86 resultados para geographical database

em Deakin Research Online - Australia


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Background: Physical activity and sedentary behaviour in youth have been reported to vary by sex, age, weight status and country. However, supporting data are often self-reported and/or do not encompass a wide range of ages or geographical locations. This study aimed to describe objectively-measured physical activity and sedentary time patterns in youth. Methods: The International Children's Accelerometry Database (ICAD) consists of ActiGraph accelerometer data from 20 studies in ten countries, processed using common data reduction procedures. Analyses were conducted on 27,637 participants (2.8-18.4 years) who provided at least three days of valid accelerometer data. Linear regression was used to examine associations between age, sex, weight status, country and physical activity outcomes. Results: Boys were less sedentary and more active than girls at all ages. After 5 years of age there was an average cross-sectional decrease of 4.2 % in total physical activity with each additional year of age, due mainly to lower levels of light-intensity physical activity and greater time spent sedentary. Physical activity did not differ by weight status in the youngest children, but from age seven onwards, overweight/obese participants were less active than their normal weight counterparts. Physical activity varied between samples from different countries, with a 15-20 % difference between the highest and lowest countries at age 9-10 and a 26-28 % difference at age 12-13. Conclusions: Physical activity differed between samples from different countries, but the associations between demographic characteristics and physical activity were consistently observed. Further research is needed to explore environmental and sociocultural explanations for these differences.

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Use of geographical information systems (GIS) in inland fisheries has hitherto been essentially restricted to site evaluation for aquaculture development and assessment of limnological changes in time and space in individual water bodies. The present GIS study was conducted on the land-use pattern of the catchments of nine reservoirs in Sri Lanka, for which detailed fishery data, viz. yield, fishing intensity, landing size of major constituent species, together with selected limnological data such as conductivity and chlorophyll-a, were available. Potential statistical relationships (linear, curvilinear, exponential and second-order polynomial) of fish yield (FY, in kg ha−1 yr−1) to different land-use patterns, such as forest cover (FC, in km2) and shrub-land (SL, in km2), either singly, or in combination, and/or the ratio of each land type to reservoir area (RA in km2) and reservoir capacity (RC in km3), were explored. Highly significant relationships were evident between FY to the ratio of SL and/or FC+SL to RA and/or RC. Similarly, the above land-use types to RA and RC ratios were significantly related to limnological features of the reservoirs. The relationships of FY to various parameters obtained in this study were much better correlated than those relationships of FY to limnological and biological parameters used in yield prediction in tropical and temperate lacustrine waters previously.

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Many real-world applications on the Internet require accessing database information and typical technology employed is client/server plus Web (C/S + Web). Although past few years saw many success applications by using this technique, there are still some drawbacks that need to be overcome. One of the drawbacks is that the transaction often fails if the network connection is unstable. Another disadvantage is high bandwidth requirement and latency. This paper argues that mobile agent technology provide an easy way to overcome the shortcomings in CIS + Web in database access on the Internet. A success case study using mobile agents to admit new students to China's institutions is then presented. The mobile agent was created by using IBM's Aglets Software Development Kit (SDK). Based on the experimental results, it is evident that mobile agent technology is well suited for such applications.

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While knowledge discovery in databases (KDD) is defined as an iterative sequence of the following steps: data pre-processing, data mining, and post data mining, a significant amount of research in data mining has been done, resulting in a variety of algorithms and techniques for each step. However, a single data-mining technique has not been proven appropriate for every domain and data set. Instead, several techniques may need to be integrated into hybrid systems and used cooperatively during a particular data-mining operation. That is, hybrid solutions are crucial for the success of data mining. This paper presents a hybrid framework for identifying patterns from databases or multi-databases. The framework integrates these techniques for mining tasks from an agent point of view. Based on the experiments conducted, putting different KDD techniques together into the agent-based architecture enables them to be used cooperatively when needed. The proposed framework provides a highly flexible and robust data-mining platform and the resulting systems demonstrate emergent behaviors although it does not improve the performance of individual KDD techniques.

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A global database containing 3365 occurrences, 821 species and 251 genera of the Capitanian (Late Guadalupian, Permian) brachiopod faunas from 24 stations has been analyzed by cluster analysis using the Jaccard and Otsuka coefficients and the probabilistic index of similarity, nonmetric multidimensional scaling and minimum spanning tree. Two supergroups, three groups and six subgroups are revealed and interpreted as representing, respectively, two biotic realms (the Palaeoequatorial and Gondwanan Realms), two regions and six provinces. An additional realm (the Boreal Realm), based on the fauna from Spitsbergen, also appears recognizable although it also shows considerable similarities with southwestern North America and the northern margin of Gondwana as revealed by the statistical analysis. The Palaeoequatorial Realm can be further subdivided into the North America Region and the Asian Tethyan Region. The six biotic provinces are the Cathaysian Province in the Palaeotethys and Mesotethys, the Greenland-Svalbard Province in the Arctic region, the Austrazean Province in eastern Australia and New Zealand, the Grandian Province in western North America and the two transitional zones (the Himalayan Province in the southern temperate zone and the Sino–Mongolian–Japanese Province in the northern temperate zone). Polynomial regression analysis and rarefaction analysis indicate that the generic diversities of brachiopod faunas during the Capitanian peaked in the Palaeoequatorial Cathaysian Province and the two transitional zones (Himalayan Province and Sino–Mongolian–Japanese Province), but fell dramatically in the polar regions. The generic diversity of the Palaeoequatorial Grandian Province is apparently lower than in the two transitional zones of temperate palaeolatitudes, suggesting that the generic diversity of Capitanian brachiopod faunas does not exhibit a strict negative correlation with palaeolatitudes. This in turn would suggest that biogeographical determinants (such as geographical barriers, inhabitable area and ocean currents) other than latitude-related temperature control may also have played an important role in the dispersal of some brachiopods and the characterization of some local provinces and high diversities. The Capitanian global brachiopod palaeobiogeography is generally comparable with those in the Wuchiapingian and Changhsingian, but with some notable differences. These include: (1) that the Grandian Province of the Capitanian in western North America vanished after the end-Guadalupian regression, (2) that the western Tethyan Province of the Lopingian could not be distinguished in the Capitanian, and (3) that the Austrazean Province was larger in area than either in the Wuchiapingian or in the Changhsingian.

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A national approach to the conservation of biodiversity in Australia’s freshwater ecosystems is a high priority. This requires a consistent and comprehensive system for the classification, inventory, and assessment of wetland ecosystems. This paper, using the State of Victoria as a case study, compares two classification systems that are commonly utilized to delineate and map wetlands—one based on hydrology (Victorian Wetland Database [VWD]) and one based on indigenous vegetation types and other natural features (Ecological Vegetation Classes [EVC]). We evaluated the extent of EVC mapping of wetlands relative to the VWD classification system using a number of datasets within a geographical information system. There were significant differences in the coverage of extant EVCs across bioregions, different-sized wetlands, and VWD wetland types. Resultant depletion levels were markedly different when examined using the two systems, with depletion levels, and therefore perceived conservation status, of EVCs being significantly higher. Although there is little doubt that many wetland ecosystems in Victoria are in fact threatened, the extent of this threat cannot accurately be determined by relying on the EVC mapping as it currently stands. The study highlighted the significant impact wetland classification methods have in determining the conservation status of freshwater ecosystems.

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"Research on the international comparison of productivity has gained significant interest throughout several previous decades. Relatively little work has however been done in the real estate sector. This paper aims to develop a new productivity measurement framework for the international comparison of the real estate sector based on the newly-published OECD input-output database. Three multifactor productivity indicators are formulated using the ratio of the sectoral final demand to value added, the intermediate output to intermediate input and the total output to total input effect respectively in the input-output table. Historical analyses and comparisons are also carried out to indicate the differences of productivities of the real estate sectors in seven selected countries. Findings can improve the understanding of how technological, organisational and policy influences combine to affect productivity growth and aid the policy makers, real estate agencies and researchers in evaluating the competitive ability of the real estate sector."

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With its growing share in national economies, the real estate sector has been considered a vital contributor of economic development. Research efforts are needed in order to gain a better comprehension of the national specificities of the real estate sector and to identify its role in economic development. Due to limited comparable data, the economic indicators of real estate sectors are hard to compare between different countries. This paper aims to explore the quantitative interdependence amongst the real estate sector and other industries in developed economies using input-output analysis, and to investigate their significant linkages. Based on the recently published Organisation for Economic Co-operation and Development (OECD) input-output database at constant prices, the analysis focuses on the real estate's escalating role in terms ofshares in gross output, value added and gross national product. With emphasis on the relative role of manufacturing, construction and services inputs, this paper also highlights the strengths of the push and pull of the real estate sector.

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This research develops a new productivity measurement framework for the construction sector in the light of an input-output table. Three group multifactor productivity indicators are formulated based on the multiplier concepts in the input-output analysis. This measurement framework focuses on the intro-industry flows of products and considers the direct and indirect effects of input and output. Moreover, this framework enables us to measure the multifactor productivity of a specific sector systematically. Historical analyses and international comparisons are carried out to indicate the differences of the productivity of the construction sectors in seven selected countries, using the newly published OECD input-output database. Research findings are expected to clarify how technological, organizational and political factors affect the productivity growth, enabling the policy makers, construction businesses and researchers to quantify the competitive ability of the construction sector.

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Current microarray databases use different terminologies and structures and thereby limit the sharing of data and collating of results between laboratories. Consequently, an effective integrated microarray data model is required. One important process to develop such an integrated database is schema matching. In this paper, we propose an effective schema matching approach called MDSM, to syntactically and semantically map attributes of different microarray schemas. The contribution from this work will be used later to create microarray global schemas. Since microarray data is complex, we use microarray ontology to improve the measuring accuracy of the similarity between attributes. The similarity relations can be represented as weighted bipartite graphs. We determine the best schema matching by computing the optimal matching in a bipartite graph using the Hungarian optimisation method. Experimental results show that our schema matching approach is effective and flexible to use in different kinds of database models such as; database schema, XML schema, and web site map. Finally, a case study on an existing public microarray schema is carried out using the proposed method.

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A distributed database system is subject to site failure and link failure. This paper presents a reactive system approach to achieving fault tolerance in such a system. The reactive system concepts are an attractive paradigm for system design, development and maintenance because it separates policies from mechanisms. In the paper we give a solution using different reactive modules to implement the fault tolerant policies and the failure detection mechanisms. The solution shows that they can be separated without impact on each other; thus the system can adapt to constant changes in environments and user requirements.

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Evidence indicates that cruciferous vegetables are protective against a range of cancers with glucosinolates and their breakdown products considered the biologically active constituents. To date, epidemiological studies have not investigated the intakes of these constituents due to a lack of food composition databases. The aim of the present study was to develop a database for the glucosinolate content of cruciferous vegetables that can be used to quantify dietary exposure for use in epidemiological studies of diet–disease relationships. Published food composition data sources for the glucosinolate content of cruciferous vegetables were identified and assessed for data quality using established criteria. Adequate data for the total glucosinolate content were available from eighteen published studies providing 140 estimates for forty-two items. The highest glucosinolate values were for cress (389 mg/100 g) while the lowest values were for Pe-tsai chinese cabbage (20 mg/100 g). There is considerable variation in the values reported for the same vegetable by different studies, with a median difference between the minimum and maximum values of 5·8-fold. Limited analysis of cooked cruciferous vegetables has been conducted; however, the available data show that average losses during cooking are approximately 36 %. This is the first attempt to collate the available literature on the glucosinolate content of cruciferous vegetables. These data will allow quantification of intakes of the glucosinolates, which can be used in epidemiological studies to investigate the role of cruciferous vegetables in cancer aetiology and prevention.

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Data collecting is necessary to some organizations such as nuclear power plants and earthquake bureaus, which have very small databases. Traditional data collecting is to obtain necessary data from internal and external data-sources and join all data together to create a homogeneous huge database. Because collected data may be untrusty, it can disguise really useful patterns in data. In this paper, breaking away traditional data collecting mode that deals with internal and external data equally, we argue that the first step for utilizing external data is to identify quality data in data-sources for given mining tasks. Pre- and post-analysis techniques are thus advocated for generating quality data.

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Traditionally. accessing databases on the Internet is based on client/server paradigm (including web-based paradigm). However. there are some drawbacks when using the techniques. Mobile agent technology provides an excellent solution that can easily eliminate those disadvantages. By conducting a series of experiments and analyzing the experimental results, this paper presents in which circumstance mobile agents can outperform traditional client/server paradigm, and how they can overcome the shortcomings in client/server paradigm in database access on the Internet.