Research review of digital modeling technologies with 3D spatial visualization for pipelines by Xin LIU, Shengwen TU, Yanfang HOU, Dong LIN, Jie SHU, Yu TANG

“…MethodsFrom the perspective of software and algorithm characteristics, this paper classifies visual modeling technologies for pipelines into three categories: 3D modeling software, secondary development based on existing components, and underlying development. …”
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Surface Reconstruction Planning with High-Quality Satellite Stereo Pairs Searching by Jinwen Li, Guangli Ren, Youmei Pan, Jing Sun, Peng Wang, Fanjiang Xu, Zhaohui Liu

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Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…Cross-validation and feature selection methods were used to optimize model performance and identify key variables that most significantly impact soil resistivity. …”
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An English Diagnostic Intelligence Evaluation Model Based on Organizational Evolutionary Information Entropy by Haiying Sang

“…In order to realize the English diagnostic intelligence evaluation, improve the English learning ability, and construct the cognitive framework of English learning, this study proposes an English diagnostic intelligence evaluation model based on the organizational evolution information entropy. …”
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The Location Privacy Protection Technology of Mobile Intelligent Terminal by LI Zhi-peng, SUN Ming-song, SONG Zeng-lin

“…Based on the existing encryption and distortion algorithm models，it introduces a coordinate transformation method，increases fragmentation of user location information，and optimizes the technologies of dummies and false-name. …”
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Designing diverse and high-performance proteins with a large language model in the loop. by Carlos A Gomez-Uribe, Japheth Gado, Meiirbek Islamov

“…We present a protein engineering approach to directed evolution with machine learning that integrates a new semi-supervised neural network fitness prediction model, Seq2Fitness, and an innovative optimization algorithm, biphasic annealing for diverse and adaptive sequence sampling (BADASS) to design sequences. …”
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Diffusion Model With Gradient Descent Module Guiding Reconstruction for Single-Pixel Imaging by Chen Huang, Qiurong Yan, Jinwei Yan, Yi Li, Xiaolong Luo, Hui Wang

“…Sampling and generation are optimized jointly to capture key image information and improve reconstruction accuracy. …”
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Unsupervised feature selection based on generalized regression model with linear discriminant constraints by Xiangguang Dai, Mingyu Guan, Facheng Dai, Wei Zhang, Tingji Zhang, Hangjun Che, Xiangqin Dai

“…Abstract Unsupervised feature selection (UFS) methods play a crucial role in improving the efficiency of extracting relevant information and reducing computational complexity in the context of big data analysis. …”
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Potential of random forest machine learning algorithm for geological mapping using PALSAR and Sentinel-2A remote sensing data: A case study of Tsagaan-uul area, southern Mongolia by Munkhsuren Badrakh, Narantsetseg Tserendash, Erdenejargal Choindonjamts, Gáspár Albert

“…Geological mapping in remote and geologically complex regions can be substantially improved by integrating remote sensing data with machine learning algorithms. …”
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Characterizing Wake Behavior of Adaptive Aerodynamic Structures Using Reduced-Order Models by Kyan Sadeghilari, Aditya Atre, John Hall

“…Morphing blades have shown an ability to improve performance in simulations. These simulations show increased performance in Region 2 (partial load) operating conditions. …”
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Unsupervised fake news detection on social media using hybrid Gaussian Mixture Model. by Sajida Perveen, Muhammad Shahbaz, Sami S Albouq, Khlood Shinan, Hanan E Alhazmi, Fatmah Alanazi, M Usman Ashraf, Rehan Ashraf

“…In particular, it also proposes a novel hybrid method that leverages the Gaussian Mixture Model (GMM) in conjunction with the Group Counseling Optimizer (GCO), a metaheuristic optimization algorithm, to identify the optimal number of clusters for the detection of fake news. …”
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Modeling of the Power Station Boiler Combustion Efficiency Considering Multiple Work Condition with Feature Selection by TANG Zhenhao, WU Xiaoyan, CAO Shengxian

“…It is difficult for power station boiler efficiency to measure precisely A datadriven modeling method is proposed to establish the boiler combustion efficiency model, according to the machine learning theories A classification and regression trees (CART) algorithm provides correlated variables which have significant relation with the boiler combustion efficiency by data analysis Then, a KNearest Neighbor (KNN) classifies the samples to distinguish the data from different work conditions Based on the classified data, a least square support vector machine (LSSVM) optimized by differential evolution (DE) algorithm is proposed to establish a datadriven model (DDMMF) The parameters of LSSVM are optimized dynamically by DE to improve the model accuracy Finally, the prediction model is corrected dynamically for further improvement of the prediction accuracy The experimental results based on actual production data illustrate that the proposed approach can predict the boiler combustion efficiency accurately, which meets the requirements of boiler control and optimization…”
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Truck Transportation Scheduling for a New Transport Mode of Battery-Swapping Trucks in Open-Pit Mines by Yufeng Xiao, Wei Zhou, Boyu Luan, Keyi Yang, Yuqing Yang

“…The primary objective is to minimize the total haulage cost and total waiting time. Both a genetic algorithm and an adaptive genetic algorithm are applied to solve the proposed multi-objective scheduling optimization model. …”
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Optimasi Algoritma Support Vector Machine Berbasis Kernel Radial Basis Function (RBF) Menggunakan Metode Particle Swarm Optimization Untuk Analisis Sentimen by Cucun Very Angkoso, Khozainul Asror, Ari Kusumaningsih, Andi Kurniawan Nugroho

“…These reviews are an important source of information for application developers to understand user perceptions, identify problems, and improve service quality. The study investigates the effectiveness of the Particle Swarm Optimization (PSO) method for balanced and unbalanced datasets and how well it improves sentiment analysis accuracy when applied to the Support Vector Machine (SVM) algorithm when using Radial Basis Function (RBF) kernel. …”
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Taking the lag out of jet lag through model-based schedule design. by Dennis A Dean, Daniel B Forger, Elizabeth B Klerman

“…In this paper, the use of mathematical models to design sleep-wake and countermeasure schedules for improved performance is demonstrated. …”
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Hybrid CNN-Transformer Model for Accurate Impacted Tooth Detection in Panoramic Radiographs by Deniz Bora Küçük, Andaç Imak, Salih Taha Alperen Özçelik, Adalet Çelebi, Muammer Türkoğlu, Abdulkadir Sengur, Deepika Koundal

“…The integration is further optimized with the Weighted Boxes Fusion (WBF) algorithm, where WBF parameters are tuned using Bayesian optimization. …”
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Multi-objective Predictive Control of Gas Turbine System Based on T-S Fuzzy Model by Guolian HOU, Xiaoyan DAI, Linjuan GONG, Haixin XU, Jianhua ZHANG

“…Next, the multi-objective predictive controller is designed in which the load tracking index and economic index are defined and combined into a comprehensive multi-objective cost function. Then, in order to improve the settling speed of load tracking process, the simultaneous heat transfer search algorithm is employed to optimize the cost function and determine the control variables. …”
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An Enhanced and Lightweight YOLOv8-Based Model for Accurate Rice Pest Detection by Guisuo Liu, Juxing Di, Qing Wang, Yan Zhao, Yang Yang

“…Experimental results demonstrate that the proposed model outperforms YOLOv8n, achieving an mAP@0.5 of 94.3%, and an mAP@0.5:0.95 of 67.3%, with 2.7% improvement in mAP@0.5 and 1.2% improvement in mAP@0.5:0.95. …”
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Anatomical Parameter-driven Volumetric Modulated Arc Therapy Optimization in Left-sided Breast Cancer: A Machine Learning Framework for Lung Dose Prediction by Mukesh Kumar Zope, Deepali Patil, Rishi Raj, Seema Devi, Richa Madhawi

“…Conclusion: VMAT-4P is identified as the most effective method for radiotherapy in left-sided breast cancer, providing an excellent balance between optimal target coverage and improved protection of surrounding OAR. …”
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Reaction Behavior and Kinetic Model of Hydroisomerization and Hydroaromatization of Fluid Catalytic Cracking Gasoline by Haijun Zhong, Xiwen Song, Shuai He, Xuerui Zhang, Qingxun Li, Haicheng Xiao, Xiaowei Hu, Yue Wang, Boyan Chen, Wangliang Li

“…These findings provide valuable guidance for the optimization, design, and operation of FCC gasoline hydro-upgrading units, as well as for catalyst development, with the aim of improving process efficiency and fuel quality.…”
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