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    Master Thesis
    Bireysel Psikoloji: Don Juan ve J. Alfred Prufrock'un Aşağılık Duygusu Üzerine Bir Araştırma; Aşk ve Cinsellik Arayışı
    (2020) Alhgam, Mohammed Yahya Sahıb; Aras, Gökşen
    Bu tez aşağılık duygusunun ve yakınlık ihtiyacının farklı durumlarda farklı olaylar şeklinde Prufrock ve Don Juan'ın mantalitesi üzerindeki etkilerini keşfetmektedir. İki karakter de içinde bulundukları topluluklarına karşı kırılgandırlar fakat farklı tepkiler vermekte ve başa çıkmada farklı yöntemler seçmektedirler. Aşağılık hisleri, cinsellik ve yakınlık ihtiyacı iki karakter için de aynı iken böyle bir yük ve arzuyla başa çıkma şekli kişiliklere bağlıdır. Bu çalışma, Don Juan'ın öğrendiğini ve aşağılık Duygusuna adapte olduğunu ve bunları telafi edebildiğini gösterirken, pasif bir karakter olan Prufrock'ın amaçları doğrultusunda nasıl harekete geçme kabiliyetine sahip olmadığını ve aşağılık kompleksi yaşadığını göstermektedir. Don Juan, cinsel açıdan tatmin olmaktadır ancak sürekli kendi kırılganlığına yenilmektedir. Bu da göstermektedir ki Prufrock'un bastırılmış cinsel arzuları tatmin olduğunda onun rahatsız aklı iyileşmeyecektir. Bu, şiirlerin bağlı oldukları akımları anlamak ve iki karakterin geçmişlerini, toplumlarını ve çevreleyen karakterleri analiz etmek bu karakterlerin mantalitelerini anlamak için anahtar bileşendir. Bu tez, Alfred Adler'in psikolojik teorisine ve Bireysel Psikoloji'ye dayanmaktadır. Bu teori, karakterlerin ne düşündüklerini ve nasıl davrandıklarını anlamak için bir yorum yöntemi olarak kullanılmaktadır. Çalışma her bir kişilikteki aşağılık hislerini tespit etmek ve buna göre onların kişiliklerini, amaçlarını, sosyal ilgilerini incelemektedir.
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    Article
    Citation - WoS: 19
    Citation - Scopus: 21
    Gender Inequity in Thermal Sensation Based on Emotional Intensity for Participants in a Warm Mediterranean Climate Zone
    (Elsevier France-editions Scientifiques Medicales Elsevier, 2023) Ceter, Aydin Ege; Ozbey, Mehmet Furkan; Turhan, Cihan
    The deficiencies of the one of the most preferred conventional thermal comfort models, the Predicted Mean Vote/ Percentage of Predicted Dissatisfied (PMV/PPD) method have emerged over time since the model does not take psychological parameters such as personal traits, mood states and adaptation into account. Therefore, re-searchers have focused on Adaptive Thermal Comfort models that integrate human behaviours into the model for better prediction of thermal comfort. In addition to the influence of the behaviours of occupants, thermal comfort may be evaluated as a subjective term, thus, the effect of one of the psychological parameters, current mood state, on thermal sensation cannot be ignored for predictions. Although, the effect of current mood state on thermal sensation is a vital concept, the findings of the studies are not effective and comprehensive in the literature. For this reason, the aim of this study is to examine the relationship between current mood state and thermal sensation in gender difference aspect. Therefore, a series of experiments were conducted in a university study hall between August 16th, 2021 and August 1st, 2022. The current mood states of the participants were evaluated with the Profile of Mood States (POMS) questionnaire and the results were represented by a novel approach called Emotional Intensity Score (EIS). One tailed t-test was applied for investigating the relationship between the EIS and the thermal sensation. Findings of the research showed that a significant association exists between the EIS and thermal sensation for male participants while no relationship was found for female.
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    Article
    Citation - WoS: 8
    Citation - Scopus: 8
    Modeling the Mood State on Thermal Sensation With a Data Mining Algorithm and Testing the Accuracy of Mood State Correction Factor
    (Pergamon-elsevier Science Ltd, 2025) Yerlikaya-Ozkurt, Fatma; Ozbey, Mehmet Furkan; Turhan, Cihan
    Psychology is proven as an influencing factor on thermal sensation. On the other hand, mood state is one of the significant parameters in psychology field. To this aim, in the literature, mood state correction factor on thermal sensation (Turhan and Ozbey coefficients) is derived utilizing with data-driven black-box model. However, novel models which present analytical form of the mood state correction factor should be derived based on the several descriptive variables on thermal sensation. Moreover, the result of this factor should also be checked with analytical model results. Therefore, this study investigates the modelling of mood state correction factor with a data mining algorithm, called Multivariate Adaptive Regression Splines (MARS). Additionally, the mood state is also taken as a thermal sensation parameter besides environmental parameters in this algorithm. The same data, which are collected from a university study hall in a temperate climate zone, are used and the model results are compared with the thermal sensation results based on mood state correction factor which is driven via black-box model. The results show that coefficient of correlation "r" between the MARS and black-box model is found as 0.9426 and 0.9420 for training and testing. Hence, the mood state is also modelled via a data mining algorithm with a high accuracy, besides the black-box model.