Advancements in Chemical Materials: Exploring Smart Storage Equipment and Protection Systems (Review) by Samah Kamil, Mohammed Al-Turfi, Riyadh Almukhtar

“…Results showed breakthroughs in sensor technologies, systems integration, and AI algorithms for real-time storage facility monitoring, danger identification, and predictive analytics. …”
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Fractional-Order Modeling and Analysis of a Variable Structure Hybrid Energy Storage System for EVs by Jianlin Wang, Dan Xu, Jiahui Zhou, Jinlu Mao

“…The establishment of a high-precision mathematical model of the hybrid energy storage system is the basis for the study of high-quality nonlinear control algorithms. Fortunately, the theory of fractional calculus can help build accurate mathematical models of hybrid energy storage systems. …”
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Application of the Machine Learning Methods to Assess the Impact of physico-chemical characteristics of water on Feed Consumption in Fish Farms by Hava Şimşek, Mükerrem Oral, Mesut Yılmaz, Mustafa Çakır, Nedim Özdemir, Okan Oral

“…In the regression analysis carried out using ML techniques, the models developed with RF, GBM and XGBoost algorithms yielded better results.…”
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Dense Sandstone Material Decomposition Based on Improved Convolutional Neural Network by Ran ZHANG, Huihua KONG, Jiaxin LI, Yijiao SONG

“…At present, the material decomposition method based on neural networks overcomes the limited decomposition effect of traditional iterative algorithms. However, the performance of traditional neural networks in feature detail recovery is still not satisfactory. …”
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A DAG Scheduling Scheme on Heterogeneous Computing Systems Using Tuple-Based Chemical Reaction Optimization by Yuyi Jiang, Zhiqing Shao, Yi Guo

“…Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. …”
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Digital Core Modeling Based on Pretrained Generative Adversarial Neural Networks by Qing Zhang, Benqiang Wang, Xusheng Liang, Yizhen Li, Feng He, Yuexiang Hao

“…With the development of deep learning technology, a variety of deep learning algorithms have been applied to digital core modeling. …”
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AN EFFECTIVE APPROACH TO FACE RECOGNITION WITH ARTIFICIAL INTELLIGENCE AND THE INTERNET OF THINGS USING NVIDIA JETSON NANO by Ngoc Giau Pham, Nhien Loc Bui, Quang Hien Tran, Le Thanh Hai Tong, Hong Ngoc Tran

“…This device is capable of capturing video and executing AI algorithms for real-time analysis, thereby deriving crucial data for IoT decision-making processes. …”
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Native RNA nanopore sequencing reveals antibiotic-induced loss of rRNA modifications in the A- and P-sites by Anna Delgado-Tejedor, Rebeca Medina, Oguzhan Begik, Luca Cozzuto, Judith López, Sandra Blanco, Julia Ponomarenko, Eva Maria Novoa

“…To identify significant rRNA modification changes, we develop NanoConsensus, a novel pipeline that is robust across RNA modification types, stoichiometries and coverage, with very low false positive rates, outperforming all individual algorithms tested. We then apply NanoConsensus to characterize the rRNA modification landscape upon antibiotic exposure, finding that rRNA modification profiles are altered in the vicinity of A and P-sites of the ribosome, in an antibiotic-specific manner, possibly contributing to antibiotic resistance. …”
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Leveraging AHP and transfer learning in machine learning for improved prediction of infectious disease outbreaks by Reham Abdallah, Sayed Abdelgaber, Hanan Ali Sayed

“…The researchers’ approach involves the deployment of several machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, and an ensemble of these methods. …”
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A Simplified Multiband Sampling and Detection Method Based on MWC Structure for Mm Wave Communications in 5G Wireless Networks by Min Jia, Xue Wang, Xuemai Gu, Qing Guo

“…In the reconstruction stage, the proposed method simplifies the computational complexity by exploiting simple linear operations instead of CS recovery algorithms and provides more stable performance of signal recovery. …”
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Robust fault detection and classification in power transmission lines via ensemble machine learning models by Tahir Anwar, Chaoxu Mu, Muhammad Zain Yousaf, Wajid Khan, Saqib Khalid, Ahmad O. Hourani, Ievgen Zaitsev

“…Leveraging a comprehensive dataset of diverse fault scenarios, various machine learning algorithms—including Random Forest (RF), K-Nearest Neighbors (KNN), and Long Short-Term Memory (LSTM) networks—are evaluated. …”
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A tunable multi-timescale Indium-Gallium-Zinc-Oxide thin-film transistor neuron towards hybrid solutions for spiking neuromorphic applications by Mauricio Velazquez Lopez, Bernabe Linares-Barranco, Jua Lee, Hamidreza Erfanijazi, Alberto Patino-Saucedo, Manolis Sifalakis, Francky Catthoor, Kris Myny

“…Abstract Spiking neural network algorithms require fine-tuned neuromorphic hardware to increase their effectiveness. …”
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Generation of Smoke Dataset for Power Equipment and Study of Image Semantic Segmentation by Rong Chang, Zhengxiong Mao, Jian Hu, Haicheng Bai, Anning Pan, Yang Yang, Shan Gao

“…This paper addresses the problems of limited smoke data, difficult labeling, and insufficient research on recognition algorithms in power systems. We propose using three-dimensional virtual technology to generate smoke and image masks and using environmental backgrounds such as HDR (high dynamic range imaging) lighting to realistically combine smoke and background. …”
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Temporary Pacing Simulator: A Training Tool for Clinicians by Ioana Cretu, Alexander Tindale, Maysam Abbod, Wamadeva Balachandran, Ashraf W. Khir, Hongying Meng

“…It simulates various pacing modes—atrial, ventricular, and dual-chamber—while modeling pacing failures and haemodynamic changes. Sophisticated algorithms replicate clinical responses, offering real-time feedback and dynamic visualizations to enhance learning. …”
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AI-driven video summarization for optimizing content retrieval and management through deep learning techniques by Deepali Vora, Payal Kadam, Dadaso D Mohite, Nilesh Kumar, Nimit Kumar, Pratheeik Radhakrishnan, Shalmali Bhagwat

“…Existing methods, often reliant on human intervention or low-complexity algorithms, are observed to struggle with the growing demands of online video quantity and quality. …”
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OVERVIEW STUDY OF MOBILE NETWORK TRAFFIC FOR BTS STATIONS by Hoang Van Thuc*, Pham Van Ngoc, Doan Thi Thanh Thao, Vu Chien Thang, Pham Thanh Nam, Mac Thi Phuong

“…This enables researchers to deploy and apply machine learning algorithms more effectively. This paper provides an overview of mobile network traffic at BTS stations, conducted from a data-driven perspective, focusing on extracting and transforming data into information that serves production and business purposes within mobile networks, as well as describing the characteristics of user traffic. …”
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Historical Reconstruction of Astronaut Cancer Risk: Context for Recent Solar Minima by Tony C. Slaba

“…To provide additional context for this level of variation, two different nuclear interaction models are used within the radiation transport algorithms used to propagate GCR ions and secondary particles through shielding and tissue. …”
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A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy by Yaoying Wang

“…Instead of relying on deep learning algorithms, this study leverages entropy-based techniques for attack detection. …”
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Angular and CP-Violation Analyses of B-→D⁎+l-ν-l Decays at Hadron Collider Experiments by Daniele Marangotto

“…This article proposes the measurement of B-→D⁎+l-ν-l angular and CP-violating observables at hadron collider experiments, by exploiting approximate reconstruction algorithms using information from detectable final-state particles only. …”
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A Computational Complexity-Based Method for Predicting Scholars’ Ages through Articles’ Information by Jun Zhang, Xiaoyan Su, Mingliang Hou, Jing Ren

“…Our method first classifies factors that affect scholars’ ages into intuitive and complex types according to their computational complexity and then apply machine learning algorithms to predict the ages of scholars based on these factors. …”
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