Design of a web-based LBS framework addressing usability, cost, and implementation constraints

This research investigates barriers that prevent Location Based Services (LBS) from reaching its full potential. The different constraints, including poor usability, lack of positioning support, costs, and integration difficulties are highlighted. A framework was designed incorporating components based on existing and new technologies that could help address the constraints of LBS and increase end-user acceptance. This research proposes that usability constraints can be addressed by adapting a system to user characteristics which are inferred on the basis of captured user context and interaction data. A prototype LBS system was developed to prove the feasibility and benefit of the framework design, demonstrating that constraints of positioning, cost, and integration can be overcome. Volunteers were asked to use the system, and to answer questions in relation to their proficiency and experience. User-feedback showed that the proposed combination of functionality was well-received, and the prototype was appealing to many users. Ground-truths from the survey were related back to data captured with a user monitoring component in order to investigate whether users can be classified according to their context and how they interact. The results have shown that statistically significant relationships exist, and that by using the C4.5 decision-tree, computer proficiency can be estimated within one class-width in 76.7% of the cases. These results suggest that it may be possible to build a user-model to estimate computer proficiency on the basis of user-interaction data. The user model could then used to improve usability through adaptive user-specific customisations

Geolocating for Web Based Geospatial Applications

The geospatial location of stationary and mobile objects and phenomena are increasingly important to geospatial applications. The availability and ease of access to geospatial information and digital earth technologies via the Internet are helping to drive a greater demand for geolocating fixed and mobile features, users, assets, services and other phenomena. A range of methods are used to determine spatial locations of fixed and mobile objects and properties including GPS, WiFi, RFID, geocoding, sensors and IP locating. Current research is investigating methods to identify user locations on the internet. The internet forms an attractive platform for Location Based Services (LBS) since it provides a nearly ubiquitous medium and web browsers provide a highly standardised application environment. However, security mechanisms in browsers complicate communication with devices used for positioning. IP positioning can provide a viable alternative, particularly since the computer network hierarchy is related to spatial hierarchies. This chapter introduces location based services and the importance of location. A range of methods for obtaining geospatial location are introduced and the contexts in which they are used are described. Finally, some current research is outlined where a methodology known as VRILS was developed to enable the use of IP addresses for geolocating in a web based environment

Enhancing accessibility to web mapping systems with technology-aligned adaptive profiles

Web-based geographic information systems have advanced rapidly on the back of web-based technologies, increased bandwidths and access to Digital Earth imagery and functionality. However, these advances are causing its capabilities to slowly overtake those of end-users. Additionally, the introduction of non-desktop devices such as smartphones, tablets and netbooks is starting to undo progress made towards standardisation of web-based technology. Large variations in screen sizes, computational power, bandwidth, and operating environments are once again introducing the need to ensure software remains functional across different platforms, standards-compliant or not. These two issues highlight the need for a mechanism to tune content and capability to end-users and their environment, to prevent information and complexity overload in a field already troubled by poor usability, while promoting cross-platform compatibility. This paper proposes the use of adaptivity to accommodate for users from different backgrounds accessing web mapping systems in different technical environments. It describes adaptive profiles aligned to the finite number of states a system can adopt, rather than the limitless range of user or environment characteristics that cannot be adapted to. Each profile consists of a combination of adaptive states comprising functionality, information detail, or technical demands to optimise for individual users or technical environments

Scale-dependency in IP-based positioning of network clusters

Although research in location-based services (LBS) is advancing well, the problem of obtaining a position for the user is still a major obstacle. Commonly available methods suffer from problems of availability, financial cost, and lack of precision or accuracy. The concept that IP-addresses tend to be spatially clustered which makes them attractive as a means for positioning. IP-based positioning would be applicable to any immobile device or interface, such as a computer or a wireless access point. Although it is believed that LBS equates to mobile computing, in reality the audience among static users in homes and offices may in fact be greater at this point in time. VRILS (varying resolution IP locating system) uses the relationship between network clusters and spatial clusters to provide positions for IP-addresses. It uses different levels of spatial precision to cope with conflicting locations within subnets, which enhances the chance of being able to provide a location. VRILS has been tested on the campus of Curtin University, where the positions of 461 IP-addresses were used in a network of over 20,000 computers. The outcome showed perfect results at the broadest spatial resolution of ‘campus’, and a reasonable result at the resolution of ‘building’. Randomness of IP-addresses across certain buildings was shown to strongly affect the accuracy. In general, it could be seen that with a relatively small amount of data, accurate positions could be obtained, but a lack of spatial clustering would decrease the efficiency to that of simple lookups

Prevalence of Autism Spectrum Disorders in Ecuador: A Pilot Study in Quito

This research presents the results of the first phase of the study on the prevalence of pupils with Autism Spectrum Disorder (ASD) in regular education in Quito, Ecuador. One-hundred-and-sixty-one regular schools in Quito were selected with a total of 51,453 pupils. Prevalence of ASD was assessed by an interview with the rector of the school or its delegate. Results show an extremely low prevalence of 0.11 % of pupils with any ASD diagnosis; another 0.21 % were suspected to have ASD, but were without a diagnosis. This low prevalence suggests that children and adolescents with ASD are not included in regular education in Quito. These results are discussed in the light of low diagnostic identification of ASD and low inclusion tolerance

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use