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Publication Open Access An empirical investigation of four well-known polynomial-size VRP formulations(NA, 2018) Öncan, Temel; Department of Business Administration; N/A; Aksen, Deniz; Sadatizamanabad, Mirehsan Hesam; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; Graduate School of Sciences and Engineering; 40308; N/AThis study presents an in-depth computational analysis of four well-known Capacitated Vehicle Routing Problem (CVRP) formulations with polynomial number of subtour elimination constraints: a node-based formulation and three arc-based (single, two- and multi-commodity flow) formulations. For each formulation, several valid inequalities (VIs) are added for the purpose of tightening the formulation. Moreover, a simple topology-driven granulation scheme is proposed to reduce the number of a certain type of VIs. The lower and upper bounding performance and the solution efficiency of the formulations and respective VI configurations are benchmarked with state-of-the-art commercial optimization software. The extensive computational analysis embraces 121 instances with up to 100 customer nodes. We believe that our findings could be useful for practitioners as well as researchers developing algorithms for the CVRP.Publication Open Access Anne ve babası boşanan çocuğun soyadı ile ilgili Anayasa Mahkemesi’nin bireysel başvuru kararları hakkında ilk değerlendirmeler(2017) N/A; Karaşahin, Yasin Alperen; Law School; 257378Publication Open Access Artificial eye model and holographic display based IOL simulator(Society of Photo-optical Instrumentation Engineers (SPIE), 2023) N/A; Department of Electrical and Electronics Engineering; N/A; Şahin, Afsun; Ürey, Hakan; Aygün, Uğur; Kavaklı, Koray; Akyazı, Deniz; Faculty Member; Faculty Member; Department of Electrical and Electronics Engineering; School of Medicine; College of Engineering; Graduate School of Sciences and Engineering; 171267; 8579; N/A; N/A; N/ACataract is a common ophthalmic disease in which a cloudy area is formed in the lens of the eye and requires surgical removal and replacement of eye lens. Careful selection of the intraocular lens (IOL) is critical for the post-surgery satisfaction of the patient. Although there are various types of IOLs in the market with different properties, it is challenging for the patient to imagine how they will perceive the world after the surgery. We propose a novel holographic vision simulator which utilizes non-cataractous regions on eye lens to allow the cataract patients to experience post-operative visual acuity before surgery. Computer generated holography display technology enables to shape and steer the light beam through the relatively clear areas of the patient’s lens. Another challenge for cataract surgeries is to match the right patient with the right IOL. To evaluate various IOLs, we developed an artificial human eye composed of a scleral lens, a glass retina, an iris, and a replaceable IOL holder. Next, we tested different IOLs (monofocal and multifocal) by capturing real-world scenes to demonstrate visual artifacts. Then, the artificial eye was implemented in the benchtop holographic simulator to evaluate various IOLs using different light sources and holographic contents.Publication Open Access Cross-context news corpus for protest event-related knowledge base construction(Massachusetts Institute of Technology (MIT) Press, 2021) Department of Sociology; N/A; Department of Computer Engineering; Yörük, Erdem; Hürriyetoğlu, Ali; Gürel, Burak; Duruşan, Fırat; Yoltar, Çağrı; Mutlu, Osman; Yüret, Deniz; Faculty Member; Teaching Faculty; Faculty Member; Researcher; Researcher; Faculty Member; Department of Sociology; Department of Computer Engineering; College of Social Sciences and Humanities; Graduate School of Sciences and Engineering; College of Engineering; 28982; N/A; 219277; N/A; N/A; N/A; 179996We describe a gold standard corpus of protest events that comprise various local and international English language sources from various countries. The corpus contains document-, sentence-, and token-level annotations. This corpus facilitates creating machine learning models that automatically classify news articles and extract protest event-related information, constructing knowledge bases that enable comparative social and political science studies. For each news source, the annotation starts with random samples of news articles and continues with samples drawn using active learning. Each batch of samples is annotated by two social and political scientists, adjudicated by an annotation supervisor, and improved by identifying annotation errors semi-automatically. We found that the corpus possesses the variety and quality that are necessary to develop and benchmark text classification and event extraction systems in a cross-context setting, contributing to the generalizability and robustness of automated text processing systems. This corpus and the reported results will establish a common foundation in automated protest event collection studies, which is currently lacking in the literature.Publication Open Access Dynamic accommodation measurement using Purkinje reflections and ML algorithms(Society of Photo-optical Instrumentation Engineers (SPIE), 2023) Department of Electrical and Electronics Engineering; N/A; Aygün, Uğur; Şahin, Afsun; Ürey, Hakan; Faculty Member; Faculty Member; Department of Electrical and Electronics Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Engineering; School of Medicine; N/A; N/A; N/A; 171267; 8579We developed a prototype device for dynamic gaze and accommodation measurements based on 4 Purkinje reflections (PR) suitable for use in AR and ophthalmology applications. PR1&2 and PR3&4 are used for accurate gaze and accommodation measurements, respectively. Our eye-model was developed in Zemax and matches the experiments well. Our model predicts the accommodation from 25cm to infinity (<4 diopters) with better than 0,25D accuracy. We performed repeatability tests and obtained accurate gaze and accommodation estimations using 15 subjects. We are generating a large synthetic data set using physically accurate models and machine learning algorithms.Publication Open Access First case of severe late ovarian hyperstimulation syndrome in a patient who was treated with in-vitro maturation of human oocytes and planed short gonadotropin stimulation(Open Journal of Clinical and Medical Case Reports, 2016) N/A; Ata, Mustafa Barış; Faculty Member; School of Medicine; 182910In-vitro maturation is a technique used to perform assisted reproduction in women with high ovarian reserve, who are at risk for ovarian stimulation. With this technique occasionally 3-4 days of gonadotropins are planned to enlarge the follicles and aid in oocyte collection. Human choreinonic gonadotropin is also given to ease the collection. These few days of ovarian stimulation were felt to be insufficient to cause severe ovarian hyperstimlation syndrome. However, the case of a 32 year old women with polycystic ovary syndrome who underwent planned ovarian stimulation with four days of gonadotropins for a stimulated IVM cycle, and who developed severe ovarian hyperstimulation syndrome is presented. This is the first case of ovarian hyperstimulation syndrome in an IVM cycle. Clearly, only unstimulated IVM can be used to completely avoid ovarian hyperstimulation syndrome.Publication Open Access Raman spectroscopic and microscopic analysis of tissue type, molecular composition, and glioblastoma identification in brain tissue sections(Koç University, 2021) N/A; Torun, Hülya; Graduate School of Sciences and EngineeringGlioblastoma (GB) is the most common primary malignant brain tumor. Despite improvements in treatments, survival probability has remained shorter than 2 years for most patients over the last 20 years. Accurate diagnosis of GB requires pathological evaluation of the tumor tissues using light microscopy, along with routine or specialized staining. Recent research also identified significant genetic/epigenetic alterations that influence diagnosis, prognosis, and treatment in addition to routine pathological evaluation. Identification requires the tissue to be sampled many times and analyzed using different methods that require additional time, resources, and expertise. To determine whether the tissue used for routine analysis can also be used to perform more detailed and comprehensive analysis without staining, we propose to use Raman Spectroscopy (RS), which is a label-free and non-destructive technique. RS provides molecule-specific spectra from the chemical composition of the sample for rapid analysis. In this thesis, we investigated GB, white matter (WM), gray matter (GM), and necrosis (NC) regions of GB patients using RS to determine whether a similar precision can be achieved as the routine histomorphologic diagnostic process. First, we proposed a refined protocol for effectively clearing paraffin from Formalin-Fixed Paraffin-Embedded brain tissue sections, without destroying the sample morphology and chemical composition, for eliminating the substantial Raman spectra of paraffin. We demonstrated that the less expensive and less toxic clearing agent CleareneTM removes paraffin as effectively as p-Xylene, the mostly used clearing agent in histopathology laboratories. Thus, we suggest substituting CleareneTM with p-Xylene for deparaffinization of brain tissue sections for Raman spectral analysis. Second, we optimized the choice of Raman spectrum acquisition parameters (excitation wavelength, acquisition time, accumulation count,), tissue thickness, and Raman substrate type (CaF2, glass). Third, we acquired the Raman spectra of GB, WM, GM, and NC regions and analyzed the spectral profile regarding the Raman peaks given in the literature. Raman spectra of GB and WM regions (nGB = 20, nWM = 18), which were annotated by an expert neuropathologist, have been classified with 87.2±1% GB and 90.7±1% WM training/test accuracies using machine learning models (SVM, kNN, RF). The effect of pre-processing of Raman spectra on classification accuracies has been investigated. Sample preparation conditions, Raman acquisition protocols, and machine learning classification models showed a successful proof-of-concept demonstration for the proposed Raman-based GB identification workflow. While there is room for further refining the machine learning models for improved training and validation accuracies, these protocols could be improved for eventual clinical utility. Once the clinical applicability and refined classification accuracies are demonstrated, these protocols might assist neuropathologists in error-free identification of GB in the clinics.Publication Open Access Response to the call for evidence of the house of Lords Select Committee on artificial intelligence(The House of Lords, 2017) Channon, Matthew; Gürses, Özlem; Kouroutakis, Antonios; Scotti, Valentina Rita; N/A; Buğra, Ayşegül; Law School; 237477Publication Open Access The transtheoretical model use for smoking cessation(International Association of Social Science Research (IASSR), 2014) Koyun, Ayşe; N/A; Eroğlu, Kafiye; Faculty Member; School of Nursing; 6061Smoking addiction is considered a disease according to the International Classification of Diseases. There is a need regular treatment due to relapse occurrence. For this reason, the psychosocial dimension of the disease should be treated. Healthcare professionals are required to find the most convenient approach to provide healthy behaviours for individuals. In this review, the Transtheoretical Model use for smoking cessation is discussed. The Transtheoretical Model (TTM) has been presented as an integrative and comprehensive model of behaviour change. The TTM has concentrated on five stages of change (precontemplation, contemplation, preparation, action; and maintenance), 10 processes of change (focuses on activities and events that create successful modification of smoking), decisional balance (the pros and cons of changing), and self-efficacy (the self-confidence of individual regarding smoking cessation). Stages of change lie at the heart of the TTM. Processes of change, decisional balance and self-efficacy work best at each stage to reduce resistance, facilitate progress, and prevent relapse. The TTM enables the use of convenient interventions for the stage of change where individual is included and increases the success. The TTM based smoking cessation studies reported success rates from 4.5% to 39.5%. Behavioural methods are more secure than other approaches in smoking cessation studies. The TTM contains powerful measurement vehicles, which reveal thoughts of individuals regarding when, why and how to change their behaviour to quit smoking, as well as their confidence on this issue. It is possible to have success in the behavioural change by using these measurement vehicles with interventions that are peculiar to the individual. For this reason, the model is recommended to use smoking cessation studies.Publication Open Access Türkiye Cumhuriyeti Anayasası’nda değişiklik yapılmasına dair kanun (üzerine teknik-bilimsel rapor)(Anayasa_Der (Anayasa Hukuku Araştırmaları Derneği), 2017) Özenç, Berke; Yılmaz, Didem; Kalaycıoğlu, Ersin; Sağlam, Fazıl; Kaboğlu, İbrahim Ö.; Uygun, Oktay; Erözden, Ozan; İnceoğlu, Sibel; Üzeltürk-Tahmazoğlu Sultan; Şirin, Tolga; Özyavuz, Tuncer; Emre,Yunus; Taşkın, Yüksel; Berksoy, İrem; N/A; Department of International Relations; Oder, Bertil Emrah; Somer, Murat; Faculty Member; Faculty Member; Department of International Relations; Law School; College of Administrative Sciences and Economics; 4038; 110135