Enhancement of user level controls in cloud databases

Industries in developed countries are moving quickly to ensure the rapid adoption of cloud computing. At this stage, several outstanding issues exist, particularly related to Service Level Agreements (SLAs), security and privacy. Consumers and businesses are willing to use cloud computing only if they can trust that their data will remain private and secure. Our review of research literature indicates the level of control that a user has on their data is directly correlated to the level of data privacy provided by the cloud service. We considered several privacy factors from the industry perspective, namely data loss, data storage location being unknown to the client, vendor lock-in, unauthorized secondary use of user's data for advertising, targeting secured backup and easy restoration. The level of user control in database models were identified according to the level of existence in these privacy factors. Finally, we focused on a novel logical model that might help to bring the level of user control of privacy in cloud databases into a higher level.

Telephone survey of service-user experiences of a telephone-based mental health triage service

The participation of service users in all aspects of mental health service delivery including policy development, service planning and evaluation is increasingly an expectation of contemporary mental health care. Although there are a growing number of publications reporting service-user perspectives in the evaluation of mental health services, little attention has been paid to the views of service users about mental health triage services. The purpose of the study reported here was to examine service-users' (consumers and informal carers) experiences of a telephone-based mental health triage service. Using a framework developed from the World Health Organisation's elements of responsiveness, we conducted structured telephone interviews with service users who had contacted a telephone-based mental health triage service in regional Victoria, Australia. The main findings of the study were that consumers experienced more difficulty than carers in accessing the service and that, although most participants were satisfied, only a minority reported being involved in decision-making. Further work is needed to improve accessibility of mental health triage services and to investigate barriers to consumer self-referral. Professional development and practice support systems should be established to support mental health triage nurses in the development of collaborative, consumer-focused care.

The Nicholas building : a user's manual

Details of the design, construction and the 1926 opening of the Nicholas Building, located on the corner of Flinders Lane and Swanston Street, Melbourne, are presented. Information about the varied types of business houses functioning in the large premises over the years is provided, highlighting the building's lasting appeal for traders and the public.

Recognising user identity in twitter social networks via text mining

Social networks have become a convenient and effective means of communication in recent years. Many people use social networks to communicate, lead, and manage activities, and express their opinions in supporting or opposing different causes. This has brought forward the issue of verifying the owners of social accounts, in order to eliminate the effect of any fake accounts on the people. This study aims to authenticate the genuine accounts versus fake account using writeprint, which is the writing style biometric. We first extract a set of features using text mining techniques. Then, training of a supervised machine learning algorithm to build the knowledge base is conducted. The recognition procedure starts by extracting the relevant features and then measuring the similarity of the feature vector with respect to all feature vectors in the knowledge base. Then, the most similar vector is identified as the verified account.

Structural equation modeling for evaluating the user perceptions of E-learning effectiveness in higher education

A crucial prerequisite for sustainable e-learning is the understanding of learners’ preferences for various pedagogical strategies, technologies, and the management of learning resources. This paper presents an empirical study aiming to empirically test the theoretical (pedagogies, technologies and management) (PTM) model on the preference of learners and on the perceived impact of the effectiveness of e-learning. This study uses structural equation modelling (SEM) to identify the critical dimensions in the PTM model for augmenting the effectiveness of e-learning. This leads to the development of a PTM model with the path coefficients showing weak to strong relationships ranging from 0.15 to 0.42 with acceptable significance levels. The results support the hypothesis that management, technology, resources and metadata ontology dimensions affect the effectiveness of elearning both directly and indirectly through enhancing the management effectiveness of learning resources. However, the result does not support positive influence of pedagogical strategy per se on e-learning effectiveness. The implications of this study indicate the criticality of effective management of learning resources to enhance e-learning effectiveness.

Training AAC users in user-centred design

User-centred design (UCD) with a focus on usability provides product developers with a design approach in which users are involved in every stage of the process: when gathering requirements; when evaluating alternative designs; and when evaluating interactive prototypes.The characteristics of people who use augmentative and alternative communication (AAC) make it difficult to follow a truly UCD approach, which in part may contribute to the high rejection of AAC devices. Training workshops have been delivered to introduce users and AAC professionals to the UCD process.Initial feedback indicates that they feel more empowered to evaluate systems and to engage in the design of new systems after attending the workshop.

Learning user preference patterns for Top-N recommendations

In this paper, we observe that the user preference styles tend to change regularly following certain patterns. Therefore, we propose a Preference Pattern model to capture the user preference styles and their temporal dynamics, and apply this model to improve the accuracy of the Top-N recommendation. Precisely, a preference pattern is defined as a set of user preference styles sorted in a time order. The basic idea is to model user preference styles and their temporal dynamics by constructing a representative subspace with an Expectation- Maximization (EM)-like algorithm, which works in an iterative fashion by refining the global and the personal preference styles simultaneously. Then, the degree which the recommendations match the active user's preference styles, can be estimated by measuring its reconstruction error from its projection on the representative subspace. The experiment results indicate that the proposed model is robust to the data sparsity problem, and can significantly outperform the state-of-the-art algorithms on the Top-N recommendation in terms of accuracy. © 2012 IEEE.

Knowledge change regarding osteoporosis prevention: translating recommended guidelines into user-friendly messages within a community forum.

Osteoporosis is a skeletal disorder characterised by low bone mineral density and increased fracture risk. Nationally the total costs of this chronic disease are currently estimated at $2.754 billion annually. Effective public health messages providing clear recommendations are vital in supporting prevention efforts. This research aimed to investigate knowledge change associated with the translation of preventive guidelines into accessible messages for the community.