MATHEMATICAL MODEL OF A THERMOELECTRIC SEMICONDUCTOR SYSTEM FOR VISUALIZING THE TEMPERATURE FIELDS OF OBJECTS by O. V. Evdulov, R. A. Magomadov, K. A. Magomedova, E. A. Dzhabrailova

“…The research objective is to develop a mathematical model of a thermoelectric semiconductor system to visualize the temperature fields of objects and study the thermophysical internal processes. …”
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CD4C: Change Detection for Remote Sensing Image Change Captioning by Xiliang Li, Bin Sun, Zhenhua Wu, Shutao Li, Hu Guo

“…This ultimately limits the overall performance of the model. To address this issue, this study introduces change detection for remote sensing image change captioning (CD4C). …”
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A Novel Transformer-Based Multiscale Siamese Framework for High-Resolution Remote Sensing Change Detection by Liangjun Wang, Weitao Chen, Haoyi Wang, Zhengchao Chen

“…However, the inadequate extraction of local and global features, along with the insufficient utilization of multiscale features, constrains the ability to identify change regions at multiple scales. …”
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Cryptographic hardness assumptions identification based on discrete wavelet transform by Ke Yuan, Yu Du, Yizheng Liu, Rongjin Feng, Bowen Xu, Gaojuan Fan, Chunfu Jia

“…To address the challenges posed by high-dimensionality, complex data distributions, and difficulty fitting ciphertext features, an ensemble learning model called MHERF is constructed, which combines four classifiers: Decision Tree, Adaptive Boosting, Support Vector Machines, and Gradient Boosting. …”
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Green-Agile Maturity Model: An Evaluation Framework for Global Software Development Vendors by Nasir Rashid, Siffat Ullah Khan, Habib Ullah Khan, Muhammad Ilyas

“…The model has been built in four phases. In phase I and II, systematic literature review (SLR) was performed to identify the success factors and risk factors that either supports or hinders the green and sustainable software development respectively by practicing the agile methods in GSD. …”
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Development and investigation of parallel model of bee colony algorithms for cryptanalysis problem solving by Yury O Chernyshev, Alexander S Sergeev, Alexander N Ryazanov, Evgeny O. Dubrov

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A Nondestructive Detection Method for the Muti-Quality Attributes of Oats Using Near-Infrared Spectroscopy by Linglei Li, Long Li, Guoyuan Gou, Lang Jia, Yonghu Zhang, Xiaogang Shen, Ruge Cao, Lili Wang

“…Subsequently, the optimal PLS model was obtained by integrating feature wavelength selection algorithms (CARS, SPA, UVE, LAR). …”
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Prediction of Automotive Wire Harness Aging Based on CNN-biLSTM-Attention by Kun Xia, Qi Zhu, Qingqing Yuan, Jingxia Wang

“…Under the transition towards electrification and intelligence in modern automotive industry, the health status of low-voltage wiring harnesses directly affects vehicle performance and safety. To address the challenge of predicting performance degradation caused by multi-physics coupling effects during wiring harness aging, this study proposes a CNN-BiLSTM-Attention hybrid neural network model. …”
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Application of Hyperspectral Imaging for Identification of Melon Seed Variety Using Deep Learning by Zhiqi Hong, Chu Zhang, Wenjian Song, Xiangbo Nie, Hongxia Ye, Yong He

“…Logistic Regression (LR), Support Vector Classification (SVC), and Extreme Gradient Boosting (XGBoost) were used to establish classification models using spectral features and the manually extracted image features. …”
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Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method by Kai Zhao, Haiqing Tian, Jue Zhang, Yang Yu, Lina Guo, Jianying Sun, Haijun Li

“…Twenty-eight effective features were preferred, based on which the SVR model had <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>R</mi></mrow><mrow><mi>p</mi></mrow><mrow><mn>2</mn></mrow></msubsup></mrow></semantics></math></inline-formula>, <i>RMSEP</i> and <i>RPD</i> scores of 0.9533, 0.4186, and 4.4186, respectively; the pH prediction performance was substantially improved. …”
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A big data analysis algorithm for massive sensor medical images by Sarah A. Alzakari, Nuha Alruwais, Shaymaa Sorour, Shouki A. Ebad, Asma Abbas Hassan Elnour, Ahmed Sayed

“…Techniques like support vector machines (SVM) and the hidden Markov model (HMM) struggle with computational overhead and scalability in large datasets, limiting their performance in critical healthcare applications. …”
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Multitemporal Sentinel and GEDI data integration for overstory and understory fuel type classification by Pegah Mohammadpour, Domingos Xavier Viegas, Alcides Pereira, Emilio Chuvieco

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Identify drug-drug interactions via deep learning: A real world study by Jingyang Li, Yanpeng Zhao, Zhenting Wang, Chunyue Lei, Lianlian Wu, Yixin Zhang, Song He, Xiaochen Bo, Jian Xiao

“…Here, we developed a Multi-Dimensional Feature Fusion model named MDFF, which integrates one-dimensional simplified molecular input line entry system sequence features, two-dimensional molecular graph features, and three-dimensional geometric features to enhance drug representations for predicting DDIs. …”
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Keratoconus disease classification with multimodel fusion and vision transformer: a pretrained model approach by Shokufeh Yaraghi, Toktam Khatibi

“…These models have been trained on large datasets and have demonstrated strong performance in various computer vision tasks.The extracted features from the three pretrained models were fused using a feature fusion technique. …”
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Para-YOLO: An Efficient High-Parameter Low-Computation Algorithm Based on YOLO11n for Remote Sensing Object Detection by Hang Chen, Qi Cao, Yongqiang Wang, Shang Wang, Haisheng Fu, Zhenjiao Chen, Feng Liang

“…The MPMS module not only reduces computation, but also increases the number of parameters and improves the model&#x2019;s ability to extract local multiscale features. …”
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Graph neural networks embedded with domain knowledge for cyber threat intelligence entity and relationship mining by Gan Liu, Kai Lu, Saiqi Pi

“…Our model performs remarkably in threat entity recognition tasks, with accuracy and F1 scores reaching 92.13% and 93.11%, respectively. …”
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AHP-Guided Stacked Ensemble Modeling for Student Engagement Level Prediction in Online Education by Jingjing Fu, Linjie Luo, Zhifeng Zhong, Jiaming Qin

“…The main goal is to improve the performance of prediction models using an innovative hybrid approach. …”
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Intelligent prediction method of virtual network function resource capacity for polymorphic network service slicing by Julong LAN, Di ZHU, Dan LI

“…First, the time series of data stream used for prediction is subjected to two-stage weighting processing,and then the processed time series and its dependent spatial topology information are input into the network model for spatiotemporal feature extraction. For the extraction of spatial features, by given an adjacency matrix and a feature matrix,graph convolutional network is used to reorganize the spatial distribution features of time series in the Fourier domain. …”
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The Role of Country- and Firm-Level Factors in Determining Firms&#x2019; Environmental, Social, and Governance (ESG) Performance: A Machine Learning Approach by Eman Abdelfattah, Mahfuja Malik, Syed Muhammad Ishraque Osman

“…Although the ranking of feature importance varies between the causal inference and predictive models, the key factors identified by both techniques largely align and are consistent with the significance of the coefficients from the multiple regression model.…”
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Assessment of Operational Effectiveness Based on Stacking Integrated Learning and Case Reasoning by Yang Bai, Dong Kan, Xiaoying Wu, Zhenglie Yang

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