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Conference Object Citation - Scopus: 4Convolution Neural Network (cnn) Based Automatic Sorting of Cherries(Institute of Electrical and Electronics Engineers Inc., 2021) Park,H.; Khan,M.U.Cherries are spring fruits enriched with nutrients, and are easily available in food markets around the world. Due to their excess demand, many enterprises solely focused on their processing. Cherries are especially susceptible to pathological-, physiological-diseases and structural degradation due to their soft outer skin. The post-harvest life of the fruit is limited by various characteristics. The agricultural industry has also been at the forefront to get benefits from the advanced machine learning tools. This study presents an image processing-based system for sorting cherries using the convolutional neural network (CNN). For this study, Prunus avium L cherries of export quality, available in Turkey, tagged as ‘0900 Ziraat’, are used. Surprisingly, there exists no dataset for these cherries; hence, we developed our dataset. Through the proposed approach based upon U-Net, the binary classification accuracy of 99% is achieved. Clear identification is demonstrated by the test results of varying mixture ratios of good and bad cherries. It can therefore be said that for cherry sorting and grading, U-Net can be applied as a reliable and promising machine learning tool. ©2021 IEEEConference Object Comparative Analysis Of Patch Antennas With Rectangular Slots For Laminate And Wearable Materials At 5g Networks(Institute of Electrical and Electronics Engineers Inc., 2024) Hakanoglu, B.G.; Agaya, E.; Gulmez, G.; Yalinsu, S.In this study, new multi-band patch antenna design models are proposed for use in 5G networks. The purpose of the designs is to open rectangular slots on rectangular shaped patch antennas and bring them to the desired operating conditions with parametric analyzes. The designs were carried out by following the same procedure steps using five different dielectric laminate substrate materials, such as RO3003, RT6006, FR4, RO3203, RO6010, and one denim fabric base material. The antennas were compared in terms of return loss, gain and radiation characteristics. Except for the antenna designed with RO3203 at certain values of rectangular slots, radiation at multiple frequencies was obtained at 5G frequencies. With the proposed method, improvement was observed for return loss and bandwidth characteristics in the RO3203 based antenna. This study will be a resource for antenna researchers by revealing the responses of different substrate materials to the same design method for 5G bands in patch antennas. © 2024 IEEE.Conference Object Citation - Scopus: 2Miniaturized 2.4 Ghz Antenna Design for Uav Communication Link;(Institute of Electrical and Electronics Engineers Inc., 2020) Yilmaz,V.S.; Kara,A.; Aydin,E.In many communications applications, unlike conventional antennas, lightweight, flexible, small antennas that can adapt to mechanical and industrial constraints are required. In this study, the results of antenna design operating at 2.4 GHz are presented for use in Unmanned Aerial Vehicle (UAV) tele command links. In the parametric and optimization studies carried out on the antenna, it is aimed to increase the gain while keeping the size as small as possible. The requirements of the industry, such as light, aesthetics, miniature and high gain aspects of the antenna were targeted in the design process. Finally, an antenna of 55.2x88 mm size and 7dB gain was achieved using commercial electromagnetic design tools. The designed antenna become satisfying industrial requirements with these features. © 2020 IEEE.Conference Object Feature fusion in part-based object detection;(Institute of Electrical and Electronics Engineers Inc., 2015) Koyuncu,M.; Cetinkaya,B.In this study, classification of complex objects in images as a whole is compared with classification of its distinctive components using different features. In addition, the impact of feature fusion in part-based object detection is investigated. Applied method, implemented system, conducted tests and their results are presented in this paper. Test results show that, even in the case of a good segmentation, object components are classified more successfully compared to whole object and feature fusion method improves the obtained results to a certain degree. © 2015 IEEE.Conference Object Informatics Engineering Education in Turkey and Expectations of Software Industry;(Institute of Electrical and Electronics Engineers Inc., 2018) Yazici,A.; Mishra,A.; Karakaya,Z.; Ustunkok,T.In this study, using the ÖSYM data, the number of intakes in Informatics Engineering programs in Turkey, accreditation data and the medium of instruction of the program are summarized for the years 2016 and 2017. In addition, the software sector's expectations from the informatics engineering graduates are reassessed based on the academic studies. The developed knowledge-skill gap set was used to evaluate the situation in Turkish informatics engineering programs. Sector expectations are discussed in the context of 2017-2019 Turkey Software Sector Strategy and Action Plan prepared by the Ministry of Science, Industry and Technology of Turkey and some proposals are made for the academia. As a result, it was observed that the expectations of the software industry were similar in all studies. Additionally, the expectations were changed in the direction of developing technologies and this change should be reflected in the informatics engineering programs. © 2018 IEEE.Conference Object Need for a Software Development Methodology for Research-Based Software Projects(Institute of Electrical and Electronics Engineers Inc., 2018) Cereci,I.; Karakaya,Z.Software development is mostly carried by a group of individuals. Software development methodologies are heavily utilized to organize these individuals and keep track of the entire software development process. Although previously proposed software development methodologies meet the needs of the industry and the firms, they are not usually suitable for research-based software projects that are carried by universities and individual researchers. In this paper, we aim to show the necessity of a new software development methodology for research-based problems carried by universities. The literature review will show the differences between industry and university software projects from certain aspects. These findings will be supported by the authors own research on the area. This qualitative research involves collecting data through interviews and applying Grounded Theory to better understand the development process. © 2018 IEEE.Conference Object Citation - Scopus: 2Insights From Eye-Movement Events in an Educational Computer-Based Environment (ece) for Endo-Neurosurgery Training Considering Gender, Hand Condition and Scenario Effects(Institute of Electrical and Electronics Engineers Inc., 2018) Dalveren,G.G.M.; Cagiltay,N.E.Surgical residents of endo-neurosurgery are required to develop several surgical skills such as eye-hand coordination, ability to use both hand coordination, and depth perception. During the process of gaining these skills, there are several effective factors on the individual performance such as gender, nature of the scenarios and hand condition that can be important to better organize appropriate training programs. Earlier studies show that, surgeons' mental workload show differences according to the difficulty levels of the tasks and hand conditions during the operations. Also there are some evidences showing that male surgeons performing the surgical tasks with a better performance compared to the females. However, in the literature there are not many studies conducted to better understand these effects by analyzing the eye-movements on simulation-based surgical training environments. This study aims to understand the mental workload and gender differences from fixation number and fixation duration eye-movement events. In this study four different computer-based-simulation scenarios which are developed for an Educational Computer-based-simulation Environment (ECE) for endo-neurosurgery training have been performed by 23 (3 female) surgical residents. Participants have performed each scenario in different hand conditions (dominant, non-dominant and both hand). While surgical residents were performing the scenarios their eye-movements were recorded by an eye-tracker. The Binocular Individual Threshold (BIT) classification algorithm was used for eye-movement event classification. According to the results of fixation number and fixation duration events in these four scenarios, hand conditions, scenario fidelity levels and gender are found to be important factors that make changes on mental workload of surgical residents. It can be concluded that, in non-dominant and both hand conditions mental workload increases according to the dominant hand condition. Additionally results show that scenario fidelity levels and gender have an effect on the eye-movements of surgical residents. © 2018 IEEE.Conference Object Perceptions, Expectations and Implementations of Big Data in Public Sector : Kamuda Buÿük Veri: Alglar, Beklentiler Ve Uygulamalar(Institute of Electrical and Electronics Engineers Inc., 2018) Dogdu,E.; Ozbayoglu,M.; Yazici,A.; Karakaya,Z.Big Data is one of the most commonly encountered buzzwords among IT professionals nowadays. Technological advancements in data acquisition, storage, telecommunications, embedded systems and sensor technologies resulted in huge inflows of streaming data coming from variety of sources, ranging from financial streaming data to social media tweets, or wearable health gadgets to drone flight logs. The processing and analysis of such data is a difficult task, but as appointed by many IT experts, it is crucial to have a Big Data Implementation plan in today's challenging industry standards. In this study, we performed a survey among IT professionals working in the public sector and tried to address some of their implementation issues and their perception of Big Data today and their expectations about how the industry will evolve. The results indicate that most of the public sector professionals are aware of the current Big Data requirements, embrace the Big Data challenge and are optimistic about the future. © 2018 IEEE.Conference Object Internet-Of Smart Transportation Systems for Safer Roads(Institute of Electrical and Electronics Engineers Inc., 2020) Derawi,M.; Dalveren,Y.; Cheikh,F.A.From the beginning of civilizations, transportation has been one of the most important requirements for humans. Over the years, it has been evolved to modern transportation systems such as road, train, and air transportation. With the development of technology, intelligent transportation systems have been enriched with Information and Communications Technology (ICT). Nowadays, smart city concept that integrates ICT and Internet-of-Things (IoT) have been appeared to optimize the efficiency of city operations and services. Recently, several IoT-based smart applications for smart cities have been developed. Among these applications, smart services for transportation are highly required to ease the issues especially regarding to road safety. In this context, this study presents a literature review that elaborates the existing IoT-based smart transportation systems especially in terms of road safety. In this way, the current state of IoT-based smart transportation systems for safer roads are provided. Then, the current research efforts undertaken by the authors to provide an IoT-based safe smart traffic system are briefly introduced. It is emphasized that road safety can be improved using Vehicle-to-Infrastructure (V2I) communication technologies via the cloud (Infrastructure-to-Cloud - I2C). Therefore, it is believed that this study offers useful information to researchers for developing safer roads in smart cities. © 2020 IEEE.Conference Object Citation - Scopus: 3Radial Basis Function (rbf) Based on Multistage Autoencoders for Intrusion Detection System (ids)(Institute of Electrical and Electronics Engineers Inc., 2019) Kadhim,Y.; Mishra,A.In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to detect IDS attacks with 98.80% accuracy when validated using UNSW-NB15 dataset. The experimental results show the proposed method presents satisfactory results when compared with those obtained in this field. © 2019 IEEE.
