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Browsing by Subject "Automated systems"

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    3-Boyutlu orman yangını yayılımı sistemi
    (IEEE, 2008) Köse, Kıvanç; Yılmaz, E.; Grammalidis, N.; Aktuğ, B.; Çetin, A. Enis; Aydın, İ.
    In the last few years, due to the global warming and draught related to it, there is an increase in the number of forest fires. Forest fire detection is mainly done by people but there exists some automated systems in this field too. Besides the detection of the forest fires, effective fire extinhguising has an important role in fire fighting. If the spread of the fire can be predicted from the starting, early intervene can be achieved and fire can be extinguished swiftly. Using the Fire Propagation Simulator explained here it is aimed, to predict the fire development beforehand and to visulalize this predictions on a 3D-GIS environment. ©2008 IEEE.
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    Cyclic scheduling of a 2-machine robotic cell with tooling constraints
    (Elsevier, 2006) Gultekin, H.; Akturk, M. S.; Karasan, O. E.
    In this study, we deal with the robotic cell scheduling problem with two machines and identical parts. In an ideal FMS, CNC machines are capable of performing all the required operations as long as the required tools are stored in their tool magazines. However, this assumption may be unrealistic at times since the tool magazines have limited capacity and in many practical instances the required number of tools exceeds this capacity. In this respect, our study assumes that some operations can only be processed on the first machine while some others can only be processed on the second machine due to tooling constraints. Remaining operations can be processed on either machine. The problem is to find the allocation of the remaining operations to the machines and the optimal robot move cycle that jointly minimize the cycle time. We prove that the optimal solution is either a 1-unit or a 2-unit robot move cycle and we present the regions of optimality. Finally, a sensitivity analysis on the results is conducted.
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    Tissue object patterns for segmentation in histopathological images
    (ACM, 2011) Gündüz-Demir, Çiğdem
    In the current practice of medicine, histopathological examination is the gold standard for routine clinical diagnosis and grading of cancer. However, as this examination involves the visual analysis of biopsies, it is subject to a considerable amount of observer variability. In order to decrease the variability, it has been proposed to develop systems that mathematically model the histopathological tissue images and automate the analysis. Segmentation constitutes the first step for most of these automated systems. Nevertheless, the segmentation in histopathological images remains a challenging task since these images typically show variances due to their complex nature and may include a large amount of noise and artifacts due to the tissue preparation procedures. In our research group, we recently developed different segmentation algorithms that rely on representing a tissue image with a set of tissue objects and using the structural pattern of these objects in segmentation. In this paper, we review these segmentation algorithms, discussing their clinical demonstrations on colon tissues. © 2011 ACM.

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