FTG: Score-based black-box watermarking by fragile trigger generation for deep model integrity verification by Heng Yin, Zhaoxia Yin, Zhenzhe Gao, Hang Su, Xinpeng Zhang, Bin Luo

“…Previous research on model watermarking for integrity detection has encountered the issue of overexposure of model parameters during embedding and extraction of the watermark. …”
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The Farahzad Neighbourhood of Tehran: Land Use Transition in the City Periphery by Seyedeh Zahra Hosseini, Martin Wynn, Seyed Mostafa Parpanchi

“…The novelty of this article lies in the use of GIS-generated images and urban fabric classifications to assess the growth of the neighbourhood since the turn of century, during which time the planning machinery has generally failed to provide an adequate framework for development in this area of the Tehran urban periphery. …”
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Ensemble machine learning for predicting academic performance in STEM education by Aklilu Mandefro Messele

“…In countries like Ethiopia, students often struggle with science and mathematics. To tackle these issues, our research focused on developing a predictive model for STEM students using advanced ensemble machine learning algorithms. …”
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Aspiring to clinical significance: Insights from developing and evaluating a machine learning model to predict emergency department return visit admissions. by Yiye Zhang, Yufang Huang, Anthony Rosen, Lynn G Jiang, Matthew McCarty, Arindam RoyChoudhury, Jin Ho Han, Adam Wright, Jessica S Ancker, Peter Ad Steel

“…Return visit admissions (RVA), which are instances where patients discharged from the emergency department (ED) rapidly return and require hospital admission, have been associated with quality issues and adverse outcomes. We developed and validated a machine learning model to predict 72-hour RVA using electronic health records (EHR) data. …”
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POROUS STRUCTURE OF ROAD CONCRETE by M. K. Pshembaev, V. V. Girinsky, Ya. N. Kovalev, V. N. Yaglov, S. S. Budnichenko

“…Protection of road concrete as a capillary-porous body is considered as one of the topical issues. The problem is solved with the help of primary and secondary protection methods. …”
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Machine learning-based disease risk stratification and prediction of metabolic dysfunction-associated fatty liver disease using vibration-controlled transient elastography: Result... by Liqiong Huang, Yu Luo, Li Zhang, Mengqi Wu, Lirong Hu

“…Abstract Background Metabolic dysfunction-associated fatty liver disease (MAFLD) is a common chronic liver disease and represents a significant public health issue. Nevertheless, current risk stratification methods remain inadequate. …”
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Diabetic retinopathy detection using adaptive deep convolutional neural networks on fundus images by Rashid Abbasi, Farhan Amin, Amerah Alabrah, Gyu Sang Choi, Salabat Khan, Md. Belal Bin Heyat, Muhammad Shahid Iqbal, Huiling Chen

“…Thus, in order to solve this issue, herein, we proposed an adaptive enhancement-based Deep Convolutional Neural Network (DCNN) model for diabetic retinopathy (DR). …”
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Adversarial Hierarchical-Aware Edge Attention Learning Method for Network Intrusion Detection by Hao Yan, Jianming Li, Lei Du, Binxing Fang, Yan Jia, Zhaoquan Gu

“…The rapid development of information technology has made cyberspace security an increasingly critical issue. Network intrusion detection methods are practical approaches to protecting network systems from cyber attacks. …”
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A novel method for power transformer fault diagnosis considering imbalanced data samples by Jun Chen, Yong Wang, Lingming Kong, Yilong Chen, Mianzhi Chen, Qian Cai, Gehao Sheng

“…IntroductionMachine learning-based power transformer fault diagnosis methods often grapple with the challenge of imbalanced fault case distributions across different categories, potentially degrading diagnostic accuracy. To address this issue and enhance the accuracy and operational efficiency of power transformer fault diagnosis models, this paper presents a novel fault diagnosis model that integrates Neighborhood Component Analysis (NCA) and k-Nearest Neighbor (KNN) learning, with the incorporation of correction factors.MethodsThe methodology begins by introducing a correction factor into the objective function of the NCA algorithm to reduce the impact of sample imbalance on model training. …”
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Fulminant emphysematous pyelonephritis in a transplant kidney (clinical observation and literature review) by R. N. Trushkin, S. S. Andreev, N. I. Belavina, T. K. Isaev, D. E. Okonskaya, E. S. Stolyarevich, N. N. Klochkova, M. A. Lysenko

“…There is no universally accepted consensus on the radiographic classification of EPN in KT recipients and its management. …”
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Detection of insect-damaged sunflower seeds using near-infrared hyperspectral imaging and machine learning by Bright Mensah, Jarrad Prasifka, Brent Hulke, Ewumbua Monono, Xin Sun

“…The results showed that MLP achieved the highest classification performance with an accuracy of 0.91 and an F1-score of 0.91, followed by SVM with an accuracy of 0.89 and an F1-score of 0.89. …”
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Cannabinoids in Chronic Pain Management: A Review of the History, Efficacy, Applications, and Risks by Brooks W. Johnson, Natalie H. Strand, John C. Raynak, Christian Jara, Kisanet Habtegiorgis, Brennan A. Hand, Sang Hong, Jillian A. Maloney

“…<b>Background/Objectives</b>: Chronic pain remains a pervasive and challenging public health issue, often resistant to conventional treatments such as opioids, which carry substantial risks of dependency and adverse effects. …”
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Licence to Simulate: When Agent-Based Models Are More Fiction than Function by Francesco Moroni, Mosè Gallo, Giovanni Romagnoli, Francesco Zammori

“…Although this concern, namely, the potential misuse of agent-based models, has been frequently raised in the literature, no previous study has precisely quantified how frequently this issue occurs, especially in the supply chain domain. …”
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Kolmogorov–Arnold Network in the Fault Diagnosis of Oil-Immersed Power Transformers by Thales W. Cabral, Felippe V. Gomes, Eduardo R. de Lima, José C. S. S. Filho, Luís G. P. Meloni

“…Strategies with more robust models increase the overall performance of the entire system. To address this issue, we propose a novel approach based on Kolmogorov–Arnold Network (KAN) for the fault diagnosis of power transformers. …”
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THE EVOLUTION OF NATIONAL PERFORMANCE ART: MUSICAL INTERPRETATION IN THE CONTEXT OF TRADITION AND MODERNITY by Nataliia POSIKIRA-OMELCHUK, Tymur IVANNIKOV, Ulyana MOLCHKO, Viktoriia PROKOPCHUK, Angelika TATARNIKOVA

“…The issue of objective analysis of interpretations based on sound recordings is raised. …”
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Examining the interconnections among income, food prices, food insecurity, and health expenditure: a multicausality approach by Ahmet Murat Günal, Sevde Cantürk, Salim Yılmaz, Canser Boz, Derya Karabay

“…Abstract Background Food insecurity is a growing global issue driven by income inequality, food price fluctuations, and unequal access to essential resources. …”
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Genetic, Metabolic, and Proteomic Polymorphisms and Clinical Phenotypes of Sepsis by V. A. Kovzel, L. A. Davydova, T. A. Lapina, A. A. Semushkina, A. I. Gutnikov

“…The heterogeneity of sepsis patient populations remains an unresolved issue, hindering the development of effective therapeutic strategies and disease prognostic tools. …”
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Innovative deep learning approach for cross-crop plant disease detection: A generalized method for identifying unhealthy leaves by Imane Bouacida, Brahim Farou, Lynda Djakhdjakha, Hamid Seridi, Muhammet Kurulay

“…In this paper, we address this issue by proposing a novel deep learning-based system capable of recognizing diseased and healthy leaves across different crops, even if the system was not trained on them. …”
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A Study on Perceptions, Practices, and Experiences About Antibiotic Consumption and Antibiotic Resistance Among Various Stakeholders From the Catchment Area of an Urban Health Trai... by Nirmika Patel, Parita Patel, Rashmi Sharma, Brijesh Patel, Sanju Gajjar, Nirav Bapat

“…Introduction: Misuse or abuse of antibiotic consumption, leading to antibiotic resistance, is an emerging global public health issue. Therefore, this qualitative study was conducted with a primary objective of documenting the perceptions, practices and experiences about antibiotic consumption and awareness of antibiotic resistance among doctors, drug dispensers, and end-users. …”
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Certainty of Linear Interrelation of Technical and Economic Parameters of Power Units of 300 МWt Thermal Power Stations by E. M. Farhadzadeh, A. Z. Muradaliyev, T. K. Rafiyeva, A. A. Rustamova

“…The article presents only one, but very important issue of the problem, viz. the assessment of the reliability of the assumption about the linear relationship of technical and economic indicators. …”
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