Passive Indoor Positioning System (PIPS) Using Near Field Communication (NFC) Technology

Travel can be an enjoyable experience but it can also be stressful when one is unable to get to the destination in timely manner. Satellite navigation systems (satnav) such as the ubiquitous Global Positioning System (GPS) provide an aid to locating unfamiliar places without hassle. However, the effectiveness of satnav stops at the doorstep of the building due to its requirement for line of sight with orbiting satellites. Within a large complex building, navigation typically relies on building signage, information from kiosks and getting assistance from information desks. The advancement of mobile devices and wireless technology offer an interesting proposition for the development of indoor positioning systems. In this paper, we propose a passive indoor positioning system to provide navigational aid and discuss findings from our pilot experiment using NFC technology

A Platform Independent Game Technology Model for Model Driven Serious Games Development

Game‑based learning (GBL) combines pedagogy and interactive entertainment to create a virtual learning environment in an effort to motivate and regain the interest of a new generation of ‘digital native’ learners. However, this approach is impeded by the limited availability of suitable ‘serious’ games and high‑level design tools to enable domain experts to develop or customise serious games. Model Driven Engineering (MDE) goes some way to provide the techniques required to generate a wide variety of interoperable serious games software solutions whilst encapsulating and shielding the technicality of the full software development process. In this paper, we present our Game Technology Model (GTM) which models serious game software in a manner independent of any hardware or operating platform specifications for use in our Model Driven Serious Game Development Framework

Multiple Density Maps Information Fusion for Effectively Assessing Intensity Pattern of Lifelogging Physical Activity

Physical activity (PA) measurement is a crucial task in healthcare technology aimed at monitoring the progression and treatment of many chronic diseases. Traditional lifelogging PA measures require relatively high cost and can only be conducted in controlled or semi-controlled environments, though they exhibit remarkable precision of PA monitoring outcomes. Recent advancement of commercial wearable devices and smartphones for recording one’s lifelogging PA has popularized data capture in uncontrolled environments. However, due to diverse life patterns and heterogeneity of connected devices as well as the PA recognition accuracy, lifelogging PA data measured by wearable devices and mobile phones contains much uncertainty thereby limiting their adoption for healthcare studies. To improve the feasibility of PA tracking datasets from commercial wearable/mobile devices, this paper proposes a lifelogging PA intensity pattern decision making approach for lifelong PA measures. The method is to firstly remove some irregular uncertainties (IU) via an Ellipse fitting model, and then construct a series of monthly based hour-day density map images for representing PA intensity patterns with regular uncertainties (RU) on each month. Finally it explores Dempster-Shafer theory of evidence fusing information from these density map images for generating a decision making model of a final personal lifelogging PA intensity pattern. The approach has significantly reduced the uncertainties and incompleteness of datasets from third party devices. Two case studies on a mobile personalized healthcare platform MHA [1] connecting the mobile app Moves are carried out. The results indicate that the proposed approach can improve effectiveness of PA tracking devices or apps for various types of people who frequently use them as a healthcare indicator

Using Serious Games to Create Awareness on Visual Impairments

Visual impairments define a wide spectrum of disabilities that vary in severity, from the need to wear glasses, to permanent loss of vision or blindness. This paper discusses the process undertaken in creating two simulators, one which emulates partially-sighted visual impairment and another focused on full -blindness. In order to create the simulators, extensive research was conducted surrounding the effects of partially-sightedness and blindness, highlighting existing software and games that promote awareness for visual impairments. This paper underlines the necessity of raising awareness for visual impairments and the effectiveness of applying serious games for this very goal. After developing the simulators, experiments were conducted to evaluate the effectiveness of it. Findings from the experiments were analysed and documented

Calcium inhibits diacylglycerol uptake by serum albumin

AbstractSerum albumin is an abundant protein in blood plasma, that is well-known for its ability to transport hydrophobic biomolecules and drugs. Recent hypotheses propose that serum albumin plays a role in the regulation of lipid metabolism in addition to its lipid transport properties. The present work explores the capacity of bovine serum albumin (BSA) to extract diacylglycerols (DAG) from phospholipid bilayers, and the inhibition of such interaction by divalent cations. Quantitative measurements using radioactive DAG and morphological evidence derived from giant unilamellar vesicles examined by confocal microscopy provide concurrent results. BSA extracts DAG from vesicles consisting of phosphatidylinositol/DAG. Long, saturated DAG species are incorporated more readily than the shorter-chain or unsaturated ones. Divalent cations hinder DAG uptake by BSA. For Ca2+, the concentration causing half-maximal inhibition is ≈10 μM; 90% inhibition is caused by 100 μM Ca2+. Sr2+ requires concentrations one order of magnitude higher, while Mg2+ has virtually no effect. As an example on how DAG uptake by BSA, and its inhibition by Ca2+, could play a regulating role in lipid metabolism, a PI-specific phospholipase C has been assayed in the presence of BSA and/or Ca2+. BSA activates the enzyme by removing the end-product DAG, but the activation is reverted by Ca2+ that inhibits DAG uptake

State-of-the-Art Model Driven Game Development: A Survey of Technological Solutions for Game-Based Learning

Game-based learning harnesses the advantages of computer games technology to create a fun, motivating and interactive virtual learning environment that promotes problem-based experiential learning. Such an approach is advocated by many commentators to provide an enhanced learning experience than those based on traditional didactic methods. However, the adoption of such a seductive learning method engenders a range of technical, educational and pedagogical challenges, including: (i) how to enable domain experts - with little computer games development skills – to plan, develop and update their teaching material without going through endless and laborious iterative cycles of software and content development and/or adaptation; (ii) how to choose the right mix of entertainment and game playing to deliver the required educational and pedagogical lesson/teaching material; and (iii) how to reuse existing games software frameworks and associated editing environments for game-based learning. Much research is already underway at addressing the stated challenges; however, these approaches do not address the key challenge of facilitating the planning and development of teaching material with the right mix of pedagogical elements, educational components and fun. Thus, this study aims to investigate the use of model-driven software engineering approaches to facilitate non-technical domain experts (teachers) to plan, develop and maintain game-based learning resources regardless of the intricacies of the game engine/environment (platform) used. This article investigates the state-of-the-art in model-driven game development to provide a summary of developments in game design languages, game software modelling languages, game models, game software models, model-driven game frameworks, game software frameworks, model-driven engineering tools and assistive user interfaces. The findings from this survey will prove a useful guide for future development of high-level educational game creation tools for game-based learning

Uncertainty Investigation for Personalised Lifelogging Physical Activity Intensity Pattern Assessment with Mobile Devices

Lifelogging physical activity (PA) assessment is crucial to healthcare technologies and studies for the purpose of treatments and interventions of chronic diseases. Traditional lifelogging PA monitoring is conducted in non-naturalistic settings by means of wearable devices or mobile phones such as fixed placements, controlled durations or dedicated sensors. Although they achieved satisfactory outcomes for healthcare studies, the practicability become the key issues. Recent advance of mobile devices make lifelogging PA tracking for healthy or unhealthy individuals possible. However, owning to diverse physical characteristics, immaturity of PA recognition techniques, different settings from manufactories and a majority of uncertainties in real life, the results of PA measurement is leading to be inapplicable for PA pattern detection in a long range, especially hardly exploited in the wellbeing monitoring or behaviour changes. This paper investigates and compares uncertainties of existing mobile devices for individual’s PA tracking. Irregular uncertainties (IU) are firstly removed by exploiting Ellipse fitting model, and then monthly density maps that contain regular uncertainties (RU) are constructed based on metabolic equivalents (METs) of different activity types. Five months of four subjects PA intensity changes using the mobile app tracker Moves [1] and Google Fit app on wearable device Samsung wear S2 are carried out from a mobile personalised healthcare platform MHA [2]. The result indicates that uncertainty of PA intensity monitored by mobile phone is 90% lower than wearable device, where the datasets tend to be further explored by healthcare/fitness studies. Whilst PA activity monitoring by mobile phone is still a challenging issue by far due to much more uncertainties than wearable devices

The chaperonin CCT inhibits assembly of α-synuclein amyloid fibrils by a specific, conformation-dependent interaction

The eukaryotic chaperonin CCT (chaperonin containing TCP-1) uses cavities built into its double-ring structure to encapsulate and to assist folding of a large subset of proteins. CCT can inhibit amyloid fibre assembly and toxicity of the polyQ extended mutant of huntingtin, the protein responsible for Huntington's disease. This raises the possibility that CCT modulates other amyloidopathies, a still-unaddressed question. We show here that CCT inhibits amyloid fibre assembly of α-synuclein A53T, one of the mutants responsible for Parkinson's disease. We evaluated fibrillation blockade in α-synuclein A53T deletion mutants and CCT interactions of full-length A53T in distinct oligomeric states to define an inhibition mechanism specific for α-synuclein. CCT interferes with fibre assembly by interaction of its CCT and CCT 3 subunits with the A53T central hydrophobic region (NAC). This interaction is specific to NAC conformation, as it is produced once soluble α-synuclein A53T oligomers form and blocks the reaction before fibres begin to grow. Finally, we show that this association inhibits α-synuclein A53T oligomer toxicity in neuroblastoma cells. In summary, our results and those for huntingtin suggest that CCT is a general modulator of amyloidogenesis via a specific mechanism.Ministerio de Economía RYC- 2011-08746 , RTC-2015-3309-1 y BFU2016-75984Ministerio de Salud CP10/00527Comunidad de Madrid S2013/MIT-280

A Measure of Student Engagement for Serious Games and IoT

Student Engagement has been a strong topic of research for the avoidance of student drop out and the increase in grading. Serious games have highlighted benefi ts in engaging students, primarily through edutainment, educating via games. This article suggests a Computer Algorithm, purposed at measuring and encouraging student engagement. In addition, the algorithm accounts for sensor networks accessed both directly and through the Internet, extending its application to the Internet of Things (IoT)