Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…The research methods include data collection and processing, construction and optimization of ML models, and the application of a risk assessment framework. …”
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Modify a dual ridge horn antenna for drone jamming applications by Alaa Hussein Hilal, Ahmed Hameed Reja, Mohammed J. Mohammed

“…This work presents a DRHA developed utilizing CST Studio and optimized by using genetic algorithm optimization (GA) that has been employed to improve parameters that enhance selected frequencies. …”
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High-voltage defibrillator unit with increased energy output from a controlled capacitor storage by E. E. Gorokhov-Miroshnikov, G. V. Slyusarev

“…The model of the proposed high-voltage unit shows the possibility of increasing the energy output from the capacitor bank when forming a pulse of optimal duration with a flat front. In this case, parallel-series restructuring of the battery capacitors is used, the algorithm of which is planned depending on the resistance of the patient's chest, which allows increasing the amount of energy given off by more than 85% of the accumulated energy of the capacitor bank. …”
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A Multi-Mode Switching Energy Management Strategy Based on Travel Habits for Range-Extended Electric Vehicle by Zhenhai Gao, Guoqing Zhang, Hanwu Liu, Cheng Chang, Jingwen Dong, Rongrong He, Yu Cai

“…To achieve the optimal energy allocation for the auxiliary power unit (APU) and battery of a range-extended electric vehicle (REEV), a travel habit-based multi-mode switching energy management strategy (M-MSEMS) has been introduced. …”
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Early feature study of Yunnan pine pinewood nematode disease based on hyperspectral remote sensing of ground objects by Xiao Zhang, Yingqun Gao, Lianjin Fu, Yiran Zhang, Zeyu Li, Qingtai Shu

“…Study identified the spectral ranges 455–677 nm and 1974–2340 nm as optimal diagnostic windows. Using Competitive Adaptive Reweighted Sampling (CARS) and Successive Projections Algorithm (SPA), we identified diagnostic spectral bands: CARS selected 20 moisture-sensitive bands in red-edge (680–760 nm) and SWIR regions, while SPA pinpointed 4 critical bands (758, 1074, 1124, 1663 nm) across red-edge, NIR, and SWIR. …”
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AI-driven modeling for predicting compressive strength of recycled aggregate concrete under thermal conditions for sustainable construction by Morteza Ghodratnama, Amir R. Masoodi, Amir H. Gandomi

“…The ANN models underwent optimization via Random Search Hyper-Parameter Tuning, resulting in high prediction accuracy, with correlation coefficients (R2) surpassing 0.9. …”
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Learning super-resolution and pyramidal convolution residual network for vehicle re-identification by Mengxue Liu, Weidong Min, Qing Han, Hongyue Xiang, Meng Zhu

“…This network employs both content loss and adversarial loss as optimization criteria, ensuring an efficient transformation from a low-resolution image into a super-resolution counterpart, while meticulously preserving intricate high-frequency details. …”
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Large Language Model–Assisted Risk-of-Bias Assessment in Randomized Controlled Trials Using the Revised Risk-of-Bias Tool: Usability Study by Jiajie Huang, Honghao Lai, Weilong Zhao, Danni Xia, Chunyang Bai, Mingyao Sun, Jianing Liu, Jiayi Liu, Bei Pan, Jinhui Tian, Long Ge

“…Furthermore, 6 RCTs (3 from each category) were randomly selected for prompt development and optimization. The remaining 40 trials established the internal validation standard, while Cochrane Reviews judgments served as external validation. …”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…A ratio greater than 1.1 indicates a good probability of lower 3rd molar eruption, while a below 0.8 indicates no eruption. The algorithm development process demonstrated the effectiveness of our hybrid approach in dental health analytics. …”
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Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN by Yousuf Babiker M. Osman, Wei Li

“…Moreover, stochastic gradient descent (SGD) is used to train each layer of SAE to optimize weight parameters, while a strategy of genetic algorithms to identify the number of neurons in each hidden layer is developed. …”
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Configuring Transmission Thresholds in IIoT Alarm Scenarios for Energy-Efficient Event Reporting by David E. Ruiz-Guirola, Onel L. A. Lopez, Samuel Montejo-Sanchez

“…We propose a threshold-based transmission-decision policy based on the sensing quality and the network spatial deployment. We optimize the transmission thresholds using several approaches such as successive convex approximation, block coordinate descent methods, Voronoi diagrams, explainable machine learning, algorithms based on natural selection and social behavior, and Q-learning. …”
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Artificial Intelligence Approaches to Energy Management in HVAC Systems: A Systematic Review by Seyed Abolfazl Aghili, Amin Haji Mohammad Rezaei, Mohammadsoroush Tafazzoli, Mostafa Khanzadi, Morteza Rahbar

“…Nevertheless, the effective implementation of artificial intelligence (AI)-based methods to optimize energy efficiency while ensuring occupant comfort in multifarious settings remains to be fully realized. …”
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Data-driven prediction of rate of penetration (ROP) in drilling operations using advanced machine learning models by Guoli Huang, Sarah Kanaan Hamzah, Pinank Patel, T. Ramachandran, Aman Shankhyan, A. Karthikeyan, Dhirendra Nath Thatoi, Deepak Gupta, S. AbdulAmeer, Mariem Alwan, Zahraa Saad Abdulali, Mahmood Jasem Jawad, Hiba Mushtaq, Mohammad Mahtab Alam, Hojjat Abbasi

“…Abstract Predicting the rate of penetration (ROP) is critical for optimizing drilling performance, yet it remains a complex task due to the interplay of multiple geological and operational parameters. …”
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Enhancement in dynamic range for dual-rotating retarder Mueller matrix polarimetry by Jiongying Lv, Shuan Yao, Nan Zeng, Caizhong Guan, Honghui He

“…In this study, we propose a novel method to generate high dynamic range (HDR) MM images based on a multi-exposure fusion algorithm. By employing an optimal exposure selection strategy for transmission imaging and a multi-exposure weighted averaging strategy for backscattering imaging, the method expands the dynamic range while accurately preserving the polarization information of the samples. …”
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Medical care costs of cancer in the last year of life using national health insurance data in Korea. by Mihai Park, Inmyung Song

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Low resolution remote sensing object detection with fine grained enhancement and swin transformer by Zhijing Xu, Xin Wang, Kan Huang, Ren Chen

“…Finally, we incorporate the Shape-IoU loss function to optimize bounding box regression, significantly improving small target detection accuracy while maintaining computational efficiency. …”
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Multi-Scale Contextual Coding for Human-Machine Vision of Volumetric Medical Images by Jietao Chen, Weijie Chen, Qianjian Xing, Feng Yu

“…Different from the existing 3D convolutional compression algorithms oriented only for human vision, this paper proposes a Multi-scale Contextual Autoencoder (MCAE) architecture that recurrently incorporates anatomical inter-slice context to optimize the compression of the current slice for both human and machine vision. …”
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Leveraging machine learning to evaluate the effect of raw materials on the compressive strength of ultra-high-performance concrete by Mohamed Abdellatief, G. Murali, Saurav Dixit

“…The impact of 12 influential features on CS was evaluated to optimize the performance of the proposed models. Among the algorithms, XGB outperformed the others with an R² of 90.1 % and a lower RMSE of 11.52 MPa, surpassing RF (88.7 %), GB (89.2 %), and GPR (86.1 %). …”
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How Small Can S-boxes Be? by Chenhao Jia, Tingting Cui, Qing Ling, Yan He, Kai Hu, Yu Sun, Meiqin Wang

“…As a contrast, the designer’s original circuit has an area of 23.33 GE, while the optimized result by Lu et al. achieves an area of 17.66 GE. …”
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On the Choice of System Strength Metrics for the Allocation and Sizing of Synchronous Condensers in Power Grids by Shereefdeen Oladapo Sanni, Olatunji Obalowu Mohammed, Suprava Chakraborty, Ayodele Isqeel Abdullateef, Abdulrahaman Okino Otuoze, Olumoroti Ikotun, Ephraim Bonah Agyekum

“…Applying a genetic algorithm (GA) to the Nigerian power grid as a case study, the SCR-based approach identified two critical points of interconnection (PoIs) requiring 68 MVA of SC capacity, while the NRSCR-based method identified four PoIs, requiring a total of 674 MVA. …”
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