Constrained Fuzzy Predictive Control Using Particle Swarm Optimization by Oussama Ait Sahed, Kamel Kara, Mohamed Laid Hadjili

“…A fuzzy predictive controller using particle swarm optimization (PSO) approach is proposed. …”
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Social Network Strategy improves access to HIV testing and harm reduction programs for PWID and their partners in Kazakhstan by Olga Denisiuk, Smyrnov Pavlo, Ainura Batyrbekova, Roman Dudnik, Alfiya Denebayeva, Ainur Zhandybayeva, Yuliya Kuznetsova, Deshko Tetyana

“…Conclusions: Low-threshold HIV testing and harm reduction services, like OCF using directly assisted self-testing and social network strategies are essential in reaching key populations with HIV prevention, increasing access to HIV testing and care. …”
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A data driven predictive viscosity model for the microemulsion phase by Akash Talapatra, Bahareh Nojabaei, Pooya Khodaparast

“…Various machine learning (ML) based regression algorithms are employed on our dataset to train and fit the model. …”
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An intelligent algorithm to fast and accurately detect chaotic correlation dimension by Mengyan Shen, Miaomiao Ma, Zhicheng Su, Xuejun Zhang

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A Robust Conformal Framework for IoT-Based Predictive Maintenance by Alberto Moccardi, Claudia Conte, Rajib Chandra Ghosh, Francesco Moscato

“…This study, set within the vast and varied research field of industrial Internet of Things (IoT) systems, proposes a methodology to address uncertainty quantification (UQ) issues in predictive maintenance (PdM) practices. At its core, this paper leverages the commercial modular aero-propulsion system simulation (CMAPSS) dataset to evaluate different artificial intelligence (AI) prognostic algorithms for remaining useful life (RUL) forecasting while supporting the estimation of a robust confidence interval (CI). …”
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Predictive reward-prediction errors of climbing fiber inputs integrate modular reinforcement learning with supervised learning. by Huu Hoang, Shinichiro Tsutsumi, Masanori Matsuzaki, Masanobu Kano, Keisuke Toyama, Kazuo Kitamura, Mitsuo Kawato

“…In this study, we investigated the cerebellum's role in executing reinforcement learning algorithms, with a particular emphasis on essential reward-prediction errors. …”
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Predictive estimations of health systems resilience using machine learning by Alessandro Jatobá, Paula de Castro-Nunes, Paloma Palmieri, Omara Machado Araujo de Oliveira, Patricia Passos Simões, Valéria da Silva Fonseca, Paulo Victor Rodrigues de Carvalho

“…Various ML algorithms, including regression models and decision trees, were applied to uncover insights into the resilience of health systems over time. …”
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Rapid Decision Algorithm for Patient Triage during Ebola Outbreaks by Denis-Luc Ardiet, Justus Nsio, Gaston Komanda, Rebecca M. Coulborn, Emmanuel Grellety, Francesco Grandesso, Richard Kitenge, Dolla L. Ngwanga, Bibiche Matady, Guyguy Manangama, Mathias Mossoko, John K. Ngwama, Placide Mbala, Francisco Luquero, Klaudia Porten, Steve Ahuka-Mundeke

“…Analyses of retrospective data from patients suspected of having Ebola virus infection identified 13 strong predictors and time from disease onset as constituents of a prediction score for Ebola virus disease. We also noted 4 highly predictive variables that could distinguish patients at high risk for infection, independent of their scores. …”
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LRST: searching tree anti-collision algorithm with low-redundancy by Qiong HUANG, Jiang-tao LING, Min ZHANG, Xiao-long YANG

“…To resolve this problem, a searching tree anti-collision algorithm with low-redundancy on the basis of regressive-style dynamic searching tree algorithm was proposed. …”
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Development and Validation of Predictive Models for Non-Adherence to Antihypertensive Medication by Cristian Daniel Marineci, Andrei Valeanu, Cornel Chiriță, Simona Negreș, Claudiu Stoicescu, Valentin Chioncel

“…Five machine learning models were developed to predict non-adherence, defined by ARMS quartile-based thresholds. …”
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Improved Algorithm to Detect Clandestine Airstrips in Amazon RainForest by Gabriel R. Pardini, Paulo M. Tasinaffo, Elcio H. Shiguemori, Tahisa N. Kuck, Marcos R. O. A. Maximo, William R. Gyotoku

“…These results suggest that, despite a slight reduction in recall, the modifications significantly improved the original algorithm by minimizing its limitations. …”
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Fitness exercise evaluation system based on improved DTW algorithm by Tinghang Guo, Qianhan Yin, Xinlin Liu, Yue Sun, Zhuanping Qin, Yu Han, Guangda Lu

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The Research of Optical Fast OFDM Based on Channel Estimation Algorithm by Li Zhao, Jing He, Zhihua Zhou, Rui Deng, Lin Chen

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Developing structural component of computational thinking using the algorithmic primitives method by Irina V. Bazhenova, Margarita M. Klunnikova, Nikolay I. Pak

“…The goal of the study is to substantiate the algorithmic primitives method to create a methodology for the development of a structural component of students’ computational thinking in the cluster of disciplines “Programming - Numerical Methods - Information Technologies in Education”. …”
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Smart diabetes management: remote monitoring and predictive health insights by K.S. Smelyakov, I.A. Lurin, K.V. Misiura, A.S. Chupryna, T.V. Tyzhnenko, O.D. Dolhanenko, V.M. Repikhov

“…The use of deep learning and neural network algorithms enhances the accuracy of these predictions by capturing complex data trends over time. …”
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Karatsuba Algorithm Revisited for 2D Convolution Computation Optimization by Qi Wang, Jianghan Zhu, Can He, Shihang Wang, Xingbo Wang, Yuan Ren, Terry Tao Ye

“…Our analysis and benchmarks have shown that for convolution operations of the same dimensions, the Karatsuba algorithm requires the same number of multiplications but fewer additions as compared with the Winograd algorithm. …”
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An algorithm for cardiac disease detection based on the magnetic resonance imaging by Heng Li, Qingni Yuan, Yi Wang, Pengju Qu, Chunhui Jiang, Hu Kuang

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Integrating Machine Learning and Educational Robotics by Charles Soares Pimentel, Fábio Ferrentini Sampaio

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Treatment algorithm for chronic vertebrogenic back pain: the role of chondroprotectors by O. S. Levin, E. E. Vasenina, A. I. Nebozhin, A. Yu. Nikitina

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MODELING OF ELECTRONIC OPEN EDUCATIONAL RESOURCES by Nina V. Komleva

“…The tools are analyzed in detail to create a virtual environment OER. The algorithm of the decision making process on the processing of contentbased neuro-fuzzy.…”
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