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  • Küçük Resim
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    Performance analysis of an aggregation and disaggregation solution procedure to obtain a maintenance plan for a partially observable multi-component system
    (Elsevier Sci Ltd, 2017-11) Özgür Ünlüakın, Demet; Bilgiç, Taner
    We analyze the performance of an aggregation and disaggregation procedure in giving the optimal maintenance decisions for a multi-component system under partial observations in a finite horizon. The components deteriorate in time and their states are hidden to the decision maker. Nevertheless, it is possible to observe signals about the system status and to replace components in each period. The aim is to find a cost effective replacement plan for the components in a given time horizon. The problem is formulated as a partially observable Markov decision process (POMDP). We aggregate states and actions in order to reduce the problem space and obtain an optimal aggregate policy which we disaggregate by simulating it using dynamic Bayesian networks (DBN). The procedure is statistically compared to an approximate POMDP solver that uses the full state space information. Cases where aggregation performs relatively better are isolated and it is shown that k-out-of-n systems belong to this class.
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    EEG signal compression based on classified signature and envelope vector sets
    (IEEE Computer Society, 2007) Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık Binboğa
    In this paper, a novel method to compress ElectroEncephaloGram (EEG) Signal is proposed. The proposed method is based on the generation Classified Signature and Envelope Vector Sets (CSEVS) by using an effective k-means clustering algorithm. In this work on a frame basis, any EEG signal is modeled by multiplying three parameters as called the Classified Signature Vector, Classified Envelope Vector, and Frame-Scaling Coefficient. In this case, EEG signal for each frame is described in terms of the two indices R and K of CSEVS and the frame-scaling coefficient. The proposed method is assessed through the use of root-mean-square error (RMSE) and visual inspection measures. The proposed method achieves good compression ratios with low level reconstruction error while preserving diagnostic information in the reconstructed EEG signal.
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    Real-time 3D inspection of large civil structures using a stereoscopic camera system equipped UAV
    (International Society for Photogrammetry and Remote Sensing, 2024-12-13) Akça, Devrim; Torkut, Çağın; Kemper, Gerhard; Kunz, Noah; Caner, Doğa; Gruen, Armin
    REALTIME3D is an innovative Mixed-Reality (MR) photogrammetry system that integrates photogrammetry, UAV technology, and VR/AR solutions to enable real-time 3D infrastructure inspection. By combining these technologies, the system allows users to remotely access, visualize, and measure 3D stereoscopic models in real time. An operator on-site pilots a UAV equipped with the stereo cameras, while experts, utilizing VR headsets, can observe and analyze the object of interest from remote locations. This approach enhances cost efficiency and safety during inspections of large-scale, critical structures. The paper introduces the first prototype of the system, detailing its hardware and software components.