Eminağaoğlu, Mete
Loading...
Name Variants
Job Title
Doç.Dr.
Email Address
Main Affiliation
01.01.09.01. Bilgisayar Mühendisliği Bölümü
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
SDG data is not available
Documents
13
Citations
232
h-index
8
Documents
8
Citations
80
Scholarly Output
9
Articles
3
Views / Downloads
0/0
Supervised MSc Theses
1
Supervised PhD Theses
1
WoS Citation Count
17
Scopus Citation Count
58
Patents
0
Projects
0
WoS Citations per Publication
1.89
Scopus Citations per Publication
6.44
Open Access Source
1
Supervised Theses
2
| Journal | Count |
|---|---|
| 10th IEEE International Conference on Application of Information and Communication Technologies (AICT) | 1 |
| 2010 International Conference on Computer Information Systems and Industrial Management Applications CISIM 2010 | 1 |
| 5th International Conference on Emerging Security Technologies EST 2014 | 1 |
| International Journal of Coal Geology | 1 |
| Journal of Computer Science and Technology | 1 |
Current Page: 1 / 2
Scopus Quartile Distribution
Quartile distribution chart data is not available
Competency Cloud
9 results
Scholarly Output Search Results
Now showing 1 - 9 of 9
Master Thesis Elektrik enerjisi talebinin akıllı tahmini: Bir vaka çalışması(2025) Savar, Mert Savaş; Eminağaoğlu, MeteEnerji talebi tahmini, enerji kaynaklarının verimli yönetimi ve sürdürülebilir enerji stratejilerinin geliştirilmesinde hayati bir rol oynamaktadır. Doğru talep tahmini, enerji üretimi ve dağıtımı için etkili stratejilerin oluşturulmasını sağladığından, enerji kaynaklarının verimli kullanımı önemli bir avantajdır. Ayrıca, talep tahminlerinin kullanılmasıyla kaynak yönetiminin optimize edilmesi mümkün hale gelmekte, bu da enerji verimliliğini artırmakta ve maliyetleri düşürmektedir. Doğru talep tahmininin sürdürülebilirlik boyutu, çevresel etkilerin azaltılması ve doğal kaynakların korunması yoluyla enerji kaynaklarının sürdürülebilir kullanımına katkı sağlamasında yatmaktadır. Bunun yanı sıra, talep tahmini, enerji politikalarının geliştirilmesi için değerli bilgiler sunarak enerji talep eğilimlerinin analiz edilmesine ve gelecekteki talep artışının öngörülmesine olanak tanımaktadır.Conference Object An Adaptive Network-Based Fuzzy Inference System for Estimating the Duration of Medical Services: A Case Study(IEEE, 2016) Ihsan Hakan Koksal; Mete Eminagaoglu; Buse Turkoglu; Eminaǧaoǧlu, Mete; Türkoǧlu, Buse; Köksal, Ihsan HakanThe aim of this study is twofold. First one is to derive a feasible numerical prediction model for the duration of medical services in a medical institution that could be used by the hospital management within their quality assurance and improvement processes. The second aim is to develop a freeware software tool which implements an adaptive artificial neural network-based fuzzy inference system with a user-friendly interface that can be effectively used by both technical and non-technical people. Some promising results have been obtained which show that both of these objectives have been successfully achieved to some extent.Article Citation - WoS: 9Citation - Scopus: 9Mineralogical and elemental composition of the Middle Miocene coal seams from the Alpu coalfield (Eskis-ehir- Central Türkiye): Insights from syngenetic zeolite formation(ELSEVIER, 2024) Ali Ihsan Karayigit; Riza Gorkem Oskay; Patricia Cordoba Sola; Yilmaz Bulut; Mete Eminagaoglu; Córdoba Sola, Patricia; Eminağaoğlu, Mete; Karayiğit, Ali İhsan; Oskay, Rıza Görkem; Bulut, Yılmaz; Sola, Patricia CordobaThis study focuses on determining mineralogical and elemental compositions of coal seams (to the upwards D C B A and S0) within seven coal exploration wells from the Alpu coalfield (Eskisehir Central Turkiye). Furthermore the special goal of the study is a comparative analysis of the relations between the elements by using agglomerative hierarchical clustering algorithm with different linkage methods as well as different similarity measures. Clay minerals and quartz are commonly detected as abundant to dominant phases while natural zeolite formations were detected in the studied seams C B A and S0. The SEM-EDX data shows that clinoptilolites in zeolite minerals were observed within the organic matter while crystalline and non-crystalline analcime minerals along with syngenetic authigenic rhomboid K-feldspars were only detected in the seam A from one studied well. The existence of some micron-sized minerals such as apatite monazite and Ti-oxides within the smectite matrix and the measurable amount of Ti in smectite imply that alteration of epiclastic and contemporaneous volcanic inputs was developed under weak acidic to neutral conditions during peat accumulation. The lack of natural zeolite and carbonate minerals in the seam D could be an indicator of weak acidic to neutral conditions and semi-closed hydrogeological conditions. Nevertheless the alkalinity of mire water water table and hydrogeological regime seem to be variable during the accumulation of precursor peats of seams C B A and S0. In turn alteration of volcanic inputs was observed under neutral to weak alkaline conditions and semi-closed to closed hydrogeological regime. Hence syngenetic authigenic micron-sized clinoptilolites were formed. Moreover the existence of authigenic rhomboid K-feldspars and syngenetic authigenic analcimes in certain exploration well could suggest local increases on dissolved Na+ concentrations alkalinity and water table. Except for volcanogenic origin for minerals accessory micron-sized minerals like chromite pentlandite and allanite grains presumably originated from clastic influxes of ophiolitic rocks in the basement into palaeomires. The variations in mire water chemistry and clastic-influx source area could also control the elemental enrichments in the studied seams. Epiclastic and contemporaneous volcanic inputs into palaeomires seem to control enrichments of Li B Sc and Ti in coal samples while clastic influx from ophiolitic rocks into palaeomires caused to enrichments of Cr V and Ni. Furthermore the liberated Ba Sr and As ions from the alteration of epiclastic and contemporaneous volcanic inputs are absorbed by syngenetic zeolite minerals while anoxic conditions in the palaeomires resulted in precipitation of Sr-barite and As-bearing pyrite grains during peat accumulation and/or early diagenetic stages. Overall the differences in water chemistry of mire water epiclastic and contemporaneous volcanic inputs and clastic influx from the adjacent areas also caused several elemental enrichments and variations in mineralogical compositions of the Middle Miocene coal seams in the Alpu coalfield.Article Citation - WoS: 8Citation - Scopus: 14Feature Selection for Malware Detection on the Android Platform Based on Differences of IDF Values(SCIENCE PRESS, 2020) Gokcer Peynirci; Mete Eminagaoglu; Korhan Karabulut; Eminagaoglu, Mete; Peynirci, Gokcer; Karabulut, KorhanAndroid is the mobile operating system most frequently targeted by malware in the smartphone ecosystem with a market share significantly higher than its competitors and a much larger total number of applications. Detection of malware before being published on official or unofficial application markets is critically important due to the typical end users' widespread security inadequacy. In this paper a novel feature selection method is proposed along with an Android malware detection approach. The feature selection method proposed in this study makes use of permissions API calls and strings as features which are statically extractable from the Android executables (APK files) and it can be used in a machine learning process with different algorithms to detect malware on the Android platform. A novel document frequencybased approach namely Delta IDF was designed and implemented for feature selection. Delta IDF was tested upon three universal benchmark datasets that contain Android malware samples and highly promising results were obtained by using several binary classification algorithms.Doctoral Thesis Android platformu için makine öğrenmesi teknikleri kullanarak kötücül yazılım tespiti(2018) Peynirci, Gökçer; Eminağaoğlu, Mete; Karabulut, KorhanAndroid mobil işletim sisteminin, rakiplerine kıyasla sahip olduğu oldukça yüksek toplam pazar payının yanında toplamda sayısal olarak çok daha fazla uygulamaya sahip olması dolayısıyla kötücül yazılımlar tarafından en sık hedef alınan mobil platform olduğu bilinmektedir. Son kullanıcının, tipik güvenlik yetersizliğine bağlı olarak, kötücül yazılımın Google Play Store veya herhangi bir resmi olmayan uygulama mağazasında yayımlanmadan önce tespit edilmesi hayati bir öneme sahiptir. Bu tezde, makine öğrenmesi teknikleri kullanarak yeni bir Android kötücül yazılım tespit metodolojisi yanında yeni bir öznitelik seçim metodolojisi ortaya konmuştur. Bu çalışmada sunulan makine öğrenmesi yaklaşımı, Android uygulamalarından (APK dosyaları) statik olarak çıkarılabilen, izinler (permissions), Uygulama Programlama Arayüzü çağrıları (API calls) ve katar (string) özelliklerini kullanmaktadır. Sunulan özellik seçim metodolojisinde literatürdeki mevcut yöntemlerden farklı olarak, belge sıklığı tabanlı (document frequency-based) bir yöntem tasarlanıp uygulanmıştır. Önerilen yöntem, Android kötücül yazılım örnekleri barındıran iki evrensel temel ölçüt veri kümesi ile test edilmiş ve bazı ikili sınıflandırma algoritmaları yanı sıra bazı topluluk (ensemble) yöntemine dayalı algoritmalar da kullanılarak literatürdeki diğer modeller ve yöntemlere göre daha başarılı sayılabilecek yüksek doğrulukta sonuçlar elde edilmiştir.Article Citation - Scopus: 1A proposed model for candidate selection process in political parties based on fuzzy logic methodology(Association for Scientific Research, 2012) METE EMİNAĞAOĞLU; Yılmaz GÖKŞEN; ONUR DOĞAN; Eminağaoğlu, Mete; Gökşen, Yılmaz; Doğan, OnurClassical logic and classical set theorems are not sufficient enough when it isnecessary to deal with complex decision making problems which also involve humanexperiences. Some researches suggest that senior management usually makes intuitivedecisions in the process of selecting the candidates in political parties which brings outthe need to derive a new efficient robust and applicable method.In this study the qualitative characteristics and their significance level which could beused for the candidate selection process in political parties are determined. Thecandidate selection process consisting vague inputs is analyzed by fuzzy logicmethodology and a quantitative final score has been determined for the candidate. It hasbeen shown that the model provided some realistic and promising results which couldenable further studies to derive more optimized and enhanced models for similarpurposes.Conference Object Citation - Scopus: 20A two-factor authentication system with QR codes for web and mobile applications(Institute of Electrical and Electronics Engineers Inc., 2014) Mete Eminaǧaoǧlu; Ece Çini; Gizem Sert; Derya Zor; Çini, Ece; Sert, Gizem; Eminaʇaoʇlu, Mete; Zor, DeryaThe use of QR code-based technologies and applications has become prevalent in recent years where QR codes are accepted to be a practical and intriguing data representation/processing mechanism amongst worldwide users. The aim of this study is to design and implement an alternative two-factor identity authentication system by using QR codes and to make the relevant mechanism and process that could be more user-friendly and practical than one-time password mechanisms used with similar purposes today. The proposed model in this project has been designed in order to enable the verification and validation steps with several security and networking options during the logon process. The model has been implemented by developing a two-factor identity verification system where the second factor is the user's smart/mobile phone device and a pseudo-randomly generated alphanumerical QR code which is used as the one-time password token sent to the user via e-mail or MMS. The proposed model has been developed using C# asp.net and jQuery languages with symmetrical and asymmetrical cryptography standards for database encryption/hashing and network infrastructure and it has been tested as a prototype where promising results are observed regarding the efficiency speed and security requirements for today's on-line financial services and similar e-commerce systems. © 2021 Elsevier B.V. All rights reserved.Conference Object Citation - Scopus: 14Implementation and comparison of machine learning classifiers for information security risk analysis of a human resources department(2010) Mete Eminaǧaoǧlu; Şaban Eren; Eminagaoglu, Mete; Eren, SabanThe aim of this study is threefold. First a qualitative information security risk survey is implemented in human resources department of a logistics company. Second a machine learning risk classification and prediction model with proper data set is established from the results obtained in this survey. Third several classifier algorithms are tested where their training and test performances are compared using error rates ROC curves Kappa statistics and F-measures. The results show that some classifier algorithms can be used to estimate specific human based information security risks within acceptable error rates. ©2010 IEEE. © 2011 Elsevier B.V. All rights reserved.Conference Object Enhancing Deepfake Detection with Audio Spectrograms and Siamese Networks(Springer Science and Business Media Deutschland GmbH, 2026) Eminağaoğlu, Mete; Çetin, Nur Ceylin; Gürbüzerol, İlayda; Özdemir, Selma İrem; Şenavcu, Bilge
