WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/256

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Citation - WoS: 2
Citation - Scopus: 2
Classification of Altruistic Punishment Decisions by Optical Neuroimaging and Machine Learning Methods
(IEEE, 2023) Erözden, Ozan; Şahin, Türkay; Akyürek, Güçlü; Filiz, Gözde; Çakar, Tuna
Altruistic punishment (third-party punishment) is important in terms of maintaining social norms and promoting prosocial behavior. This study examined data obtained using the near infrared spectroscopy (fNIRS) method to predict altruistic punishment decisions. It was found that specific neural activity patterns were significantly related to decisions regarding the punishment of the perpetrator. This research contributes to the development of social decision-making models and helps advance our understanding of the cognitive and neural processes involved in third-party punishments.
Citation - Scopus: 1
Liking Prediction Using fNIRS and Machine Learning: Comparison of Feature Extraction Methods
(IEEE, 2022) Koksal, Mehmet Yigit; Çakar, Tuna; Demircioğlu, Esin Tuna; Girisken, Yener
The fMRI method, which is generally used to detect behavioral patterns, draws attention with its expensive and impractical features. On the other hand, near infrared spectroscopy (fNIRS) method is less expensive and portable, but it is as effective as fMRI in creating a good prediction model. With this method, a model has been developed that can predict whether people like a stimulus or not, using machine learning various algorithms. A comparison was made between feature extraction methods, which was the main focus while developing the model.
Citation - WoS: 2
Citation - Scopus: 2
Implementation of Multi-Threaded Erasure Coding Under Multi-Processing Environments
(2016) Arslan, Şuayb Şefik
Galois alan aritmetiği depolama ve iletişim cihazlarını veri kayıplarına karşı korumak için Reed-Solomon silme kodlarının temelini oluşturmaktadır. Galois alan aritmeti^ginin en güncel uygulamaları hızlı Galois alan hesaplamaları yapmamıza imkan sağlayan Intel’in SIMD eklerinde olduğu gibi 128-bitlik işlemci vektör talimatlarına dayanmaktadır. Buna rağmen, bu uygulamalar çoklu–dizin ve çoklu–süreçli ortamlara göre optimize edilmemiştir. Diğer taraftan, sunucuların çoklu istekleri eş zamanlı olarak yerine getirmesi ve donanımın sağladığı tüm paralelliği kodlama yükünü etkili yürütmek için kullanması arzu edilmektedir. Bu makale silme kodlarının çoklu-dizin işlemcilerle çoklu–süreçli ortamlarda nasıl kullanılaca^gının detaylarını sunmakta ve tek dizinli uygulamalara göre emtia mikro işlemciler ve Jerasure 2.0 yazılım kütüphanesini kullanarak önemli ölçüde performans artışının olabileceğini göstermektedir.
Uluslararası Hukukta Andlaşma Akdetme Yetkisi ve Viyana Andlaşmalar Hukuku Sözleşmesi Madde 46 Kapsamında Andlaşmaların Geçersizliği
(İstanbul Üniversitesi Yayınevi, 2023) Asar, Bilge Erson
Devletlerin bir andlaşma ile bağlanma süreçlerinde iç hukuklarında uygulanacak usule ilişkin düzenlemeleri, uluslararası hukuk ile iç hukukun kesiştiği sınırlı alanlardan biri olarak karşımıza çıkmaktadır. Bununla birlikte devletlerin bu alandaki düzenlemelerinin çeşitli usulleri içerdiği gözlenmektedir. Geleneksel olarak yürütmenin elinde olan andlaşma akdetme yetkisinin demokratikleşme süreçleriyle birlikte yasama ile paylaşılan bir uygulama halini aldığı görülmektedir. Kimi devletlerde bu süreçlere anayasa mahkemeleri veya benzer yetkiyle donatılmış yargı organlarının da dahil olması mümkün olabilir. Hatta halk oylamasından geçmesi öngörülen andlaşma akdetme usulleri de mevcuttur. İç hukukta öngörülen bu kuralların ihlal edilmesi yoluyla bir uluslararası andlaşmaya taraf olan devlet, andlaşmanın geçersizliğini 1969 Viyana Andlaşmalar Hukuku Sözleşmesi’nin (VAHS) 46. maddesine dayanarak ileri sürebilir. Uluslararasıcılık ile anayasalcılığı bağdaştırıcı bir çözüm sunar gibi gözüken bu hüküm, gerçekte son derece zor ve istisnaî bir uygulamaya sahiptir. Gerek devletlerin andlaşma akdetme konusundaki kurallarının karmaşık olması gerekse genel bir sınıflandırmayı zorlaştıracak kadar çeşitli olması, konuyu daha da çetrefilli hale getirmektedir. Bu çalışma, ilgili hükmün hazırlık çalışmaları, kapsamı ve sınırlarını ayrıntılı bir biçimde incelemektedir. Çalışmada ayrıca, VAHS’nin hazırlık çalışmalarında da en tartışmalı konulardan biri olan bu geçersizlik gerekçesinin neden son derece istisnaî ve ileri sürüldüğünde başarı şansının zayıf olduğu değerlendirilmiştir. Bunların yanında, bu hükmün şu anda akademik çevrelerde tartışılmakta olan andlaşmalardan çekilmeye ilişkin kurallara benzer şekilde uygulanabilirliği de ele alınmıştır.
Neural Decoding of Brand Perception and Preferences: Understanding Consumer Behavior Through Fnirs and Machine Learning
(Ieee, 2024) Çakar, Tuna; Girisken, Yener; Tuna, Esin; Filiz, Gozde; Drias, Yassine
This research examines the link between consumer brand perceptions and neural activity by employing Functional Near-Infrared Spectroscopy (fNIRS) and machine learning techniques. The study analyzes the neural projections of participants' reactions to brand-associated adjectives, processing data collected from 168 individuals through machine learning algorithms. The findings underscore the significance of the lateral regions of the prefrontal cortex in the decision- making process related to brand perceptions. The aim is to understand how brands are perceived when associated with various adjectives and to develop this understanding through neural patterns using machine learning models. This study demonstrates the potential of integrating neural data with machine learning methods in the field of applied neuroscience.
Türkiye'de Yükseköğrenim Finansmanının Özelleştirilmesi
(Sosyoekonomi Society, 2018) Son-Turan, Semen
This study aims at developing a model for the privatization of higher education finance inTurkey. While the primary target is the NEET (Not in Education, Employment, or Training)population, it offers a broad range of potential solutions involving asset securitization for highereducation financing. Data is driven from secondary sources. The paper presents an interdisciplinaryapproach for privatizing higher education finance involving the labor market, higher educationinstitutions and the Turkish capital market and constitutes a unique contribution to the Turkish highereducation finance literature.
Customer Segmentation and Churn Prediction via Customer Metrics
(IEEE, 2022) Bozkan, Tunahan; Cakar, Tuna; Sayar, Alperen; Ertugrul, Seyit
In this study, it is aimed to predict whether customers operating in the factoring sector will continue to trade in the next three months after the last transaction date, using data-driven machine learning models, based on their past transaction movements and their risk, limit and company data. As a result of the models established, Loss Analysis (Churn) of two different customer groups (Real and Legal factory) was carried out. It was estimated by the XGBoost model with an F1 Score of 74% and 77%. Thanks to this modeling, it was aimed to increase the retention rate of customers through special promotions and campaigns to be made to these customer groups, together with the prediction of the customers who will leave. Thanks to the increase in retention rates, a direct contribution to the transaction volume on a company basis was ensured.
Bitişik Yapıların Deprem Performanslarının Ayrı veya Bitişik Olarak Kırılganlık Eğrileri Yardımı ile İncelenmesi
(2015) Akbulut, Ali; Boduroğlu, M. Hasan
Mevcut yapıların deprem performans, risk ve güçlendirme analizlerinde, yanındaki yapı ile olan ilişkisini uygun modelleme teknikleri ile analiz aşamasının içine dâhil ederek, sonuçların tekbaşına analiz edilmiş binalara göre olan farklılıklarını incelemek önemli bir konu olarak ortaya çıkmaktadır. Bu çalışmada, literatürdeki komşu binaların birbirleri ile olan etkileşim modelleri, statik itme analizi ve doğrusal olmayan hesap yöntemleri, deprem ivme kayıtlarının bir veri tabanından alınması ve tasarım spektrumuna göre ölçeklenmesi, zaman tanım alanına göre hesap yöntemi, hareket denkleminin Newmark-b yöntemi ile sayısal çözümü ve kırılganlık eğrileri ile bina performans seviyelerinin belirlenmesi konuları incelenmiştir. Bitişik (komşu) ve birbirine benzer binaların, deprem performanslarının birbirileri ile olan etkileşimli ve deprem yönüne göre değişen bir şekilde yapı blokları olarak ele alınıp, hasar görebilirlik-kırılganlık eğrileri yönünden değerlendirilmeleri incelenmiş ve binaların ayrı ayrı analiz edildikleri duruma göre daha farklı sonuçlar verdiği tespit edilmiştir.
Noise Effect on Forecasting
(IEEE, 2023) Tuncer, Suat; Kayan, Ersan; Çakar, Tuna
The lack of regulation and liquidity in crypto money markets causes higher volatility compared to other financial markets. This situation increases the noise in price change. The high noise and random walk create a problem that cannot be explained by traditional stochastic financial methods. For this reason, a multi-layered deep learning model with an additive attention layer, which uses a single observation in 10-day sequences, was used in this study. Different transformations are used to reduce the noise of the closing values. As a result of the comparisons made between different approaches, it has been revealed that exponential moving averages, to be used as the value to predict, give better results than other conversions and estimation of the original price, since they explain the price better than simple moving averages and reduce the noise of the original price.
Citation - WoS: 1
Citation - Scopus: 1
İlişkisel Veri Ayrıştırılmasında Model Seçimi
(IEEE, 2019) Kırbız, Serap; Cemgil, Taylan; Hızlı, Çağlar
Abstract—As a fundamental problem in relational data analysis, model selection for relational data factorization is still an open problem. In our work, we propose to estimate model order for mixed membership blockmodels (MMSB) within the generic allocation framework of Bayesian allocation model (BAM). We describe how relational data is represented as Poisson counts of the allocation model, and demonstrate our results both on synthetic and real-world data sets. We believe that the generic allocation perspective promises a generalized model selection solution where we do not only select the model order, but also choose the most appropriate factorization.
Parallelization and Performance Analysis of Reversible Circuit Synthesis
(IEEE, 2018) Susam, Ömercan; Arslan, Şuayb Şefik
Rising popularity of quantum computers in the last decade resulted in increased interest paid to reversible circuitsynthesis process. In this work, a popular essential function-based synthesis algorithm known in the literature is parallelized using openMP library. Contrary to conventional way, essential functions are synthesized when needed without keeping a table-lookup library. When the reversible circuit is synthesized in parallel using a double core processor (4 active threads with hyperthearding technology), around 2.6 speed-up is demonstrated relative tothe performance of serial synthesis work. Comparison between serial and parallel synthesis by using common benchmark circuits demonstrated that the performance of the proposed parallel synthesis is always better in the overall operation work load.
Citation - Scopus: 2
Alternative Data Sources and Psychometric Scales Supported Credit Scoring Models
(IEEE, 2023) Şahin, Türkay; Filiz, Gözde; Çakar, Tuna; Özvural, Özden Gebizlioğlu; Nicat, Şahin
This study aims to evaluate individuals with limited access to banking services and enhance credit scoring models with alternative data sources. A psychometric-based credit scoring model was developed and tested. Despite limited data, significant potential findings were obtained. However, clarification of the distinction between credit payment intention and ability and validation of the results with more data are necessary.
Citation - WoS: 2
Sürdürülebilir Bir Kurumsal Akademik Arşiv Yönetimi: Doğuş Üniversitesi Akademik Arşiv Sistemi Deneyimi
(Deomed, 2019) Çelik, Ramazan; Çelik, Sönmez
Bu çalışma, sürdürülebilir bir kurumsal akademik arşiv yönetimini Doğuş Üniversitesi Akademik Arşiv Sistemi deneyimi ile paylaşmak, bu konudaki girişimlere yardımcı olmak ve kurumsal akademik arşivlerin önemini vurgulamak üzere hazırlanmıştır. Çalışmada betimsel yöntem kullanılmıştır. Bu çerçevede dünyada ve Türkiye’deki kurumsal akademik arşivler, harmanlama sistemleri ve Doğuş Üniversitesi Akademik Arşiv Sistemi uygulamaları üzerinde durulmuştur.
Feature Enrichment Via Similar Trajectories for Xgboost Based Time Series Forecasting
(Ieee, 2024) Yilmaz, Elif; Islak, Umit; Çakar, Tuna; Arslan, Ilker
In this study, new time series forecasting models are developed based on XGBoost, and the similar trajectories method (ST), which can be interpreted as a regression based on nearest neighbors. Both the similar trajectories method and XGBoost model are known to have successful applications in traffic flow prediction. In our case, the focus is on similar trajectories used in the former method, and features based on these trajectories are used in the training of XGBoost. The success of the proposed models is confirmed through metrics such as the mean absolute error. Also, statistical tests are performed among the compared benchmark models. The study is concluded with discussions and questions about how these models can be further developed.
Highlighting of Lecture Video Closed Captions
(IEEE, 2020) Yıldırım, Göktuğ; Öztufan, Huseyin Efe; Arısoy, Ebru
The main purpose of this study is to automatically highlight important regions of lecture video subtitles. Even though watching videos is an effective way of learning, the main disadvantage of video-based education is limited interaction between the learner and the video. With the developed system, important regions that are automatically determined in lecture subtitles will be highlighted with the aim of increasing the learner's attention to these regions. In this paper first the lecture videos are converted into text by using an automatic speech recognition system. Then continuous space representations for sentences or word sequences in the transcriptions are generated using Bidirectional Encoder Representations from Transformers (BERT). Important regions of the subtitles are selected using a clustering method based on the similarity of these representations. The developed system is applied to the lecture videos and it is found that using word sequence representations in determining the important regions of subtitles gives higher performance than using sentence representations. This result is encouraging in terms of automatic highlighting of speech recognition outputs where sentence boundaries are not defined explicitly.
Citation - WoS: 1
Citation - Scopus: 1
Hata Düzeltme Çıktı Kodları: Genel Bakış, Zorluklar ve Gelecek Yönelimler
(IEEE, 2019) Arslan, Şuayb Şefik; Güney, Osman B.
Çok sınıflı sınıflandırma problemini çözmenin en etkili yollarından biri, bir grup akıllıca tasarlanmıs ikili sınıflandırıcı kullanarak, sınıflandırıcı sonuçlarını belli bir kritere göre bir araya getirmektir. Hata Düzeltme Çıktı Kodları (HDÇK) birden fazla ikili sınıflandırma yoluyla is bölümü saglayan basarılı tekniklerden biridir. Bu çalışmamızın amacı modern HDÇK tiplerine kısa bir giris yapmak, ikili sınıflandırma sonuçlarını birlestiren çesitli kod çözme yöntemleri ve zorlukları, avantajları ve dezavantajlarını ortaya koyan karsılastırmalı bir çalısma sunmaktır. Ayrıca HDÇK tekniğinin birkaç önemli uygulaması, MNIST veri seti üzerindeki performansı ve gelecekteki egilimlerin bazıları sunulmaktadır.
Reliability Study of Psychometric Tests in a Credit Scoring Model
(Ieee, 2024) Nicat, Sahin; Filiz, Gozde; Ozvural, Ozden Gebizlioglu; Çakar, Tuna
This study investigates the effectiveness and reliability of using psychometric tests in the credit decision-making processes within the finance sector. Psychometric tests, by measuring individuals' cognitive and psychological traits, hold the potential to broaden access to credit and identify high credit risk. However, after the literature review, it was seen that there was a need for more studies on the reliability and validity of these tests in finance. This study is designed to measure the test-retest reliability of a machine learning model and its inputs that utilize psychometric test results. Within the scope of the research, 115 participants were re-subjected to the same psychometric tests after an average of 6 months. Findings showed that psychometric tests and the machine learning model were generally consistent over time. This work has the potential to fill the gaps in the literature regarding the use of psychometric tests in the finance sector and lays a foundation for future research.
Citation - Scopus: 1
A Microwave Imaging Scheme for Detection of Pulmonary Edema and Hemorrhage
(IEEE, 2022) Ertek, Didem; Kucuk, Gokhan; Bilgin, Egemen
The microwave imaging systems have the potential to present a cost effective and less hazardous alternative to conventional medical imaging techniques. In this paper, a Contrast Source Inversion method based microwave imaging scheme is proposed and tested for the detection of pulmonary edema and hemorrhage. To this end, a realistic human torso phantom is used, and the electromagnetic parameters of the human tissues is determined via Cole-Cole model. The scattered field is simulated via Method of Moments at the operating frequency of 350 MHz, and a 50 dB white Gaussian noise is added to model a realistic measurement setup. The numerical tests performed with the proposed technique suggest that the method can be used to locate the pulmonary edema and hemorrhage, and it is capable of distinguishing these two medical conditions successfully.
Dialogue Enhancement Using Kernel Additive Modelling
(Institute of Electrical and Electronics Engineers Inc., 2015) Liutkus, A.; Kırbız, Serap; Cemgil, A. Taylan
It is a major problem for the sound engineers to find the right balance between the dialogue signals and the ambient sources. This problem also makes one of the main causes of the audience concerns. The audience wants to arrange the sound balance based on their personal preferences, listening environment and their hearing. In this work, a method is proposed for enhancing the dialogue signals in stereo recordings that consist of more than one source. The kernel additive modelling that has been used successfully in sound source separation is used to extract the dialogues and the ambient sources from the movie sounds. The separated dialogue and ambient sources can later be upmixed by the user to make a personal mix. The separation performance of the proposed method is evaluated on the sounds generated by mixing the sources which were taken from the only dialogue and only music parts of the movies. It has been shown that the Kernel Additive Modelling (KAM) based method can be successfully used for dialogue enhancement. © 2015 IEEE.
Prediction of Loan Decisions With Optical Neuroimaging (fnirs) and Machine Learning
(IEEE, 2023) Girişken, Yener; Son Turan, Semen; Çakar, Tuna; Ertuğrul, Seyit; Sayar, Alperen
The successful applications of neuroscientific methods and artificial learning approaches have increased in applied fields such as economics, marketing, and finance in the last decade. In this study, a prediction model was developed using the output of optical neuroimaging (fNIRS) measurements from the prefrontal brain regions while 40 participants made decisions for 35 credit offers. The aim was to predict participants' responses to credit offers using artificial learning methods based on four metrics obtained over time from the optical neuroimaging system. The findings of the study indicate that the first 6 seconds (prior to the response entry) are particularly critical. While the performance rate in the developed prediction models is found to be higher, especially in tree-based algorithms, this paper includes a performance comparison of 5 models specifically.

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