Une application mobile pour les victimes d'intimidation par les pairs : examen des récits d'expérience et perceptions d'utilité.

Au Canada, la prévalence de l'intimidation par les pairs (IPP) est estimée à environ 20 %. L'IPP est associée à de nombreuses difficultés sur le rendement scolaire et le fonctionnement émotionnel, cognitif et comportemental de la victime. Afin de s'investir dans la lutte contre l'IPP, le Québec a promulgué en 2012 la Loi visant à lutter contre l'intimidation et la violence à l'école. Ainsi, les écoles ont pour obligation d'instaurer un plan d'action contre l'intimidation. Toutefois, les services d'aide aux victimes sont parfois limités. C'est pourquoi l'application mobile « +Fort » a été développée. +Fort vise à soutenir les victimes d'IPP à réduire leurs expériences et à prévenir les difficultés associées. Le présent mémoire a trois objectifs: (1) décrire l'expérience des victimes d'IPP ayant utilisé +Fort pendant quatre semaines, (2) effectuer une première appréciation de l'utilité de +Fort à partir des récits des victimes et (3) décrire comment +Fort soutien les jeunes à réduire leurs expériences d'intimidation. Des entrevues semi-dirigées ont été menées auprès de 12 victimes d'IPP (12 à 16 ans) de la région de Montréal puis analysées thématiquement. Les résultats suggèrent que +Fort agirait comme un facilitateur dans les démarches de changement des victimes pour réduire l'IPP. Les ressources offertes par +Fort procureraient aussi une impression de soutien aux victimes qui influencerait ensuite leur désir et leur motivation à entreprendre des actions pour que cesse l'intimidation. Ainsi, les technologies mobiles représenteraient une plateforme attrayante pour soutenir le mieux-être des jeunes vivant de l'intimidation.

Faciliter la mise en place d'études d'utilisabilité par des outils de stockage des données et d'analyse automatique des traces d'utilisation : un cas d'étude avec une application mobile

Le laboratoire DOMUS développe des applications pour assister les personnes en perte d'autonomie et les personnes avec des troubles cognitifs. Chaque application est ou a déjà été le sujet de plusieurs études d'utilisabilité qui permettent de les améliorer. Ces études prennent beaucoup de temps à mettre en place, car l'on rencontre souvent des problèmes de logistique (format et sensibilité des données, chercheurs répartis sur une grande aire géographique). C'est pourquoi un outil appelé GEDOPAL a été développé. Il permet de partager entre chercheurs de différents centres les données créées et utilisées lors de la mise en place des études d'utilisabilité. La conception et la réalisation de cet outil ont nécessité une réflexion en amont sur la nature et la sensibilité de ces données. Cette réflexion est l'objet du Chapitre 3. Ces études prennent aussi beaucoup de temps lors de l'analyse des résultats. De plus, certaines données créées lors de ces études, telles que les traces d'utilisation ont des volumétries trop importantes pour être analysées manuellement. C'est pourquoi nous avons créé un processus permettant d'analyser ces traces d'utilisation pour y détecter les erreurs utilisateurs dans l'espoir de les relier à des problèmes d'utilisabilité. Ce processus se compose de deux parties : la première est une analyse formelle de l'application, qui sera présentée au Chapitre 4, et la seconde l'application d'un outil d'apprentissage automatique aux traces d'utilisation pour y détecter les erreurs utilisateurs. Cet outil est présenté au Chapitre 5.

Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells

Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.

移动数据库及其应用

近年来 ,随着硬件技术及无线通讯技术的发展 ,移动计算及移动数据库技术的发展呈加速趋势 ,并在越来越多的领域中获得了成功的应用。可以预见 :在不久的将来 ,人们希望随时随地存取任意数据信息的愿望终将成为现实。本文分析了移动数据库的特点及其关键技术 ,描述了小金灵移动数据库系统的三级体系结构及其实现技术 ,并对移动数据库技术的应用领域进行了分析。

An Effective Path Protection Method to Attain the Route Stability in MANET

With the increasing popularity of wireless network and its application, mobile ad-hoc networks (MANETS) emerged recently. MANET topology is highly dynamic in nature and nodes are highly mobile so that the rate of link failure is more in MANET. There is no central control over the nodes and the control is distributed among nodes and they can act as either router or source. MANTEs have been considered as isolated stand-alone network. Node can add or remove at any time and it is not infrastructure dependent. So at any time at any where the network can setup and a trouble free communication is possible. Due to more chances of link failures, collisions and transmission errors in MANET, the maintenance of network became costly. As per the study more frequent link failures became an important aspect of diminishing the performance of the network and also it is not predictable. The main objective of this paper is to study the route instability in AODV protocol and suggest a solution for improvement. This paper proposes a new approach to reduce the route failure by storing the alternate route in the intermediate nodes. In this algorithm intermediate nodes are also involved in the route discovery process. This reduces the route establishment overhead as well as the time to find the reroute when a link failure occurs.

Mobile communication in power distribution application

This paper investigates how to interface the wireless application protocol (WAP) architecture to the SCADA system running distributed network protocol (DNP) in a power process plant. DNP is a well-developed protocol to be applied in the supervisory control and data acquisition (SCADA) system but the system control centre and remote terminal units (RTUs) are presently connected through a local area network. The conditions in a process plant are harsh and the site is remote. Resources for data communication are difficult to obtain under these conditions, thus, a wireless channel communication through a mobile phone is practical and efficient in a process plant environment. The mobile communication industries and the public have a strong interest in the WAP technology application in mobile phone networks and the WAP application programming interface (API) in power industry applications is one area that requires extensive investigation.

A gamified mobile application for engaging new students at university orientation

The term gamification describes the addition of game elements to non-game contexts as a means to motivate and engage users. This study investigates the design, delivery and pilot evaluation of a gamified, smartphone application built to introduce new students to the campus, services and people at university during their first few weeks. This paper describes changes to the application made after an initial field study was undertaken and provides an evaluation of the impact of the redesign. Survey responses were collected from thirteen students and usage data was captured from 105 students. Results indicate three levels of user engagement and suggest that there is value in adding game elements to the experience in this way. A number of issues are identified and discussed based on game challenges, input, and facilitating game elements in an event setting such as university orientation.

Uninav : a context-aware mobile application for university campus maps

The smart phones we carry with us are becoming ubiquitous with everyday life and the sensing capabilities of these devices allow us to provide context-aware services. In this paper, we discuss the development of UniNav, a context-aware mobile application that delivers personalised campus maps for universities. The application utilises university students’ details to provide information and services that are relevant and important to them. It helps students to navigate within the campus and become familiar with their university environment quickly. A study was undertaken to evaluate the acceptability and usefulness of the campus map, as well as the impact on a users’ navigation efficiency by utilising the personal and environmental contexts. The result indicates the integration of personal and environmental contexts on digital maps can improve its usefulness and navigation efficiency.

A context-fusion framework for enhancing context-awareness on mobile application

Mobile devices and smartphones have become a significant communication channel for everyday life. The sensing capabilities of mobile devices are expanding rapidly, and sensors embedded in these devices are cheaper and more powerful than before. It is evident that mobile devices have become the most suitable candidates to sense contextual information without needing extra tools. However, current research shows only a limited number of sensors are being explored and investigated. As a result, it still needs to be clarified what forms of contextual information extracted from mo- bile sensors are useful. Therefore, this research investigates the context sensing using current mobile sensors, the study follows experimental methods and sensor data is evaluated and synthesised, in order to deduce the value of various sensors and combinations of sensor for the use in context-aware mobile applications. This study aims to develop a context fusion framework that will enhance the context-awareness on mobile applications, as well as exploring innovative techniques for context sensing on smartphone devices.

BioCondition assessment tool : a mobile application to aid vegetation assessment

Environmental degradation has become increasingly aggressive in recent years due to rapid urban development and other land use pressures. This chapter looks at BioCondition, a newly developed vegetation assessment framework by Queensland Department of Resource Management (DERM) and how mobile technology can assist beginners in conducting the survey. Even though BioCondition is designed to be simple, it is still fairly inaccessible to beginners due to its complex, time consuming, and repetitive nature. A Windows Phone mobile application, BioCondition Assessment Tool, was developed to provide on-site guidance to beginners and document the assessment process for future revision and comparison. The application was tested in an experiment at Samford Conservation Park with 12 students studying ecology in Queensland University of Technology.

The Mobile Application Rating Scale (MARS): A new tool to measure the quality of health mobile applications

Smartphone technology provides free or inexpensive access to mental health and wellbeing resources. As a result the use of mobile applications for these purposes has increased significantly in recent years. Yet, there is currently no app quality assessment alternative to the popular ‘star’-ratings, which are often unreliable. This presentation describes the development of the Mobile Application Rating Scale (MARS) a new measure for classifying and rating the quality of mobile applications. A review of existing literature on app and web quality identified 25 published papers, conference proceedings, and online resources (published since 1999), which identified 372 explicit quality criteria. Qualitative analysis identified five broad categories of app quality rating criteria: engagement, functionality, aesthetics, information quality, and overall satisfaction, which were refined into the 23-item MARS. Independent ratings of 50 randomly selected mental health and wellbeing mobile apps indicated the MARS had excellent levels of internal consistency (α = 0.92) and inter-rater reliability (ICC = 0.85). The MARS provides practitioners and researchers with an easy-to-use, simple, objective and reliable tool for assessing mobile app quality. It also provides mHealth professionals with a checklist for the design and development of high quality apps.

Mobile cloud application models facilitated by the CPA

This paper describes implementations of two mobile cloud applications, file synchronisation and intensive data processing, using the Context Aware Mobile Cloud Services middleware, and the Cloud Personal Assistant. Both are part of the same mobile cloud project, actively developed and currently at the second version. We describe recent changes to the middleware, along with our experimental results of the two application models. We discuss challenges faced during the development of the middleware and their implications. The paper includes performance analysis of the CPA support for the two applications in respect to existing solutions.

Designing and evaluating an interactive assessment instrument to improve the process for mobile service application innovation

Published Version

An efficient feature selection method for mobile devices with application to activity recognition

This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.