A SYNTHESIS METHOD OF BASIC TERNARY BENT-SQUARES BASED ON THE TRIAD SHIFT OPERATOR by O. N. Zhdanov, A. V. Sokolov

“…The paper results are valuable for practical use: the development of new constant amplitude codes for MC-CDMA technology, cryptographic primitives, data compression algorithms, signal structures, algorithms of block and stream encryption, based on advanced principles of many-valued logic. …”
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Undersampled Blade Tip-Timing Vibration Reconstruction under Rotating Speed Fluctuation: Uniform and Nonuniform Sensor Configurations by Zhongsheng Chen, Jing He, Chi Zhan

“…Then, two NTT-based reconstruction algorithms are derived for uniform and nonuniform BTT sensor configurations, respectively. …”
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Predicting child mortality determinants in Uttar Pradesh using Machine Learning: Insights from the National Family and Health Survey (2019–21) by Pinky Pandey, Sacheendra Shukla, Niraj Kumar Singh, Mukesh Kumar

“…Aim: This study aimed to delineate spatial variations in under-five mortality across Uttar Pradesh and evaluate the efficacy of various machine learning algorithms in identifying critical determinants influencing these mortality rates. …”
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Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…Artificial intelligence (AI), encompassing techniques such as machine learning, deep learning, and Generative AI, offers powerful tools and algorithms to efficiently identify meaningful patterns, correlations, and drug–target interactions from big data, enabling more accurate predictions and novel hypothesis generation. …”
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Random Forests in Count Data Modelling: An Analysis of the Influence of Data Features and Overdispersion on Regression Performance by Ciza Arsène Mushagalusa, Adandé Belarmain Fandohan, Romain Glèlè Kakaï

“…Machine learning algorithms, especially random forests (RFs), have become an integrated part of the modern scientific methodology and represent an efficient alternative to conventional parametric algorithms. …”
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A retrial queueing system with processor sharing and impatient customers by V. I. Klimenok

“…A condition for the existence of a stationary distribution is found, and algorithms for calculating the stationary distribution and stationary performance characteristics of the system are proposed.Methods. …”
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Study on a New Method of Link-Based Link Prediction in the Context of Big Data by Chen Jicheng, Chen Hongchang, Li Hanchao

“…It uses this concept to recommend friends by checking their links using various algorithms. The same goes for shopping and e-commerce sites. …”
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A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity by Abdullah Al Siam, Moutaz Alazab, Albara Awajan, Nuruzzaman Faruqui

“…We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. …”
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Multiple machine learning-based integrations of multi-omics data to identify molecular subtypes and construct a prognostic model for HNSCC by Xiaoqin Luo, Chao Li, Gang Qin

“…Using 10 multi-omics consensus clustering algorithms via the MOVICS package, we identified two molecular subtypes (CS1 and CS2) and validated their stability. …”
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Robust Prediction of Healthcare Inflation Rate With Statistical and AI Methods in Iran by Mohammad Javad Shaibani, Ali Akbar Fazaeli

“…Using monthly time series data of HCIR in Iran, we developed various forecasting techniques based on classical smoothing methods, decomposition ETS (error, trend, and seasonality) approaches, autoregressive (AR) integrated moving average (ARIMA), seasonal ARIMA (SARIMA), and a multilayer nonlinear AR artificial neural network (NARANN) with several training algorithms including Bayesian regularization (BR), Levenberg–Marquardt (LM), scaled conjugate gradient (SCG), Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton, conjugate gradient with Powell–Beale restarts (CGB), conjugate gradient with Fletcher–Reeves updates (CGF), and resilient propagation (RPROP) algorithms. …”
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Retrieval of nicotine content in cigar leaves by remote analysis of aerial hyperspectral combining machine learning methods by Chenyu Tian, Yifei Lu, Hengduo Xie, Yufan Yu, Liming Lu

“…Three machine learning algorithms were then used to analyze the data: PLS, BP, RF, and the SVM. …”
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Navigating the landscape: Unveiling the reflection of AI in the sharing economy through bibliometric-based approach by Veljko Uskoković, Milica Maričić, Aleksandra Dacić-Pilčević, Veljko Jeremić

“…Furthermore, AI optimizes resource allocation and improves matching algorithms on online labour platforms, thereby boosting platform efficiency. …”
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A Novel Remote Sensing Recognition Using Modified GMM Segmentation and DenseNet by Muhammad Waqas Ahmed, Moneerah Alotaibi, Sultan Refa Alotaibi, Dina Abdulaziz Alhammadi, Asaad Algarni, Ahmad Jalal, Jeongho Cho

“…The use of optimization algorithms further enhances the discriminative power of the features, leading to improved classification accuracy.…”
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Ion suppression correction and normalization for non-targeted metabolomics by Iqbal Mahmud, Bo Wei, Lucas Veillon, Lin Tan, Sara Martinez, Bao Tran, Alexander Raskind, Felice de Jong, Yiwei Liu, Jibin Ding, Yun Xiong, Wai-kin Chan, Rehan Akbani, John N. Weinstein, Chris Beecher, Philip L. Lorenzi

“…Here we report a method, the IROA TruQuant Workflow, that uses a stable isotope-labeled internal standard (IROA-IS) library plus companion algorithms to: 1) measure and correct for ion suppression, and 2) perform Dual MSTUS normalization of MS metabolomic data. …”
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Motion feature extraction using magnocellular-inspired spiking neural networks for drone detection by Jiayi Zheng, Jiayi Zheng, Yaping Wan, Xin Yang, Hua Zhong, Minghua Du, Gang Wang, Gang Wang

“…Experimental results in terms of drone detection performance indicate that the incorporation of MG-SNN significantly improves the accuracy of low-altitude drone detection tasks compared to popular small object detection algorithms, acting as a cheap plug-and-play module in detecting small flying targets against complex backgrounds.…”
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HPGCN: A graph convolutional network-based prediction model for herbal heat/cold properties by Qikai Niu, Jing’ai Wang, Hongtao Li, Lin Tong, Haiyu Xu, Weina Zhang, Ziling Zeng, Sihong Liu, Wenjing Zong, Siqi Zhang, Siwei Tian, Huamin Zhang, Bing Li

“…Compared to previous machine learning algorithms, the HPGCN obtained optimal classification prediction results for ACC, Recall, Precision, F1, and AUC indicators by 5-fold cross-validation on the training and test sets. …”
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Automated Control System of 35 KV and Higher Power Networks by M. I. Fursanov, A. A. Zalatoi, A. N. Mukha, V. I. Privalov, I. V. Krupa

“…The description of algorithms for solution of some technological problems realized in the library of applied programs that presents a calculative nucleus of the given developed system. …”
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An Occlusion Approach with Consistency Constraint for Multiscopic Depth Extraction by Cédric Niquin, Stéphanie Prévost, Yannick Remion

“…This is a new approach to handle occlusions in stereovision algorithms in the multiview context using images destined for autostereoscopic displays. …”
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Comparison of Predictive Control Methods for High Consumption Industrial Furnace by Goran Stojanovski, Mile Stankovski

“…In order to demonstrate the benefits from implementation of the advanced predictive control algorithms, we have compared several major criteria for furnace control. …”
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New Investigation for the Liu-Story Scaled Conjugate Gradient Method for Nonlinear Optimization by Eman T. Hamed, Rana Z. Al-Kawaz, Abbas Y. Al-Bayati

“…Our numerical experiments show that the new proposed algorithms are more stable and economic as compared to some well-known standard CG methods.…”
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