Hakkari Üniversitesi Akademik Veri Yönetim Sistemi
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YALĞAN “YALAN” SÖZCÜĞÜNÜN ETİMOLOJİSİNE DAİR
No full textTürkçe söz varlığı, farklı dönemlerde ve çeşitli Türk lehçeleriyle yazılmış en eski kaynaklardan günümüze kadar değişime açık bir şekilde gelişim göstermiştir. Türkçenin zengin bir sözcük türetme sistemine sahip olması, sözcüklerin oluşum aşamalarında pek çok ses ve şekil değişimine maruz kalmasına, kimi zaman türetilmiş olduğu kökten farklı görünüşe sahip yeni sözcükler türetilmesine yol açmıştır. Bu durum, en eski sözcüklerin kökenleriyle ilgili kesin ve açık çıkarımlarda bulunmayı güçleştirmektedir. Bu sözcüklerden biri de eski Uygur Türkçesinden itibaren tanıklanan yalğan “yalan” sözcüğüdür. Bugüne kadar sözcüğün kökeniyle ilgili çeşitli çıkarımlarda bulunulmuş olmasına rağmen bu çalışmaların çoğunda sözcük, ya farazi bir fiil köküne dayandırılmış ya da farklı kavram alanlarına ait sözcüklerle ilişkilendirilmiştir. Bu durum, sözcüğün kökeniyle ilgili kesin bir etimolojik çözümlemenin yapılamamasına neden olmuştur. Bu çalışmada yalğan “yalan” sözcüğü ile al “hile, kandırma” sözcüğü arasında anlam yakınlığına dayalı bir bağ kurulmuş ve sözcüğün etimolojisine dair önerilerde bulunulmuştur. Nitekim al “hile, kandırma” sözcüğü ve türevlerinin temelinde kandırmak anlamı yatmakta ve yalan sözcüğüne ait kavram alanını yansıtan söz varlığı bulunmaktadır. Yalğan “yalan” sözcüğünün oluşum aşamaları ve geçirdiği ses değişimleri tarihî ve çağdaş Türk lehçelerinden örneklerle tanıklanarak al “hile, kandırma” sözcüğünden yapılmış diğer türevlerle ilişkilendirilmiştir. Çalışmada, sözcüğün kökenine dair yeni bir bakış açısı sunularak hazırlanacak etimolojik sözlüklere katkıda bulunulması amaçlanmıştır.Turkic vocabulary has evolved in a way that has remained open to change, from the earliest sources written in various Turkic dialects across different historical periods to the present day. The fact that Turkic has a rich word derivation system has led to the words being exposed to many phonetic and morphological changes during their formation stages and sometimes to the generation of new words that have a different appearance from the root from which they were derived. This situation makes it difficult to draw definitive and clear inferences about the origins of the oldest words. One of these words is yalğan (meaning “lie”), which has been attested since Old Uyghur Turkic. Although various inferences have been made about the origin of the word to date, in most of these studies the word has either been based on a hypothetical verb root or associated with words belonging to different conceptual fields. This situation has led to the inability to make a definitive etymological analysis of the word’s origin. In this study, a connection based on the semantic similarity between the words yalğan (meaning “lie”) and al (meaning “deception, trickery”) has been established, and suggestions regarding the etymology of the word have been made. Indeed, the word al “trickery, deception” and its derivatives are based on the meaning of deceiving and reflect the lexical field associated with the word “yalan”. The stages of formation and phonetic changes of the word yalğan “lie” have been attested with examples from historical and contemporary Turkic dialects and it has been related to other derivatives made from the word al “trickery, deception”. In this study, a new perspective on the origin of the word has been presented with the aim of contributing to future etymological dictionaries
OPINIONS OF EDUCATION STAKEHOLDERS ON FEMALE SCHOOL ADMINISTRATORS IN THE CONTEXT OF THE QUEEN BEE SYNDROME
No full textThe perspectives of nurses, as prominent advocates in sustainability, on the global climate crises and its impact on mental health
No full textObjective: To evaluate the perspective of nurses in Turkey towards the global climate crisis and its impact on mental health using a qualitative approach. Materials and Method: This study was conducted from August to September 2023 with 35 nurses living in seven regions of Turkey using an inductive qualitative approach. The researchers employed the snowball sampling method to select participants. Interviews with the participants were conducted until data saturation was reached. Thematic analysis was used to emerge themes. Results: The findings revealed five main themes (perception of the global climate crisis, effects of the global climate crisis, effects of the global climate crisis on mental health, reflections of the global climate crisis on nursing and nurses' views on prevention and intervention studies for the global climate crisis). Also, the findings revealed 12 sub-themes (physical outcomes, mental outcomes, direct and indirect impacts, psychosocial effects and personal, national and international-based reflections). Conclusion: Our study indicates that nurses exhibit genuine concern for the global climate crisis and experience psychological effects related to this pressing environmental issue. Nurses are keenly aware of their responsibility to safeguard the planet and demonstrate a strong sense of concern for the state of the world. Impact: It is evident that nurses, being prominent advocates for sustainability, are cognizant of their responsibility to protect the planet and demonstrate genuine apprehension for the state of the world. Implications: Nurses play a crucial role, as they make up 60% of the global healthcare workforce and are often the frontline healthcare professionals during natural disasters. It is vital to elucidate and clarify the terminology concerning the relationship between the climate crisis and the mental health of nurses, to determine the scope of this relationship and to make recommendations for future research areas. Patient or Public Contribution: No patient or Public Contribution
Van-Akdamar Adası ve Kilisesi Ziyaretçi Deneyimleri Üzerine Netnografik Bir Araştırma:Tripadvisor Örneği (A Netnographic Study on Visitor Experiences of Van-Akdamar Island and Church:The Case of Tripadvisor)
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Artificial Neural Network Models for Solar Radiation Estimation Based on Meteorological Data
No full textThe presence of solar energy in a particular area is closely related to meteorological parameters in that region. In this study, solar radiation estimation was carried out by using meteorological data recorded in different time series. Artificial neural networks (ANN) models were developed to determine the most effective parameters for solar radiation estimation. During the training and testing of ANN, site-specific meteorological data recorded by a meteorological station established in Hakkâri, Turkey, which has difficult climatic conditions, were used. To estimate solar radiation, basic input variables such as ambient temperature (T), wind speed (w), relative humidity (H), and atmospheric pressure (P), were modified by keeping the time series constant. To obtain the best estimation result, the number of input parameters of the input layer was applied with different possible input combinations, and the hidden layer neuron was changed to be multiples of the input layer (n, 2n, n²). The performance of all models was analyzed using statistical tools. ANN model, which has all possible combinations of input variables and determines the number of neurons in the hidden layer by framing the number of input variables, yielded the best estimation result. The performance indicator showed the mean square error (MSE) as the lowest value of 2.56 with all data entries and modeling the number of neurons in the hidden layer as n2. The mean absolute percentage error (MAPE) and relative root mean square error (rRMSE) values were obtained within the limits of high estimation accuracy in the network combination of T, P and H parameters as 1.99% and 1.91%, respectively. This study has revealed that increasing the variety and number of meteorological parameters affects solar radiation estimation success, but only basic meteorological parameters achieve very high estimation results
