Automatic identification and characteristics analysis of crack tips in rocks with prefabricated defects based on deep learning methods. by Mingtao Gao, Minhui Li, Lu Chen, Zihao Guo, Chengyang Guo, Liping Li, Changsen Bu

“…Especially in the rock specimen analysis of prefabricated multi-angle cracks, image quality and algorithm adaptability have emerged as the critical bottlenecks restricting the identification accuracy. …”
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Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS by Weiwei Lyu, Yingli Wang, Shuanggen Jin, Haocai Huang, Xiaojuan Tian, Jinling Wang

“…Furthermore, the modified variational Bayesian Kalman filter (VBKF) that accurately adjusts the measurement noise covariance matrix is proposed, and the Expectation–Maximization (EM) algorithm is employed to refine the prior parameter of the predicted error covariance matrix. …”
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Development of a New Correlation Model for Heat Transfer in Solar Air Heater with Corrugated Absorber Plates Using Swarm Optimization by Abdulkadir Kocer, Uğur Ercan, Zeki Yetgin, Filiz Karaomerlioglu

“…As the main contribution, two different model equations, namely M1 and M2, for the correlation model of the solar heat transfer were proposed to predict the Nusselt number, where M2 is an original model and M1 is newly established with the fine-tuned coefficients. …”
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Investigating lightweight and interpretable machine learning models for efficient and explainable stress detection by Debasish Ghose, Ayan Chatterjee, Indika A. M. Balapuwaduge, Yuan Lin, Soumya P. Dash

“…Furthermore, our study has incorporated local interpretable model-agnostic explanations to provide comprehensive insights into the predictions made by the k-NN-based architecture.…”
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HIDS-RPL: A Hybrid Deep Learning-Based Intrusion Detection System for RPL in Internet of Medical Things Network by Abdelwahed Berguiga, Ahlem Harchay, Ayman Massaoudi

“…The suggested model, designated HIDS-RPL, results from the hybridization of the Convolutional Neural Network (CNN) for feature extraction and the Long Short Term Memory neural network (LSTM), typically employed for sequence data prediction. We evaluate the proposed algorithm to detect intrusions using the benchmark CIC-DDoS2019 dataset. …”
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MICROCIRCULATORY DISORDERS IN PATIENTS WITH ACUTE CORONARY SYNDROME by Sergey S. Krutitsky, Georgiy P. Plotnikov, Irina N. Sizova, Damir M. Galimzyanov, Dmitriy L. Shukevich, Evgeniy V. Grigoriev

“…Conclusions: Microcirculation parameters can be included in the diagnostic algorithm for ACS in patients with low cardiac output in order to predict cardiogenic shock and multiple organ failure. …”
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Crashworthiness and optimization for foam-filled multi-layer composite lattice structures by Jiye Chen, Wangwang He, Hai Fang, Yong Zhuang, Zhixiong Zhang, Yufeng Zhao

“…Additionally, the equivalent compressive modulus and compressive strength of the FMCLSs were predicted using a rule of mixtures.…”
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Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits by Yun Zhao, Yang Li, Xing Xu

“…Blueberries, as one of the more economically rewarding fruits in the fruit industry, play a significant role in fruit detection during their growing season, which is crucial for orchard farmers’ later harvesting and yield prediction. Due to the small size and dense growth of blueberry fruits, manual detection is both time-consuming and labor-intensive. …”
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An object-based and Lagrangian view on an intense hailstorm day in Switzerland as represented in COSMO-1E ensemble hindcast simulations by K. P. Brennan, M. Sprenger, A. Walser, M. Arpagaus, H. Wernli

“…A tracking algorithm that facilitates object-based analysis of the simulated hailstorms is introduced. …”
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APPLICATION OF THE SUPPORT VECTOR MACHINE, LIGHT GRADIENT BOOSTING MACHINE, ADAPTIVE BOOSTING, AND HYBRID ADABOOST-SVM MODEL ON CUSTOMERS CHURN DATA by Felice Elena, Robyn Irawan, Benny Yong

“…In order to classify and predict churning customers, machine learning techniques are required to build the classifier model. …”
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Synergistic Matching and Influencing Factors of Grain Production and Cropland Net Primary Productivity in the Black Soil Region of Northeast China by Quanxi Wang, Jun Ren, Maomao Zhang, Hongjun Sui, Xiaodan Li

“…This study analyzed the spatial–temporal mismatch characteristics of grain production and cropland net primary productivity (CNPP) using the gravity center model, spatial autocorrelation analysis, and spatial mismatch index (SMI), and identified the spatial heterogeneity and prediction–response relationships of influencing factors based on a geographically and temporally weighted regression (GTWR) model and boosted regression tree (BRT) machine learning algorithm. …”
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Investigating the Nonlinear Relationship Between the Built Environment and Urban Vitality Based on Multi-Source Data and Interpretable Machine Learning by Wenhao Liu, Zhen Yang, Chen Gui, Gen Li, Hongyi Xu

“…In this study, we investigate the potential non-linear interactions between the built environment and urban vitality by employing an interpretable spatial machine learning framework that integrates the XGBoost model with the SHapley Additive exPlanations (SHAP) algorithm. Additionally, we analyze the determinants of urban vitality across both micro and macro-scales using multi-source data, semantic segmentation models, and street view imagery. …”
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Physicochemical profiling and ranking of parkinson’s disease drugs through QSPR and Fuzzy TOPSIS analysis by YuLan Chen, Abdul Rauf, Aqsa Shafique, Fairouz Tchier, Adnan Aslam, Keneni Abera Tola

“…Molecular structures were encoded as adjacency matrices using MATLAB 2017, and six Sombor index variants—computed via a custom Maple 2020 algorithm—served as topological descriptors for QSPR modeling. …”
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Unveiling the immune microenvironment of complex tissues and tumors in transcriptomics through a deconvolution approach by Shu-Hwa Chen, Bo-Yi Yu, Wen-Yu Kuo, Ya-Bo Lin, Sheng-Yao Su, Wei-Hsuan Chuang, I.-Hsuan Lu, Chung-Yen Lin

“…The output from DOCexpress_fastqc is seamlessly formatted with mySORT, a web application that employs a deconvolution algorithm to determine the immune content across 21 cell subclasses. …”
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A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation by Kaihua Yao, Xinyu Yan, Xiling Mao, Mengwei Li, Xiao Li, Ziyu Lian, Yuxiang Han

“…The novelty of the model stems from the application of the IDBO algorithm, which incorporating Circle chaotic mapping, the Golden sine strategy, and the Levy flight strategy, for hyper-parameter optimization. …”
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Characterizing Wake Behavior of Adaptive Aerodynamic Structures Using Reduced-Order Models by Kyan Sadeghilari, Aditya Atre, John Hall

“…The previous study used a genetic algorithm to obtain nine TAD shapes that maximized aerodynamic efficiency in Region 2. …”
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THE TASK OF MINIMAX ADAPTIVE MANAGEMENT OF INNOVATIVE PROCESSES AT AN ENTERPRISE WITH RISK ASSESSMENT by Vitalina Babenko, Elena Alisejko, Zoya Kochuyeva

“…The result of the research is a recurrent algorithm which reduces the initial multi-step task to the implementation of finite sequence of tasks of minimax software management of EIP. …”
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Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) by Montaser N.A. Ramadan, Mohammed A.H. Ali, Shin Yee Khoo, Layth Hamad, Mohammad Alkhedher

“…The results show that the XGBoost instantaneous classification algorithm continuously beat the competition, obtaining an astounding success rate of 97 percent in predicting and differentiating between the four oil classes. …”
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Uncovering Antibiotic Resistance Genes in Marmara Sea Mucilage via Shotgun Metagenome Sequencing by Gizem Karış, Herdem Aslan, Mehmet Hora, Aycan Gundogdu

“…The DNA data was analyzed using a de novo approach with IDBA-UD assembler, BWA-mem2, and Prodigal gene prediction algorithm. For ARG profiling, gene clusters were aligned to the CARD (The Comprehensive Antibiotic Resistance Database) using BlastX. …”
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Mechanical Properties and Fracture Surface Morphology of Quartz Sandstone Under Triaxial Shear by Zhinan LIN, Shihong FENG, Jiaquan WANG, Qiang ZHANG, Haifeng LONG

“…The present results are very important for predicting the triaxial shear strength of rock under complex stress and for evaluating the stability of slopes in rock engineering and optimizing the design schemes for supporting them.…”
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