40 results
Search Results
Now showing 1 - 10 of 40
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 Citation - Scopus: 2Detecting Errors in Automatic Image Captioning by Deep Learning;(Institute of Electrical and Electronics Engineers Inc., 2021) Karakaya,M.Automatic tagging of images is an important researcli topic in tlie field of image processing. Anotlier area similar to this is the automatic generation of picture captions. In this study, a deep learning model that automatically tags the pictures is used to detect errors in image captions. As a result of the initial experiments, it is observed that the proposed system can find up to 80% of the errors in the image captions. © 2021 IEEEConference Object Citation - Scopus: 50Internet-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: 34Improving Text Classification With Transformer(Institute of Electrical and Electronics Engineers Inc., 2021) Soyalp,G.; Alar,A.; Ozkanli,K.; Yildiz,B.Huge amounts of text data are produced every day. Processing text data that accumulates and grows exponentially every day requires the use of appropriate automation tools. Text classification, a Natural Language Processing task, has the potential to provide automatic text data processing. Many new models have been proposed to achieve much better results in text classification. The transformer model has been introduced recently to provide superior performance in terms of accuracy and processing speed in deep learning. In this article, we propose an improved Transformer model for text classification. The dataset containing information about the books was collected from an online resource and used to train the models. We witnessed superior performance in our proposed Transformer model compared to previous state-of-art models such as L S T M and CNN. © 2021 IEEEConference Object Securing the Internet of Things: Challenges and Complementary Overview of Machine Learning-Based Intrusion Detection(Institute of Electrical and Electronics Engineers Inc., 2024) Isin, L.I.; Dalveren, Y.; Leka, E.; Kara, A.The significant increase in the number of IoT devices has also brought with it various security concerns. The ability of these devices to collect a lot of data, including personal information, is one of the important reasons for these concerns. The integration of machine learning into systems that can detect security vulnerabilities has been presented as an effective solution in the face of these concerns. In this review, it is aimed to examine the machine learning algorithms used in the current studies in the literature for IoT network security. Based on the authors' previous research in physical layer security, this research also aims to investigate the intersecting lines between upper layers of security and physical layer security. To achieve this, the current state of the area is presented. Then, relevant studies are examined to identify the key challenges and research directions as an initial overview within the authors' ongoing project. © 2024 IEEE.Conference Object Citation - Scopus: 6Topic-Controlled Text Generation(Institute of Electrical and Electronics Engineers Inc., 2021) Çağlayan,C.; Karakaya,M.Today, the text generation subject in the field of Natural Language Processing (NLP) has gained a lot of importance. In particular, the quality of the text generated with the emergence of new transformer-based models has reached high levels. In this way, controllable text generation has become an important research area. There are various methods applied for controllable text generation, but since these methods are mostly applied on Recurrent Neural Network (RNN) based encoder decoder models, which were used frequently, studies using transformer-based models are few. Transformer-based models are very successful in long sequences thanks to their parallel working ability. This study aimed to generate Turkish reviews on the desired topics by using a transformer-based language model. We used the method of adding the topic information to the sequential input. We concatenated input token embedding and topic embedding (control) at each time step during the training. As a result, we were able to create Turkish reviews on the specified topics. © 2021 IEEEConference Object Citation - WoS: 1Citation - Scopus: 4Smart Contract Upgradability: a Structured and Natural Approach(Institute of Electrical and Electronics Engineers Inc., 2024) Culha, Davut; Yazici, AliSoftware maintenance is crucial as technology rapidly evolves, requiring software to meet new demands and correct errors. Smart contracts, immutable programs on blockchains like Ethereum, face challenges despite their immutability, often needing updates for errors or new features. Smart contracts are upgraded using different patterns, which are not natural because most of them implement upgrades using low-level operations that deviate from their intended use. In other words, these patterns are not natural because upgrades are done by implementing workarounds. Moreover, smart contracts are also susceptible to security vulnerabilities because they may hold large amounts of money. In this paper, upgradability of smart contracts is considered a necessity. For this purpose, a more structured method is proposed by adding high-level features and combining inheritance properties of object-oriented languages. A key component of this method is the gotoContract variable, which allows for the redirection of function calls to upgraded contracts. The proposed method provides a complete upgrade of data and functions in smart contracts. It aims to minimize the effects of upgrades on end users of the smart contracts. Additionally, this natural way of upgrading will help mitigate security risks in the smart contracts by providing a high-level approach to upgrade.Conference Object Citation - Scopus: 1Semantic Interoperability and Reusability in Iot: a Systematic Mapping Study(Institute of Electrical and Electronics Engineers Inc., 2024) Alsaeh, A.; Sezen, A.Internet of Things (IoT) enables different devices, sensors, or humans to connect via the Internet. However, various IoT devices generate heterogeneous data in different formats. This hinders IoT devices from integrating and exchanging data between them. Adding semantic web technologies to the Web of Things (WoT) has greatly enabled IoT devices to be semantically interoperable. Moreover, W3C has established a Semantic Sensor Network (SSN) ontology that can be reused in different IoT applications due to difficulties in developing new ontologies. Many systematic mapping reviews in the literature have addressed semantic interoperability in IoT. Although reusability can play a vital role in enhancing semantic interoperability, none of those studies has discussed reusability and semantic interoperability together in the IoT area. In this article, we are seeking to fill this gap in the current literature by conducting a systematic mapping review for 72 articles to point out semantic interoperability as well as reusability in IoT. Five research questions have been identified regarding challenges and possible solutions about both semantic interoperability and reusability. The reviewed articles are classified into four categories. There are 47 articles about semantic interoperability, 2 of which discuss reusability, 18 of which include semantic interoperability with reusability, and the last category includes surveys. Moreover, the research questions are also assigned to the related category that answers the questions. This article highlights important insights about semantic web techniques namely, RDF, ontology, SPARQL, and OWL. Additionally, this article concludes how these techniques are enhanced in diverse domains such as healthcare, smart cities, and the energy domain. On top of that, this systematic mapping shows how reused ontology plays a remarkable role in the IoT domain Finally, results that answer the research questions are figured out and deeply analyzed in the tables and graphs. © 2024 IEEE.
