Deep Reinforcement Learning for Automated Insulin Delivery Systems: Algorithms, Applications, and Prospects by Xia Yu, Zi Yang, Xiaoyu Sun, Hao Liu, Hongru Li, Jingyi Lu, Jian Zhou, Ali Cinar

“…Advances in continuous glucose monitoring (CGM) technologies and wearable devices are enabling the enhancement of automated insulin delivery systems (AIDs) towards fully automated closed-loop systems, aiming to achieve secure, personalized, and optimal blood glucose concentration (BGC) management for individuals with diabetes. While model predictive control provides a flexible framework for developing AIDs control algorithms, models that capture inter- and intra-patient variability and perturbation uncertainty are needed for accurate and effective regulation of BGC. …”
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Algorithm for the Management of Patients with Ischemic Heart Disease and Cardio-Renal-Metabolic Syndrome by Yevhen Yu. Marushko, Georgii B. Mankovskyi

“…To assess the prognostic impact of using a new algorithm for managing patients with CAD and CRMS over a 5-year follow-up period. …”
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PDAA: An End-to-End Polygon Dynamic Adjustment Algorithm for Building Footprint Extraction by Longjie Luo, Jiangchen Cai, Bin Feng, Liufeng Tao

“…This paper proposes an end-to-end polygon dynamic adjustment algorithm (PDAA) to improve the accuracy and geometric consistency of building contour extraction by dynamically generating and optimizing polygon vertices. …”
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Exploring unsupervised feature extraction algorithms: tackling high dimensionality in small datasets by Hongqi Niu, Gabrielle B. McCallum, Anne B. Chang, Khalid Khan, Sami Azam

“…In this regard, feature extraction algorithms are important in addressing these challenges by reducing dimensionality while retaining essential information. …”
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Network Efficient Hierarchical Authentication Algorithm for Secure Communication in IoT and IoE by Abhiram Sharma, R. Suganya, P. B. Krishna, Rudra Raj, Raja Kumar Murugesan

“…Adding to that is the advanced block reordering techniques and circular right shift operations further enhance security while minimizing computational overhead, making the proposed algorithm ideal for resource-constrained IoT environments. …”
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Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis by Farhan Hussain, M. Hasanuzzaman, Nasrudin Abd Rahim

“…Seasonal trend analyses indicate peak electricity demand during summer, while autumn exhibits greatest vulnerability in prediction accuracy. …”
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Optimizing firefighting resilience in airports through genetic algorithms and decision-making frameworks by Yulong Zhu, Wei Tian, Xuhong Jia, Quanyi Liu

“…We propose a modified composite weight calculation framework that innovatively introduces genetic algorithm (GA) in the weight combination process to simplify the model into a constrained minimization problem from a mathematical perspective, thus making the ranking results reflect ordinal and intensity information. …”
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Performance Evaluation of Some Selected Classification Algorithms in a Facial Recognition System by Michael Olumuyiwa Adio, Ogunmakinde Jimoh Ogunwuyi, Mayowa Oyedepo Oyediran, Adebimpe Omolayo Esan, Olufikayo Adepoju Adedapo

“…The third stage is feature extraction; Discrete Cosine Transform (DCT) is adopted for this purpose. While the fourth stage is face recognition classification, Receiver Operating Characteristics (ROC) was used to test the performance of each the three algorithms. …”
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Research on a traffic flow statistical algorithm based on YBOVDT and SAM2 by Yuanyuan Wang, Zheng Ding, Jiange Liu, Kexiao Wu, Md Sharid Kayes Dipu, Tingmei Ma, Yonghao Ma, Haiyan Zhang

“…A comparative analysis with YOLO-v3,YOLO-v5, YOLO-v6,and YOLO-v8 algorithms indicated that, while balancing spatial and temporal resource consumption and accuracy, the proposed algorithm offers higher recognition accuracy and environmental adaptability. …”
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YOLO-DKM: A Flame and Spark Detection Algorithm Based on Deep Learning by Linpo Shang, Xufei Hu, Zijian Huang, Qiang Zhang, Zhiyu Zhang, Xin Li, Yanzuo Chang

“…Moreover, for some fire warning factors, the current focus is mainly on detecting smoke, while existing detection algorithms are still relatively lacking in detecting other warning factors. …”
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Hybrid Reinforcement Learning-Based Collision Avoidance Algorithm for Autonomous Vehicle Clusters by Chubing Guo, Jianshe Wu, Panzheng Luo, Zhigang Wang, Kai Zhang, Ziyi Yang, Zengfa Dou, Kan Song

“…The experimental results show that the proposed algorithm in this study showed a high success rate of collision avoidance and a low average reaction time under most collision avoidance times.…”
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IFDA: Intermittent Fault Diagnosis Algorithm for Augmented Cubes Under the PMC Model by Chongwen Yuan, Chenghao Zou, Jiong Wu, Hao Feng, Jie Li

“…Many previous studies have paid close attention to the permanent faults of systems while ignoring the rise of intermittent faults. Meanwhile, there is a lack of a rapid diagnostic algorithm tailored for intermittent faults. …”
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Predicting student self-efficacy in Muslim societies using machine learning algorithms by Mohammed Ba-Aoum, Mohammed Ba-Aoum, Mohammed Alrezq, Jyotishka Datta, Konstantinos P. Triantis

“…Four machine learning algorithms-Decision Tree, Random Forest, XGBoost, and Neural Network-were employed to predict self-efficacy using two demographic variables and 10 socio-emotional, cognitive, and regulatory factors. …”
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Comparison of Energy Consumption Optimization in Sugar Factory Using Meta-Heuristic Algorithms by M. Boroun, M. Ghahderijani, A. A. Naseri, B. Beheshti

“…The total energy input reduction with the genetic algorithm was 17.05%, while the imperialist competitive algorithm achieved a higher reduction of 26.40%. …”
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Application of Multi-Strategy Controlled Rime Algorithm in Path Planning for Delivery Robots by Haokai Lv, Qian Qian, Jiawen Pan, Miao Song, Yong Feng, Yingna Li

“…To address these limitations, this study proposes the Multi-Strategy Controlled Rime Algorithm (MSRIME), whose innovation primarily manifests in three aspects: first, it constructs a multi-strategy collaborative optimization framework, utilizing an infinite folding Fuch chaotic map for intelligent population initialization to significantly enhance the diversity of solutions; second, it designs a cooperative mechanism between a controlled elite strategy and an adaptive search strategy that, through a dynamic control factor, autonomously adjusts the strategy activation probability and adaptation rate, expanding the search space while ensuring algorithmic convergence efficiency; and finally, it introduces a cosine annealing strategy to improve the step size adjustment mechanism, reducing parameter sensitivity and effectively preventing path distortions caused by abrupt step size changes. …”
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Design and Application of Algorithm Intensive Environment for CMA Big Data and Cloud Platform by Huo Qing, He Wenchun, He Lin, Gao Feng, Chen Shiwang, Xu Yongjun

“…The algorithm library facilitates the standardization, unified management and sharing of algorithms. …”
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Optimal mixture design for organic Rankine cycle using machine learning algorithm by Valerio Mariani, Saverio Ottaviano, Davide Scampamorte, Andrea De Pascale, Giulio Cazzoli, Lisa Branchini, Gian Marco Bianchi

“…Importantly, the targets and their respective weights within the objective function can be adjusted to meet the specific requirements of the application under analysis, making this approach adaptable to diverse research and industrial objectives. The algorithm is applied to a case study to demonstrate its ability to define a low-GWP blend that can replace HFC-134a in a micro-scale ORC with recuperator, while maintaining and potentially enhancing performance. …”
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Individual behavior tracking of heifers by using object detection algorithm YOLOv4 by Sarah Jahn, Gabriel Schmidt, Lisa Bachmann, Robert Kammerer, Helen Louton, Anne K. Schütz, Timo Homeier-Bachmann

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Classification of Survivors and Non-survivors of the Latest Epidemic Using Association Rules Algorithm by Nasrin Talkhi, Nooshin Akbari sharak, Zahra Pasdar, Maryam Salari, Seyed Masoud Sadati, Mohammad Taghi Shakeri

“…The most common symptom seen in men was respiratory distress, while the most common symptom in women was hypertension. …”
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Comparative analysis of machine learning algorithms for predicting depression among individuals with diabetes by Hind Bourkhime, Noura Qarmiche, Soumaya Benmaamar, Nada Lazar, Mohammed Omari, Mohamed Berraho, Nabil Tachfouti, Samira El Fakir, Hanan El Ouahabi, Nada Otmani

“…This research study presents a comprehensive comparative analysis of eight distinct machine learning (ML) algorithms to predict depression among individuals with diabetes. …”
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