Using mobile technology to motivate adolescents with type 1 diabetes mellitus: A systematic review of recent literature

Introduction Behavioural interventions have been shown to improve outcomes in patients with type 1 diabetes mellitus (T1DM). There are a small number of studies that suggest text-messages (TM), native mobile applications (NMAs), and other mobile tools may be useful platforms for delivering behavioural interventions to adolescents. Aim The aim of this study was to explore, by way of a systematic review of available literature, (a) the outcomes of interventions using mobile technology for youth with T1DM and (b) what mobile technologies, functional design elements and aesthetic design elements have the best evidence to support their use. Methods A search of six online databases returned 196 unique results, of which 13 met the inclusion criteria. Results Four studies were randomised controlled trials (RCTs), and all others prospective cohort studies. TM (10) was the most common intervention technology, while NMAs were used in four studies. The most common outcome measured was HbA1c (9); however, only three studies showed a significant decrease. Similarly, the results reported for other outcome measures were mixed. The studies included in this review suggest that interventions which have data collection and clinician support functionality may be more effective in improving adherence and glycaemic control, but more evidence is needed. Further, the evidence base supporting the use of NMAs in T1DM management for adolescents is weak, with most studies adopting TM as the intervention tool. Overall, the studies lack adequate descriptions of their methodology, and better quality studies are required to inform future intervention design.

Collaborative data exploration interfaces - From participatory sensing to participatory sensemaking

As technological capabilities for capturing, aggregating, and processing large quantities of data continue to improve, the question becomes how to effectively utilise these resources. Whenever automatic methods fail, it is necessary to rely on human background knowledge, intuition, and deliberation. This creates demand for data exploration interfaces that support the analytical process, allowing users to absorb and derive knowledge from data. Such interfaces have historically been designed for experts. However, existing research has shown promise in involving a broader range of users that act as citizen scientists, placing high demands in terms of usability. Visualisation is one of the most effective analytical tools for humans to process abstract information. Our research focuses on the development of interfaces to support collaborative, community-led inquiry into data, which we refer to as Participatory Data Analytics. The development of data exploration interfaces to support independent investigations by local communities around topics of their interest presents a unique set of challenges, which we discuss in this paper. We present our preliminary work towards suitable high-level abstractions and interaction concepts to allow users to construct and tailor visualisations to their own needs.

Medical Data Access Accountability in EHR Systems, A Practical Perspective

The world has experienced a large increase in the amount of available data. Therefore, it requires better and more specialized tools for data storage and retrieval and information privacy. Recently Electronic Health Record (EHR) Systems have emerged to fulfill this need in health systems. They play an important role in medicine by granting access to information that can be used in medical diagnosis. Traditional systems have a focus on the storage and retrieval of this information, usually leaving issues related to privacy in the background. Doctors and patients may have different objectives when using an EHR system: patients try to restrict sensible information in their medical records to avoid misuse information while doctors want to see as much information as possible to ensure a correct diagnosis. One solution to this dilemma is the Accountable e-Health model, an access protocol model based in the Information Accountability Protocol. In this model patients are warned when doctors access their restricted data. They also enable a non-restrictive access for authenticated doctors. In this work we use FluxMED, an EHR system, and augment it with aspects of the Information Accountability Protocol to address these issues. The Implementation of the Information Accountability Framework (IAF) in FluxMED provides ways for both patients and physicians to have their privacy and access needs achieved. Issues related to storage and data security are secured by FluxMED, which contains mechanisms to ensure security and data integrity. The effort required to develop a platform for the management of medical information is mitigated by the FluxMED's workflow-based architecture: the system is flexible enough to allow the type and amount of information being altered without the need to change in your source code.

Review and future options for computer modelling in the sugar industry

Computer modelling has been used extensively in some processes in the sugar industry to achieve significant gains. This paper reviews the investigations carried out over approximately the last twenty five years, including the successes but also areas where problems and delays have been encountered. In that time the capability of both hardware and software have increased dramatically. For some processes such as cane cleaning, cane billet preparation, and sugar drying, the application of computer modelling towards improved equipment design and operation has been quite limited. A particular problem has been the large number of particles and particle interactions in these…

Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions

Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention. Bayesian networks are useful extensions to logic maps when initiating a review or to facilitate synthesis and bridge the gap between evidence acquisition and decision-making. Formal elicitation techniques allow development of BNs on the basis of expert opinion. Such applications are useful alternatives to ‘empty’ reviews, which identify knowledge gaps but fail to support decision-making. Where review evidence exists, it can inform the development of a BN. We illustrate the construction of a BN using a motivating example that demonstrates how BNs can ensure coherence, transparently structure the problem addressed by a complex intervention and assess sensitivity to context, all of which are critical components of robust reviews of complex interventions. We suggest that BNs should be utilised to routinely synthesise reviews of complex interventions or empty reviews where decisions must be made despite poor evidence.

Collaborative learning from distributed places and spaces: Exploring the use of virtual collaborative tools for local and global student teamwork projects

Educating responsive graduates. Graduate competencies include reliability, communication skills and ability to work in teams. Students using Collaborative technologies adapt to a new working environment, working in teams and using collaborative technologies for learning. Collaborative Technologies were used not simply for delivery of learning but innovatively to supplement and enrich research-based learning, providing a space for active engagement and interaction with resources and team. This promotes the development of responsive ‘intellectual producers’, able to effectively communicate, collaborate and negotiate in complex work environments. Exploiting technologies. Students use ‘new’ technologies to work collaboratively, allowing them to experience the reality of distributed workplaces incorporating both flexibility and ‘real’ time responsiveness. Students are responsible and accountable for individual and group work contributions in a highly transparent and readily accessible workspace. This experience provides a model of an effective learning tool. Navigating uncertainty and complexity. Collaborative technologies allows students to develop critical thinking and reflective skills as they develop a group product. In this forum students build resilience by taking ownership and managing group work, and navigating the uncertainties and complexities of group dynamics as they constructively and professionally engage in team dialogue and learn to focus on the goal of the team task.

Turning gaming EEG peripherals into trainable brain computer interfaces

Companies such as NeuroSky and Emotiv Systems are selling non-medical EEG devices for human computer interaction. These devices are significantly more affordable than their medical counterparts, and are mainly used to measure levels of engagement, focus, relaxation and stress. This information is sought after for marketing research and games. However, these EEG devices have the potential to enable users to interact with their surrounding environment using thoughts only, without activating any muscles. In this paper, we present preliminary results that demonstrate that despite reduced voltage and time sensitivity compared to medical-grade EEG systems, the quality of the signals of the Emotiv EPOC neuroheadset is sufficiently good in allowing discrimina tion between imaging events. We collected streams of EEG raw data and trained different types of classifiers to discriminate between three states (rest and two imaging events). We achieved a generalisation error of less than 2% for two types of non-linear classifiers.

QUT’s research data storage solutions: A launchpad for research journeys

This poster presents key features of how QUT’s integrated research data storage and management services work with researchers through their own individual or team research life cycle. By understanding the characteristics of research data, and the long-term need to store this data, QUT has provided resources and tools that support QUT’s goal of being a research intensive institute. Key to successful delivery and operation has been the focus upon researchers’ individual needs and the collaboration between providers, in particular, Information Technology Services, High Performance Computing and Research Support, and QUT Library. QUT’s Research Data Storage service provides all QUT researchers (staff and Higher Degree Research students (HDRs)) with a secure data repository throughout the research data lifecycle. Three distinct storage areas provide for raw research data to be acquired, project data to be worked on, and published data to be archived. Since the service was launched in late 2014, it has provided research project teams from all QUT faculties with acquisition, working or archival data space. Feedback indicates that the storage suits the unique needs of researchers and their data. As part of the workflow to establish storage space for researchers, Research Support Specialists and Research Data Librarians consult with researchers and HDRs to identify data storage requirements for projects and individual researchers, and to select and implement the most suitable data storage services and facilities. While research can be a journey into the unknown[1], a plan can help navigate through the uncertainty. Intertwined in the storage provision is QUT’s Research Data Management Planning tool. Launched in March 2015, it has already attracted 273 QUT staff and 352 HDR student registrations, and over 620 plans have been created (2/10/2015). Developed in collaboration with Office of Research Ethics and Integrity (OREI), uptake of the plan has exceeded expectations.

Computer-assisted sampling of acoustic data for more efficient determination of bird species richness

Bird species richness survey is one of the most intriguing ecological topics for evaluating environmental health. Here, bird species richness denotes the number of unique bird species in a particular area. Factors affecting the investigation of bird species richness include weather, observation bias, and most importantly, the prohibitive costs of conducting surveys at large spatiotemporal scales. Thanks to advances in recording techniques, these problems have been alleviated by deploying sensors for acoustic data collection. Although automated detection techniques have been introduced to identify various bird species, the innate complexity of bird vocalizations, the background noise present in the recording and the escalating volumes of acoustic data pose a challenging task on determination of bird species richness. In this paper we proposed a two-step computer-assisted sampling approach for determining bird species richness in one-day acoustic data. First, a classification model is built based on acoustic indices for filtering out minutes that contain few bird species. Then the classified bird minutes are ordered by an acoustic index and the redundant temporal minutes are removed from the ranked minute sequence. The experimental results show that our method is more efficient in directing experts for determination of bird species compared with the previous methods.

Using conceptual tool for intuitive interaction to design intuitive website for SME in India : A case study

Statistical reports of SMEs Internet usage from various countries indicate a steady growth. However, deeper investigation of SME’s e-commerce adoption and usage reveals that a number of SMEs fail to realize the full potential of e-commerce. Factors such as lack of tools and models in Information Systems and Information Technology for SMEs, and lack of technical expertise and specialized knowledge within and outside the SME have the most effect. This study aims to address the two important factors in two steps. First, introduce the conceptual tool for intuitive interaction. Second, explain the implementation process of the conceptual tool with the help of a case study. The subject chosen for the case study is a real estate SME from India. The design and development process of the website for the real estate SME was captured in this case study and the duration of the study was four months. Results indicated specific benefits for web designers and SME business owners. Results also indicated that the conceptual tool is easy to use without the need for technical expertise and specialized knowledge.

SPSA Based Feature Relevance Estimation For Video Retrieval

With the availability of a huge amount of video data on various sources, efficient video retrieval tools are increasingly in demand. Video being a multi-modal data, the perceptions of ``relevance'' between the user provided query video (in case of Query-By-Example type of video search) and retrieved video clips are subjective in nature. We present an efficient video retrieval method that takes user's feedback on the relevance of retrieved videos and iteratively reformulates the input query feature vectors (QFV) for improved video retrieval. The QFV reformulation is done by a simple, but powerful feature weight optimization method based on Simultaneous Perturbation Stochastic Approximation (SPSA) technique. A video retrieval system with video indexing, searching and relevance feedback (RF) phases is built for demonstrating the performance of the proposed method. The query and database videos are indexed using the conventional video features like color, texture, etc. However, we use the comprehensive and novel methods of feature representations, and a spatio-temporal distance measure to retrieve the top M videos that are similar to the query. In feedback phase, the user activated iterative on the previously retrieved videos is used to reformulate the QFV weights (measure of importance) that reflect the user's preference, automatically. It is our observation that a few iterations of such feedback are generally sufficient for retrieving the desired video clips. The novel application of SPSA based RF for user-oriented feature weights optimization makes the proposed method to be distinct from the existing ones. The experimental results show that the proposed RF based video retrieval exhibit good performance.

Development of molecular tools for the improvement of transgene expression in sugar cane

Biotechnology has the potential to improve sugar cane, one of the world's major crops for food and fuel. This research describes the detailed characterisation of introns and their potential for enhancing transgene expression in sugar cane via intron-mediated enhancement (IME). IME is a phenomenon whereby an intron enhances gene expression from a promoter. Current knowledge on the mechanism of IME or its potential for enhancing gene expression in sugar cane is limited. A better understanding of the factors responsible for IME will help develop new molecular tools that facilitate high levels of constitutive and tissue-specific gene expression in this crop.

Public disclosure of biological sequences in global patent practice

Biological sequences are an important part of global patenting, with unique challenges for their effective and equitable use in practice and in policy. Because their function can only be determined with computer-aided technology, the form in which sequences are disclosed matters greatly. Similarly, the scope of patent rights sought and granted requires computer readable data and tools for comparison. Critically, the primary data provided to the national patent offices and thence to the public, must be comprehensive, standardized, timely and meaningful. It is not yet. The proposed global Patent Sequence (PatSeq) Data platform can enable national and regional jurisdictions meet the desired standards.