Spectral Fingerprinting of Tencha Processing: Optimising the Detection of Total Free Amino Acid Content in Processing Lines by Hyperspectral Analysis by Qinghai He, Yihang Guo, Xiaoli Li, Yong He, Zhi Lin, Hui Zeng

“…This study employs VNIR-HSI combined with machine learning algorithms to develop a model for visualizing the total free amino acid content in Tencha samples that have undergone different processing steps on the production line. …”
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Unsupervised Learning With Hybrid Models for Detecting Electricity Theft in Smart Grids by Ali Jaber Almalki

“…By fusing supervised learning models (Random Forest) with unsupervised learning algorithms (Isolation Forest, One-Class Support Vector Machine (SVM), Local Outlier Factor (LOF), and Density-Based Spatial Clustering of Applications with Noise(DBSCAN)), this study presents a unique hybrid technique for identifying power theft. …”
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Predictive modeling for rework detection in sustainable building projects by AbdulLateef Olanrewaju, Kafayat Shobowale

“…Feature scaling and normalisation were performed across the dataset to standardise the features. Six machine learning models that comprised support vector machine, Adaboost, Logistic regression, a K-nearest neighbour, neural network and random forest classifier were trained to predict the occurrence of reworks in sustainable buildings. …”
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Establishing strength prediction models for low-carbon rubberized cementitious mortar using advanced AI tools by Fu Limei, Xu Feng

“…Rubberized cementitious composites have emerged as a sustainable alternative in the construction sector by promoting circular economy principles. However, their reduced compressive strength (CS) due to the inclusion of rubber remains a significant barrier to widespread adoption. …”
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Artificial Intelligence and Smart Technologies in Safety Management: A Comprehensive Analysis Across Multiple Industries by Jiyoung Park, Dongheon Kang

“…For instance, in the energy and power sector, intelligent gas meters and automated fire suppression systems manage gas-related risks effectively, while in the health sector, AI-powered health monitoring devices and mental health support applications improve patient and worker safety. …”
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GIS Analysis Model Integration and Service Composition Prospects by L. Ding, P. Cai, W. Huang, H. Zhang, F. Ding, W. Zhao, D. Tang, Z. Wang

“…GIS model integration involves combining diverse spatial algorithms—such as buffer analysis, network analysis, spatial regression, and machine learning models—to tackle multifaceted geographic challenges. …”
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Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent. by Alejandra de-la-Rica-Escudero, Eduardo C Garrido-Merchán, María Coronado-Vaca

“…Financial portfolio management investment policies computed quantitatively by modern portfolio theory techniques like the Markowitz model rely on a set of assumptions that are not supported by data in high volatility markets such as the technological sector or cryptocurrencies. …”
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Artificial Intelligence in Medicine: Transforming The Future of Healthcare by Tashfeen Alam Jan, Shumaila Naz

“…Machine learning (ML) and deep learning (DL) technologies have proved invaluable for the analysis of complex datasets, supporting early diagnosis and optimizing treatment protocols. …”
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AI-Driven Accounting and Sensing Applications for Investment Management by Foziljonov Ibrohimjon, Yuldashev Jahongir, Turgunov Jasurbek, Khujamurodov Askarjon, Rozhkova Elena

“…Al-driven accounting and sensing applications have enabled the formulation of multiple investment decision-support models with considerable predictive accuracy, real-time responsiveness, and cost-efficiency benefits. …”
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Developing a Transparent Anaemia Prediction Model Empowered With Explainable Artificial Intelligence by Muhammad Sajid Farooq, Muhammad Hassan Ghulam Muhammad, Oualid Ali, Zahid Zeeshan, Muhammad Saleem, Munir Ahmad, Sagheer Abbas, Muhammad Adnan Khan, Taher M. Ghazal

“…The proposed model utilizes machine learning algorithms such as Support Vector Machine (SVM), Decision Trees, K-Neighbors Classifier, and Gradient Boosting Classifier, enhanced with Explainable AI (XAI) techniques like SHAP and LIME. …”
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Optimizing role assignment for scaling innovations through AI in agricultural frameworks: An effective approach by Sonia Bisht, Ranjana, Swapnila Roy

“…By leveraging advanced algorithms and machine learning techniques, the research aims to streamline the allocation of tasks and responsibilities among various stakeholders, including farmers, agronomists, technicians, and AI systems. …”
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Shipyard Manpower Digital Recruitment: A Data-Driven Approach for Norwegian Stakeholders by Bogdan Florian Socoliuc, Andrei Alexandru Suciu, Mădălina Ecaterina Popescu, Doru Alexandru Plesea, Florin Nicolae

“…Additionally, pre-vetting candidates enhances hiring precision, achieving a CAR of 90% and reducing mismatches. The application of machine learning algorithms provides predictive insights that support real-time adjustments to job postings, optimizing recruitment strategies. …”
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A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade by Attila Kovari

“…Artificial intelligence tools, in particular machine learning, natural language processing and recommender algorithms, facilitate collaborative learning by enabling personalized learning through feedback and group work. …”
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TAE Predict: An Ensemble Methodology for Multivariate Time Series Forecasting of Climate Variables in the Context of Climate Change by Juan Frausto Solís, Erick Estrada-Patiño, Mirna Ponce Flores, Juan Paulo Sánchez-Hernández, Guadalupe Castilla-Valdez, Javier González-Barbosa

“…The ensemble combines Long Short-Term Memory neural networks, Random Forest regression, and Support Vector Machines, optimizing their contributions using heuristic algorithms such as Particle Swarm Optimization. …”
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Federated Learning Based on an Internet of Medical Things Framework for a Secure Brain Tumor Diagnostic System: A Capsule Networks Application by Roman Rodriguez-Aguilar, Jose-Antonio Marmolejo-Saucedo, Utku Köse

“…This technique ensures the secure exchange of sensitive patient and institutional data. It enables machine learning or deep learning algorithms to establish a client–server relationship, whereby specific parameters are securely shared between models while maintaining the integrity of the learning tasks being executed. …”
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Predicting climate-driven shift of the East Mediterranean endemic Cynara cornigera Lindl by Heba Bedair, Heba Bedair, Yehia Hazzazi, Asmaa Abo Hatab, Marwa Waseem A. Halmy, Mohammed A. Dakhil, Mohammed A. Dakhil, Mubaraka S. Alghariani, Mubaraka S. Alghariani, Mari Sumayli, A. El-Shabasy, Mohamed M. El-Khalafy

“…Our analysis involved inclusion of bioclimatic variables, in the SDM modeling process that incorporated five algorithms: generalized linear model (GLM), Random Forest (RF), Boosted Regression Trees (BRT), Support Vector Machines (SVM), and Generalized Additive Model (GAM).Results and discussionThe ensemble model obtained high accuracy and performance model outcomes with a mean AUC of 0.95 and TSS of 0.85 for the overall model. …”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Advanced algorithms, including neural networks, decision trees, and random forests, significantly improved detection rates when integrated with EHRs, enabling real-time surveillance and timely interventions. …”
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Use of ICT to Confront COVID-19 by Yousry Saber El Gamal

“…. , AI techniques, particularly machine learning algorithms, can also be used to correlate the patient’s data parameters with a specific drug’s usage. …”
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Research status and progress on key technologies of intelligent orchard by CUI Hongwei, LU Xiaoxuan, YANG Yaqing, LU Xinyi, MA Hao, JI Jiangtao, JIN Xin, LI Xiuzhen, ZHAO Zimeng, ZENG Ningning

“…Using LiDAR, vision-based navigation, and obstacle avoidance algorithms, machinery can complete tasks safely and efficiently. …”
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Investigating the hydrogen renaissance in the global energy transition with AI integration by Abderrahim Lakhouit

“…Hydrogen is increasingly recognized as a crucial element in the global shift towards a low-carbon economy, with the potential to decarbonize multiple sectors, including industry, transportation, and energy systems. …”
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