Soil Salinity Detection and Mapping by Multi-Temporal Landsat Data: Zaghouan Case Study (Tunisia) by Karem Saad, Amjad Kallel, Fabio Castaldi, Thouraya Sahli Chahed

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Synergistic Mechanisms Between Elderly Oriented Community Activity Space Morphology and Microclimate Performance: An Integrated Learning and Multi-Objective Optimization Approach by Fang Wen, Lu Zhang, Ling Jiang, Rui Tang, Bo Zhang

“…This study collected site and spatial morphological data from 63 typical aging community activity spaces and extracted 12 spatial types through statistical analysis. …”
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Comparative Analysis of Attention Mechanisms in Densely Connected Network for Network Traffic Prediction by Myeongjun Oh, Sung Oh, Jongkyung Im, Myungho Kim, Joung-Sik Kim, Ji-Yeon Park, Na-Rae Yi, Sung-Ho Bae

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Application of Machine Learning Models in Optimizing Wastewater Treatment Processes: A Review by Florin-Stefan Zamfir, Madalina Carbureanu, Sanda Florentina Mihalache

“…This research studies how machine learning (ML) with a focus on deep learning (DL) techniques can be applied to optimize the treatment processes of WWTPs, highlighting those case studies that propose ML and DL methods that directly address this issue. …”
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Garbage prediction using regression analysis for municipal corporations of Indian cities by Raj Kumar Sharma, Manisha Jailia

“…To establish a connection between the variables, the descriptive study employs statistical techniques to learn about the composition of data collected from municipal corporations and conduct correlation analysis. …”
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Domain Adaptation in Application to Gravitational Lens Finding by Hanna Parul, Sergei Gleyzer, Pranath Reddy, Michael W. Toomey

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Separating Repeating Fast Radio Bursts Using the Minimum Spanning Tree as an Unsupervised Methodology by C. R. García, Diego F. Torres, Jia-Ming Zhu-Ge, Bing Zhang

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JOB: Japan Omics Browser provides integrative visualization of multi-omics data by Yugo Takahashi, Qingbo S. Wang, Takanori Hasegawa, Ho Namkoong, Fumitaka Inoue, Koichi Fukunaga, Seiya Imoto, Satoru Miyano, Yukinori Okada, Japan COVID-19 Task Force

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Learning from the diversity of national structures, processes and intentions with regard to extended education by Bettina Krepper, Alexandra Efstathiades, James Loparics, James Loparics

“…Factors influenced by EE.DiscussionThe analysis of the data shows that, despite national differences, there are common intentions, processes and structures that are productive for the development of key competences and future skills. …”
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Leveraging TEMI Transcription Software for Qualitative Analysis in ESL Research by Jala Hashim

“…TEMI’s automated transcription provided structured transcripts for analysis. TEMI's automated transcription, synchronized video playback, and customizable speaker labels supported the organization and review of interviews and focus groups, contributing to structured data analysis. …”
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A Hybrid Transformer-CNN Model for Interpolating Meteorological Data on the Tibetan Plateau by Quanzhe Hou, Zhiqiu Gao, Mingxinyu Lu, Yinxin Yu

“…This study employs eight machine learning models (support vector regression (SVR), k-nearest neighbors (KNN), extreme gradient boosting (XGBoost), random forest (RF), long short-term memory (LSTM), gated recurrent unit (GRU), Transformer, and Transformer–convolutional neural network (Transformer-CNN)) to interpolate missing observational data on surface net radiation (Rn), soil surface temperature (Ts), soil water content (SWC), air temperature (Ta), relative humidity (RH), and wind speed (WS) from the QOMS observation site. …”
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Real-time lithology identification while drilling based on drilling parameters analysis with machine learning by Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Chunmiao Liang

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Reflections on dynamic prediction of Alzheimer’s disease: advancements in modeling longitudinal outcomes and time-to-event data by Durong Chen, Meiling Zhang, Hongjuan Han, Yalu Wen, Hongmei Yu

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Improved cluster analysis of Werner solutions for geologic depth estimation using unsupervised machine learning by Daniel Eshimiakhe, Raimi Jimoh, Magaji Suleiman, Kola Lawal

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Machine Learning for Anomaly Detection in Blockchain: A Critical Analysis, Empirical Validation, and Future Outlook by Fouzia Jumani, Muhammad Raza

“…Although blockchain provides multiple advantages, it has also been subject to some malicious attacks, such as a 51% attack, which is considered a potential risk to data integrity. These attacks can be detected by analyzing the anomalous node behavior of miner nodes in the network, and data analysis plays a vital role in detecting and overcoming these attacks to make a secure blockchain. …”
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Identification of Clusters in a Population With Obesity Using Machine Learning: Secondary Analysis of The Maastricht Study by Maik JM Beuken, Melanie Kleynen, Susy Braun, Kees Van Berkel, Carla van der Kallen, Annemarie Koster, Hans Bosma, Tos TJM Berendschot, Alfons JHM Houben, Nicole Dukers-Muijrers, Joop P van den Bergh, Abraham A Kroon, Iris M Kanera

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Filter Learning-Based Partial Least Squares Regression and Its Application in Infrared Spectral Analysis by Yi Mou, Long Zhou, Weizhen Chen, Jianguo Liu, Teng Li

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Improving Location-Based Thermal Emission Side-Channel Analysis Using Iterative Transfer Learning by Kai Zhang, Tun-Chieh Lou, Chung-Che Wang, Jyh-Shing Roger Jang, Henian Li, Lang Lin, Norman Chang

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Application of multimodal machine learning-based analysis for the biomethane yields of NaOH-pretreated biomass by Oluwatobi Adeleke, Kehinde O. Olatunji, Daniel M. Madyira, Tien-Chien Jen

“…The biomass was subjected to varying NaOH concentrations and exposure times, then digested anaerobically for 35 days. A comprehensive data-driven insight was gained through correlation-mapping, SHAP-based XAI for feature-ranking, cluster analysis for bio-digestion operational dataset using k-means integrated with Principal Component Analysis (PCA). …”
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Comparative Analysis of Machine Learning Techniques for Fault Diagnosis of Rolling Element Bearing with Wear Defects by Devendra Sahu, Ritesh Kumar Dewangan, Surendra Pal Singh Matharu

“…The model was further refined by extracting 14 types of features from the SNR-enhanced vibration data, presenting a comprehensive depiction of fault patterns and finally, machine learning techniques were applied to categorize faults using the aforementioned datasets, facilitating a comparative analysis of results. …”
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