Bond graph formulation of an optimal control problem for linear time invariant systems

A recent communication has proposed a conjectural procedure for representing a category of optimal control problems in bond graph language [W. Marquis-Favre, B. Chereji, D. Thomasset, S. Scavarda, Bond graph representation of an optimal control problem: the dc motor example, in: ICBGM’05 International Conference of Bond Graph Modelling and Simulation, New Orleans, USA, January 23-27, 2005, pp. 239-244]. This paper aims at providing a fundamental theory for proving the effectiveness of this procedure. The class of problem that the procedure can deal with has been extended. Its application was formerly restricted to linear time invariant siso system. The systems considered now are linear time invariant mimo systems. The optimization objective is the minimization of dissipation and input. The developments concerning the optimal control problem are based on the Pontryagin maximum principle and the proof of the effectiveness of the procedure makes a broad use of the port-Hamiltonian concept. As a result, the bond graph representation of the given optimization problem enables the analytical system, which provides the optimal solution, to be derived. The work presented in this paper is the first step in research with perspectives towards formulating dynamic optimization problems in bond graph and, towards coupling this formulation with a sizing methodology using bond graph language and a state-space inverse model approach. This sizing methodology, however, is not the topic of this paper and thus is not presented here.     

Implementing crowdsourcing-based relevance experimentation: an industrial perspective

Crowdsourcing has emerged as a viable platform for conducting different types of relevance evaluation. The main reason behind this trend is that it makes possible to conduct experiments extremely fast, with good results at a low cost. However, like in any experiment, there are several implementation details that would make an experiment work or fail. To gather useful results, clear instructions, user interface guidelines, content quality, inter-rater agreement metrics, work quality, and worker feedback are important characteristics of a successful crowdsourcing experiment. Furthermore, designing and implementing experiments that require thousands or millions of labels is different than conducting small scale research investigations. In this paper we outline a framework for conducting continuous crowdsourcing experiments, emphasizing aspects that should be of importance for all sorts of tasks. We illustrate the value of characteristics that can impact the overall outcome using examples based on TREC, INEX, and Wikipedia data sets.     

Students’ assessment of interactive distance experimentation in nuclear reactor physics laboratory education

Laboratory experiments develop students’ skills in dealing with laboratory instruments and physical processes with the objective of reinforcing the understanding of the investigated subject. In nuclear engineering, where research reactors play a vital role in the practical education of students, the high cost and long construction time of research reactors limit their accessibility to few educational programmes around the world. The concept of the Internet Reactor Laboratory (IRL) was introduced earlier as a new approach that utilises distance education in nuclear reactor physics laboratory education. This paper presents an initial assessment of the implementation of the IRL between the PULSTAR research reactor at North Carolina State University in the USA and the Department of Nuclear Engineering at Jordan University of Science and Technology (JUST) in Jordan. The IRL was implemented in teaching the Nuclear Reactor laboratory course for two semesters. Feedback from surveyed students verifies that the outcomes attained from using IRL in experimentation are comparable to that attainable from other on-campus laboratories performed by the students.     

Using crowdsourcing for TREC relevance assessment

Crowdsourcing has recently gained a lot of attention as a tool for conducting different kinds of relevance evaluations. At a very high level, crowdsourcing describes outsourcing of tasks to a large group of people instead of assigning such tasks to an in-house employee. This crowdsourcing approach makes possible to conduct information retrieval experiments extremely fast, with good results at a low cost.