Abstract
A traffic tensor or simply origin x destination x time is a new data model for conventional origin/destination (O/D) matrices. Tensor models are traffic data analysis techniques which use this new data model to improve performance. Tensors outperform other models because both temporal and spatial fluctuations of traffic patterns are simultaneously taken into account, obtaining results that follow a more natural pattern. Three major types of fluctuations can occur in traffic tensors: mutations to the overall traffic flows, alterations to the network topology and chaotic behaviors. How can we detect events in a system that is faced with all types of fluctuations during its life cycle? Our initial studies reveal that the current design of tensor models face some difficulties in dealing with such a realistic scenario. We propose a new hybrid tensor model called HTM that enhances the detection ability of tensor models by using a parallel tracking technique on the traffic's topology. However, tensor decomposition techniques such as Tucker, a key step for tensor models, require a complicated parameter that not only is difficult to choose but also affects the model's quality. We address this problem examining a recent technique called adjustable core size Tucker decomposition (ACS-Tucker). Experiments on simulated and real-world data sets from different domains versus several techniques indicate that the proposed model is effective and robust, therefore it constitutes a viable alternative for analysis of the traffic tensors.

Abstract
This paper presents the evolution of the process for management of surgery waiting lists in the Portuguese public hospital network. We use the perspective of the software development and deployment by UTAD, as a partner of the Ministry of Health, to create an information system to manage list recovery programs. We describe the early status and work, when data harvesting was the core challenge, up to the current automated situation. This paper bridges the PERLE, PPMA, PECLEC and SIGIC programmes, and concludes with lessons learned and suggestions for evolution of the process.

Abstract
Motion is a fundamental cue for scene analysis and human activity understanding in videos. It can be encoded in trajectories for tracking objects and for action recognition, or in form of flow to address behavior analysis in crowded scenes. Each approach can only be applied on limited scenarios. We propose a motion-based system that represents the spatial and temporal features of the flow in terms of I ong-range trajectories. The novelty resides on the system formulation, its generic approach to handle scene variability and motion variations, motion integration from local and global representations, and the resulting long-range trajectories that overcome trajectory-based approach problems. We report the results and conclusions that state its pertinence on different scenarios, comparing and correlating the extracted trajectories of individual pedestrians, manually annotated. We also propose an evaluation framework and stress the diverse system characteristics that can be used for human activity tasks, namely on motion segmentation.

Abstract
This paper investigates the impact of projection design on the reconstruction of high-dimensional signals from low-dimensional measurements in the presence of side information. In particular, we assume that both the signal of interest and the side information are described by a joint Gaussian mixture model (GMM) distribution. Sharp necessary and sufficient conditions on the number of measurements needed to guarantee that the average reconstruction error approaches zero in the low-noise regime are derived, for both cases when the side information is available at the decoder or at the decoder and encoder. Numerical results are also presented to showcase the impact of projection design on applications with real imaging data in the presence of side information. © 2016 IEEE.

Abstract

Abstract
Computer programming courses in higher education tend to have high rates of academic failure and students struggle, particularly so in the transition from entry-level programming to advanced programming. Some of the reasons given in the literature relate to the type of teaching approach and the strategies used by students and their attitudes towards computer programming. The literature also mentions that educational approaches are not always appropriate to the needs of students and to the development of skills required in the job market. We developed a teaching approach to try to address some of these issues and support students learning computer programming in the transition from entry-level to advanced computer programming: the SimProgramming approach. This approach was introduced at the University of Tros-os-Montes e Alto Douro (Portugal), within the scope of the course " Programming Methodologies III", part of the second curricular year of the programmes of studies in Informatics Engineering and in Information & Communication Technologies. We present in detail the origins of the SimProgramming approach, starting from the first trials that introduced, in two iterations, learning activities based on problem-based learning, and up to the third iteration where the current SimProgramming approach was implemented. We describe the reasoning, design and implementation of these three iterations, to show how the approach evolved. The SimProgramming approach is based in four conceptual foundations: business-like learning environment, self-regulated learning, co-regulated learning and formative assessment. For each of these conceptual foundations, we explain the teaching strategies adopted. In SimProgramming, the learning activity process develops in four phases, and students have specific tasks in each phase. We analyse interview data regarding student perceptions about the SimProgramming approach, and registration grids data on team work dynamics and final assessment of the assignment, noting the impact of SimProgramming in student grades. The application of SimProgramming revealed promising evidences in the overall results of student learning in the activities proposed in this approach. The average grades improved, and did the number of students regularly submitting their tasks on schedule. The perceptions of students regarding the SimProgramming approach are very positive: they recommend using it in the following years, and provided some suggestions to improve the approach. We conclude with reflections and recommendations for subsequent development of the SimProgramming approach in its application to the teaching of computer programming and potential for using it in other educational contexts.