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Engineering honours program

In September 2009 the department of Engineering of Fontys University of Applied Sciences in the Netherlands has started a pilot honours program for excellent engineering students called PRogram OUstanding Development (PROUD). Aim of this program is to give those engineering students, who have the ambition, the opportunity to work on extra profession related challenges in their study. By means of this PROUD program Fontys University of Applied Sciences is responding to the wishes of students for extra curricular activities and increasing need from the industry for excellent professionals with an extra level of theoretical knowledge and practical experience. In this paper the courses offered at the Engineering department of the Fontys University of Applied Sciences are discussed. Different study possibilities/routings for students were developed depending on earlier acquainted competences, adaptation abilities to our system (special possibilities for slow starters) and tracking and tracing by intensive study coaching. This resulted in an improvement of the yield of students to 74% of students started in 2008. After working successfully on reducing the drop out rate of our engineering students the department focused on possibilities for excellent students. The department started the PROUD pilot together with engaged engineering students. In 2008 engineering students have carried out a research among their fellow students, lecturers, other institutes [1] and industry. This resulted in a quite different approach of an honours program for the department of Electronic and Electrical Engineering. In the PROUD program the student is stimulated to personally shape his educational career and to explicitly work on developing his own competences. The PROUD excellent program starts after the first year and extends to at least 3 semesters in the following years. The student, guided by a supervisor and outside the regular study time, is working on building an excellent portfolio at the university as well as in industry. During this period the PROUD student will work in industry one day a week in average. This is on top of his bachelor educational program. The students will receive an excellent honours certificate together with their bachelor's degree at the end of the study to express their honourable work. Each year about 20 students apply for a place in PROUD but thus far only about 3-4 passed the first interview round. It turns out that student, university and industry are eager to participate in this PROUD program.

Establishing Typologies for Diverging Career Paths through the Life Course: A Comparison of two Methods

Discussions on policy and management initiatives to facilitate individuals throughout working careers take place without sufficient insight into how career paths are changing, how these changes are related to a modernization of life course biographies, and whether this leads to increased labour market transitions. This paper asks how new, flexible labour market patterns can best be analyzed using an empirical, quantitative approach. The data used are from the career module of the Panel Study of Belgian Households (PSBH). This module, completed by almost 4500 respondents consists of retrospective questions tracing lengthy and even entire working life histories. To establish any changes in career patterns over such extended periods of time, we compare two evolving methodologies: Optimal Matching Analysis (OMA) and Latent Class Regression Analysis (LCA). The analyses demonstrate that both methods show promising potential in discerning working life typologies and analyzing sequence trajectories. However, particularities of the methods demonstrate that not all research questions are suitable for each method. The OMA methodology is appropriate when the analysis concentrates on the labour market statuses and is well equipped to make clear and interpretable differentiations if there is relative stability in career paths during the period of observation but not if careers become less stable. Latent Class has the strength of adopting covariates in the clustering allowing for more historically connected types than the other methodology. The clustering is denser and the technique allows for more detailed model fitting controls than OMA. However, when incorporating covariates in a typology, the possibilities of using the typology in later, causal, analyses is somewhat reduced.

The Path To Entrepreneurship: Searching And Learning From Role Models

In this study, we address the function of role models for entrepreneurship students. By using entrepreneurs as role models, students can get a better and realistic picture of the complexity of the entrepreneurial path. Choosing whom to interview as role model can be diverse, but it can be problematic if, as a result of that choice, the learning effect in the same group of students is different.

The Brigade Renderer: A path tracer for real-time games

We present the Brigade renderer: an efficient system that uses the path tracing algorithm to produce images for real-time games. We describe the architecture of the Brigade renderer, and provide implementation details. We describe two games that have been created using Brigade.

Primary sample space path guiding.

Improving data locality for efficient in-core path tracing

In this paper, we investigate the efficiency of ray queries on the CPU in the context of path tracing, where ray distributions are mostly random. We show that existing schemes that exploit data locality to improve ray tracing efficiency fail to do so beyond the first diffuse bounce, and analyze the cause for this. We then present an alternative scheme inspired by the work of Pharr et al. in which we improve data locality by using a data-centric breadth-first approach. We show that our scheme improves on state-of-the-art performance for ray distributions in a path tracer.