RP-DETR: end-to-end rice pests detection using a transformer by Jinsheng Wang, Tao Wang, Qin Xu, Lu Gao, Guosong Gu, Liangquan Jia, Chong Yao

“…In precision agriculture, fast and accurate automatic pest identification is essential. To tackle this issue, multiple models utilizing computer vision and deep learning have been applied. …”
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The effects of climate and geomorphology on bankfull conditions in subtropical Australian streams by Ryan Shojinaga, David Hamilton, Michele A. Burford, Daniel J. Sobota

“…Furthermore, one analytical method of bankfull identification, the bench index method, produced similar bankfull stage estimates to the qualitative bankfull identification. …”
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MSCPUnet: A multi-task neural network for plot-level crop classification in complex agricultural areas by Kedi Fang, Shengwei Zhang, Yongting Han, Lin Yang, Meng Luo, Lu Liu, Qian Zhang, Bo Wang

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Atomic orbits in molecules and materials for improving machine learning force fields by Anton Charkin-Gorbulin, Artem Kokorin, Huziel E Sauceda, Stefan Chmiela, Claudio Quarti, David Beljonne, Alexandre Tkatchenko, Igor Poltavsky

“…Overall, our approach provides a scalable and efficient solution for modeling complex chemical systems with state-of-the-art MLFFs.…”
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MANAGEMENT OF INNOVATION IN HEALTH CARE AT THE REGIONAL LEVEL by Ye. G. Totskaya, M. A. Sadovoy

“…Conceptual model for management includes structuring (resource, processes, and quality management; application of international standards) and strategic management mechanisms, provides a systematic approach to management, and ensures efficient operation of medical institutions and public access to innovative medical diagnostic technologies. …”
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Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…The QoS modeling task was carried out using MBPerf pre-processed dataset. …”
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Adaptive Gradient-Based Iterative Algorithm for Multivariable Controlled Autoregressive Moving Average Systems Using the Data Filtering Technique by Jian Pan, Hao Ma, Xiao Jiang, Wenfang Ding, Feng Ding

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Current application of artificial intelligence in laparoscopic cholecystectomy by S.M. Chooklin, S.S. Chuklin

“…Future research on the use of CV in laparoscopic cholecystectomy should focus on application in more scenarios, such as surgeon skill assessment and the development of more efficient models.…”
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NeSyDPP-4: discovering DPP-4 inhibitors for diabetes treatment with a neuro-symbolic AI approach by Delower Hossain, Delower Hossain, Ehsan Saghapour, Ehsan Saghapour, Jake Y. Chen, Jake Y. Chen, Jake Y. Chen

“…These challenges highlight the urgent need for efficient in-silico approaches to facilitate the discovery and optimization of safer and more effective DPP-4 inhibitors.MethodologyQuantitative Structure-Activity Relationship (QSAR) modeling is a widely used computational approach for evaluating the properties of chemical substances. …”
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Safety helmet detection methods in heavy machinery factory by Liu Baoju, Wei Xiangqian, Chen Qingshan, Liu Jiaqi, Chen Ye, Yu Peng, Lei shi, Hu Yongfeng

“…In light of this, this paper presents an improved model based on YOLOv10 to achieve safety helmet identification. …”
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EF-net: Accurate edge segmentation for segmenting COVID-19 lung infections from CT images by Wenjin Zhong, Hanwen Zhang

“…EDA efficiently extracts structural and textural features from low-level features, enabling the precise identification of lesion boundaries. …”
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Augmented Reality for Assistance of Total Knee Replacement by Castillo Daniel, Olga Ramos

“…With the marker identification, it was possible to compute its position and orientation for locating the virtual models, obtaining a monitoring system for giving accurate information about the procedure. …”
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The effect of room air cleaners on infection control in day care centres by Ville A. Vartiainen, Johanna Hela, Anni Luoto, Petra Nikuri, Enni Sanmark, Aimo Taipale, Inga Ehder-Gahm, Natalia Lastovets, Piia Sormunen, Ilpo Kulmala, Arto Säämänen

“…The clinical results support the findings suggested by the theoretical model. Implications and impacts: – Air cleaning seems to be an effective way to reduce infection risk in day cares – Identification of infection risk hotspot will help in desgining the preventive methods – Portable air cleaners offer an affordable and versatile solution also in buildings where existing ventilation is insufficient for infection risk management”…”
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GNNSeq: A Sequence-Based Graph Neural Network for Predicting Protein–Ligand Binding Affinity by Somanath Dandibhotla, Madhav Samudrala, Arjun Kaneriya, Sivanesan Dakshanamurthy

“…The GNNSeq unique kernel-based context switching scheme optimizes model efficiency and runtime, dynamically adjusts feature weighting between sequence and basic structural information, and improves predictive accuracy and model generalization. …”
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An Improved Diagnosis Approach for Short-Circuit Fault Diagnosis in MPC-Based Current Source Inverter System by Jonggrist Jongudomkarn, Pirat Khunkitti, Apirat Siritaratiwat

“…This is because traditional methods rely heavily on detecting changes in the measured current amplitude, which become increasingly subtle and difficult to distinguish as the current decreases, making fault identification unreliable. This approach provides a reliable and efficient solution for enhancing the safety and performance of CSI systems, particularly in applications where precise fault detection is crucial.…”
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A Deep Learning for Optimization and Visualization of Expressway Toll Lane Management by Pattarapon Klaykul, Wilaiporn Lee, Kanabadee Srisomboon, Luepol Pipanmekaporn, Akara Prayote

“…This paper proposes a novel framework combining deep learning and multi-objective optimization to improve toll plaza efficiency. A Gated Recurrent Unit (GRU) model with Optuna hyperparameter tuning predicts average queue lengths for various ETC lane proportions. …”
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Rapid Recognition of Geoherbalism and Authenticity of a Chinese Herb by Data Fusion of Near-Infrared Spectroscopy (NIR) and Mid-Infrared (MIR) Spectroscopy Combined with Chemometri... by Haiyan Fu, Qiong Shi, Liuna Wei, Lu Xu, Xiaoming Guo, Ou Hu, Wei Lan, Shunping Xie, Tianming Yang

“…Furthermore, the PLSDA model based on the data fusion of NIR and IR was more accurate and efficient. …”
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Implications of machine learning techniques for prediction of motor health disorders in Saudi Arabia by Ehab M. Almetwally, I. Elbatal, Mohammed Elgarhy, Amr R. Kamel

“…This system aims to detect and forecast motor impairment disorders early on using AI model approaches. This system is an efficient tool that properly detects and diagnoses a variety of motor impairment problems using ML algorithms. …”
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Artificial Intelligence Precision Recognition and Auxiliary Diagnosis of Dental X-ray Panoramic Images Based on Deep Learning by Liu Riming, Gao Zhenshan

“…Conclusion: The deep learning-based automatic diagnostic system for dental X-ray panoramic images, especially the Unet++ model, provides high-precision predictive results in dental caries segmentation and wisdom tooth type identification, significantly improving diagnostic efficiency and accuracy.…”
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Distributed trust management scheme based on blockchain in Internet of vehicles by Haibo ZHANG, Yukun CAO, Kaijian LIU, Ruyan WANG

“…Aiming at the security problems caused by the low efficiency and accuracy of malicious vehicle identification in Internet of vehicles, a distributed trust management scheme based on blockchain in Internet of vehicles was proposed.A false information identification strategy was designed by aggregating the scoring information of vehicles, combined with Bayesian inference model.A reputation value updating algorithm was designed by combining the historical interaction information of vehicles and traffic information, malicious vehicles were identified by the reputation threshold.A blockchain was constructed roadside units to realize the distributed storage of traffic data and vehicle reputation values.The traditional proof of work consensus mechanism was improved to dynamically change the difficulty of miner node generating a block through the event level and the number of vehicles involved in scoring, and the waiting mechanism was used to temporarily stop the nodes that had recently blocked from participating in the election process of miner nodes, thus reducing the resource consumption caused by repeated calculations.The simulation results show that the proposed scheme can effectively identify false information, resist the deceptive behavior of malicious vehicles, improve the identification efficiency of malicious vehicles, reduce resource consumption, and is effective and feasible in distributed trust management for Internet of vehicles.…”
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