Effects of wireless sensor network uncertainties on output-only modal-based damage identification

The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research examining effects of uncertainties of generic WSN platform and verifying the capability of SHM-oriented WSNs, particularly on demanding SHM applications like modal analysis and damage identification of real civil structures. This article first reviews the major technical uncertainties of both generic and SHM-oriented WSN platforms and efforts of SHM research community to cope with them. Then, effects of the most inherent WSN uncertainty on the first level of a common Output-only Modal-based Damage Identification (OMDI) approach are intensively investigated. Experimental accelerations collected by a wired sensory system on a benchmark civil structure are initially used as clean data before being contaminated with different levels of data pollutants to simulate practical uncertainties in both WSN platforms. Statistical analyses are comprehensively employed in order to uncover the distribution pattern of the uncertainty influence on the OMDI approach. The result of this research shows that uncertainties of generic WSNs can cause serious impact for level 1 OMDI methods utilizing mode shapes. It also proves that SHM-WSN can substantially lessen the impact and obtain truly structural information without having used costly computation solutions.

Perceptions of climate change and trust in information providers in rural Australia

Disagreement within the global science community about the certainty and causes of climate change has led the general public to question what to believe and who to trust on matters related to this issue. This paper reports on qualitative research undertaken with Australian residents from two rural areas to explore their perceptions of climate change and trust in information providers. While overall, residents tended to agree that climate change is a reality, perceptions varied in terms of its causes and how best to address it. Politicians, government, and the media were described as untrustworthy sources of information about climate change, with independent scientists being the most trusted. The vested interests of information providers appeared to be a key reason for their distrust. The findings highlight the importance of improved transparency and consultation with the public when communicating information about climate change and related policies.

Strategies and solutions for housing sustainability : building information files and performance certificates

The overall aim of this research project was to provide a broader range of value propositions (beyond upfront traditional construction costs) that could transform both the demand side and supply side of the housing industry. The project involved gathering information about how building information is created, used and communicated and classifying building information, leading to the formation of an Information Flow Chart and Stakeholder Relationship Map. These were then tested via broad housing industry focus groups and surveys. The project revealed four key relationships that appear to operate in isolation to the whole housing sector and may have significant impact on the sustainability outcomes and life cycle costs of dwellings over their life cycle. It also found that although a lot of information about individual dwellings does already exist, this information is not coordinated or inventoried in any systematic manner and that national building information files of building passports would present value to a wide range of stakeholders.

Pattern-based topics for document modelling in information filtering

Many mature term-based or pattern-based approaches have been used in the field of information filtering to generate users’ information needs from a collection of documents. A fundamental assumption for these approaches is that the documents in the collection are all about one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, and this has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering has not been so well explored. Patterns are always thought to be more discriminative than single terms for describing documents. However, the enormous amount of discovered patterns hinder them from being effectively and efficiently used in real applications, therefore, selection of the most discriminative and representative patterns from the huge amount of discovered patterns becomes crucial. To deal with the above mentioned limitations and problems, in this paper, a novel information filtering model, Maximum matched Pattern-based Topic Model (MPBTM), is proposed. The main distinctive features of the proposed model include: (1) user information needs are generated in terms of multiple topics; (2) each topic is represented by patterns; (3) patterns are generated from topic models and are organized in terms of their statistical and taxonomic features, and; (4) the most discriminative and representative patterns, called Maximum Matched Patterns, are proposed to estimate the document relevance to the user’s information needs in order to filter out irrelevant documents. Extensive experiments are conducted to evaluate the effectiveness of the proposed model by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models

Did you see that? Dissociating advanced visual information and ball flight constrains perception and action processes during one-handed catching

The integration of separate, yet complimentary, cortical pathways appears to play a role in visual perception and action when intercepting objects. The ventral system is responsible for object recognition and identification, while the dorsal system facilitates continuous regulation of action. This dual-system model implies that empirically manipulating different visual information sources during performance of an interceptive action might lead to the emergence of distinct gaze and movement pattern profiles. To test this idea, we recorded hand kinematics and eye movements of participants as they attempted to catch balls projected from a novel apparatus that synchronised or de-synchronised accompanying video images of a throwing action and ball trajectory. Results revealed that ball catching performance was less successful when patterns of hand movements and gaze behaviours were constrained by the absence of advanced perceptual information from the thrower's actions. Under these task constraints, participants began tracking the ball later, followed less of its trajectory, and adapted their actions by initiating movements later and moving the hand faster. There were no performance differences when the throwing action image and ball speed were synchronised or de-synchronised since hand movements were closely linked to information from ball trajectory. Results are interpreted relative to the two-visual system hypothesis, demonstrating that accurate interception requires integration of advanced visual information from kinematics of the throwing action and from ball flight trajectory.

Supplementary information : weighted tree kernels for sequence analysis

Genomic sequences are fundamentally text documents, admitting various representations according to need and tokenization. Gene expression depends crucially on binding of enzymes to the DNA sequence at small, poorly conserved binding sites, limiting the utility of standard pattern search. However, one may exploit the regular syntactic structure of the enzyme's component proteins and the corresponding binding sites, framing the problem as one of detecting grammatically correct genomic phrases. In this paper we propose new kernels based on weighted tree structures, traversing the paths within them to capture the features which underpin the task. Experimentally, we and that these kernels provide performance comparable with state of the art approaches for this problem, while offering significant computational advantages over earlier methods. The methods proposed may be applied to a broad range of sequence or tree-structured data in molecular biology and other domains.

Media and information literacy : policy and strategy guidelines

In the evolving knowledge societies of today, some people are overloaded with information, others are starved for information. Everywhere, people are yearning to freely express themselves,to actively participate in governance processes and cultural exchanges. Universally, there is a deep thirst to understand the complex world around us. Media and Information Literacy (MIL) is a basis for enhancing access to information and knowledge, freedom of expression, and quality education. It describes skills, and attitudes that are needed to value the functions of media and other information providers, including those on the Internet, in societies and to find, evaluate and produce information and media content; in other words, it covers the competencies that are vital for people to be effectively engaged in all aspects of development.

Tourism TV commercials : a delicate balance between aural and visual information load

This article content analyzes music in tourism TV commercials from 95 regions and countries to identify their general acoustic characteristics. The objective is to offer a general guideline in the postproduction of tourism TV commercials. It is found that tourism TV commercials tend to be produced in a faster tempo with beats per minute close to 120, which is rare to be found in general TV commercials. To compensate for the faster tempo (increased aural information load), less scenes (longer duration per scene) were edited into the footage. Production recommendations and future research are presented.

Learning information literacy

Introduction This paper reports on university students' experiences of learning information literacy. Method Phenomenography was selected as the research approach as it describes the experience from the perspective of the study participants, which in this case is a mixture of undergraduate and postgraduate students studying education at an Australian university. Semi-structured, one-on-one interviews were conducted with fifteen students. Analysis The interview transcripts were iteratively reviewed for similarities and differences in students' experiences of learning information literacy. Categories were constructed from an analysis of the distinct features of the experiences that students reported. The categories were grouped into a hierarchical structure that represents students' increasingly sophisticated experiences of learning information literacy. Results The study reveals that students experience learning information literacy in six ways: learning to find information; learning a process to use information; learning to use information to create a product; learning to use information to build a personal knowledge base; learning to use information to advance disciplinary knowledge; and learning to use information to grow as a person and to contribute to others. Conclusions Understanding the complexity of the concept of information literacy, and the collective and diverse range of ways students experience learning information literacy, enables academics and librarians to draw on the range of experiences reported by students to design academic curricula and information literacy education that targets more powerful ways of learning to find and use information.

Creating and sharing : teens' information practices in digital communities

Introduction In a connected world youth are participating in digital content creating communities. This paper introduces a description of teens' information practices in digital content creating and sharing communities. Method The research design was a constructivist grounded theory methodology. Seventeen interviews with eleven teens were collected and observation of their digital communities occurred over a two-year period. Analysis The data were analysed iteratively to describe teens' interactions with information through open and then focused coding. Emergent categories were shared with participants to confirm conceptual categories. Focused coding provided connections between conceptual categories resulting in the theory, which was also shared with participants for feedback. Results The paper posits a substantive theory of teens' information practices as they create and share content. It highlights that teens engage in the information actions of accessing, evaluating, and using information. They experienced information in five ways: participation, information, collaboration, process, and artefact. The intersection of enacting information actions and experiences of information resulted in five information practices: learning community, negotiating aesthetic, negotiating control, negotiating capacity, and representing knowledge. Conclusion This study contributes to our understanding of youth information actions, experiences, and practices. Further research into these communities might indicate what information practices are foundational to digital communities.

Mining specific features for acquiring user information needs

Term-based approaches can extract many features in text documents, but most include noise. Many popular text-mining strategies have been adapted to reduce noisy information from extracted features; however, text-mining techniques suffer from low frequency. The key issue is how to discover relevance features in text documents to fulfil user information needs. To address this issue, we propose a new method to extract specific features from user relevance feedback. The proposed approach includes two stages. The first stage extracts topics (or patterns) from text documents to focus on interesting topics. In the second stage, topics are deployed to lower level terms to address the low-frequency problem and find specific terms. The specific terms are determined based on their appearances in relevance feedback and their distribution in topics or high-level patterns. We test our proposed method with extensive experiments in the Reuters Corpus Volume 1 dataset and TREC topics. Results show that our proposed approach significantly outperforms the state-of-the-art models.

A sequential Monte Carlo framework for adaptive Bayesian model discrimination designs using mutual information

In this paper we present a unified sequential Monte Carlo (SMC) framework for performing sequential experimental design for discriminating between a set of models. The model discrimination utility that we advocate is fully Bayesian and based upon the mutual information. SMC provides a convenient way to estimate the mutual information. Our experience suggests that the approach works well on either a set of discrete or continuous models and outperforms other model discrimination approaches.

Transitioning from vocational education and training to university : strengthening information literacy through collaboration

"Students transitioning from vocational education and training (VET) to university can experience a number of challenges. This small research project explored the information literacy needs of VET and university students and how they differ. Students studying early childhood related VET and university courses reported differences in how and where they searched for information in their studies. These differences reflect the more practical focus of VET compared with the more academic and theoretical approach of university. The author proposes a framework of support that could be provided to transitioning students to enable them to develop the necessary information literacy skills for university study."--publisher website

"The Stratified Record upon Which We Set Our Feet" : The Spatial Turn and the Multilayering of History, Geography, and Geology

In Thomas Mann’s tetralogy of the 1930s and 1940s, Joseph and His Brothers, the narrator declares history is not only “that which has happened and that which goes on happening in time,” but it is also “the stratified record upon which we set our feet, the ground beneath us.” By opening up history to its spatial, geographical, and geological dimensions Mann both predicts and encapsulates the twentieth-century’s “spatial turn,” a critical shift that divested geography of its largely passive role as history’s “stage” and brought to the fore intersections between the humanities and the earth sciences. In this paper, I draw out the relationships between history, narrative, geography, and geology revealed by this spatial turn and the questions these pose for thinking about the disciplinary relationship between geography and the humanities. As Mann’s statement exemplifies, the spatial turn itself has often been captured most strikingly in fiction, and I would argue nowhere more so than in Graham Swift’s Waterland (1983) and Anne Michaels’s Fugitive Pieces (1996), both of which present space, place, and landscape as having a palpable influence on history and memory. The geographical/geological line that runs through both Waterland and Fugitive Pieces continues through Tim Robinson’s non-fictional, two-volume “topographical” history Stones of Aran. Robinson’s Stones of Aran—which is not history, not geography, and not literature, and yet is all three—constructs an imaginative geography that renders inseparable geography, geology, history, memory, and the act of writing.

A formalization of logical imaging for information retrieval using quantum theory

In this paper we introduce a formalization of Logical Imaging applied to IR in terms of Quantum Theory through the use of an analogy between states of a quantum system and terms in text documents. Our formalization relies upon the Schrodinger Picture, creating an analogy between the dynamics of a physical system and the kinematics of probabilities generated by Logical Imaging. By using Quantum Theory, it is possible to model more precisely contextual information in a seamless and principled fashion within the Logical Imaging process. While further work is needed to empirically validate this, the foundations for doing so are provided.