Generating Synthetic Datasets with Deep Learning Models for Human Physical Fatigue Analysis by Arsalan Lambay, Ying Liu, Phillip Morgan, Ze Ji

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Data-driven price trends prediction of Ethereum: A hybrid machine learning and signal processing approach by Ebenezer Fiifi Emire Atta Mills, Yuexin Liao, Zihui Deng

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Generate medical synthetic data based on generative adversarial network by Xiayu XIANG, Jiahui WANG, Zirui WANG, Shaoming DUAN, Hezhong PAN, Rongfei ZHUANG, Peiyi HAN, Chuanyi LIU

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Geospatial dataset on deforestation and urban sprawl in Dhaka, Bangladesh: A resource for environmental analysisMendeley Data by Md. Fahad Khan, Md. Rakibul Islam, Shanto Kumar Basak, Ahmed Imtiaz, Abhijit Bhowmik, Dip Nandi, Mashiour Rahman, Debajyoti Karmaker

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Analysis of VAE-LSTM Performance in Detecting Anomalies in Average Daily Temperature Data in Jakarta 2000-2023 by INDRI RAMDANI, YENNI ANGRAINI, INDAHWATI INDAHWATI

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Image data-driven intelligent recognition of permafrost strength and feature visualization based analysis by Zhaoming YAO, Xun WANG, Hang WEI, Xiaolong WANG

“…The labeled sample images and actual strength data, combined with image data augmentation techniques, were used to construct the image dataset required for training the deep learning model. …”
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Comparative analysis of data transformation methods for detecting non-technical losses in electricity grids by Maria Gabriel Chuwa, Daniel Ngondya, Rukia Mwifunyi

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Quantifying Haptic Affection of Car Door Through Data-Driven Analysis of Force Profile by Mudassir Ibrahim Awan, Ahsan Raza, Waseem Hassan, Ki-Uk Kyung, Seokhee Jeon

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Plastic Injection Molding Process Analysis: Data Integration and Modeling for Improved Production Efficiency by Jose Isidro Hernández-Vega, Luis Alejandro Reynoso-Guajardo, Mario Carlos Gallardo-Morales, María Ernestina Macias-Arias, Amadeo Hernández, Nain de la Cruz, Jesús E. Soto-Soto, Carlos Hernández-Santos

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CryptoEval: Evaluating the risk of cryptographic misuses in Android apps with data‐flow analysis by Cong Sun, Xinpeng Xu, Yafei Wu, Dongrui Zeng, Gang Tan, Siqi Ma, Peicheng Wang

“…Secondly, the authors employ a misuse‐originating data‐flow analysis to connect each cryptographic misuse to a set of data‐flow sinks in an app, based on which the authors propose a quantitative data‐flow‐driven metric for assessing the overall risk of the app introduced by cryptographic misuses. …”
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Graph technologies in an intelligent system of complex analysis of data from Internet sources by I. I. Piletski, M. Р. Batura, L. Y. Shylin

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Finding White Dwarfs’ Hidden Companions Using an Unsupervised Machine Learning Technique by Xabier Pérez-Couto, Minia Manteiga, Eva Villaver

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Analysis of Microbiome for AP and CRC Discrimination by Alessio Rotelli, Ali Salman, Leandro Di Gloria, Giulia Nannini, Elena Niccolai, Alessio Luschi, Amedeo Amedei, Ernesto Iadanza

“…Microbiome data analysis is essential for understanding the role of microbial communities in human health. …”
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Explainable Siamese Neural Networks for Detection of High Fall Risk Older Adults in the Community Based on Gait Analysis by Christos Kokkotis, Kyriakos Apostolidis, Dimitrios Menychtas, Ioannis Kansizoglou, Evangeli Karampina, Maria Karageorgopoulou, Athanasios Gkrekidis, Serafeim Moustakidis, Evangelos Karakasis, Erasmia Giannakou, Maria Michalopoulou, Georgios Ch Sirakoulis, Nikolaos Aggelousis

“…To address this, the present study proposes a novel approach that transforms biomechanical time-series data, derived from gait analysis, into visual representations to facilitate the application of deep learning (DL) methods for fall risk assessment. …”
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Benchmarking Machine Learning Algorithms for Bearing Fault Classification Using Vibration Data: A Deployment-Oriented Study by Prasanta Kumar Samal, R. Srinidhi, Pramod Kumar Malik, H. J. Manjunatha, Imran M. Jamadar

“…This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in condition monitoring systems. …”
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Machine learning for prediction of Helicobacter pylori infection based on basic health examination data in adults: a retrospective study by Qiaoli Wang, Tao Liang, Yuexi Li, Peng Zhou, Xiaoqin Liu

“…ObjectiveThis study aimed to investigate the feasibility of developing machine learning models for non-invasive prediction of Helicobacter pylori (H pylori) infection using routinely collected adult health screening data, including demographic characteristics and clinical biomarkers, to establish a potential decision-support tool for clinical practice.MethodsThe data was sourced from the adult health examination records within the health management centers of the hospital. …”
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Research on the application of network security defence in database security services based on deep learning integrated with big data analytics by Feilu Hang, Linjiang Xie, Zhenhong Zhang, Wei Guo, Hanruo Li

Subjects: “…Big data analysis…”
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Learning Optimal Dynamic Treatment Regime from Observational Clinical Data through Reinforcement Learning by Seyum Abebe, Irene Poli, Roger D. Jones, Debora Slanzi

“…To overcome these challenges, decision tree-based reinforcement learning approaches have been proposed. Our study aims to evaluate the performance and feasibility of such algorithms: tree-based reinforcement learning (T-RL), DTR-Causal Tree (DTR-CT), DTR-Causal Forest (DTR-CF), stochastic tree-based reinforcement learning (SL-RL), and Q-learning with Random Forest. …”
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Retraining and evaluation of machine learning and deep learning models for seizure classification from EEG data by Juan Pablo Carvajal-Dossman¹, Laura Guio, Danilo García-Orjuela, Jennifer J. Guzmán-Porras, Kelly Garces, Andres Naranjo, Silvia Juliana Maradei-Anaya, Jorge Duitama

“…However, manual annotation of seizures in EEG data is a major time-consuming step in the analysis process of EEGs. …”
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Digital Educational History Database Structure for Solving Learning Analytics Tasks by Tatyana Zykova, Alexey Kytmanov, Tatyana Kustitskaya, Roman Esin

Subjects: “…learning analytics…”
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