Real-Time Compensation for Unknown Image Displacement and Rotation in Infrared Multispectral Camera Push-Broom Imaging by Tongxu Zhang, Guoliang Tang, Shouzheng Zhu, Fang Ding, Wenli Wu, Jindong Bai, Chunlai Li, Jianyu Wang

“…Subsequently, parameter prediction is conducted using the Kalman model, and real-time compensation is achieved by dynamically adjusting the infrared TDI integration unit based on the predicted parameters. …”
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Study of Cutting Forces in Drilling of Aluminum Alloy 2024-T351 by Răzvan Sebastian Crăciun, Virgil Gabriel Teodor, Nicușor Baroiu, Viorel Păunoiu, Georgiana-Alexandra Moroșanu

“…The experimental plan included 27 combinations of the parameters of the cutting regime (cutting depth, cutting speed, and feed), for which energetic cutting parameters were measured, the axial force and the torsion moment, respectively Based on these data, a neural network was trained, using the Bayesian regularization algorithm, in order to predict the optimal values of the cutting energy parameters. …”
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Hyperspectral Inversion of Soil Cu Content in Agricultural Land Based on Continuous Wavelet Transform and Stacking Ensemble Learning by Kai Yang, Fan Wu, Hongxu Guo, Dongbin Chen, Yirong Deng, Zaoquan Huang, Cunliang Han, Zhiliang Chen, Rongbo Xiao, Pengcheng Chen

“…Therefore, the rapid and accurate prediction of heavy metal content in agricultural soil is crucial for environmental protection and soil remediation. …”
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Research on short-term power load forecasting based on deep reinforcement learning with multiple intelligences by Tianyun Luo, Dunlin Zhu, Jinming Liu, Sheng Yang, Jinglong He, Yuan Fu

“…Therefore, to realize accurate and efficient prediction of short-term power loads, a short-term power load prediction method based on multi-intelligence deep reinforcement learning is proposed to address the complex nonlinear characteristics of load data. …”
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Machine-Learning-Based Optimal Feed Rate Determination in Machining: Integrating GA-Calibrated Cutting Force Modeling and Vibration Analysis by Yu-Peng Yeh, Han-Hao Tsai, Jen-Yuan Chang

“…This study proposes a machine learning-based approach to optimize feed rate in machining operations by integrating a genetic algorithm (GA)-calibrated cutting force model with vibration analysis. …”
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“Bias Correction Method” for Regional Correction Experiment of Warm Season Rainstorm in Zhejiang by Chengyan Mao, Xin Pan, Haowen Li, Weibiao Li, Haoya Liu

“…This study employs the K-means clustering algorithm to partition warm-season precipitation in Zhejiang Province into distinct regions. …”
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Location-Dependent Query Processing: Semantic Cache for Real-Time Smart City Analytics by Rabia Hasan, Waseem Shehzad, Ejaz Ahmed, Hasan Ali Khattak, Ahmed S. AlGhamdi, Sultan S. Alshamrani

“…In this paper, our novel approach comprise of usage of semantic caches with the Bayesian networks using a prediction algorithm. Our approach is unique and distinct from the traditional query processing system especially in mobile domain for the prediction of future locations of users. …”
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CSearch: chemical space search via virtual synthesis and global optimization by Hakjean Kim, Seongok Ryu, Nuri Jung, Jinsol Yang, Chaok Seok

“…Abstract The two key components of computational molecular design are virtually generating molecules and predicting the properties of these generated molecules. …”
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3D conformation and crystal interaction insights into drug development challenges for HCV drug analogues via molecular simulations by Richard S. Hong, Alessandra Mattei, Mark E. Tuckerman, Ahmad Y. Sheikh

“…In this article, we demonstrate how a suite of molecular simulation approaches, including crystal structure prediction augmented with a new hydrate CSP algorithm, free-energy perturbation, molecular dynamics (MD) based solubility predictions, and topological assessment to evaluate surface re-crystallization tendencies, provide key atomistic-level insights into the differentiated performance of the two analogs. …”
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Road-Adaptive Precise Path Tracking Based on Reinforcement Learning Method by Bingheng Han, Jinhong Sun

“…The framework first analyzes the obstacles around the vehicle and plans an obstacle-free reference path with the minimum curvature using the hybrid A* algorithm. Next, based on the generated reference path, the current state of the vehicle, and the vehicle motor energy efficiency diagram, the optimal speed is calculated in real time, and the vehicle dynamics preview point at the future moment—specifically, the look-ahead distance—is predicted. …”
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Enhancing climate action evaluation using artificial neural networks: An analysis of SDG 13 by Cosimo Magazzino, Zakaria Zoundi

“…A key component of the research is the application of Garson's algorithm, which identifies the relative importance of each of the seven indexes in influencing climate outcomes. …”
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Profiling public perception of emerging technologies: Gene editing, brain chips and exoskeletons. A data-analytics framework by Simona-Vasilica Oprea, Adela Bâra

“…It consists of about 100 questions that are grouped using a prefix code by the 3 above-mentioned human enhancement, science role, concerns and excitements, perceived algorithm fairness and demographics. To investigate this survey and extract insights regarding the general attitude, a data analytics framework is proposed that consists of clustering using DBSCAN and K-means, ANOVA for clusters, PCA, t-SNE and UMAP for graphical visualization, prediction and advanced customers’ profiles analyses. …”
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Adaptive Panoramic Video Multicast Streaming with Limited FoV Feedback by Jie Li, Ling Han, Cong Zhang, Qiyue Li, Weitao Li

“…Then, we design a QoE-driven panoramic video streaming system with a client/server (C/S) architecture, in which the server performs rate adaptation based on the bandwidth and the predicted FoV. We then formulate it as a nonlinear integer programming (NLP) problem and propose an optimal algorithm that combines the Karush–Kuhn–Tucker (KKT) conditions with the branch-and-bound method to solve this problem. …”
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Navigation strategies in Caenorhabditis elegans are differentially altered by learning. by Kevin S Chen, Anuj K Sharma, Jonathan W Pillow, Andrew M Leifer

“…Together, we present a flexible navigation algorithm that is supported by distributed neural computation in a compact brain.…”
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Application of business analysis tools in company management by A. Yu. Orlova, A. A. Sorokin, D. G. Lovyannikov

“…We have developed an algorithm for the implementation of a business intelligence system and for this purpose built models in the EPC AS-IS and TO-BE notation. …”
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A model of head direction and landmark coding in complex environments. by Yijia Yan, Neil Burgess, Andrej Bicanski

“…Our account of visual feedback for HD stabilization provides a novel perspective on neural mechanisms of spatial navigation within richer sensory environments, and makes experimentally testable predictions.…”
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SmilODB: a multi-omics database for the medicinal plant danshen (Salvia miltiorrhiza, Lamiaceae) by Yong-Hui Liu, Wen-Qiong Zeng, Si-Fan Tao, Yi-Nuo Du, Fei-Hong Yu, Zhe-Chen Qi, Dong-Feng Yang

“…Although various omics resources have been published, there remains a lack of an integrated platform to unify genomic, transcriptomic, proteomic, and metabolomic data.MethodsTo address this gap, we constructed the S. miltiorrhiza Multi-omics Database (SmilODB, http://www.isage.top:56789/), which systematically integrates publicly available genome assemblies, transcriptome datasets, metabolic pathway annotations, and protein structural predictions. Protein structures were predicted using the RoseTTAFold algorithm, and all data were visualized using interactive heat maps, line charts, and histograms.ResultsSmilODB includes: (i) two genome assemblies of S. miltiorrhiza, (ii) 48 tissue-specific transcriptome datasets from root, leaf, and other vegetative tissues, (iii) annotated biosynthetic pathways for bioactive compounds such as tanshinones and salvianolic acids, and (iv) 2,967 high-confidence protein models. …”
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Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand by Liu He, Tangyi Guo, Kun Tang

“…A two-layer dynamic coupling model with iterative feedback is obtained by combining the demand prediction model and scheduling optimization model and is then solved by Nicked Pareto Genetic Algorithm (NPGA). …”
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High precision water quality retrieval in Dianchi Lake using Gaofen 5 data and machine learning methods by Yuewen Feng, Jun Zhang, Sanjie Guo, Yunbai Zhang, Zhongwei Zhang

“…Extracting these indicators from remote sensing data enables rapid and efficient inversion of water quality conditions, providing a key step in predicting water pollution. The low-precision inversion results of WQI limit the understanding of the ecological safety of water resources. …”
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CNN-GRU Battery SOC Estimation Method Fused with Attention Mechanism for Electric Multiple Units by WANG Shenghui, TIAN Qin, LIU Lihao, FENG Enlai, YU Tianjian

“…To precisely estimate the SOC of small-sample battery cycling data, this paper transforms the continuous regression model into a classification problem, discretizes the battery SOC ranges, and converts the final prediction result into discrete SOC values. The experimental results show that compared with the CNN-GRU algorithm, the proposed approach improves three key metrics — root mean square error, mean absolute error, and mean relative error by 18.90%, 17.92% and 19.78%, respectively, demonstrating impressive prediction accuracy and stability.…”
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