Estimating forest aboveground carbon sink based on landsat time series and its response to climate change by Kun Yang, Kai Luo, Jialong Zhang, Bo Qiu, Feiping Wang, Qinglin Xiao, Jun Cao, Yunrun He, Jian Yang

“…Fewer studies have used machine learning-based dynamic models to estimate forest carbon sink. …”
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Data on battery health and performance: Analysing Samsung INR21700-50E cells with advanced feature engineering by Sahar Qaadan, Aiman Alshare, Alexander Popp, Myrel Tiemann, Utz Spaeth, Benedikt Schmuelling

“…These features are indispensable for predictive modelling, lifecycle management, and battery performance optimization, addressing key challenges in battery technology. …”
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Automated Design Method Based on Boosting Algorithms for Improving the Radiation Performance of Microstrip Antenna Arrays by Sina Hasibi Taheri, Ali Lalbakhsh, Amirhassan Zareanborji, Slawomir Koziel

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Development of an upper limb muscle strength rehabilitation assessment system using particle swarm optimisation by Chuangan Zhou, Siqi Wang, Meiyi Wu, Wei Lai, Junyu Yao, Xingyue Gou, Hui Ye, Jun Yi, Dong Cao

“…Simultaneously, triaxial kinematic data of the glenohumeral joint were obtained via an MPU6050 inertial measurement unit, processed through quaternion-based orientation estimation. Machine learning models, including Backpropagation Neural Network (BPNN), Support Vector Machines (SVM), and particle swarm optimization algorithms (PSO-BPNN, PSO-SVR), were applied for regression analysis. …”
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SLAM: Sales Lead AMplification Through GenAI and ML for e-Learning Platforms by Ganesan Ramachandran, Tanmay Narang, Vallidevi Krishnamurthy

“…This study investigates sales lead prediction utilizing machine learning techniques. In the domain of sales, the accurate prediction of leads is deemed essential for optimizing resource allocation and maximizing conversion rates. …”
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A survey of decision-making and planning methods for self-driving vehicles by Jun Hu, Jun Hu, Yuefeng Wang, Shuai Cheng, Jinghan Xu, Ningjia Wang, Bingjie Fu, Zuotao Ning, Jingyao Li, Hualin Chen, Chaolu Feng, Yin Zhang

“…For knowledge-driven methods, this paper explores independent decision-making systems, including rule based, state transition based, game-theory based methods and independent planing systems including search based, sampling based, and optimization based methods. For data-driven methods, it provides a detailed analysis of machine learning paradigms such as imitation learning, reinforcement learning, and inverse reinforcement learning. …”
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Hybrid Graph Representation and Learning Framework for High-Level Synthesis Design Space Exploration by Pouya Taghipour, Eric Granger, Yves Blaquiere

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Modelo matemático y algoritmo de solución de un flujo con tiempos dependientes de la secuencia by A. Fiol-Zulueta, José Arbola-Ruíz, Adriano da Silva-Carvalho

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Explainable AI for Chronic Kidney Disease Prediction in Medical IoT: Integrating GANs and Few-Shot Learning by Nermeen Gamal Rezk, Samah Alshathri, Amged Sayed, Ezz El-Din Hemdan

“…Additionally, traditional machine learning models, including support vector machines (SVM), logistic regression (LR), decision trees (DT), random forests (RF), and voting ensemble learning (VEL), are applied for comparison. …”
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Improving the Dynamics of an Electrical Drive Using a Modified Controller Structure Accompanied by Delayed Inputs by Konrad Urbanski, Dariusz Janiszewski

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Precision Enhanced Bioactivity Prediction of Tyrosine Kinase Inhibitors by Integrating Deep Learning and Molecular Fingerprints Towards Cost-Effective and Targeted Cancer Therapy by Fatma Hilal Yagin, Yasin Gormez, Cemil Colak, Abdulmohsen Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…By enabling accurate bioactivity prediction, our model pipeline can effectively reduce experimental burden, optimize compound selection, and support personalized cancer treatment design. …”
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METHODOLOGY OF DETERMINING FORECASTING CONTROLLERS OF DISTRIBUTED GENERATION PLANTS by Yu. N. Bulatov, A. V. Kryukov, N. V. Huan

“…The paper presents a methodology of determining the parameters predictive links AEC and ASC and the results of research on the computer model railway power supply systems (RPSS) including in its membership following the DG plants: turbogenerator mini thermoelectric plant, hydro small power plant, wind power plant on the basis of the machine DC and solar power. …”
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Domain Knowledge-Enhanced Process Mining for Anomaly Detection in Commercial Bank Business Processes by Yanying Li, Zaiwen Ni, Binqing Xiao

“…Additionally, we employed large language models (LLMs) for root cause analysis and process optimization recommendations. …”
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Evaluating Properties and Applications of Innovative Recycled Aggregate Concrete by Kameshwar Sahani, Anish Kunwar, Prajwal Dhakal, Arjun Kunwar, Suresh Kumar Sahani, Binay Kumar Pandey, Digvijay Pandey

“…The review also emphasizes the role of numerical models and machine learning in optimizing RAC mix designs and predicting its behavior, offering valuable insights for sustainable construction practices. …”
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Distribution of Remaining Oil and Enhanced Oil Recovery Strategy for Carboniferous Buried-Hill Reservoirs in Junggar Basin by Qijun Lv, Zhaowen Shi, Linsong Cheng, Chunjing Zan

“…The present study systematically identified the lithology of the study area through microscopic lithological identification combined with logging data, conducted reservoir matrix property research under facies constraints, and established a three-dimensional geological model of lithology and physical properties. To more reasonably study the reservoir development process and establish an optimal development plan, a machine learning model for fracture density was trained using imaging logging interpretation results and conventional logging curve data. …”
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Current Trends and Advances in Extractive Text Summarization: A Comprehensive Review by Maryam Azam, Shah Khalid, Sulaiman Almutairi, Hasan Ali Khattak, Abdallah Namoun, Amjad Ali, Hafiz Syed Muhammad Bilal

“…These techniques include statistical, fuzzy logic, rule, optimization, graph, clustering-based, machine learning, and deep learning. …”
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Exploring the integration of medical and preventive chronic disease health management in the context of big data by Yueyang Wang, Yueyang Wang, Ruigang Deng, Xinyu Geng

“…This study employs a comprehensive literature review method to systematically evaluate the integration of medical and preventive services for chronic disease management in the context of big data, focusing on pre—hospital risk prediction, in—hospital clinical prevention, and post—hospital follow—up optimization. Through synthesizing existing research, we propose a novel framework that includes the development of machine learning models and interoperable health information platforms for real—time data sharing. …”
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Method for prediction magnetic silencing of uncertain energy-saturated extended technical objects in prolate spheroidal coordinate system by B. I. Kuznetsov, A. S. Kutsenko, T. B. Nikitina, I. V. Bovdui, K. V. Chunikhin, V. V. Kolomiets

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System analysis and information processing to solve the problem of detecting breakdowns of computer information storage by N. M. Kodatsky, E. A. Revyakina, A. R. Gazizov

“…It involves conducting experiments with a data set and the Google Colab cloud environment, creating and analyzing a machine learning model, and evaluating the effectiveness and quality of training. …”
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Estimation of Above-Ground Biomass for <italic>Dendrocalamus Giganteus</italic> Utilizing Spaceborne LiDAR GEDI Data by Huanfen Yang, Zhen Qin, Qingtai Shu, Li Xu, Jinge Yu, Shaolong Luo, Zaikun Wu, Cuifen Xia, Zhengdao Yang

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