Enstitüler / Institutes
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Item Effects of Repair Techniques and Scarf Angles on Mechanical Performance of Composite Materials(2023) Karaduman, Beyza Naz; Elaldi, Faruk; https://orcid.org/0000-0003-0592-6868; AAG-5060-2019Today, composite materials, which have the advantage of strength and lightness ratio, have gained great importance especially in the aeronautical industry and automotive sector. With widespread use of composites, the repair of damages caused by external factors has also become an important research topic. In this study, the effects of different repair methods and scarf angles on the mechanical performance of the material were investigated. Scarf angles of 20 degrees, 30 degrees, and 45 degrees have been selected in order not to create too many scarf areas and to find a quick repair method. Also, a comparison of single scarf and double scarf repair was made to find a more robust solution. The samples were produced from carbon fiber prepreg and with the [45/0/90/0/45](2s) fiber orientation. Tensile, compression, and flexural (3-point bending) tests according to ASTM standards were applied to composite samples prepared with single scarf and double scarf repair configurations at different angles. The stress-strain curves obtained as a result of the tests showed that the specimens repaired at 20 degrees had the highest strength. In addition, it has been determined that the samples repaired with double scarf withstand higher forces compared to the samples repaired with single scarf at the same angle.Item The Effects of Instrument-Assisted Soft Tissue Mobilization and Kinesio Taping on Pain, Functional Disability and Depression in Patients with Chronic Low Back Pain: A Randomized Trial(2022) Cakmak, Ozge; Atici, Emine; Gulsen, MustafaPurpose: Low back pain is a common condition that can become chronic, which reduces the life quality of the patient by causing functional disability and depression. This study aimed to investigate the effects of instrument-assisted soft tissue mobilization (IASTM) and kinesio taping (KT) along with conservative treatment in patients with chronic nonspecific low back pain (CNLBP). Methods: A total of 30 patients with chronic low back pain aged between 30-50 years included in the study were randomized to IASTM (n=15) and KT (n=15) groups. Both the groups underwent conservative treatment that comprised of a hot pack, ultrasound, transcutaneous electrical nerve stimulation (TENS) and home exercises. In this study, assessments were made using the Visual Analogue Scale (VAS), Roland Morris Disability Questionnaire (RMDQ), and Beck Depression Inventory (BDI). The measurements were carried out at the beginning and end of the treatment. Results: As a result of the study, IASTM method improved in parameters such as pain (p<0.05), functionality (p=0.001) and depression (p<0.05). As a result of the study, the KT group improved in parameters such as pain, functionality and depression compared to pre-treatment (p<0.05). However, the two treatments were not superior to each other in pain (p=0.241), functionality (p=0.687) and depression (p=0.699) parameters. Conclusion: It has been observed that both treatments have positive effects on many parameters such as pain, disability, depression and mental state in patients with CNLBP. This study demonstrates that IASTM and KT treatments can be used to support therapeutic effects in patients with CNLBP.Item Relationship Between Exercise Perception With Physical Activity Level, Body Awareness, and Illness Cognition in Renal Transplant Patients: A Pilot Study(2019) Tigli, Ayca; Soy, Ebru Hatice Ayvazoglu; Aytar, Aydan; Moray, Gokhan; Haberal, Mehmet; https://orcid.org/0000-0002-0993-9917; https://orcid.org/0000-0003-2498-7287; https://orcid.org/0000-0002-3462-7632; 30777573; AAC-5566-2019; HIR-3735-2022; AAE-1041-2021; AAJ-8097-2021Objectives: Transplantation offers better quality of life and long-term survival benefits. Further knowledge is needed regarding exercise in daily life of transplant recipients. Here, we investigated the relationship between exercise perception and physical activity level, body awareness, and illness cognition in renal transplant patients. Materials and Methods: Our study included 53 renal transplant recipients (Standardized Mini-Mental Test score = 26.35 +/- 1.36; age = 41.11 +/- 13.52 year, body mass index = 25.96 +/- 5.26 kg/m(2), elapsed time after transplant = 3.68 +/- 1.53 year). Perceived benefits and barriers to exercise, physical activity level, body awareness, and illness cognition were assessed with the Exercise Benefits/Barriers Scale, International Physical Activity Questionnaire, Body Awareness Questionnaire, and Patient Illness Perception Questionnaire, respectively. Correlations were established with Spearman test for nonparametric data, with regression analysis used to find determinants of physical activity levels. Results: We observed correlations between physical activity level and perceived benefits and barriers to exercise. There was a positive relationship between body awareness and perceived benefits and barriers to exercise and also illness cognition, with significant correlation between perceived benefits and barriers to exercise and illness cognition (P < .05). Perceived benefits and barriers to exercise (P = .006, R = 0.373, R2 = 0.139, beta = 0.373, t = 2.867, F = 8.22) were determining factors for physical activity level. Conclusions: Psychologic and physical factors, including negative emotions and body dissatisfaction, are risk factors for poor quality of life. Although it is important to increase quality of life, tools to enhance body awareness and to develop strategies to alter motor behaviors in daily living activities are needed. Treatment and assessment strategies on body awareness and illness perception should be considered, with emphasis on the importance of physical activity posttransplant.Item Omics in Oxidative Stress Tolerance in Crops(2019) Kayihan, Ceyhun; Eyidogan, Fusun; https://orcid.org/0000-0003-1684-4147; Q-4515-2016; ACA-9644-2022Item How patients perceive healthcare services: A case of Ayub Teaching Hospital, Abbottabad - Pakistan. SERV Service QUAL Quality(2018) Ali, MuhammadA field study was conducted in Ayub Teaching Hospital in the outpatient department, to evaluate the level of service quality offered by the healthcare services with a view to identifying the relationship between service quality dimensions and overall service quality. The researchers used the SERVQUAL instrument for the purpose of assessing the quality of the service offered by the healthcare workers at the outpatient department in Ayub Teaching Hospital. A sample of 246 patients in the outpatient department participated in the questionnaire survey. Descriptive statistics were used to find out mean values and variance between actual values from perceived values. To assess the strength of model regression, the aforementioned technique was adopted. The study results showed that there exists a gap between patients' expectation and actual services offered by the healthcare workers. There were five dimensions that were assessed: tangibles, reliability, responsiveness, assurance and empathy. The results revealed that patients are dissatisfied with three dimensions (tangibles, reliability and assurance), but they are satisfied with the other two dimensions (responsiveness and empathy). This research adopts the marketing concept to measure the healthcare services. The SERVQUAL tool was modified as per need to meet the requirements in accordance with the nature and scope of the research. Patients' attitudes toward service quality dimensions were the concern of the research. To get a comprehensive evaluation of service quality, healthcare providers have to be considered in future research. Based on the findings of this study, Ayub Teaching Hospital's (ATH) management is in a position to recognize the patients' perceptions about the healthcare services and offer them service accordingly. Results can be used by management and government policymakers regarding healthcare to bring better and more effective services. Consequently, based on the results, new structure can be designed by adopting strategies that improve the quality of services in order to provide effective services and gain patients' satisfaction and propensity to further recommend the services of healthcare to other patients. This study investigates the healthcare quality in a small area in Pakistan. Pakistan is a developing country. Future research can adopt the SERVPREF technique, which is a more developed technique than SERVQUAL in order to measure service quality as it provides a two-factor solution for the dimensionality of health service quality.Item Encryption and multi-share-based seganography methods on images with low spectral resolution(Başkent Üniversitesi Fen Bilimler Enstitüsü, 2023) Çiftçi, Efe; Sumer, EmreSteganography is the name given to secret communication methods that third parties cannot detect. This secret communication is performed by hiding the secret information to be transmitted on a carrier medium so that the carrier does not raise any suspicions. Steganography science, of which many examples can be presented from the past to the present, has gained new application areas with the development of digital technologies. This thesis aims to develop new steganography methods that hide secret messages in plain text format on binary images, which have a lower spectral resolution when compared to color or grayscale images, used in digital devices as carriers. It has been observed that all implemented methods can successfully hide considerable lengths of plaintext payloads on binary images generated by both thresholding and halftoning methods, and this finding has been reinforced with conducted objective and subjective evaluations. Steganografi, üçüncü şahıslar tarafından tespit edilmeyecek şekilde gizli iletişim kurma yöntemlerine verilen isimdir. Bu gizli iletişim, iletilmek istenen gizli bilginin şüphe uyandırmayacak bir şekilde bir taşıyıcı ortamın üzerine gizlenmesiyle gerçekleşir. Geçmişten günümüze bir çok örneği sunulabilen steganografi bilimi, dijital teknolojilerin gelişmesiyle yeni uygulama alanları kazanmıştır. Bu tezin amacı, düz metin biçimindeki gizli mesajları, taşıyıcı olarak dijital cihazlarda kullanılan renkli veya gri tonlu görüntülere kıyasla daha düşük spektral çözünürlüğe sahip ikili görüntüler üzerine gizleyecek olan yeni steganografi yöntemlerinin geliştirilmesidir. Geliştirilen tüm yöntemlerin hem eşikleme, hem de yarıtonlama yöntemleriyle üretilen ikili görüntülere büyük uzunluklarda düz metin türünde veriyi başarıyla gizleyebildikleri görülmüş ve yapılan objektif ile subjektif değerlendirmelerle de bu bulgu pekiştirilmiştir.Item Videolarda insan eylemlerini tanımada poligon tabanlı öznitelik çıkarımı(Başkent Üniversitesi Fen Bilimleri Enstitüsü, 2023) Gocmen, Ogul; Akata, Murat EminVideolardaki insan eylemlerinin tanınması ve sınıflandırılması için, silüet tabanlı yeni bir öznitelik çıkarma yöntemi önerilmiştir. Bu amaçla, “Hareket Geçmişi Görüntüsü (HGG)” ve “Poli-Siluet (PoS)” adı verilen yeni görüntü şekilleri, yeni bir “Poligonlaştırma Algoritması (PoG)” ve yeni bir “Poligon Kodlama Algoritması (PoC)” geliştirilmiştir. Önerilen yöntem, “Silüet Videolarından (SiVi)” , HGG’lerin elde edilmesi, daha az köşeye indirgenerek poligon formuna dönüştürülmesi ve kodlanmasına dayanmaktadır. Geleneksel siluet oluşturma yöntemleri siluetlerin gövde bütünlüğünü tek başlarına karşılayamadıklarından, bu sorunu aşmak için, görüntü ve videolarda yer alan insan ve nesneler üzerinde örnek bölütlemesi yapabilen Yolact++’ın kodları değiştirilerek, modelin ürettiği insan maskeleri ile SiVi’ler oluşturulmuştur. Hareketi daha iyi tanımlayan HGG’ler, ardışık olmayan SiVi karelerindeki silüetleri ağırlık merkezlerine göre toplanması ile elde edilir. Poligonlaştırma işlemi, HGG görüntülerine uygulanır. PoG, eğri şekilleri ve görüntülerin poligonlaştırılmasına dayansa da, çalışması tam olarak bunlara benzemez. PoG, HGG’nin kontur koordinatlarını hızlı bir şekilde istenilen boyuta indirger. Elde edilen poligonlaştırılmış HGG görüntülerine PoS adı verilir. PoC algoritması, PoS görüntüsünü parametre olarak alır ve içerisindeki şeklin sol üst köşe koordinatından başlayarak, saat yönünün tersinde dolanırken, üzerinden geçilen her bir kenar ile bir vektör oluşturur. Bu esnada vektörün, çalışmada belirlenen sekiz adet açısal alandan hangisine iz düşümü olduğunu hesaplayarak, ilgili vektörün kodunu belirler. Bir PoS’un tüm kenar vektörlerinin kodları, dolaşılma sırasıyla dizi içine kaydedildiğinde, o vektörler ile oluşan PoS için poligon kodu elde edilir.Uzun poligon kodları ile kolay işlem yapılabilmek ve farklı uzunlukta vektörler oluşturulabilmek için, genetik algoritmada kullanılan k-mer gruplandırma tekniği benzeri bir yaklaşım çalışmada geliştirilmiştir. Düşünülen işlem poligon kodunun normalizasyonunu sağlamakla kalmamış, aynı zamanda poligon kodunun adaptif bir çekirdeğe göre uyarlanmasını doğurarak çalışmada önceden düşünülmeyen, farklı bir boyuta bu çalışmayı taşındığı görülmüştür. Gruplama k boyu olarak farklı uzunluklar seçilmiş ve poligon kod grupları, k boyuna göre oluşabilecek en büyük kodlara bölünerek normalize edilmiştir. Önerilen öznitelik çıkarma yöntemi, herhangi bir aksiyon videosunun karelerinden elde edilmiş PoS üzerinde eşit uzunlukta öznitelik vektörlerinin üretilmesini garanti eder, bu durum, boyut sorununun üstesinden gelmek için ekstra boyut indirgeme algoritmalarının kullanımına ihtiyacı ortadan kaldırır. Farklı k-mer uzunlukları, çalışmada kullanılan veri setleri üzerinden elde edilen öznitelik vektörlerinde denenerek “işlem hızı” ile “sınıflandırma doğruluğu” karşılaştırmaları yapılmıştır. Yöntem, HMDB51 ve UCF101 veri setleri üzerinde denenmiş en iyi performans veren k-mer boyu ve sınıflandırma doğruluk sonuçları, diğer çalışmalarla karşılaştırılmış ve daha başarılı sonuçların elde edildiği görülmüştür. Ayrıca, çalışmaya özgü hazırlanan Yoga veri seti üzerinde HGG görüntülerinin farklı formları ile ek olarak derin ağ uygulamaları da gerçekleştirilmiş ve kayda değer cesaretlendirici sonuçlar alınmıştır. A new silhouette-based feature extraction method for the recognition and classification of human actions in videos is proposed. For this purpose, new image forms called “Motion History Image (HGG)” and “Poly-Silhouette (PoS)”, a new “Polygonization Algorithm (PoG)” and a new “Polygon Encoding Algorithm (PoC)” have been developed. The proposed method is based on obtaining HGGs from “Silhouette Videos (SiVi)”, converting them to polygon form with fewer corners and encoding them. Since traditional silhouette creation methods cannot meet the body integrity, to overcome this problem, the codes of Yolact++ were changed and human masks produced by the model is saved as SiVis. HGGs that better describe motion have been obtained by summing the silhouettes in non-consecutive SiVi frames according to bounding box centroids. The polygonization process has been applied to the HGG images. PoG quickly reduces the contour coordinates of the HGG to the desired size. The resulting polygonized HGG images are called PoS. The PoC algorithm takes the PoS image as a parameter and creates a vector with each edge, starting from the upper left corner coordinate, while tracing in counterclockwise direction. It calculates the related vector code by projecting the vector on to the area that are presented in the study. When the codes of all edge vectors of a PoS are recorded, the polygon code for the PoS is formed. An approach similar to the k-mer grouping technique in genetic algorithms has been developed in order to be able to process with long polygon codes and to create feature vectors of different lengths. This idea not only provided for the normalization of the code, but also for the adaptation of the code according to an adaptive kernel. Different lengths were chosen as k and groups were normalized by dividing them into the largest codes according to the k length. The proposed feature extraction method guarantees the generation of feature vectors of equal length on PoS, eliminating the need for the use of extra dimension reduction algorithms to overcome the size problem. Different k-mer lengths were tested on HMDB51 and UCF101 datasets and comparisons of "processing speed" and "classification accuracy" were made. The results of best k-mer and classification accuracy were compared with studies and it was found that more successful results were obtained. In addition, extra deep network applications were performed out on the yoga dataset created specifically for the study, and remarkable encouraging results were obtained.Item Automated Audio Captioning with Acoustic and Semantic Feature Representation(Başkent Üniversitesi Fen Bilimleri Enstitüsü, 2023) Ozkaya Eren, AysegulToday, audio data is increasing rapidly with the developing technology and the increasing amount of data. Therefore, there is a need for understanding and interpretation of the content of audio data by human-like systems. Generally, audio processing studies have focused on speech recognition, audio event/scene, and tagging to process audio data. Speech recognition aims to translate a spoken language into text. Audio event/scene and tagging studies make single or few-word explanations of an audio recording. Unlike the previous studies, automatic audio captioning aims to explain an environmental audio record with a natural language sentence. This thesis explores the importance of using semantic information to improve audio captioning performance after a detailed literature study on audio processing, image/video, and audio captioning. In this context, computational models have been developed using linguistic knowledge (subject-verbs), topic model, knowledge graphs, and acoustic events for audio captioning. As a methodology, the contributions of different features, word embedding methods, deep learning architectures and datasets, and the contribution of semantic information to audio captioning were examined. Within the scope of the studies, two publicly open audio captioning datasets were used. The success of the models proposed in the thesis was compared with the studies using the same datasets. The results show that the proposed methods improve AAC performance and give results comparable to the literature. Günümüzde gelişen teknoloji ve artan veri miktarı ile birlikte ses verileri de hızla artmaktadır. Bu nedenle, ses verilerinin içeriğinin insan benzeri sistemler tarafından anlaşılmasına ve yorumlanmasına ihtiyaç duyulmaktadır. Genel olarak ses işleme çalışmaları konuşma tanıma, ses olay/sahne tanıma ve ses etiketlemeye odaklanmıştır. Konuşma tanıma, konuşulan bir dili metne çevirmeyi amaçlar. Ses olay/sahne tanıma ve etiketleme sistemleri, bir ses kaydına tek veya birkaç kelimelik açıklamalar yapar. Otomatik ses başlıklandırma ise önceki çalışmalardan farklı olarak çevresel bir ses kaydını doğal bir dil cümlesi ile açıklamayı amaçlar. Bu tez, ses işleme, görüntü/video ve ses başlıklandırma üzerine ayrıntılı bir literatür çalışmasının ardından ses başlıklandırma performansını iyileştirmek için anlamsal bilgileri kullanmanın önemini araştırmaktadır. Bu bağlamda, otomatik ses başlıklandırma için dilbilimsel (özne-fiiller), konu modeli, bilgi çizgesi ve akustik olaylar kullanılarak sayısal modeller geliştirilmiştir. Metodoloji olarak, farklı özniteliklerin, kelime gömme yöntemlerinin, derin öğrenme mimarilerinin ve veri kümelerinin katkıları ve semantik bilginin ses başlıklandırmaya katkısı incelenmiştir. Çalışmalar kapsamında iki adet ses başlıklandırma veri seti kullanılmıştır. Tezde önerilen modellerin başarısı, aynı veri setlerini kullanan çalışmalarla karşılaştırılmıştır. Sonuçlar, önerilen yöntemlerin otomatik ses başlıklandırma performansını iyileştirdiğini ve literatürle karşılaştırılabilir sonuçlar verdiğini göstermektedir.Item Teacher Competencies for Differentiated Instruction Approach(2022) Zoraloglu, Saadet; Sahin, Ali EkberDifferentiated instruction is an approach ensuring the fairness in education. Therefore, it is a professional responsibility of teachers to differentiate the instruction. In this study, it is aimed to specify the competencies for the differentiated instruction approach. In compliance with the nature and context of the research question, the method of examination of the relevant field literature was chosen to specify the competencies. In this research, document analysis method, one of the qualitative approaches, was used. The data source of the study consist of peer reviewed publications and basic reference books related to the differentiated instruction approach. Competencies specified through the analysis of the data sources are grouped under the certain themes along with their findings. Subsequently, competencies were finalized by taking the expert opinions. As a result of the research, 39 teacher competencies were identified under the three competency area; knowledge, skill and belief. In line with the use of the identified competencies, suggestions for research and practice were made.Item How To Improve The Quality Of Online Education From Online Education Directors' Perspectives(2022) Akbaba Altun, Sadegul; Johnson, Tristan E.COVID-19 pandemic showed once again the need for quality in online education all over the world. The aim of this research is to solicit how to improve the quality of online education from online education program directors' perspectives. The research was designed as a qualitative case study. Eight participants who were responsible for directing, managing, supervising and organizing online education programs participated to this study. The data were collected through interviews and were analyzed through content analysis. Eight dimensions were found to improve the quality of online education. These dimensions were focusing on students' needs; focusing on change in education; focusing on system as a whole; focusing on leadership; focusing on continuous improvement of online education; focusing on integrating learning and teaching theories into online education; focusing on research about online education; and focusing on quality of instructors.