Zobrazeno 1 - 10
of 118
pro vyhledávání: '"Aziz Nasridinov"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Recent advances in deep learning have led to a surge in computer vision research, including the recognition and classification of human behavior in video data. However, most studies have focused on recognizing individual behaviors, whereas r
Externí odkaz:
https://doaj.org/article/2d89d088181744cda961290b623f0dcd
Autor:
Jeong-Hun Kim, Hyunseok Ko, Dong-Hun Yeo, Zeehoon Park, Upendra Kumar, Kwan-Hee Yoo, Aziz Nasridinov, Sung Beom Cho
Publikováno v:
Materials & Design, Vol 234, Iss , Pp 112357- (2023)
In manufacturing industry, finding optimal design parameters for targeted properties has traditionally been guided by trial and error. However, limited data availability to few hundreds sets of experimental data in typical materials processes, the ma
Externí odkaz:
https://doaj.org/article/53007ba0c8104289a3b5fc83ed137f61
Publikováno v:
Agriculture, Vol 13, Iss 11, p 2044 (2023)
In the domain of agricultural product sales and consumption forecasting, the presence of infrequent yet impactful events such as livestock epidemics and mass media influences poses substantial challenges. These rare occurrences, termed Sparse Critica
Externí odkaz:
https://doaj.org/article/2657b5275bd74803888760428ca71e60
Publikováno v:
IEEE Access, Vol 9, Pp 130170-130184 (2021)
Skyline queries identify skyline points, the minimal set of data points that dominate all other data points in a large dataset. The main challenge with skyline queries is executing the skyline query in the shortest possible time. To address and solve
Externí odkaz:
https://doaj.org/article/12acb70d269a445ab1b7aa058cf56e12
Publikováno v:
IEEE Access, Vol 9, Pp 152616-152627 (2021)
Spectral clustering is a well-known graph-theoretic clustering algorithm. Although spectral clustering has several desirable advantages (such as the capability of discovering non-convex clusters and applicability to any data type), it often leads to
Externí odkaz:
https://doaj.org/article/411c0af5a74c4e0b80e4e417506947de
Publikováno v:
Energies, Vol 15, Iss 20, p 7482 (2022)
Ensemble deep learning methods have demonstrated significant improvements in forecasting the solar panel power generation using historical time-series data. Although many studies have used ensemble deep learning methods with various data partitioning
Externí odkaz:
https://doaj.org/article/59058723d45c435b8e543e494f13f529
Publikováno v:
Applied Sciences, Vol 12, Iss 16, p 8248 (2022)
Big data have become a core technology to provide innovative solutions in numerical applications and services in many fields [...]
Externí odkaz:
https://doaj.org/article/8156736b8e264938a2ac5aa5b3f5555c
Autor:
Tola Pheng, Tserenpurev Chuluunsaikhan, Ga-Ae Ryu, Sung-Hoon Kim, Aziz Nasridinov, Kwan-Hee Yoo
Publikováno v:
Applied Sciences, Vol 12, Iss 2, p 735 (2022)
In the manufacturing industry, the process capability index (Cpk) measures the level and capability required to improve the processes. However, the Cpk is not enough to represent the process capability and performance of the manufacturing processes.
Externí odkaz:
https://doaj.org/article/7ea8b4a6ef5c41f19e833b87078139f5
Publikováno v:
IEEE Access, Vol 6, Pp 23820-23827 (2018)
Vast quantities of data are generated by social networks in seconds. The information generated in a social network is transformed into a flow by the subjects who produce, transmit, and consume it. This flow can be represented in a very complicated di
Externí odkaz:
https://doaj.org/article/8f738520fb6748a2aff11b81616f2b0c
Autor:
Manas Bazarbaev, Tserenpurev Chuluunsaikhan, Hyoseok Oh, Ga-Ae Ryu, Aziz Nasridinov, Kwan-Hee Yoo
Publikováno v:
Sensors, Vol 22, Iss 1, p 29 (2021)
Product quality is a major concern in manufacturing. In the metal processing industry, low-quality products must be remanufactured, which requires additional labor, money, and time. Therefore, user-controllable variables for machines and raw material
Externí odkaz:
https://doaj.org/article/7c3d2e98006d4442901ff17527205d81