Robust self-triggered MPC with fast convergence for constrained linear systems

In this paper, a robust self-triggered model predictive control (MPC) scheme is proposed for linear discrete-time systems subject to additive disturbances, state and control constraints. To reduce the amount of computation on controller sides, MPC optimization problems are only solved at certain sampling instants which are determined by a novel self-triggering mechanism. The main idea of the self-triggering mechanism is to choose inter-sampling times by guaranteeing a fast decrease in optimal costs. It implies a fast convergence of system states to a compact set where it is ultimately bounded and a reduction of computation times to stabilize the system. Once the state enters a terminal region, the system can be stabilized to a robust invariant set by a state feedback controller. Robust constraint satisfaction is ensured by utilizing the worst-case set-valued predictions of future states in such a way that recursive feasibility is guaranteed for all possible realisations of disturbances. In the case where a priority is given to reducing communication costs rather than improvement in control performance in a neighborhood of the origin, a feedback control law based on nominal state predictions is designed in the terminal region to avoid frequent feedback. Performances of the closed-loop system are demonstrated by a simulation example.     

Adaptation and evaluation of a learning analytics dashboard to improve academic support at three Latin American universities

Despite the success of academic advising dashboards in several higher educational institutions (HEI), these dashboards are still under-explored in Latin American HEI's. To close this gap, three different Latin American universities adapted an existing advising dashboard, originally deployed at the KU Leuven to their own context. In all three cases, the context was the main ruling factor to these adaptations. In this paper, we describe these adaptions using a framework that focuses on four different elements of the context: Objectives, Stakeholders, Key moment and Interactions. Evaluation of the adapted dashboards in the three different Latin American universities is conducted through pilots. This evaluation shows the value of the dashboard approach in different contexts in terms of satisfaction, usefulness and impact in academic decision-making and advising tasks. The main contribution of this paper is the systematic reporting of the adaptations to an academic advising dashboard and showing the value of an academic advising dashboard on academic decision-making and advising tasks.     

Cognitive-inspired domain adaptation of sentiment lexicons

Sentiment lexicons are essential tools for polarity classification and opinion mining. In contrast to machine learning methods that only leverage text features or raw text for sentiment analysis, methods that use sentiment lexicons embrace higher interpretability. Although a number of domain-specific sentiment lexicons are made available, it is impractical to build an ex ante lexicon that fully reflects the characteristics of the language usage in endless domains. In this article, we propose a novel approach to simultaneously train a vanilla sentiment classifier and adapt word polarities to the target domain. Specifically, we sequentially track the wrongly predicted sentences and use them as the supervision instead of addressing the gold standard as a whole to emulate the life-long cognitive process of lexicon learning. An exploration-exploitation mechanism is designed to trade off between searching for new sentiment words and updating the polarity score of one word. Experimental results on several popular datasets show that our approach significantly improves the sentiment classification performance for a variety of domains by means of improving the quality of sentiment lexicons. Case-studies also illustrate how polarity scores of the same words are discovered for different domains.     

Analytical attractions and the techno-continuum: Conceptualising data obsessions and consequences in elite sport

The proliferation of sports science and technological innovation within performance settings has precipitated the generation of increasing volumes of data to aid athletes. Copious data production has also perpetuated the privileging of scientific information, and a ‘thirst’ for ‘more data’ as an unproblematic ‘truth’. Of significance is not merely the use of technology for the production of data-for-data's sake, or the utility of data for a greater cause (e.g. the good of the team), but the quest for personalised data for individual athletes to be analysed, and reflected upon ad nauseam. Furthering scholarship on disciplining bodies, we argue that increased technological consumption, and the related excessive quantification of athletes’ bodies via data production, adds further insecurity into performance sports work. Finally, attention is given to the cultural step-change new techno-dispositions may now present.     

论教学活动中教师心理状态的自我调节特点

本文探讨的是高情绪化和低情绪化教师心理自我调节的特点问题.通过抽样调查和分析获得了具有不同程度情绪化的教师心理自我调节风格特征的准确差异.     

On the Complexity of the Reduction of Multidimensional Data Models

In this paper, decomposition methods for multidimensional data hypercubes of OLAP systems are investigated. Criteria for reducing the computational complexity of the decomposition methods are presented and comparisons are made with the traditional solutions of multidimensional data analysis problems. Examples illustrating the application of these criteria to investigating the dynamics of computational complexity changes for specific types of reduction problems are considered.     

Prospective Elementary Mathematics Specialists’ developing instructional practices: support and mentorship during an authentic residency

Journal of Mathematics Teacher Education - This case study explored Prospective Elementary Mathematics Specialists’ (PEMSs) pedagogical practices during a K-5 Mathematics Endorsement (K-5 ME)...     

The videoconferencing learning environment: Technology, interaction and learning intersect

This paper is a study on the interaction patterns of distance learners enrolled in the Mathematics and Physics programmes of Universiti Sains Malaysia in the videoconferencing learning environment (VCLE). Interaction patterns are analysed in six randomly chosen videoconferencing sessions within one academic year. The findings show there are more interactions in the graphics display mode than the video display mode. The graphics display mode, which involves the simultaneous interaction of the teacher, students and course materials, shows greater student engagement in the VCLE. The focus on a three-component interaction in distance learning differs from previous studies which looked at distinct types of two-component interactions. The types of communicative interaction, in particular the explanatory and cognitive types which are dominant in the graphics display mode, are discussed within the construct of learning. The higher number of teacher-initiated interactions may also imply that the teacher plays a crucial role in creating and maintaining a community of inquiry focused on exploring and developing content as well as giving feedback on concepts, ideas or solutions.     

Modelling impact of dredging and dumping in ebb-flood channel systems

For a channel-shoal system in a funnel-shaped basin the impact of dredging and dumping is investigated using a complex process-based model. First, the residual flow and sediment transport circulations are analysed for the channel-shoal pattern, which has emerged after a long-term model simulation. Results are compared to the Western Scheldt estuary, which forms the inspiration for this study. Subsequently, different dredge and dump scenarios are modelled, according to a conceptual model, in which ebb-and flood-channels and enclosed shoals form morphodynamic units (cells) with their own sediment circulation. Model results show that dumping sediment in a channel further reduces the channel depth and induces erosion in the opposite channel, which enhances tilting of the cross-section of the cell and eventually can lead to the degeneration of a multiple channel system into a single channel. The impact of different dredging and dumping cases agrees with results from a stability analysis. This means that this type of model applied to a realistic geometry can potentially be used for better prediction of the impact of human interventions.