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Carbon-based interface engineering and architecture design for high-performance lithium metal anodes

Carbon Energy 2024年第1期6卷 207-235页

作者： Na Zhu Yuxiang Yang Yu Li Ying Bai Junfeng Rong Chuan Wu SINOPEC Research Institute of Petroleum Processing Co. Ltd.BeijingChina Beijing Key Laboratory of Environmental Science and Engineering School of Materials Science and EngineeringBeijing Institute of TechnologyBeijingChina Yangtze Delta Region Academy of Beijing Institute of Technology JiaxingChina

Metallic lithium(Li)is considered the“Holy Grail”anode material for the nextgeneration of Li batteries with high energy density owing to the extraordinary theoretical specific capacity and the lowest negative electrochemical ***,owing to inhomogeneous Li-ion flux,Li anodes undergo uncontrollable Li deposition,leading to limited power output and practical *** materials and their composites with controllable structures and properties have received extensive attention to guide the homogeneous growth of Li to achieve high-performance Li *** this review,the correlation between the behavior of Li anode and the properties of carbon materials is ***,we review emerging strategies for rationally designing high-performance Li anodes with carbon materials,including interface engineering(stabilizing solid electrolyte interphase layer and other functionalized interfacial layer)and architecture design of host carbon(constructing three-dimension structure,preparing hollow structure,introducing lithiophilic sites,optimizing geometric effects,and compositing with Li).Based on the insights,some prospects on critical challenges and possible future research directions in this field are *** is anticipated that further innovative works on the fundamental chemistry and theoretical research of Li anodes are needed.

关键词： carbon materials dendrites hosts interfacial layers Li metal anodes

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SIGN LANGUAGE RECOGNITION USING CNN 2

SIGN LANGUAGE RECOGNITION USING CNN

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Allam, Sangeetha Balaram, Allam Rao, Yedavalli Venkata Raghava Kiran, Ajmeera Valpadasu, Hema Navya, Soleti Mlr Institute of Technology Department of Computer Science & Engineering Hyderabad India Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India Cse Aiml Avniet Jntuh Aiml Dept India Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad Dundigal India Computer Science and Engineering Mlr Institute of Technology Telangana Hyderabad India Mlr Institute of Technology Department of Computer Science and Information Technology India

ISBN: (纸本)9798350370188

Conversation between both the deaf and the general population is becoming exceedingly challenging, and there is no reputable translator accessible in society to aid. This program enables real-time voice and signal language translation, in distinctive: 1. recognizing male or female signals 2. Establishing a system learning model for interpreting image-to-text data. 3. Seeking innovative terms Four. Constructing Sentences 5. After creating all of the content, 6. Is to obtain the audio output. The goal of this research is to develop a framework for a potential sign language interpreter who could also translate conversations between sign languages into written and spoken English. If there had a translator like this, it would be much easier for many deaf and partially deaf people to interact with others in everyday situations © 2024 IEEE.

关键词： Translation (languages)

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A Scalable and Secure Facial Recognition Attendance System Leveraging CNN Algorithms for Real-Time Accuracy and Efficiency

A Scalable and Secure Facial Recognition Attendance System L...

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2025 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Kumar, Aakash Sharma, Jiya Renjith, P.N. Vellore Institute of Technology School of Computer Science and Engineering India

ISBN: (纸本)9798331529833

The facial recognition attendance system represents a modern approach to attendance tracking, designed to improve efficiency, accuracy, and security in various organizational settings. Advanced biometric technologies are leveraged to capture and encode facial features, creating unique digital identifiers for each individual. The methodology employs cutting-edge facial recognition algorithms powered by convolutional neural networks (CNNs) with a 99.5% recognition accuracy rate. These algorithms extract and encode facial vectors with sub-millisecond latency, which are then compared in real-time against a secure, encrypted database of preregistered individuals. Upon a successful match, the system automatically records the attendance, ensuring an accurate and efficient process. With an intuitive web interface built on ReactJS and a backend supported by *** and MongoDB, the system provides seamless access to attendance records and administrative functionalities. The entire attendance recording process is optimized for speed, typically completing within two seconds per individual. Additionally, advanced anti-spoofing measures and integration support with existing HR management systems redefine traditional attendance management practices with a scalable, robust, and secure solution. (Abstract) © 2025 IEEE.

关键词： Efficiency

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Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

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computers, Materials & Continua 2024年第3期78卷 4243-4262页

作者： Youseef Alotaibi B.Rajasekar R.Jayalakshmi Surendran Rajendran Department of Software Engineering College of ComputingUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Electronics and Communication Engineering Sathyabama Institute of Science and TechnologyChennai600119India Department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical ScienceChennai602105India

Rapid development in Information technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)*** networks give a safe and more effective driving experience by presenting time-sensitive and location-aware *** communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with ***,the scheme of an effectual routing protocol for reliable and stable communications is *** research demonstrates that clustering is an intelligent method for effectual routing in a mobile ***,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in *** FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the *** accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust *** the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR *** experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

关键词： Vehicular networks communication protocol clustering falcon optimization algorithm routing

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The Power of Virtual Reality-Next-Gen Radiology Training 15

The Power of Virtual Reality-Next-Gen Radiology Training

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Ahmed, Alisha Rajarajeswari, S. Mallegowda, M. Subash, N. Ramaiah Institute of Technology Computer Science Engineering India

ISBN: (纸本)9798350370249

Advancements in medical education are continuously evolving, with virtual reality (VR) emerging as a groundbreaking technology reshaping the landscape of radiology training. This abstract presents a paradigm shift in radiology education through the creation of immersive VR simulations tailored for medical students and professionals. Our VR simulation leverages state-of-the-art graphics, interactive modules, and realistic patient scenarios to provide a dynamic learning environment. Users can navigate through virtual clinics, interact with lifelike patients, and practice diagnostic procedures in a risk-free yet lifelike setting. The incorporation of haptic feedback and spatial audio enhances realism, fostering deeper engagement and skill acquisition. Furthermore, our VR simulation integrates artificial intelligence algorithms for personalized learning pathways, adapting to individual learning styles and providing real-time feedback. By harnessing the power of VR, this simulation not only enhances diagnostic skills but also promotes critical thinking, teamwork, and decision-making under pressure. This abstract explores the transformative impact of VR simulations in revolutionizing radiology education, paving the way for a new era of experiential learning in medical training. © 2024 IEEE.

关键词： Radiology

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Porous nanofibrous dressing enables mesenchymal stem cell spheroid formation and delivery to promote diabetic wound healing

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Chinese Journal of Chemical engineering 2024年第4期68卷 156-164页

作者： Kexin Zhang Wenmin Zhang Heng An Zhe Huang Yanzhen Wen Xiangyu Jiao Yongqiang Wen College of Chemical Engineering and Technology Taiyuan University of Science and TechnologyTaiyuan 030024China Beijing Key Laboratory for Bioengineering and Sensing Technology Daxing Research InstituteSchool of Chemistry&Biological EngineeringUniversity of Science&Technology BeijingBeijing 100083China

Delayed and nonhealing of diabetic wounds imposes substantial economic burdens and physical pain on *** stem cells(MSCs)promote diabetic wound *** when MSCs aggregate into multicellular spheroids,their therapeutic effect is ***,traditional culture platforms are inadequate for the efficient preparation and delivery of MSC spheroids,resulting in inefficiencies and inconveniences in MSC spheroid *** this study,a three-dimensional porous nanofibrous dressing(NFD)is prepared using a combination of electrospinning and homogeneous *** thermal crosslinking,the NFD not only achieves satisfactory elasticity but also maintains notable *** the design of its structure and chemical composition,the NFD allows MSCs to spontaneously form MSC spheroids with controllable sizes,serving as MSC spheroid delivery systems for diabetic wound *** importantly,MSC spheroids cultured on the NFD exhibit improved secretion of vascular endothelial growth factor,basic fibroblast growth factor,and hepatocyte growth factor,thereby accelerating diabetic wound *** NFD provides a competitive strategy for MSC spheroid formation and delivery to promote diabetic wound healing.

关键词： Electrospinning Homogenization Biomedical engineering Nanomaterials Stem cell spheroids Diabetic wound healing

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Efficient Cache Retrieving Scheme in VANET via Online Reinforcement Learning

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IEEE Transactions on Vehicular technology 2025年第6期74卷 9506-9519页

作者： Tan, Zhenhao Chen, Bin Li, Ruidong Yang, Lei Xu, Xiaohua University of Science and Technology of China School of Computer Science and Technology Hefei230026 China Kanazawa University Institute of Science and Engineering Ishikawa920-1192 Japan South China University of Technology School of Software Engineering Guangdong510640 China

The implementation of intelligent driving technology is inseparable from reliable wireless communication and efficient cache scheduling in Vehicle Ad-hoc Networks (VANETs). The purpose of cache scheduling in VANETs is to provide efficient and fast data services to vehicles. In response to difficult to handle wireless communication interference and high requirements for communication delay and energy consumption optimization in vehicle-road cooperation, we propose a new communication model of "Retrieving-Cast"to simplify the cache scheduling process oriented by data requirements. In V2I mode, consider the uplink of all roadside units(RSUs) retrieving data from vehicles, and prioritize data retrieving based on factors such as the number, density, and urgency of vehicles within the communication coverage range of RSUs. We hope that as many high-priority RSUs as possible to complete cached data retrieving as soon as possible under wireless communication interference. To overcome the limitations of traditional heuristic algorithms with low scheduling efficiency and deep learning methods requiring a large amount of training data, we propose a double-online reinforcement learning method, which efficiently solves the cache retrieval scheduling problem. Through experiments and analysis, our method achieved better scheduling results compared to traditional approximation algorithms and single greedy Deep Q-learning methods. The designed data transformation method also addresses the issue of requiring a large amount of training data, enabling rapid computation of scheduling requests in the network at an extremely low training cost, meeting the low-latency computation requirements in VANETs. © 1967-2012 IEEE.

关键词： Reinforcement learning

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Secure deep learning-based energy efficient routing with intrusion detection system for wireless sensor networks

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Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 8587-8603页

作者： Sakthimohan, M. Deny, J. Elizabeth Rani, G. Department of Electronics and Communication Engineering Kalasalingam Academy of Research and Education Tamil Nadu India Department of Computer Science and Engineering Kalaignar Karunanidhi Institute of Technology Tamil Nadu Coimbatore India

In general, wireless sensor networks are used in various industries, including environmental monitoring, military applications, and queue tracking. To support vital applications, it is crucial to ensure effectiveness and security. To prolong the network lifetime, most current works either introduce energy-preserving and dynamic clustering strategies to maintain the optimal energy level or attempt to address intrusion detection to fix attacks. In addition, some strategies use routing algorithms to secure the network from one or two attacks to meet this requirement, but many fewer solutions can withstand multiple types of attacks. So, this paper proposes a secure deep learning-based energy-efficient routing (SDLEER) mechanism for WSNs that comes with an intrusion detection system for detecting attacks in the network. The proposed system overcomes the existing solutions’ drawbacks by including energy-efficient intrusion detection and prevention mechanisms in a single network. The system transfers the network’s data in an energy-aware manner and detects various kinds of network attacks in WSNs. The proposed system mainly comprises two phases, such as optimal cluster-based energy-aware routing and deep learning-based intrusion detection system. Initially, the cluster of sensor nodes is formed using the density peak k-mean clustering algorithm. After that, the proposed system applies an improved pelican optimization approach to select the cluster heads optimally. The data are transmitted to the base station via the chosen optimal cluster heads. Next, in the attack detection phase, the preprocessing operations, such as missing value imputation and normalization, are done on the gathered dataset. Next, the proposed system applies principal component analysis to reduce the dimensionality of the dataset. Finally, intrusion classification is performed by Smish activation included recurrent neural networks. The proposed system uses the NSL-KDD dataset to train and test it. The

关键词： Intrusion detection

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A Secure Framework for WSN-IoT Using Deep Learning for Enhanced Intrusion Detection

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computers, Materials & Continua 2024年第10期81卷 471-501页

作者： Chandraumakantham Om Kumar Sudhakaran Gajendran Suguna Marappan Mohammed Zakariah Abdulaziz S.Almazyad School of Computer Science&Engineering Vellore Institute of TechnologyChennai CampusChennai600127India School of Electronics&Engineering Vellore Institute of TechnologyChennai CampusChennai600127India Department of Computer Sciences and Engineering College of Applied ScienceKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

The security of the wireless sensor network-Internet of Things(WSN-IoT)network is more challenging due to its randomness and self-organized *** detection is one of the key methodologies utilized to ensure the security of the *** intrusion detection mechanisms have issues such as higher misclassification rates,increased model complexity,insignificant feature extraction,increased training time,increased run time complexity,computation overhead,failure to identify new attacks,increased energy consumption,and a variety of other factors that limit the performance of the intrusion system *** this research a security framework for WSN-IoT,through a deep learning technique is introduced using Modified Fuzzy-Adaptive DenseNet(MF_AdaDenseNet)and is benchmarked with datasets like NSL-KDD,UNSWNB15,CIDDS-001,Edge IIoT,Bot *** this,the optimal feature selection using Capturing Dingo Optimization(CDO)is devised to acquire relevant features by removing redundant *** proposed MF_AdaDenseNet intrusion detection model offers significant benefits by utilizing optimal feature selection with the CDO *** results in enhanced Detection Capacity with minimal computation complexity,as well as a reduction in False Alarm Rate(FAR)due to the consideration of classification error in the fitness *** a result,the combined CDO-based feature selection and MF_AdaDenseNet intrusion detection mechanism outperform other state-of-the-art techniques,achieving maximal Detection Capacity,precision,recall,and F-Measure of 99.46%,99.54%,99.91%,and 99.68%,respectively,along with minimal FAR and Mean Absolute Error(MAE)of 0.9%and 0.11.

关键词： Deep learning intrusion detection fuzzy rules feature selection false alarm rate accuracy wireless sensor networks

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Thermal-force control ability under variation of electromagnetic stick structure parameters in RPECT

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Journal of Iron and Steel research International 2024年第1期31卷 224-236页

作者： Ting-song Yang Wen-quan Sun Feng-shan Du An-rui He Quan Yang National Engineering Research Center of Advanced Rolling and Intelligent Manufacturing University of Science and Technology BeijingBeijing100083China Institute of Engineering and Technology University of Science and Technology BeijingBeijing100083China College of Mechanical Engineering Yanshan UniversityQinhuangdao066004HebeiChina

Thermal-force driving of roll profile electromagnetic control technology(RPECT),which can be used to adjust the roll profile,can be affected by the sequential temperature rise between the electromagnetic stick(ES)and electromagnetic control *** to the limited space of ES and induction coil,the cross-sectional area of induction coil can be inevitably affected by changing the size of the ES induction zone,which can further change the energy input under the same electromagnetic parameters,the temperature rising effect and the bulging *** investigate this phenomenon,the effects of the radius of the induction zone on the thermal-force contribution ratio,the heating ability of ES and the temperature distribution were analyzed through an electromagnetic-thermal-structural finite element *** ensure that the results are applicable to RPECT,the thermal energy conversion ability and thermal-force roll crown control ability under different lengths of the induction zone were *** was found that whether the current density regulation mode or the current frequency regulation mode is adopted,the cases with 20 or 25 mm radius of the induction zone have the great thermal energy conversion ability and the good thermal-force roll crown control *** reasonable adjustment of the length of the induction zone can reduce the radius required for the maximum energy efficiency *** with the results of the simulation analysis,the optimization of ES based on the control ability maximization requirement is achieved,which provides the base for the design and configuration of ES in RPECT.

关键词： Roll profile electromagnetic control technology Electromagnetic stick Electromagnetic control roll Induction area Thermal-force driving

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