Machine Learning Models Informed by Connected Mixture Components for Short- and Medium-Term Time Series Forecasting by Andrey K. Gorshenin, Anton L. Vilyaev

“…These components are formed using probability mixture models and a special algorithm for merging parameters in the sliding window mode. …”
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Sparse Deep Neural Network for Encoding and Decoding the Structural Connectome by Satya P. Singh, Sukrit Gupta, Jagath C. Rajapakse

“…For decoding, we propose recursive feature elimination (RFE) algorithm based on DeepLIFT, layer-wise relevance propagation (LRP), and Integrated Gradients (IG) algorithms to remove irrelevant features and thereby identify key biomarkers associated with AD and PD. …”
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A pipeline for processing hyperspectral images, with a case of melanin-containing barley grains as an example by I. D. Busov, M. A. Genaev, E. G. Komyshev, V. S. Koval, T. E. Zykova, A. Y. Glagoleva, D. A. Afonnikov

“…The current version of the package implements the following methods: construction of a confidence interval of an arbitrary level for the difference of sample averages; verification of the similarity of intensity distributions of spectral lines for two sets of hyperspectral images on the basis of the Mann–Whitney U-criterion and Pearson’s criterion of agreement; visualization in two-dimensional space using dimensionality reduction methods PCA, ISOMAP and UMAP; classification using linear or ridge regression, random forest and catboost; clustering of samples using the EM-algorithm. …”
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Implementing Blockchain Technology for Secure Data Transactions in Cloud Computing Environments Challenges and Solutions by Dandu Varalakshmi, N Shirisha, K Suresh, Saidhbi Shaik, V Venkatesh, C F Theresa Cenate

“…It also includes quantum-resilient cryptographic algorithms, which provide protection against potential future quantum attacks. …”
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Microfluidic-enabled three-dimensional stretchable thermoelectrics by Zhenlong Huang, Tao Chen, Yan Jiang, Rui Zhou, Yizhuo Wang, Junjie Ji, Hongwei Xie, Taisong Pan, Dongpeng Fan, Linlong Liang, Longpeng Yang, Binbin Jiang, Peng Li, Min Gao, Jia Zhu, Guang Yao, Dongfeng Xue, Yuan Lin

“…The device achieves ~10 °C environmental and 11 °C on-skin temperature reduction with precise control. Furthermore, by integrating a temperature sensor and control circuit with the 3D TED, a wearable closed-loop system is developed. …”
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Exploring the potential of antifungal-loaded proniosomes to consolidate corneal permeation in fungal keratitis: A comprehensive investigation from laboratory characterization to mi... by Sadek Ahmed, Michael M. Farag, Heba Attia, Bander Balkhi, Islam M. Adel, Asmaa Ashraf Nemr

“…Additionally, microbiological assessments of the optimal TCZ-PNS compared to TCZ suspension demonstrated an inhibition zone nearly 50 % larger, a significantly lower MIC and MFC (64-fold reduction), and enhanced biofilm inhibition activity across most tested concentrations. …”
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Classification of intracranial tumors based on optical-spectral analysis by I. D. Romanishkin, T. A. Savelieva, A. Ospanov, K. G. Linkov, S. V. Shugai, S. A. Goryajnov, G. V. Pavlova, I. N. Pronin, V. B. Loschenov

“…In case the number of parameters exceeds a couple of dozens, it is necessary to use machine learning algorithms  to build a intraoperative decision support system for the surgeon. …”
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Cooperate or Not Cooperate: Transfer Learning With Multi-Armed Bandit for Spatial Reuse in Wi-Fi by Pedro Enrique Iturria-Rivera, Marcel Chenier, Bernard Herscovici, Burak Kantarci, Melike Erol-Kantarci

“…Simulation results show that cooperation via the SAU-Coop algorithm leads to a 14.7% improvement in cumulative throughput and a 32.5% reduction in Packet Loss Rate (PLR) in comparison to non-cooperative approaches. …”
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Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance by Sugunakar Mamidala, Yellapragada Venkata Pavan Kumar, Rammohan Mallipeddi

“…This paper proposes a novel framework that integrates deep Q networks (DQNs) for real-time charging optimization, coupled with multimodal bioinspired algorithms like ant lion optimization (ALO) and moth flame optimization (MFO). …”
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Trading off Iodine and Radiation Dose in Coronary Computed Tomography by Guillaume Fahrni, Thomas Saliba, Damien Racine, Marianna Gulizia, Georgios Tzimas, Chiara Pozzessere, David C. Rotzinger

“…This review explores the balance between radiation and CM volumes, emphasizing patient-specific protocol optimization to improve diagnostic accuracy while minimizing risks. Radiation dose reduction strategies, such as low tube voltage protocols, prospective ECG-gating, and modern reconstruction algorithms, have significantly decreased radiation exposure, with some studies achieving sub-millisievert doses. …”
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Methodology сomparative statistical analysis of Russian industry based on cluster analysis by Sergey S. Shishulin

“…Thus, for example, in analyzing the structure of industrial production, the reduction was from fifteen industries to three basic, well-interpreted factors: the relatively extractive industries (with a low degree of processing), high-tech industries and consumer goods (medium-technology) sectors. …”
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Monitoring the antibiotic resistance in the intensive care unit of a multidisciplinary hospital by V. Yu. Zemko, V. K. Okulich, A. M. Dzyadz’ko

“…It is necessary to monitor the resistance of common microorganisms to certain antibiotics in order to develop algorithms for rational antibacterial treatment in each hospital.…”
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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid, Hamza Kheddar, Noureddine Batel, Muhammad E. H. Chowdhury

“…These processes begin with capturing speech in analog form and applying signal processing algorithms to ensure compatibility with devices like cochlear implants (CIs). …”
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An Adaptive Robust Event-Triggered Variational Bayesian Filtering Method with Heavy-Tailed Noise by Di Deng, Peng Yi, Junlin Xiong

“…The one-step state prediction probability density function and the measurement likelihood function are modeled as Student’s t-distributions. …”
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Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

“…At the same time, artificial intelligence (AI), with its powerful algorithms for data analysis and predictive modeling, is transforming how we design, evaluate, and monitor advanced therapies, including the optimization of manufacturing processes. …”
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Optimizing the Finishing Treatment of Potato Harvester Transmission Shafts by A. V. Nemenko, M. M. Nikitin

“…The paper provides the results of testing the proposed algorithm for predicting the yield of viable products using the proposed method based on interim measurements of defect characteristics during the treatment process. …”
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Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence by Xiaoyin Wu, Xiaoyin Wu, Buyu Guo, Buyu Guo, Xingyu Chang, Xingyu Chang, Yuxuan Yang, Yuxuan Yang, Qianqian Liu, Qianqian Liu, Jiahui Liu, Jiahui Liu, Yichen Yang, Yichen Yang, Kang Zhang, Yumei Ma, Songbo Fu, Songbo Fu, Songbo Fu

“…The current lack of reliable predictive biomarkers hinders early diagnosis and personalized therapy.MethodsTranscriptomic profiles of DN samples and controls were extracted from GEO databases. …”
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A Dynamic and Timely Point-of-Interest Recommendation Based on Spatio-Temporal Influences, Timeliness Feature and Social Relationships by Jun Zhu, Haifeng Lin, Zhinan Gou, Yiqing Xu, Hongying Liu, Ming Tang, Li Wang, Shu Li, Bing Hu

“…The experimental results reveal that our algorithm outperforms seven state-of-the-art recommenders in terms of prediction accuracy and system timeliness.…”
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Rapid and Accurate Acquisition of Equivalent Economic Scale in Flood Protection Area Based on Multi-source Big Data by ZHENG Yong, XU Zhangfan, ZHOU Xiaoxin, CAI Jihong, JI Hongxiang, QIN Yan

“…The results show that the accuracy of the population prediction model is 82%, and the accuracy of the GDP prediction model is 76%. …”
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A New State Estimation Method with Radar Measurement Missing by Hongjian Wang, Cun Li, Ying Wang, Qing Li, Xicheng Ban

“…The state transition model based on the historical observation data fit prediction is designed because the existing state estimation method can only use the system model prediction while the observation is missing. …”
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