What Others Say About This Work? Scalable Extraction of Citation Contexts from Research Papers

This work presents a new, scalable solution to the problem of extracting citation contexts: the textual fragments surrounding citation references. These citation contexts can be used to navigate digital libraries of research papers to help users in deciding what to read. We have developed a prototype system which can retrieve, on-demand, citation contexts from the full text of over 15 million research articles in the Mendeley catalog for a given reference research paper. The evaluation results show that our citation extraction system provides additional functionality over existing tools, has two orders of magnitude faster runtime performance, while providing a 9% improvement in F-measure over the current state-of-the-art

Exploring challenging variations of parsons problems

Introductory programming classes teach students to program using worked examples, code tracing, and code writing exercises. Parsons Problems are an educational innovation in which students unscramble provided lines of code, as a step towards bridging the gap between reading and writing code. Though Parsons Problems have been found effective, there is some evidence that students can use syntactic heuristics to help them solve these problems without fully understanding the solution. To address this limitation, we introduce Faded Parsons Problems, a variation of Parsons Problems where parts of the provided code are incomplete. We explore a specific instantiation of this idea, Blank-Variable Parsons Problems, in which all variable names are blanked out. Unlike another Parsons Problem variation-adding distractor code lines-Blank-Variable Parsons can be automatically created from a solution without additional effort from an instructor. A 75 minute pilot study with CS1 students indicates that solving standard Parsons Problems does not lead to short-term near-transfer in code writing, suggesting a need for problems with less scaffolding. Additionally, students self-report Blank-Variable Parsons as fitting in difficulty between Parsons Problems and code writing, suggesting Blank-Variable Parsons may be one opportunity to fill this gap

Multi Visualization and Dynamic Query for Effective Exploration of Semantic Data

Semantic formalisms represent content in a uniform way according to ontologies. This enables manipulation and reasoning via automated means (e.g. Semantic Web services), but limits the user’s ability to explore the semantic data from a point of view that originates from knowledge representation motivations. We show how, for user consumption, a visualization of semantic data according to some easily graspable dimensions (e.g. space and time) provides effective sense-making of data. In this paper, we look holistically at the interaction between users and semantic data, and propose multiple visualization strategies and dynamic filters to support the exploration of semantic-rich data. We discuss a user evaluation and how interaction challenges could be overcome to create an effective user-centred framework for the visualization and manipulation of semantic data. The approach has been implemented and evaluated on a real company archive

A Review of Object Detection Models based on Convolutional Neural Network

Convolutional Neural Network (CNN) has become the state-of-the-art for object detection in image task. In this chapter, we have explained different state-of-the-art CNN based object detection models. We have made this review with categorization those detection models according to two different approaches: two-stage approach and one-stage approach. Through this chapter, it has shown advancements in object detection models from R-CNN to latest RefineDet. It has also discussed the model description and training details of each model. Here, we have also drawn a comparison among those models.Comment: 17 pages, 11 figures, 1 tabl

Supporting Newly Identified or Diagnosed Autistic Adults: An Initial Evaluation of an Autistic-Led Programme

Sixteen adults (diagnosed or self-identified as autistic) participated in one of two iterations of a ten-week autistic-led programme, aimed at helping autistic adults learn more about autism within a peer group context. Motivations for taking part in the programme included a desire for: (1) exploration of autism; (2) empowerment; and (3) the development of practical strategies and coping mechanisms. Interviews were conducted upon completion of the programme and again six months later. Using thematic analysis, three themes were identified: (1) appreciation of the autistic-led nature of the programme; (2) unity in diversity; and (3) developing a positive, practical outlook on autism. These promising initial results highlight the value of autistic-led peer support for those recently diagnosed/identified as autistic

Advance Care Planning in Huntington's Disease

Advance care planning (ACP) is a useful tool that benefits adult patients, care providers, and surrogate decision makers, through providing opportunities for patients to consider, express, and formalize their beliefs, preferences, and wishes pertaining to decisions regarding future medical care at a time when they retain decision-making capacity. Early and timely consideration of ACP discussions is paramount in Huntington's disease (HD) given the potential challenges in ascertaining decision-making capacity in the advanced stages of the disease. ACP helps to empower and extend patient autonomy, providing clinicians and surrogate decision makers with reassurance that management is consistent with a patient's expressed wishes. Regular follow up is vital to establish consistency of decisions and wishes. We outline the framework of the dedicated ACP clinic integrated within our HD service to highlight the importance of a patient-centred and tailored care plan that fulfils the patient's expressed goals, preferences, and values