Nezih Önal
Biographic Data
| ID | 8664398 |
|---|---|
| NAME | Nezih Önal |
| GIVEN NAMES | Nezih |
| FAMILY NAME | Önal |
| SIGNATURE | ÖNAL N |
| AFFILIATIONS | Niğde Ömer Halisdemir Üniversitesi |
| ORCID | 0000-0002-1103-8771 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Scientific and practical basis for implementing machine learning on a parallel computing cluster
The rapid expansion of machine learning (ML) applications in high-performance computing has motivated extensive research on theoretical models and practical challenges in deploying ML on parallel computing clusters. This PRISMA-guided systematic mapping review synthesized 21 peer-reviewed, open-access studies indexed in IEEE Xplore and published between 2023 and 2024. The review examines distributed optimization frameworks, asynchronous training …
Artificial intelligence in early childhood classrooms
Nomophobia
The aim of this study is to examine high school students' use of smartphones and their nomophobia levels. This research was designed using one of the mixed research methods, the Explanatory Mixed Method, with the combined use of both quantitative and qualitative paradigms. Nomophobia Scale was used to collect the quantitative data of the research study. 767 students from two different high schools in Nigde in Turkey participated in the research. …
No prominent works on this page.
Nomophobia
The aim of this study is to examine high school students' use of smartphones and their nomophobia levels. This research was designed using one of the mixed research methods, the Explanatory Mixed Method, with the combined use of both quantitative and qualitative paradigms. Nomophobia Scale was used to collect the quantitative data of the research study. 767 students from two different high schools in Nigde in Turkey participated in the research. …
Scientific and practical basis for implementing machine learning on a parallel computing cluster
The rapid expansion of machine learning (ML) applications in high-performance computing has motivated extensive research on theoretical models and practical challenges in deploying ML on parallel computing clusters. This PRISMA-guided systematic mapping review synthesized 21 peer-reviewed, open-access studies indexed in IEEE Xplore and published between 2023 and 2024. The review examines distributed optimization frameworks, asynchronous training …
Artificial intelligence in early childhood classrooms
Child Development and Digital Technology (2 works) · Addiction (1 work) · Applied Psychology (1 work) · Asynchronous communication (1 work) · Child development (1 work) · Cloud Computing and Resource Management (1 work) · Computer cluster (1 work) · Computer Science (1 work) · Descriptive statistics (1 work) · Distributed and Parallel Computing Systems (1 work)