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Öğe A Model Suggestion on Smart Home Systems(Akademik Bilişim Araştırmaları Derneği, 2021) İlkbahar, Fatih; Ünal, Şeyma; Karakaya, Armağan Tuğçe; Eren, BayramToday, the use of technology has become more widespread in order to facilitate home and business life. With the ever-evolving and changing technology, the concept of smart home has emerged. Our homes are becoming smart as we employ remote management and security solutions. Smart homes are living spaces that give us time, confidence, speed and comfort. In this busy life, while being away from home, the devices that cause energy waste can be controlled remotely, and the entrance to the house can be controlled, providing a more economical, safer and more comfortable life for users. In this study, the control of the AC lamps in the prototype house and the camera located in the garden entrance are carried out with a short message sent via the Telegram application. In addition, the face of the person entering the house is detected with the face recognition system and the system sends the information of the person entering to the owner as a notification via Telegram. Thus, it is aimed to create a safer environment at the entrance to the house.Öğe Analysis of Artificial Intelligence Technologies Used In The Covid-19 Outbreak Process(İsmail SARITAŞ, 2020) İlkbahar, Fatih; Sungu, EylulIn the course of the outbreak of coronovirus (Covid-19), which emerged in Wuhan, China at the end of 2019, and then spread all over the world, the biggest assistants in the fight against this virus were the technologies which used. Today, the areas where artificial intelligence is applied and the developments in the focus of artificial intelligence lead the technology. With Industry 4.0, there is no need for manpower to meet especially unqualified workforce in many business sectors. The idea of doing things by machines has begun to cause serious changes in the world. In order for the work to be done by the machines, importance has been given to the development of the decision making capabilities of the machines. The decision-making ability of the machines is based on previous periods. The lack of necessary computer hardware parts in testing the hypotheses made in the previous periods caused. It has not been applied in the past due to the high time and cost of hypotheses developed. Today, as a result of the rapid growth of technology, hardware elements with high processing capability can now be obtained at affordable prices. As a result of the acceleration of the developed hardware elements, many methods that took a long time in the past have reached the level that everyone can apply. We observe that what needs to be done for digital transformation in our country has been tested in many sectors. The most basic element for digital transformation is artificial intelligence technology. This is an indication that artificial intelligence technologies have started to be used in many areas of our lives. Accordingly, the use of artificial intelligence technologies in different areas, especially in medicine, played an important role in combating the epidemic during the coronavirus (Covid-19) epidemic process. In this study, the concept of artificial intelligence and the usage areas of artificial intelligence techniques are discussed in the literature section. Then, the applications developed using artificial intelligence technologies during the coronavirus (Covid-19) epidemic process were evaluated and the adequacy of the applications developed by analysing in the method section was discussed.Öğe Performance Analysis of Face Recognition Algorithms(Ieee, 2017) İlkbahar, Fatih; Kara, ResulThe usage areas of biometric systems are becoming widespread in today's technology. Face recognition systems among biometric systems; Ease of use, reliability, cost, etc., the preference between public institutions, commercial enterprises and researchers is increasing. In this study, it is suggested that students should use face recognition system instead of traditional methods of absenteeism in education and training institutions. It is very important that face recognition systems work quickly with matching people correctly. In this study, the training and recognition times of Eigenfaces, Fisherfaces and Local Binary Pattern algorithms used in face recognition systems are calculated by using Visual C ++ and Python programming languages using ORL dataset.Öğe Video görüntüleri üzerinde FPGA ile gerçek zamanlı yüz eşleştirme(Düzce Üniversitesi, 2020) İlkbahar, Fatih; Kara, ResulGüvenlik sistemlerinin gelişmesiyle kimlik tanımayı ve doğrulamayı sağlayan biyometrik sistemlerin günümüzde kullanımı yaygınlaşmıştır. Biyometrik doğrulama yöntemlerinden biri olan yüz tanıma, günümüzde en çok tercih edilenlerden biri olmuştur. Bu çalışmada geleneksel yüz tanıma sistemleri (YTS) yöntemlerinde kullanılan Özyüzler, Fisheryüzleri ve Yerel İkili Örüntü tanıma algoritmaları incelenmiştir. İncelenen algoritmalarda aynı anda yapılması gereken işlem sayısı fazla olmasından dolayı zaman verimliliğinin düştüğü anlaşılmıştır. Bu çalışmada yaygın kullanılan bilgisayar işlemcilerinin performansının düşük kaldığı aynı andaki çoklu işlemlerin hesaplanması için donanım tabanlı hızlandırılmış yeni bir yüz eşleştirme sistemi gerçekleştirilmiştir. Önerilen donanım tabanlı algoritma için Xilinx Artix-7 serisinden FPGA içeren Nexys 4 DDR kartı kullanılarak analiz işlemleri yapılmıştır. Önerilen yöntemin zaman kazancının 5.7 kat daha hızlı olduğu gösterilmiştir. İyileştirilen Yerel İkili Örüntü yöntemi modüler bir yapıda esnek olarak tasarlandığı için daha gelişmiş özellikteki FPGA kartlarında da uygulanabilir olduğu görülmüştür. Sistem, ORL veri seti kullanılarak test edilmiştir. Geliştirilen yöntemin günlük hayatta kullanımına ilişkin iki örnek üzerinde uygulaması yapılmış ve geçerli sonuçlar alınmıştır.Öğe What is the impact and efficacy of routine immunological, biochemical and hematological biomarkers as predictors of COVID-19 mortality?(Elsevier, 2022) Huyut, Mehmet Tahir; Huyut, Zübeyir; İlkbahar, Fatih; Mertoğlu, CumaIt remains important to investigate the changing and impact of routine blood values (RBVs) in order to predict mortality and follow an appropriate treatment in COVID-19 patients. In the study, the importance of RBVs in the mortality of patients with COVID-19 was investigated. The changes in the biochemical, hematological, and immunological parameters of patients who recovered (n = 4364) and died (n = 233) from COVID-19 over time and their relationship with the mortality of the disease were evaluated retrospectively. Odds ratios of the parameters affecting one-month mortality were calculated by running multiple-logistic-regression analysis. The cut off values and diagnostic efficiencies of the parameters that posed a risk for mortality were obtained via receiver operating curve analysis. It was determined that the C-reactive protein (CRP), D-dimer, procalcitonin, erythrocyte-sedimentation-rate (ESR), troponin values were at abnormal levels until death occurred in the patients who died. In addition, the procalcitonin levels were consistently high in patients who died. The patients who died generally had a sustained increase in their leukocyte and neutrophil levels and biochemical variables, and an ongoing decrease in lymphopenia and eosinopenia levels. Although significant changes were observed in liver function tests, cardiac troponin, hemogram values, kidney function tests and parameters related to inflammation in deceased patients, high ESR, international-normalized-ratio (INR), prothrombin-time (PT), CRP, D-dimer, ferritin and red-cell-distribution width (RDW) values, respectively, were the most effective predictive mortality risk biomarkers of COVID-19. In addition, neutrophilia, leukocytosis, thrombocytopenia, erythrocytopenia were other risk predictors of mortality. Indicators was found in this study can be successfully used to predict mortality from COVID-19.
