501 resultados para Personal data
Resumo:
In daily activities people are using a number of available means for the achievement of balance, such as the use of hands and the co-ordination of balance. One of the approaches that explains this relationship between perception and action is the ecological theory that is based on the work of a) Bernstein (1967), who imposed the problem of ‘the degrees of freedom’, b) Gibson (1979), who referred to the theory of perception and the way which the information is received from the environment in order for a certain movement to be achieved, c) Newell (1986), who proposed that movement can derive from the interaction of the constraints that imposed from the environment and the organism and d) Kugler, Kelso and Turvey (1982), who showed the way which “the degrees of freedom” are connected and interact. According to the above mentioned theories, the development of movement co-ordination can result from the different constraints that imposed into the organism-environment system. The close relation between the environmental and organismic constraints, as well as their interaction is responsible for the movement system that will be activated. These constraints apart from shaping the co-ordination of specific movements can be a rate limiting factor, to a certain degree, in the acquisition and mastering of a new skill. This frame of work can be an essential tool for the study of catching an object (e.g., a ball). The importance of this study becomes obvious due to the fact that movements that involved in catching an object are representative of every day actions and characteristic of the interaction between perception and action.
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This paper explores how people communicate in reference to local interests and suggests information and communication technology (ICT) design for enhancement of local community networks. Qualitative data was gathered from participant observations of local community collective action and open interviews with active community members. Data analysis revealed concepts, leading to categories in relation to local interactions and interests. Design suggestions consider introducing people to local community private-strategic activity via public displays that indicate simple entry points to active participation, and creating information collections according to local community perspectives for long-term reference.
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PURPOSE: To introduce techniques for deriving a map that relates visual field locations to optic nerve head (ONH) sectors and to use the techniques to derive a map relating Medmont perimetric data to data from the Heidelberg Retinal Tomograph. METHODS: Spearman correlation coefficients were calculated relating each visual field location (Medmont M700) to rim area and volume measures for 10 degrees ONH sectors (HRT III software) for 57 participants: 34 with glaucoma, 18 with suspected glaucoma, and 5 with ocular hypertension. Correlations were constrained to be anatomically plausible with a computational model of the axon growth of retinal ganglion cells (Algorithm GROW). GROW generated a map relating field locations to sectors of the ONH. The sector with the maximum statistically significant (P < 0.05) correlation coefficient within 40 degrees of the angle predicted by GROW for each location was computed. Before correlation, both functional and structural data were normalized by either normative data or the fellow eye in each participant. RESULTS: The model of axon growth produced a 24-2 map that is qualitatively similar to existing maps derived from empiric data. When GROW was used in conjunction with normative data, 31% of field locations exhibited a statistically significant relationship. This significance increased to 67% (z-test, z = 4.84; P < 0.001) when both field and rim area data were normalized with the fellow eye. CONCLUSIONS: A computational model of axon growth and normalizing data by the fellow eye can assist in constructing an anatomically plausible map connecting visual field data and sectoral ONH data.
Error, Bias, and Long-Branch Attraction in Data for Two Chloroplast Photosystem Genes in Seed Plants
Resumo:
Sequences of two chloroplast photosystem genes, psaA and psbB, together comprising about 3,500 bp, were obtained for all five major groups of extant seed plants and several outgroups among other vascular plants. Strongly supported, but significantly conflicting, phylogenetic signals were obtained in parsimony analyses from partitions of the data into first and second codon positions versus third positions. In the former, both genes agreed on a monophyletic gymnosperms, with Gnetales closely related to certain conifers. In the latter, Gnetales are inferred to be the sister group of all other seed plants, with gymnosperms paraphyletic. None of the data supported the modern ‘‘anthophyte hypothesis,’’ which places Gnetales as the sister group of flowering plants. A series of simulation studies were undertaken to examine the error rate for parsimony inference. Three kinds of errors were examined: random error, systematic bias (both properties of finite data sets), and statistical inconsistency owing to long-branch attraction (an asymptotic property). Parsimony reconstructions were extremely biased for third-position data for psbB. Regardless of the true underlying tree, a tree in which Gnetales are sister to all other seed plants was likely to be reconstructed for these data. None of the combinations of genes or partitions permits the anthophyte tree to be reconstructed with high probability. Simulations of progressively larger data sets indicate the existence of long-branch attraction (statistical inconsistency) for third-position psbB data if either the anthophyte tree or the gymnosperm tree is correct. This is also true for the anthophyte tree using either psaA third positions or psbB first and second positions. A factor contributing to bias and inconsistency is extremely short branches at the base of the seed plant radiation, coupled with extremely high rates in Gnetales and nonseed plant outgroups. M. J. Sanderson,* M. F. Wojciechowski,*† J.-M. Hu,* T. Sher Khan,* and S. G. Brady
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There exists a general consensus in the science education literature around the goal of enhancing students. and teachers. views of nature of science (NOS). An emerging area of research in science education explores NOS and argumentation, and the aim of this study was to explore the effectiveness of a science content course incorporating explicit NOS and argumentation instruction on preservice primary teachers. views of NOS. A constructivist perspective guided the study, and the research strategy employed was case study research. Five preservice primary teachers were selected for intensive investigation in the study, which incorporated explicit NOS and argumentation instruction, and utilised scientific and socioscientific contexts for argumentation to provide opportunities for participants to apply their NOS understandings to their arguments. Four primary sources of data were used to provide evidence for the interpretations, recommendations, and implications that emerged from the study. These data sources included questionnaires and surveys, interviews, audio- and video-taped class sessions, and written artefacts. Data analysis involved the formation of various assertions that informed the major findings of the study, and a variety of validity and ethical protocols were considered during the analysis to ensure the findings and interpretations emerging from the data were valid. Results indicated that the science content course was effective in enabling four of the five participants. views of NOS to be changed. All of the participants expressed predominantly limited views of the majority of the examined NOS aspects at the commencement of the study. Many positive changes were evident at the end of the study with four of the five participants expressing partially informed and/or informed views of the majority of the examined NOS aspects. A critical analysis of the effectiveness of the various course components designed to facilitate the development of participants‟ views of NOS in the study, led to the identification of three factors that mediated the development of participants‟ NOS views: (a) contextual factors (including context of argumentation, and mode of argumentation), (b) task-specific factors (including argumentation scaffolds, epistemological probes, and consideration of alternative data and explanations), and (c) personal factors (including perceived previous knowledge about NOS, appreciation of the importance and utility value of NOS, and durability and persistence of pre-existing beliefs). A consideration of the above factors informs recommendations for future studies that seek to incorporate explicit NOS and argumentation instruction as a context for learning about NOS.
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We surveyed 506 Australian high school students on career development (exploration, planning, job-knowledge, decision-making, indecision), personal functioning (well-being, self-esteem, life satisfaction, school satisfaction) and control variables (parents’ education, school achievement), and tested differences among work-bound, college-bound and university-bound students. The work-bound students had the poorest career development and personal functioning, the university-bound students the highest, with the college-bound students falling in-between the other two groups. Work-bound students did poorest, even after controlling for parental education and school achievement. The results suggest a relationship between career development and personal functioning in high school students.
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This thesis reports the outcomes of an investigation into students’ experience of Problem-based learning (PBL) in virtual space. PBL is increasingly being used in many fields including engineering education. At the same time many engineering education providers are turning to online distance education. Unfortunately there is a dearth of research into what constitutes an effective learning experience for adult learners who undertake PBL instruction through online distance education. Research was therefore focussed on discovering the qualitatively different ways that students experience PBL in virtual space. Data was collected in an electronic environment from a course, which adopted the PBL strategy and was delivered entirely in virtual space. Students in this course were asked to respond to open-ended questions designed to elicit their learning experience in the course. Data was analysed using the phenomenographical approach. This interpretative research method concentrated on mapping the qualitative differences in students’ interpretations of their experience in the course. Five qualitatively different ways of experiencing were discovered: Conception 1: ‘A necessary evil for program progression’; Conception 2: ‘Developing skills to understand, evaluate, and solve technical Engineering and Surveying problems’; Conception 3: ‘Developing skills to work effectively in teams in virtual space’; Conception 4: ‘A unique approach to learning how to learn’; Conception 5: ‘Enhancing personal growth’. Each conception reveals variation in how students attend to learning by PBL in virtual space. Results indicate that the design of students’ online learning experience was responsible for making students aware of deeper ways of experiencing PBL in virtual space. Results also suggest that the quality and quantity of interaction with the team facilitator may have a significant impact on the student experience in virtual PBL courses. The outcomes imply pedagogical strategies can be devised for shifting students’ focus as they engage in the virtual PBL experience to effectively manage the student learning experience and thereby ensure that they gain maximum benefit. The results from this research hold important ramifications for graduates with respect to their ease of transition into professional work as well as their later professional competence in terms of problem solving, ability to transfer basic knowledge to real-life engineering scenarios, ability to adapt to changes and apply knowledge in unusual situations, ability to think critically and creatively, and a commitment to continuous life-long learning and self-improvement.
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With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.
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We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.
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• Introduction: Concern and action for rural road safety is relatively new in Australia in comparison to the field of traffic safety as a whole. In 2003, a program of research was begun by the Centre for Accident Research and Road Safety - Queensland (CARRS-Q) and the Rural Health Research Unit (RHRU) at James Cook University to investigate factors contributing to serious rural road crashes in the North Queensland region. This project was funded by the Premier’s Department, Main Roads Department, Queensland Transport, QFleet, Queensland Rail, Queensland Ambulance Service, Department of Natural Resources and Queensland Police Service. Additional funding was provided by NRMA Insurance for a PhD scholarship. In-kind support was provided through the four hospitals used for data collection, namely Cairns Base Hospital, The Townsville Hospital, Mount Isa Hospital and Atherton Hospital.----- The primary aim of the project was to: Identify human factors related to the occurrence of serious traffic incidents in rural and remote areas of Australia, and to the trauma suffered by persons as a result of these incidents, using a sample drawn from a rural and remote area in North Queensland.----- The data and analyses presented in this report are the core findings from two broad studies: a general examination of fatalities and casualties from rural and remote crashes for the period 1 March 2004 until 30 June 2007, and a further linked case-comparison study of hospitalised patients compared with a sample of non-crash-involved drivers.----- • Method: The study was undertaken in rural North Queensland, as defined by the Australian Bureau of Statistics (ABS) statistical divisions of North Queensland, Far North Queensland and North-West Queensland. Urban areas surrounding Townsville, Thuringowa and Cairns were not included. The study methodology was centred on serious crashes, as defined by a resulting hospitalisation for 24 hours or more and/or a fatality. Crashes meeting this criteria within the North Queensland region between 1 March 2004 and 30 June 2007 were identified through hospital records and interviewed where possible. Additional data was sourced from coroner’s reports, the Queensland Transport road crash database, the Queensland Ambulance Service and the study hospitals in the region.----- This report is divided into chapters corresponding to analyses conducted on the collected crash and casualty data.----- Chapter 3 presents an overview of all crashes and casualties identified during the study period. Details are presented in regard to the demographics and road user types of casualties; the locations, times, types, and circumstances of crashes; along with the contributing circumstances of crashes.----- Chapter 4 presents the results of summary statistics for all casualties for which an interview was able to be conducted. Statistics are presented separately for drivers and riders, passengers, pedestrians and cyclists. Details are also presented separately for drivers and riders crashing in off-road and on-road settings. Results from questionnaire data are presented in relation to demographics; the experience of the crash in narrative form; vehicle characteristics and maintenance; trip characteristics (e.g. purpose and length of journey; periods of fatigue and monotony; distractions from driving task); driving history; alcohol and drug use; medical history; driving attitudes, intentions and behaviour; attitudes to enforcement; and experience of road safety advertising.----- Chapter 5 compares the above-listed questionnaire results between on-road crash-involved casualties and interviews conducted in the region with non-crash-involved persons. Direct comparisons as well as age and sex adjusted comparisons are presented.----- Chapter 6 presents information on those casualties who were admitted to one of the study hospitals during the study period. Brief information is given regarding the demographic characteristics of these casualties. Emergency services’ data is used to highlight the characteristics of patient retrieval and transport to and between hospitals. The major injuries resulting from the crashes are presented for each region of the body and analysed by vehicle type, occupant type, seatbelt status, helmet status, alcohol involvement and nature of crash. Estimates are provided of the costs associated with in-hospital treatment and retrieval.----- Chapter 7 describes the characteristics of the fatal casualties and the nature and circumstances of the crashes. Demographics, road user types, licence status, crash type and contributing factors for crashes are presented. Coronial data is provided in regard to contributing circumstances (including alcohol, drugs and medical conditions), cause of death, resulting injuries, and restraint and helmet use.----- Chapter 8 presents the results of a comparison between casualties’ crash descriptions and police-attributed crash circumstances. The relative frequency of contributing circumstances are compared both broadly within the categories of behavioural, environmental, vehicle related, medical and other groupings and specifically for circumstances within these groups.----- Chapter 9 reports on the associated research projects which have been undertaken on specific topics related to rural road safety.----- Finally, Chapter 10 reports on the conclusions and recommendations made from the program of research.---- • Major Recommendations : From the findings of these analyses, a number of major recommendations were made: + Male drivers and riders - Male drivers and riders should continue to be the focus of interventions, given their very high representation among rural and remote road crash fatalities and serious injuries.----- - The group of males aged between 30 and 50 years comprised the largest number of casualties and must also be targeted for change if there is to be a meaningful improvement in rural and remote road safety.----- + Motorcyclists - Single vehicle motorcycle crashes constitute over 80% of serious, on-road rural motorcycle crashes and need particular attention in development of policy and infrastructure.----- - The motorcycle safety consultation process currently being undertaken by Queensland Transport (via the "Motorbike Safety in Queensland - Consultation Paper") is strongly endorsed. As part of this process, particular attention needs to be given to initiatives designed to reduce rural and single vehicle motorcycle crashes.----- - The safety of off-road riders is a serious problem that falls outside the direct responsibility of either Transport or Health departments. Responsibility for this issue needs to be attributed to develop appropriate policy, regulations and countermeasures.----- + Road safety for Indigenous people - Continued resourcing and expansion of The Queensland Aboriginal Peoples and Torres Strait Islander Peoples Driver Licensing Program to meet the needs of remote and Indigenous communities with significantly lower licence ownership levels.----- - Increased attention needs to focus on the contribution of geographic disadvantage (remoteness) factors to remote and Indigenous road trauma.----- + Road environment - Speed is the ‘final common pathway’ in determining the severity of rural and remote crashes and rural speed limits should be reduced to 90km/hr for sealed off-highway roads and 80km/hr for all unsealed roads as recommended in the Austroads review and in line with the current Tasmanian government trial.----- - The Department of Main Roads should monitor rural crash clusters and where appropriate work with local authorities to conduct relevant audits and take mitigating action. - The international experts at the workshop reviewed the data and identified the need to focus particular attention on road design management for dangerous curves. They also indicated the need to maximise the use of audio-tactile linemarking (audible lines) and rumble strips to alert drivers to dangerous conditions and behaviours.----- + Trauma costs - In accordance with Queensland Health priorities, recognition should be given to the substantial financial costs associated with acute management of trauma resulting from serious rural and remote crashes.----- - Efforts should be made to develop a comprehensive, regionally specific costing formula for road trauma that incorporates the pre-hospital, hospital and post-hospital phases of care. This would inform health resource allocation and facilitate the evaluation of interventions.----- - The commitment of funds to the development of preventive strategies to reduce rural and remote crashes should take into account the potential cost savings associated with trauma.----- - A dedicated study of the rehabilitation needs and associated personal and healthcare costs arising from rural and remote road crashes should be undertaken.----- + Emergency services - While the study has demonstrated considerable efficiency in the response and retrieval systems of rural and remote North Queensland, relevant Intelligent Transport Systems technologies (such as vehicle alarm systems) to improve crash notification should be both developed and evaluated.----- + Enforcement - Alcohol and speed enforcement programs should target the period between 2 and 6pm because of the high numbers of crashes in the afternoon period throughout the rural region.----- + Drink driving - Courtesy buses should be advocated and schemes such as the Skipper project promoted as local drink driving countermeasures in line with the very high levels of community support for these measures identified in the hospital study.------ - Programs should be developed to target the high levels of alcohol consumption identified in rural and remote areas and related involvement in crashes.----- - Referrals to drink driving rehabilitation programs should be mandated for recidivist offenders.----- + Data requirements - Rural and remote road crashes should receive the same quality of attention as urban crashes. As such, it is strongly recommended that increased resources be committed to enable dedicated Forensic Crash Units to investigate rural and remote fatal and serious injury crashes.----- - Transport department records of rural and remote crashes should record the crash location using the national ARIA area classifications used by health departments as a means to better identifying rural crashes.----- - Rural and remote crashes tend to be unnoticed except in relatively infrequent rural reviews. They should receive the same level of attention and this could be achieved if fatalities and fatal crashes were coded by the ARIA classification system and included in regular crash reporting.----- - Health, Transport and Police agencies should collect a common, minimal set of data relating to road crashes and injuries, including presentations to small rural and remote health facilities.----- + Media and community education programmes - Interventions seeking to highlight the human contribution to crashes should be prioritised. Driver distraction, alcohol and inappropriate speed for the road conditions are key examples of such behaviours.----- - Promotion of basic safety behaviours such as the use of seatbelts and helmets should be given a renewed focus.----- - Knowledge, attitude and behavioural factors that have been identified for the hospital Brief Intervention Trial should be considered in developing safety campaigns for rural and remote people. For example challenging the myth of the dangerous ‘other’ or ‘non-local’ driver.----- - Special educational initiatives on the issues involved in rural and remote driving should be undertaken. For example the material used by Main Roads, the Australian Defence Force and local initiatives.
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Perceptual aliasing makes topological navigation a difficult task. In this paper we present a general approach for topological SLAM~(simultaneous localisation and mapping) which does not require motion or odometry information but only a sequence of noisy measurements from visited places. We propose a particle filtering technique for topological SLAM which relies on a method for disambiguating places which appear indistinguishable using neighbourhood information extracted from the sequence of observations. The algorithm aims to induce a small topological map which is consistent with the observations and simultaneously estimate the location of the robot. The proposed approach is evaluated using a data set of sonar measurements from an indoor environment which contains several similar places. It is demonstrated that our approach is capable of dealing with severe ambiguities and, and that it infers a small map in terms of vertices which is consistent with the sequence of observations.
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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
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This study investigated the mediating effect of learner selfconcept between conceptions of learning and students' approaches to learning using structural equation modelling. Data were collected using a modified version of Biggs' Learning Process Questionnaire, together with the recently developed 'What is Learning Survey' and 'Learner Self-Concept Scale'. A sample of 355 high school students participated in the study. Results indicate that learner self-concept does mediate between conceptions of meaning and approaches to learning. Students who adopted a deep approach liked learning new things and indirectly viewed learning as experiential, involving social interaction and directly viewed learning as personal development. Implications for teachers are discussed, with consideration given to appropriate classroom practice.
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Vibration based damage identification methods examine the changes in primary modal parameters or quantities derived from modal parameters. As one method may have advantages over the other under some circumstances, a multi-criteria approach is proposed. Case studies are conducted separately on beam, plate and plate-on-beam structures. Using the numerically simulated modal data obtained through finite element analysis software, algorithms based on flexibility and strain energy changes before and after damage are obtained and used as the indices for the assessment of the state of structural health. Results show that the proposed multi-criteria method is effective in damage identification in these structures.
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The construction industry has adapted information technology in its processes in terms of computer aided design and drafting, construction documentation and maintenance. The data generated within the construction industry has become increasingly overwhelming. Data mining is a sophisticated data search capability that uses classification algorithms to discover patterns and correlations within a large volume of data. This paper presents the selection and application of data mining techniques on maintenance data of buildings. The results of applying such techniques and potential benefits of utilising their results to identify useful patterns of knowledge and correlations to support decision making of improving the management of building life cycle are presented and discussed.