Healthcare Futures: Opportunities, Challenges and Risks in a Blockchain-Driven Environment by Robert Goldberg, Peter J. Pitts, Jennifer Hinkel

“…By using structured notes and algorithm-driven health indices, market participants can dynamically hedge against fluctuations in healthcare costs while aligning incentives across the healthcare value chain. …”
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Cost-Efficient Fall Risk Assessment With Attention Augmented Vision Machine Learning on Sit-to-Stand Test Videos by Chunhua Pan, Boting Qu, Rui Miao, Xin Wang

“…Median-average filtering is used to reduce noise caused by video shaking and pose estimation inaccuracies, while a new Dynamic Time Warping (DTW)-based matching algorithm is designed to handle interference from irrelevant individuals appearing in the video. …”
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A novel fault diagnosis method for gearbox based on RVMD and TELM with composite chaotic grey wolf optimizer by Xuebin Huang, Anfeng Xu, Hongbing Liu, Bingcheng Ye

“…A novel grey wolf optimization algorithm, named composite chaotic grey wolf optimizer (CCGWO), is used to optimize the kernel parameter of TELM. …”
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Transmission Line Icing Prediction Based on Physically Guided Fast-Slow Transformer by Feng Wang, Ziming Ma

“…Finally, the sample mixing enhancement algorithm is used to reduce the overfitting problem and improve the generalization performance of the prediction model. …”
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Advanced thermal management in radiology equipment: Numerical and semi-analytical analysis of flat heat pipes by Maryam Johari, Hossein Ali Hoshyar, Davood Domiri Ganji

“…Advanced techniques—specifically the Least Squares Method (LSM) and the fourth-order Runge-Kutta-Fehlberg (RKF) algorithm, are employed to conduct a comprehensive analytical investigation of heat pipe performance. …”
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Computability of the Zero-Error Capacity of Noisy Channels by Holger Boche, Christian Deppe

“…We prove that key semi-decidability questions are equivalent for all three capacities, thus unifying these problems into a common algorithmic framework. While the computability status of the Shannon capacity of graphs remains unresolved, our equivalence result clarifies what makes this problem so challenging and identifies the logical barriers that must be overcome to resolve it. …”
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Lightweight LDA-UNet for accurate and interpretable visualization of retinopathy of prematurity by Honghao Lu, Madhavi Devaraj

“…Our model significantly reduces parameters (by 85.4% compared to standard UNet) while alleviating the lack of spatial information loss during the encoding stage. …”
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Bulk Heterojunction Organic Solar Cell Area-Dependent Parameter Fluctuation by A. J. Trindade, L. Pereira

“…Device figures of merit were extracted from the equivalent circuit using a genetic-based algorithm, and their relationship with the active area was compared. …”
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AsymGroup: Asymmetric Grouping and Communication Optimization for 2D Tensor Parallelism in LLM Inference by Ki Tae Kim, Seok-Ju Im, Eui-Young Chung

“…In addition, we introduce a formal communication cost model to accurately quantify bottlenecks and a group optimization algorithm to systematically determine efficient group configurations. …”
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Adaptive Large Neighborhood Search Metaheuristic for the Capacitated Vehicle Routing Problem with Parcel Lockers by Amira Saker, Amr Eltawil, Islam Ali

“…The problem is resolved by ALNS algorithm, which outperformed the MIP model.…”
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Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components by Anna Konovalenko, Lars Magnus Hvattum

“…Our goal is to develop an application that can make real-time decisions to maximize total performance while adapting to the dynamic nature of incoming orders. …”
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Hybrid Harris hawks-optimized random forest model for detecting multi-element geochemical anomalies related to mineralization by Hamid Sabbaghi, Nader Fathianpour

“…Performance of the AML algorithms are extremely dependent to values of their hyperparameters. …”
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On-Site Safety Inspections Through Marker-Less Augmented Reality and Blockchain Notarization of BIM-Based Processes by Alessandra Corneli, Alessandro Carbonari, Francesco Spegni, Tommaso Pieroni, Berardo Naticchia

“…On-site outdoor localization is ensured by a GPS-RTK system, while for indoor spaces, an artificial intelligence algorithm that recognizes features is used. …”
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Improving Accuracy and Calibration of Deep Image Classifiers With Agreement-Driven Dynamic Ensemble by Pedro Conde, Rui L. Lopes, Cristiano Premebida

“…The merits of the proposed algorithm are shown through a series of representative experiments, leveraging two different neural network architectures and three different datasets against multiple state-of-the-art baselines.…”
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Folded Context Condensation in Path Integral Formalism for Infinite Context Transformers by Won-Gi Paeng, Daesuk Kwon, Kyungwon Jeong, Honggyo Suh

“…In this work, we present a generalized formulation of the Transformer algorithm by reinterpreting its core mechanisms within the framework of Path Integral formalism. …”
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Memory dependent modulation of hippocampal theta power through frontoparietal phase synchronous brain stimulation by Nina M. Ehrhardt, Jevri Hanna, Dayana Hayek, Robert Fleischmann, Ulrike Grittner, Axel Thielscher, Agnes Flöel, Daria Antonenko

“…To quantify hippocampal activity and connectivity, we performed subcortical source analyses of electroencephalography (EEG) data using a hierarchical subspace pursuit algorithm. While memory did not differ between tACS and sham conditions, we observed tACS-induced increases in hippocampal theta power and its connectivity in individuals with superior memory performance. …”
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Development of an enhanced base unit generation framework for predicting demand in free‐floating micro‐mobility by Dohyun Lee, Kyoungok Kim

“…Therefore, a novel base areal unit generation algorithm is proposed that employs a clustering approach to enhance the prediction accuracy in free‐floating micro‐mobility system demand. …”
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Analysis of the Effectiveness of Traditional and Ensemble Machine Learning Models for Mushroom Classification by Neny Sulistianingsih, Galih Hendro Martono

“…Overall, this study highlights the importance of algorithm selection tailored to data characteristics and supports the use of ensemble learning to boost predictive reliability. …”
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Machine Learning Innovations for Improving Mineral Recovery and Processing: A Comprehensive Review* by Korie, Josephmartin Izuchukwu*, Chudi-Ajabor, Ogochukwu Gabriela, Ezeonyema, Chukwudalu Chukwuekezie, Oshim, Francisca Ogechukwu

“…Among these applications, predictive modeling for process optimization and enhanced ore sorting and classification stand out, with ANN being the most frequently employed algorithm. While challenges persist, such as limited data availability, non-normally distributed and non-linear data, and varying data dimensions and rates, the advantages of employing ML algorithms are undeniable. …”
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Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

“…Specifically, the TD3 algorithm, featuring a dual-critic structure, is employed to enhance control precision within predefined state and action spaces. …”
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