An ontological modelling of user requirements for personalised information provision

The knowledge economy offers opportunity to a broad and diverse community of information systems users to efficiently gain information and know-how for improving qualifications and enhancing productivity in the work place. Such demand will continue and users will frequently require optimised and personalised information content. The advancement of information technology and the wide dissemination of information endorse individual users when constructing new knowledge from their experience in the real-world context. However, a design of personalised information provision is challenging because users’ requirements and information provision specifications are complex in their representation. The existing methods are not able to effectively support this analysis process. This paper presents a mechanism which can holistically facilitate customisation of information provision based on individual users’ goals, level of knowledge and cognitive styles preferences. An ontology model with embedded norms represents the domain knowledge of information provision in a specific context where users’ needs can be articulated and represented in a user profile. These formal requirements can then be transformed onto information provision specifications which are used to discover suitable information content from repositories and pedagogically organise the selected content to meet the users’ needs. The method is provided with adaptability which enables an appropriate response to changes in users’ requirements during the process of acquiring knowledge and skills.

Ocean data dissemination: new challenges for data integration

In the decade since OceanObs `99, great advances have been made in the field of ocean data dissemination. The use of Internet technologies has transformed the landscape: users can now find, evaluate and access data rapidly and securely using only a web browser. This paper describes the current state of the art in dissemination methods for ocean data, focussing particularly on ocean observations from in situ and remote sensing platforms. We discuss current efforts being made to improve the consistency of delivered data and to increase the potential for automated integration of diverse datasets. An important recent development is the adoption of open standards from the Geographic Information Systems community; we discuss the current impact of these new technologies and their future potential. We conclude that new approaches will indeed be necessary to exchange data more effectively and forge links between communities, but these approaches must be evaluated critically through practical tests, and existing ocean data exchange technologies must be used to their best advantage. Investment in key technology components, cross-community pilot projects and the enhancement of end-user software tools will be required in order to assess and demonstrate the value of any new technology.

An examination of the complementary volume–volatility information theories

The volume–volatility relationship during the dissemination stages of information flow is examined by analyzing various theories relating volume and volatility as complementary rather than competing models. The mixture of distributions hypothesis, sequential arrival of information hypothesis, the dispersion of beliefs hypothesis, and the noise trader hypothesis all add to the understanding of how volume and volatility interact for different types of futures traders. An integrated picture of the volume–volatility relationship is provided by investigating the dynamic linear and nonlinear associations between volatility and the volume of informed (institutional) and uninformed (the general public) traders. In particular, the trading behavior explanation for the persistence of futures volatility, the effect of the timing of private information arrival, and the response of institutional traders to excess noise trading risk is examined

Effectively finding relevant web pages from linkage information

This paper presents two hyperlink analysis-based algorithms to find relevant pages for a given Web page (URL). The first algorithm comes from the extended cocitation analysis of the Web pages. It is intuitive and easy to implement. The second one takes advantage of linear algebra theories to reveal deeper relationships among the Web pages and to identify relevant pages more precisely and effectively. The experimental results show the feasibility and effectiveness of the algorithms. These algorithms could be used for various Web applications, such as enhancing Web search. The ideas and techniques in this work would be helpful to other Web-related researches.

Accessible information for people with complex communication needs

Information can be empowering if it is accessible. While a number of known information access barriers have been reported for the broader group of people with disabilities, specific information issues for people with complex communication needs have not been previously reported. In this consumer-focused study, the accessibility of information design and dissemination practices were discussed by 17 people with complex communication needs; by eight parents, advocates, therapists, and agency representatives in focus groups; and by seven individuals in individual interviews. Participants explored issues and made recommendations for content, including language, visual and audio supports; print accessibility; physical access; and human support for information access. Consumer-generated accessibility guidelines were an outcome of this study.

Evolutionary structure learning algorithm for Bayesian network and penalized mutual information metric

This paper formulates the problem of learning Bayesian network structures from data as determining the structure that best approximates the probability distribution indicated by the data. A new metric, Penalized Mutual Information metric, is proposed, and a evolutionary algorithm is designed to search for the best structure among alternatives. The experimental results show that this approach is reliable and promising.

How practice size impacts on the implementation and dissemination of post occupancy evaluation

There has been much research on the subject of environmentally sustainable design (ESD), with emerging techniques and technologies improving rapidly and informing sustainability higher education teaching to architects and prospective architects. By examining the success of sustainable designs using post occupancy evaluations, architectural practices might also increase their knowledge of sustainable building practice. Post occupancy evaluations could be useful for improving the designs of future buildings and the design processes that generated them. This paper aims to evaluate these claims by asking: "Do sustainable design practices use the feedback gained from post occupancy evaluations?," "How does the feedback refine the design process?," "How is the information gained in these evaluations absorbed within the firm's design practices?," and, "Does the size of a practice impact on its implementation and
dissemination of POE?" This paper investigates the questions posed above through the questioning of architectural practices that have gained a reputation for environmentally sustainable design by having a strong sustainable design philosophy and/or by being recognised for this by winning a sustainability design award. The interviewed practices will have provided some form of post occupancy evaluation as a service or employed them to add to their own knowledge.

The crossroads approach to information discovery in wireless sensor networks

Wireless sensor networks (WSN) are attractive for information gathering in large-scale data rich environments. In order to fully exploit the data gathering and dissemination capabilities of these networks, energy-efficient and scalable solutions for data storage and information discovery are essential. In this paper, we formulate the information discovery problem as a load-balancing problem, with the combined aim being to maximize network lifetime and minimize query processing delay resulting in QoS improvements. We propose a novel information storage and distribution mechanism that takes into account the residual energy levels in individual sensors. Further, we propose a hybrid push-pull strategy that enables fast response to information discovery queries.

Simulations results prove the proposed method(s) of information discovery offer significant QoS benefits for global as well as individual queries in comparison to previous approaches.

Exploiting affinity propagation for energy-efficient information discovery in sensor networks

Wireless sensor networks (WSN) are attractive for information gathering in large-scale data rich environments. Emerging WSN applications require dissemination of information to interested clients within the network requiring support for differing traffic patterns. Further, in-network query processing capabilities are required for autonomic information discovery. In this paper, we formulate the information discovery problem as a load-balancing problem, with the combined aim being to maximize network lifetime and minimize query processing delay. We propose novel methods for data dissemination, information discovery and data aggregation that are designed to provide significant QoS benefits. We make use of affinity propagation to group "similar" sensors and have developed efficient mechanisms that can resolve both ALL-type and ANY-type queries in-network with improved energy-efficiency and query resolution time. Simulation results prove the proposed method(s) of information discovery offer significant QoS benefits for ALL-type and ANY-type queries in comparison to previous approaches.

The availability of information in knowledge-based economies

The use of information is preceded by its availability. For post-industrial economies to exploit information to full potential it is important for knowledge to be free of vested-interest censorship and manipulation. History suggests that a range of vested-interests have manipulated explicit> information availability through various forms of sectarian, state and business manipulation of the systems of information storage and transfer. The OECD 1996 report "The Knowledge-Based Economy" recognized that the diffusion of knowledge was as significant as its creation, and that knowledge distribution networks were crucial to innovation, production processes and product development. The success of enterprises and national economies is considered reliant on the effectiveness of their ability to gather, distribute and utilize knowledge. The increasing need for ready access (of information that might become knowledge) in accordance with the OEDC definition is particularly relevant to this paper as it assumes infrastructures capable of providing that need. Wherever there are infrastructures there are opportunities to benefit from them, either for profit or power. This paper considers the implications of sectarian, state and business-model control over the selective content, storage and dissemination of information and knowledge, both from historical and current perspectives. The advent of new technologies and how they have enabled the flow of information adds new dimensions to knowledge control but the quality of knowledge is less certain and who controls or influences distribution of knowledge less transparent. It could be argued that at each step in the development of knowledge distribution networks, knowledge and its distribution, is not free of the possibility of third-party vested interest.

Dissemination of therapist-assisted internet cognitive behaviour therapy : development and open pilot study of a workshop

There is considerable research suggesting that therapist-assisted Internet cognitive behaviour therapy (ICBT) is efficacious in the treatment of depression and anxiety. Given this research, there is a growing interest in training students in therapist-assisted ICBT in order to assist with the dissemination of this emerging modality into routine clinical practice. In this study, we developed, delivered, and evaluated a therapist-assisted ICBT workshop for clinical psychology graduate students (n = 20). The workshop provided both research evidence and practical information related to the delivery of therapist-assisted ICBT. The workshop also incorporated an experiential component with students working on and discussing responses to client e-mails. Before and after the workshop, we measured knowledge of therapist-assisted ICBT research and professional practice issues, as well as attitudes towards and confidence in delivering therapist-assisted ICBT. Statistically significant changes were observed in all areas. Eighty-five per cent of students are now offering therapist-assisted ICBT under supervision. We conclude by discussing future research directions related to disseminating therapist-assisted ICBT.

An adaptive approach to information discovery in multi-dimensional wireless sensor networks

Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multidimensional data). Such networks present unique challenges to data dissemination, data storage and in-network query processing (information discovery). In this paper, we investigate efficient strategies for information discovery in large-scale multidimensional WSNs and propose the Adaptive MultiDimensional Multi-Resolution Architecture (A-MDMRA) that efficiently combines “push” and “pull” strategies for information discovery and adapts to variations in the frequencies of events and queries in the network to construct optimal routing structures. We present simulation results showing the optimal routing structure depends on the frequency of events and query occurrence in the network. It also balances push and pull operations in large scale networks enabling significant QoS improvements and energy savings.

The communication of diabetes health campaign information in remote Botswana

This study was essentially about health promotion, and specifically about diabetes health campaigns in remote rural villages of Botswana. Its overall objective was to explore whether or not diabetes campaign messages were communicated in ways that were beneficial to remote villagers in Botswana. It was driven by social constructionist scholarship which emphasizes embedding the dissemination of information within the socio-cultural context, norms and value systems of target audiences.

A block-aware hybrid data dissemination with hotspot elimination in wireless sensor network

As a significant milestone in the data dissemination of wireless sensor networks (WSNs), the comb-needle (CN) model was developed to dynamically balance the sensor data pushing and pulling during hybrid data dissemination. Unfortunately, the hybrid push-pull data dissemination strategy may overload some sensor nodes and form the hotspots that consume energy significantly. This usually leads to the collapse of the network at a very early stage. In the past decade, although many energy-aware dynamic data dissemination methods have been proposed to alleviate the hotspots issue, the block characteristic of sensor nodes has been overlooked and how to offload traffic from hot blocks with low energy through long-distance hybrid dissemination remains an open problem. In this paper, we developed a block-aware data dissemination model to balance the inter-block energy and eliminate the spreading of intra-block hotspots. Through the clustering mechanism based on geography and energy, "similar" large-scale sensor nodes can be efficiently grouped into specific blocks to form the global block information (GBI). Based on GBI, the long-distance block-cross hybrid algorithms are further developed by effectively aggregating inter-block and intra-block data disseminations. Extensive experimental results demonstrate the capability and the efficiency of the proposed approach. © 2014 Elsevier Ltd.

Energy efficient information discovery approach for range queries in multi-dimensional WSNs

Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multi-dimensional data). Such networks present unique challenges to data dissemination, data storage and in-network query processing (information discovery). Recent algorithms proposed for such WSNs are aimed at achieving better energy efficiency and minimizing latency. This creates a partitioned network area due to the overuse of certain nodes in areas which are on the shortest or closest or path to the base station or data aggregation points which results in hotspots nodes. In this paper, we propose a time-based multi-dimensional, multi-resolution storage approach for range queries that balances the energy consumption by balancing the traffic load as uniformly as possible. Thus ensuring a maximum network lifetime. We present simulation results to show that the proposed approach to information discovery offers significant improvements on information discovery latency compared with current approaches. In addition, the results prove that the Quality of Service (QoS) improvements reduces hotspots thus resulting in significant network-wide energy saving and an increased network lifetime.