Damage diagnosis for complex steel truss bridges using multi-layer genetic algorithm

Considerate amount of research has proposed optimization-based approaches employing various vibration parameters for structural damage diagnosis. The damage detection by these methods is in fact a result of updating the analytical structural model in line with the current physical model. The feasibility of these approaches has been proven. But most of the verification has been done on simple structures, such as beams or plates. In the application on a complex structure, like steel truss bridges, a traditional optimization process will cost massive computational resources and lengthy convergence. This study presents a multi-layer genetic algorithm (ML-GA) to overcome the problem. Unlike the tedious convergence process in a conventional damage optimization process, in each layer, the proposed algorithm divides the GA’s population into groups with a less number of damage candidates; then, the converged population in each group evolves as an initial population of the next layer, where the groups merge to larger groups. In a damage detection process featuring ML-GA, as parallel computation can be implemented, the optimization performance and computational efficiency can be enhanced. In order to assess the proposed algorithm, the modal strain energy correlation (MSEC) has been considered as the objective function. Several damage scenarios of a complex steel truss bridge’s finite element model have been employed to evaluate the effectiveness and performance of ML-GA, against a conventional GA. In both single- and multiple damage scenarios, the analytical and experimental study shows that the MSEC index has achieved excellent damage indication and efficiency using the proposed ML-GA, whereas the conventional GA only converges at a local solution.

Modelling users' contextual querying behaviour for web image searching

The rapid growth of visual information on Web has led to immense interest in multimedia information retrieval (MIR). While advancement in MIR systems has achieved some success in specific domains, particularly the content-based approaches, general Web users still struggle to find the images they want. Despite the success in content-based object recognition or concept extraction, the major problem in current Web image searching remains in the querying process. Since most online users only express their needs in semantic terms or objects, systems that utilize visual features (e.g., color or texture) to search images create a semantic gap which hinders general users from fully expressing their needs. In addition, query-by-example (QBE) retrieval imposes extra obstacles for exploratory search because users may not always have the representative image at hand or in mind when starting a search (i.e. the page zero problem). As a result, the majority of current online image search engines (e.g., Google, Yahoo, and Flickr) still primarily use textual queries to search. The problem with query-based retrieval systems is that they only capture users’ information need in terms of formal queries;; the implicit and abstract parts of users’ information needs are inevitably overlooked. Hence, users often struggle to formulate queries that best represent their needs, and some compromises have to be made. Studies of Web search logs suggest that multimedia searches are more difficult than textual Web searches, and Web image searching is the most difficult compared to video or audio searches. Hence, online users need to put in more effort when searching multimedia contents, especially for image searches. Most interactions in Web image searching occur during query reformulation. While log analysis provides intriguing views on how the majority of users search, their search needs or motivations are ultimately neglected. User studies on image searching have attempted to understand users’ search contexts in terms of users’ background (e.g., knowledge, profession, motivation for search and task types) and the search outcomes (e.g., use of retrieved images, search performance). However, these studies typically focused on particular domains with a selective group of professional users. General users’ Web image searching contexts and behaviors are little understood although they represent the majority of online image searching activities nowadays. We argue that only by understanding Web image users’ contexts can the current Web search engines further improve their usefulness and provide more efficient searches. In order to understand users’ search contexts, a user study was conducted based on university students’ Web image searching in News, Travel, and commercial Product domains. The three search domains were deliberately chosen to reflect image users’ interests in people, time, event, location, and objects. We investigated participants’ Web image searching behavior, with the focus on query reformulation and search strategies. Participants’ search contexts such as their search background, motivation for search, and search outcomes were gathered by questionnaires. The searching activity was recorded with participants’ think aloud data for analyzing significant search patterns. The relationships between participants’ search contexts and corresponding search strategies were discovered by Grounded Theory approach. Our key findings include the following aspects: - Effects of users' interactive intents on query reformulation patterns and search strategies - Effects of task domain on task specificity and task difficulty, as well as on some specific searching behaviors - Effects of searching experience on result expansion strategies A contextual image searching model was constructed based on these findings. The model helped us understand Web image searching from user perspective, and introduced a context-aware searching paradigm for current retrieval systems. A query recommendation tool was also developed to demonstrate how users’ query reformulation contexts can potentially contribute to more efficient searching.

Automatic query expansion : a structural linguistic perspective

A user’s query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques ignore information about the dependencies that exist between words in natural language. However, more recent approaches have demonstrated that by explicitly modeling associations between terms significant improvements in retrieval effectiveness can be achieved over those that ignore these dependencies. State-of-the-art dependency-based approaches have been shown to primarily model syntagmatic associations. Syntagmatic associations infer a likelihood that two terms co-occur more often than by chance. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process will improve retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.

Multimodality, media, and access to multiliteracies

In many English-speaking countries bilingual and multilingual speakers of English are integrated into mainstream classrooms, where the teacher is expected to help them “catch up” with speakers of the dominant language. In this presentation, I argue that we teach in culturally and linguistically diverse societies that are increasingly interconnected through a broadened range of multimodal and digital textual practices. Intuitively, one might expect that multimodal approaches are more equitable than exclusively print-based approaches because learners can draw from a broader range of semiotic resources. Yet the potentials of using multiple modes and new digital media to provide greater access to multiliteracies cannot be assumed. I draw on a case study of a multilingual language learner, Paweni, a Thai immigrant, describing how she and her peers negotiated cultural and linguistic difference. These encounters occur during multiliteracies lessons involving both print and digital texts. I theorise a “dialectic of access” to explain the reciprocal interaction between the agency of learners, modes, and media. I apply Giddens’ structuration theory to take into account the social structures – domination, signification, and legitimation – that played an important role in this dialectic of access.

Term associations in query expansion : a structural linguistic perspective

Many successful query expansion techniques ignore information about the term dependencies that exist within natural language. However, researchers have recently demonstrated that consistent and significant improvements in retrieval effectiveness can be achieved by explicitly modelling term dependencies within the query expansion process. This has created an increased interest in dependency-based models. State-of-the-art dependency-based approaches primarily model term associations known within structural linguistics as syntagmatic associations, which are formed when terms co-occur together more often than by chance. However, structural linguistics proposes that the meaning of a word is also dependent on its paradigmatic associations, which are formed between words that can substitute for each other without effecting the acceptability of a sentence. Given the reliance on word meanings when a user formulates their query, our approach takes the novel step of modelling both syntagmatic and paradigmatic associations within the query expansion process based on the (pseudo) relevant documents returned in web search. The results demonstrate that this approach can provide significant improvements in web re- trieval effectiveness when compared to a strong benchmark retrieval system.

Dynamic robot path planning using an enhanced simulated annealing approach

Evolutionary computation is an effective tool for solving optimization problems. However, its significant computational demand has limited its real-time and on-line applications, especially in embedded systems with limited computing resources, e.g., mobile robots. Heuristic methods such as the genetic algorithm (GA) based approaches have been investigated for robot path planning in dynamic environments. However, research on the simulated annealing (SA) algorithm, another popular evolutionary computation algorithm, for dynamic path planning is still limited mainly due to its high computational demand. An enhanced SA approach, which integrates two additional mathematical operators and initial path selection heuristics into the standard SA, is developed in this work for robot path planning in dynamic environments with both static and dynamic obstacles. It improves the computing performance of the standard SA significantly while giving an optimal or near-optimal robot path solution, making its real-time and on-line applications possible. Using the classic and deterministic Dijkstra algorithm as a benchmark, comprehensive case studies are carried out to demonstrate the performance of the enhanced SA and other SA algorithms in various dynamic path planning scenarios.

Humorous health messages : "a fresh approach" for road safety advertising campaigns?

Theoretical Background and research questions/hypothesis: Recently, throughout Australasia, humorous appeals have become implemented increasingly in health advertising despite limited evidence regarding the persuasiveness of different types of humour. Of those studies available which have examined the persuasiveness of humorous messages, the type of humour is often not defined so it is unclear what type of humour is being examined. Speck’s (1991) typology includes five types of humour; comic wit, sentimental humour, satire, sentimental comedy, and full comedy. Each type of humour is based on one or more humour generation processes; namely, incongruity-resolution, disparagement humour, and arousal-safety. It has been acknowledged that more research is needed to determine the relative persuasiveness of these different types of humour and to identify those types which may be most effective for health advertising. The current research explored individuals’ thoughts about, and their responses to some different types of, humorous messages addressing the serious health topic of road safety. Methods: A preliminary qualitative, study was conducted involving discussions with licensed drivers (N = 18) regarding their thoughts and feelings about humorous road safety messages in general as well as in response to some (5 in total) pre-existing advertisements. Men (n = 10) and women of younger and older age groups (17-24 or 25+ years) participated in one of six discussions. Participants were recruited from an existing community-based database held by the authors’ Research Centre or were approached directly on the university campus. Ethical approval was gained for the study. Each participant was offered $AUD40. A semi-structured interview schedule guided the discussion (e.g., was it humorous?, would this ad influence you?). Audio-recordings of the discussions were professionally transcribed and the transcripts were analysed using thematic analysis. Results: The findings revealed that, irrespective of age and gender, humour that was clever, incorporated something unexpected and contrasting with the everyday, was a preferred and relevant approach, thus aligning with incongruity-based theories of humour generation and humour types, such as comic wit and satire. As a persuasive function, humorous messages were considered likely to be talked about (and relatively more so than traditional fear-based approaches). Participants also felt that humorous messages would need to be used cautiously as humour that was considered inappropriate and/or associated with serious occurrences, such as a crash, would be unlikely to persuade. Conclusions: The findings highlight some of the potential benefits of using humour, such as increasing the extent to which an advertisement is talked about as well as the types of humour which may be effective in this context. Implications for research and/or practice: While this research has provided important insight, future research which quantitatively assesses the persuasive effects of different types of humorous road safety messages within a larger, representative sample is needed. This current study has highlighted some humorous approaches which may hold persuasive promise in encouraging individuals to adopt safer attitudes and behaviours not only on the road, but in relation to serious health issues more broadly.

Recognising team activities from noisy data

Recently, vision-based systems have been deployed in professional sports to track the ball and players to enhance analysis of matches. Due to their unobtrusive nature, vision-based approaches are preferred to wearable sensors (e.g. GPS or RFID sensors) as it does not require players or balls to be instrumented prior to matches. Unfortunately, in continuous team sports where players need to be tracked continuously over long-periods of time (e.g. 35 minutes in field-hockey or 45 minutes in soccer), current vision-based tracking approaches are not reliable enough to provide fully automatic solutions. As such, human intervention is required to fix-up missed or false detections. However, in instances where a human can not intervene due to the sheer amount of data being generated - this data can not be used due to the missing/noisy data. In this paper, we investigate two representations based on raw player detections (and not tracking) which are immune to missed and false detections. Specifically, we show that both team occupancy maps and centroids can be used to detect team activities, while the occupancy maps can be used to retrieve specific team activities. An evaluation on over 8 hours of field hockey data captured at a recent international tournament demonstrates the validity of the proposed approach.

Back to the future

In the field of education, explicit instruction refers to teacher-­‐centred instruction that is focused on clear behavioural and cognitive goals and outcomes. These in turn are made ‘explicit’ or transparent to learners. Sociologist Basil Bernstein defined explicit instruction as featuring “strong classification” and “strong framing”: clearly defined and boundaried knowledge and skills, and teacher-­‐directed interaction. Explicit instruction is affiliated with but not limited to highly structured, instruction in basic skills in early literacy and numeracy education. It is also used in Australian genre-­‐based approaches to writing that stress the value of “explicit” knowledge of grammar and all textual codes. Several major meta-­‐analyses and reviews have identified explicit instruction as a major instructional approach in contemporary schooling...

Digital storytelling as a social work tool : learning from ethnographic research with women from refugee backgrounds

This paper reflects on the wider potential of digital narratives as a useful tool for social work practitioners. Despite the multiple points of connection between narrative approaches and social work, the influence of narratives on practice remains limited. A case study of a digital storytelling (DST) process employed in a research project with a small group of lone mothers from refugee backgrounds is used to trigger discussion of broader applications of DST as part of everyday social work practice. The use of DST acknowledged women’s capacities for self-representation and agency, in line with participatory and strengths-based approaches inherent in contemporary social work. The benefits of using DST with lone mothers from refugee backgrounds illustrate how this method can act as a pathway to produce counter-narratives, both at the individual and broader community levels. Documenting life stories digitally provides the opportunity to construct narratives about experiences of relocation and settlement as tools for social advocacy, which can assist social workers to ensure meaningful outcomes for service-users. These propositions can serve to inform social work practices with people from refugee backgrounds and address some of the intricacies of working in diverse and challenging contexts.

In arrayed ranks array technology in the study of mesothelioma steven

Mesothelioma is a rare malignancy arising from mesothelial cells lining the pleura and peritoneum. Advances in modern technology have allowed the development of array based approaches to the study of disease allowing researchers the opportunity to study many genes or proteins in a high-throughput fashion. This review describes the current knowledge surrounding array based approaches with respect to mesothelioma research. © 2009 by the International Association for the Study of Lung Cancer.

Open access and scholarly books : Australian perspectives

This three-hour workshop tackles the crucial question of whether globally coordinated, market based approaches to funding open access monographs can support the unique needs of Australian research communities. The workshop takes place in the context of the release in August 2013 of the Book Industry Collaborative Council (BICC) report and especially the recommendations included in the chapter on scholarly book publishing in the humanities and social sciences. This workshop, with expert speakers from the BICC Committee and from across the scholarly publishing industry, will discuss the policy issues most likely to ensure that Australian scholarly communities and audiences are best served in an era of digital technology and globalisation. Australia must think globally and support developments that enhance the accessibility of publicly-funded research. Speakers will outline recent developments in scholarly monograph publishing including new Open Access initiatives and developments. Knowledge Unlatched, is one example of an attempt to create an internationally coordinated, market-based route to open access for Humanities, Arts and Social Sciences (HASS) monographs. Knowledge Unlatched, a not-for-profit London-based company is piloting a global library consortium approach to funding open access monographs and released its pilot program in early October with 28 titles from 13 publishers. The workshop invites discussion and debate from librarians, publishers, researchers and research funders on the role of international coordination and markets in securing a more open future for Australian HASS scholarship.

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.

The why dimension - opening frontiers for digital learning

Digital learning has come a long way from the days of simple 'if-then' queries. It is now enabled by countless innovations that support knowledge sharing, openness, flexibility, and independent inquiry. Set against an evolutionary context this study investigated innovations that directly support human inquiry. Specifically, it identified five activities that together are defined as the 'why dimension' – asking, learning, understanding, knowing, and explaining why. Findings highlight deficiencies in mainstream search-based approaches to inquiry, which tend to privilege the retrieval of information as distinct from explanation. Instrumental to sense-making, the 'why dimension' provides a conceptual framework for development of 'sense-making technologies'.

What is a good project manager? An Aristotelian perspective

The purpose of this paper is to take a critical look at the question “what is a competent project manager?” and bring some fresh added-value insights. This leads us to analyze the definitions, and assessment approaches of project manager competence. Three major standards as prescribed by PMI, IPMA, and GAPPS are considered for review from an attribute-based and performance-based approach and from a deontological and consequentialist ethics perspectives. Two fundamental tensions are identified: an ethical tension between the standards and the related competence assessment frameworks and a tension between attribute and performance-based approaches. Aristotelian ethical and practical philosophy is brought in to reconcile these differences. Considering ethics of character that rises beyond the normative deontological and consequentialist perspectives is suggested. Taking the mediating role of praxis and phrónêsis between theory and practice into consideration is advocated to resolve the tension between performance and attribute-based approaches to competence assessment.