Deep learning radiomics based on MRI for differentiating tongue cancer T - staging by Zhaoyi Lu, Bowen Zhu, Hang Ling, Xi Chen

“…ResNet18 and ResNet50 algorithms were employed to build deep learning models (deep learning radiomics (DLR) resnet18 / DLRresnet50), compared with a radiomics model (Rad) based on 17 optimized features. …”
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Parallel Machine Production and Transportation Operations’ Scheduling with Tight Time Windows by Yang Jiang, Tong He, Jie Xiong, Xin Wu, Yao Chen

“…The results show that the use of the system coordination model in this method obviously improves the number of successful transfers and deliveries.…”
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Risk Limiting Based Resilient Operation Method for Power Grid by Xiyue WANG, Hao ZHANG, Chaoyi PENG

“…By deriving three intermediate state models of RLB and their analytical solutions, we present an iterative RLB solution algorithm based on intermediate state models and provide a rigorous proof of its global optimality. …”
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Comparing the Potential of Near- and Mid-Infrared Spectroscopy in Determining the Freshness of Strawberry Powder from Freshly Available and Stored Strawberry by Da Wang, Wenwen Wei, Yanhua Lai, Xiangzheng Yang, Shaojia Li, Lianwen Jia, Di Wu

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Full lifecycle security management scheme for terminal keys under power IoT by Wang Hui, Yuan Jiahui, Shi Zhentong, Fang Mu

“…Compared to conventional terminal key storage and management methods, the scheme of this paper improves key access performance without changing the existing hardware platform.…”
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Vibration Control of Wind Turbine Blade Based on Data Fitting and Pole Placement with Minimum-Order Observer by Tingrui Liu, Lin Chang

“…It not only ensures certain accuracy, but also greatly improves the speed of calculation. The Wilson method, developed on the basis of the blade momentum theory, is adopted to optimize the structural parameters of the blade, with all parameters fitted as general model Sin6 (Sum of Sine) fitting curves. …”
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Three-Dimensional in Vivo Imaging of Green Fluorescent Protein-Expressing T Cells in Mice with Noncontact Fluorescence Molecular Tomography by Anikitos Garofalakis, Giannis Zacharakis, Heiko Meyer, Eleftherios N. Economou, Clio Mamalaki, Joseph Papamatheakis, Dimitris Kioussis, Vasilis Ntziachristos, Jorge Ripoll

“…By measuring multiple projections, large data sets can be obtained, thus improving the accuracy of the inversion models used for quantitative three-dimensional reconstruction of fluorochrome distribution, as well as facilitating a higher spatial resolution. …”
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Rapid Quality Assessment of Polygoni Multiflori Radix Based on Near-Infrared Spectroscopy by Bin Jia, Ziying Mai, Chaoqun Xiang, Qiwen Chen, Min Cheng, Longkai Zhang, Xue Xiao

“…After optimizing the model using CARS, R2C increased by 0.15%, 0.41%, and 0.34%, RMSECV decreased by 0.53%, 0.32%, and 0.24%, R2P increased by 0.21%, 0.63%, and 0.35%, RMSEP decreased by 0.36%, 0.41%, and 0.31%, and RPD increased by 1.1, 0.9, and 0.6, significantly improving the predictive capacity of the model. …”
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Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting by Ubaid Ahmed, Anzar Mahmood, Ahsan Raza Khan, Levin Kuhlmann, Khurram Saleem Alimgeer, Sohail Razzaq, Imran Aziz, Amin Hammad

“…Traditional deep learning (DL) models and decision tree (DT)-based algorithms have been widely employed for this purpose. …”
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Predicting Employee Turnover Using Machine Learning Techniques by Adil Benabou, Fatima Touhami, My Abdelouahed Sabri

“…This study aims to identify the most effective machine learning model for predicting employee attrition, thereby providing organizations with a reliable tool to anticipate turnover and implement proactive retention strategies.Objective: This study aims to address the challenge of employee attrition by applying machine learning techniques to provide predictive insights that can improve retention strategies.Methods: Nine machine learning algorithms are applied to a dataset of 1,470 employee records. …”
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Blockchain based solid waste classification with AI powered tracking and IoT integration by Aliaa M. Alabdali

“…Abstract Smart waste management is vital for reducing environmental impact and improving quality of life in smart cities. This study presents an AI-driven waste classification model that integrates IoT and Blockchain technologies. …”
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Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…The model’s strong performance and interpretability suggest its potential application in clinical decision support systems to improve diagnostic stewardship, reduce unnecessary cultures, and optimize resource use in suspected BSI cases.…”
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Deep deterministic policy gradient-based automatic negotiation framework for shared decision-making by Xin Chen, Ping Lu, Yong Liu, Fei-Ping Hong

“…Fuzzy membership functions are applied to model the uncertainty in patient preferences, enhancing representation and improving multi-issue negotiation outcomes. …”
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Utilising AI technique to identify depression risk among doctoral students by Changhong Teng, Chunmei Yang, Qiushi Liu

“…Based on the data from the 2019 Nature Global Doctoral Student Survey, we first screened 13 highly relevant features from a total of 37 features potentially related to the risk of depression among doctoral students by Random Forest algorithm. Subsequently, we trained the optimal prediction model to predict the doctoral students with depression risk using a Multilayer Perceptron (MLP), achieving an accuracy of 89.09% on the test set. …”
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Adaptive Window Multi-Feature Fusion Point Cloud Semantic Segmentation Network by Lie Zhu

“…The method combines dynamic and fixed window feature extraction mechanisms, using dynamic windows to model global features and fixed windows to enhance local features, effectively improving segmentation accuracy and robustness. …”
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YOLO-MES: An Effective Lightweight Underwater Garbage Detection Scheme for Marine Ecosystems by Chengxu Huang, Wenyuan Zhang, Beitian Zheng, Jiahao Li, Bochen Xie, Ruisi Nan, Zongming Tan, Baohua Tan, Neal N. Xiong

“…However, existing high-precision detection algorithms are challenging to deploy on performance-constrained IoT underwater devices due to their large computational complexity and model size. …”
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Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson’s disease patients by Yandong lian, Yibin Xu, Linlin Hu, Yuguo Wei, Zhaoge Wang

“…Conclusion MRI-based radiomic signatures have the potential to serve as biomarkers for PD-RBD. The random forest model, which integrates radiomic signatures with postural instability, and shows improved performance in identifying PD-RBD. …”
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Medical Device Failure Predictions Through AI-Driven Analysis of Multimodal Maintenance Records by Noorul Husna Abd Rahman, Khairunnisa Hasikin, Nasrul Anuar Abd Razak, Ayman Khallel Al-Ani, D. Jerline Sheebha Anni, Prabu Mohandas

“…Then, four machine learning algorithms and three deep learning networks are evaluated to determine the best predictive model. …”
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SDGTrack: A Multi-Target Tracking Method for Pigs in Multiple Farming Scenarios by Tao Liu, Dengfei Jie, Junwei Zhuang, Dehui Zhang, Jincheng He

“…This method improves tracking performance across various farming environments by enhancing the model’s adaptability to different domains and integrating an optimized tracking strategy, significantly increasing the generalization of group pig tracking technology across different scenarios. …”
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CPT-DF: Congestion Prediction on Toll-Gates Using Deep Learning and Fuzzy Evaluation for Freeway Network in China by Tongtong Shi, Ping Wang, Xudong Qi, Jiacheng Yang, Rui He, Jingwen Yang, Yu Han

“…The comparative tests show the proposed CPT-DF (congestion prediction on toll-gates using deep learning and fuzzy evaluation) outperforms the current-used other models by 6-15%. The successful prediction could extend to the real-time prediction and early warning of traffic congestion in the toll system to improve the intelligent level of traffic emergency management and guidance on the key road of disasters to some extent.…”
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