85,965 research outputs found
Business Process Management Education in Academia: Status, challenges, and Recommendations
In response to the growing proliferation of Business Process Management (BPM) in industry and the demand this creates for BPM expertise, universities across the globe are at various stages of incorporating knowledge and skills in their teaching offerings. However, there are still only a handful of institutions that offer specialized education in BPM in a systematic and in-depth manner. This article is based on a global educatorsā panel discussion held at the 2009 European Conference on Information Systems in Verona, Italy. The article presents the BPM programs of five universities from Australia, Europe, Africa, and North America, describing the BPM content covered, program and course structures, and challenges and lessons learned. The article also provides a comparative content analysis of BPM education programs illustrating a heterogeneous view of BPM. The examples presented demonstrate how different courses and programs can be developed to meet the educational goals of a university department, program, or school. This article contributes insights on how best to continuously sustain and reshape BPM education to ensure it remains dynamic, responsive, and sustainable in light of the evolving and ever-changing marketplace demands for BPM expertise
Teaching Data Science
We describe an introductory data science course, entitled Introduction to
Data Science, offered at the University of Illinois at Urbana-Champaign. The
course introduced general programming concepts by using the Python programming
language with an emphasis on data preparation, processing, and presentation.
The course had no prerequisites, and students were not expected to have any
programming experience. This introductory course was designed to cover a wide
range of topics, from the nature of data, to storage, to visualization, to
probability and statistical analysis, to cloud and high performance computing,
without becoming overly focused on any one subject. We conclude this article
with a discussion of lessons learned and our plans to develop new data science
courses.Comment: 10 pages, 4 figures, International Conference on Computational
Science (ICCS 2016
GPU cards as a low cost solution for efficient and fast classification of high dimensional gene expression datasets
The days when bioinformatics tools will be so reliable to become a standard aid in routine clinical diagnostics are getting very close. However, it is important to remember that the more complex and advanced bioinformatics tools become, the more performances are required by the computing platforms. Unfortunately, the cost of High Performance Computing (HPC) platforms is still prohibitive for both public and private medical practices. Therefore, to promote and facilitate the use of bioinformatics tools it is important to identify low-cost parallel computing solutions. This paper presents a successful experience in using the parallel processing capabilities of Graphical Processing Units (GPU) to speed up classification of gene expression profiles. Results show that using open source CUDA programming libraries allows to obtain a significant increase in performances and therefore to shorten the gap between advanced bioinformatics tools and real medical practic
Energy-efficient through-life smart design, manufacturing and operation of ships in an industry 4.0 environment
Energy efficiency is an important factor in the marine industry to help reduce manufacturing and operational costs as well as the impact on the environment. In the face of global competition and cost-effectiveness, ship builders and operators today require a major overhaul in the entire ship design, manufacturing and operation process to achieve these goals. This paper highlights smart design, manufacturing and operation as the way forward in an industry 4.0 (i4) era from designing for better energy efficiency to more intelligent ships and smart operation through-life. The paper (i) draws parallels between ship design, manufacturing and operation processes, (ii) identifies key challenges facing such a temporal (lifecycle) as opposed to spatial (mass) products, (iii) proposes a closed-loop ship lifecycle framework and (iv) outlines potential future directions in smart design, manufacturing and operation of ships in an industry 4.0 value chain so as to achieve more energy-efficient vessels. Through computational intelligence and cyber-physical integration, we envision that industry 4.0 can revolutionise ship design, manufacturing and operations in a smart product through-life process in the near future
Route Planning in Transportation Networks
We survey recent advances in algorithms for route planning in transportation
networks. For road networks, we show that one can compute driving directions in
milliseconds or less even at continental scale. A variety of techniques provide
different trade-offs between preprocessing effort, space requirements, and
query time. Some algorithms can answer queries in a fraction of a microsecond,
while others can deal efficiently with real-time traffic. Journey planning on
public transportation systems, although conceptually similar, is a
significantly harder problem due to its inherent time-dependent and
multicriteria nature. Although exact algorithms are fast enough for interactive
queries on metropolitan transit systems, dealing with continent-sized instances
requires simplifications or heavy preprocessing. The multimodal route planning
problem, which seeks journeys combining schedule-based transportation (buses,
trains) with unrestricted modes (walking, driving), is even harder, relying on
approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4,
previously published by Microsoft Research. This work was mostly done while
the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at
Microsoft Research Silicon Valle
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