Korkmaz, İlker
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Korkmaz, I.
Korkmaz, Ilker
Korkmaz I.
Korkmaz, Ilker
Korkmaz I.
Job Title
Email Address
ilker.korkmaz@ieu.edu.tr
Main Affiliation
05.05. Computer Engineering
Status
Current Staff
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ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
1
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3GOOD HEALTH AND WELL-BEING
1
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4QUALITY EDUCATION
0
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5GENDER EQUALITY
0
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6CLEAN WATER AND SANITATION
0
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7AFFORDABLE AND CLEAN ENERGY
0
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8DECENT WORK AND ECONOMIC GROWTH
0
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9INDUSTRY, INNOVATION AND INFRASTRUCTURE
2
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10REDUCED INEQUALITIES
0
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11SUSTAINABLE CITIES AND COMMUNITIES
1
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12RESPONSIBLE CONSUMPTION AND PRODUCTION
0
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13CLIMATE ACTION
0
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14LIFE BELOW WATER
0
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15LIFE ON LAND
0
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
1
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17PARTNERSHIPS FOR THE GOALS
0
Research Products
Documents
18
Citations
146
h-index
5
Documents
10
Citations
43
Scholarly Output
20
Articles
2
Views / Downloads
15/15
Supervised MSc Theses
1
Supervised PhD Theses
0
WoS Citation Count
43
Scopus Citation Count
108
Patents
0
Projects
0
WoS Citations per Publication
2.15
Scopus Citations per Publication
5.40
Open Access Source
0
Supervised Theses
1
| Journal | Count |
|---|---|
| Proceedings - 2020 Innovations in Intelligent Systems and Applications Conference, ASYU 2020 | 2 |
| 2024 Medical Technologies Congress -- OCT 10-12, 2024 -- Bodrum, TURKIYE | 2 |
| TIPTEKNO 2025 - Medical Technologies Congress, Proceedings -- 2025 Medical Technologies Congress, TIPTEKNO 2025 -- 26 October 2025 through 28 October 2025 -- Gazi Magusa -- 217812 | 2 |
| 2021 Eıghth Internatıonal Conference on Internet of Thıngs, Systems, Management And Securıty (Iotsms) | 1 |
| 2022 Medıcal Technologıes Congress (Tıptekno'22) | 1 |
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20 results
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Now showing 1 - 10 of 20
Conference Object Citation - Scopus: 1An Energy Conservative Wireless Sensor Network Model for Object Tracking(IEEE, 2014) Peynirci, Gokcer; Korkmaz, Ilker; Gurgen, MuharremThis study aims to find the relationship between energy consumption level and object tracking success in an object tracking sensor network (OTSN). Convenient use of energy proposes a great challenge for wireless sensor network (WSN) design and the balance between successful object tracking and low energy consumption is a tight one. To address this issue, we propose a new network operation scheme for object tracking, implement this scheme in Network Simulator 2 (ns-2) and present the obtained results of the conducted simulation experiments. The simulation results show that the proposed method can be used to track objects in a WSN network in an energy conservative manner.Book Part Citation - Scopus: 2A Survey on Security in Wireless Sensor Networks: Attacks and Defense Mechanisms(IGI Global, 2013) Korkmaz I.; Dagdeviren O.; Tekbacak F.; Dalkilic M.E.Wireless Sensor Network (WSN) is a promising technology that has attracted the interest of research in the last decade. Security is one of the fundamental issues in sensor networks since sensor nodes are very resource constrained. An attacker may modify, insert, and delete new hardware and software components to the system where a single node, a specific part of the sensing area, and the whole network may become inoperable. Thus, the design of early attack detection and defense mechanisms must be carefully considered. In this chapter, the authors survey attacks and their defense mechanisms in WSNs. Attacks are categorized according to the related protocol layer. They also investigate the open research issues and emerging technologies on security in WSNs.Conference Object A 2-Hop Coloring-Based Collision Free Infrastructure Design for Wireless Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2016) Korkmaz I.; Dagdeviren O.; Dalkilic M.E.This paper mainly proposes a design for a communication infrastructure for Wireless Sensor Networks. The proposed design prevents message collisions by arranging the time schedules to send, receive, forward and overhear packets of the nodes considering 2-hop graph coloring mechanism. The system aims to exclude the compromised nodes in the network using the overhearing mechanism, and copes with recovering the paths of the legitimate nodes using multipath redundancy. The proposed scheduling-based and overhearing supported infrastructure brings the advantage of providing the Sensor Networks with both reliable communication using backup paths and energy conservation by preventing the collisions. © 2016 IEEE.Conference Object Citation - Scopus: 3A mobile patient monitoring system using RFID(2010) Korkmaz I.; Atay C.; Kyparisis G.In the last decade, Radio Frequency Identification (RFID) has become popular in so many fields from military to industry applications. RFID tags have been embedded into many various products especially in logistics sector. A tag stores individual information of its attached object and an RFID reader communicates with the tag in radio frequencies to identify the object. This object to be monitored may also be a human. In our work, RFID technology is applied in health care systems. The system supports wireless mobile communication between the RFID tags and readers. Each patient available in the system is inherently mobile and wears a bracelet integrated with a unique tag, and the readers are mobile PDA devices each including a wireless RFID reader card. The proposed application can be used to identify and monitor the patients.Conference Object Viability Analysis of Drug-Treated Tumor Spheroids Using Machine Learning(IEEE, 2024) Oguz, Kaya; Aslan, Arda; Evcin, Emre; Ozogul, Emre; Sonmez, Mehmet Eren; Karabacak, Yaren; Karagonlar, Zeynep Firtina3D spheroids that are able to mimic the microenvironment of tumors effectively have emerged as significant structures in cancer biology and drug development. This study aims to help cancer researchers monitor the changes in human liver cancer spheroids in response to drug treatment by offering a software tool for evaluating cell viability within 3D spheroids. A dataset of spheroid images are collected, processed, and classified using alternative machine learning models constructed with Random Forest, Logistic Regression, Support Vector Machine and Extreme Gradient Boosting methods. The classification performances of the models are evaluated in terms of the prediction accuracy, precision, recall, and F1-score values. Based on the test experiments conducted, Extreme Gradient Boosting model achieved the highest ratios for all of the performance metrics. Furthermore, a standalone desktop application is implemented to perform analyses of the images with the help of its user-friendly interface.Conference Object A Shuttle Route Divergence Detection System(Institute of Electrical and Electronics Engineers Inc., 2020) Korkmaz I.; Ozturk S.D.; Ozturk, Serhat Deniz; Korkmaz, IlkerShuttle Route Divergence Detection System is a mobile tracking information system designed for parents to follow the safety of their children who are transported by shuttle buses on regular routes. Main purpose of the system is to provide the parents with a tracking system to monitor their children when they are far away from the home. With the help of the system, the parents will be informed about the location of their children and can early intervene in unusual circumstances. The tracking system developed uses a rule based algorithm to learn and compare the routes with operating data which are written in the database. The system runs in a machine to machine approach using peer to peer communication. The prototype system implemented includes three main devices: parent's PC, child's smartphone, and a management server. Child's mobile phone informs the parent about its location via GPS; parent's computer learns the routes of the shuttle vehicle carrying the child; server provides re-establishment of the data communication between child's and parent's devices. The system is able to warn the parents immediately if the shuttle bus diverges out from any part of the learned route. © 2020 IEEE.Conference Object Citation - Scopus: 14A smart school bus tracking system(Institute of Electrical and Electronics Engineers Inc., 2019) Korkmaz I.; Camci A.; Cengiz C.; Dirik D.; Cekci E.; Akbaba F.M.The proposed smart school bus tracking system is an easy-to-use software, including both a web-based program and a mobile application, that mainly gives parents, students and school service firms the ability to track accurately the location of their school service vehicles. Such a smart school bus service information system is inevitable within the context of smart city features. The mobile application makes it smarter for kids/students using their school services; also, parents can easily track their kids' buses. In addition, bus service companies can easily register new students and determine the routes of the school buses dynamically. The system provides scalability, flexibility, low cost, security, and reliability. All shared location information and users' private data are stored encrypted; the parents may receive information about their related buses only. The system is based on both web and mobile platforms and it is implemented as an interactive application. © 2019 IEEE.Conference Object Mushroom Classification Using Machine Learning(Springer Science and Business Media Deutschland GmbH, 2025) Ercan, G.B.; Baran, M.; Konca, E.; Cetin, I.M.; Korkmaz, I.This study aims to develop a robust system using image processing and machine learning to accurately differentiate poisonous and non-poisonous mushroom species, addressing the significant public health threat posed by poisonous mushroom consumption. Motivated by the urgent need for an efficient tool to aid mushroom enthusiasts, farmers, and healthcare professionals in real-time identification of harmful species, the research focuses on creating a mobile application capable of processing mushroom images, extracting pertinent features, and employing a well-trained machine learning model for precise toxic and non-toxic categorization. Through a diverse image dataset collection, preprocessing, feature extraction, and rigorous model evaluation, the study endeavors to enhance public safety and encourage the development of similar applications for species identification and environmental protection. Based on the experiments conducted, amongst many machine learning algorithms used to train a proper system to decide whether a mushroom is edible or poisonous, InceptionV3 deep learning model is chosen to be integrated into the mobile application implemented as the endpoint to the users. Additionally, a simple game is also embedded in the mobile app to make the users learn the poisonous mushrooms from their images. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Conference Object Effect of Age and Gender on Facial Emotion Recognition(Institute of Electrical and Electronics Engineers Inc., 2020) Oguz K.; Korkmaz I.; Korkmaz B.; Akkaya G.; Alici C.; Kilic E.; Kilic, Ece; Korkmaz, Beyza; Korkmaz, Ilker; Alici, Cem; Akkaya, Guliz; Oguz, KayaNew research fields and applications on human computer interaction will emerge based on the recognition of emotions on faces. With such aim, our study evaluates the features extracted from faces to recognize emotions. To increase the success rate of these features, we have run several tests to demonstrate how age and gender affect the results. The artificial neural networks were trained by the apparent regions on the face such as eyes, eyebrows, nose, mouth, and jawline and then the networks are tested with different age and gender groups. According to the results, faces of older people have a lower performance rate of emotion recognition. Then, age and gender based groups are created manually, and we show that performance rates of facial emotion recognition have increased for the networks that are trained using these particular groups. © 2020 IEEE.Master Thesis Uçan Tasarsız Ağlar için Doğadan İlham Alan ve Geleneksel Yönlendirme Algoritmalarının Araştırılması(2025) Karaküçük, Ömer Hakan; Korkmaz, İlkerUçan Tasarsız Ağ (FANET), mobil tasarsız ağların (MANET) özel bir türüdür ve ağ düğümlerinin son derece hareketli insansız hava araçları (İHA) olduğu bir iletişim ağını ifade eder. Doğal afetler, ulusal güvenlik veya terörle mücadele gibi bazı İHA kullanım durumlarının kırılgan ve kritik doğası, paketlerin düğümler veya eşler arasında iletim hızı açısından en doğru yönlendirme algoritmasını seçmenin büyük önemini ortaya koymaktadır. Uçan tasarsız ağlardaki düğümlerin yüksek hareketliliği, FANET'ler için son derece dinamik bir topolojiye yol açar ve amaca uygun bir yönlendirme algoritmasının dikkatlice seçilmesini gerektiren bir ağ yönlendirme zorluğu ortaya çıkarır. Bu bağlamda uygun bir yönlendirme algoritması için örnek olarak, karınca kolonisi optimizasyon metasezgisine dayanan bir sürü zekası optimizasyon algoritması olan AntHocNet verilebilir. Bu tezde, popüler geleneksel yönlendirme algoritmalarından bazıları (AODV, DSDV ve OLSR) ve doğadan ilham alan bir yönlendirme algoritması (AntHocNet), önceden belirlenmiş çeşitli senaryolar çalıştırılarak ns-3 simülasyonları aracılığıyla karşılaştırılmıştır. Önceden belirlenmiş senaryolara dayalı olarak yürütülen simülasyonlar, karşılaştırılan yönlendirme protokollerinin performansının dinamik olarak değişen ağ topolojileri, ağ yükleri ve ağ boyutları altında nasıl etkilendiğine dair araştırma sorularına yanıt aramaktadır. Simülasyon sonuçlarının karşılaştırmalı analizi, doğadan ilham alan yönlendirme protokolü AntHocNet'in hem reaktif yönlendirme protokolü AODV hem de proaktif yönlendirme protokolleri DSDV ve OLSR'nin çok ötesinde performans sunduğunu göstermektedir.
