Architecture of an automated program complex based on a multiple kernel svm classifier for analyzing malicious executable files by Alan Nafiiev, Andrii Rodionov

“…This article presents the development and architecture of an automated program complex designed to identify and analyze malicious executable files using a classifier based on a multiple kernel support vector machine (SVM). Goal. The aim of the work is to create an automated system that enhances the accuracy and efficiency of malware detection by combining static and dynamic analysis into a single framework capable of processing large volumes of data with optimal time expenditure. …”
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Classification of Melanoma and Nevus in Digital Images for Diagnosis of Skin Cancer by Muhammad Qasim Khan, Ayyaz Hussain, Saeed Ur Rehman, Umair Khan, Muazzam Maqsood, Kashif Mehmood, Muazzam A. Khan

“…Support vector machine (SVM) is utilized for the classification of skin cancer into melanoma and nevus. …”
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SCIENTIFIC PARADIGM SHIFT AS THE BACKGROUND OF LANGUAGE EDUCATION by V. D. Tabanakova

“…At a time of global changes in domestic higher education the linguistic education is considered to be a display of the convergence process of natural sciences, technology and humanities. …”
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American Sign Language Recognition Model Using Complex Zernike Moments and Complex-Valued Deep Neural Networks by Selda Bayrak, Vasif Nabiyev, Celal Atalar

“…In the developed model, complex Zernike moments are used to obtain the feature vector of character images. A complex-valued deep neural network (CVDNN) capable of processing the feature vector composed of complex numbers across layers is also developed. …”
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Using machine learning to assist decision making in the assessment of mental health patients presenting to emergency departments by Oliver Higgins, Rhonda L. Wilson, Stephan K. Chalup

“…Methods The study utilised existing data from January 2016 to December 2021. After data pre-processing, an exploratory analysis revealed the non-linear nature of the dataset. …”
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Innovative segmentation technique for aerial power lines via amplitude stretching transform by Pengfei Xu, Nor Anis Asma Sulaiman, Yafei Ding, Jiangwei Zhao

“…For this reason, this paper designs a pure amplitude stretching kernel function to form a Fourier amplitude vector field and uses this amplitude vector field to implement the stretching transformation of the amplitude field of the aerial power line image, so that the angular field after the Fourier inverse transformation can better react to the spatial domain line targets, and finally, after the Relative Total Variation (RTV) processing, the power line can be well detected. …”
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, and -like MO-1 infection in the brain of a child with seizures, mycotoxin exposure and suspected Rasmussen's encephalitis by Edward B. Breitschwerdt, Ricardo G. Maggi, Cynthia Robveille, Emily Kingston

“…Background In conjunction with more sensitive culture and molecular diagnostic testing modalities, simultaneous or sequential infection with more than 1 vector borne zoonotic pathogen is being increasingly documented in human patients. …”
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Performance Comparison of 10 State-of-the-Art Machine Learning Algorithms for Outcome Prediction Modeling of Radiation-Induced Toxicity by Ramon M. Salazar, PhD, Saurabh S. Nair, MS, Alexandra O. Leone, MBS, Ting Xu, PhD, Raymond P. Mumme, BS, Jack D. Duryea, BA, Brian De, MD, Kelsey L. Corrigan, MD, Michael K. Rooney, MD, Matthew S. Ning, MD, Prajnan Das, MD, Emma B. Holliday, MD, Zhongxing Liao, MD, Laurence E. Court, PhD, Joshua S. Niedzielski, PhD

“…The training set was used to create and tune the model, and the test set served to assess it by calculating performance metrics. This process was repeated 100 times by each algorithm for each data set. …”
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A novel mechanism of sperm midpiece epididymal maturation and the role of CCDC112 in sperm midpiece formation and establishing an optimal flagella waveform by Maddison L. Graffeo, Joseph Nguyen, Farin Yazdan Parast, Jessica E. M. Dunleavy, Denis Korneev, Hongyi Yang, Hidenobu Okuda, Anne E. O’Connor, Donald F. Conrad, Reza Nosrati, Brendan J. Houston, Moira K. O’Bryan

“…We further unveil a previously unrecognized process of epididymal mitochondrial sheath maturation. …”
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The miR‐6779/XIAP axis alleviates IL‐1β‐induced chondrocyte senescence and extracellular matrix loss in osteoarthritis by Zongchao Li, Aonan Dai, Xiaoxiang Fang, Kexing Tang, Kun Chen, Peng Gao, Jingyue Su, Xin Chen, Shengwu Yang, Zhenhan Deng, Liangjun Li

“…MicroRNAs have been confirmed to regulate different cellular processes. They contribute to OA pathology and may help to identify novel biomarkers and therapies for OA. …”
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Machine-Learning-Based Integrated Mining Big Data and Multi-Dimensional Ore-Forming Prediction: A Case Study of Yanshan Iron Mine, Hebei, China by Yuhao Chen, Gongwen Wang, Nini Mou, Leilei Huang, Rong Mei, Mingyuan Zhang

“…Combined with spectral and elemental analysis, the universality of alteration features such as chloritization and carbonation, which are closely related to the mineralization process, was further verified. (3) Based on the spectral and elemental grade data of rock and mineral samples, a training model for ore grade–spectrum correlation was constructed using Random Forests, Support Vector Machines, and other algorithms, with the SMOTE algorithm applied to balance positive and negative samples. …”
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High-Precision Phenotyping in Soybeans: Applying Multispectral Variables Acquired at Different Phenological Stages by Celí Santana Silva, Dthenifer Cordeiro Santana, Fábio Henrique Rojo Baio, Ana Carina da Silva Cândido Seron, Rita de Cássia Félix Alvarez, Larissa Pereira Ribeiro Teodoro, Carlos Antônio da Silva Junior, Paulo Eduardo Teodoro

“…Machine learning (ML) methods, together with the advent of demand for remotely piloted aircraft available on the market in the recent decade, have been conducive to remote sensing data processes. The objective of this work was to evaluate the best ML and input configurations in the classification of agronomic variables in different phenological stages. …”
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Prediction of digestible energy requirement in growing finishing stage of pigs using machine learning models by Nibas Chandra Deb, Jayanta Kumar Basak, Sijan Karki, Elanchezhian Arulmozhi, Dae Yeong Kang, Niraj Tamrakar, Eun Wan Seo, Junghoo Kook, Myeong Yong Kang, Hyeon Tae Kim

“…Proper management of digestible energy (DE) is crucial for maintaining pig health, promoting growth, and facilitating reproduction by supporting essential biological processes. Therefore, this study sought to predict the digestible energy requirement (DER) in the growing-finishing phase of pigs, where four machine learning (ML) models: multiple linear regression (MLR), support vector regression (SVR), random forest regression (RFR), and multilayer perceptron (MLP) were applied across four datasets, with the input parameters including body weight of pigs (BW), inside temperature (IT), inside relative humidity (IRH), and inside CO2 concentration (ICO2) of pig barns. …”
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THE INFLUENCE OF HUMAN LEUKEMIA DIFFERENTIATION FACTOR ON ABILITY OF BLOOD CELLS TO PRODUCE IL-1β, IL-1ra AND IL-8 IN CHRONIC ATROPHIC GASTRITIS, ADENOMAS AND ADENOCARCINOMAS OF TH... by A. V. Sosnina, E. S. Mikhailova, D. V. Morozov, A. I. Autenshlyus, N. A. Varaksin, L. A. Shpagina, E. E. Vorobyeva, T. V. Rakitina, V. M. Lipkin

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Integrated Assessment of the Quality of Functioning of Local Electric Energy Systems by Waldemar Wójcik, Petro Lezhniuk, Cezary Kaczmarek, Viacheslav Komar, Iryna Hunko, Nataliia Sobchuk, Laura Yesmakhanova, Zhazira Shermantayeva

“…The integral indicator of the functioning of complex systems is based on a combination of the theory of Markov processes and the criterion method of similarity theory. …”
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Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models—an empirical analysis of Indian patient liver disease datasets by Ritu Rani, Garima Jaiswal, Nancy, Lipika, Shashi Bhushan, Fasee Ullah, Prabhishek Singh, Manoj Diwakar, Manoj Diwakar

“…IntroductionThe liver is one of the vital organs of human body that performs some of the most crucial biological processes such as protein and biochemical synthesis, which is required for digestion and cleansing. …”
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Modeling Stock High-Low Price Range: Fractional Cointegrating VAR Approach (FCVAR) by Elham Farzanegan

“…ConclusionThe empirical results show that, unlike the return, which is stationary and unpredictable, the range prices have characteristics of the long-memory processes, falling into non-stationary and stationary levels with mean-reverting behavior. …”
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Digital mapping of soil erodibility factor in response to land use change using machine learning models by Wudu Abiye, Orhan Dengiz

“…The resulting maps provide a valuable baseline for land use planning, natural resource management, and decision-making processes.…”
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Physiological, environmental, and life-history drivers of haemosporidian infections in non-passerine birds from a rehabilitation center by Lis Marques de Carvalho e Vieira, Victor Aguiar de Souza Penha, Kevin J. McGraw, Amanda Vitória Dornelas da Silva, Erika Martins Braga

“…IntroductionPathogens and parasites play a crucial role in shaping ecological and evolutionary processes, influencing the behavior, physiology, and survival of their hosts across diverse ecosystems. …”
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Experience of Hypoxic Conditioning in Rehabilitation Programs for Patients with Chronic Occupational Lung Diseases: a Pilot Study by Xinliang Zhang, Evgeny Е. Achkasov, Elena N. Dudnik, Olga I. Rumyantseva, Oleg S. Glazachev

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