Location Design of Electrification Road in Transportation Networks for On-Way Charging by Yue Qiu, Yuchuan Du, Shanchuan Yu, Shengchuan Jiang

“…We develop a modified active set algorithm to solve the MPEC model. Numerical experiments are presented to demonstrate the performance of the model and the solution algorithm and analyze the impact of charging efficiency, battery size, and comfortable range.…”
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Age- and Post-Based Complex Analyses of Heart Rate Variability in Young Male Handball Players for Potential Prevention of Overload-induced Injuries by Zita Petrovszki, Olivér Czimbalmos, Vera Gal, Gabor Korosi, Edit Nagy, Rita Mikulan, Gyongyi Horvath

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Application of Neural Networks to Analyse the Spatial Distribution of Bicycle Traffic Before, During and After the Closure of the Mill Road Bridge in Cambridgeshire, United Kingdom by Shohel Amin

“…The application of wireless sensors and machine learning algorithms can enhance the analysis and prediction ability of traffic distribution and characteristics in the proximity of road closures. …”
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Enhanced Multi-Criteria DNA Sequence Analysis Using Neutrosophic Logic and Deep Learning: An Integrated Approach for Comparison and Classification by Romany M. Farag, Mahmoud Y. Shams, Dalia A. Aldawody, Hazem M. El-Bakry, Huda E. Khalid, Ahmed K. Essa, A. A. Salama

“…Traditionally, traditional methods such as multiple sequence alignment (MSA) algorithms or the NeedlemanWinch algorithm become extremely cumbersome when faced with large or unclear data. …”
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A novel transformer-based approach for cardiovascular disease detection by Nimra Noor, Muhammad Bilal, Saadullah Farooq Abbasi, Omid Pournik, Theodoros N. Arvanitis

“…The proposed study achieved a maximum accuracy, precision, recall, and F1 score of 0.9979, 0.9959, 0.9958, and 0.9959, respectively. The proposed algorithm outperformed all the existing state-of-the-art algorithms for CVD classification.…”
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Deep‐NCA: A deep learning methodology for performing noncompartmental analysis of pharmacokinetic data by Gengbo Liu, Logan Brooks, John Canty, Dan Lu, Jin Y. Jin, James Lu

“…Although the existing NCA algorithms are very well‐established and widely utilized, they suffer from low accuracies in the setting of sparse PK samples. …”
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An integrated framework for satellite-based flood mapping and socioeconomic risk analysis: A case of Thailand by Nutchapon Prasertsoong, Nattapong Puttanapong

“…The study also merges these satellite-based indices with official provincial GDP data from 2018 to 2022 to empirically analyze socioeconomic impacts using four machine learning algorithms. The result obtained from Random Forest (RF) demonstrates the highest predictive power for GDP forecasting (r-squared value of 0.912). …”
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Advancing Smart Zero-Carbon Cities: High-Resolution Wind Energy Forecasting to 36 Hours Ahead by Haytham Elmousalami, Aljawharah A. Alnaser, Felix Kin Peng Hui

“…A multi-horizon prediction approach is proposed, using WSF model outputs as inputs for WPF modeling. …”
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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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Use of artificial intelligence to assess genetic predisposition to develop critical COVID-19 disease: a comparative study of machine learning models by Martín Pérez Salomón, Sanchez Jimenez Flora, Fuentes Cantero Sandra, Jímenez Barragan Marta, Sanchez Mora Catalina, Borreguero Leon Juan M., Teresa Arrobas Velilla, Valido Morales Agustín, Delgado Torralbo Juan A., León Justel Antonio

“…The objective of this study was to optimize predictive models for critical COVID-19 disease. Clinical data, laboratory data and genetic polymorphisms were integrated into AI models to compare the performance of different machine learning algorithms.…”
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Assessing wildfire susceptibility in Iran: Leveraging machine learning for geospatial analysis of climatic and anthropogenic factors by Ehsan Masoudian, Ali Mirzaei, Hossein Bagheri

“…Utilizing advanced remote sensing, geospatial information system (GIS) processing techniques such as cloud computing, and machine learning algorithms, this research analyzed the impact of climatic parameters, topographic features, and human-related factors on wildfire susceptibility assessment and prediction in Iran. …”
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MeDML: Med-Dynamic Meta Learning - A multi-layered representation to identify provider fraud in healthcare by Nitish Kumar, Deepak Chaurasiya, Alok Singh, Siddhartha Asthana, Kushagra Agarwal, Ankur Arora

“…We test the dynamically generated meta embedding using various downstream models and show that it outperforms all baseline algorithms for provider fraud prediction task.…”
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Development of New Radar and Pyroelectric Sensors for Road Safety Increase in Cloud-Based Multi-Agent Control Application by Leslie Robert Adrian, Ansis Avotins, Donato Repole, Olegs Tetervenoks

“…The proposed sensor solutions can detect the road user (vehicle or pedestrian) and determine its movement direction and approximate speed that can be used for dynamic lighting control algorithms, traffic intensity prediction, and increased safety for both driver and pedestrian traffic. …”
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Machine Learning-Based Classification for Crop-Type Mapping Using the Fusion of High-Resolution Satellite Imagery in a Semiarid Area by Aicha Moumni, Abderrahman Lahrouni

“…Three machine learning classifier algorithms, artificial neural network (ANN), support vector machine (SVM), and maximum likelihood (ML), were applied to identify and map crop types in irrigated perimeter. …”
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Source Tracing of Raw Material Components in Wood Vinegar Distillation Process Based on Machine Learning and Aspen Simulation by Siqi Liao, Wanting Sun, Haoran Zheng, Qiyang Xu

“…The experimental results demonstrate that the Random Forest model exhibits superior predictive accuracy to traditional decision tree methods, and an R² of 0.9728 can be achieved for phenol concentration prediction. …”
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Evaluation method of distribution network operation status based on local fuzzy measure in boundary region by Bing Yu, Peng Xie, Zhonglin Ding, Letian Li, Changan Chen, Chunfeng Jing

“…The research results found that the five evaluation indicators of the proposed algorithm were 112, 0, 2, 26, and 5, respectively, all of which were superior to the comparison algorithms. …”
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Discordance between a deep learning model and clinical-grade variant pathogenicity classification in a rare disease cohort by Sek Won Kong, In-Hee Lee, Lauren V. Collen, Michael Field, Arjun K. Manrai, Scott B. Snapper, Kenneth D. Mandl

“…This observation underscores ongoing challenges in clinical genetics, highlighting the need for continued refinement of computational methods in variant pathogenicity prediction.…”
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LoRa Technology Enhanced with a Custom-Designed High-Gain Yagi-Uda Antenna for Data Transmission from Misti Volcano Monitoring to Arequipa City by Flor de Milagro Yesit Arana Medina, Jorge Rendulich

“…In response, this project integrates Internet of Things (IoT) technology, the LoRa (Long Range) network, and an optimized seven-element Yagi-Uda antenna, developed using advanced optimization algorithms to enhance transmission efficiency. The primary objective is to facilitate the reliable collection and transmission of critical sensor data for subsequent analysis by volcanological experts, thereby supporting improved prediction and mitigation of potential volcanic hazards. …”
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An Intelligent System for Management of Medical Equipment Maintenance by Abbas Izadi, Mohamad Amin Bakhshali, Hadi Ghasemifard, Omid Sarrafzadeh

“…The system utilizes machine learning algorithms and data analytics to predict equipment failures, schedule maintenance tasks, and manage spare parts inventory efficiently. …”
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Role of Bioinformatics in Agriculture by M. N. V. Prasad Gajula, Anuj Kumar, E. A. Siddiq, A. K. Polumetla

“…Bioinformatics is the use of computer technology, mathematical algorithms, and statistics with concepts in the life sciences to solve biological problems. …”
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