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Conference Object Edge-Enabled Blockchain Architecture for Scalable and Trustworthy IoT Data Marketplaces(Institute of Electrical and Electronics Engineers Inc., 2026) Ayribas, Haktan; Culha, DavutConference Object Citation - WoS: 28Citation - Scopus: 25A Comparison of Stream Processing Frameworks(Institute of Electrical and Electronics Engineers Inc., 2017) Karakaya,Z.; Yazici,A.; Alayyoub,M.This study compares the performance of Big Data Stream Processing frameworks including Apache Spark, Flink, and Storm. Also, it measures the resource usage and performance scalability of the frameworks against a varying number of cluster sizes. It has been observed that, Flink outperforms both Spark and Storm under equal constraints. However, Spark can be optimized to provide the higher throughput than Flink with the cost of higher latency. © 2017 IEEE.Conference Object Citation - Scopus: 9A Layered Security Architecture for Corporate 802.11 Wireless Networks(Institute of Electrical and Electronics Engineers Inc., 2004) Erten,Y.M.; Tomur,E.In this study we have investigated the security aspects of wireless local area networks and discussed the weaknesses associated with various conventional 802.11 security protocols such as WEP and 802.1x. We propose an architecture to control access to corporate 802.11 wireless networks, based on the privileges and location of users, using the tested wired network components such as VPNs and Firewalls. The presented architecture reduces the security risks in enterprise level deployment of wireless LANs.Conference Object Citation - Scopus: 4Software engineering issues in big data application development(Institute of Electrical and Electronics Engineers Inc., 2017) Karakaya,Z.Big Data has become one of the most important concepts that is being studied in Computer/Software Engineering. The data produced in recent years have increased rapidly and exponentially, necessitating the solution of major problems such as the collection, processing and storage of huge volume of data. Big Data Frameworks are developed specifically to solve these problems that facilitates application developers by providing opportunities to collect, process, manage, monitor and analyze these data. A few examples of these frameworks are Hadoop, Spark, Storm, and Flink, which are developed by Software Engineers as open source projects. Although the challenges raised from coordination of IT resources such as huge amounts of computation power, storage area, memory, and network bandwidth in a distributed manner solved by these frameworks, there still remains many Software Engineering problems in application development phase, even if they based on these frameworks. High scalability, fault tolerance, flexibility, reliability and testability can be listed as the main issues need to be carefully considered in terms of Software Engineering. In this paper, we first clarify the terms Framework-Application, and then the overview information about Big Data and related frameworks are given before emphasizing the problems arising in terms of Software Engineering. Nevertheless, we tried to provide guidance to the people who would develop software for Big Data and tried to give the further research guidance. © 2017 IEEE.Conference Object The Impact of Prompting Strategies on the Quality of LLM-Generated Biomedical Explanations(Institute of Electrical and Electronics Engineers Inc., 2026) Bon, Mohammad; Kizilirmak, Merve; Alper, Barkin Mert; Nazlioglu, SelmaConference Object A Multimodal Synthetic Dataset for Multi-Camera Human Detection and Occlusion Analysis in Indoor Environments(Institute of Electrical and Electronics Engineers Inc., 2026) Kocabas, Ifagat Buse; Sezen, Arda; Ustun, Tutku Irem; Bakal, Mahmut Furkan; Turkmen, Guzin; Sengul, GokhanConference 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 Citation - WoS: 1Citation - Scopus: 1Sizing of Series Hybrid Electric Vehicle With Hybrid Energy Storage System(Institute of Electrical and Electronics Engineers Inc., 2018) Ertan,H.B.; Arikan,F.R.This work is aimed to develop a realistic design procedure for a series hybrid plug in vehicle, with a view to use it in a mathematical design optimization. The purpose of the optimization is minimizing the initial cost, as well as the running costs of the vehicle. Therefore there is a multi-objective design optimization problem in hand. Such problems are very suitable for mathematical optimization, however, accurate and not time consuming design procedure is a must, to obtain meaningful results. This paper introduces such a design procedure. The approach is illustrated on a commercial vehicle simulation model. The accuracy of the model is illustrated by comparing simulation results with vehicle test results. © 2018 IEEE.Conference Object LLM Integration into Physics Informed Neural Networks(Institute of Electrical and Electronics Engineers Inc., 2026) Yetkin, Sadik; Akay, Hasan Umur; Nazlioglu, SelmaConference Object Neuronavigation systems and passive usage problem;(Institute of Electrical and Electronics Engineers Inc., 2017) Cagiltay,N.; Topalli,D.; Borcek,A.O.; Tokdemir,G.; Maras,H.; Tonbul,G.; Aydin,E.Nowadays, neuronavigation systems are used in brain surgery procedures, known as a technology to help the surgeon during the operational period. However, the surgeons have faced several problems with the existing systems. Some of these problems are related to the systems software and user interfaces. In this study, such problems are examined and the 'Passive Usage' term is added to the literature by establishing a connection between the problems of endoscopic surgical procedures and similar issues occurred in other domains. The passive usage problem is generalized on different domains for the first time with this study. The results of the study expected to gather up the similar passive usage problems experienced in different domains. Accordingly, the methodologies and studies that are conducted in different research areas may lead to eliminate the Passive Usage problems efficiently. © 2016 IEEE.
