Şengül, Gökhan

Şengül, Gökhan

Name Variants

Gokhan, Sengul
Sengul, Gokhan
Sengul,G.
Gökhan, Şengül
Engul G.
Şengül G.
Şengül, Gökhan
G.,Sengul
Sengul, G.
S.,Gokhan
Sengul G.
Ş., Gökhan
G.,Şengül
G., Sengul
Şengül,G.
G., Şengül
S., Gokhan
Ş.,Gökhan

Job Title

Profesor Doktor

Email Address

gokhan.sengul@atilim.edu.tr

Main Affiliation

Computer Engineering

Scopus Author ID

8402817900

Full item page

Scholarly Output

77

Articles

47

Citation Count

128

Supervised Theses

10 Scholarly Output Search Results

Now showing 1 - 10 of 76

A Smart Classroom Application: Monitoring and Reporting Attendance Automatically Using Smart Devices
(International Journal of Scientific Research in Information Systems and Engineering, 2017) Şengül, Gökhan; Karakaya, Murat; Bostan, Atila; Computer Engineering
For recording attendance in a classroom, generally instructors collect signatures of the attendees. Then, at the end of the semester, those signatures need to be counted and reported. This process causes waste of time and effort for both instructors and attendees. Besides this process is very error prone. Moreover, in crowded classes, there could be some misuses of this process. In this study, a smart classroom application is proposed and developed in order to monitor the attendance of the students in a classroom environment. In the design, a low-energy Bluetooth device is located at each classroom. Identification number (ID) of the low-energy Bluetooth device and the name/number of the classroom that the device is located are matched and stored in a central database. In addition to this information, the name of the courses given in that classroom and their time tables are also stored in the central database. Thus, in the database, the weekly course schedule of the classrooms is available. In addition to this central database infrastructure, a mobile application is developed that can run on both in mobile phones and smart watches. The users first install the application on their own smart devices. Whenever an attendee enters to a classroom, the smart device and its application interacts with the low-energy Bluetooth device. The student’s identification number (Student ID: SID), the identification number (ID) of the low-energy Bluetooth device located at the class, the day and time of the interaction are sent to the central database by the smart device. Using this information, the name of the attendee and the courses that he/she attended are matched using the SID of the attendee, the ID of the low-energy Bluetooth device, the day and time of the interaction. Those matching information are also stored in the central database. The records in the central database are used to create any automatic reports, i.e. the attendance status, the time and duration of the attendance, and the classroom (course) of the record. The advantage of the proposed system is that it is a fully automatic system that records the presence of the students, generates automatic attendance reports, does not require any extra device except installing a mobile application onto smart phones or smart watches of the student, and can be deployed with a low budget. The proposed system is tested in real classroom environment and it is proven to be operational.
Citation - Scopus: 0
A Fully Automatic Photogrammetric System Design Using a 1.3 Mp Web Camera To Determine Eeg Electrode Positions;
(2010) Şengül,G.; Baysal,U.; Computer Engineering
In this study a fully automatic fotogrammetric system is designed to determine the EEG electrode positions in 3D. The proposed system uses a 1.3 MP web camera rotating over the subject's head. The camera is driven by a step motor. The camera takes photos in every 7.20 angles during the rotation. In order to realize full automation, electrodes are labeled by colored circular markers and an electrode identification algorithm is develeoped for full automation. The proposed method is tested by using a realistic head phantom carrying 25 electrodes. The positions of the test electrodes are also measured by a conventional 3-D digitizer. The measurements are repeated 3 times for repeatibility purposes. It is found that 3-d digitizer localizes the electrodes with an average error of 8.46 mm, 7.63 mm and 8.32 mm, while the proposed system localizes the electrodes with an average error of 1.76 mm, 1.42 mm and 1.53 mm. ©2010 IEEE.
Citation - WoS: 7
Citation - Scopus: 23
An Improved Random Bit-Stuffing Technique With a Modified Rsa Algorithm for Resisting Attacks in Information Security (rbmrsa)
(Cairo Univ, Fac Computers & information, 2022) Mojisola, Falowo O.; Misra, Sanjay; Febisola, C. Falayi; Abayomi-Alli, Olusola; Sengul, Gokhan; Computer Engineering
The recent innovations in network application and the internet have made data and network security the major role in data communication system development. Cryptography is one of the outstanding and powerful tools for ensuring data and network security. In cryptography, randomization of encrypted data increases the security level as well as the Computational Complexity of cryptographic algorithms involved. This research study provides encryption algorithms that bring confidentiality and integrity based on two algorithms. The encryption algorithms include a well-known RSA algorithm (1024 key length) with an enhanced bit insertion algorithm to enhance the security of RSA against different attacks. The security classical RSA has depreciated irrespective of the size of the key length due to the development in computing technology and hacking system. Due to these lapses, we have tried to improve on the contribution of the paper by enhancing the security of RSA against different attacks and also increasing diffusion degree without increasing the key length. The security analysis of the study was compared with classical RSA of 1024 key length using mathematical evaluation proofs, the experimental results generated were compared with classical RSA of 1024 key length using avalanche effect in (%) and computational complexity as performance evaluation metrics. The results show that RBMRSA is better than classical RSA in terms of security but at the cost of execution time. (C) 2022 THE AUTHORS. Published by Elsevier B.V. on behalf of Faculty of Computers and Information, Cairo University.
Citation - WoS: 17
Citation - Scopus: 19
Gender Detection Using 3d Anthropometric Measurements by Kinect
(Polska Akad Nauk, Polish Acad Sciences, 2018) Camalan, Seda; Sengul, Gokhan; Misra, Sanjay; Maskeliunas, Rytis; Damasevicius, Robertas; Computer Engineering; Information Systems Engineering
Automatic gender detection is a process of determining the gender of a human according to the characteristic properties that represent the masculine and feminine attributes of a subject. Automatic gender detection is used in many areas such as customer behaviour analysis, robust security system construction, resource management, human-computer interaction, video games, mobile applications, neuro-marketing etc., in which manual gender detection may be not feasible. In this study, we have developed a fully automatic system that uses the 3D anthropometric measurements of human subjects for gender detection. A Kinect 3D camera was used to recognize the human posture, and body metrics are used as features for classification. To classify the gender, KNN, SVM classifiers and Neural Network were used with the parameters. A unique dataset gathered from 29 female and 31 male (a total of 60 people) participants was used in the experiment and the Leave One Out method was used as the cross-validation approach. The maximum accuracy achieved is 96.77% for SVM with an MLP kernel function.
Citation - WoS: 6
Citation - Scopus: 7
Teaching Software Verification and Validation Course: a Case Study
(Tempus Publications, 2014) Mishra, Deepti; Hacaloglu, Tuna; Mishra, Alok; Computer Engineering; Computer Engineering; Software Engineering; Information Systems Engineering; Software Engineering; Information Systems Engineering
Software verification and validation (V & V) is one of the significant areas of software engineering for developing high quality software. It is also becoming part of the curriculum of a universities' software and computer engineering departments. This paper reports the experience of teaching undergraduate software engineering students and discusses the main problems encountered during the course, along with suggestions to overcome these problems. This study covers all the different topics generally covered in the software verification and validation course, including static verification and validation. It is found that prior knowledge about software quality concepts and good programming skills can help students to achieve success in this course. Further, team work can be chosen as a strategy, since it facilitates students' understanding and motivates them to study. It is observed that students were more successful in white box testing than in black box testing.
Görüntü İşleme Yöntemlerı ile Araç Logo Tanıma
(2016) Albera, Sumıa; Şengül, Gökhan; Computer Engineering
Araç logolarının tanımlanması, farkli çevre şartlarında araçların logolarının yüksek performans ile algılanması ve sınıflandırılması yeteneği olarak tanımlanabilir. Logo tanıma, devlet kurumları, askeri alanlar gibi kontrol gerektiren bölgelerde güvenlik ve gözetleme amacıyla kullanılmaktadır. Logo tanımlamada öncelikle logo görüntüleri okunur, analiz edilir ve logonun ait olduğu üretici belirlenir. Bu tez çalışmasının amacı, araç logolarının tanımlanması için kullanılan üç farklı yöntemin gürültülü ve gürültüsüz ortamlardaki başarımlarını araştırmak ve bu yöntemlerin karşılaştırmasını yapmaktır. Bu tez çalışmasında logo tanımlama için SURF, LBP ve GLCM yöntemleri denenmiştir. LBP ve GLCM yöntemleri için sınıflandırıcı olarak kNN kullanılmıştır. Önerilen yöntemler biri üreticilerin internet sitelerinden alınan görüntüler diğeri ise doğrudan araçların logoların fotoğraflarının çekilmesi ile elde edilen görüntüler olmak üzere iki farklı veri kümesinde test edilmiştir. Sonuç olarak en iyi başarım, SURF algoritması ile elde edilmiştir.
Citation - Scopus: 3
Self Archiving in Atilim University
(2012) Ertürk,K.L.; Şengül,G.; Information Systems Engineering; Computer Engineering
Self archiving is defined as storing the scientific research outputs in researchers' own web pages/sites, organizational web sites or institutional repositories. In this study the self archiving activities of academicians of AtIlIm University are investigated. For the purpose of the study the web pages of the university, personal web pages of the academicians and open repository of the university are explored. We found the details of 2176 academic activities of the instructors in web pages. More than half of these activities (1147 - 53%) consist of refereed journal papers. Almost a quarter of the instructors saved their research outputs in the university's open repository. Yet, those instructors have not published their works in their personal web pages or institutional web pages. Only 4% of the works are published in personal/organizational web pages. According to the results obtained, the usage of institutional repository is the common self archiving method in the AtIlIm University. On the other hand, the personal/organizational web pages should be as a point of attraction in self archiving. While discussing the efficient usage of the institutional repository, we suggest that the social networks as a meeting point should include links to personal/institutional web pages containing academicians' papers. © 2012 Springer-Verlag.
Citation - Scopus: 3
Gender Prediction by Using Local Binary Pattern and K Nearest Neighbor and Discriminant Analysis Classifications;
(Institute of Electrical and Electronics Engineers Inc., 2016) Camalan,S.; Sengul,G.; Information Systems Engineering; Computer Engineering
In this study, gender prediction is investigated for the face images. To extract the features of the images, Local Binary Pattern (LBP) is used with its different parameters. To classify the images male or female, K-Nearest Neighbors (KNN) and Discriminant Analysis (DA) methods are used. Their performances according to the LBP parameters are compared. Also classification methods' parameters are changed and the comparison results are shown. These methods are applied on FERET database with 530 female and 731 male images. To have better performance, the face parts of the images are cropped then feature extraction and classification methods applied on the face part of the images. © 2016 IEEE.
Citation - WoS: 9
Citation - Scopus: 9
Benchmarking Classification Models for Cell Viability on Novel Cancer Image Datasets
(Bentham Science Publ Ltd, 2019) Ozkan, Akin; Isgor, Sultan Belgin; Sengul, Gokhan; Isgor, Yasemin Gulgun; Chemical Engineering; Computer Engineering; Department of Electrical & Electronics Engineering
Background: Dye-exclusion based cell viability analysis has been broadly used in cell biology including anticancer drug discovery studies. Viability analysis refers to the whole decision making process for the distinction of dead cells from live ones. Basically, cell culture samples are dyed with a special stain called trypan blue, so that the dead cells are selectively colored to darkish. This distinction provides critical information that may be used to expose influences of the studied drug on considering cell culture including cancer. Examiner's experience and tiredness substantially affect the consistency throughout the manual observation of cell viability. The unsteady results of cell viability may end up with biased experimental results accordingly. Therefore, a machine learning based automated decision-making procedure is inevitably needed to improve consistency of the cell viability analysis. Objective: In this study, we investigate various combinations of classifiers and feature extractors (i.e. classification models) to maximize the performance of computer vision-based viability analysis. Method: The classification models are tested on novel hemocytometer image datasets which contain two types of cancer cell images, namely, caucasian promyelocytic leukemia (HL60), and chronic myelogenous leukemia (K562). Results: From the experimental results, k-Nearest Neighbor (KNN) and Random Forest (RF) by combining Local Phase Quantization (LPQ) achieve the lowest misclassification rates that are 0.031 and 0.082, respectively. Conclusion: The experimental results show that KNN and RF with LPQ can be powerful alternatives to the conventional manual cell viability analysis. Also, the collected datasets are released from the "biochem.atilim.edu.tr/datasets/ " web address publically to academic studies.
Citation - Scopus: 0
The Effect of Split Attention in Surgical Education
(Springer Verlag, 2014) Özçelik,E.; Ercil Cagiltay,N.; Sengul,G.; Tuner,E.; Unal,B.; Department of Modern Languages; Computer Engineering
Surgical education through simulation is an important area to improve the level of education and to decrease the risks, ethical considerations and cost of the educational environments. In the literature there are several studies conducted to better understand the effect of these simulation environments on learning. However among those studies the human-computer interaction point of view is very limited. Surgeons need to look at radiological images such as magnetic resonance images (MRI) to be sure about the location of the patient's tumor during a surgical operation. Thus, they go back and forth between physically separated places (e.g. the operating table and light screen display for MRI volume sets). This study is conducted to investigate the effect of presenting different information sources in close proximity on human performance in surgical education. For this purpose, we have developed a surgical education simulation scenario which is controlled by a haptic interface. To better understand the effect of split attention in surgical education, an experimental study is conducted with 27 subjects. The descriptive results of study show that even the integrated group performed the tasks with a higher accuracy level (by traveling less distance, entering less wrong directions and hitting less walls), the results are not statistically significant. Accordingly, even there are some evidences about the effect of split attention on surgical simulation environments, the results of this study need to be validated by controlling students' skill levels on controlling the haptic devices and 2D/3D space perception skills. The results of this study may guide the system developers to better design the HCI interface of their designs especially for the area of surgical simulation. © 2014 Springer International Publishing.

Şengül, Gökhan

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Scholarly Output

77

Articles

47

Citation Count

128

Supervised Theses

10

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