2 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 2 / 2
Yayın Healthy lifestyle behaviors of university students: the role of sense of coherence and family health climate(Dokuz Eylul University, 2025-01-31) Cerrahoğlu, Ece; Ünver, Buket; Ülkümen, İpekPurpose: This study aims to examine the predictive role of individual sense of coherence, family sense of coherence and family health climate variables on university students' healthy lifestyle behaviors. Material and Methods: The sample of the study consisted of 371 university students aged 18-25. Sociodemographic Information Form, Healthy Lifestyle Behaviors Scale, Sense of Coherence Scale, Family Sense of Coherence Scale, Family Health Climate Scale were applied to the participants in order to collect the research data. Correlation analysis, independent two-sample t-test, one-way ANOVA test and multiple linear regression analysis were used to analyze the data. Results: According to the results of correlation analysis, a positive relationship was found between healthy lifestyle behaviors and individual sense of coherence, family sense of coherence and family health climate (p<.05). As a result of the multiple linear hierarchical regression analysis, after controlling for the sex variable, individual sense of coherence and family health climate variables significantly predicted healthy lifestyle behaviors (p<.05), while family sense of coherence had no significant predictive role on healthy lifestyle behaviors (p>.05). Conclusion: The findings show that individual sense of coherence, family sense of coherence and family health climate variables are essential on university students' healthy lifestyle behaviors. The sense of coherence provides significant protection in adopting health behaviors that will determine future health and well-being. Similarly, increasing healthy living practices within the family is of great importance for young people to adopt healthy lifestyle behaviors.Yayın Text-to-SQL: a methodical review of challenges and models(TÜBİTAK, 2024-05-20) Kanburoğlu, Ali Buğra; Tek, Faik BorayThis survey focuses on Text-to-SQL, automated translation of natural language queries into SQL queries. Initially, we describe the problem and its main challenges. Then, by following the PRISMA systematic review methodology, we survey the existing Text-to-SQL review papers in the literature. We apply the same method to extract proposed Text-to-SQL models and classify them with respect to used evaluation metrics and benchmarks. We highlight the accuracies achieved by various models on Text-to-SQL datasets and discuss execution-guided evaluation strategies. We present insights into model training times and implementations of different models. We also explore the availability of Text-to-SQL datasets in non-English languages. Additionally, we focus on large language model (LLM) based approaches for the Text-to-SQL task, where we examine LLM-based studies in the literature and subsequently evaluate the LLMs on the cross-domain Spider dataset. Finally, we conclude with a discussion of future directions for Text-to-SQL research, identifying potential areas of improvement and advancements in this field.
