envisioned FSC. There is a careful construction of the network model and a mathematical explanation of the FSC parameters. We use a well-known logistics company in China is a case study to assess the efficacy of the suggested platform and clarify the network architecture in a real-world logistics situation. The experiment's results confirm that, with regard to bandwidth usage and service delay, the FSC for logistics parks is demonstrably superior to standard internet-based and fog computing models. © 2024 IEEE.

关键词： Fog

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