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Conference Object Citation - Scopus: 1A Distributed Smart Pev Charging Algorithm Based on Forecasted Mobility Energy Demand(Institute of Electrical and Electronics Engineers Inc., 2017) Kisacikoglu,M.C.; Erden,F.; Erdogan,N.This study proposes a new distributed control strategy for the grid integration of plug-in electric vehicles. The proposed strategy consists of two stages: (i) an offline process to determine an aggregated reference charge power level based on mobility estimation and base load profile, and (ii) a real-time operation based on the distributed control approach. The control algorithm manages PEV charge load profiles in order to flatten the residential distribution transformer loading while ensuring the desired state of the charge (SOC) level. The proposed algorithm is tested on real distribution transformer loading data, and compared with heuristic charging scenarios. The numerical results are presented to demonstrate the impact of the proposed algorithm. © 2016 IEEE.Conference Object A Framework for Fuzzy Video Content Extraction, Storage and Retrieval(Institute of Electrical and Electronics Engineers Inc., 2010) Koyuncu,M.; Yilmaz,T.; Yildirim,Y.; Yazici,A.This study presents a new comprehensive framework for semantic content extraction from raw video, storage of the extracted data and retrieval of the stored data. Objects, spatial relations between objects, events and temporal relations between events, which are considered as semantic contents of the video, are extracted automatically to a certain extend with the developed approach. Extraction process is supported by manual annotation when automatic extraction is not satisfactory. The extracted information is stored in an intelligent fuzzy object-oriented database in which the database is enhanced with a fuzzy knowledge-based system. Domain specific deduction rules can be defined to derive new information about semantic contents of the video. The database is also supported by an access structure to increase retrieval efficiency. The proposed framework is capable of handling uncertain data arising from annotation process or video nature. © 2010 IEEE.Conference 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 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 Citation - WoS: 1Citation - Scopus: 1Characterization of satellite transponder impairments based on simulations with test data(Institute of Electrical and Electronics Engineers Inc., 2015) Ulubey,O.; Gulgonul,S.; Kara,A.A satellite transponder simulator based on actual test data of TURKSAT 3A satellite has been developed to analyze degradation in multicarrier scenarios. Communication impairment sources through a transponder are explained in conjunction with a methodology defined to characterize total degradation resulting from them. Several transponder utilization scenarios are studied with respect to total degradation and optimum operation conditions are demonstrated. © 2015 IEEE.Conference Object Citation - WoS: 2Citation - Scopus: 2New Wavelet-Based Features for the Recognition of Jittered and Stagger Pri Modulation Types;(Institute of Electrical and Electronics Engineers Inc., 2015) Gencol,K.; Kara,A.; At,N.In dense electronic warfare environments, numerous emitters can be active simultaneously and an interleaved stream of pulses in natural time of arrival order is received by the Electronic Support Measures (ESM) receiver. It is the task of the ESM system to de-interleave this mixed pulse sequence and thus to identify the surrounding threatening emitters. In this processing, pulse repetition interval (PRI) modulation recognition has a significant role due to the fact that it can reveal the hidden patterns inside pulse repetition intervals and thus help identify the emission source and its functional purpose. In this paper, we propose new wavelet-based features for the recognition of jittered and stagger PRI modulation types. The recognition of these types are heavily based on histogram features. Experimental results show that the proposed feature set have very high recognition rates and outperform histogram based methods. © 2015 IEEE.Conference Object Design and Implementation of an Expressive Talking Mobile Robot: Toztorus(Institute of Electrical and Electronics Engineers Inc., 2018) Tozan,O.; Tora,H.; Uslu,B.; Una,B.; Ceylan,E.This paper is about a brand new robot and all its development stages from the design to the show time. As an undergraduate research project (the LAP program at Atilim University), the robot TozTorUs is the outcome of the dense efforts of a team. With the sensors equipped, it navigates autonomously in the environment in which it is located by avoiding the obstacles. It can understand your questions and answer them using Google's speech technologies. Although it is not a humanoid robot, with eyes and mouth simulator LED displays, it is as friendly as a human. We can also control TozTorUs using a mobile phone. Apart from these, it is able to adjust its height with respect to the visitor's, thus allowing it to make an eye contact with the person. Although TozTorUs is designed for welcoming, it may also be employed for consulting, security and elderly assistance. © 2018 IEEE.Conference Object Citation - WoS: 3Citation - Scopus: 10Biomechanical Design and Control of Lower Limb Exoskeleton for Sit-To and Stand-To Movements(Institute of Electrical and Electronics Engineers Inc., 2018) Qureshi,M.H.; Masood,Z.; Rehman,L.; Owais,M.; Khan,M.U.In this paper, we present design and development phase of lower limb robotic exoskeleton that can assist paralyzed individuals. Motion of the human wearing exoskeleton is introduced by actuators. Both exoskeleton legs are attached to the supporting frame by passive universal joints. The exoskeleton provides 3 DOFs per limb of which two joints are active and one passive. The control actions i.e., sit-to-stand and stand-to-sit movements are triggered using Double Pole Double Throw (DPDT) toggle switch. The control scheme is implement using Switch control method and the feedback is provided by means of current measurement. This assistive device can be utilized for the disabled persons. The simulation results are provided that evaluates the performance of the control actions on exoskeleton. © 2018 IEEE.
