Zobrazeno 1 - 10
of 98
pro vyhledávání: '"Ismail, Uysal"'
Publikováno v:
BMC Musculoskeletal Disorders, Vol 25, Iss 1, Pp 1-8 (2024)
Abstract Background Due to time and setting constraints in clinical practice, performing a comprehensive assessment with both questionnaires and physical performance tests may not be possible. This study aimed to demonstrate the relationship between
Externí odkaz:
https://doaj.org/article/25ee4a09bfe54a8e82732117d4668b30
Publikováno v:
Medicina, Vol 60, Iss 9, p 1510 (2024)
Background and Objectives: Defining the exercise habits of individuals with Alzheimer’s Disease (AD) may help to determine optimal rehabilitation programs. This study aimed to investigate the physical and psychological parameters associated with ex
Externí odkaz:
https://doaj.org/article/50ac95aa8af54258a23ed43edc8ead99
Publikováno v:
Egyptian Pediatric Association Gazette, Vol 71, Iss 1, Pp 1-7 (2023)
Abstract Background To our knowledge, no other studies investigated the internal consistency of the Edinburgh Visual Gait Score (EVGS). The aim of our study was to determine the reliability and construct validity of the EVGS in children with cerebral
Externí odkaz:
https://doaj.org/article/80193e36203d4c62b870538725527d72
Autor:
Muhammed Furkan Kucuk, Ismail Uysal
Publikováno v:
IEEE Access, Vol 10, Pp 61744-61752 (2022)
This paper presents a comparison of conventional and modern machine (deep) learning within the framework of anomaly detection in self-organizing networks. While deep learning has gained significant traction, especially in application scenarios where
Externí odkaz:
https://doaj.org/article/01048d68de504bb88e3e1a89c7b6a26d
Publikováno v:
Smart Agricultural Technology, Vol 2, Iss , Pp 100055- (2022)
The paper presents a complete collection of data and its preliminary statistical analysis obtained from the first phase of a large soil study on how to improve strawberry production and achieve sustainable and high-quality harvests through sensor-ass
Externí odkaz:
https://doaj.org/article/8b34c881967242b4976ff9569b113404
Autor:
Mehmet Bugrahan Ayanoglu, Ismail Uysal
Publikováno v:
Sensors, Vol 23, Iss 9, p 4303 (2023)
Temperature-controlled closed-loop systems are vital to the transportation of produce. By maintaining specific transportation temperatures and adjusting to environmental factors, these systems delay decomposition. Wireless sensor networks (WSN) can b
Externí odkaz:
https://doaj.org/article/e764149831cf4d1c988ec225ebe6ff5d
Publikováno v:
Annals of Geriatric Medicine and Research, Vol 24, Iss 1, Pp 35-40 (2020)
Background The Lawton Instrumental Activities of Daily Living (IADL) scale is the most widely used scale for the assessment of IADL in the elderly population. The aim of this study was to adapt the Lawton IADL Scale in Turkish and to investigate the
Externí odkaz:
https://doaj.org/article/9fc88237bb404c06a075cbe34d8a6915
Autor:
Alla Abdella, Ismail Uysal
Publikováno v:
IEEE Access, Vol 8, Pp 25626-25637 (2020)
Deep clustering achieves unprecedented levels of accuracy with unsupervised feature extraction on rich datasets where the joint statistics of the latent space is learned via highly nonlinear compression. This paper has two separate contributions to t
Externí odkaz:
https://doaj.org/article/07a3792fd9634c659bfc652ae451276f
Publikováno v:
IEEE Access, Vol 8, Pp 198168-198177 (2020)
Unsupervised matrix completion algorithms mostly model the data generation process by using linear latent variable models. Recently proposed algorithms introduce non-linearity via multi-layer perceptrons (MLP), and self-supervision by setting separat
Externí odkaz:
https://doaj.org/article/4d6ef6a51f394952b30d939127b3a2dd
Autor:
Rania Elashmawy, Ismail Uysal
Publikováno v:
Sensors, Vol 23, Iss 4, p 2247 (2023)
Ubiquitous sensor networks collecting real-time data have been adopted in many industrial settings. This paper describes the second stage of an end-to-end system integrating modern hardware and software tools for precise monitoring and control of soi
Externí odkaz:
https://doaj.org/article/6216fb4fdb5d49dc8024207a09853cd1