Pretty maps: evaluating GIS adoption of cartographic design standards and best practices in professional publications

The nature of GIS maps, as tools designed for visual communication, puts them in the realm of art that is in many ways unique among scientific tools. As a visual form of communication, maps are responsive to methods of visual design, affecting the map’s appeal and function. Through cartography, a well established body of standards and best-practices exists to help GIS users avoid common design errors and create effective and meaningful maps that support their work. This research examines the adoption rate of those standards amongst professionals using GIS software for creating maps for journal publications. A selection of 80 GIS-produced maps from the AAG’s Professional Geographer were examined and compared to a uniform set of cartographic standards to look for trends in the adoption rates of map design standards amongst GIS map makers. Maps were rated by the author on their use of cartographic standards based on map content and purpose as opposed to their aesthetic quality. The data show trends in GIS cartographic design use that closely follow the inclusion of default values in common GIS software. The implication is that GIS professionals making maps are typically not applying cartographic standards on their own, but mostly following the standards set up in their software of choice. This suggests that there is still significant work to be done in teaching the value of cartographic principles to GIS students and practitioners

Feasibility study of an Integrated Program for Aerospace-vehicle Design (IPAD) system. Volume 2: Characterization of the IPAD system, phase 1, task 1

The aircraft design process is discussed along with the degree of participation of the various engineering disciplines considered in this feasibility study

FraudDroid: Automated Ad Fraud Detection for Android Apps

Although mobile ad frauds have been widespread, state-of-the-art approaches in the literature have mainly focused on detecting the so-called static placement frauds, where only a single UI state is involved and can be identified based on static information such as the size or location of ad views. Other types of fraud exist that involve multiple UI states and are performed dynamically while users interact with the app. Such dynamic interaction frauds, although now widely spread in apps, have not yet been explored nor addressed in the literature. In this work, we investigate a wide range of mobile ad frauds to provide a comprehensive taxonomy to the research community. We then propose, FraudDroid, a novel hybrid approach to detect ad frauds in mobile Android apps. FraudDroid analyses apps dynamically to build UI state transition graphs and collects their associated runtime network traffics, which are then leveraged to check against a set of heuristic-based rules for identifying ad fraudulent behaviours. We show empirically that FraudDroid detects ad frauds with a high precision (93%) and recall (92%). Experimental results further show that FraudDroid is capable of detecting ad frauds across the spectrum of fraud types. By analysing 12,000 ad-supported Android apps, FraudDroid identified 335 cases of fraud associated with 20 ad networks that are further confirmed to be true positive results and are shared with our fellow researchers to promote advanced ad fraud detectionComment: 12 pages, 10 figure

Visualisation of the information resources for cell biology

Intelligent multimodal interfaces can facilitate scientists in utilising available information resources. Combining scientific visualisations with interactive and intelligent tools can help create a “habitable” information space. Development of such tools remains largely iterative. We discuss an ongoing implementation of intelligent interactive visualisation of information resources in cell biology

Learning to Generate Posters of Scientific Papers

Researchers often summarize their work in the form of posters. Posters provide a coherent and efficient way to convey core ideas from scientific papers. Generating a good scientific poster, however, is a complex and time consuming cognitive task, since such posters need to be readable, informative, and visually aesthetic. In this paper, for the first time, we study the challenging problem of learning to generate posters from scientific papers. To this end, a data-driven framework, that utilizes graphical models, is proposed. Specifically, given content to display, the key elements of a good poster, including panel layout and attributes of each panel, are learned and inferred from data. Then, given inferred layout and attributes, composition of graphical elements within each panel is synthesized. To learn and validate our model, we collect and make public a Poster-Paper dataset, which consists of scientific papers and corresponding posters with exhaustively labelled panels and attributes. Qualitative and quantitative results indicate the effectiveness of our approach.Comment: in Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 201

Leveraging Citation Networks to Visualize Scholarly Influence Over Time

Assessing the influence of a scholar's work is an important task for funding organizations, academic departments, and researchers. Common methods, such as measures of citation counts, can ignore much of the nuance and multidimensionality of scholarly influence. We present an approach for generating dynamic visualizations of scholars' careers. This approach uses an animated node-link diagram showing the citation network accumulated around the researcher over the course of the career in concert with key indicators, highlighting influence both within and across fields. We developed our design in collaboration with one funding organization---the Pew Biomedical Scholars program---but the methods are generalizable to visualizations of scholarly influence. We applied the design method to the Microsoft Academic Graph, which includes more than 120 million publications. We validate our abstractions throughout the process through collaboration with the Pew Biomedical Scholars program officers and summative evaluations with their scholars