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Conference Object Citation - WoS: 4Citation - Scopus: 6A Reinforcement Learning Algorithm for Data Collection in Uav-Aided Iot Networks With Uncertain Time Windows(Ieee, 2021) Cicek, Cihan TugrulUnmanned aerial vehicles (UAVs) have been considered as an efficient solution to collect data from ground sensor nodes in Internet-of-Things (IoT) networks due to their several advantages such as flexibility, quick deployment and maneuverability. Studies on this subject have been mainly focused on problems where limited UAV battery is introduced as a tight constraint that shortens the mission time in the models, which significantly undervalues the UAV potential. Moreover, the sensors in the network are typically assumed to have deterministic working times during which the data is uploaded. In this study, we revisit the UAV trajectory planning problem with a different approach and revise the battery constraint by allowing UAVs to swap their batteries at fixed stations and continue their data collection task, hence, the planning horizon can be extended. In particular, we develop a discrete time Markov process (DTMP) in which the UAV trajectory and battery swapping times are jointly determined to minimize the total data loss in the network, where the sensors have uncertain time windows for uploading. Due to the so-called curse-of-dimensionality, we propose a reinforcement learning (RL) algorithm in which the UAV is trained as an agent to explore the network. The computational study shows that our proposed algorithm outperforms two benchmark approaches and achieves significant reduction in data loss.Article Citation - WoS: 9Citation - Scopus: 11Food Index: a Multidimensional Index Structure for Similarity-Based Fuzzy Object Oriented Database Models(Ieee-inst Electrical Electronics Engineers inc, 2008) Yazici, Adnan; Ince, Cagri; Koyuncu, MuratA fuzzy object-oriented data model is a fuzzy logic-based extension to an object-oriented database model that permits uncertain data to be explicitly represented. The fuzzy object-oriented database (FOOD) model is one of the proposed models in the literature to handle uncertainty in object-oriented databases. Several kinds of fuzziness are dealt with in the FOOD model, including fuzziness at attribute level and between object and class and between class and superclass relations. The traditional index structures do not allow efficient access to both crisp and fuzzy objects for fuzzy object-oriented databases since they are not efficient enough in processing both crisp and fuzzy queries. In this study, we propose a new index structure, namely a FOOD index (FI), to deal with different kinds of fuzziness in fuzzy object-oriented databases and to support multidimensional indexing. In this paper, we describe this proposed index structure and show how it supports various types of flexible queries, and evaluate its performance for exact, range, and fuzzy queries.Article Citation - WoS: 1Citation - Scopus: 1Capital Structure Decisions Under Uncertainty: the Case of Turkey(Routledge Journals, Taylor & Francis Ltd, 2024) Dincergok, Burcu; Eruygur, Hakki OzanThis study analyzes the relationship between uncertainty and target leverage ratios on manufacturing firms listed in Borsa Istanbul between 2005-2020. To handle possible instrument proliferation and weak instrument problems of System GMM methodology of dynamic panel data, we mainly adopted the Quasi Maximum Likelihood estimator and found that uncertainty has a significant negative marginal effect on target leverage ratios. Our analysis revealed that firms with high levels of uncertainty have lower average leverage ratios than other firms. ANCOVA analysis results show that uncertainty is in the first three time-varying variables which have the highest impact on target leverage variation.
