Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Conference Object Citation - WoS: 30Citation - Scopus: 38Software Defined Communication Framework for Smart Grid to Meet Energy Demands in Smart Cities(IEEE, 2019-04) Faheem, Muhammad; Umar, Muhammad; Butt, Rizwan Aslam; Raza, Basit; Ngadi, Md. Asri; Gungor, Vehbi CagriIn smart cities, the electricity is an essential component since it preserves a certain level of residents' life quality and provisions the entire spectrum of their economic activities. Thus, a smart way is essential to develop cities without disregarding energy issues. In this scope, the smart grid paradigm offers power supply in an efficient, sustainable and economical manner with minimal impact on the environment and can meet the future energy demands. However, real-time monitoring and control of the smart grid (SG) for continuous and quality-aware power supply in smart cities (SCs) is challenging and requires an advanced quality of service (QoS)-aware communication framework. In this context, this research aims to present a novel data-gathering scheme by using the Internet of software-defined mobile sinks (SDMSs) and wireless sensor networks (WSNs) in the smart grid. The extensive simulation results conducted through the EstiNet9.0 indicate that the designed scheme outperforms existing approaches and achieves its defined goals for events-drive applications in the SG.Book Part Micro-Electromechanical Systems for Underwater Environments(Igi Global, 2017) Tuna, Gurkan; Gungor, Vehbi CagriUnderwater networking technologies have brought us unforeseen ways to explore the unexplored aquatic environment and this way provided us with a large number of different kinds of applications for environmental, scientific, commercial, and military purposes. Although precise and continuous aquatic environment monitoring capability is highly important for various underwater applications, due to the unique characteristics of underwater networks such as low communication bandwidth, high error rate, node mobility, large propagation delay, and harsh underwater environmental conditions, existing solutions cannot be applied directly to underwater networks. Therefore, new solutions considering the unique features of underwater environment are highly demanded. In this chapter, the authors mainly focus on the use of wireless micro-electromechanical systems for underwater networks and present its advantages. In addition, the authors investigate the challenges and open research issues of wireless MEMS to provide an insight into future research opportunities.Conference Object Citation - Scopus: 4Deep Learning Based Employee Attrition Prediction(Springer International Publishing AG, 2023) Gurler, Kerem; Pak, Burcu Kuleli; Gungor, Vehbi CagriEmployee attrition is a critical issue for the business sectors as leaving employees cause various types of difficulties for the company. Some studies exist on examining the reasons for this phenomenon and predicting it with Machine Learning algorithms. In this paper, the causes for employee attrition is explored in three datasets, one of them being our own novel dataset and others obtained from Kaggle. Employee attrition was predicted with multiple Machine Learning and Deep Learning algorithms with feature selection and hyperparameter optimization and their performances are evaluated with multiple metrics. Deep Learning methods showed superior performances in all of the datasets we explored. SMOTE Tomek Links were utilized to oversample minority classes and effectively tackle the problem of class imbalance. Best performing methods were Deep Random Forest on HR Dataset from Kaggle and Neural Network for IBM and Adesso datasets with F1 scores of 0.972, 0.642 and 0.853, respectively.Book Part Citation - WoS: 1Cognitive Radio Networks for Smart Grid Communications Potential Applications, Protocols, and Research Challenges(CRC Press-Taylor & Francis Group, 2017-12-19) Kogias, Dimitris; Tuna, Gurkan; Gungor, Vehbi Cagri