Dataset of aerial photographs acquired with UAV using a multispectral (green, red and near-infrared) camera for cherry tomato (Solanum lycopersicum var. cerasiforme) monitoringDrya... by Osiris Chávez-Martínez, Sergio Alberto Monjardin-Armenta, Jesús Gabriel Rangel-Peraza, Zuriel Dathan Mora-Felix, Antonio Jesus Sanhouse-García

“…However, this multispectral imagery dataset can also have various uses, such as creating training datasets with accurate labels or classes which can then be used to develop, train, and/or validate machine learning algorithms for image classification, object detection tasks, or change detection analysis.…”
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Kidney Diseases Classification using Hybrid Transfer-Learning DenseNet201-Based and Random Forest Classifier by Abdalbasit Mohammed Qadir, Dana Faiq Abd

“…In this study, a hybrid technique is used by utilizing both pre-train models for feature extraction and classification using machine learning algorithms for the task of kidney disease image diagnosis. …”
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Instruments for assessing healthcare professionals’ knowledge, attitudes and practices regarding deprescribing: a scoping review protocol by Luciane Cruz Lopes, Jardel Corrêa de Oliveira, Luis Phillipe Nagem Lopes, Mariana Del Grossi Moura, Ana Carolina Figueiredo Modesto, Laís Lessa Neiva Pantuzza

“…Studies focusing on deprescribing algorithms will be excluded. Studies in any healthcare setting will be included. …”
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Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization by Felipe A.C. Viana, Valder Steffen Jr., Marcelo A.X. Zanini, Sandro A. Magalhães, Luiz C.S. Góes

“…In the present formulation two nature-based methods, namely the Genetic Algorithms and the Particle Swarm Optimization were used. …”
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Identification of a novel immunogenic cell death-related classifier to predict prognosis and optimize precision treatment in hepatocellular carcinoma by Dongjing Zhang, Bingyun Lu, Qianqian Ma, Wen Xu, Qi Zhang, Zhiqi Xiao, Yuanheng Li, Ren Chen, An-jiang Wang

“…A reliable risk model named ICD score was constructed via machine learning algorithms to assess the immunological status, therapeutic responses, and clinical outcomes of individual HCC patients. …”
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Machine Learning Models for Predicting Thermal Properties of Radiative Cooling Aerogels by Chengce Yuan, Yimin Shi, Zhichen Ba, Daxin Liang, Jing Wang, Xiaorui Liu, Yabei Xu, Junreng Liu, Hongbo Xu

“…A comparative analysis of various machine learning algorithms revealed that an optimized XGBoost model demonstrated superior predictive performance, achieving an R² value of 0.943 and an RMSE of 1.423 for the test dataset. …”
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Design of Coffee Disease Detection Web Application Using Image Processing: A Case Study of Kyabugimbi-Kajunju Cooperative Farms in Bushenyi District. by Asiimwe, Mark, Kakuru, Ambrose

“…The methodology involves acquiring high-resolution images, employing pre-processing methods to enhance data quality, and implementing state-of-the-art machine-learning algorithms for disease classification. The proposed system seeks to surpass existing methods by achieving higher efficiency in disease detection. …”
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Effectiveness and Design of PBL-Based Project Approach for Non-Major University Computing Courses by Jung-In Choi, Sooyeon Yang

“…These findings suggest that the Problem-Based Learning project approach mirrors real-world practices, equipping students with essential computational thinking skills and a deeper understanding of foundational topics such as Python, data structures, and algorithms. This study provides valuable insights for the development of instructional strategies in computing courses for non-major students, emphasizing the importance of creating systematic learning environments that bridge theoretical knowledge and practical application through real-world problem-solving activities.…”
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Development of Competent Mathematical Speech of Students at Technical University by A. V. Muzhikova, M. N. Gabova

“…The prepared organizational and methodological support of teaching, the systemic educational work allow students to improve their speech skills and skills of active use of mathematical language as a universal language of science, to develop logical, algorithmic and mathematical thinking, the ability to apply methods of mathematical analysis and modeling, theoretical and experimental research in solving professional problems.…”
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Metatheory and Classification of Digital Human Rights and Freedoms by G. V. Alexeyev

“…The theory of individual freedom and legal equality, when faced with computer information processing algorithms, gives rise to paradoxes and oxymorons. The obvious contradictions in the moralism of the virtual world and real justice are complemented by the paradoxical conclusions of lawyers about the legal personality of robots with artificial intelligence and the similarity of the laws for the real world and cyberspace. …”
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Robust Schnorr-based subgroup multi-signature scheme by ZHANG Zhenqi, ZHU Qiuchi, WANG Zhiwei

“…Theoretical analysis and experimental results show that the scheme possesses smaller public key length, private key length, single signature length, and multi-signature length, with fewer communication rounds and reduced time overhead in the signature generation and verification algorithms, providing superior performance when applied to consensus mechanisms.…”
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Can the number of confirmed COVID-19 cases be predicted more accurately by including lifestyle data? An exploratory study for data-driven prediction of COVID-19 cases in metropolit... by Sungwook Jung

“…Finally, a ‘lifestyle addition’ set was constructed that added lifestyle data to the number of past confirmed cases and search term frequency data. The deep learning algorithms used in the analysis are deep neural networks (DNNs) and recurrent neural networks (RNNs). …”
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Random Forest–Based Coal Mine Roof Displacement Prediction and Application by Hongxia Li, Rong Wu, Jianan Gao

“…Based on Random Forest (RF), XGBoost, and Gradient Boosting Decision Tree (GBDT) algorithms, three kinds of roof displacement prediction models are established respectively. …”
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High-Quality Text-to-Image Generation Using High-Detail Feature-Preserving Network by Wei-Yen Hsu, Jing-Wen Lin

“…Multistage text-to-image generation algorithms have shown remarkable success. However, the images produced often lack detail and suffer from feature loss. …”
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Multi-Scale Feature Fusion and Context-Enhanced Spatial Sparse Convolution Single-Shot Detector for Unmanned Aerial Vehicle Image Object Detection by Guimei Qi, Zhihong Yu, Jian Song

“…., VisDrone and ARH2000; the latter dataset was created by the researchers) demonstrate that the MFFCESSC-SSD remarkably outperforms the performance of the SSD and numerous conventional object detection algorithms in terms of accuracy and efficiency.…”
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A data-driven methodology for the classification of different liquids in artificial taste recognition applications with a pulse voltammetric electronic tongue by Jersson X Leon-Medina, Leydi J Cardenas-Flechas, Diego A Tibaduiza

“…However, one of the problems in the use of this kind of device is associated with the development of reliable pattern recognition algorithms and robust data analysis. In this sense, this work introduces a taste recognition methodology, which is composed of several steps including unfolding data, data normalization, principal component analysis for compressing the data, and classification through different machine learning models. …”
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A spatially explicit containment modelling approach for escaped wildfires in a Mediterranean climate using machine learning by Gbenga Lawrence Alawode, Pere Joan Gelabert, Marcos Rodrigues

“…Using machine learning algorithms, geospatial data, and 124 historical wildfire perimeters from 2000 to 2015, we developed a predictive model with high accuracy (Area Under the Receiver Operating Characteristics Curve = 0.81 ± 0.03) over 32,108 km2 at a 30-meter resolution. …”
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ExAIRFC-GSDC: An Advanced Machine Learning-Based Interpretable Framework for Accurate Gas Leakage Detection and Classification by B. Lalithadevi, S. Krishnaveni

“…The proposed ExAIRFC-GSDC model integrates machine learning algorithms, particularly a Random Forest Classifier, with explainable artificial intelligence (XAI) techniques to enhance interpretability. …”
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Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review by Catalina Gomez, Sue Min Cho, Shichang Ke, Chien-Ming Huang, Mathias Unberath

“…Leveraging Artificial Intelligence (AI) in decision support systems has disproportionately focused on technological advancements, often overlooking the alignment between algorithmic outputs and human expectations. A human-centered perspective attempts to alleviate this concern by designing AI solutions for seamless integration with existing processes. …”
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