Machine-learning-based reconstruction of long-term global terrestrial water storage anomalies from observed, satellite and land-surface model data by N. Mandal, P. Das, K. Chanda, K. Chanda

“…<p>Understanding long-term terrestrial water storage (TWS) variations is vital for investigating hydrological extreme events, managing water resources and assessing climate change impacts. However, the limited data duration from the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) poses challenges for comprehensive long-term analysis. …”
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Towards automated and real-time multi-object detection of anguilliform fishes from sonar data using YOLOv8 deep learning algorithm by Tao Huang, Xiaoqin Zang, Grigoriy Kondyukov, Zhangshuan Hou, Guanze Peng, Joachim Pander, Josef Knott, Juergen Geist, Meklit Berihun Melesse, Paul Jacobson, Zhiqun Daniel Deng

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PyCSBtool: Python-Based GUI Learning Tool for Basics Control System Education by C. H. Manathunga, R. A. D. D. Dharmasiri, W. K. Indika L. Wanniarachchi, M. K. Jayananda, Tadachika Nakayama

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Interpretable machine learning approaches for predicting prostate cancer by using multiple heavy metal exposures based on the data from NHANES 2003–2018 by Zu-Ming You, Yuan-Sheng Li, Fan-Shuo Meng, Rui-Xiang Zhang, Chen-Xi Xie, Zhijiang Liang, Ji-Yuan Zhou

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Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model by Kwang Cheol Oh, Sunyong Park, Seok Jun Kim, La Hoon Cho, Chung Geon Lee, Dae Hyun Kim

“…We developed an internal environment prediction model for smart greenhouses using machine learning models. Machine learning models were developed by finding certain rules based on the data obtained from the target system and have the advantage of learning various characteristics that are difficult to define theoretically. …”
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Quantifying axonal features of human superficial white matter from three-dimensional multibeam serial electron microscopy data assisted by deep learning by Qiyuan Tian, Chanon Ngamsombat, Hong-Hsi Lee, Daniel R. Berger, Yuelong Wu, Qiuyun Fan, Berkin Bilgic, Ziyu Li, Dmitry S. Novikov, Els Fieremans, Bruce R. Rosen, Jeff W. Lichtman, Susie Y. Huang

“…This work presents results from multi-beam scanning electron microscopy (EM) data acquired at 4 × 4 × 33 nm3 resolution in a volume of human superficial white matter measuring 200 × 200 × 112 μm3, leveraging automated analysis methods. …”
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Transfer learning‑based attenuation correction in 99mTc-TRODAT-1 SPECT for Parkinson’s disease using realistic simulation and clinical data by Wenbo Huang, Han Jiang, Yu Du, Haiyan Wang, Hao Sun, Guang-Uei Hung, Greta S. P. Mok

“…Comparisons were made against without FT (DLAC-MC), training on purely limited clinical data (DLAC-CLI), clinical data with data augmentation (DLAC-AUG), mixed MC and clinical data (DLAC-MIX), TL using analytical simulation data (TLAC-ANA), and Chang’s AC (ChangAC). …”
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Data fusion-based improvements in empirical regression and machine learning for global daily ∼ 8 km resolution sea surface nitrate estimation and interpretation by Aifen Zhong, Difeng Wang, Fang Gong, Jingjing Huang, Zhuoqi Zheng, Xianqiang He, Qing Zhang, Qiankun Zhu

“…Here we aim to enhance the accuracy and spatial resolution of SSN retrievals by developing improved regression and machine learning models, enabling the generation of global daily ∼ 8 km SSN products from satellite and model data. …”
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Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance by Firgiawan Faira, Dandy Pramana Hostiadi

“…The novelty of this research lies in the application of a data aggregation technique to address class imbalance, significantly improving machine learning model performance and optimizing training time. …”
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Portable XRF and Vis-NIR spectrometry for predicting chemical properties of forest soils in the Amazon: Insights into sensor data dimensionality reduction by Quésia Sá Pavão, Paula Godinho Ribeiro, Gutierre Pereira Maciel, Sérgio Henrique Godinho Silva, Suzana Romeiro Araújo, Antonio Rodrigues Fernandes, José Alexandre Melo Demattê, Pedro Walfir Martins e Souza Filho, Silvio Junio Ramos

“…Proximal sensor data integrated with machine learning algorithms have been successful in assessing soil chemical parameters. …”
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The Analysis of Barriers to the Use of Physics Practicum Applications by Novi Ramayani, Lia Amalia

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Assessing concordance between RNA-Seq and NanoString technologies in Ebola-infected nonhuman primates using machine learning by Mostafa Rezapour, Aarthi Narayanan, Wyatt H. Mowery, Metin Nafi Gurcan

“…Using a machine learning approach with the Supervised Magnitude-Altitude Scoring (SMAS) method trained on NanoString data, OAS1 was identified as a key gene signature for distinguishing RT-qPCR positive from negative samples. …”
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A Data Imputation Strategy to Enhance Online Game Churn Prediction, Considering Non-Login Periods by JaeHong Lee, Pavinee Rerkjirattikal, SangGyu Nam

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Determination of Pear Cultivars (Pyrus communis L.) Based on Colour Change Levels by Using Data Mining by Dilara Gerdan, Abdullah Beyaz, Mustafa Vatandaş

“…For this aim the colour change of the damaged pears were determined, in another term, colour change value from red to green and yellow to blue at the damaged pears were determined with lightness values by using image analysis technique and analysed with data mining methods. …”
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P-V-L Deep: A Big Data Analytics Solution for Now-casting in Monetary Policy by Maryam Hajipour Sarduie, Mohammadali Afshar Kazemi, Mahmood Alborzi, Adel Azar, Ali Kermanshah

“…So, it is necessary to consider the highly data-driven technologies and to use new methods of analysis, like machine learning and visualization tools, with the ability of interaction and connection to different data resources with varieties of data regarding the type of big data aimed at reducing the risks of policy-making institution’s investment in the field of IT. …”
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The Role of Big Data Analytics in Revolutionizing Diabetes Management and Healthcare Decision-Making by Muhammad Nauman, Ahmad S. Almadhor, Mohammed Albekairi, Ali R. Ansari, Muhammad A. B. Fayyaz, Raheel Nawaz

“…The remarkable increases in data volumes, along with the enticing prospects and potential inherent in data analysis, have contributed to the concept of Big Data. …”
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Oriented ice eddy detection network based on the Sentinel-1 dual-polarization data by Jinqun Wu, Jinqun Wu, Yiqin Zheng, Tingting Wang, Chunyong Ma, Chunyong Ma, Ge Chen, Ge Chen

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A comprehensive diagnostic framework for hepatitis C using structured data and predictive analytics by Behnaz Motamedi, Balázs Villányi

“…This study posits that a structured preprocessing and feature selection methodology might substantially improve the classification accuracy and generalizability of machine learning (ML) models in predicting stages of hepatitis C virus (HCV) using clinical and demographic data. …”
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Data-driven predictive model of coal permeability based on microscopic fracture structure characterization by Tianhao Yan, Xiaomeng Xu, Jiafeng Liu, Yihuai Zhang, Muhammad Arif, Xiaowei Xu, Qiang Wang

“…The proposed framework encompasses data generation through the integration of three-dimensional (3D) digital core analysis and numerical simulations, followed by data-driven modeling via machine learning (ML) techniques. …”
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Pine Wilt Disease Monitoring Using Multimodal Remote Sensing Data and Feature Classification by Xin Ye, Hanwen Yu, Yan Yan, Tieming Liu, Yan Zhang, Taoli Yang

“…To facilitate practical implementation, we developed a deep learning-based model, PWD-Net, which efficiently integrates these multimodal data for the monitoring of diseased pine trees. …”
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