Neighborhood Information Aggregation and Multi-View Feature Extraction-Based Contrastive Graph Clustering by Liulong Yao, Jinrong Cui, Yazi Xie, Chengli Sun

“…Extensive experiments on five benchmark datasets show that our proposed method outperforms most other clustering algorithms.…”
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An integrated global and local thresholding method for segmenting blood vessels in angiography by Min Zhang, Jun Wang, Xinhua Cao, Xiaoyin Xu, Jie Zhou, Huai Chen

“…We tested the method on angiography and compared it with several widely used algorithms. Results: In total, there were 72 DSA images in our dataset. …”
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Deepmol: an automated machine and deep learning framework for computational chemistry by João Correia, João Capela, Miguel Rocha

“…Despite its potential to revolutionize the field, researchers are often encumbered by obstacles, such as the complexity of selecting optimal algorithms, the automation of data pre-processing steps, the necessity for adaptive feature engineering, and the assurance of model performance consistency across different datasets. …”
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The intelligent fault identification method based on multi-source information fusion and deep learning by Dashu Guo, Xiaoshuang Yang, Peng Peng, Lei Zhu, Handong He

“…By training samples and applying fusion algorithms, the spectral, topographic, geomorphic, and structural features are integrated to enhance the morphological features information of faults. …”
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Spectral Variation and Corresponding Changing Mechanism of Suspended Particulate Material Absorption in Poyang Lake during Flood Periods by Yuandong Wang, Xibin You, Lianfang Yu, Lihong Meng, Xiangming Xu, Guangxu Liu

“…Evidence also presented that the nonlinear dependency of specific phytoplankton particulate absorption on pigment concentration for various trophic statuses in different periods could be unstable due to relative contributions of the package effect and accessory pigments; this could bring uncertainties to the parameterization of optical models and remote sensing algorithms proposed for accurate applications in lake water environment monitoring.…”
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Dynamic Response Prediction of Railway Bridges Considering Train Load Duration Using the Deep LSTM Network by Sui Tan, Xiandong Ke, Zhenhao Pang, Jianxiao Mao

“…Therefore, this study develops a novel framework, combining the train–bridge coupling mechanism and deep learning algorithms to efficiently predict the train-induced bridge responses while considering train load duration. …”
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Best practices and joint calling of the HumanExome BeadChip: the CHARGE Consortium. by Megan L Grove, Bing Yu, Barbara J Cochran, Talin Haritunians, Joshua C Bis, Kent D Taylor, Mark Hansen, Ingrid B Borecki, L Adrienne Cupples, Myriam Fornage, Vilmundur Gudnason, Tamara B Harris, Sekar Kathiresan, Robert Kraaij, Lenore J Launer, Daniel Levy, Yongmei Liu, Thomas Mosley, Gina M Peloso, Bruce M Psaty, Stephen S Rich, Fernando Rivadeneira, David S Siscovick, Albert V Smith, Andre Uitterlinden, Cornelia M van Duijn, James G Wilson, Christopher J O'Donnell, Jerome I Rotter, Eric Boerwinkle

“…., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. …”
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Advanced strategies for the efficient optimization and control of industrial compressed air systems by D. Salomone-González

“…Real-time data transmission, powered by big data algorithms, enables continuous analysis to optimize the overall performance of the compressor plant. …”
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Predicting Quality of Multimedia Experience Using Electrocardiogram and Respiration Signals by Sowmya Vijayakumar, Ronan Flynn, Peter Corcoran, Niall Murray

“…The ML models considered are support vector machines, k-nearest neighbor, and random forest algorithms; the DL models considered are bidirectional long-short-term memory (BLSTM), convolutional neural networks (CNN), and a hybrid model of CNN and BLSTM (CNN-BLSTM). …”
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Real-Time Compression Scheme for Urban Rail Transit Train Operation Data by LI Dexiang, WANG Linmei, WANG Shu

“…The scheme is proved to be effective by the real-time verification test of algorithms and the verification test of the actual train operation data. …”
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Identification of developmental and reproductive toxicity of biocides in consumer products using ToxCast bioassays data and machine learning models by Donghyeon Kim, Siyeol Ahn, Jinhee Choi

“…Using the bioactivity data from these selected assays, we trained machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Decision Tree, and Logistic Regression, on molecular fingerprints (MACCS, Morgan, Layered, RDKit). …”
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Multi-Feature Lightweight DeeplabV3+ Network for Polarimetric SAR Image Classification with Attention Mechanism by Junfei Shi, Shanshan Ji, Haiyan Jin, Yuanlin Zhang, Maoguo Gong, Weisi Lin

“…Experiments are conducted on five real PolSAR data sets, and experimental results demonstrate the proposed method can achieve more precise boundaries and smoother regions than the state-of-the-art algorithms. In this paper, we develop a novel multi-feature learning framework, achieving a fast and effective classification network for PolSAR images.…”
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Design and Analysis of a Serial Manipulator for Pick and Drop Objects for Material Handling at Uiri Metal Forming Workshop. by Behangana, Abert

“…Future recommendations include refining control algorithms, integrating advanced safety features, and exploring innovative materials to improve performance. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Recent research investigations have shown that Machine Learning (ML) algorithms can identify geochemical anomalies associated with mineralization that represent targets for mineral exploration. …”
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Open real-time, non-invasive fish detection and size estimation utilizing binocular camera system in a Portuguese river affected by hydropeaking by Jürgen Soom, Isabel Boavida, Renan Leite, Maria João Costa, Gert Toming, Mairo Leier, Jeffrey A. Tuhtan

“…Nonetheless, employing an automated camera system for underwater monitoring requires that the algorithms function under highly variable environmental conditions, which affect the ability to detect and assess fish size. …”
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A Machine Learning-Based Real-Time Remaining Useful Life Estimation and Fair Pricing Strategy for Electric Vehicle Battery Swapping Stations by Seyit Alperen Celtek, Seda Kul, A. Ozgur Polat, Hamed Zeinoddini-Meymand, Farhad Shahnia

“…The paper evaluates various machine learning algorithms for real-time RUL estimation regarding accuracy, computation time, and memory usage. …”
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An Immune-Related Prognostic Classifier Is Associated with Diffuse Large B Cell Lymphoma Microenvironment by Xiao-Jie Liang, Rui-ying Fu, He-nan Wang, Jing Yang, Na Yao, Xin-di Liu, Liang Wang

“…To assess differences in overall survival between the low- and high-risk groups, we analyzed the tumor microenvironment (TME) and immune infiltration in DLBCL using the ESTIMATE and CIBERSORT algorithms. WGCNA was applied to study the molecular mechanisms explaining the clinical significance of our immune-related classifier and TFs. …”
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The Relationship Between Stiff Knee Gait Runner’s Dystonia and Musculoskeletal Knee Pathology: A Case Series by Jared A. Stowers, Derek S. Day, Steven Jow, Sarah Heins, Euan Forrest, Yonathan M. Assefa, Paige M. Lind, Afreen Mushtaheed, Frances T. Sheehan, Katharine E. Alter

“…Future research should determine the ideal sequence of interventions for RD patients with MSK issues to develop effective, personalized treatment algorithms.…”
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Delirium in tetanus patients: a review of clinical features, pathophysiology, and integrated management strategies by Yanwei Rao, Xinzao Xu, Lijing Chen, Di Wang, Lin Liu, Tingting Jiang, Yang Chen, Yongjie Wang

“…Large-scale prospective studies are essential to validate proposed management algorithms and refine evidence-based treatment protocols. …”
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Ethical and Legal Challenges of Implementing AI in Science and Math Education in Central Asia by Dilfuza M.Makhmudova, Xilola R. Sharipova, Nosirjon K. Hojiyev, Azamat E.Ergashev, Yulduzknon Kh.Satvaldieva, Khosiyat U.Mamatkulova, Egambergan M. Khudoynazarov

“…Qualitative interviews (N = 18) uncovered recurring themes such as lack of legal frameworks, teacher autonomy dilemmas, and algorithmic bias in grading systems. The study highlights a critical need for policy interventions and professional development targeting ethical and legal dimensions of AIEd in post-Soviet education systems. …”
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