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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Automated Alerts Systems for Pediatric Sepsis Patients: A Systematic Review by Mahmasoni Masdar, Ariani Arista Putri Pertiwi, Tiara Royani, Nana Caterina Sandi, Muhammad Ulin Nuha, Fransiska Regina Cealy, Alessandra Hernanda Soselisa, Suprihatiningsih Suprihatiningsih, Desi Dwi Siwi Atika Dewi

“…Limitations include language restrictions and the inability to assess each tool's effectiveness or identify the optimal sepsis detection algorithm, underscoring the need for further research, including a meta-analysis.…”
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Experimental Study on the Unsteady Characteristics and the Impact Performance of a High-Pressure Submerged Cavitation Jet by Yongfei Yang, Wei Li, Weidong Shi, Ling Zhou, Wenquan Zhang

“…The impact load of the cavitation jet is mainly affected by the stand-off distance of the nozzle from the impinged target, while the nozzle outlet geometry also has an effect on the impact performance. Optimizing the stand-off distance and the outlet geometry of the nozzles is found to be a good way to improve the performance of the cavitation jet.…”
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Association of MTHFR Polymorphisms with H-Type Hypertension: A Systemic Review and Network Meta-Analysis of Diagnostic Test Accuracy by Yixuan Kong, Jinghui Zheng, Lijuan Li, Liying Lu, Jie Wang

“…A network meta-analysis of diagnostic test and Thakkinstian’s algorithm were used to select the most appropriate genetic model, along with false-positive report probability (FPRP) for noteworthy associations. …”
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Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME by Md. Manowarul Islam, Habibur Rahman Rifat, Md. Shamim Bin Shahid, Arnisha Akhter, Md Ashraf Uddin, Khandaker Mohammad Mohi Uddin

“…To tackle the challenge of designing an improved diabetes classification algorithm that is more accurate, random oversampling and hyper‐tuning parameter techniques have been used in this study. …”
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Energy-Saving Techniques in the Next Generation of Mobile Communication Networks by Viroslava Kapustynska

“…In modern research, dynamic network scaling algorithms are more often presented, and location management investigation has been identified as a solution that can help improve energy-saving techniques and keep the quality of service at the optimal level.…”
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Research on rock burst prediction based on an integrated model by Junming Zhang, Qiyuan Xia, Hai Wu, Sailei Wei, Zhen Hu, Bing Du, Yuejing Yang, Huaixing Xiong

“…Additionally, the sparrow search algorithm (SSA) is employed to optimize hyperparameters, further improving the model’s performance. …”
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An SVDD-based post-processing approach for vibration risk assessment of the hydro-turbine-generator in a large hydropower station by Jinliang Zhang, Fengwei Yang, Chao Liang, Yuansheng Zhang, Yongchang Li

“…Then, the boundary extension operation with detailed theoretical deduction is performed and the extended boundary is further optimized inspired by path planning problem. The advantage of proposed approach is that it can improve the data fitting performance for single dimension (i.e. vibration amplitude) without leading to complex boundary which cannot be used for vibration risk assessment. …”
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Enhancing remote patient monitoring with AI-driven IoMT and cloud computing technologies by Vijay Kumar Damera, Ramesh Cheripelli, Narsaiah Putta, G. Sirisha, Deepthi Kalavala

“…The proposed TL-SAM framework effectively extracts spatial and spectral features from patient health data, optimizing classification accuracy. Furthermore, the model employs an Improved Wild Horse Optimization with Levy Flight Algorithm (IWHOLFA) for hyperparameter tuning, enhancing its predictive performance. …”
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Research on Self-Diagnosis and Self-Healing Technologies for Intelligent Fiber Optic Sensing Networks by Ruiqi Zhang, Liang Fan, Dongzhu Lu

“…Unlike traditional self-diagnosis techniques that rely on an optical time domain reflectometer, the proposed self-diagnosis algorithm utilizes data structure analysis, significantly reducing dependence on costly equipment and improving self-diagnosis efficiency. …”
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High-robustness integrated adversarial training method for fingerprint-based indoor localization systems by ZHANG Xuejun, LI Mei, CHEN Hui, WANG Guohua

“…In EDEAD, the data distillation technique was employed to improve the quality of the augmented data and the early stopping algorithm was used to save training costs. …”
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Economic Dispatch Analysis of Risk Prevention and Control Based on Game Theory Equilibrium by Qixiang WANG, Zhentao HAN, Yi LIANG

“…In order to solve these problems, this paper first proposes an economic dispatch mathematical model for risk prevention and control of the power system considering green power generation and consumption and then puts forward a game theory equilibrium solution algorithm based on the optimal response method. Through case analysis, the game theory equilibrium situation of the economic dispatch problem under the generation and consumption of renewable energy is evaluated, and relevant suggestions are put forward for investment planning on the power generation side of the power system.…”
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TECHNOLOGICAL ADVANCES IN ELECTROPLATING: ARTIFICIAL INTELLIGENCE TO PREDICT ZINC COATING THICKNESS ON SAE 1008 LOW CARBON STEELS by Luciano M. L. de Oliveira, Fabiana L. da Silva, Paulo R. Janissek, Juliano C. Toniolo

“…This ultimately reduces costs and improves product quality.…”
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The Adversarial Robust and Generalizable Stereo Matching for Infrared Binocular Based on Deep Learning by Bowen Liu, Jiawei Ji, Cancan Tao, Jujiu Li, Yingxun Wang

“…To compute the matching cost volume, we apply the multi-scale census transform to the input stereo images. …”
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Automating attendance management in human resources: A design science approach using computer vision and facial recognition by Bao-Thien Nguyen-Tat, Minh-Quoc Bui, Vuong M. Ngo

“…Haar Cascade is a cost-effective and user-friendly machine learning-based algorithm for detecting objects in images and videos. …”
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Problems and perspectives of family doctors training on the undergraduate stage by Yu. M. Kolesnik, V. D. Syvolap, N. S. Mikhaylovskaya, T.O. Kulinich

“…Under healthcare reform activities of all medical schools and post-graduate education institutions are directed to improvement of the effectiveness of high-qualified family doctors training. …”
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Finding a suitable chest x-ray image size for the process of Machine learning to build a model for predicting Pneumonia by Kriengsak Yothapakdee, Yosawaj Pugtao, Sarawoot Charoenkhun, Tanunchai Boonnuk, Kreangsak Tamee

“…This study focused on algorithm performance and training/testing time, evaluating the most suitable chest X-ray image size for machine learning models to predict pneumonia infection. …”
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SORA: Energy-Efficient Resource Allocation in Open Radio Access Network With Online Learning by Aerman Tuerxun, Akihiro Nakao

“…By integrating variational inference with Thompson Sampling, the framework efficiently balances exploration and exploitation, allowing dynamic adjustment of MCS and PRB allocations in response to changing network states. The proposed algorithm achieves sub-linear regret, ensuring convergence toward an optimal policy over time while maintaining robust adaptability. …”
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Integrated Systemic Modeling of Production Scheduling, Maintenance, and Quality Control in Closed-Loop Supply Chains by Javad Rahim, Ali Morovati Sharifabadi, Davood Andalib Ardakani

“…The Strategic Choice Approach (SCA) was employed to structure complex decision-making processes, leveraging the expertise of industry professionals to identify key uncertainties and variables. A Genetic Algorithm (GA) was utilized to optimize decision variables, including sample size, sampling intervals, control limits, and maintenance schedules, ensuring robust solutions under real-world constraints. …”
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Cerebral gray matter volume identifies healthy older drivers with a critical decline in driving safety performance using actual vehicles on a closed-circuit course by Handityo Aulia Putra, Kaechang Park, Kaechang Park, Fumio Yamashita

“…Feature selection and classification were performed using the Random Forest machine learning algorithm, optimized to identify the most predictive GM regions.ResultsOut of 114 GM regions, eleven were selected as optimal predictors: left angular gyrus, frontal operculum, occipital fusiform gyrus, parietal operculum, postcentral gyrus, planum polare, superior temporal gyrus, and right hippocampus, orbital part of the inferior frontal gyrus, posterior cingulate gyrus, and posterior orbital gyrus. …”
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