Browsing by Author "Sehribanoglu, Sanem"

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Burnout Among Turkish Teachers: the Influence of Sleep Quality and Job Satisfaction
(Hacettepe Univ, 2013) Merey, Zihni; Piskin, Metin; Boysan, Murat; Sehribanoglu, Sanem
Given the associations between job satisfaction and burnout, it is important to consider relations between job-related stress and sleep quality. Studies have consistently suggested that linkages between sleep problems and job-related stress are significant and have serious consequences on quality of life, work performance and motivation. Teaching is a stressful occupation, and to date possible influences of poor sleep quality on job burnout have received little attention. The aim of this study was to investigate predicting value of poor sleep quality on job burnout. Data were collected from 184 elementary school teachers. The Maschlack Burnout Inventory (MBI), Minnesota Satisfaction Questionnaire (MSQ), and Pittsburgh Sleep Quality Index (PSQI) were administered to volunteers. The linkage between poor sleep quality and job burnout was evaluated by using hierarchical regression analyses after controlling for demographical characteristics of subjects and job satisfaction. School climate, intrinsic job satisfaction, and sleep quality were significant determinants of burnout in school. Findings were discussed in the light of the theoretical considerations about job burnout.
Chemometric Data Analysis of Gross Radioactivity and Heavy Metal Concentrations in Soil and Sediments of Bendimahi River, Turkey
(Springer, 2020) Sehribanoglu, Sanem; Zorer, Halil; Zorer, Ozlem Selcuk
This study deals with radioactivity and heavy metal distribution and statistical analyses in the Bendimahi River Basin, which is within the Lake Van Closed Basin, Turkey. In order to identify the relationships between measured variables and to categorize soils and sediments collected at 15 sites on Bendimahi River, factor and cluster analysis have been applied. The data set is constituted of 9 radiological and physico-chemical variables, including gross alpha and gross beta activities and Pb, Zn, Cu, Cr, Cd, Co and Mn concentrations. Factor and cluster analysis were used to describe the relationship and similarity among data sets (variables) for the Bendimahi River. The convergence diagnostics such as trace plot and kernel density were applied to determine the convergence criteria to the data sets.
A Comprehensive Exploration of Deep Learning Approaches for Pulmonary Nodule Classification and Segmentation in Chest Ct Images
(Springer London Ltd, 2024) Canayaz, Murat; Sehribanoglu, Sanem; Ozgokce, Mesut; Akinci, M. Bilal
Accurately determining whether nodules on CT images of the lung are benign or malignant plays an important role in the early diagnosis and treatment of tumors. In this study, the classification and segmentation of benign and malignant nodules on CT images of the lung were performed using deep learning models. A new approach, C+EffxNet, is used for classification. With this approach, the features are extracted from CT images and then classified with different classifiers. In other phases of the study, a segmentation between benign and malignant was performed and, for the first time, a comparison of nodes was made during segmentation. The deep learning models InceptionV3, DenseNet121, and SeResNet101 were used as backbone models for feature extraction in the segmentation phase. In the classification phase, an accuracy of 0.9798, a precision of 0.9802, a recognition of 0.9798, an F1 score of 0.9798, and a kappa value of 0.9690 were achieved. During segmentation, the highest values of 0.8026 Jacard index and 0.8877 Dice coefficient were achieved.
Contributions of Cultural Ess To Human Well-Being, Landscape Planning and Rural Development in Border Landscapes: Local Insights From the Bendimahi River Basin (Eastern Anatolia, Türkiye)
(Springer, 2025) Baylan, Emel; Sehribanoglu, Sanem; Satir, Onur
Despite the rise in cultural ecosystem services (CESs) research in urban or peri-urban settings and related participatory approaches, studies on the social values of CESs benefits, in the largely natural and rural border landscapes to locals' well-being are still few. This study uses the Bendimahi River Basin (Van), one of Turkiye's least developed areas along the Iranian border, as an empirical case to explore the links between the locals' social values for ecosystem benefits, landscape characteristics, and human well-being dimensions such as personal and social fulfilment and enjoyment. A questionnaire survey combined with PPGIS landscape value mapping with 348 people was employed to gather data for 15 ecosystem services with an emphasis on CES. The findings of the statistical and spatial analyses revealed that while enjoyment benefits are lowest in the landscape due to the low development, respondents have the highest well-being benefits in social fulfilment through intrinsic, future, continuity, and sense of place values. The male respondents found as experiencing both of these well-being benefits more than women in the Basin. Physical features such as accessibility, water bodies/wetlands, settlements, dynamic topography, and naturalness displayed positive influence on the locals' CES experiences. Due to their facilitation on CESs experiences, improvements in rural tourism and environmental protection are proposed as two paths for the Basin's development and for enhancing the well-being of its inhabitants. A discussion is provided on how and when to incorporate the social values of CES into landscape planning to improve participatory decision making in rural landscapes.
Covid-19 Diagnosis on Ct Images With Bayes Optimization-Based Deep Neural Networks and Machine Learning Algorithms
(Springer London Ltd, 2022) Canayaz, Murat; Sehribanoglu, Sanem; Ozdag, Recep; Demir, Murat
Early diagnosis of COVID-19, the new coronavirus disease, is considered important for the treatment and control of this disease. The diagnosis of COVID-19 is based on two basic approaches of laboratory and chest radiography, and there has been a significant increase in studies performed in recent months by using chest computed tomography (CT) scans and artificial intelligence techniques. Classification of patient CT scans results in a serious loss of radiology professionals' valuable time. Considering the rapid increase in COVID-19 infections, in order to automate the analysis of CT scans and minimize this loss of time, in this paper a new method is proposed using BO (BO)-based MobilNetv2, ResNet-50 models, SVM and kNN machine learning algorithms. In this method, an accuracy of 99.37% was achieved with an average precision of 99.38%, 99.36% recall and 99.37% F-score on datasets containing COVID and non-COVID classes. When we examine the performance results of the proposed method, it is predicted that it can be used as a decision support mechanism with high classification success for the diagnosis of COVID-19 with CT scans.
Sense of Place and Satisfaction With Landscaping in Post-Earthquakehousing Areas: the Case of Edremit Toki-Van (Turkey)
(Univ Politecnica Catalunya, 2018) Baylan, Emel; Asur, Feran; Sehribanoglu, Sanem
Objectives This research aimed to provide a greater insight into the relationship between feelings of satisfaction with the landscaping and the sense of place, particularly emphasizing on the planning and landscape design of post-disaster housing environments for the enhancement of the victims' and other residents' well-being on the case of Edremit TOKI ( Van) post-earthquake housing area which was built after the devastating earthquakes in 2011. Methodology The residents' satisfaction with various parts of landscaping in the housing area; their place identity, place attachment and place dependence characteristics as part of their sense of place; and the interrelations between these were examined through a questionnaire survey. The data collected from 235 locals were subjected to two types of factor analysis including both explanatory and structural equation modelling (SEM) in order to create a model. Conclusions According to the SEM results, the proposed model based on the hypothesis, which states that "there are positive relationship between the sense of place and satisfaction with landscaping," was not supported. In contrast, a negative relationship was found between the satisfaction with landscaping and sense of place. This suggests that when the respondents' sense of place has increased, it is likely that there might be lower satisfaction with the landscaping they have. Originality This study is original in two aspects; first being focused on the diverse dimensions of landscaping different from the studies mostly dealing with vegetation and visual quality; second being investigated the relationship amongst the satisfaction with landscaping, sense of place and the sub-components of these concepts in a post-earthquake residential area.