Borehole‐Based Interval Kriging for 3D Lithofacies Modeling by Yuqi Song, Frank T.‐C. Tsai

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Three-dimensional design, simulation and optimization of a centrifugal compressor impeller with double-splitter blades by Mohammadjavad Tasharrofi, Mojtaba Heidarian Shahri, Ali Madadi

“…After the emergence of turbo-machines in the industrial field, researchers have always been seeking to increase their efficiency. …”
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A Hybrid Deep Learning–Based Approach for Visual Field Test Forecasting by Ashkan Abbasi, PhD, Sowjanya Gowrisankaran, PhD, Wei-Chun Lin, MD, PhD, Xubo Song, PhD, Bhavna Josephine Antony, PhD, Gadi Wollstein, MD, Joel S. Schuman, MD, Hiroshi Ishikawa, MD

“…Subjects and Controls: A total of 1750 subjects (healthy and glaucoma patients) with 19 437 Humphrey VF (24-2 Swedish Interactive Threshold Algorithm) tests collected from longitudinal glaucoma cohorts at the University of Pittsburgh and New York University. …”
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Photovoltaic Module Fault Detection Technology Based on Remote Sensing Technology and Deeplabv3+ Model by Xiaowei Xu, Mingxian Liu, Yongjie Nie, Ke Wang, Wenhua Xu

“…Combining remote sensing technology with Deeplabv3+ model, fast and accurate photovoltaic module fault detection can be achieved. The research results indicated that bilateral filtering and gamma filtering algorithms showed superior performance in testing, with the highest indicator evaluation results. …”
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Review of optimization modeling and solution of long-distance natural gas pipeline network by Peng ZHOU, Qi WEI

“…Presently, the modeling methods based on the physical attributes are mainly researched for the optimization model of natural gas pipeline networks in China. …”
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Pre-modulated multi-coset sampling system by Huang Zhen, Bai Zhengyao

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Error Analysis and Compensation of 3‒PTT Parallel Robot by CHEN Mingfang, LIANG Hongjian, WEI Songpo, HE Chaoyin

“…Thus, the algorithm is more feasible. In addition, to improve the efficiency of the aforementioned error compensation algorithm, the standard particle swarm optimization algorithm is further enhanced by integrating the dynamic inertia weight value and dynamic learning factor, thus overcoming the problems of precocious convergence to a local optimum and slow convergence in the later iteration of the standard particle swarm optimization algorithm. …”
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Structure and dynamics analysis of brain functional hypernetworks based on the null models by Chen Cheng, Yao Li, Chunyan Wang, Yanli Yang, Hao Guo

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Managing IoT and Mass Communication in 6G: Strategies for Low Latency Real-Time Applications through Proximity-Based Request Handling by Fariborz Rasouli

“…Utilizing DBSCAN clustering facilitates the preemptive identification of potential user congestion and traffic, enabling the deployment of the outlined strategies to mitigate service degradation and maintain data transfer rates. This research explores the formulation of a prioritized scheduling system for requests, wherein, as per the DBSCAN algorithm, real-time applications are accorded elevated execution precedence.…”
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Stronger compact representations of object trajectories by Adrián Gómez-Brandón, Gonzalo Navarro, José R. Paramá, Nieves R. Brisaboa, Travis Gagie

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Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

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Adversarial attack and defense on graph neural networks: a survey by Jinyin CHEN, Dunjie ZHANG, Guohan HUANG, Xiang LIN, Liang BAO

“…For the numerous existing adversarial attack and defense methods on GNN, the main adversarial attack and defense algorithms of GNN were reviewed comprehensively, as well as robustness analysis techniques.Besides, the commonly used benchmark datasets and evaluation metrics in the security research of GNN were introduced.In conclusion, some insights on the future research direction of adversarial attacks and the trend of development were put forward.…”
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Combined use of non-steroidal anti-inflammatory drugs and symptomatic slow-acting drugs in musculoskeletal diseases by A. E. Karateev, A. M. Lila, V. A. Parfenov, M. N. Khokhlova, M. A. Strakhov

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A Progressive Clustering Approach for Buildings Using MST and SOM with Feature Factors by Tianliang Zhang, Xiaoji Lan, Jianhua Feng

“…To address the challenges in current research on spatial clustering algorithms for buildings in topographic maps—namely, their limited ability to effectively accommodate diverse application scenarios, including dense and regular urban environments, sparsely and irregularly distributed rural areas, and urban villages with complex structures—this paper introduces an innovative progressive clustering algorithm framework. …”
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A systematic mapping to investigate the application of machine learning techniques in requirement engineering activities by Shoaib Hassan, Qianmu Li, Khursheed Aurangzeb, Affan Yasin, Javed Ali Khan, Muhammad Shahid Anwar

“…The authors aim to investigate the research trends, main RE activities, ML algorithms, and data sources that were studied during this period. …”
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Development and validation of a machine learning model for online predicting the risk of in heart failure: based on the routine blood test and their derived parameters by Jianchen Pu, Yimin Yao, Xiaochun Wang

“…In addition, eight different machine learning algorithms were applied for prediction, and the prediction performances of these algorithms were comprehensively evaluated using the receiver operating characteristic curve, area under the curve (AUC), calibration curve analysis, and decision curve analysis and confusion matrix.ConclusionsUsing LASSO regression analysis, leukocyte, neutrophil, red blood cell, hemoglobin, platelet, and monocyte-to-lymphocyte ratios were identified as risk factors for HF. …”
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THE EUROPEAN SOCIETY FOR CLINICAL AND ECONOMIC ASPECTS OF OSTEOPOROSIS AND OSTEOARTHRITIS (ESCEO) ALGORITHM FOR THE MANAGEMENT OF KNEE OSTEOARTHRITIS IS APPLICABLE TO RUSSIAN CLINI... by L. N. Denisov, E. S. Tsvetkova, G. Sh. Golubev, O. V. Bugrova, I. S. Dydykina, A. I. Dubikov, L. V. Menshikova, L. K. Peshekhonova, A. P. Rebrov, A. N. Torgashin, E. A. Trofimov, S. P. Yakupova, E. V. Zonova, O. Brewer, C. Cooper, J. Reginster, L. A. Knyazeva

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Diagnosis methods for pancreatic cancer with the technique of deep learning: a review and a meta-analysis by Yuanbo Bi, Dongrui Li, Ruochen Pang, Chengxv Du, Da Li, Xiaoyv Zhao, Haitao Lv

“…Inclusion criteria were studies involving PDAC patients, using deep learning algorithms for diagnosis evaluation, using histopathological results as the reference standard, and having sufficient data. …”
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Identification and land-Environment analysis of centralized photovoltaic stations in the arid northwest region of China by Yiyang Chen, Li Zhang, Min Yan, Yin Wu, Yuqi Dong, Wei Shao, Qinglan Zhang

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Groundwater estimation and determination of its probable recharge source in the Lower Swat District, Khyber Pakhtunkhwa, Pakistan, using analytical data and multiple machine learni... by Imran Ahmad, Ibrar Ul Haq, Mansoor Ahmad, Iram Gul, Mursaleen Khan, Khushnuma Khushnuma, Ubaid Ullah, Maqsood Ur Rehman, Mohamed Metwaly

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