Lightweight encryption solution for train communication network by TANG Jun, GE Qianghua, ZOU Zhirong, CHEN Bo, TANG Pin

“…To mitigate these risks, data encryption has emerged as an important means, albeit with additional demand on CPU computing resources. …”
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Spatial association analysis on epidemic of SARS in Beijing, 2003 by WU Ji-lei, WANG Jin-feng, MENG Bin, LIU Xu-hua

“…Exploratory spatial data analysis (ESDA), newly emerged technique with application of information technology, especially with geographical information system (GIS), can be used in studying objects with spatial reference to effectively perceive and interpret the relationship among them. …”
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The Application of Controlled-Source Audio-Frequency Magnetotellurics Numerical Simulations in the Exploration and Electrical Structure Interpretation of the Jinding Lead–Zinc Depo... by Lincheng Zhang, Jingtian Tang, Jiayong Lin, Xiao Xiao

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Robust fault detection in electrochemical energy storage systems under label noise: applications to lithium-ion batteries and transformer windings by Tao He, Wei Liu, Xin Wu, Yu Wei

“…The approach is computationally efficient, classifier-agnostic, and easily applicable to existing fault diagnosis pipelines. We evaluate the proposed method on two datasets: simulated lithium-ion battery voltage data under various fault scenarios, and transformer winding oscillation wave data under multiple winding fault conditions. …”
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A successive variational mode extraction method based on spectrum trend and its application in non‐contact vital sign detection by Qianxi Zhao, Zhichao Sheng, Guoqiang He, Hongwen Yu, Yong Fang

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ANALISA METODE CLASSIFICATION-DECISSION TREE DAN ALGORITMA C.45 UNTUK MEMPREDIKSI PENYAKIT DIABETES DENGAN MENGGUNAKAN APLIKASI RAPID MINER by Febie Elfaladonna, Ayu Rahmadani

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Comprehensive analysis of supervised learning methods for electrical source imaging by Sarah Reynaud, Adrien Merlini, Douraied Ben Salem, François Rousseau

“…This work explores the application of supervised learning methods for spatio-temporal ESI, where the relationship between measurements and sources is learned directly from the data. …”
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A domain generalization network for imbalanced machinery fault diagnosis by Yu Guo, Guangshuo Ju, Jundong Zhang

“…Domain Generalization (DG) models provide an advantage over traditional approaches by learning class-discriminative and domain-invariant feature representations, allowing them to generalize to unseen target data. However, the scarcity of fault samples relative to healthy ones limits their application in real-world industrial scenarios. …”
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Source Apportionment of Fine Particulate Matter in Wuhan: Application of Rolling Positive Matrix Factorization Under Different Seasons and Episodic Events by Ziye Guo, Qiongqiong Wang, Nan Chen, Bo Zhu, Huang Zheng, Shaofei Kong, Mingjie Xie, Huan Yu

“…Rolling PMF strategy with source profile constraints has been demonstrated as an effective tool for source apportionment of the non-refractory submicron aerosol, while its application in PM chemical speciation data under different pollution conditions was less studied. …”
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Life cycle assessment of electric kick scooters: consolidating environmental impact quantification and concluding climate-friendly use options by Corinna Baumgartner, Eckard Helmers

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Radar versus optical: The impact of cloud cover when mapping seasonal surface water for health applications in monsoon-affected India. by Gowri Uday, Bethan V Purse, Douglas I Kelley, Abi Vanak, Abhishek Samrat, Anusha Chaudhary, Mujeeb Rahman, France F Gerard

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Sentiment Analysis of User Reviews of the KitaLulus Application on Google Play Store using the Support Vector Machine (SVM) Algorithm by Ahmad Syaifudin Agil Rafsanjani, Diana Laily Fithri, Supriyono Supriyono

“…This study aims to analyze user sentiment toward the KitaLulus application using the Support Vector Machine (SVM) algorithm, combined with the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance in sentiment data. …”
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A Robust Hybrid CNN–LSTM Model for Predicting Student Academic Performance by Kuburat Oyeranti Adefemi, Murimo Bethel Mutanga

“…The rapid increase in educational data from diverse sources such as learning management systems and assessment records necessitates the application of advanced analytical techniques to identify at-risk students and address persistent issues like dropout rates and academic underperformance. …”
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Community Detection Framework Using Deep Learning in Social Media Analysis by Ao Shen, Kam-Pui Chow

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Impact Monitor Framework: Development and Implementation of a Collaborative Framework for Aviation Impact Assessment by Marko Alder, Patrick Ratei, Atif Riaz, Utkarsh Gupta, Thierry Lefebvre, Prajwal Shiva Prakasha

“…The focus is on which technologies can be used to enable the collaborative aspect, including the use of a common data model, the secure transfer of data between domain experts in different locations, and the automated execution of impact assessment workflows. …”
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Application of Polynomial Regression Method in Non-invasive Measurement of Blood Sugar, Cholesterol, and Non-invasive Uric Acid Based on IoT by Desi Rahmadaniar, Irma Salamah, Martinus Mujur Rose

“…At the same time, a mobile application was developed using MIT App Inventor for user-friendly health data visualization. …”
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Blockchain and Digital Twins in Smart Industry 4.0: The Use Case of Supply Chain-A Review of Integration Techniques and Applications by Christos Roumeliotis, Minas Dasygenis, Vasilis Lazaridis, Michael Dossis

“…However, traditional DT development relies on centralized systems, which are vulnerable to data tampering and security breaches, especially in the management of transaction logs and historical data. …”
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Application of the One Health Surveillance (OHS) Matrix to Evaluate the Disease Surveillance Systems in Gujarat, India: A Policy Content Analysis by Sandul Yasobant, Ravina Tadvi, Walter Bruchhausen, Deepak B. Saxena

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APPLICATION OF K-MEANS AND FUZZY C-MEANS ALGORITHMS TO DETERMINE FLOOD VULNERABILITY CLUSTERS (CASE STUDY: KUTAI KARTANEGARA REGENCY) by Desi Nurjanah, Indira Anggriani, Primadina Hasanah

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Reservoir parameter prediction technology based on deep learning and its application in the Panyu 4 Sag, Pearl river mouth Bain by Yingwei Li, Yanhui Zhu, Zhenshen Li, Xiaozhao Zhang, Guofu Cai

“…Finally, the trained deep learning model is applied to the elastic parameter bodies to obtain predictions of effective porosity and VCL, thereby achieving a quantitative characterization of high-quality deep sandstone reservoirs. The application of this method in the deltaic sediments of the Panyu 4 Sag in the Pearl River Mouth Basin shows that the deep learning-based predictions of facies distribution and porosity are consistent with well data and geological understanding. …”
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