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Robust self management classification via sparse representation based discriminative model for mild cognitive impairment associated with diabetes mellitus.
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The School of Nursing, Fujian Medical University, No. 1 Xuefu North Road, Fuzhou, 350122, Fujian, China.
Diabetes Mellitus combined with Mild Cognitive Impairment (DM-MCI) is a high incidence disease among the elderly. Patients with DM-MCI have considerably higher risk of dementia, whose daily self-care and life management (i.e.
View Article and Find Full Text PDFA deep transfer learning based convolution neural network framework for air temperature classification using human clothing images.
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Department of Electrical Engineering, College of Engineering, Taif University, P.O. BOX 11099, 21944, Taif, Saudi Arabia.
Weather recognition is crucial due to its significant impact on various aspects of daily life, such as weather prediction, environmental monitoring, tourism, and energy production. Several studies have already conducted research on image-based weather recognition. However, previous studies have addressed few types of weather phenomena recognition from images with insufficient accuracy.
View Article and Find Full Text PDFNutritional quality and climate impact of Norwegian adults' diet classified according to the NOVA system.
Nutr J
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Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
Information about how ultra-processed foods (UPF) contribute to the intake of energy and nutrients and environmental impact is important for future food policies and dietary recommendations. This study assessed the contribution of the four NOVA food groups, including UPF, to energy intake, nutritional quality, and climate impact in Norwegian adults' diet. We used dietary data from 348 participants in the Norkost 4 pilot study, collected through two non-consecutive 24-h dietary recalls.
View Article and Find Full Text PDFEnhance fashion classification of mosquito vector species via self-supervised vision transformer.
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College of Advanced Manufacturing Innovation, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.
Vector-borne diseases pose a major worldwide health concern, impacting more than 1 billion people globally. Among various blood-feeding arthropods, mosquitoes stand out as the primary carriers of diseases significant in both medical and veterinary fields. Hence, comprehending their distinct role fulfilled by different mosquito types is crucial for efficiently addressing and enhancing control measures against mosquito-transmitted diseases.
View Article and Find Full Text PDFClustering and classification for dry bean feature imbalanced data.
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School of Big Data, Fuzhou University of International Studies and Trade, Fuzhou, 350202, China.
The traditional machine learning methods such as decision tree (DT), random forest (RF), and support vector machine (SVM) have low classification performance. This paper proposes an algorithm for the dry bean dataset and obesity levels dataset that can balance the minority class and the majority class and has a clustering function to improve the traditional machine learning classification accuracy and various performance indicators such as precision, recall, f1-score, and area under curve (AUC) for imbalanced data. The key idea is to use the advantages of borderline-synthetic minority oversampling technique (BLSMOTE) to generate new samples using samples on the boundary of minority class samples to reduce the impact of noise on model building, and the advantages of K-means clustering to divide data into different groups according to similarities or common features.
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