4 resultados para lean implementation time

em Digital Peer Publishing


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During the past years, Brazil has been mentioned internationally as a one of the so-called BRICs (Brazil, Russia, India and China). These countries have been taking increasing space in the economical and political global scenarios in the XXI century. The facts that they possess a vast territory and stand among the highest populated countries increase their relevance within the United Nations. Besides, three of them constitute nuclear powers and two of them belong to the United Nations Security Council. Brazil has significantly participated in forums such as WTO and UNO, representing central political articulation and stability to Latin America and in the structuring and growth of MERCOSUL (Brazil, Argentina, Uruguay, Paraguay and Venezuela). Once again among the ten greatest economies of the world, the country has launched ambitious poverty-fighting programs helping more than 20 million people in the last years, such as the “Bolsa Família” (Familienstipendium) Program or and its complements). Nevertheless, Latin American countries are far from generating structural funds as the “European Social Fund” to assist specific demands of big cities as Sao Paulo and Buenos Aires. The commitments are restricted to commercial areas and bring nothing but slow and scarce advances to education or infra-structure and to the integration of systems related to these areas.

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Given arbitrary pictures, we explore the possibility of using new techniques from computer vision and artificial intelligence to create customized visual games on-the-fly. This includes coloring books, link-the-dot and spot-the-difference popular games. The feasibility of these systems is discussed and we describe prototype implementation that work well in practice in an automatic or semi-automatic way.

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This article investigates barriers to a wider utilization of a Learning Management System (LMS). The study aims to identify the reasons why some tools in the LMS are rarely used, in spite of assertions that the learning experience and students’ performance can be improved by interaction and collaboration, facilitated by the LMS. Lecturers’ perceptions about the use of LMSs over the last four years at the School of Engineering, University of Borås were investigated. Seventeen lecturers who were interviewed in 2006 were interviewed again in 2011. The lecturers’ still use the LMS primarily for distribution of documents and course administration. The results indicate that their attitudes have not changed significantly. The apparent reluctance to utilize interactive features in the LMS is analyzed, by looking at the expected impact on the lecturers’ work situation. The author argues that the main barrier to a wider utilization of LMS is the lecturers’ fear of additional demands on their time. Hence, if educational institutions want a wider utilization of LMS, some kind of incentives for lecturers are needed, in addition to support and training.

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In recent years, depth cameras have been widely utilized in camera tracking for augmented and mixed reality. Many of the studies focus on the methods that generate the reference model simultaneously with the tracking and allow operation in unprepared environments. However, methods that rely on predefined CAD models have their advantages. In such methods, the measurement errors are not accumulated to the model, they are tolerant to inaccurate initialization, and the tracking is always performed directly in reference model's coordinate system. In this paper, we present a method for tracking a depth camera with existing CAD models and the Iterative Closest Point (ICP) algorithm. In our approach, we render the CAD model using the latest pose estimate and construct a point cloud from the corresponding depth map. We construct another point cloud from currently captured depth frame, and find the incremental change in the camera pose by aligning the point clouds. We utilize a GPGPU-based implementation of the ICP which efficiently uses all the depth data in the process. The method runs in real-time, it is robust for outliers, and it does not require any preprocessing of the CAD models. We evaluated the approach using the Kinect depth sensor, and compared the results to a 2D edge-based method, to a depth-based SLAM method, and to the ground truth. The results show that the approach is more stable compared to the edge-based method and it suffers less from drift compared to the depth-based SLAM.