Işık Üniversitesi Kurumsal Akademik Bellek Sistemi

Işık Üniversitesi'nin doğrudan veya dolaylı olarak yayınladığı kitap, kitap bölümü, makale, tez, bildiri, rapor ve araştırma verisi gibi tüm akademik yayınlar, uluslararası standartlara uygun olarak dijital ortamda tutulmaktadır. Platform, üniversitenin akademik performansını izlemeye aracılık eder, akademik yayınları uzun süreli belleğinde tutar ve erişime sunar. Ayrıca, bu kaynaklar, yayınların etkisini artırmak ve bilimsel bilgiye sınırsız erişim sağlamak amacıyla telif haklarına uygun şekilde açık erişime sunulmaktadır.


Güncel Gönderiler

Mental disorder and suicidal ideation detection from social media using deep neural networks
(Springer, 2024-07-06) Ezerceli, Özay; Dehkharghani, Rahim
Depression and suicidal ideation are global reasons for life-threatening injury and death. Mental disorders have increased especially among young people in recent years, and early detection of those cases can prevent suicide attempts. Social media platforms provide users with an anonymous space to interact with others, making them a secure environment to discuss their mental disorders. This paper proposes a solution to detect depression/suicidal ideation using natural language processing and deep learning techniques. We used Transformers and a unique model to train the proposed model and applied it to three different datasets: SuicideDetection, CEASEv2.0, and SWMH. The proposed model is evaluated using the accuracy, precision, recall, and ROC curve. The proposed model outperforms the state-of-the-art in the SuicideDetection and CEASEv2.0 datasets, achieving F1 scores of 0.97 and 0.75, respectively. However, in the SWMH data set, the proposed model is 4% points behind the state-of-the-art precision providing the F1 score of 0.68. In the real world, this project could help psychologists in the early detection of depression and suicidal ideation for a more efficient treatment. The proposed model achieves state-of-the-art performance in two of the three datasets, so they could be used to develop a screening tool that could be used by mental health professionals or individuals to assess their own risk of suicide. This could lead to early intervention and treatment, which could save lives.
Best proximity point theorems in non-Archimedean Menger probabilistic spaces
(University of Kragujevac, Faculty of Science, 2024-01-01) Karaaslan, Arife Aysun; Karakaya, Vatan
In this work, we prove best proximity point theorems for γ-contractions with conditions the weak P-property in non-Archimedean Menger probabilistic metric spaces. We give the notion of γ- proximal contractions of first and second type in non-Archimedean Menger probabilistic metric spaces and also we establish best proximity point theorems for these proximal contractions. Lastly, we complete our study by giving examples that support our results.
Remote neuropscyhological assessment: teleneuropsychology
(Turkish Neuropsychiatric Society, 2024-06-01) Yıldırım, Elif; Soncu Büyükişcan, Ezgi; Akça Kalem, Şükriye; Gürvit, İbrahim Hakan
Introduction: Teleneuropsychology, which includes the remote application of neuropsychological tests to patients via telephone or videoconferencing, can expand access to health services for patients who reside in distant areas or have mobility restrictions. With the emergence of the COVID-19 pandemic, there has been a significant increase in the use of teleneuropsychology in cognitive assessment. In this review, the aim was to critically review the results of studies conducted in the field of teleneuropsychology and the fundamental principles related to tele-neuropsychological assessment. Additionally, the “guideline for home-based teleneuropsychology” developed for Türkiye’s practices is outlined in this review. Method: A literature search was conducted using the Web of Science and PubMed databases to include all types of articles related to the subject. Results: The results of studies on in-clinic and home-based teleneuropsychological assessment indicate that tests that assess cognitive functions such as attention, memory, executive functions,and language, particularly those based on verbal administration, can be reliably applied through teleneuropsychological assessment. However, there are factors to consider when referring patients for teleneuropsychological assessment, selecting tests for assessment, and making ethical considerations. Additionally, it is important to follow recommended steps for both the clinician and the patient and/or their caregiver before and during the interview in order for the assessment to be carried out effectively. Conclusion: Although direct contact with the patient is an essential element in clinical neuropsychology practice, when necessary, teleneuropsychological assessment performed by trained experts following appropriate application procedures can be a good alternative to face-to-face evaluations.
Higher analogues of discrete topological complexity
(Springer-Verlag Italia s.r.l., 2024-07-01) Alabay, Hilal; Borat, Ayşe; Cihangirli, Esra; Erdal, Esma Dirican
In this paper, we introduce the nth discrete topological complexity and study its properties such as its relation with simplicial Lusternik–Schnirelmann category and how the higher dimensions of discrete topological complexity relate with each other. Moreover, we find a lower bound of n-th discrete topological complexity which is given by the nth usual topological complexity of the geometric realisation of that complex. Furthermore, we give an example for the strict case of that lower bound.
Text-to-SQL: A methodical review of challenges and models
(TÜBİTAK, 2024-05-20) Kanburoğlu, Ali Buğra; Tek, Faik Boray
This 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.