İZÜ Araştırma ve Akademik Performans Sistemi
DSpace@İZÜ, İstanbul Sabahattin Zaim Üniversitesi’nin bilimsel araştırma ve akademik performansını izleme, analiz etme ve raporlama süreçlerini tek çatı altında buluşturan bütünleşik bilgi sistemidir.
Güncel Gönderiler
Öğe Türü: Yayın , Perceived Social Support and Psychological Well-Being as Mediators in the Relationship Between Social Media Use and Quality of Life Among Older Adults in Nursing Homes in Istanbul(Taylor & Francis, 2025) Alaçayır, Derya; Irmak, Hatice Selin; Yurtsever, Emel; Yurtsever, EmelObjectives: This cross-sectional study investigates the mediating role of perceived social support and psychological well-being in the relationship between social media use and quality of life among older adults residing in nursing homes.Method: The sample comprised 302 individuals aged 60 and above living in six official nursing homes in Istanbul. Data were collected using a socio-demographic questionnaire, the Psychological Well-Being Scale, the Multidimensional Scale of Perceived Social Support, and the Quality of Life Scale for the Elderly. Analyses were conducted using SPSS 25, and mediation hypotheses were tested using the PROCESS Macro (Model 4) with 5,000 bootstrap samples.Results: The mediation analyses revealed a significant complete mediation association between social media use and quality of life through perceived social support (B = −0.5417, SE = 0.2588, 95% CI [−1.1030, −0.0867]) and psychological well-being (B = −3.2602, SE = 0.5360, 95% CI [−4.3560, −2.2456]).Conclusion: These findings suggest that social media use affects quality of life not only directly but also indirectly by enhancing social support and psychological well-being, highlighting the importance of digital connectivity for older adults in institutional care settings.Öğe Türü: Yayın , From the Nest to the World: Helicopter Parenting and Challenges in Young Adult Social Integration(Frontiers Media SA, 2025) Yılmaz, Yelda; Artan, Taner; Gurbanova, Farida; Aliyeva, Nargiz; Yılmaz, YeldaIntroduction: Helicopter parenting is a new parenting style that has become widespread globally. This study aimed to evaluate the eects of helicopter parenting experiences on Turkish young adults, focusing on self-determination and fear of intimacy. Methods: A cross-sectional design was used with 800 Turkish young adults. Data were collected using the Personal Information Form, Perceived Helicopter Parenting Attitude Scale, Self-Determination Scale, and Fear of Intimacy Scale. Results: Results showed a significant negative correlation between perceived helicopter parenting and self-determination. There was also a significant positive correlation between perceived helicopter parenting and fear of intimacy. Furthermore, self-determination mediated the relationship between both maternal and paternal helicopter parenting attitudes and fear of intimacy. Discussion: The findings suggest the importance of increasing awareness about helicopter parenting and its impact on young adults’ future lives.Öğe Türü: Yayın , Vision-Based Localization in Urban Areas for Mobile Robots(MDPI, 2025) Alimovski, Erdal; Erdemir, Gökhan; Kuzucuoğlu, Ahmet Emin; Alımovskı, Erdal;Robust autonomous navigation systems rely on mapping, locomotion, path planning, and localization factors. Localization, one of the most essential factors of navigation, is a crucial requirement for a mobile robot because it needs the capability to localize itself in the environment. Global Positioning Systems (GPSs) are commonly used for outdoor mobile robot localization tasks. However, various environmental circumstances, such as high-rise buildings and trees, affect GPS signal quality, which leads to reduced precision or complete signal blockage. This study proposes a visual-based localization system for outdoor mobile robots in crowded urban environments. The proposed system comprises three steps. The first step is to detect the text in urban areas using the “Efficient and Accurate Scene Text Detector (EAST)” algorithm. Then, EasyOCR was applied to the detected text for the recognition phase to extract text from images that were obtained from EAST. The results from text detection and recognition algorithms were enhanced by applying post-processing and word similarity algorithms. In the second step, once the text detection and recognition process is completed, the recognized word (label/tag) is sent to the Places API in order to return the recognized word’s coordinates that are passed within the specified radius. Parallely, points of interest (POI) data are collected for a defined area by a certain radius while the robot has an accurate internet connection. The proposed system was tested in three distinct urban areas by creating five scenarios under different lighting conditions, such as morning and evening, using the outdoor delivery robot utilized in this study. In the case studies, it has been shown that the proposed system provides a low error of around 4 m for localization tasks. Compared to existing works, the proposed system consistently outperforms all other approaches using just one sensor. The results indicate the efficacy of the proposed system for localization tasks in environments where GPS signals are limited or completely blocked.Öğe Türü: Yayın , Aging in Place as a Mediator Between Satisfaction with Life and Geriatric Depressive Symptoms in Turkish Older Adults(Taylor & Francis, 2025) Altındiş, Esma; Artan, Taner; Arifoğlu, Ahmed TahaThe concept of aging in place refers to older adults’ capacity to undergo the aging process without being separated from their phy-sical and social environments. However, existing literature on the mediating role of this concept in the relationship between geriatric depression and life satisfaction among older adults is limited. Accordingly, the present study aims to investigate the mediating role of satisfaction with aging in place in the relationship between life satisfaction and geriatric depression among Turkish older adults. The study population comprised older adults residing in Istanbul, and the sample consisted of 412 individuals aged 65 years and above living at home, selected through stratified and cluster sampling methods (42.23% female, 57.77% male). Data were analyzed using confirmatory factor analysis and structural equation modeling – based mediation analysis. the findings indicated a positively associa-tion with satisfaction with aging in place and life satisfaction, while a negatively association was observed between satisfaction with aging in place and geriatric depression levels. Moreover, satisfaction with aging in place was found to partially mediate the relationship between life satisfaction and geriatric depression. These results sug-gest that policies aimed at enhancing satisfaction with aging in place among older adults may be an effective strategy to reduce symptoms of geriatric depression.Öğe Türü: Yayın , A Machine Learning Approach of Text Classification forHigh- and Low-Resource Languages(Wiley, 2025) Raza, Muhammad Owais; Mahoto, Naeem Ahmed; Shaikh, Asadullah; Pathan, Nazia; Alshahrani, Hani Mohammed; Elmagzoub, Mohamed A.;A large amount of data have been published online in textual format for the last decade because of the advancement of informationand communication technologies. This is an open challenge to organize and classify large amounts of textual data automatically,especially for a language that has limited resources available online. In this study, two types of approaches are adopted for exper-iments. First one is a traditional strategy that uses six (06) classical state-of-the-art classification models (1. decision tree (DT),2. logistic regression (LR), 3. support vector machine (SVM), 4. k-nearest neighbour (k-NN), 5. Naive Bayes (NB), and 6. randomforest (RF)) along with two (02) ensemble methods (1. Adaboost and 2. gradient boosting (GB)) and second modeling technique isour proposed voting based ensembling scheme. Models are trained on a 75-25 split where 75% of data is used for training and 25%for testing. The evaluation of the classification models is carried out based on accuracy, precision, recall, and F1-score indexes.The experimental outcomes witnessed that for the traditional approach, gradient boosting outperformed for the limited resourcelanguage with 98.08% F1-score, while SVM performed better (97.34% F1-score) for the resource-rich language.
