6 research outputs found

    A Sensor System for Detection of Hull Surface Defects

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    This paper presents a sensor system for detecting defects in ship hull surfaces. The sensor was developed to enable a robotic system to perform grit blasting operations on ship hulls. To achieve this, the proposed sensor system captures images with the help of a camera and processes them in real time using a new defect detection method based on thresholding techniques. What makes this method different is its efficiency in the automatic detection of defects from images recorded in variable lighting conditions. The sensor system was tested under real conditions at a Spanish shipyard, with excellent results

    A Novel Method to Increase LinLog CMOS Sensors’ Performance in High Dynamic Range Scenarios

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    Images from high dynamic range (HDR) scenes must be obtained with minimum loss of information. For this purpose it is necessary to take full advantage of the quantification levels provided by the CCD/CMOS image sensor. LinLog CMOS sensors satisfy the above demand by offering an adjustable response curve that combines linear and logarithmic responses. This paper presents a novel method to quickly adjust the parameters that control the response curve of a LinLog CMOS image sensor. We propose to use an Adaptive Proportional-Integral-Derivative controller to adjust the exposure time of the sensor, together with control algorithms based on the saturation level and the entropy of the images. With this method the sensor’s maximum dynamic range (120 dB) can be used to acquire good quality images from HDR scenes with fast, automatic adaptation to scene conditions. Adaptation to a new scene is rapid, with a sensor response adjustment of less than eight frames when working in real time video mode. At least 67% of the scene entropy can be retained with this method

    Short-Term Resource Allocation and Management

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    Almost all sectors of the economy, such as, government, healthcare, education, ship repair, construction, and manufacturing require project management. A key component of project management deals with scheduling of tasks such that limited resources are utilized in an effective manner. Current research on resource constrained project-scheduling has been classified as: a) Single project with single mode for various tasks, b) Single project with multiple task modes, c) Multiple projects with single task mode, and d) Multiple projects with multiple task modes.;This work extends the current multi-project, multi-mode scheduling techniques. The resources can be renewable, and non-renewable. In addition, it focuses on short term scheduling, that is, scheduling on an hourly, daily, or weekly basis. Long term scheduling assumes a stable system, that is, resources, priorities, and other constraints do no change during the scheduling period. In this research, short term scheduling assumes a dynamic system, that is, resources, priorities, and other constraints change over time.;A hybrid approach is proposed to address the dynamic nature of the problem. It is based on discrete event simulation and a set of empirical rules provided by the project manager. The project manager is assumed to be highly knowledgeable about the project. He/she is regarded as an integral part of the system. Such an approach is better suited to deal with real world scheduling. The proposed approach does not seek to provide a single optimum solution, instead, it generates a series of feasible solutions, along with the impact of each solution on schedule and cost.;Two project case studies dealing with finding an optimum solution were selected from the literature. The proposed technique was applied to the data set in these studies. In both cases the proposed approach found the optimum solution. The model was then applied to two additional problems to test the features that could not be tested on the dataset from the literature.;As for practical implications, the proposed approach enhances the decision making process, by providing more resource allocation flexibility, and results in improved solutions in terms of total project duration and cost. From an academic viewpoint, this research enriches the existing literature, as it provides an extension of the resource constrained project scheduling problems, a discrete event simulation and four cases studies which highlights relevant issues to model properly the complexity of real-life projects
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