Custodial Naturalness by Thede de Boer, Manfred Lindner, Andreas Trautner

“…The cosmological evolution features a strongly supercooled phase transition implying that consequences of Custodial Naturalness may also be tested by gravitational wave observatories.…”
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Support Vector Machine Berbasis Feature Selection Untuk Sentiment Analysis Kepuasan Pelanggan Terhadap Pelayanan Warung dan Restoran Kuliner Kota Tegal by Oman Somantri, Dyah Apriliani

“…Selisih rata-rata yang dihasilkan setelah dilakukannya optimasi SVM dengan feature selection adalah 2,51% kenaikan tingkat akurasinya. …”
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Analysis of Plastic Zone and Pressure Variance Features of Surrounding Rock of High-Altitude Macker Tunnel: A Case Study in Jiangluling Macker Tunnel in Qinghai by Xiaojun Ma, Hongyan Guo, Juyi Hu, Shuang Cai, Liang Cheng, Danfeng Zhang

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Development of an Algorithm for a National Microprocessor-Based Centralization System With a Modular Architecture KZ-MPC-MA Featuring Advanced Intelligent Control Functions by Kanibek M. Sansyzbay, Yelena A. Bakhtiyarova, Teodor Iliev, Gennady S. Patokin, Laura T. Tasbolatova, Daniyar B. Sagmedinov

“…The authors also present the architecture and key features of the developing microprocessor-based system. …”
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FORENSIC COMPARISON OF FACIAL IMAGES OF DOPPELGÄNGERS by Aleksandr M. Zinin, Zhanna G. Berger

“…The paper examines the problem of forensic examination of doppelgängers' portraits for dominant matching features. …”
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Features of angina development across age groups: data from the World Health Survey (WHS) and the WHO Study on global AGEing and adult health (SAGE) by T. M. Maksimova, V. B. Belov, N. P. Lushkina

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The Problem of Assessing the Extent of Somatic Comorbidity in Patients with Major Depressive Disorder and Bipolar Disorder: Metabolic Syndrome, Cardiovascular Diseases, and Type II... by V. E. Makeenko, D. S. Shumskaia, A. O. Kibitov

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View on the problem of diabetic nephropathy in children and adolescents with type 1 diabetes mellitus: the role of renin-angiotensin-aldosterone system (literature review) (part 1) by K. V. Skobeleva, L. V. Tyrtova, I. L. Nikitina, A. S. Olenev

“…The relevance and importance of this problem led to the active study by scientists of various pathogenic aspects of damage to the structure of the kidneys and microvascular bed. …”
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Reference crust-mantle density contrast beneath Antarctica based on the Vening Meinesz-Moritz isostatic inverse problem and CRUST2.0 seismic model by Robert Tenzer, Mohammad Bagherbandi

“…We estimate the crust-mantle (Moho) density contrast beneath Antarctica based on solving the inverse problem of isostasy and using the constraining information from the seismic global crustal model (CRUST2.0). …”
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AI-powered smart emergency services support for 9-1-1 call handlers using textual features and SVM model for digital health optimization by Afraa Attiah, Manal Kalkatawi

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A high-resolution remote sensing land use/land cover classification method based on multi-level features adaptation of segment anything model by Hui Yang, Zhipeng Jiang, Yaobo Zhang, Yanlan Wu, Heng Luo, Peng Zhang, Biao Wang

“…To address this problem, we propose an innovative network model named multi-level feature adaptation-segment anything Model (MLFA-SAM). …”
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Machine Learning in Baseball Analytics: Sabermetrics and Beyond by Wenbing Zhao, Vyaghri Seetharamayya Akella, Shunkun Yang, Xiong Luo

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Early Prediction of Cardio Vascular Disease (CVD) from Diabetic Retinopathy using improvised deep Belief Network (I-DBN) with Optimum feature selection technique by T. K. Revathi, B. Sathiyabhama, S Kaliraj, Vidhushavarshini Sureshkumar

“…However, there are many works have been carried out on classification of the disease but they focused less on feature selection and increasing the accuracy of the model. …”
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A multistrategy improved hunger games search algorithm by Qiu Yihui, Zhang Xinqiang, Li Ruoyu, Li Dongyi, Xia Feihan

“…Moreover, a binary variant, BMHGS_V3, using sigmoid transformation, attains an average classification accuracy of 92.3% on ten UCI datasets for feature selection tasks. The proposed MHGS algorithm provides a novel and effective framework for solving complex optimization problems, demonstrating significant theoretical and practical value in the field of computational intelligence.…”
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GrotUNet: a novel leaf segmentation method by Hongfei Deng, Hongfei Deng, Bin Wen, Bin Wen, Cheng Gu, Yingjie Fan

“…The former two make full use of the design ideas of GoogLeNet parallel branching and Resnet residual connectivity, while the latter further mines the fine-grained semantic information distributed in the feature space on the feature map after extraction by the WGRblock module to make the feature expression richer. …”
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Oil well productivity capacity prediction based on support vector machine optimized by improved whale algorithm by Kuiqian Ma, Chunxin Wu, Yige Huang, Pengfei Mu, Peng Shi

“…Aiming at these problems, a well productivity prediction method based on machine learning algorithm was proposed. …”
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Toward Intelligent Financial Advisors for Identifying Potential Clients: A Multitask Perspective by Qixiang Shao, Runlong Yu, Hongke Zhao, Chunli Liu, Mengyi Zhang, Hongmei Song, Qi Liu

“…Then, we propose a Multitask Feature Extraction Model (MFEM), which can leverage useful information contained in these related tasks and learn them jointly, thereby solving the two problems simultaneously. …”
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A Hybrid Deep Learning–Based Feature Selection Approach for Supporting Early Detection of Long-Term Behavioral Outcomes in Survivors of Cancer: Cross-Sectional Study by Tracy Huang, Chun-Kit Ngan, Yin Ting Cheung, Madelyn Marcotte, Benjamin Cabrera

“…Our approach holistically has higher F1, precision, and recall scores compared to existing feature selection methods. The models in this study select several significant clinical and socioenvironmental variables as risk factors associated with the development of behavioral problems in young survivors of acute lymphoblastic leukemia. …”
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Psychological characteristics of Far North patients with arterial hypertension by V. A. Lobova, A. A. Buganov

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Research onconvolutional neural network for reservoir parameter prediction by You-xiang DUAN, Gen-tian LI, Qi-feng SUN

“…As the branch of artificial intelligence,artificial neural network solved many difficult practical problems in pattern recognition and classification prediction field successfully.However,they cannot learn the feature from networks.In recent years,deep learning becomes more and more advanced,but the research on the field of geological reservoir pa-rameter prediction is still rare.A method to predict reservoir parameters by convolutional neural network was presented,which can not only predict reservoir parameters accurately,but also get features of the geological reservoir.The study es-tablished the convolutional neural network model.Results show that the convolutional neural network can be used for reservoir parameter prediction,and get high prediction precision.Moreover,convolutional features from convolutional neural network provided important support for geological modeling and logging interpretation.…”
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