Fakülteler / Faculties

Permanent URI for this communityhttps://hdl.handle.net/11727/1395

Browse

Filters

202415

Settings

Has files: Nosearch.filters.applied.f.language: search.filters.language.en_US

Search Results

Now showing 1 - 10 of 15
  • No Thumbnail Available
    Item
    Use Of Advanced Measurement And Reality Technologies In Cultural Heritage Sites From The Perspective Of Technology And Tourism
    (Başkent Üniversitesi Ticari Bilimler Fakültesi, 2024-03-12) Varol, Fatih; Oksuz, Merve
    In recent years, in parallel with technological innovations, the use of modern techniques instead of traditional methods has become widespread in studies on archiving, preserving, restoring and visiting cultural heritage (CH) in the digital environment. Reality technologies, advanced measurement methods in engineering and mobile applications have brought a multidisciplinary perspective to the subject of sustainability of CH sites and visiting them within the scope of tourism. This study investigates the contribution of studies carried out with the latest technological opportunities in CH areas to sustainability and tourism activities. It reveals with the most concrete examples how the fastest LIDAR (Light Detection and Ranging) technology used in remote sensing of concrete objects, as well as close range photogrammetry and unmanned aerial vehicle (UAV) photogrammetry applications can be integrated into the sustainability of CH and reality technologies. The three-dimensional (3D) images obtained in this way have enabled world-famous ancient cities, museums, natural and archaeological sites to be visited virtually with the help of augmented reality (AR), virtual reality (VR) and mixed reality (MR) applications. These methods also provide significant advantages in terms of time and cost compared to traditional technologies in the digital documentation of CH and VR studies.
  • No Thumbnail Available
    Item
    Comments on "Accounting for Fractionation and Heterogeneous Dose Distributions in the Modelling of Osteoradionecrosis in Oropharyngeal Carcinoma Treatment"
    (Başkent Üniversitesi Diş Hekimliği Fakültesi, 2024-03-25) Somay, Efsun; Yilmaz, Busra; Topkan, Erkan
  • No Thumbnail Available
    Item
    Tooth Extraction and Osteoradionecrosis
    (Başkent Üniversitesi Diş Hekimliği Fakültesi, 2024-04-08) Topkan, Erkan; Somay, Efsun; Selek, Ugur
  • No Thumbnail Available
    Item
    Functional Connectivity In Rumination: A Systematic Review Of Magnetic Resonance Imaging Studies
    (Başkent Üniversitesi, 2024-02-18) Misir, Emre; Alici, Yasemin Hosgoren; Kocak, Orhan Murat
    IntroductionRumination, defined as intrusive and repetitive thoughts in response to negative emotions, uncertainty, and inconsistency between goal and current situation, is a significant risk factor for depressive disorders. The rumination literature presents diverse findings on functional connectivity and shows heterogeneity in research methods. This systematic review seeks to integrate these findings and provide readers diverse perspectives.MethodFor this purpose, the literature on functional connectivity in rumination was reviewed according to the PRISMA guidelines. Regional connectivity and network connectivity results were scrutinized according to the presence of depression, research methods, and type of rumination. After screening 492 articles, a total of 36 studies were included.ResultsThe results showed that increased connectivity of the default mode network (DMN) was consistently reported. Other important findings include alterations in the connectivity between the DMN and the frontoparietal network and the salience network (SN) and impaired regulatory function of the SN. Region-level connectivity studies consistently show that increased connectivity between the posterior cingulate cortex and the prefrontal cortex is associated with rumination, which may cause the loss of control of the frontoparietal network over self-referential processes. We have seen that the number of studies examining brooding and reflective rumination as separate dimensions are relatively limited. Although there are overlaps between the connectivity patterns of the two types of rumination in these studies, it can be thought that reflective rumination is more associated with more increased functional connectivity of the prefrontal cortex.ConclusionsAlthough there are many consistent functional connectivity outcomes associated with trait rumination, less is known about connectivity changes during state rumination. Relatively few studies have taken into account the subjective aspect of this thinking style. In order to better explain the relationship between rumination and depression, rumination induction studies during episode and remission periods of depression are needed.
  • No Thumbnail Available
    Item
    Exploring The Viability Of Alternative Cooling-Lubrication Strategies İn Machining Processes: A Comprehensive Review On The Performance And Sustainability Assessment
    (Başkent Üniversitesi Mühendislik Fakültesi, 2024-02-19) Roy, Soumikh; Das, Anshuman; Kumar, Ramanuj; Das, Sudhansu Ranjan; Rafighi, Mohammad; Sharma, Priyaranjan
    This paper explores the challenges of machining difficult-to-cut metals using tools like coated carbide, ceramics, and CBN under dry conditions, addressing issues such as heat generation, tool wear and friction, chip evacuation, surface integrity, vibration, and chatter. Though cutting fluids have historically improved machinability, environmental concerns, such as toxicity and non-biodegradability, are significant. Researchers aim to enhance the economic and ecological aspects of machining by reducing cutting fluid usage. This paper provides an overview of the performance assessment and sustainability evaluation of various cooling and lubrication methods during the machining of hard-to-machine as well as difficult-to-cut metals. Additionally, the literature review highlights various environmentally friendly cooling strategies, such as minimum quantity lubrication (MQL) and cryogenic arrangements. According to the results of this review, the utilization of various cooling and lubrication technologies has the potential to enhance both sustainability and machinability properties while prolonging the lifespan of cutting tools. The findings also show that there is a lot of room for improvement in terms of optimizing and making these cooling-lubrication solutions more practical and effective.
  • No Thumbnail Available
    Item
    Toxicities And Prognostic Factors In Elderly HPV-Associated Oropharyngeal Cancer Patients Treated With Radiotherapy Or Chemoradiotherapy
    (JOURNAL OF MEDICAL VIROLOGY, 2024-03-24) Topkan, Erkan; Somay, Efsun; Selek, Ugur
  • No Thumbnail Available
    Item
    ParsyBot: Chatbot for Baskent University Related FAQs
    (18TH IEEE INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING, ICSC 2024, 2024-05-17) Karkiner, Zeynep; Yaman, Begum; Zengin, Begum; Cavli, Feride Nursena; Sert, Mustafa
    Reading regulations and instructions may take lots of time and sometimes it results in disappointments. To avoid this issue, people are prone to use sources that provide fast and accurate answers while accessing the information. Chatbots, are one of the most popular trend topics nowadays, and may adapted into various fields e.g., healthcare, finance, and education. This paper proposes the development of ParsyBot which is a Turkish chatbot designed to inform users about the regulations, admissions, departments, scholarships, and social clubs of Baskent University. Furthermore, users may ask via voice in Turkish this feature is not common among the other chatbots. ParsyBot uses a pre-trained BERT model which is specifically trained with regulations and instructions of Baskent University. Parsybot runs on web and mobile platforms to make it available for everyone. Our experiments on the utilized dataset, ParsyBot, reached 0.81 in METEOR, and 0.24 in ROGUE-1, which are promising compared to the ChatGPT 3.5.
  • No Thumbnail Available
    Item
    Cost Of Hepatocellular Carcinoma In Turkiye: Results Of A Delphi Panel Analysis
    (VALUE IN HEALTH, 2024-12) Dane, F.; Tatar, M.; Goker, E.; Yildiz, B.; Saglam, S.; Karaca, M.; Seker, M.; Sendur, M. A.; Dilber, F.; Lacin, S.; Dulundu, E.; Kose, F.; Aydogan, D.; Ozturk, B.; Yalcin, S.
  • No Thumbnail Available
    Item
    Implementation of Smooth Transitions for Grid Connected PV System between the Operating Modes
    (18TH INTERNATIONAL CONFERENCE ON COMPATIBILITY, POWER ELECTRONICS AND POWER ENGINEERING, CPE-POWERENG 2024, 2024-10-02) Onar, Burak; Fesli, Ugur; Demirbas, Sevki
    The grid-connected PV microgrid needs coordination among the components, compromising the whole system to supply the power required by the loads. Well-designed energy management and control structures should be ensured to operate grid-connected PV microgrids with smooth and uninterruptible power. Much of the power system instability arises from transitions between grid-connected mode and island mode. This study introduces a control method to ensure a smooth transition between operating modes for PV microgrids operating in both grid-connected and island modes. The proposed control method has been verified with simulation performed with Matlab & Simulink simulation programs.
  • No Thumbnail Available
    Item
    Sarcasm Detection in News Headlines with Deep Learning
    (32ND IEEE SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, SIU 2024, 2024-12-05) Karkiner, Zeynep; Sert, Mustafa
    Sarcasm detection is one of the recent topics studied in the field of natural language processing. Although sarcasm detection is generally carried out through social media comments in the literature, it can also be applied to news headlines that are expected to be completely objective and reflect reality. In this study, sarcasm detection was carried out using various deep learning models in a dataset containing sarcastic and non-sarcastic news headlines. The accuracy of classification results of BERT, RNN, LSTM, and GRU models and their training time performance were compared. While the BERT model reached the highest accuracy (0.88), RNN was the most successful model in terms of training time performance.