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6th International Conference on Recent Trends in Advance Computing, ICRTAC 2023

作者： Ignisha Rajathi, G. Prakalya, B.S. Nitin Sailesh, V. Sanchana, M. Anbu Gandhi, P. Sri Krishna College of Engineering and Technology Department of Computer Science and Business System Coimbatore India

ISBN: (纸本)9798350394702

With the rapidly increasing technology and globalization, the internet has become an inevitable part of one's day-to-day life. The use of a sophisticated recommendation system has revolutionized the way consumers interact with online shopping platforms. To keep in pace with the emerging technology, every field needs to be digitalized and made up to date. In this context, the commercial shops and dealers too need to upgrade their traditional shopping methods. The old conventional methods don't always serve the new generation. The transition to online mode of shopping has made it mandatory for retailers and producers to customize according to the customer's requirement and providing various options than what was possible before. The focus in this system is to increase customer engagement, enhance the customer shopping experience, and boost sales by suggesting relevant products based on a user's browsing and purchase history, these products that are most likely to interest and satisfy individual customers. This paper reviews recent developments in recommendation systems in the domain of ecommerce. © 2023 IEEE.

关键词： Collaborative filtering

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Autonomous Vehicle Lane Following Network based on Multimodal Sensor Fusion and LiDAR Reconstruction in Extreme Lighting and Snowing Environments 4

Autonomous Vehicle Lane Following Network based on Multimoda...

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

作者： Padmapriya, J. Meera, V. Murugavalli, S. Karthikeyan, L. Panimalar Engineering College Department of Computer Science and Engineering Chennai India Panimalar Engineering College Department of Computer Science and Engineering Chennai City Campus Chennai India Panimalar Engineering College Department of Mechanical Engineering Chennai India

ISBN: (数字)9798350387063

ISBN: (纸本)9798350387063

The self-driving car industry is gaining attention for its role in motion planning technology. Deep learning approaches have been implemented to plan autonomous vehicles' motion, but their effectiveness depends on the data used in training. Despite advancements, fully autonomous vehicles still face limitations, such as lighting-related issues affecting camera image accuracy, and LiDARs are negatively impacted by challenging weather circumstances like snow in varied snowfall conditions, thus becoming imperative to precisely control the motion of the Autonomous Vehicle. To address this, an architecture based on deep-learning networks is proposed for lane-following on roads, consisting of LiDAR De-snowing, Multi-modal Sensor Fusion, VGG16, and gated recurrent units (GRUs). The Point Reconstruction Network (PR-Net) rebuilds points from neighbors, while the Reconstruction Difficulty Network forecasts reconstruction difficulty. Radar measurements and de-snowed LiDAR point clouds are projected onto the front-view image plane, fed into VGG16 and GRU output layers, and processed into two fully connected layers for steering and speed parameters estimation. © 2024 IEEE.

关键词： Snow

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Thermal intelligence: exploring AI’s role in optimizing thermal systems – a review

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Interactions 2024年第1期245卷 1-19页

作者： Devasenan, Madhesh Madhavan, Saritha Department of Mechanical Engineering AMET University Tamil Nadu Chennai603112 India Department of Computer Science and Engineering Sri Sivasubramaniya Nadar College of Engineering Tamil Nadu Kalavakkam Chennai603110 India

Artificial Intelligence (AI) is profoundly transforming multiple industries by enhancing efficiency, decision-making, and problem-solving capabilities. This impact is particularly notable in sectors such as thermal engineering, industrial processing, and solar thermal systems. In thermal engineering, AI has addressed challenges in modeling, prediction, control, and optimization, leading to improvements in energy efficiency, system reliability, and environmental sustainability. Innovations in AI-driven models, such as gradient-boosted regression trees and deep reinforcement learning, have advanced the design and management of thermal systems, including energy storage devices, power plants, and HVAC systems. AI is also revolutionizing industrial processing and solar thermal systems. In industrial settings, AI applications such as quality control, process optimization, and predictive maintenance are enhancing operational efficiency and supporting the transition towards Industry 5.0. Despite these advancements, challenges remain in aligning AI solutions with real-world industrial requirements. Similarly, in solar thermal systems, AI is optimizing performance through advanced tracking systems, predictive maintenance, and energy storage strategies. The integration of AI with technologies like the Internet of Things (IoT) and advanced materials is proving effective in boosting system efficiency. Overall, AI is providing innovative solutions that improve efficiency, reliability, and sustainability across various applications. However, ongoing research is essential to address limitations in AI models, enhance their generalizability, and integrate emerging technologies. Continued development in AI methodologies will be crucial for optimizing energy efficiency, system performance, and environmental impact in these sectors. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Predictive maintenance

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A Bioinspired Method for Optimal Task Scheduling in Fog-Cloud Environment

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computer Modeling in engineering & sciences 2025年第3期142卷 2691-2724页

作者： Ferzat Anka Ghanshyam G.Tejani Sunil Kumar Sharma Mohammed Baljon Data Science Application and Research Center(VEBIM) Fatih Sultan Mehmet Vakif UniversityIstanbul34445Turkiye Department of Industrial Engineering and Management Yuan Ze UniversityTaoyuan320315Taiwan Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Department of Information System College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia

Due to the intense data flow in expanding Internet of Things(IoT)applications,a heavy processing cost and workload on the fog-cloud side become *** of the most critical challenges is optimal task *** this is an NP-hard problem type,a metaheuristic approach can be a good *** study introduces a novel enhancement to the Artificial Rabbits Optimization(ARO)algorithm by integrating Chaotic maps and Levy flight strategies(CLARO).This dual approach addresses the limitations of standard ARO in terms of population diversity and convergence *** is designed for task scheduling in fog-cloud environments,optimizing energy consumption,makespan,and execution time simultaneously three critical parameters often treated individually in prior *** conventional single-objective methods,the proposed approach incorporates a multi-objective fitness function that dynamically adjusts the weight of each parameter,resulting in better resource allocation and load *** analysis,a real-world dataset,the Open-source Google Cloud Jobs Dataset(GoCJ_Dataset),is used for performance measurement,and analyses are performed on three considered *** are applied with well-known algorithms:GWO,SCSO,PSO,WOA,and ARO to indicate the reliability of the proposed *** this regard,performance evaluation is performed by assigning these tasks to Virtual Machines(VMs)in the resource *** are performed on 90 base cases and 30 scenarios for each evaluation *** results indicated that the proposed algorithm achieved the best makespan performance in 80% of cases,ranked first in execution time in 61%of cases,and performed best in the final parameter in 69% of *** addition,according to the obtained results based on the defined fitness function,the proposed method(CLARO)is 2.52%better than ARO,3.95%better than SCSO,5.06%better than GWO,8.15%better than PSO,and 9.41%better than WOA.

关键词： Improved ARO fog computing task scheduling GoCJ_Dataset chaotic map levy flight

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CPL-SLAM: Centralized Collaborative Multi-Robot Visual-Inertial SLAM Using Point-and-Line Features

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IEEE Internet of Things Journal 2025年第12期12卷 21866-21875页

作者： Liu, Xin Wen, Shuhuan Liu, Huaping Richard Yu, F. Yanshan University Engineering Research Center The Ministry of Education for Intelligent Control System and Intelligent Equipment Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Department of Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Tsinghua University Department of Computer Science and Technology Beijing100084 China Shenzhen University College of Computer Science and Software Engineering China Carleton University Canada

Traditional visual-inertial SLAM (Simultaneous Localization and Mapping) systems predominantly rely on feature point matching from a single robot to realize the robot pose estimation and environment map construction. However, in complex scenarios, these traditional systems struggle with issues such as tracking failures due to illumination changes, rapid movements, and low-texture environments, and they perform poorly in terms of mapping efficiency and global consistency. To address these challenges, we propose a centralized collaborative SLAM system that employs both point and line features for tracking in the robot and map fusion in the cloud. The proposed system leverages the fusion of point and line features across all instances in the process, which allows our method to achieve higher localization accuracy in structured, low-texture scenes. With the aid of classifying gravity-aligned vertical lines and spatial parallel lines, the proposed system can deliver faster and more accurate odometry in complex scenes. Furthermore, we developed intra-robot and inter-robot loop closure detection methods based on point and line features, generating a globally consistent sparse point cloud and structured scene map in the cloud. Our method is able to build richer maps while improving accuracy compared to existing methods. Experimental results on public datasets and in real-world environments show that, compared to existing advanced methods, our approach demonstrates better performance. © 2014 IEEE.

关键词： SLAM robotics

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Blockchain architecture in upcoming digital world 4th

Blockchain architecture in upcoming digital world

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4th Annual International Conference on Data science, Machine Learning and Blockchain Technology, AICDMB 2023

作者： Promod Kumar, B.M. Manoj Gowda, K.S. Heemashree, S.S. Siddesh Kumar, N.M. Tejas, S. Haran, Pranadhi Vikas, C.M. Department of Computer Science and Engineering PES College of Engineering Mandya India Department of Information Science and Engineering PES College of Engineering Mandya India Department of Mechanical Engineering PES College of Engineering Mandya India

ISBN: (纸本)9781032426853

Blockchain architecture is a multi-layered system with various components that work together to ensure stability, security, and efficiency. The bottom layer, the Data Layer, holds transactions and data, while the Consensus Layer ensures accuracy and validates transactions. The Network Layer manages communication and data transmission, and the Application Layer provides user access. The Contract Layer executes smart contracts and defines rules, and the Security Layer protects the system from attacks. Blockchain architecture is widely used in various industries including finance, healthcare, supply chain, and voting systems, providing secure, transparent, and immutable data. The combination of blockchain and AI technology results in secure, decentralized and automated execution of agreements, transforming industries such as finance, supply chain and healthcare. © 2024 The Author(s).

关键词： Blockchain

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Cold spray processing of AA2024/Al2O3 coating on magnesium AZ31B alloy: Process parameters optimization, microstructure and adhesive strength performance of coating

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International Journal of Lightweight Materials and Manufacture 2024年第5期7卷 721-737页

作者： Mohankumar, Ashokkumar Thirumalaikumarasamy, Duraisamy Sonar, Tushar Ivanov, Mikhail Vignesh, Packkirisamy Pavendhan, Rajangam Mariappan, Mathanbabu Xu, Jinyang Centre for Sustainable Materials and Surface Metamorphosis Chennai Institute of Technology Tamil Nadu Chennai600069 India Chelyabinsk454080 Russia Department of Mechanical Engineering ARM College of Engineering &Technology Tamil Nadu Chennai603209 India Department of Mechanical Engineering Government College of Engineering Tamil Nadu Bargur635104 India State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China

The automotive and aerospace sectors are progressively employing the magnesium (Mg) alloy of the grade AZ31B because of its excellent castability, low density, and high ratio of strength to weight. Nevertheless, the limited ability of AZ31B alloy to withstand corrosion limits their use in several fields of technology. In order to solve this problem, the AZ31B alloy is coated utilizing an AA2024/Al2O3 metal matrix composite (MMC) coating that is applied by the cold spray coating (CS) method. The primary goal of this work is the parametric optimization of CS process for maximizing adhesive strength of MMC-coated Mg-alloy substrate. Response surface methodology (RSM) is implemented to find the optimum CS parameters, including feed rate of powder – FRP (g/min), standoff distance of gun – SDG (mm) and processing temperature – TEMP (°C). The regression-based parametric adhesion strength prediction (ASP) model was formulated using the RSM and statistically validated using analysis of variance (ANOVA). Employing 3D surface of responses, the influence of CS parameters on the adhesion strength of an MMC-coating was assessed. The findings revealed that when the MMC-coating was cold sprayed on the Mg-alloy using FRP of 22 g/min, SDG of 12 mm, and TEMP of 520 °C, the maximum adhesion strength of MMC-coating was 70 MPa (actual). Given less than 2% error at 95% confidence, the parametric ASP model correctly predicted the adhesion strength of the MMC-coating. The ANOVA findings showed that FRP (g/min) had significant effect on adhesive strength of MMC-coating followed by SDG (mm) and TEMP (°C). The MMC-coating applied using the RSM optimized CS parameters showed 70.73% superior adhesive strength owing to the lower porosity formation of 2 vol% which offers greater interfacial area. The ASP equation was formulated using the "best fitting line" approach and validated using ANOVA for predicting the adhesive strength (MPa) from the porosity formation (vol%) in the MMC-coating. © 2024 Th

关键词： Magnesium alloys

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Oxidation-induced superelasticity in metallic glass nanotubes

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Nature Materials 2024年第1期23卷 52-57页

作者： Li, Fucheng Zhang, Zhibo Liu, Huanrong Zhu, Wenqing Wang, Tianyu Park, Minhyuk Zhang, Jingyang Bönninghoff, Niklas Feng, Xiaobin Zhang, Hongti Luan, Junhua Wang, Jianguo Liu, Xiaodi Chang, Tinghao Chu, Jinn P. Lu, Yang Liu, Yanhui Guan, Pengfei Yang, Yong Department of Mechanical Engineering College of Engineering City University of Hong Kong Kowloon Tong Hong Kong Institute of Physics Chinese Academy of Sciences Beijing China Songshan Lake Materials Laboratory Dongguan China Beijing Computational Science Research Center Beijing China Department of Material Science and Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Materials Science and Engineering College of Engineering City University of Hong Kong Kowloon Tong Hong Kong College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Department of Mechanical Engineering The University of Hong Kong Pok Fu Lam Hong Kong Department of System Engineering College of Engineering City University of Hong Kong Kowloon Tong Hong Kong

Although metallic nanostructures have been attracting tremendous research interest in nanoscience and nanotechnologies, it is known that environmental attacks, such as surface oxidation, can easily initiate cracking on the surface of metals, thus deteriorating their overall functional/structural properties 1–3. In sharp contrast, here we report that severely oxidized metallic glass nanotubes can attain an ultrahigh recoverable elastic strain of up to ~14% at room temperature, which outperform bulk metallic glasses, metallic glass nanowires and many other superelastic metals hitherto reported. Through in situ experiments and atomistic simulations, we reveal that the physical mechanisms underpinning the observed superelasticity can be attributed to the formation of a percolating oxide network in metallic glass nanotubes, which not only restricts atomic-scale plastic events during loading but also leads to the recovery of elastic rigidity on unloading. Our discovery implies that oxidation in low-dimensional metallic glasses can result in unique properties for applications in nanodevices. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

关键词： Metallic glass

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Performance analysis and material distribution optimization for sound barriers using a semianalytical meshless method

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International Journal of mechanical system Dynamics 2023年第4期3卷 331-344页

作者： Hanqing Liu Fajie Wang Chuanzeng Zhang National Engineering Research Center for Intelligent Electrical Vehicle Power System College of Mechanical and Electrical EngineeringQingdao UniversityQingdaoChina Department of Civil Engineering University of SiegenSiegenGermany

With the increase in car ownership,traffic noise pollution has increased considerably and is one of the most severe types of noise pollution that affects living *** reduction by sound barriers is a common protective measure used in this country and *** acoustic performance of a sound barrier is highly dependent on its shape and *** this paper,a semianalytical meshless Burton-Miller‐type singular boundary method is proposed to analyze the acoustic performance of various shapes of sound barriers,and the distribution of sound‐absorbing materials on the surface of sound barriers is optimized by combining a solid isotropic material with a penalization *** acoustic effect of the sound‐absorbing material is simplified as the acoustical impedance boundary *** objective of optimization is to minimize the sound pressure in a given reference *** volume of the sound‐absorbing material is used as a *** density of the nodes covered with the sound‐absorbing material is used as the design *** method of moving asymptotes was used to update the design *** model completely avoids the mesh discretization process in the finite element method and requires only boundary *** addition,the approach also does not require the singular integral calculation in the boundary element *** method is illustrated and validated using numerical examples to demonstrate its accuracy and efficiency.

关键词： sound barrier acoustic analysis material distribution optimization semianalytical meshless method

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Snap-through behaviors and nonlinear vibrations of a bistable composite laminated cantilever shell:an experimental and numerical study

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 779-794页

作者： Lele REN Wei ZHANG Ting DONG Yufei ZHANG State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240China Department of Mechanics Guangxi UniversityNanning 530004China Beijing Key Laboratory of Nonlinear Vibrations and Strength of Mechanical Structures College of Mechanical EngineeringBeijing University of TechnologyBeijing 100124China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

The snap-through behaviors and nonlinear vibrations are investigated for a bistable composite laminated cantilever shell subjected to transversal foundation excitation based on experimental and theoretical *** improved experimental specimen is designed in order to satisfy the cantilever support boundary condition,which is composed of an asymmetric region and a symmetric *** symmetric region of the experimental specimen is entirely clamped,which is rigidly connected to an electromagnetic shaker,while the asymmetric region remains free of *** motion paths are realized for the bistable cantilever shell by changing the input signal levels of the electromagnetic shaker,and the displacement responses of the shell are collected by the laser displacement *** numerical simulation is conducted based on the established theoretical model of the bistable composite laminated cantilever shell,and an off-axis three-dimensional dynamic snap-through domain is *** numerical solutions are in good agreement with the experimental *** nonlinear stiffness characteristics,dynamic snap-through domain,and chaos and bifurcation behaviors of the shell are quantitatively *** to the asymmetry of the boundary condition and the shell,the upper stable-state of the shell exhibits an obvious soft spring stiffness characteristic,and the lower stable-state shows a linear stiffness characteristic of the shell.

关键词： bistable composite laminated cantilever shell snap-through behavior nonlinear vibration nonlinear stiffness characteristic chaos and bifurcation

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