A new approach to sleep analysis based on fuzzy prediction theory is described. This article gives a general introduction to detection and processing of biologic signals with LabVIEW software, and the application of the designed fuzzy measurement system in fuzzy prediction analysis of the physiological signals recorded during sleep. The results of trials of the fuzzy prediction analysis demonstrated the reliability of this method. LabVIEW-based fuzzy prediction analysis can be helpful for early diagnosis, monitoring and prognostic assessment of some diseases, and may be valuable in the analysis of the physiologic signals of patients with obstructive sleep apnea syndrome (OSAS) during sleep.
Download full-text PDF |
Source |
---|
Self-regulated learning (SRL) has been regarded as one of the indispensable factors affecting students' academic success in online learning environments. However, the current understanding of the mechanism/causes of SRL in online ill-structured problem-solving remains insufficient. This study, therefore, examines the configural causal effects of goal attributes, motivational beliefs, creativity, and grit on self-regulated learning.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Geology, University of Patras, 26504, Patras, Greece.
This study aims to construct a coastal vulnerability assessment conceptual framework to improve the outcomes of Coastal Vulnerability Index (CVI) for local scale areas. Consequently, a new CVI was created adapted to the specific conditions of the area using seven variables. The new index was named Geotechnical Coastal Vulnerability Index (GCVI) due to the incorporation of two new geotechnical variables: (1) Coastal geotechnical properties and (2) Median grain size distribution.
View Article and Find Full Text PDFAnimals (Basel)
December 2024
Division of Artificial Intelligence Engineering, National Korea Maritime & Ocean University, Busan 49112, Republic of Korea.
While the pet market is continuously rapidly increasing in Korea, pet dog owners feel uncomfortable in coping with pet dog's health problems in time. In this paper, we propose a pre-diagnosis system based on neuro-fuzzy learning, enabling non-expert users to monitor their pets' health by inputting observed symptoms. To develop such a system, we form a disease-symptom database based on several textbooks with veterinarians' guidance and filtering.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
January 2025
Department of Environmental Health Engineering, School of Public Health, Mazandaran University of Medical Sciences, Sari, Iran.
Climate change significantly impacts the risk of eutrophication and, consequently, chlorophyll-a (Chl-a) concentrations. Understanding the impact of water flows is a crucial first step in developing insights into future patterns of change and associated risks. In this study, the Statistical DownScaling Model (SDSM)-a widely used daily downscaling method-is implemented to produce downscaled local climate variables, which serve as input for simulating future hydro-climate conditions using a hydrological model.
View Article and Find Full Text PDFComput Biol Med
January 2025
Department of Mathematics, NED University of Engineering & Technology, Pakistan. Electronic address:
For consideration of uncertainties of a medicine dataset, a new conceptual architecture fuzzy three-valued logic is introduced in this research work. The proposed concept is applied to the heart disease dataset for the assessment of heart disease risk in individuals. By comparison of three binary (0,1) input variables, the variables' uncertainties and their collective impact can be analyzed that provide complete information leading to better outcome prediction.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!