Digital mapping of soil electrical conductivity for paddy field by The Anh Anh, Luu Trong Hieu, Chi Ngon Nguyen

“…Using 228 data samples, the study found that the Gaussian model within Kriging was the most effective for interpolating soil EC, achieving the highest R-squared values (0.79 with test data and 0.96 with full data) and the lowest RMSE values (0.049 with test data and 0.022 with full data). …”
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A fault diagnosis model for pumping units based on small sample electric parameters by Chunhua Yuan, Zhupei Liao, Xiangyu Li

“…Abstract In the field of modern petroleum industry, fault diagnosis and classification of pumping units are among the most crucial research topics. The conventional diagnostic method involves installing sensors on the pumping unit to analyze the dynamometer cards(DCs). …”
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Predictive Analysis of Maritime Congestion Using Dynamic Big Data and Multiscale Feature Analysis by Yalin Wu

“…The maritime industry is one of the most crucial sectors in the global economy, facilitating the transportation of goods and commodities across vast distances. …”
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Large-Scale Image Retrieval of Tourist Attractions Based on Multiple Linear Regression Equations by Yinping Song

“…The advantages of feature extraction by a convolutional neural network and the high efficiency of a hash index structure in retrieval are used to solve the shortcomings of traditional methods in terms of accuracy and other aspects in image retrieval. …”
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Enhanced Workload Prediction in Data Centers Using Two-Stage Decomposition and Hybrid Parallel Deep Learning by Dalal Alqahtani, Hamidreza Imani, Tarek El-Ghazawi

“…Workload prediction is one of the most basic requirements in developing cost and energy-efficient Cloud Data Centers (CDCs). …”
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Evaluating the efficacy and site-specific performance of machine learning approaches: A comprehensive review of autism detection models by Deblina Mazumder Setu, Tania Islam, Md Maklachur Rahman, Samrat Kumar Dey, Tazizur Rahman

“…From them, 18 studies are based on 14 popular machine learning (ML) models to identify the most effective prediction methods. And four of them are more progressive, sophisticated methods including the convolutional neural network (CNN) model, diagnostic autism spectrum disorder (DASD) strategy, Ensemble Diagnosis Methodology (EKNN), and Self-Organizing Maps (SOM). …”
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AI and Data Analytics in the Dairy Farms: A Scoping Review by Osvaldo Palma, Lluis M. Plà-Aragonés, Alejandro Mac Cawley, Víctor M. Albornoz

“…To this end, a scoping review was carried out, which resulted in 151 articles of interest. Among the most important results, we found that (i) the identified studies are relatively recent with an average publication time of 5.95 years; (ii) the scope of the selected studies is mostly concentrated on milk and prediction (29%), early detection of lameness (26%), and timely detection of mastitis (13%); (iii) the type of analysis is mostly predictive (87%), and prescriptive is barely present (3%); (iv) the types of input data used in the studies are preferably historical (70%), and real-time data (25%) are used less frequently; (v) we found that the method of artificial neural networks (47%) and the convolutional neural networks (24%) are the most used for the studies regarding bovine milk output predictions. …”
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Constraint-aware wind power forecasting with an optimized hybrid machine learning model by Md. Omer Faruque, Md. Alamgir Hossain, S.M. Mahfuz Alam, Muhammad Khalid

“…On top of that, the performance of the proposed scheme was assessed under diverse ramping threshold settings, ranging from the most stringent worst-case scenarios to relaxed operational conditions. …”
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DenseNet-FPA: Integrating DenseNet and Flower Pollination Algorithm for Breast Cancer Histopathology Image Classification by Musa Adamu Wakili, Harisu Abdullahi Shehu, Mahdi Abdollahi, Badamasi Imam Ya'u, Md Haidar Sharif, Huseyin Kusetogullari

“…Breast cancer is one of the most prevalent and life-threatening diseases affecting women worldwide. …”
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Development and evaluation of deep neural networks for the classification of subtypes of renal cell carcinoma from kidney histopathology images by Amit Kumar Chanchal, Shyam Lal, Shilpa Suresh

“…Abstract Kidney cancer is a leading cause of cancer-related mortality, with renal cell carcinoma (RCC) being the most prevalent form, accounting for 80–85% of all renal tumors. …”
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Deep Learning-Based Sign Language Recognition Using Efficient Multi-Feature Attention Mechanism by Esma Yenisari, Sirma Yavuz

“…These features are adaptively weighted using an attention mechanism and focus on the most critical information for the classification task. …”
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Impact of eye fundus image preprocessing on key objects segmentation for glaucoma identification by Sandra Virbukaitė, Jolita Bernatavičienė

“…The experimental results show that the most accurate segmentation is achieved by resizing images to a size of 512 x 512 px and applying bicubic interpolation. …”
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Structural Similarity-Guided Siamese U-Net Model for Detecting Changes in Snow Water Equivalent by Karim Malik, Colin Robertson

“…Snow water equivalent (SWE), the amount of water generated when a snowpack melts, has been used to study the impacts of climate change on the cryosphere processes and snow cover dynamics during the winter season. In most analyses, high-temporal-resolution SWE and SD data are aggregated into monthly and yearly averages to detect and characterize changes. …”
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Unmanned Aerial Vehicle-Based Hyperspectral Imaging for Potato Virus Y Detection: Machine Learning Insights by Siddat B. Nesar, Paul W. Nugent, Nina K. Zidack, Bradley M. Whitaker

“…The potato is the third most important crop in the world, and more than 375 million metric tonnes of potatoes are produced globally on an annual basis. …”
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Role of Artificial Intelligence and Deep Learning in Easier Skin Cancer Detection through Antioxidants Present in Food by Sreevidya R. C., Jalaja G, Sajitha N, D. Lakshmi Padmaja, S. Nagaprasad, Kumud Pant, Yekula Prasanna Kumar

“…Skin cancer is one of the most common types of cancer that has a high mortality rate. …”
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Enhanced skin cancer diagnosis: a deep feature extraction-based framework for the multi-classification of skin cancer utilizing dermoscopy images by Hadeel Alharbi, Gabriel Avelino Sampedro, Roben A. Juanatas, Se-jung Lim

“…Skin cancer is one of the most common, deadly, and widespread cancers worldwide. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…It also goes over the most popular datasets used by various diagnostic models (ECG and PCG signals datasets). …”
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A Review: Radar Remote-Based Gait Identification Methods and Techniques by Bruno Figueiredo, Álvaro Frazão, André Rouco, Beatriz Soares, Daniel Albuquerque, Pedro Pinho

“…Despite the fact that FMCW is the most closely related radar to real-world scenarios, it still has some limitations in terms of multi-subject identification and open-set scenarios. …”
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Progression risk of adolescent idiopathic scoliosis based on SHAP-Explained machine learning models: a multicenter retrospective study by Xinyi Fang, Ting Weng, Zhehao Zhang, Wanfeng Gong, Yu Zhang, Mei Wang, Jianhua Wang, Zhongxiang Ding, Can Lai

“…Abstract Objective To develop an interpretable machine learning model, explained using SHAP, based on imaging features of adolescent idiopathic scoliosis extracted by convolutional neural networks (CNNs), in order to predict the risk of curve progression and identify the most accurate predictive model. …”
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An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…Classification is one of the most prominent modeling approaches that can be successfully applied in model-based medical support systems to make more accurate diagnostic decisions. …”
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