Analysis of the Impact of the Stylometric Characteristics of Different Levels for the Verification of Authors of the Prose by Alla Mikhajlovna Manakhova, Nadezhda Stanislavovna Lagutina

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Lexical associations can characterize clinical documentation trends related to palliative care and metastatic cancer by Hao Yuan Yang, Karthik Raghunathan, Eric Widera, Steven Z. Pantilat, Teva Brender, Timothy A. Heintz, Edie Espejo, John Boscardin, Hunter Mills, Albert Lee, Jacob Berchuck, Julien Cobert

“…We used word2vec to model language numerically as vectors. Relational data between vectors was captured using cosine similarity. …”
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Textual similarity for legal precedents discovery: Assessing the performance of machine learning techniques in an administrative court by Hugo Mentzingen, Nuno António, Fernando Bacao, Marcio Cunha

“…Leveraging the capabilities of natural language processing (NLP) and machine learning (ML), our study delves into the potential of automation in identifying similar cases indicative of precedents. …”
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AE-XGBoost: A Novel Approach for Machine Tool Machining Size Prediction Combining XGBoost, AE and SHAP by Mu Gu, Shuimiao Kang, Zishuo Xu, Lin Lin, Zhihui Zhang

“…The subsequent SHAP analysis reveals the importance and interrelationship of features and provides a reliable decision support system for machine tool processing personnel, helping to improve processing quality and achieve intelligent manufacturing.…”
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The essence, features and stages in the development of urbanization by L.V. Sergienko, K.M. Voitsitska

“…It is established that urbanization is a complex global process that influences the socio-economic development of regions, and its characteristic features are defined. …”
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Prediction of Hydrogen Production from Solid Oxide Electrolytic Cells Based on ANN and SVM Machine Learning Methods by Ke Chen, Youran Li, Jie Chen, Minyang Li, Qing Song, Yushui Huang, Xiaolong Wu, Yuanwu Xu, Xi Li

“…We developed two models using artificial neural networks (ANNs) and support vector machine (SVM) to predict hydrogen production. …”
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Dynamic neutrosophic cognitive map with improved cuckoo search algorithm (DNCM-ICSA) and ensemble classifier for rheumatoid arthritis (RA) disease by B. Chithra, R. Nedunchezhian

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Designing ISAR Lab Experiments for EO-SAR ATR by Michael Andrew Saville, Jacob D. Compaleo, Heather L. Judd, Jared Smith, Paul Sotirelis

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COMPARISON OF SPACE IMAGES OF A SURFACE OF EARTH TO A STANDARD OF A DIGITAL DISTRICT MAP by A. A. Zalatoi, D. I. Novikau

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Theoretical Proposals for Improving the Noise Immunity of Receiving Multi-Position Signals in Channels with Variable Parameters by S. V. Dvornikov, A. V. Pshenichnikov, A. F. Kryachko, M. R. Bibarsov, G. S. Bibarsova

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Classical Gasses with Singular Densities by Luca Di Persio, Yuri Kondratiev, Viktorya Vardanyan

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Realization of Three-level SVPWM Algorithm Based on FPGA by LIN Xin, KOU Shuren, YANG Fan

“…Three-levels space vector pulse width modulation(SVPWM) topological structure and algorithm was introduced , and its realization with FPGA was described. …”
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Data augmentation for dense passage retrieval using corpus-passage frequency-based token deletion by A-Seong Moon, Kyumin Kim, Jaesung Lee

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Comparative Analysis of Machine Learning Algorithms With Advanced Feature Extraction for ECG Signal Classification by Tanuja Subba, Tejbanta Chingtham

“…However, its availability has been restricted, especially in contexts with limited resources, due to the cost associated with conventional ECG signal processing equipment. The importance of ECG signal processing classification for improving early diagnoses in clinical and remote monitoring contexts is highlighted here. …”
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Concept of natural genome reconstruction. Part 3. Analysis of changes in the amount of telomeric DNA in colony cells as a new amplified feature that arose during the processing of... by V. S. Ruzanova, S. G. Oshikhmina, G. S. Ritter, E. V. Dolgova, S. S. Kirikovich, E. V. Levites, Y. R. Efremov, T. V. Karamysheva, A. G. Bogomolov, M. I. Meschaninova, A. L. Mamaev, O. S. Taranov, S. V. Sidorov, S. D. Nikonov, O. Y. Leplina, A. A. Ostanin, E. R. Chernykh, N. A. Kolchanov, A. S. Proskurina, S. S. Bogachev

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Equi‐MOI ratio for rapid baculovirus‐mediated multiprotein co‐expression in insect cells integrating selenomethionine for structural studies by Andrej Bitala, Mário Benko, Marek Nemčovič, Ivana Nemčovičová

“…Proteins often co‐exist as multicomponent assemblies, making their co‐expression essential in recombinant production processes. The baculovirus expression vector system is commonly used to produce recombinant multiprotein complexes mostly for structural and functional studies. …”
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Maize Kernel Broken Rate Prediction Using Machine Vision and Machine Learning Algorithms by Chenlong Fan, Wenjing Wang, Tao Cui, Ying Liu, Mengmeng Qiao

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Artificial intelligence for severity triage based on conversations in an emergency department in Korea by Jae Won Seo, Sung-Joon Park, Young Jae Kim, Jung-Youn Kim, Kwang Gi Kim, Young-Hoon Yoon

“…Based on the area under the receiver operating characteristic curve (AUROC) values, the support vector machine achieved the best performance among the term frequency-inverse document frequency-based conventional machine learning models with an AUROC of 0.764 (95% CI 0.019). …”
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Kernel to computation: identifying optimal feature set for red rice classification by Suma D, Narendra V G, Darshan Holla M, Shreyas, Raviraja Holla M

“…The integration of size, shape, and texture features yielded the highest average accuracy across the models, with K-Nearest Neighbours achieving 98.67 % accuracy and Support Vector Machine reaching 97.34 % accuracy with the size and shape combination. …”
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SVM directed machine learning classifier for human action recognition network by Dharmanna Lamani, Pramod Kumar, A Bhagyalakshmi, J. Maria Shanthi, Lakshmana Phaneendra Maguluri, Mohammad Arif, C Dhanamjayulu, Sathish Kumar. K, Baseem Khan

“…After that, these features are entered into the Support Vector Machine (SVM) classifier in order to accomplish action recognition. …”
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