Flexible constrained sampling with guarantees for pattern mining

Pattern sampling has been proposed as a potential solution to the infamous pattern explosion. Instead of enumerating all patterns that satisfy the constraints, individual patterns are sampled proportional to a given quality measure. Several sampling algorithms have been proposed, but each of them has its limitations when it comes to 1) flexibility in terms of quality measures and constraints that can be used, and/or 2) guarantees with respect to sampling accuracy. We therefore present Flexics, the first flexible pattern sampler that supports a broad class of quality measures and constraints, while providing strong guarantees regarding sampling accuracy. To achieve this, we leverage the perspective on pattern mining as a constraint satisfaction problem and build upon the latest advances in sampling solutions in SAT as well as existing pattern mining algorithms. Furthermore, the proposed algorithm is applicable to a variety of pattern languages, which allows us to introduce and tackle the novel task of sampling sets of patterns. We introduce and empirically evaluate two variants of Flexics: 1) a generic variant that addresses the well-known itemset sampling task and the novel pattern set sampling task as well as a wide range of expressive constraints within these tasks, and 2) a specialized variant that exploits existing frequent itemset techniques to achieve substantial speed-ups. Experiments show that Flexics is both accurate and efficient, making it a useful tool for pattern-based data exploration.Comment: Accepted for publication in Data Mining & Knowledge Discovery journal (ECML/PKDD 2017 journal track

Video conferencing: an effective solution to long distance student placement support?

Background Within many health related degree programmes, students receive support during placements via visiting tutors. Literature discusses the importance of this support but economic and environmental arguments indicate a need for alternatives to supporting a student in situ. This project investigated the logistics of and perceptions towards using video conferencing as a means of providing this support. Methods A pilot project was undertaken in which an in situ, support meeting was replaced with a meeting via video link. All participants completed evaluative questionnaires and students attended a follow up focus group in order to explore responses in more depth. Results and discussion Use of the medium identified key logistical hurdles in implementing technology into existing support systems. All participants expressed enthusiasm for the medium with educators expressing a preference. Students identified concerns over the use of this medium for failing placements but could not identify why. As a result of evaluation, this project has raised a number of questions relating to the fitness for purpose of video conferencing in this context. Conclusion Future research aims to respond to the questions raised in evaluating the value and purpose of placement support and the nature of conversations via the video conferencing medium

Organisational participation and women - an attitude problem?

Employee participation is a dynamic and contested area of organisational behaviour, attracting continuing academic, practitioner and policy interest and debate. This chapter focuses on organisational participation and women

Visual Analytics and Interactive Machine Learning for Human Brain Data

Indiana University-Purdue University Indianapolis (IUPUI)This study mainly focuses on applying visualization techniques on human brain data for data exploration, quality control, and hypothesis discovery. It mainly consists of two parts: multi-modal data visualization and interactive machine learning. For multi-modal data visualization, a major challenge is how to integrate structural, functional and connectivity data to form a comprehensive visual context. We develop a new integrated visualization solution for brain imaging data by combining scientific and information visualization techniques within the context of the same anatomic structure. For interactive machine learning, we propose a new visual analytics approach to interactive machine learning. In this approach, multi-dimensional data visualization techniques are employed to facilitate user interactions with the machine learning process. This allows dynamic user feedback in different forms, such as data selection, data labeling, and data correction, to enhance the efficiency of model building

Zifazah: A Scientific Visualization Language for Tensor Field Visualizations

This thesis presents the design and prototype implementation of a scientific visualization language called Zifazah for composing and exploring 3D visualizations of diffusion tensor magnetic resonance imaging (DT-MRI or DTI) data. Unlike existing tools allowing flexible customization of data visualizations that are programmer-oriented, Zifazah focuses on domain scientists as end users in order to enable them to freely compose visualizations of their scientific data set. Verbal descriptions of end users about how they would build and explore DTI visualizations are analyzed to collect syntax, semantics, and control structures of the language. Zifazah makes use of the initial set of lexical terms and semantical patterns to provide a declarative language in the spirit of intuitive syntax and usage. Along with sample scripts representative of the main language design features, some new DTI visualizations created by end users using the novel language have also been presented

Searching Low and High What Types of Firms use Universities as a Source of Innovation?

This paper examines the factors that influence whether firms draw from universities in their innovative activities. The link between the universities and industrial innovation, and the role of different search strategies in influencing the propensity of firms to use universities is explored. The results suggest that firms who adopt “open” search strategies and invest in R&D are more likely than other firms to draw from universities, indicating that managerial choice matters in shaping the propensity of firms to draw from universities.University-industry links, innovation, external search strategies