Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Doctoral Thesis A reliable and secure communication design for underwater sensor networks concerning energy efficiency(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023) UYAN, Osman Gökhan; Güngör, Vehbi ÇağrıUnderwater Acoustic Sensor Networks (UASNs) recently attract scientists because of its wide range of applications and emerging technology. A design challenge in UASN's is the limited network lifetime and poor reliability caused by limited battery supply of sensors and harsh channel conditions in underwater environment. Moreover, sensors might transmit sensitive data that must be disguised against eavesdropping attacks. To maintain a reliability level, packet-duplication and multi-path routing method are suggested, which renders eavesdropping attacks easier. For data security, cryptographic encryption is the most acclaimed method. However, encryption needs extra computations, which consume extra energy and cause a decrease in the network lifetime. As a countermeasure along with encryption against silent listening, fragmenting data and transmitting in pieces over different paths has been proposed. To address these challenges, an optimization framework has been developed to analyze the effects of multi-path routing, packet duplication, encryption, and data fragmentation on network lifetime. However, the solution time of the proposed optimization model is quite high, and sometimes it cannot come up with feasible solutions. To this end, in this study, different regression and neural network methods have been proposed to predict the energy consumptions of underwater nodes as supplementary methods to optimization models. Performance evaluations show that the proposed methods yield remarkably accurate predictions and can be used for energy consumption prediction in UASNs.Article Citation - WoS: 2Citation - Scopus: 2Slow Motion in Corona Times: Modeling Cyclists' Spatial Choice Behavior Using Real-Time Probe Data(Univ Minnesota, Center Transportation Studies, 2024-11-11) Kourtit, Karima; Osth, John; Nijkamp, Peter; Turk, UmutThe recent COVID-19 pandemic has provided a renewed impetus for empirical research on slow and active modes of transportation, specifically bicycling and walking. Changes in modal choice appear to be sensitive to the actual quality of the environment, the attractive land use and built environment conditions, and the ultimate destination choice. This study examines and models the influence of cyclists' health concerns during the pandemic on their spatial destination and route choices. Using a large real-time dataset on the individual daily mobility of cyclists in the province of Utrecht, the Netherlands, collected through GPS-linked sensors on bikes (VGI, or volunteered geographical information), the analysis employs spatial regression models, Shapley decomposition techniques, and spatial autocorrelation methods to unveil the backgrounds of changes in spatial behavior. The results reveal that the perceived wellbeing benefits of bicycling in green areas during the pandemic have significantly influenced cyclists' choice behavior, in particular route and destination choice.