Robust Controller Design of Networked Control Systems with Nonlinear Uncertainties

We address robust stabilization problem for networked control systems with nonlinear uncertainties and packet losses by modelling such systems as a class of uncertain switched systems. Based on theories on switched Lyapunov functions, we derive the robustly stabilizing conditions for state feedback stabilization and design packet-loss dependent controllers by solving some matrix inequalities. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design method.

Raman spectroscopic study of the mixed anion mineral Yecoraite Bi5Fe3O9(Te4+O3)(Te6+O4)2•9H2O

Tellurates are rare minerals as the tellurate anion is readily reduced to the tellurite ion. Often minerals with both tellurate and tellurite anions in the mineral are found. An example of such a mineral containing tellurate and tellurite is yecoraite. Raman spectroscopy has been used to study this mineral, the exact structure of which is unknown. Two Raman bands at 796 and 808 cm-1 are assigned to the ν1 (TeO4)2- symmetric and ν3 (TeO3)2- antisymmetric stretching modes and Raman bands at 699 cm-1 are attributed to the the ν3 (TeO4)2- antisymmetric stretching mode and the band at 690 cm-1 to the ν1 (TeO3)2- symmetric stretching mode. The intense band at 465 cm-1 with a shoulder at 470 cm-1 is assigned the (TeO4)2- and (TeO3)2- bending modes. Prominent Raman bands are observed at 2878, 2936, 3180 and 3400 cm-1. The band at 3936 cm-1 appears quite distinct and the observation of multiple bands indicates the water molecules in the yecoraite structure are not equivalent. The values for the OH stretching vibrations listed provide hydrogen bond distances of 2.625 Å (2878 cm-1), 2.636 Å (2936 cm-1), 2.697 Å (3180 cm-1) and 2.798 Å (3400 cm-1). This range of hydrogen bonding contributes to the stability of the mineral. A comparison of the Raman spectra of yecoraite with that of tellurate containing minerals kuranakhite, tlapallite and xocomecatlite is made.

Losing their marbles : syntax-free programming for assessing problem-solving skills

Novice programmers have difficulty developing an algorithmic solution while simultaneously obeying the syntactic constraints of the target programming language. To see how students fare in algorithmic problem solving when not burdened by syntax, we conducted an experiment in which a large class of beginning programmers were required to write a solution to a computational problem in structured English, as if instructing a child, without reference to program code at all. The students produced an unexpectedly wide range of correct, and attempted, solutions, some of which had not occurred to their teachers. We also found that many common programming errors were evident in the natural language algorithms, including failure to ensure loop termination, hardwiring of solutions, failure to properly initialise the computation, and use of unnecessary temporary variables, suggesting that these mistakes are caused by inexperience at thinking algorithmically, rather than difficulties in expressing solutions as program code.

Further evidence of a relationship between explaining, tracing and writing skills in introductory programming

This paper reports on a replication of earlier studies into a possible hierarchy of programming skills. In this study, the students from whom data was collected were at a university that had not provided data for earlier studies. Also, the students were taught the programming language Python, which had not been used in earlier studies. Thus this study serves as a test of whether the findings in the earlier studies were specific to certain institutions, student cohorts, and programming languages. Also, we used a non–parametric approach to the analysis, rather than the linear approach of earlier studies. Our results are consistent with the earlier studies. We found that students who cannot trace code usually cannot explain code, and also that students who tend to perform reasonably well at code writing tasks have also usually acquired the ability to both trace code and explain code.

Seeing is understanding : the effect of visualisation in understanding programming concepts

How and why visualisations support learning was the subject of this qualitative instrumental collective case study. Five computer programming languages (PHP, Visual Basic, Alice, GameMaker, and RoboLab) supporting differing degrees of visualisation were used as cases to explore the effectiveness of software visualisation to develop fundamental computer programming concepts (sequence, iteration, selection, and modularity). Cognitive theories of visual and auditory processing, cognitive load, and mental models provided a framework in which student cognitive development was tracked and measured by thirty-one 15-17 year old students drawn from a Queensland metropolitan secondary private girls’ school, as active participants in the research. Seventeen findings in three sections increase our understanding of the effects of visualisation on the learning process. The study extended the use of mental model theory to track the learning process, and demonstrated application of student research based metacognitive analysis on individual and peer cognitive development as a means to support research and as an approach to teaching. The findings also forward an explanation for failures in previous software visualisation studies, in particular the study has demonstrated that for the cases examined, where complex concepts are being developed, the mixing of auditory (or text) and visual elements can result in excessive cognitive load and impede learning. This finding provides a framework for selecting the most appropriate instructional programming language based on the cognitive complexity of the concepts under study.

Nonlinear pedagogy : implications for teaching games for understanding (TGfU)

Nonlinear Dynamics, provides a framework for understanding how teaching and learning processes function in Teaching Games for Understanding (TGfU). In Nonlinear Pedagogy, emergent movement behaviors in learners arise as a consequence of intrinsic self-adjusted processes shaped by interacting constraints in the learning environment. In a TGfU setting, representative, conditioned games provide ideal opportunities for pedagogists to manipulate key constraints so that self-adjusted processes by players lead to emergent behaviors as they explore functional movement solutions. The implication is that, during skill learning, functional movement variability is necessary as players explore different motor patterns for effective skill execution in the context of the game. Learning progressions in TGfU take into account learners’ development through learning stages and have important implications for organisation of practices, instructions and feedback. A practical application of Nonlinear Pedagogy in a national sports institute is shared to exemplify its relevance for TGfU practitioners.