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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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Unlocking new possibilities in ionic thermoelectric materials:a machine learning perspective

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国家科学评论（英文版） 2025年第1期12卷 188-199页

作者： Yidan Wu Dongxing Song Meng An Cheng Chi Chunyu Zhao Bing Yao Weigang Ma Xing Zhang Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Engineering MechanicsTsinghua UniversityBeijing 100084China Key Laboratory of Process Heat Transfer and Energy Saving of Henan Province School of Mechanics and Safety EngineeringZhengzhou UniversityZhengzhou 450001China College of Mechanical and Electrical Engineering Shaanxi University of Science and TechnologyXi'an 710021China Key Laboratory of Power Station Energy Transfer Conversion and System of Ministry of Education School of Energy Power and Mechanical EngineeringNorth China Electric Power UniversityBeijing 102206China Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Engineering MechanicsTsinghua UniversityBeijing 100084China School of Materials and Chemical Engineering Xuzhou University of TechnologyXuzhou 221018China

The high thermopower of ionic thermoelectric(i-TE)materials holds promise for miniaturized waste-heat recovery devices and thermal ***,progress is hampered by laborious trial-and-error experimentations,which lack theoretical ***,by introducing the simplified molecular-input line-entry system,we have addressed the challenge posed by the inconsistency of i-TE material types,and present a machine learning model that evaluates the Seebeck coefficient with an R2 of 0.98 on the test *** this tool,we experimentally identify a waterborne polyurethane/potassium iodide ionogel with a Seebeck coefficient of 41.39 mV/***,interpretable analysis reveals that the number of rotatable bonds and the octanol-water partition coefficient of ions negatively affect Seebeck coefficients,which is corroborated by molecular dynamics *** machine learning-assisted framework represents a pioneering effort in the i-TE field,offering significant promise for accelerating the discovery and development of high-performance i-TE materials.

关键词： thermoelectric conversion ionic thermoelectric materials machine learning interpretable analysis

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A Simple Method to Measure the Contact Angle of Metal Droplets on Graphite

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Nanomanufacturing and Metrology 2023年第4期6卷 35-45页

作者： Bozhao Wu Yongping Kang Cai Lu Langquan Shui Wengen Ouyang Qi Peng Qiankun He Ze Liu Department of Engineering Mechanics School of Civil EngineeringWuhan UniversityWuhan 430072HubeiChina School of Civil Engineering Architecture and Environment Hubei University of TechnologyWuhan 430068HubeiChina System Design Institute of Hubei Areospace Technology Academy Wuhan 430040China State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan UniversityWuhan 430072China

The determination of solid–liquid interfacial tension plays an important role in science and ***,we propose a simple method to directly measure the contact angle between metal droplets and a graphite substrate for the determination of metal–graphite interfacial *** proposed method involves the synthesis of micro-and nanosized metal droplets on graphite by arc *** to its small volume,the rapid cooling of the prepared metal droplets on the graphite substrate leads to the freezing of equilibrium contact confguration after *** observe that the measured contact angle between micro-and nanosized Au(or Ag)particles and the graphite substrate is almost size independent,even though the size of the particles synthesized herein is 1–3 orders of magnitude smaller than that studied in previous *** addition,the interfacial tensions of Au and Ag on the step edges(edge plane)of graphite are found to be larger than that on the(0001)plane(basal plane).The proposed method provides a simple approach to determine the solid–liquid interfacial tension and may be efective in the study of interface related science and technology.

关键词： Metal droplets Graphite/graphenes Contact angle Interfacial tension

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Performance Analysis of the Machine Learning Algorithms for the Early Detection of Breast Carcinoma 2

Performance Analysis of the Machine Learning Algorithms for ...

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2nd IEEE International Conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Vanitha, K. Karpagavalli, S.M. Mahesh, T.R. Ali, A. Althaf Sridhar, T. Anitha, K. Faculty of Engineering Department of Computer Science and Engineering Coimbatore India Al Ameen Engineering College Department of Computer Science and Engg Tamilnadu Erode India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India Madanapalle Institute of Technology & Science Department of Computer Applications Andhra Pradesh India Alliance University Alliance College of Engineering and Design Bangalore India Csi College of Engineering Department of Information Technology Tamilnadu Ooty India

ISBN: (纸本)9798350360523

Breast Carcinoma, generally known as breast cancer, primarily affects women, though men can develop it as well. Because of the existence of breast tissue and exposure to female hormones, notably oestrogen, women are at a higher risk It's critical to diagnose breast tumors early. Several techniques based on machine learning (ML were used in this study to classify breast cancer using a dataset that was made available to the public. F-score, recall, precision, preciseness, and other performance metrics were used to evaluate these ML algorithms. Previous research and experimental findings indicate that Random Forest achieved the highest accuracy, with a remarkable accuracy rate of 99.12%. © 2024 IEEE.

关键词： Hormones

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Customer Segmentation Using Clustering Analysis

Customer Segmentation Using Clustering Analysis

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2024 IEEE International Conference on Information technology, Electronics and Intelligent Communication systems, ICITEICS 2024

作者： Jiet, Moses Makuei Kamble, Aahash Puri, Chetan Yesankar, Prajyot Verma, Prateek Rewatkar, Rajendra Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Data Science Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Biomedical Engineering Maharashtra Wardha442001 India

ISBN: (纸本)9798350382693

This research focuses on the crucial role of the clustering technique in data mining, specifically in market forecasting and planning. The study presents a comprehensive report on utilizing the k-means clustering technique and data visualization tools to develop a real- time system for a supermarket, predicting sales across various annual cycles. An open-source dataset of a mall with n = 200 customers divided into k = 3 groups, demonstrated high accuracy in predicting day-to-day sales statistics when compared with actual results. The research highlights the effectiveness of the clustering technique in real-time sales prediction for supermarkets. © 2024 IEEE.

关键词： Sales

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Network-Based Rail Running Band Anomaly Recognition via Recurrent Attention Graphs

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IEEE Transactions on Automation science and engineering 2025年 22卷 15381-15395页

作者： Ni, Xuefeng Fieguth, Paul W. Ma, Ziji Shi, Bo Liu, Hongli Hunan University College of Electrical and Information Engineering Changsha410012 China University of Waterloo Department of Systems Design Engineering WaterlooONN2L 3G1 Canada The Hong Kong University of Science and Technology Department of Computer Science and Engineering Sai Kung Hong Kong

Anomaly detection for rail running bands, the pattern of wheel-rail contact area, is crucial to analyze composite rail irregularities. This paper presents an all-weather vision-based solution for running-band inspection. However, two major algorithmic challenges restrict inspection effectiveness: 1) the identification of high-quality features for diversified and imbalanced data subject to noise and outliers, and 2) inferring implicit anomaly co-occurrence patterns. We regard overall running-band anomaly detection as a multi-label classification problem and develop a novel deep multi-anomaly recognition network via recurrent attention graphs (RAGRN). © 2004-2012 IEEE.

关键词： Network theory (graphs)

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Deep Convolutional Multi-Relational Graph Attention Network for Autonomous Drone Navigation in Urban Wind Zones

Deep Convolutional Multi-Relational Graph Attention Network ...

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2025 International Conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Pabitha, C. Joshua, K. Paul Pradeep, S. Sophia, S. Sharma, R. Rajesh Prabhu, D. Karthik Srm Valliammai Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Scad College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Tirunelveli India MAlla Reddy Engineering College for Women Department of Computer Science and Engineering Telangana Secunderabad India Karunya Institute of Technology and Sciences Department of computer Science and Engineering Tamil Nadu Coimbatore India Alliance University Department of Computer Technology Alliance College of Engineering and Design Bangalore India Ramco Institute of Technology Department of Electrical and Electronics Engineering Tamil Nadu Rajapalaiyam India

ISBN: (纸本)9798331509828

Drones are essential for civil engineering operations like logistics and data collecting. Current autonomous drone studies mainly concerns itself with safe path planning in static scenarios;however one of the major challenges of over urban environment is often dynamic factors such as wind, building layouts, and signal coverage that can significantly impact direction stability. For autonomous navigation across dynamic wind zones, this study proposed a new Shape-aware Mesh Dual Lightweight Deep Convolutional Multi-Relational Graph Attention Network with Growth Optimizer (SAMDLDCMRGANet-GO) that leverages local data from RGB cameras and GPS. The method incorporates a Dual Aggregation Transformer for feature extraction, Shape-aware Mesh Normal Filtering for preprocessing, and the LDCMRGAN et for efficient path planning. The proposed approach demonstrates its efficacy in navigating complicated surroundings while retaining high precision in obstacle avoidance and target acquisition, achieving an impressive 99.14% recall, 99.15% accuracy, an outstanding EVA of 0.99, and a low RMSE of 0.41. © 2025 IEEE.

关键词： Mesh generation

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Paired restraint domination in extended supergrid graphs

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Journal of Supercomputing 2024年第9期80卷 13217-13249页

作者： Hung, Ruo-Wei Hung, Ling-Ju Department of Computer Science and Information Engineering Chaoyang University of Technology Wufeng District Taichung413310 Taiwan Department of Creative Technologies and Product Design National Taipei University of Business Pingzhen District Taoyuan324 Taiwan

Consider a graph G with vertex set V(G) and edge set E(G). A subset D of V(G) is said to be a dominating set of G if every vertex not in D is adjacent to at least one vertex in D. If, in addition, every vertex not in a dominating set R of G is adjacent to at least one vertex in V(G)-R, then R is called a restrained dominating set of G. A paired restraint dominating set S of a graph G is a restrained dominating set of G satisfying that the induced subgraph by S contains a perfect matching. The problems of computing the dominating set, restrained dominating set, and paired restraint dominating set with minimum cardinality are referred to as the domination, restrained domination, and paired restraint domination problems, respectively. The paired restraint domination problem and its applications are first proposed here. Our focus is on examining the complexity of the proposed problem on extended supergrid graphs and their subclasses, which include grid, diagonal supergrid, and (original) supergrid graphs. The domination problem is known to be NP-complete on grid graphs and, therefore, also on extended supergrid graphs. Our previous research demonstrated that the domination and restrained domination problems on diagonal and original supergrid graphs are NP-complete. However, the complexity of the paired restraint domination problem on grid, diagonal supergrid, and original supergrid graphs remains unknown. The NP-completeness of the paired restraint domination problem on diagonal supergrid graphs is demonstrated in this paper, and this finding is also applicable to the original supergrid graphs and planar graphs with maximum degree 4. We then examine a subclass of diagonal and original supergrid graphs known as rectangular supergrid graphs. These graphs are distinguished by a rectangular shape consisting of m rows and n columns of vertices. Specifically, we address the paired restraint domination problem on Rm×n and develop a linear time algorithm for 3⩾m⩾1 and n⩾m. Then

关键词： Graphic methods

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Automated CKD Detection via Image Processing Employing Delta-E Metric and CNN

Automated CKD Detection via Image Processing Employing Delta...

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2024 International Conference on system, Computation, Automation and Networking, ICSCAN 2024

作者： Espin Shalo, S.P. Jeeshan, R.J. Gunasekar, S. Pius Agbulu, G. Venkat Ramana, N. Rajalakshmi Engineering College Department of Computer Science and Engineering Tamilnadu Chennai602105 India Rajalakshmi Engineering College Department of Computer Science and Design Tamilnadu Chennai602105 India Chinhoyi University of Technology Department of Mechatronics Engineering Zimbabwe Indian Institute of Technology Department of Electrical Engineering Tamilnadu Chennai India

ISBN: (纸本)9798331510022

Chronic Kidney Disease (CKD) is a global health concern that often progresses silently until advanced stages, making early detection critical. This paper presents a point-of-care system that automates the color comparison between a test strip and a reference strip to detect biomarkers like albumin associated with kidney dysfunction. The system leverages mobile-captured images, applying image processing techniques such as segmentation and color extraction, and compares the test strip's top color with reference colors on the parent strip using the Delta-E metric in the LAB color space. The closest match quantifies the biomarker concentration, providing a reliable diagnostic measure. To enhance diagnostic precision, this research incorporates Convolutional Neural Networks (CNNs) to refine image preprocessing and anomaly detection. The CNN model complements existing methods by mitigating environmental influences like lighting variability and improving feature extraction accuracy. This hybrid approach ensures consistency while adapting to diverse datasets and image conditions. The result is a cost-effective, fast, and accessible diagnostic tool that reduces manual errors and supports early CKD detection in resource-limited settings. Future work will focus on expanding the application of this system to detect other diseases and further optimize the integration of CNNs for enhanced scalability and robustness. © 2024 IEEE.

关键词： Convolutional neural networks

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Operando chemo-mechanical evolution in LiNi0.8Co0.1Mn0.1O2 cathodes

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National science Review 2024年第9期11卷 253-263页

作者： Yi Zhang Shuaipeng Hao Fei Pei Xiangpeng Xiao Chang Lu Xing Lin Zhe Li Haijin Ji Yue Shen Lixia Yuan Zhen Li Yunhui Huang State Key Laboratory of Material Processing and Die & Mould Technology School of Materials Science and EngineeringHuazhong University of Science and Technology School of Optical and Electronic Information National Engineering Laboratory for Next Generation Internet Access SystemWuhan National Laboratory for OptoelectronicsHuazhong University of Science and Technology Gatan Inc.& EDAX LLC. AMETEK Commercial Enterprise (Shanghai)Co. Ltd.Pilot Free Trade Zone Department of Physics The Chinese University of Hong Kong

Ni-rich LiNixCoyMnzO2（NCMxyz,x+y+z=1,x≥0.8） layered oxide materials are considered the main cathode materials for high-energy-density Li-ion ***,the endless cracking of polycrystalline NCM materials caused by stress accelerates the loss of active materials and electrolyte decomposition,limiting the cycle ***,understanding the chemo-mechanical evolution during（de）lithiation of NCM materials is crucial to performance *** this work,an optical fiber with με resolution is designed to in operando detect the stress evolution of a polycrystalline LiNi0.8Co0.1Mn0.1O2（P-NCM811） cathode during *** integrating the sensor inside the cathode,the stress variation of P-NCM811 is completely transferred to the optical *** find that the anisotropy of primary particles leads to the appearance of structural stress,inducing the formation of microcracks in polycrystalline particles,which is the main reason for capacity *** isotropy of primary particles reduces the structural stress of polycrystalline particles,eliminating the generation of ***,the P-NCM811 with an ordered arrangement structure delivered high electrochemical performance with capacity retention of 82% over 500 *** work provides a brand-new perspective with regard to understanding the operando chemo-mechanical evolution of NCM materials during battery operation,and guides the design of electrode materials for rechargeable batteries.

关键词： Ni-rich layered oxide cathode in operando stress monitoring polycrystalline chemo-mechanical evolution

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