Browsing by Author "Karakaya, Murat"

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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
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.
A Wireless Control System Based on Smart Bluetooth and Ibeacon Technology for Auditing the Patrols
(International Journal of Scientific Research in Information Systems and Engineering, 2016) Karakaya, Murat; Şengül, Gökhan; Bostan, Atila
Patrol systems are used as a method of ensuring security and protection of large areas and facilities such as university campuses, military zones, etc. In general, security personnel assigned to the patrol system visit the pre-determined checkpoints at regular intervals and are obliged to make the safety control of these locations. Security personnel (guards) are also audited to check if they covered all the essential control points on time or not. In recent years, considering energy efficiency, new Bluetooth devices and protocols are designed and produced. One of the most popular low-energy Bluetooth protocols is Smart Bluetooth (version 4.0). In this work, we integrated mobile devices (smart phone or tablet) with IBeacons. IBeacons are devices emitting beacons using Smart Bluetooth signals. Since Smart Bluetooth consumes low energy, these devices are small in size, have long life durations and very cheap. In this work, we propose and implement a new system to record the patrol officers’ movements in the subject areas. At the proposed system, IBeacons are first deployed in the monitoring areas. The location and the identification of the deployed IBeacon are stored in a central database. We developed a mobile application for Android devices which can scan the environment for IBeacon signals. The mobile application collects the sensed IBeacon IDs, stamps it with a time tag and uploads it along with the mobile device ID to the central database. Using these records, we can monitor the movements of the security guards. We have also developed a web application to generate an executive summary report from these records.
Citation - Scopus: 1
Analyzing Students' Academic Success in Pre-requisite Course Chains: A Case Study in Turkey
(Tempus Publications, 2018) Karakaya, Murat; Eryilmaz, Meltem; Ceyhan, Ulas; Computer Engineering
There are several principles which have been accepted as approaches to successful curriculum development. In spite of the differences in the proposed sequencing of topics, all approaches basically depend on the pre-requisite chains to implement their educational approach in the curriculum development for specifying the order of the subjects. In this research, two prerequisite chains representing two different curriculum development approaches are taken into consideration in a case study. The first research question considered is whether academic success in a follow-up course is positively related to success attained in the pre-requisite course. The second one is whether or not the selected curriculum development approach for deciding the chains has a significant impact on the academic success relationships between a pre-requisite and its follow-up course. To answer these questions, course data of 441 undergraduate students who graduated from the Atilim University between Fall 2001 and Spring 2015 semesters were collected and analyzed. The results indicate that the succes levels gained in a pre-requisite and its follow-up course are corelated. Moreover, different cirriculum development methods can affect this corelation. Thus, cirriculum developers should consider appropriate approaches to improve student success for deciding chaining courses and their contents.
Biometric Verification on E-Id Secure Access Devices: a Case Study on Turkish National E-Id Card Secure Access Device Specifications
(International Journal of Information Security Science, 2017) Bostan, Atila; Şengül, Gökhan; Karakaya, Murat
Biometric verification on e-ID cards requires clear procedures and standards be defined, especially when the access devices are anticipated to be produced commercial companies. Turkish national e-ID card project has reached the dissemination step. Now the commercial companies are expected to produce and market e-ID card access devices which will conduct secure electronic identity verification functions. However, published standards specifying e-ID card-access-device requirements are ambiguous on biometric verification procedures. In this study, we intended to attract scientific interest to the problems identified in the current design of biometric verification on Turkish national e-ID cards and proposed several verification alternatives which enables the production of e-ID card access devices in a commercial-competition environment.
Citation - WoS: 5
Citation - Scopus: 7
Deadline-Aware Energy-Efficient Query Scheduling in Wireless Sensor Networks With Mobile Sink
(Hindawi Ltd, 2013) Karakaya, Murat
Mobile sinks are proposed to save sensor energy spent for multihop communication in transferring data to a base station (sink) in Wireless Sensor Networks. Due to relative low speed of mobile sinks, these approaches are mostly suitable for delay-tolerant applications. In this paper, we study the design of a query scheduling algorithmfor query-based data gathering applications using mobile sinks. However, these kinds of applications are sensitive to delays due to specified query deadlines. Thus, the proposed scheduling algorithm aims to minimize the number of missed deadlines while keeping the level of energy consumption at the minimum.
Deep Learning and Current Trends in Machine Learning
(Ieee, 2018) Bostan, Atila; Sengul, Gokhan; Tirkes, Guzin; Ekin, Cansu; Karakaya, Murat
Academic interest and commercial attention can be used to identify how much potential a novel technology may have. Since the prospective advantages in it may help solving some problems that are not solved yet or improving the performance of readily available ones. In this study, we have investigated the Web of Science (WOS) indexing service database for the publications on Deep Learning (DL), Machine Learning (ML), Convolutional Neural Networks (CNN), and Image Processing to reveal out the current trend. The figures indicate the strong potential in DL approach especially in image processing domain.
Citation - WoS: 47
Citation - Scopus: 66
Deep Learning Based Fall Detection Using Smartwatches for Healthcare Applications
(Elsevier Sci Ltd, 2022) Sengul, Gokhan; Karakaya, Murat; Misra, Sanjay; Abayomi-Alli, Olusola O.; Damasevicius, Robertas
We implement a smart watch-based system to predict fall detection. We differentiate fall detection from four common daily activities: sitting, squatting, running, and walking. Moreover, we separate falling into falling from a chair and falling from a standing position. We develop a mobile application that collects the acceleration and gyroscope sensor data and transfers them to the cloud. In the cloud, we implement a deep learning algorithm to classify the activity according to the given classes. To increase the number of data samples available for training, we use the Bica cubic Hermite interpolation, which allows us to improve the accuracy of the neural network. The 38 statistical data features were calculated using the rolling update approach and used as input to the classifier. For activity classification, we have adopted the bi-directional long short-term memory (BiLSTM) neural network. The results demonstrate that our system can detect falling with an accuracy of 99.59% (using leave-one-activityout cross-validation) and 97.35% (using leave-one-subject-out cross-validation) considering all activities. When considering only binary classification (falling vs. all other activities), perfect accuracy is achieved.
Determination and Identification of Dangerously Lane Changing Vehicles in Traffic by Image Processing Techniques
(International Journal of Scientific Research in Information Systems and Engineering, 2017) Şengül, Gökhan; Karakaya, Murat; Bostan, Atila
Due to increase of vehicle usage all around the world, the importance of safety driving in traffic is increasing. All of the countries around the world are taking actions to increase the safety driving habitats and decrease the number of traffic accidents. One of the applied precautions is to put necessary automatic auditing mechanisms into service for controlling the drivers as they drive since reckless drivers may not obey many traffic rules. In this study, image and video processing based methods are applied to identify the dangerously lane changing vehicles/drivers in the traffic. The proposed method focuses on to detect three different violations in traffic: the vehicles frequently changing traffic lanes, the vehicles changing lanes when it is forbidden, and the vehicles overtaking the other vehicles using the right lanes instead of left one. The proposed method is based on the image and video processing techniques. It first detects the vehicles in video sequences, then tracks the vehicles in the following frames and determines the lane changes of the vehicles. In the vehicle detection phase an image subtraction method is used. In the vehicle tracking phase, Kalman filtering tracking algorithm is used. After determining the lane changes of the vehicles/drivers, a rule based decision system is used to find out the vehicles/drivers improperly changing lanes and those vehicles are marked on the video. The proposed method is tested on the videos captured from real traffic environments and promising results are obtained.
Citation - WoS: 71
Citation - Scopus: 87
Efficient Route Planning for an Unmanned Air Vehicle Deployed on a Moving Carrier
(Springer, 2016) Savuran, Halil; Karakaya, Murat
Vehicle routing problem (VRP) is a constrained extension of the well-known traveling salesman problem (TSP). Emerging from the current conceptual trends in operations field, a new constraint to be included to the existing VRP parameters is the depot mobility. A practical example of such a problem is planning a route for an Unmanned air vehicle (UAV) deployed on a mobile platform to visit fixed targets. Furthermore, the range constraint of the UAV becomes another constraint within this sample case as well. In this paper, we define new VRP variants by introducing depot mobility (Mobile Depot VRP: MoDVRP) and extending it with capacity constraint (Capacitated MoDVRP: C-MoDVRP). As a sample use case, we study route planning for a UAV deployed on a moving carrier. To deal with the C-MoDVRP, we propose a Genetic Algorithm that is adapted to satisfy the constraints of depot mobility and range, while maximizing the number of targets visited by the UAV. To examine the success of our approach, we compare the individual performances of our proposed genetic operators with conventional ones and the performance of our overall solution with the Nearest Neighbor and Hill Climbing heuristics, on some well-known TSP benchmark problems, and receive successful results.
An Iot Application for Locating Victims Aftermath of an Earthquake
(Ieee, 2017) Karakaya, Murat; Sengul, Gokhan; Gokcay, Erhan
This paper presents an Internet of Things (IoT) framework which is specially designed for assisting the research and rescue operations targeted to collapsed buildings aftermath of an earthquake. In general, an IoT network is used to collect and process data from different sources called things. According to the collected data, an IoT system can actuate different mechanisms to react the environment. In the problem at hand, we exploit the IoT capabilities to collect the data about the victims before the building collapses and when it falls down the collected data is processed to generate useful reports which will direct the search and rescue efforts. The proposed framework is tested by a pilot implementation with some simplifications. The initial results and experiences are promising. During the pilot implementation, we observed some issues which are addressed in the proposed IoT framework properly.
Citation - WoS: 1
Citation - Scopus: 1
Msct: an Efficient Data Collection Heuristic for Wireless Sensor Networks With Limited Sensor Memory Capacity
(Ksii-kor Soc internet information, 2015) Karakaya, Murat
Sensors used in Wireless Sensor Networks (WSN) have mostly limited capacity which affects the performance of their applications. One of the data-gathering methods is to use mobile sinks to visit these sensors so that they can save their limited battery energies from forwarding data packages to static sinks. The main disadvantage of employing mobile sinks is the delay of data collection due to relative low speed of mobile sinks. Since sensors have very limited memory capacities, whenever a mobile sink is too late to visit a sensor, that sensor's memory would be full, which is called a 'memory overflow', and thus, needs to be purged, which causes loss of collected data. In this work, a method is proposed to generate mobile sink tours, such that the number of overflows and the amount of lost data are minimized. Moreover, the proposed method does not need either the sensor locations or sensor memory status in advance. Hence, the overhead stemmed from the information exchange of these requirements are avoided. The proposed method is compared with a previously published heuristic. The simulation experiment results show the success of the proposed method over the rival heuristic with respect to the considered metrics under various parameters.
Öğrenci Ders Devamının Sınavlarda Alınan Notlara Etkisi Üzerine Bir Durum Çalışması
(Mersin Üniversitesi Eğitim Fakültesi Dergisi, 2016) Bostan, Atila; Karakaya, Murat
Üniversite eğitimde öğrencilerin derslere devam mecburiyetinin olup olmaması, okuldan okula değişebileceği gibi aynı okul içinde verilen dersler arasında da farklılıklar göstermektedir. Öğrencilerin derse devam etmesiyle, dönem sonucu elde ettiği ders başarısı arasında olumlu bir ilişki olup olmadığı önemli bir araştırma konusu olmuştur. Bu konuda yapılan çalışmaların önemli bir bölümünde, dersteki başarı kriteri olarak dönem sonu başarı notu esas alınmış ve yapılan çalışmaların çoğunluğunda iki olgu arasında olumlu bir ilişki gözlemlenmiştir. Bunun sonucu olarak da, çalışmaların sonuç bölümlerinde öğrencilerin derslere devam etmelerinin sağlanması ve devamlarının artırılması tavsiye edilmiştir. Ancak, çok az çalışmada bu tedbirin gerçek hayata nasıl geçirilebileceği ile ilgili önerilerde bulunulmuştur. Diğer taraftan bu önerilerin ders devamını veya başarıyı artırmakta etkisi genellikle ölçülmemiştir. Derse devam durumunun artırılması için önerilen yöntemlerin çoğu, idari tedbirlerle öğrencileri derse devam etmeye zorlamayı içermektedir. Halbuki, ders devamından beklenen faydanın sağlanabilmesi için; öğrencinin bir zorunluluktan ziyade, öğrenme sürecinin bir parçası olarak derse devam etmeye teşvik edilmesi önemlidir. Bu çalışmada; ders devamı ile sınav notu arasındaki ilişki hem dönem sonu sınav notu hem de dönem içerisinde yapılan ara sınavlar dikkate alınarak incelenmiştir. Böylelikle öğrencinin devam durumu ile sınavlar arasında ilişkiyi gözlemlemek mümkün olmuştur. Ayrıca, ders işleme yönteminde yapılan bir değişikliğin, ders devamına ve öğrencinin notuna olan etkisi de bu kapsamda değerlendirilmiştir. Böylelikle, derse devam ile alınan notlar arasındaki ilişki üzerinde ders işleme yönteminin etkisi de izlenebilmiştir. Bu yönleriyle makalede sunulan çalışma, yazımda var olan yayınlardan farklılaşmaktadır.
Citation - WoS: 1
Ontology-Supported Enterprise Architecture Analysis
(Ieee, 2017) Uysal, Murat Pasa; Karakaya, Murat
Today, processing integrated information within and between enterprises is increasingly becoming more and more critical, and so is the implementation and evaluation of an Enterprise Architecture (EA). The review of literature on EA evaluation shows several issues. However, the evaluation of EAs has not attracted sufficient attention, and thus, this research area has not been explored thoroughly yet. We believe that in order to ensure consistency, interoperability and computational inferences among EAs, a complete and holistic approach, rather than monolithic, should be developed. Therefore, in this study, we propose an ontology-supported process model for the evaluation of EAs, and present the implementation details. The main contributions of the present study are the improvements realized in the expressiveness, extensibility, and computable power of EAs, and their evaluation techniques. Although the proposed model requires gathering empirical evidences and investigating applications in concrete cases, the first implications of the proposed model indicates its validity and feasibility, and, hence, the initial results are promising for continuing future studies.
Citation - WoS: 1
Parking Space Occupancy Detection Using Deep Learning Methods
(Ieee, 2018) Akinci, Fatih Can; Karakaya, Murat
This paper presents an approach for gathering information about the availabilty of the parking lots using Convoltional Neural Network (CNN) for image processing running on an embedded system. By using an efiicent neural network model, we made it possible to use a very low cost embedded system compared to the ones used in previous works on this topic. This efficient model's performance is compared to one of the models that proved its accuracy in image classification competitions. In these tests, we used datasets that has thousands of different images taken from parking lots in different light and weather conditions.
Remotely Monitoring Activities of the Elders Using Smart Watches
(International Journal of Scientific Research in Information Systems and Engineering, 2017) Karakaya, Murat; Şengül, Gökhan; Bostan, Atila
In this paper, we propose a model for using smart watches as Internet of Things (IoT). IoT can be defined as a network of physical devices, vehicles, buildings and other items which have electronics, software, sensors, and network connectivity so that these “things” can collect and exchange data. In the proposed system, the purpose is to identify daily activities such as walking, sitting, falling, etc., by using the data acquired from the sensors of a smart watch. As smart watches have the necessary hardware and sensors, the implementation such an IoT application would not cost much. Moreover, analyzing the sensor data would yield useful information. Besides it would be a user-friendly system that does not make the elderly uncomfortable. As being a watch, this device can be always on the user. The proposed system is implemented and the results of initial experiments and user experiences are promising.
Citation - WoS: 3
Citation - Scopus: 3
Time-Sensitive Ant Colony Optimization To Schedule a Mobile Sink for Data Collection in Wireless Sensor Networks
(Old City Publishing inc, 2015) Karakaya, Murat; Computer Engineering
In Wireless Sensor Networks, sensor nodes are deployed to monitor and record the changes in their surroundings. The collected data in the sensor memories is transferred to a remote central via static or mobile sinks. Because sensors have scarce memory capacity various challenges occur in gathering the data from the environment and transferring them to the remote control. For instance, a sensor's memory might get completely full with the sensed data if the sensor can not transfer them on time. Then, a memory overflow happens which causes all the collected data to be erased to free the memory for future readings. Therefore, when a mobile sink (MS) is employed to collect data from the sensors, the MS has to visit each sensor before any memory overflow takes place. In this paper, we study the design of a mobile sink scheduling algorithm based on the Ant Colony Optimization (ACO) meta-heuristic to address this specific issue. The proposed scheduling algorithm, called Mobile Element Scheduling with Time Sensitive ACO (MES/TSACO), aims to prepare a schedule for a mobile sink to visit sensors such that the number of memory overflow incidents is reduced and the amount of collected data is increased. To test and compare the effectiveness of the MES/TSACO approach, the Minimum Weighted Sum First (MWSF) heuristic is implemented as an alternative solution. The results obtained from the extensive simulation tests show that the MES/TSACO generates schedules with considerably reduced number of overflow incidents and increased amount of collected data compared to the MWSF heuristic.
Uçuş Menzili ve Hizmet Süresi Kısıtları Altında Çoklu İha Yönlendirme için Etkin Genetik Algoritma
(2017) Karakaya, Murat; Sevinç, Ender
Son zamanlarda gerek askeri gerekse sivil amaçlı İnsansız Hava Aracı (İHA) kullanımı giderek popülerlik kazanmaktadır. Ancak İHA'ların etkin kullanımı için gerekli Servis Kalitesi(QoS)'ni karşılaması için benimsenen yaklaşımlarının sınırlamaları vardır. İHA'lar arasındaki kıyaslamanın önemli sınırlarından biri de uçuş menzilidir. Çoğu zaman, İHA'ların, yeterli enerji kaynağı olmaması ve böylelikle nispeten kısa uçuş menzillerine sahip olmalarıdır. İlave olarak, İHA'ları kullanan uygulamalar için, verilen hizmet süresi zamanı içerisinde ziyaret edilmesi gereken pek çok nokta olabilir. Üstelik, uygulamalar tarafından yönlendirilecek İHA'ların sayısı da sınırlıdır. Bu nedenle, gerçek hayattaki uygulamalarda, önceden belirlenen zaman aralığı pencerelerinde daha fazla noktanın ziyaret edilmesi maksadıyla belirli bir uçuş menzili olan çok sayıda İHA için bir optimizasyon sorunu ile karşılaşılmaktadır. Bu problemde biz, kullanılan İHA sayısını en aza indirmek ve zaman aralığı içerisinde ziyaret edilecek nokta sayısını en üst düzeye çıkarmak istiyoruz. Bu nedenle, Genetik bir algoritma tasarladık ve çeşitli uçuş menzilleri, servis zaman aralıkları ve nokta ağ topolojileri için kapsamlı simülasyon testleri yoluyla etkinliğini doğruladık. Daha da ötesinde, tasarlanan algoritma ile arzu edilen başarıyı sağlayabilecek rakip bir algoritma ile de sonuçlar karşılaştırılmıştır.
Citation - WoS: 1
An Undergraduate Curriculum for Deep Learning
(Ieee, 2018) Tirkes, Guzin; Ekin, Cansu Cigdem; Sengul, Gokhan; Bostan, Atila; Karakaya, Murat
Deep Learning (DL) is an interesting and rapidly developing field of research which has been currently utilized as a part of industry and in many disciplines to address a wide range of problems, from image classification, computer vision, video games, bioinformatics, and handwriting recognition to machine translation. The starting point of this study is the recognition of a big gap between the sector need of specialists in DL technology and the lack of sufficient education provided by the universities. Higher education institutions are the best environment to provide this expertise to the students. However, currently most universities do not provide specifically designed DL courses to their students. Thus, the main objective of this study is to design a novel curriculum including two courses to facilitate teaching and learning of DL topic. The proposed curriculum will enable students to solve real-world problems by applying DL approaches and gain necessary background to adapt their knowledge to more advanced, industry-specific fields.
Unidirectional Data Transfer: a Secure System To Push the Data From a High Security Network To a Lower One Over an Actual Air-Gap
(International Journal of Scientific Research in Information Systems and Engineering, 2017) Şengül, Gökhan; Bostan, Atila; Karakaya, Murat
The term “air-gap” is typically used to refer physical and logical separation of two computer networks. This type of a separation is generally preferred when the security levels of the networks are not identical. Although the security requirements entail parting the data networks, there is a growing need for fast and automatic transfer of data especially from high-security networks to low-security ones. To protect security sensitive system from the risks originating from low-security network, unidirectional connections that permit the data transfer only from high to low-security network, namely information-diodes, are in use. Nonetheless, each diode solution has its drawbacks either in performance or security viewpoints. In this study, we present a unidirectional data transfer system in which the primary focus is data and signal security in technical design and with a plausible and adaptable data transfer performance. Such that the networks do not touch each other either in physically or logically and the transfer is guaranteed to be unidirectional. Apart from avoiding the malicious transmissions from low to high-security network, we claim that the proposed data diode design is safe from emanation leakage with respect to the contemporary sniffing and spoofing techniques.
Using Bluetooth Low Energy Beacons for Indoor Localization
(International Journal of Intelligent Systems and Applications in Engineering, 2017) Şengül, Gökhan; Karakaya, Murat
Bluetooth Low Energy (BLE) Beacons gain high popularity due to their low consumption of energy and, thereby, long lifetime. Using the BLE protocol, these devices emit advertisement packets at fixed intervals for a short duration. Indoor localization solutions aim to provide an accurate, low cost estimate of sub-room indoor positioning. There are various techniques proposed for this purpose. BLE Beacons are good hardware candidates to assist the creation of such indoor localization solutions. Given the exact position of BLE Beacons, one can attempt to estimate a receiver position according to the received signal power. In this work, we investigated the success of such an indoor localization approach employing multiple BLE Beacons and two different estimation techniques. The results of the experiments indicate that employing multiple BLE Beacons increases the success of prediction techniques considerably.