Yazar "AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü" için Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed listeleme
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Credit Card Fraud Detection with Machine Learning Methods
Goy, Gokhan; Gezer, Cengiz; Gungor, Vehbi Cagri (IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 01.01.2019)With the increase in credit card usage of people, the credit card transactions increase dramatically. It is difficult to identify fraudulent transactions among the vast amount of credit card transactions. Although credit ... -
Credit Risk Analysis based on Hybrid Classification: Case Studies on German and Turkish Credit Datasets
Cetiner, Erkan; Kocak, Taskin; Güngör, Vehbi Çağrı (IEEE, 2018)— Kredi risk analizi, karar verme süreçleri açısından finans sektöründe önemli bir rol oynamaktadır. Bankalar ve finansal kuruluşlar, müşterilerinden büyük ölçeklerde ham veri toplamaktadırlar. Veri madenciliği teknikleri, ... -
A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection
Fourati, Slim; Talla, Aarthi; Mahmoudian, Mehrad; Burkhart, Joshua G.; Klén, Riku; Henao, Ricardo; Yu, Thomas; Aydın, Zafer; Yeung, Ka Yee; Ahsen, Mehmet Eren; Almugbel, Reem; Jahandideh, Samad; Liang, Xiao; Nordling, Torbjörn E.M.; Shiga, Motoki; Stanescu, Ana; Vogel, Robert; Pandey, The Respiratory Viral DREAM Challenge Consortium# , Gaurav; Chiu, Christopher; McClain, Micah T.; Woods, Christopher W.; Ginsburg, Geoffrey S.; Elo, Laura L.; Tsalik, Ephraim L.; Mangravite, Lara M.; Sieberts, Solveig K. (NATURE PUBLISHING GROUP, MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND, 2018)The response to respiratory viruses varies substantially between individuals, and there are currently no known molecular predictors from the early stages of infection. Here we conduct a community-based analysis to determine ... -
A Data Mining Method For Refining Groups In Data Using Dynamic Model Based Clustering
Servi, Tayfun; Erol, Hamza (IEEE, 2013)A new data mining method is proposed for determining the number and structure of clusters, and refining groups in multivariate heterogeneous data set including groups, partly and completely overlapped group structures ... -
Data Mining Techniques in Direct Marketing on Imbalanced Data using Tomek Link Combined with Random Under-sampling
Ümit Yilmaz; Zafer Aydin; V. Çağri Güngör; Cengiz Gezer (Association for Computing Machinery, 2021)Determining the potential customers is very important in direct marketing. Data mining techniques are one of the most important methods for companies to determine potential customers. However, since the number of potential ... -
A Deep Ensemble Approach for Long-Term Traffic Flow Prediction
Cini, Nevin; Aydin, Zafer (SPRINGER, 2024)In the last 50 years, with the growth of cities and increase in the number of vehicles and mobility, traffic has become troublesome. As a result, traffic flow prediction started to attract attention as an important research ... -
A deep learning approach with Bayesian optimization and ensemble classifiers for detecting denial of service attacks
Gormez, Yasin; Aydin, Zafer; Karademir, Ramazan; Gungor, Vehbi C. (WILEY, 111 RIVER ST, HOBOKEN 07030-5774, NJ USA, 2020)Detecting malicious behavior is important for preventing security threats in a computer network. Denial of Service (DoS) is among the popular cyber attacks targeted at web sites of high-profile organizations and can ... -
Deep learning approaches for vehicle type classification with 3-D magnetic sensor
Kolukisa, Burak; Yildirim, Veli Can; Elmas, Bahadir; Ayyildiz, Cem; Gungor, Vehbi Cagri (ELSEVIER, 2022)In the Intelligent Transportation Systems, it is crucial to determine the type of vehicles to improve traffic management, increase human comfort, and enable future development of transport infrastructures. This paper presents ... -
Deep Learning Based Employee Attrition Prediction
Gurler, Kerem; Pak, Burcu Kuleli; Gungor, Vehbi Cagri (SPRINGER LINK, 2023)Employee attrition is a critical issue for the business sectors as leaving employees cause various types of difficulties for the company. Some studies exist on examining the reasons for this phenomenon and predicting it ... -
Deep learning based semantic segmentation and quantification for MRD biochip images
Çelebi, Fatma; Tasdemir, Kasim; Icoz, Kutay (ELSEVIER SCI LTD, 2022)Microfluidic platforms offer prominent advantages for the early detection of cancer and monitoring the patient response to therapy. Numerous microfluidic platforms have been developed for capturing and quantifying the tumor ... -
A deep neural network approach with hyper-parameter optimization for vehicle type classification using 3-D magnetic sensor
Kolukisa, Burak; Yildirim, Veli Can; Ayyildiz, Cem; Gungor, Vehbi Cagri (ELSEVIER, 2023)The identification of vehicle types plays a critical role in Intelligent Transportation Systems. In this study, battery-operated, easy-to-install, low-cost 3-D magnetic traffic sensors have been developed for vehicle type ... -
Design of a Tri band 5-Fingers Shaped Microstrip Patch Antenna with an Adjustable Resistor
Aoad, Ashrf; Aydin, Zafer; Korkmaz, Erdal (IEEE, 2014)This paper presents a tri band 5-fingers shaped microstrip patch antenna, which resonates initially at dual band of 3.2 GHz and 5.2 GHz frequencies for VSWR < 2. The antenna is modified by adding an adjustable resistor ... -
Designing and Modelling Selective Replication for Fault-tolerant HPC Applications
Subasi, Omer; Yalcin, Gulay; Zyulkyarov, Ferad; Unsal, Osman; Labarta, Jesus (IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2017)Fail-stop errors and Silent Data Corruptions (SDCs) are the most common failure modes for High Performance Computing (HPC) applications. There are studies that address fail-stop errors and studies that address SDCs. However ... -
The Determination of Distinctive Single Nucleotide Polymorphism Sets for the Diagnosis of Behçet's Disease
Isik, Yunus EMRE; Gormez, Yasin; Aydin, Zafer; Bakir-Gungor, Burcu (Institute of Electrical and Electronics Engineers Inc., 2021)Behçet's Disease (BD) is a multi-system inflammatory disorder in which the etiology remains unclear. The most probable hypothesis is that genetic tendency and environmental factors play roles in the development of BD. In ... -
Developing a label propagation approach for cancer subtype classification problem
Guner, Pinar; Bakir-Gungor, Burcu; Coskun, Mustafa (TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEYATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA 00000, TURKEY, 2022)Cancer is a disease in which abnormal cells grow uncontrollably and invade other tissues. Several types of cancer have various subtypes with different clinical and biological implications. Based on these differences, ... -
Developing structural profile matrices for protein secondary structure and solvent accessibility prediction
Aydin, Zafer; Azginoglu, Nuh; Bilgin, Halil Ibrahim; Celik, Mete (OXFORD UNIV PRESS, GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND, 2019)Motivation: Predicting secondary structure and solvent accessibility of proteins are among the essential steps that preclude more elaborate 3D structure prediction tasks. Incorporating class label information contained in ... -
Development of Knowledge Based Response Correction for a Reconfigurable N-Shaped Microstrip Antenna Design
Aoad, Ashrf; Simsek, Murat; Aydin, Zafer (IEEE, 2015)This study presents the use of prior knowledge of inverse artificial neural network (ANN) to model and optimize a reconfigurable N-shaped microstrip antenna. Three accurate prior knowledge inverse ANNs with large amount ... -
Dimensionality reduction for protein secondary structure and solvent accesibility prediction
Aydin, Zafer; Kaynar, Oguz; Gormez, Yasin (IMPERIAL COLLEGE PRESS, 57 SHELTON ST, COVENT GARDEN, LONDON WC2H 9HE, ENGLAND, 2018)Secondary structure and solvent accessibility prediction provide valuable information for estimating the three dimensional structure of a protein. As new feature extraction methods are developed the dimensionality of the ... -
Disaster-resilient lightpath routing in WDM optical networks
Ashraf, M. Waqar; Butt, Rizwan Aslam; Faheem, M; Tariq, M.; Munir, Abid (SPRINGER, 2022)Optical network serves as a core network with huge capacity and a multitude of high-speed data transmission. Natural disasters and physical attacks showed signifcant impacts on the optical networks such as damages the ... -
Disaster-Resilient Optical Network Survivability: A Comprehensive Survey
Ashraf, Muhammad Waqar; Idrus, Sevia M.; Iqbal, Farabi; Butt, Rizwan Aslam; Faheem, Muhammad (MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2018)Network survivability endeavors to ensure the uninterrupted provisioning of services by the network operators in case of a disaster event. Studies and news reports show that network failures caused by physical attacks and ...