ecochange: An R‐package to derive ecosystem change indicators from freely available earth observation products by Wilson Lara, Maria C. Londoño, Ivan Gonzalez, Victor H. Gutierrez‐Velez

“…Abstract Spatial resources accessible for the derivation of biodiversity indicators of the class ecosystem structure are sparse and disparate, and their integration into computer algorithms for biodiversity monitoring remains problematic. …”
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Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis by Leonel J. R. Nunes, Sandra Silva

“…Techniques such as linear programming, genetic algorithms, and tabu search are contextualized within these models. …”
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Task Scheduling in Cloud Environment–Techniques, Applications, and Tools: A Systematic Literature Review by Olanrewaju L. Abraham, Md Asri Bin Ngadi, Johan Bin Mohamad Sharif, Mohd Kufaisal Mohd Sidik

“…This taxonomy categorizes metaheuristic scheduling techniques based on scheduling algorithms, problem nature, task types, primary scheduling objectives, task-resource mapping, scheduling constraints, and testing environments. …”
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Artificial intelligence in personalized nutrition and food manufacturing: a comprehensive review of methods, applications, and future directions by Kushagra Agrawal, Polat Goktas, Navneet Kumar, Man-Fai Leung

“…Drawing on advances in deep learning, federated learning, and computer vision, the review outlines how AI transforms static, population-level dietary models into dynamic, data-informed frameworks tailored to individual needs. The paper also addresses critical challenges related to algorithmic transparency, data privacy, and equitable access, and proposes actionable pathways for ethical and scalable implementation. …”
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A Hybrid Automata-Driven Machine Learning Framework for Real-Time Energy Optimization in Smart Buildings by Rikame Rajashri, Ranjan Mritunjay Kr., Jadhav Monali, Wankhede Shrushti, Bankar Sakshi, Bachhav Pranjal

“…This study presents a hybrid approach that combines Finite Automata (FA) with sophisticated Machine Learning (ML) algorithms and Artificial Intelligence (AI) to minimize energy consumption in smart buildings. …”
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BLE phase-based ranging: accuracy and capability under strong Wi-Fi interference by Igor Kravets, Nazarii Kotliar, Oleksandr Karpin, Andriy Luchechko

“…Unfortunately, due to limitations of the ISM radio band, other communication technologies such as Z-Wave, ZigBee, and Wi-Fi also use the same frequency bandwidth. This overlap often leads to interference that affects the performance of BLE systems. …”
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Artificial Intelligence in IVF Laboratories: Elevating Outcomes Through Precision and Efficiency by Yaling Hew, Duygu Kutuk, Tuba Duzcu, Yagmur Ergun, Murat Basar

“…However, integrating AI also brings ethical, regulatory, and societal challenges, including concerns about data security, algorithmic bias, and the human–machine interface in clinical decision-making. …”
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Intelligent Motion Compensation for Improving the Tracking Performance of Shipborne Phased Array Radar by J. Mar, K. C. Tsai, Y. T. Wang, M. B. Basnet

“…In addition, the effect of automatic beam pointing error compensation mechanism on the tracking performance of adaptive extended Kalman filter (AEKF) implemented in ship borne phased array radar is also investigated. Simulations find out that the proposed algorithms are stable and accurate.…”
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Progress and perspectives on genomic selection models for crop breeding by Dongfeng Zhang, Feng Yang, Jinlong Li, Zhongqiang Liu, Yanyun Han, Qiusi Zhang, Shouhui Pan, Xiangyu Zhao, Kaiyi Wang

“…Genomic selection, a molecular breeding technique, is playing an increasingly important role in improving the efficiency of artificial selection and genetic gain in modern crop breeding programs. A series of algorithms have been proposed to improve the prediction accuracy of genomic selection. …”
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Deep learning-based natural language processing in human–agent interaction: Applications, advancements and challenges by Nafiz Ahmed, Anik Kumar Saha, Md. Abdullah Al Noman, Jamin Rahman Jim, M.F. Mridha, Md Mohsin Kabir

“…It also presents common pre-processing techniques, datasets and customized evaluation metrics. …”
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Pavement performance model for road maintenance and repair planning: a review of predictive techniques by Krishna Singh Basnet, Jagat Kumar Shrestha, Rabindra Nath Shrestha

“…It explores the implications of these limitations on accuracy and application, while also discussing how advanced predictive analytics can address these challenges. …”
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Improved Correlation of Oil Recovery Factor for Water Driven Reservoirs in the Niger Delta by Ayodele Daniel, Faisal Olasubomi Olanipekun, Sunday Oloruntoba Isehunwa

“…After data cleaning and quality checking, cleaned data was used to train the machine learning model using multiple linear regression algorithms optimized with batch gradient descent method. …”
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Raman Spectra Classification of Pharmaceutical Compounds: A Benchmark of Machine Learning Models with SHAP-Based Explainability by Dimitris Kalatzis, Alkmini Nega, Yiannis Kiouvrekis

“…A diverse array of algorithms—including Support Vector Machines (SVMs), Random Forests, k-Nearest Neighbors (k-NN), Gradient Boosting (XGBoost, LightGBM), and 1D Convolutional Neural Networks (CNNs)—were evaluated on a publicly available dataset. …”
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Vibration control and noise attenuation strategies via acoustic metamaterial in railway transportation: a state-of-the-art review by Cong Wang, Guifeng Wang, Zhenyu Chen, C. W. Lim, Weiqiu Chen

“…Additionally, integrating optimization algorithms and artificial intelligence (AI) enhances AMM design precision and scalability. …”
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Explainable Supervised Learning Models for Aviation Predictions in Australia by Aziida Nanyonga, Hassan Wasswa, Keith Joiner, Ugur Turhan, Graham Wild

“…To address the issue of class imbalance in the Australian Transport Safety Bureau (ATSB) dataset, a Variational Autoencoder (VAE) is also employed for data augmentation. A comparative evaluation of four machine learning algorithms is conducted for a three-class classification task:—Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), and a deep neural network (DNN) comprising five hidden layers. …”
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Smartphone based non invasive real time white blood cell counter leveraging blue light and static magnetic field by Nafi Us Sabbir Sabith, Masud Rabbani, Kazi Shafiul Alam, Sheikh Iqbal Ahamed

“…Abstract White blood cells (WBCs), also known as leukocytes, are one of the most significant parts of the immune system. …”
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Improving Daily Precipitation Estimates by Merging Satellite and Reanalysis Data in Northeast China by Gaohong Yin, Yanling Zhang, Yuxi Cao, Jongmin Park

“…Precipitation plays a key control in the water, energy, and carbon cycles, and it is also an important driving force for land surface modeling. …”
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Recent advances in AI-based toxicity prediction for drug discovery by Hyundo Lee, Jisan Kim, Ji-Woon Kim, Yoonji Lee, Yoonji Lee

“…Ongoing advances in databases, algorithms, and computational power have further expanded AI’s role in pharmaceutical research. …”
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A Review About the Effects of Digital Competences on Professional Recognition; The Mediating Role of Social Media and Structural Social Capital by Javier De la Hoz-Ruiz, Rawad Chaker, Lucía Fernández-Terol, Marta Olmo-Extremera

“…The results indicate that social media proficiency has become a central determinant of social recognition, favoring individuals who possess not only digital fluency but also the ability to strategically develop and mobilize their networks. …”
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A data-driven state identification method for intelligent control of the joint station export system by Guangli Xu, Yifu Wang, Zhihao Zhou, Yifeng Lu, Liangxue Cai

“…Compared with the traditional hydraulic calculation modified (THCM) models and other machine learning algorithms, the PSO-GWO-BP model has significant advantages in prediction accuracy. …”
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