Balancing AI-assisted learning and traditional assessment: the FACT assessment in environmental data science education by Ahmed S. Elshall, Ahmed S. Elshall, Ahmed S. Elshall, Ashraf Badir

“…To address these challenges, the Fundamental, Applied, Conceptual, critical Thinking (FACT) assessment was implemented in an Environmental Data Science course for upper-level undergraduate and graduate students from civil and environmental engineering, and Earth sciences. …”
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Monitoring water quality parameters using multi-source data-driven machine learning models by Yubo Zhao, Mo Chen, Jinyu He, Yanping Ma

“…Remote sensing technology, as an effective monitoring tool, provided real-time water quality data. Currently, most research primarily relied on reflectance analysis of remote sensing data, often overlooking the impact of environmental factors on aquatic environments. …”
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Optimising dynamic treatment regimens using sequential multiple assignment randomised trials data with missing data by Jessica Xu, Anurika P. De Silva, Katherine J. Lee, Robert K. Mahar, Julie A. Simpson

“…Common methods for handling missing data such as complete case analysis (CCA) and multiple imputation (MI) have been widely explored in single-stage randomised trials, however, the only study that explored these methods in SMARTs did not consider Q-learning. …”
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Pothole detection and segmentation in the Bushveld Complex using physics-based data augmentation and deep learning by Glen T. Nwaila, Musa S.D. Manzi, Emmanuel John M. Carranza, Raymond J. Durrheim, Hartwig E. Frimmel

“…We demonstrate that a self-reinforcing feedback loop of knowledge-driven data engineering and deep learning has the potential to overcome data quality issues in supervised tasks of seismic data analysis. …”
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Predictions of Spartina alterniflora leaf functional traits based on hyperspectral data and machine learning models by Wei Li, Xueyan Zuo, Zhijun Liu, Leichao Nie, Huazhe Li, Junjie Wang, Zhiguo Dou, Yang Cai, Xiajie Zhai, Lijuan Cui

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Mapping Gridded GDP Distribution of China Based on Remote Sensing Data and Machine Learning Methods by Saimiao Liu, Wenliang Liu, Yi Zhou, Shixin Wang, Futao Wang, Zhenqing Wang

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Machine learning-based identification of proteomic markers in colorectal cancer using UK Biobank data by Swarnima Kollampallath Radhakrishnan, Dipanwita Nath, Dominic Russ, Dominic Russ, Dominic Russ, Laura Bravo Merodio, Laura Bravo Merodio, Laura Bravo Merodio, Priyani Lad, Folakemi Kola Daisi, Animesh Acharjee, Animesh Acharjee, Animesh Acharjee

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The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review by Norah Hamad Alhumaidi, Doni Dermawan, Hanin Farhana Kamaruzaman, Nasser Alotaiq

“… BackgroundMachine learning (ML) and big data analytics are rapidly transforming health care, particularly disease prediction, management, and personalized care. …”
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Quantitative insights into the Winnipeg rental sector: A data-driven analytical approach using geographic and property metrics by Lahiru Wickramasinghe, Aditya Jain

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ONLINE FUZZY CLUSTERING OF HIGH DIMENSION DATA STREAMS BASED ON NEURAL NETWORK ENSEMBLES by Yevgeniy Bodyanskiy, Iryna Perova, Polina Zhernova

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Integrating CT radiomics and clinical data with machine learning to predict fibrosis progression in coalworker pneumoconiosis by Xiaobing Li, Xiaobing Li, Xiaobing Li, Xiaobing Li, Xiaobing Li, Qian Li, Qian Li, Qian Li, Qian Li, Xinyi Xie, Wei Wang, Xuemei Li, Tingqiang Zhang, Tingqiang Zhang, Tingqiang Zhang, Tingqiang Zhang, Li Zhang, Li Zhang, Li Zhang, Li Zhang, Yongsheng Liu, Yongsheng Liu, Yongsheng Liu, Yongsheng Liu, Li Wang, Li Wang, Li Wang, Li Wang, Wutao Xie

“…ObjectiveThis study aims to develop a machine learning (ML) model that integrates computed tomography (CT) radiomics with clinical features to predict the progression of pulmonary interstitial fibrosis in patients with coalworker pneumoconiosis (CWP).MethodsClinical and imaging data from 297 patients diagnosed with CWP at The First Affiliated Hospital of Chongqing Medical and Pharmaceutical College between December 2021 and December 2023 were analyzed. …”
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Modeling Population Mobility Flows: A Hybrid Approach Integrating a Gravity Model and Machine Learning by Jingjing Liu, Lei Xu, Le Ma, Nengcheng Chen

“…Traditional population migration models reveal the factors influencing migration, while machine learning methods provide effective tools for creating data-driven models to handle the nonlinear relationships between origin and destination characteristics and migration. …”
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Crop Yield Prediction: Data Structure and Ai-Powered Methods by V. K. Kalichkin, K. Yu. Maksimovich, O. A. Aleshchenko, V. V. Aleshchenko

“…(Research purpose) The aim of this study is to analyze data structures and compare machine learning and deep learning algorithms used in used in crop yield prediction. …”
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The Role of Education in Building National Soft Power: An Empirical Analysis From a Global Perspective Using Deep Neural Networks by Yun Bai

“…These advancements have led to significant achievements in predictive modeling, data analysis, and decision-making processes. However, there remains a need for more sophisticated models that can accurately capture complex relationships in dynamic, real-world datasets. …”
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From molecules to data: the emerging impact of chemoinformatics in chemistry by Anup Basnet Chetry, Keisuke Ohto

“…Abstract Chemoinformatics is a rapidly advancing field that integrates chemistry, computer science, and data analysis to enhance the study and application of chemical systems. …”
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Research on the quantification and automatic classification method of Chinese cabbage plant type based on point cloud data and PointNet++ by Chongchong Yang, Chongchong Yang, Lei Sun, Lei Sun, Jun Zhang, Jun Zhang, Xiaofei Fan, Xiaofei Fan, Dongfang Zhang, Dongfang Zhang, Tianyi Ren, Tianyi Ren, Minggeng Liu, Minggeng Liu, Zhiming Zhang, Zhiming Zhang, Wei Ma, Wei Ma

Subjects: “…point cloud data…”
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BCP-based joint delegation learning model and protocol by Sheng GAO, Kang XIANG, Youliang TIAN, Weijie TAN, Tao FENG, Xiaoxue WU

“…In order to realize data security sharing and reduce the computing costs of clients in data mining process, a joint delegation learning model and protocol based on BCP homomorphic encryption algorithm was proposed.Firstly, a privacy preserving method based on false records was proposed for the security of decision tree model.Secondly, in view of the vertical and horizontal distribution of data, the corresponding delegation learning protocols based on privacy preserving delegation dot product algorithm and privacy preserving delegation entropy algorithm was proposed.Finally, the security proof and the performance analysis of delegation learning protocols and decision tree model structure were given.The results show that the privacy protection method based on false records does not affect the final model construction, and the final model obtained by each client is the same as that constructed by real data.…”
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Resource Allocation for Federated Learning With Highly Distorted Model by Ryu Junewoo, Nguyen Xuan Tung, Minh-Duong Nguyen, Quang-Vinh do, Won-Joo Hwang

“…Therefore, existing communication-effective federated learning (FL) approaches (e.g., model quantization, data sparsification, and model compression) incurred a considerable trade-off between communication efficiency and global convergence rate when an extreme encryption rate is applied. …”
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Spatial Deep Learning Approach to Older Driver Classification by Charles Boateng, Seyedeh Gol Ara Ghoreishi, Kwangsoo Yang, Muhammad Tanveer Jan, Ruth Tappen, Jinwoo Jang, David Newman, Sonia Moshfeghi, Kelley Jackson, Rhian Resnick, Borko Furht, Monica Rosselli, Joshua Conniff

“…This paper proposes a novel spatial deep-learning approach that leverages Grid-Index based data augmentation to enhance the detection of abnormal driving behaviors. …”
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Multivariate Modelling and Prediction of High-Frequency Sensor-Based Cerebral Physiologic Signals: Narrative Review of Machine Learning Methodologies by Nuray Vakitbilir, Abrar Islam, Alwyn Gomez, Kevin Y. Stein, Logan Froese, Tobias Bergmann, Amanjyot Singh Sainbhi, Davis McClarty, Rahul Raj, Frederick A. Zeiler

Subjects: “…high-dimensional cerebral data analysis…”
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