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8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Jamil, Ishat Raihan Humaira, Mayeesha Department of Mechanical Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Department of Computer Science and Engineering Ahsanullah University of Science and Technology Dhaka Bangladesh

AHMERS, active health monitoring and emergency response system, is a mobile application-based system that wirelessly connects to a smartwatch to constantly monitor the human body and respond to sudden changes in vital data, in case of emergency. This app monitors heartbeat rate, blood oxygen saturation, body temperature, and compares them with pre-set normal values. If the data deviates or the user presses one of the emergency switches, the app immediately asks the person if he/she is ok. If the person fails to respond within a few seconds to the "Are you ok?" message, the app continues to send out distress signals to pre-set phone numbers and server along with the person's altitude, latitude and longitude, and current location on the map so that help can be sent quickly. It can determine whether a person is suffering from a health-related problem such as heart failure, Corona virus infection, hypothermia, etc. © 2023 The Authors. Published by Elsevier B.V.

关键词： Blood Oxygen Saturation Body Temperature Health Monitoring Heart Rate

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Track-Rex:A universal toolbox for tracking recrystallization nucleation and grain growth behaviors in polycrystalline materials

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Journal of Materials science & Technology 2024年第30期197卷 149-159页

作者： Xun Zeng Haoran Yi Zhuoran Zeng Liang Yuan Sangbong Yi Junheng Gao Mark Rainforth Dikai Guan Department of Mechanical Engineering University of SouthamptonSouthamptonSO171BJUK College of Engineering and Computer Science Australian National UniversityACT 2601Australia College of Bioresources Chemical and Materials Engineering Shaanxi University of Science and TechnologyXi’an710021China Institute of Materials and Process Design Helmholtz-Zentrum HereonGeesthacht21502Germany Department of Materials Science and Engineering University of SheffieldSheffieldS13JDUK Institute for Carbon Neutrality University of Science and Technology BeijingNo.30 Xueyuan RoadHaidian DistrictBeijing100083China

Recrystallization annealing is widely used to tailor the microstructure and enhance the performance of cold-deformed metallic ***,the underlying recrystallization mechanisms are debated,even with the use of cutting-edge characterization ***,we develop a Track-Rex toolbox to analyze quasi-in-situ electron backscatter diffraction(EBSD)datasets of two magnesium(Mg)alloys dur-ing static recrystallization via grain *** results show that the recrystallized grains do not always grow;instead,they can shrink or even be *** is attributed to the presence of newly formed recrystallized grains that possess a growth advantage over the old recrystallized *** rare earth containing Mg-2.4Zn-0.2Ce wt.%(ZE20)alloy exhibits a higher nucleation activity in the shear bands compared to the commercial Mg-3Al-1 Zn(AZ31)*** of the nucleation timing and sites,re-crystallized grains in the ZE20 alloy show consistent off-basal orientations,serving as the origin of the rare earth ***,the off-basal texture of these recrystallized grains is further strengthened through preferential growth during subsequent *** the contrary,the recrystallized grains in the AZ31 exhibit scattered basal orientations that grow uniformly,resulting in a weak basal texture.

关键词： Grain correlation Grain tracking Recrystallization Texture Mg alloys

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Estimating the State of Health for Lithium-ion Batteries:A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1530-1543页

作者： Guijun Ma Zidong Wang Weibo Liu Jingzhong Fang Yong Zhang Han Ding Ye Yuan The School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China the College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China the Department of Computer Science Brunel University LondonUxbridgeMiddlesexUB83PHUnited Kingdom the School of Information Science and Engineering Wuhan University of Science and TechnologyWuhan 430081China the School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China

The state of health(SOH)is a critical factor in evaluating the performance of the lithium-ion batteries(LIBs).Due to various end-user behaviors,the LIBs exhibit different degradation modes,which makes it challenging to estimate the SOHs in a personalized *** this article,we present a novel particle swarm optimization-assisted deep domain adaptation(PSO-DDA)method to estimate the SOH of LIBs in a personalized manner,where a new domain adaptation strategy is put forward to reduce cross-domain distribution *** standard PSO algorithm is exploited to automatically adjust the chosen hyperparameters of developed DDA-based *** proposed PSODDA method is validated by extensive experiments on two LIB datasets with different battery chemistry materials,ambient temperatures and charge-discharge *** results indicate that the proposed PSO-DDA method surpasses the convolutional neural network-based method and the standard DDA-based *** Py Torch implementation of the proposed PSO-DDA method is available at https://***/mxt0607/PSO-DDA.

关键词： Deep transfer learning domain adaptation hyperparameter selection lithium-ion batteries(LIBs) particle swarm optimization state of health estimation(SOH)

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Convolutional Neural Networks Aided Reinforcement Learning for Accelerated Optimization of Antenna Topology

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Applied Computational Electromagnetics Society Journal 2025年第1期40卷 35-41页

作者： Dou, Jiangling Gong, Hao Wei, Shuaibing Chen, Haokang Chen, Yujie Shen, Tao Song, Jian Yunnan Key Laboratory of Computer Technologies Application Kunming University of Science and Technology Kunming650500 China School of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China College of Mechanical and Electrical Engineering Yunnan Electromechanical Vocational and Technical College Kunming650500 China

A machine learning (ML) framework is proposed to achieve the automatic and rapid optimization of antenna topologies. A convolutional neural network (CNN) is utilized as a surrogate model (SM) and is combined with reinforcement learning (RL) algorithms. Specifically, the RL agent interacts with simulation software to learn. Data accumulated from electromagnetic (EM) simulations are used to train the SM. The CNN-based SM predicts antenna performance based on the topology of the antenna. Subsequently, the SM replaces EM simulations within the RL training environment. The RL agent interacts with the CNN-based SM to search for the optimal topology. This approach significantly reduces dependence on time-consuming EM simulations. To validate the effectiveness of the optimization method, a center-fed microstrip patch antenna is optimized. Simulation results demonstrate that, compared to other optimization methods, impedance bandwidth is improved, while the number of simulation samples and optimization time are significantly reduced. © ACES.

关键词： Convolutional neural networks

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An Improved Deep Learning Framework Approach for Detecting the Psoriasis Disease

An Improved Deep Learning Framework Approach for Detecting t...

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2023 International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent engineering, ICECONF 2023

作者： Singh, Anuj Kumar, K.C. Nithin Kumar, M. Anand Negi, Harendra Singh Department of Computer Science Dehradun India Department of Mechanical Engineering Dehradun India

ISBN: (纸本)9798350334357

Normal skin is necessary for a healthy lifestyle since it is the most crucial component of the human body. However, it has several dermatological complications. One of these skin disorders is psoriasis. The research proposes a unique deep learning framework that assesses three separate scenarios, namely Visual Geometry Group-16, Visual Geometry Group-19, and Inception v3, and examines some cutting-edge deep learning algorithms using several measures, including 'AUC,' CA, Precision, F1, and Recall. Based on the results, Visual Geometry Group-19 is chosen as the feature extractor and Logistic Regression is chosen as the classifier. The 'AUC' value is 0.990, and the CA is 94.2%. © 2023 IEEE.

关键词： Geometry

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M3Rec: Selective State Space Models with Mixture-of-Modality Experts for Multi-Modal Sequential Recommendation

M3Rec: Selective State Space Models with Mixture-of-Modality...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Guo, Xu Zhang, Tong Xue, Yufei Wang, Chenxu Wang, Fuyun Cui, Zhen School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350368741

The rapid growth of multimedia-sharing platforms drives the development of recommender systems. While traditional ID-based methods for mining user behavior signals are well-studied, research into multimodal sequential recommendation remains nascent. Current approaches face three critical challenges: (1) inadequate modeling of user preferences across diverse modalities, (2) ineffective capture of user action sequence dependencies hinders representation learning of preferences, and (3) inefficiency in Transformer-based models due to the quadratic complexity of attention mechanisms. To address these issues, we propose M3Rec, a Mamba-based selective state space model incorporating Mixture-of-Modality experts for Multimodal sequential recommendation. M3Rec strengthens the modeling of user action sequence dependencies through shared Mamba blocks across modalities and employs modality experts to extract modality-specific user preferences. The shared Mamba blocks efficiently model long-term user preferences with fast inference and linear scalability through hardware-aware parallelism, enhancing ID-based sequence signals and filtering out non-action-dependent redundant information. This enables more accurate modeling of user preferences across heterogeneous data. Extensive experiments on three public datasets validate the model's effectiveness. The implementation is released at https://***/Xu107/M3Rec-main. © 2025 IEEE.

关键词： Mamba Multimedia Sequential Recommendation

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Improved Energy Efficient Divergent Path Routing for Energy-Harvesting Wireless Sensor Networks 9

Improved Energy Efficient Divergent Path Routing for Energy-...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Sivakumar, S. Sabaresan, V. Prakash, S. Om Dharmaraj, T.B. Nehru Institute of Engineering and Technology Department of Computer Science and Engineering India St.Joseph's Institute of Technology Department of Computer Science and Engineering India Ppg Institute of Technology Department of Mechanical Engineering India Ppg Institute of Technology Department of Information Technology India

ISBN: (纸本)9798350377972

Since packets are dropped when there is an insufficient connection between each of the sensor nodes in the network, a sensor node in a sensor network is unable to efficiently aggregate the data packets. Since each area has a different sensor node location, the sender node rarely shares information with its neighbour. Only a certain number of packets are received for each communication, the rest are dropped, and the communication is lost. In order to determine each node's minimum residual energy level, the node transmits packets on the path once more. It raises the energy consumption and packet loss rate. Energy-efficient packet aggregation along the network environment is the goal of the suggested Improved Energy Efficient Divergent Path Routing (IEEDP) technique. The node's position is clearly tracked before a different route is assigned for routing. Using metrics such as end-to-end delay, overhead for communication, packet delivery ratio, link stability, consumption of energy, packet loss, and network lifetime using a simulation model, the suggested improved energy efficient divergent path routing (IEEDP) approach outperformed existing methods like Wireless Access Range (WAR) and Congestion-Aware Clustering And Routing (CCR). Energy preservation is a process to extend the network's lifetime by examining the residual Energy Effects on EH-WSN. The Combining Packet Aggregation algorithm is made for sensor networks and collects data packets without any loss during the entire transmission period from the origin node to a target node in a network environment. It lowers energy consumption and packet loss rate. © 2024 IEEE.

关键词： Packet loss

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Elite-guided equilibrium optimiser based on information enhancement:Algorithm and mobile edge computing applications

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CAAI Transactions on Intelligence Technology 2024年第5期9卷 1126-1171页

作者： Zong-Shan Wang Shi-Jin Li Hong-Wei Ding Gaurav Dhiman Peng Hou Ai-Shan Li Peng Hu Zhi-Jun Yang Jie Wang School of Information Science and Engineering Yunnan UniversityKunmingChina Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhenChina Academic Affairs Office Yunnan University of Finance and EconomicsKunmingChina Faculty of Management and Economics Kunming University of TechnologyKunmingChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirutLebanon Department of Computer Science and Engineering University Centre for Research and DevelopmentChandigarh UniversityChennaiIndia Department of Computer Science and Engineering Graphic Era Deemed to Be UniversityDehradunIndia School of Computer Science Fudan UniversityShanghaiChina Rackham Graduate School University of MichiganAnn ArborMIUSA Research and Development Department Youbei Technology Co.LTDKunmingChina School of Mechanical and Power Engineering Zhengzhou UniversityZhengzhouChina

The Equilibrium Optimiser(EO)has been demonstrated to be one of the metaheuristic algorithms that can effectively solve global optimisation *** the paradox between exploration and exploitation operations while enhancing the ability to jump out of the local optimum are two key points to be addressed in EO *** alleviate these limitations,an EO variant named adaptive elite-guided Equilibrium Optimiser(AEEO)is ***,the adaptive elite-guided search mechanism enhances the balance between exploration and *** modified mutualism phase reinforces the information interaction among particles and local optima *** cooperation of these two mechanisms boosts the overall performance of the basic *** AEEO is subjected to competitive experiments with state-of-the-art algorithms and modified algorithms on 23 classical benchmark functions and IEE CEC 2017 function test *** results demonstrate that AEEO outperforms several well-performing EO variants,DE variants,PSO variants,SSA variants,and GWO variants in terms of convergence speed and *** addition,the AEEO algorithm is used for the edge server(ES)placement problem in mobile edge computing(MEC)*** experimental results show that the author’s approach outperforms the representative approaches compared in terms of access latency and deployment cost.

关键词： ANT COLONY optimization CLOUD COMPUTING GENETIC ALGORITHMS SWARM intelligence

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Imaging and structure analysis of ferroelectric domains,domain walls,and vortices by scanning electron diffraction

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npj Computational Materials 2024年第1期10卷 2154-2161页

作者： Ursula Ludacka Jiali He Shuyu Qin Manuel Zahn Emil Frang Christiansen Kasper A.Hunnestad Xinqiao Zhang Zewu Yan Edith Bourret István Kézsmárki Antonius T.Jvan Helvoort Joshua Agar Dennis Meier Department of Materials Science and Engineering NTNU Norwegian University of Science and TechnologyTrondheimNorway Department of Computer Science and Engineering Lehigh UniversityBethlehemPAUSA Department of Mechanical Engineering and Mechanics Drexel UniversityPhiladelphiaPAUSA Experimental Physics V University of AugsburgAugsburgGermany Department of Physics NTNU Norwegian University of Science and TechnologyTrondheimNorway Department of Physics ETH ZurichZürichSwitzerland Materials Sciences Division Lawrence Berkeley National LaboratoryBerkeleyCAUSA

Direct electron detectors in scanning transmission electron microscopy give unprecedented possibilities for structure analysis at the *** electronic and quantum materials,this new capability gives access to,for example,emergent chiral structures and symmetry-breaking distortions that underpin functional *** nanoscale structural features with statistical significance,however,is complicated by the subtleties of dynamic diffraction and coexisting contrast mechanisms,which often results in a low signal-to-noise ratio and the superposition of multiple signals that are challenging to deconvolute.

关键词： properties structure ferroelectric

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Analysis of performance, combustion, and emission parameters in a reactivity-controlled combustion ignition (RCCI) engine–an intensive review

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International Journal of Ambient Energy 2022年第1期43卷 6839-6848页

作者： Elumalai, P.V. Pradeepkumar, A.R. Murugan, M. Saravanan, A. Sreenivasa Reddy, M. Rama Sree, S. Meenakshi Sundaram, G. Department of Mechanical Engineering Aditya Engineering College Surampalem India Department of Mechanical Engineering Dhanalashmi College of Engineering Chennai India Department of Mechanical Engineering Aditya College of Engineering and Technology Surampalem India Department of Computer Science Engineering Aditya Engineering College Surampalem India Department of Electronics and Communication Engineering Aditya College of Engineering Surampalem India

The new diversion of research in the field of engine modification is reactivity-induced compression ignition (RCCI). Researchers recommend that RCCI is the solution for regulating pre-mixed combustion, thereby promoting lean air–fuel mixture combustion. It is also suitable for low-temperature operations. The combination of lean mixture and low-temperature operations leads to a reduction of the oxides of nitrogen and particles of soot production during combustion. This paper analyses the principle and methodology of RCCI and compares its performance with homogeneous controlled compression ignition (HCCI). An intensive literature review is done and a concluding report is compiled. This will be an essential content for researchers who pursue their experimental and analytical work in RCCI. The future scope of RCCI can be extended to alternate fuel sources such as biodiesel ethanol and natural gas by adopting HCCI concepts. However, there are a few limitations in this, such as higher HC and CO emissions, which may necessitate oxidation catalysts. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Biodiesel

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