Exoplanet Classification Through Vision Transformers with Temporal Image Analysis by Anupma Choudhary, Sohith Bandari, B. S. Kushvah, C. Swastik

“…Traditional methods demand substantial effort, time, and cost, highlighting the need for advanced machine learning techniques to enhance classification efficiency. …”
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Comparative analysis of convolutional neural networks and traditional machine learning models for IVF live birth prediction: a retrospective analysis of 48514 IVF cycles and an eva... by Yu Liu, Yi Wang, Kai Huang, Hao Shi, Hang Xin, Shanjun Dai, Jinhao Liu, Xinhong Yang, Jianyuan Song, Fuli Zhang, Yihong Guo

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EmoTrans attention based emotion recognition using EEG signals and facial analysis with expert validation by Ch Anwar Ul Hassan, Muhammad Ehatisham-ul-Haq, Fiza Murtaza, Aman Ullah Yasin, Syed Sajid Ullah

“…The model was validated with machine learning and deep learning classifiers and also by Leave-one-subject-out cross-validation (LOSO-CV). …”
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autoMEA: machine learning-based burst detection for multi-electrode array datasets by Vinicius Hernandes, Anouk M. Heuvelmans, Anouk M. Heuvelmans, Valentina Gualtieri, Dimphna H. Meijer, Geeske M. van Woerden, Geeske M. van Woerden, Geeske M. van Woerden, Eliska Greplova

“…At present, the key challenge in the utilization of MEA data is the sheer complexity of the measured datasets. …”
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Identification of biomarkers and immune microenvironment associated with heart failure through bioinformatics and machine learning by Jingyun Jin, Jingyun Jin, Shuyan Qin, Qiang Fu, Changzhi Yu, Hongjin Wu, Hongjin Wu, Hongjin Wu

“…Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis were performed. Feature genes were further determined using two machine learning algorithms, Random Forest (RF) and Least Absolute Shrinkage and Selection Operator (LASSO), with diagnostic accuracy assessed via Receiver Operating Characteristic (ROC) curves and nomograms to screen hub genes, and external datasets further were used for validation. …”
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Dataset of SCAPS-1D simulated halide perovskite solar cells with SHAP and machine learning-based PCE optimizationZenodo by Ivan E. Novoselov, Alexander M. Gvozdev, Andrey A. Smirnov, Ivan S. Zhidkov

“…Additional files include detailed material databases featuring physical properties of electron and hole transport layers—such as band gap energies, electron affinities, dielectric permittivity, and carrier mobilities—organized in separate spreadsheets.Moreover, the repository offers a pre-trained CatBoost machine learning to predict the solar cell efficiency, along with a Jupyter Notebook that outlines the data preprocessing, machine learning workflow, and feature importance analysis via SHAP values. …”
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Anomaly detection of industrial state quantity time-Series data based on correlation and long short-term memory by Mingxin Tang, Wei Chen, Wen Yang

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RLDEAO optimized of air quality data clustering analysis(RLDEAO优化的空气质量数据聚类分析) by 田闯(TIAN Chuang), 黄鹤(HUANG He), 杨澜(YANG Lan), 王会峰(WANG Huifeng), 茹锋(RU Feng)

“…Aiming at the problems of high randomness, low clustering accuracy and multiple central points in clustering the same air quality data by traditional clustering methods due to different choice of initial points, a K-means complementary iterative air quality data clustering analysis method optimized by RLDEAO is proposed. …”
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Enhancing soil total nitrogen prediction in rice fields using advanced Geo-AI integration of remote sensing data and environmental covariates by Novandi Rizky Prasetya, Aditya Nugraha Putra, Mochtar Lutfi Rayes, Sri Rahayu Utami

“…STN content data were obtained for the top 20 cm soil from a total of 318 sampling points across all landforms—alluvial, karst, and volcanic—of the Malang Regency in East Java, Indonesia. …”
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Examining Nasdaq Market Data and Presenting an Optimized Model by Extreme Gradient Boosting Regression and Artificial Bee Colony by Ali Ahmadpour

“…This paper presents a comparative analysis of machine learning models applied to stock price prediction using historical data from the Nasdaq stock index spanning the years 2015 to 2023. …”
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Spatial Downscaling of Soil Moisture Product to Generate High-Resolution Data: A Multi-Source Approach over Heterogeneous Landscapes in Kenya by Asnake Kassahun Abebe, Xiang Zhou, Tingting Lv, Zui Tao, Abdelrazek Elnashar, Asfaw Kebede, Chunmei Wang, Hongming Zhang

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From Camera Image to Active Target Tracking: Modelling, Encoding and Metrical Analysis for Unmanned Underwater Vehicles by Samuel Appleby, Giacomo Bergami, Gary Ushaw

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Research on learning achievement classification based on machine learning. by Jianwei Dong, Ruishuang Sun, Zhipeng Yan, Meilun Shi, Xinyu Bi

“…In order to improve the accuracy and robustness of student performance classification, we adopted Gaussian Distribution based Data Augmentation technique (GDO), combined with multiple Deep Learning (DL) and Machine Learning (ML) models. …”
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Transferable Deep Learning Models for Accurate Ankle Joint Moment Estimation during Gait Using Electromyography by Amged Elsheikh Abdelgadir Ali, Dai Owaki, Mitsuhiro Hayashibe

“…This study evaluates the feasibility of different deep-learning models for estimating ankle moments using sEMG data to find an optimal intrasubject model against the inverse dynamic approach. …”
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Exploring distance learning in higher education: satisfaction and insights from Mexico, Saudi Arabia, Romania, Turkey by Miltiadis D. Lytras, Andreea Claudia Serban, Stamatios Ntanos

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Obstacles behind the innovation- a peek into Artificial intelligence in the field of orthodontics – A Literature review by Bushra Butul, Lina Sharab

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Risk level prediction for problematic internet use: A digital health perspective by Youngjung Suh, Jinwon Yoo

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Enhancing Dermatological Diagnosis Through Medical Image Analysis: How Effective Is YOLO11 Compared to Leading CNN Models? by Rakib Ahammed Diptho, Sarnali Basak

“…This investigation undertakes a comparative analysis of four state-of-the-art deep learning architectures, YOLO11, YOLOv8, VGG16, and ResNet50, in the context of skin disease identification. …”
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Evolutionary accumulation modeling in AMR: machine learning to infer and predict evolutionary dynamics of multi-drug resistance by Jessica Renz, Kazeem A. Dauda, Olav N. L. Aga, Ramon Diaz-Uriarte, Iren H. Löhr, Bjørn Blomberg, Iain G. Johnston

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Research on multiscale OpenStreetMap in China: data quality assessment with EWM-TOPSIS and GDP modeling by Chuqiao Han, Binbin Lu, Jianghua Zheng, Danlin Yu, Shudan Zheng

“…In addition to evaluating the data quality, the use of OSM data quality index factors in economic modeling at different spatial scales in China was explored by using a geographic information system (GIS) analysis method and a geographically and temporally weighted regression (GTWR) model. …”
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