The Application of Artificial Intelligence in Medical Diagnostics: Implications for Sports Medicine by Michał Bolek, Dominika Musialska, Aleksandra Kędzia, Bartosz Jagieła, Monika Fidyk, Magda Minkiewicz, Maciej Dyda

“…By focusing on ethical considerations and refining AI technologies, the healthcare community can harness AI's full potential while safeguarding patient interests and enhancing outcomes. …”
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Implementation of Machine Vision Methods for Cattle Detection and Activity Monitoring by Roman Bumbálek, Tomáš Zoubek, Jean de Dieu Marcel Ufitikirezi, Sandra Nicole Umurungi, Radim Stehlík, Zbyněk Havelka, Radim Kuneš, Petr Bartoš

“…The goal of this research was to implement machine vision algorithms in a cattle stable to detect cattle in stalls and determine their activities. …”
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ARIMA-Kriging and GWO-BiLSTM Multi-Model Coupling in Greenhouse Temperature Prediction by Wei Zhou, Shuo Liu, Junxian Guo, Na Liu, Zhenglin Li, Chang Xie

“…This study introduces an ARIMA-Kriging spatiotemporal coupling model, which combines temperature time-series data with sensor spatial coordinates to accurately determine minimum temperatures in greenhouses while reducing hardware costs. Utilizing the high-quality data processed by this model, this study proposes and constructs a novel Grey Wolf Optimizer and Bidirectional Long Short-Term Memory (GWO-BiLSTM) temperature prediction framework, which combines a Grey Wolf Optimizer (GWO)-enhanced algorithm with a Bidirectional Long Short-Term Memory (BiLSTM) network. …”
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Enhancing proximal and remote sensing of soil organic carbon: A local modelling approach guided by spectral and spatial similarities by Qi Sun, Pu Shi

“…Different spectral similarity metrics, and weighted combinations of spectral and geographical similarity matrices were tested to optimize the selection of local training samples. As a result, the optimal modelling strategy, with partial least squares regression (PLSR) as the local fitting algorithm, consistently produced superior performances (R2: 0.66 to 0.82) than the conventional global modelling approach (R2: 0.59 to 0.77) for all three data types. …”
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Reinforcement Q-Learning-Based Adaptive Encryption Model for Cyberthreat Mitigation in Wireless Sensor Networks by Sreeja Balachandran Nair Premakumari, Gopikrishnan Sundaram, Marco Rivera, Patrick Wheeler, Ricardo E. Pérez Guzmán

“…A Hybrid Policy Derivation Algorithm is introduced to balance encryption complexity and computational overhead by dynamically switching between these learning models. …”
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Local power flow control by L. M. Chetochnikova, N. I. Smolentsev, N. V. Tomskich, D. A. Gimgina, D. A. Lavrentieva

“…The  considered power management algorithm is a simple implementation of classical load balancing, and at the same time allows for optimal energy distribution within a given error. …”
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A novel lightweight YOLOv8-PSS model for obstacle detection on the path of unmanned agricultural vehicles by Zhijian Chen, Yijun Fang, Jianjun Yin, Shiyu Lv, Farhan Sheikh Muhammad, Lu Liu

“…When compared with other algorithms, such as Faster RCNN, SSD, YOLOv3-tiny, and YOLOv5, the improved model strikes an optimal balance between parameter count, computational efficiency, detection speed, and accuracy, yielding superior results. …”
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Deep learning approach with ConvNeXt-SE-attn model for in vitro oral squamous cell carcinoma and chemotherapy analysis by Abhay Nath, Om Roy, Priyanka Silveri, Sanskruti Patel

“…Our method applies residual connections with Squeeze-and-Excitation blocks along with hybrid attention systems and enhanced activation functions and optimization algorithms to boost gradient movement throughout feature extraction. …”
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Artificial Intelligence Control Methodologies for Shape Memory Alloy Actuators: A Systematic Review and Performance Analysis by Stefano Rodinò, Giuseppe Rota, Matteo Chiodo, Antonio Corigliano, Carmine Maletta

“…Feedforward neural networks outperformed recurrent architectures (+3.1%), while Model Predictive Control (MPC) excelled for SMA actuators (+5.8% accuracy) but underperformed for MSMAs (−7.7%). …”
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Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China by Ningjing Yang, Yuning Wang, Ying Li, Dongying Xiao, Ruirui Cui, Nana Li, Rong Liu, Jing Chai, Xingrong Shen, Debin Wang

“…The procedure-based measures were derived from specific quality-facts of 21 stages/procedures (e.g., lipid lowering medication prescription) using self-designed algorithms. While the encounter-based measures included number or rate of visits for HL, currently-noticed hyperlipidemia (CNHL, or HL noticed during the current consultation), and ever-diagnosed hyperlipidemia (EDHL). …”
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LSTM-Enhanced Deep Reinforcement Learning for Robust Trajectory Tracking Control of Skid-Steer Mobile Robots Under Terra-Mechanical Constraints by Jose Manuel Alcayaga, Oswaldo Anibal Menéndez, Miguel Attilio Torres-Torriti, Juan Pablo Vásconez, Tito Arévalo-Ramirez, Alvaro Javier Prado Romo

“…Four state-of-the-art DRL algorithms, i.e., Proximal Policy Optimization (PPO), Deep Deterministic Policy Gradient (DDPG), Twin Delayed DDPG (TD3), and Soft Actor–Critic (SAC), are selected to evaluate their ability to generate stable and adaptive control policies under varying environmental conditions. …”
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Research Progress on Selective Depolymerization of Waste Plastics to High-Quality Liquid Fuels by Xinze LI, Zhicheng LUO, Rui XIAO

“…Catalytic pyrolysis faces the challenge of rapid catalyst deactivation (resulting in a 30% activity loss after 5 cycles), while microwave systems incur high capital costs. …”
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Automatic Phase Correction of NMR Spectra Using Brute-Force GPU Method by Mario Gazziro, Marcio Luís Munhoz Amorim, Marco Roberto Cavallari, João Paulo Carmo, Alberto Tannus, Oswaldo Hideo Ando Junior, Loren Schwiebert

“…The results demonstrate that our algorithm always find the globally optimal solution while previous CPU-based heuristics were stalled in a poor solution in 6.25% of a 16 sample universe.…”
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Research on fine-grained classification of rare metal granite lithology based on deep learning by ZHAO Hengqian, WANG Pan, LIU Zhiguo, MIAO Qunfeng, LI Zhibin, TANG Guanglong, QI Yunfei, XIE Yu, WANG Mengmeng

“…In the future, the accuracy of fine-grained classification of rare metal granite lithology can be further improved by improving the quantity and quality of rock samples and optimizing the model algorithm.…”
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Development and Validation of Machine Learning Models for Outcome Prediction in Patients with Poor-Grade Aneurysmal Subarachnoid Hemorrhage Following Endovascular Treatment by Du S, Wu Y, Tao J, Shu L, Yan T, Xiao B, Lv S, Ye M, Gong Y, Zhu X, Hu P, Wu M

“…We further use Shapley Additive Explanations (SHAP) methods for the distribution of feature visualization based on the optimal models.Results: A total of 226 eligible patients with poor-grade aSAH undergoing EVT were enrolled, while 89 (39.4%) has a poor 12-month outcome. …”
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Enhanced identification of Morganella spp. using MALDI-TOF mass spectrometry by Mathilde Duque, Cécile Emeraud, Rémy A. Bonnin, Quentin Giai-Gianetto, Laurent Dortet, Alexandre Godmer

“…Methods: We applied Machine Learning (ML) algorithms to a collection of 235 clinicial Morganella spp. strains to develop an optimized identification model. …”
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Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…The RBF neural network model achieved the highest accuracy (94.57 %) on the feature fusion dataset, while Grey Wolf Optimizer (GWO) optimization further improved accuracy to 96.74 %. …”
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Data stewardship and curation practices in AI-based genomics and automated microscopy image analysis for high-throughput screening studies: promoting robust and ethical AI applicat... by Asefa Adimasu Taddese, Assefa Chekole Addis, Bjorn T. Tam

“…The study also examined specific AI considerations, such as algorithmic bias, model explainability, and the application of advanced cryptographic techniques. …”
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Application of Three-Dimensional Hierarchical Density-Based Spatial Clustering of Applications with Noise in Ship Automatic Identification System Trajectory-Cluster Analysis by Shih-Ming Wang, Wen-Rong Yang, Qian-Yi Zhuang, Wei-Hong Lin, Mau-Yi Tian, Te-Jen Su, Jui-Chuan Cheng

“…Using ship coordinates and heading, the experiment normalized and transformed them into three-dimensional spatial features, employing the HDBSCAN algorithm to obtain optimal clustering results. These results provided a more nuanced analysis compared to human visual observation. …”
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Predictive model for determining the indications for automated 3D ultrasound for screening patients at low risk of developing breast tumors by A. E. Garanina, A. V. Kholin

“…The developed algorithms will help optimize screening and referral for additional examinations, which is of practical importance for improving diagnostics and optimizing healthcare resources.…”
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