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4th IEEE International Conference on Emerging Techniques in Computational Intelligence, ICETCI 2024

作者： Vishnukumar, Ravula Padma, Adla Ramaiah, Mangayarkarasi School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350387063

IoT and AI created a Transportation Management System, resulting in the Internet of Vehicles. Intelligent vehicles are combined with contemporary communication technologies (5G) to achieve automated driving and adequate mobility. IoV faces security issues in the next five (5) areas: data safety, V2X communication safety, platform safety, Intermediate Commercial Vehicles (ICV) safety, and intelligent device safety. Numerous types of AI models have been created to reduce the outcome infiltration risks on ICVs. The need to integrate confidence, transparency, and repeatability into the creation of Artificial Intelligence (AI) for the safety of ICV and to deliver harmless transport systems, on the other hand, has led to an increase in explainable AI (XAI). Therefore, the space of this analysis protected the XAI models employed in ICV intrusion detection systems (IDSs), their taxonomies, and available research concerns. The study's findings demonstrate that, despite its relatively recent submission to ICV, XAI is a potential explore area for those looking to increase the net effect of ICVs. The paper also demonstrates that XAI's greater transparency will help it gain acceptance in the vehicle industry. © 2024 IEEE.

关键词： Network intrusion

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Effect of an Inclined Slots on the Power Consumption and Vortices Size in a Rushton Turbine Agitated Tank

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Chinese Journal of Mechanical engineering 2023年第6期36卷 261-276页

作者： Sarra Youcefi Mohamed Bouzit Abdelkader Youcefi Abderrahim Mokhefi Laboratory of Applied Mechanics Department of Mechanical EngineeringUniversity of Sciences and Technology of OranOran 31000Algeria Laboratory of Maritime Sciences and Engineering Department of Marine EngineeringUniversity of Science and Technology of OranOran 31000Algeria Laboratory of Aeronautics and Propulsion Systems Department of Mechanical EngineeringUniversity of Science and Technology of OranOran 31000Algeria Laboratory of Mechanics Modeling and ExperimentationDepartment of Mechanical EngineeringTahri Mohamed University of BecharBechar 08000Algeria

Mechanical agitation in baffled vessels with turbines plays a vital role in achieving homogeneous fluid mixing and promoting various transfer ***,designing vessels with optimal energy efficiency and flow dynamics is essential to enhance operational performance and eliminate flow ***,the present research focuses on a numerical investigation of the impact of inclined slots with different angles installed at the side-wall of a cylindrical vessel equipped with a Rushton *** study explores power consumption and vortex size while considering various rotation directions of the impeller with different rotation *** numerical simulations are conducted for Reynolds numbers ranging from 104 to 105,using the RANS k-εturbulence model to govern the flow inside the stirred vessel,accounting for mass and momentum *** results have shown that the installation of slots reduces power consumption and vortex size compared to conventional vessel ***,increasing the slot angle from 0 to 32.5°further reduces energy consumption and vortex size,especially with negative rotation *** the other hand,increasing the Reynolds numbers leads to a decrease in power consumption and an increase in vortex *** present research therefore proposes a design for con-structing Rushton-turbine stirred vessels offering optimal operation,characterized by reduced energy consumption and minimized vortex size.

关键词： Mixing Stirred tank Rushton turbine Inclined slots Hydrodynamic Power consumption Vortices size

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Femtosecond laser-induced periodic surface structures on hard and brittle materials

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science China(Technological sciences) 2024年第1期67卷 19-36页

作者： ZHAO GuoXu WANG Gong LI YunFei WANG Lei LIAN YuDong YU Yu ZHAO Hui WANG YuLei LU ZhiWei Center for Advanced Laser Technology Hebei University of TechnologyTianjin 300401China Hebei Key Laboratory of Advanced Laser Technology and Equipment Tianjin 300401China State Key Laboratory of Integrated Optoelectronics College of Electronic Science and EngineeringJilin UniversityChangchun 130012China School of Information and Electrical Engineering Hebei University of EngineeringHandan 056038China

Hard and brittle materials have high hardness,excellent optical stability,chemical stability,and high thermal ***,they have huge application potential in various fields,such as optical components,substrate materials,and quantum information,especially under harsh conditions,such as high temperatures and high *** laser direct writing technology has greatly promoted the development of femtosecond laser-induced periodic surface structure(Fs-LIPSS or LIPSS by a femtosecond laser)applications of hard and brittle materials due to its high precision,controllability,and three-dimensional processing *** far,LIPSSs have been widely used in material surface treatment,optoelectronic devices,and ***,a consensus has not been reached regarding the formation mechanism of LIPSSs on hard and brittle *** this paper,three widely accepted LIPSS formation mechanisms are introduced,and the characteristics and applications of LIPSSs on diamonds,silicon,silicon carbide,and fused silica surfaces in recent years are *** addition,the application prospects and challenges of LIPSSs on hard and brittle materials by a femtosecond laser are discussed.

关键词： laser-induced periodic surface structures hard and brittle materials femtosecond laser

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Physics-Informed Neural Networks with Two Weighted Loss Function Methods for Interactions of Two-Dimensional Oceanic Internal Solitary Waves

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Journal of systems science & Complexity 2024年第2期37卷 545-566页

作者： SUN Junchao CHEN Yong TANG Xiaoyan School of Mathematical Sciences Key Laboratory of Mathematics and Engineering Applications(Ministry of Education)&Shanghai Key Laboratory of PMMPEast China Normal UniversityShanghai 200241China College of Mathematics and Systems Science Shandong University of Science and TechnologyQingdao 266590China

The multiple patterns of internal solitary wave interactions(ISWI)are a complex oceanic *** remote sensing techniques indirectly detect these ISWI,but do not provide information on their detailed structure and ***,the authors considered a three-layer fluid with shear flow and developed a(2+1)Kadomtsev-Petviashvili(KP)model that is capable of describing five types of oceanic ISWI,including O-type,P-type,TO-type,TP-type,and *** learning models,particularly physics-informed neural networks(PINN),are widely used in the field of fluids and internal solitary ***,the authors find that the amplitude of internal solitary waves is much smaller than the wavelength and the ISWI occur at relatively large spatial scales,and these characteristics lead to an imbalance in the loss function of the PINN *** solve this problem,the authors introduce two weighted loss function methods,the fixed weighing and the adaptive weighting methods,to improve the PINN *** successfully simulated the detailed structure and dynamics of ISWI,with simulation results corresponding to the satellite *** particular,the adaptive weighting method can automatically update the weights of different terms in the loss function and outperforms the fixed weighting method in terms of generalization ability.

关键词： Internal solitary wave interactions KP equation PINN method weighted loss function method

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Modulation of inactive Li_(2)O via iodinated MOF nanocapsules interfacial transformation engineering for high-performance solid electrolyte interphase

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Journal of Energy Chemistry 2025年第5期104卷 482-493页

作者： Xingxing Zhang Qingmei Su Gaohui Du Bingshe Xu Xuehan Hou Xiaowei Yang Weihao Shi Zhuo Chen Yang Shi Yujie Lv Wenhuan Huang School of Materials Science&Engineering Shaanxi University of Science and TechnologyXi’an 710021ShaanxiChina Key Laboratory of Chemical Additives for China National Light Industry College of Chemistry and Chemical EngineeringShaanxi University of Science and TechnologyXi’an 710021ShaanxiChina Materials Institute of Atomic and Molecular Science School of Physics&Information ScienceShaanxi University of Science and TechnologyXi’an 710021ShaanxiChina School of Chemistry and Chemical Engineering Shanghai Jiaotong UniversityShanghai 200240China

Lithium(Li)deposition and nucleation at solid electrolyte interphase(SEI)is the main origin for the capacity decay in Li metal batteries(LMBs).SEI conversion with enhanced electrochemical and mechanical properties is an effective approach to achieve uniform nucleation of Li^(+)and stabilize the lithium metal ***,complex interfacial reaction mechanisms and interface compatibility issues hinder the development of SEI conversion strategies for stabilizing lithium metal ***,we presented the release of I_(3)^(-)in–NH_(2)-modified metal–organic frameworks for a Li metal surface SEI phase conversion ***–NH_(2)group in MOF pores induced the formation of I_(3)^(-)from I_(2),which was further spontaneously reacted with inactive Li_(2)O transforming into high-performance LiI and LiIO_(3)***,theoretical calculation provided deeply insight into the unique reconstructed interfacial formation and electrochemical mechanism of rich LiI and LiIO_(3)*** a result,the Li^(+)deposition and nucleation were improved,facilitating the transport kinetics of Li^(+)and inhibiting the growth of lithium *** assembled solid-state Li||LiFePO_(4)full cells exhibited superior long-term stability of 800 cycles and high Coulombic efficiency(>99%),Li||LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)pouch cell also displayed superior practical performance over 200 cycles at 2 C,high loading of 5 mg cm^(-2)and safety *** innovative SEI design strategy promotes the development of high-performance solid-state Li metal batteries.

关键词： Solid electrolyte interphase(SEI) SEI phase conversion MOF Nano-capsule Solid-state electrolytes Li metal battery

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Glycine betaine modulates extracellular polymeric substances to enhance microbial salinity tolerance

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Environmental science and Ecotechnology 2024年第4期20卷 259-268页

作者： Yan Xia Xinbai Jiang Shuaishuai Guo Yuxuan Wang Yang Mu Jinyou Shen Key Laboratory of Environmental Remediation and Ecological Health Ministry of Industry and Information TechnologySchool of Environmental and Biological EngineeringNanjing University of Science and TechnologyNanjing210094China CAS Key Laboratory of Urban Pollutant Conversion Department of Environmental Science and EngineeringUniversity of Science&Technology of ChinaHefei230026China

High salinity inhibits microbial activity in the bioremediation of saline *** alleviate osmotic stress,glycine betaine(GB),an osmoprotectant,is added to enhance the secretion of extracellular polymeric substances(EPS).These EPS are pivotal in withstanding environmental stressors,yet the intricate interplay between GB supplementation and microbial responses through EPS modificationsdencompassing composition,molecular architecture,and electrochemical featuresdremains elusive in hypersaline *** we show microbial strategies for salinity endurance by investigating the impact of GB on the dynamic alterations of EPS *** findings reveal that GB supplementation at 3.5%salinity elevates the total EPS(T-EPS)content from 12.50±0.05 to 24.58±0.96 mg per g dry cell *** observed shift in zeta potential from-28.95 to-6.25 mV at 0%and 3.5%salinity,respectively,with GB treatment,indicates a reduction in electrostatic repulsion and ***,the EPS protein secondary structure transition from b-sheet to a-helix,with GB addition,signifies a more compact protein configuration,less susceptible to salinity *** analyses,including cyclic voltammetry(CV)and differential pulse voltammetry(DPV),reveal GB's role in promoting the release of exogenous electron shuttles,such as flavins and c-type cytochromes(c-Cyts).The enhancement in DPV peak areas(Q_(DPV))with GB addition implies an increase in available extracellular electron transfer *** investigation advances our comprehension of microbial adaptation mechanisms to salinity through EPS modifications facilitated by GB in saline habitats.

关键词： High salinity Extracellular polymeric substances Glycine betaine Protein secondary structure Extracellular electron transfer

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Representation learning via an integrated autoencoder for unsupervised domain adaptation

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Frontiers of Computer science 2023年第5期17卷 75-87页

作者： Yi ZHU Xindong WU Jipeng QIANG Yunhao YUAN Yun LI School of Information Engineering Yangzhou UniversityYangzhou 225127China Key Laboratory of Knowledge Engineering with Big Data(Ministry of Education of China) Hefei University of TechnologyHefei 230009China School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230601China

The purpose of unsupervised domain adaptation is to use the knowledge of the source domain whose data distribution is different from that of the target domain for promoting the learning task in the target *** key bottleneck in unsupervised domain adaptation is how to obtain higher-level and more abstract feature representations between source and target domains which can bridge the chasm of domain ***,deep learning methods based on autoencoder have achieved sound performance in representation learning,and many dual or serial autoencoderbased methods take different characteristics of data into consideration for improving the effectiveness of unsupervised domain ***,most existing methods of autoencoders just serially connect the features generated by different autoencoders,which pose challenges for the discriminative representation learning and fail to find the real cross-domain *** address this problem,we propose a novel representation learning method based on an integrated autoencoders for unsupervised domain adaptation,called *** capture the inter-and inner-domain features of the raw data,two different autoencoders,which are the marginalized autoencoder with maximum mean discrepancy(mAE)and convolutional autoencoder(CAE)respectively,are proposed to learn different feature *** higher-level features are obtained by these two different autoencoders,a sparse autoencoder is introduced to compact these inter-and inner-domain *** addition,a whitening layer is embedded for features processed before the mAE to reduce redundant features inside a local *** results demonstrate the effectiveness of our proposed method compared with several state-of-the-art baseline methods.

关键词： unsupervised domain adaptation representation learning marginalized autoencoder convolutional autoen-coder sparse autoencoder

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Broadband Chaos Generation and Synchronization Induced by Integrated Tri-section Laser

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IEEE Access 2024年 13卷 1-1页

作者： Guo, Yuanyuan Wei, Wuyin Gao, Hua Zhang, Yuanye Zhao, Tong Jia, Zhiwei Chang, Pengfa Wang, Longsheng Wang, Anbang Wang, Yuncai Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province Taiyuan China College of Information Engineering Shanxi Vocational University of Engineering Science and Technology Taiyuan China School of Information Engineering Guangdong University of Technology Guangzhou China

Broadband chaos generation is numerically demonstrated using an integrated tri-section laser which is composed of mutually coupled distributed feedback (DFB) lasers with a phase section, and the broadband chaos synchronization of two DFB lasers is achieved using the integrated laser as a driver. The simulation results indicate that the integrated tri-section laser with optical feedback can generate broadband chaos with a bandwidth up to 34 GHz, based on dual-mode beating effect. The influence of feedback strength and frequency interval on the chaos bandwidth are studied in detail. As a common driving signal, the broadband chaos signal can induce the response DFB lasers to generate chaos signals with a bandwidth of no less than 25 GHz and meanwhile achieve chaos synchronization with a correlation coefficient beyond 0.98. The low correlation coefficient between the drive signal and the response signal ensures the security of the chaos carrier from the public channel. Moreover, the dynamic properties of the integrated laser and the influence of the external parameters on chaotic synchronization are also investigated. Authors

关键词： Distributed feedback lasers

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Single-level Discrete Two Dimensional Wavelet Transform Based Multiscale Deep Learning Framework for Two-Wheeler Helmet Classification

EAI Endorsed Transactions on Industrial Networks and Intelli...

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EAI Endorsed Transactions on Industrial Networks and Intelligent systems 2025年第2期12卷 1-13页

作者： Annadurai, Amrutha Prusty, Manas Ranjan Pandey, Trilok Nath Patra, Subhra Rani School of Computer Science and Engineering Vellore Institute of Technology Chennai India Centre for Cyber Physical Systems Vellore Institute of Technology Chennai India Information Systems and Operations Management University of Texas at Arlington Texas 76019 United States

INTRODUCTION: A robust method is proposed in this paper to detect helmet usage in two-wheeler riders to enhance road safety. OBJECTIVES: This involves a custom made dataset that contains 1000 images captured under diverse real-world scenarios, including variations in helmet size, colour, and lighting conditions. This dataset has two classes namely with helmet and without helmet. METHODS: The proposed helmet classification approach utilizes the Multi-Scale Deep Convolutional Neural Network (CNN) framework cascaded with Long Short-Term Memory (LSTM) network. Initially the Multi-Scale Deep CNN extracts modes by applying Single-level Discrete 2D Wavelet Transform (dwt2) to decompose the original images. In particular, four different modes are used for segmenting a single image namely approximation, horizontal detail, vertical detail and diagonal detail. After feeding the segmented images into a Multi-Scale Deep CNN model, it is cascaded with an LSTM network. RESULTS: The proposed model achieved accuracies of 99.20% and 95.99% using both 5-Fold Cross-Validation (CV) and Hold-out CV methods, respectively. CONCLUSION: This result was better than the CNN-LSTM, dwt2-LSTM and a tailor made CNN model. © 2025 A. Annadurai et al.

关键词： Convolutional neural networks

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Boosting Adversarial Training with Learnable Distribution

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Computers, Materials & Continua 2024年第3期78卷 3247-3265页

作者： Kai Chen Jinwei Wang James Msughter Adeke Guangjie Liu Yuewei Dai School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing210044China Key Laboratory of Intelligent Support Technology for Complex Environments Ministry of EducationNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Nanjing Center for Applied Mathematics Nanjing211135China

In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural *** training is one of the most potent methods to defend against adversarial ***,the difference in the feature space between natural and adversarial examples hinders the accuracy and robustness of the model in adversarial *** paper proposes a learnable distribution adversarial training method,aiming to construct the same distribution for training data utilizing the Gaussian mixture *** distribution centroid is built to classify samples and constrain the distribution of the sample *** natural and adversarial examples are pushed to the same distribution centroid to improve the accuracy and robustness of the *** proposed method generates adversarial examples to close the distribution gap between the natural and adversarial examples through an attack algorithm explicitly designed for adversarial *** algorithm gradually increases the accuracy and robustness of the model by scaling ***,the proposed method outputs the predicted labels and the distance between the sample and the distribution *** distribution characteristics of the samples can be utilized to detect adversarial cases that can potentially evade the model *** effectiveness of the proposed method is demonstrated through comprehensive experiments.

关键词： Adversarial training feature space learnable distribution distribution centroid

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