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Статті в журналах з теми "International Classification of Activities for Time-Use Statistics"
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Simonova, M. D. "OECD Structural Analysis Databases: Sectoral Principles in the Study of Markets for Goods and Services." MGIMO Review of International Relations, no. 3(42) (June 28, 2015): 190–98. http://dx.doi.org/10.24833/2071-8160-2015-3-42-190-198.
Повний текст джерелаАнотація:
This study focuses on the characteristics of the information database of the OECD structural business statistics in the analysis of markets of goods and services, and macroeconomic trends. The system of indicators of structural statistics is presented in OECD publications and on-line access to a wide range of users. Collected data sources generated by the OECD offices are based on the national statistical offices of country-members, Russia and the BRICS. Data on the development of economic sectors are calculated according to the methodology of individual countries, regional and international standards: annual national accounts of countries, annual industry and business surveys, methodology of short-term indicators, statistics of international trade in goods. Data are aggregated on the basis of complex indicators statements of the enterprises' questionnaire and business surveys. Information system of structural statistics which is available and continuously updated, has certain features. It is composed of several subsystems: Structural Statistics on Industry and Services, EU entrepreneurship statistics, Indicators of Industry and Services, International Trade in Commodities Statistics. The grouping of industries is based on the International standard industrial classification of all economic activities (ISIC). Classification of foreign trade flows is made in accordance with the Harmonized system of description and coding of goods. The structural statistics databases comprise four classes of industries' grouping according to the technology intensity. The paper discusses the main reasons for the non-comparability of data in the subsystems in certain time intervals.
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Mostafa, Toka S., and Matthew J. Roorda. "Discrete Choice Modeling of Freight Outsourcing Decisions of Canadian Manufacturers." Transportation Research Record: Journal of the Transportation Research Board 2610, no. 1 (January 2017): 76–86. http://dx.doi.org/10.3141/2610-09.
Повний текст джерелаАнотація:
Behavioral freight transportation modeling is an approach to enhance the quality of freight and logistics policy assessments. Outsourcing of freight activities is one of the essential decisions that firms make. Such decisions are influenced by factors such as economic conditions, competition, the industry, firm strategies, and firm characteristics. In this paper, the authors introduce a set of discrete choice models—binary and multinomial logit—that quantify the effect of some of these factors on outsourcing of the freight-related activities of goods production and logistics for Canadian manufacturers. The models were estimated with the use of data from the Survey of Innovation and Business Strategy obtained from Statistics Canada. The models consider firm characteristics (e.g., employment, number of products or services, and supplier locations), economic conditions, and local and international competition. The models also show the influence of the use of innovation and advanced technologies and measure the impact of government support programs for businesses (e.g., government grants) on outsourcing decisions. Models that explain international freight outsourcing are also presented. Model results highlight that freight outsourcing culture differs from one industry to another. Firms that use government training programs are more likely to outsource freight operations locally, whereas those that use government grants outsource their freight activities internationally. Model validation indicated acceptable predictive capabilities. Simplified models that were based on industry classification, location, and firm size were estimated and are to be used for future microsimulation purposes.
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Liangruenrom, Nucharapon, Dorothea Dumuid, and Zeljko Pedisic. "Physical activity, sedentary behaviour, and sleep in the Thai population: A compositional data analysis including 135,824 participants from two national time-use surveys." PLOS ONE 18, no. 1 (January 24, 2023): e0280957. http://dx.doi.org/10.1371/journal.pone.0280957.
Повний текст джерелаАнотація:
Purpose To determine the amounts of time spent in physical activity (PA), sedentary behaviour (SB), and sleep in the Thai population, as well as their sociodemographic correlates and changes over time. Methods We analysed cross-sectional data collected in a population-representative, stratified random sample of 135,824 Thais aged 10 years and over as part of the two most recent Thai National time-use surveys (2009 and 2015). Daily activities reported by the participants were coded using the International Classification of Activities for Time-Use Statistics (ICATUS) and categorised as PA, SB, or sleep. Results In the latest survey, participants spent on average the largest amount of time sleeping (geometric mean [g] = 9.44 h/day; 95% confidence interval [CI]: 9.42, 9.47), followed by PA (g = 8.60 h/day; 95% CI: 8.55, 8.64) and SB (g = 5.96 h/day; 95% CI: 5.93, 6.00). The time spent in PA was higher on weekdays, while the amounts of SB and sleep were higher on weekends (p < 0.05). Males, older age groups, and unemployed people spent less time in PA and more time in SB, compared with other population groups (p < 0.05). We found a relatively large increase in SB (mean difference [d] = 39.64 min/day; 95% CI: 36.18, 42.98) and decrease in PA (d = 54.33 min/day; 95% CI: -58.88, -49.30) over time. These findings were consistent across most sociodemographic groups, with the most concerning shifts from active to sedentary lifestyle found among people with a higher education degree and on weekends. Conclusions Our findings revealed a shift to a more sedentary lifestyle in the Thai population. Public health interventions should focus on improving time use among males, older age groups, and unemployed people, while preventing the rapid decrease in PA and increase in SB among those with a higher education degree and on weekends.
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Selvaraj, Ganesh, and Michael Butchard. "O4E.1 Cross-walking countries’ industry classifications using concordance files compared to fuzzy data matching, to utilise an international exposure dataset." Occupational and Environmental Medicine 76, Suppl 1 (April 2019): A39.1—A39. http://dx.doi.org/10.1136/oem-2019-epi.106.
Повний текст джерелаАнотація:
BackgroundCarcinogen exposure data can potentially guide the work of health and safety (H and S) regulators. This project aims to use CAREX Canada data to estimate carcinogen exposures in New Zealand industries. This requires the creation of a cross-walk between the countries’ industry classifications.MethodsAgile and big-data-science methodologies were used to construct two versions of an industry classification cross-walk from the 2006 Australian and New Zealand Standard Industrial Classification (ANZSIC06) to the Canadian version of the 2002 North American Industrial Classification (NAICS2002), used by CAREX Canada.Firstly, concordance files from government statistics bureaus cross-walked the path: ANZSIC06 ->International Standard Industrial Classification of All Economic Activities Rev4 ->NAICS2017->NAICS2012->NAICS2007->NAICS2002. The cross-walk accounted for ‘one-to-many-to-one’, non-machine formats, and missing/erroneous values.Secondly, a fuzzy data matching pipeline was designed. Data preparation removed redundant, stop, and common domain words, and lemmatised using morphological analysis (e.g. fishing to fish). Data matching used a hybrid algorithm combining ‘JaroWinkler-distance’ and a token-sort approach (i.e. ignoring the positional occurrence of words in a sentence) to match descriptions. A trial-and-error approach was used to assign weightings and concatenate the hierarchical industry classification levels to improve match accuracy. Python language was used for implementation.For each method, random samples of 50 matches were manually classified as either poor or sufficient by two people. Disagreements were discussed and consensus reached.ResultsThe concordance cross-walk sample had 52% (95% C.I. 38%–66%) sufficient matches compared to 84% (95% C.I. 74%–94%) for the fuzzy data matching pipeline cross-walk sample.ConclusionsCross-walking countries’ industry classifications using a fuzzy data matching pipeline was more accurate than using a concordance cross-walk. The pipeline is modular enough to easily include more components. This work is part of a vision to design a semantic big-data lake, enabling integration of any data relevant to H and S.
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Getman, A. G. "Problems of Interaction between the Participants of Foreign Economic Activities in the Context of the Customs Protection of Intellectual Property." Intellectual property law 2 (July 1, 2021): 36–40. http://dx.doi.org/10.18572/2072-4322-2021-2-36-40.
Повний текст джерелаАнотація:
Risks in supply chains directly affect the security of these chains and their continuity, the main possible consequences are increased costs and reduced profits. Methods. The research is based on general scientific methods of cognition — historical, analysis, systematization, comparison method, partially-scientific methods and dialectical method Results. The concept of “risk” is considered from different points of view: customs control and state standards. The classification of risks is proposed, which includes the risks of delay in the release of goods, non-payment of customs duties, bringing to administrative responsibility, confiscation of goods, the risk of depriving a foreign trade participant of the status of “bona fide”, failure to fulfill the terms of the contract for the delivery of goods. Their indicators that allow identifying risks are given. A method is proposed for calculating the probability of occurrence of risks in the international supply chain of goods containing intellectual property objects, which is necessary to determine the risk category and assign it to a high, medium or low level. Discussion. The proposals put forward are the basis for further research in the field of forecasting the risks of moving goods containing OIS. The main problem in risk forecasting is the lack of information and statistics. In this connection, it is not always possible to make the necessary calculations. For example, statistics on the accounting of license fees in the customs authorities are not kept, although this information could allow: on the one hand, to qualitatively improve the effectiveness of the application of the RMS, in terms of the possibility of replenishing funds to the federal budget at the expense of the added value for the use of the IPR by the customs authorities, and on the other — to participants of foreign trade will allow to predict and minimize risks.
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Salin, V. N., M. V. Vakhrameeva, and O. Yu Sitnikova. "Presentation of Financial Assets in Russian Macroeconomic Statistics." Statistics and Economics 18, no. 5 (October 22, 2021): 14–25. http://dx.doi.org/10.21686/2500-3925-2021-5-14-25.
Повний текст джерелаАнотація:
The purpose of the study. Currently, much attention is paid to the collection, presentation and analysis of data on the volume, structure and dynamics of economic assets. The value of economic assets, their composition, and effective asset management determine the trajectory of the development of the national economy and its individual sectors. Financial assets are an integral part of economic assets, their importance in the activities of economic entities is steadily increasing. The purpose of the work is to systematize theoretical and practical developments on the presentation of data on financial assets in modern macroeconomic statistics of Russia, to determine the directions for improving the methods of evaluating financial assets, the system of indicators characterizing their condition and movement.Materials and methods. The authors considered the classification of financial assets, applied structural and dynamic data analysis, as well as methods of theoretical research in the form of generalization, comparison and special analytical procedures.Results. The paper defines the main directions of studying financial assets based on existing international standards, taking into account national statistical practice. The current issues of the theory and practice of statistical observation and presentation of data on financial assets, the adaptation of concepts and classifications of international standards to the Russian system of statistical accounting are considered. The features of the presentation of data on financial assets at the macro level are formulated, which are reflected in the national accounts, the system of indicators of monetary statistics and statistics of foreign economic relations, statistical indicators of the Bank of Russia. The authors conducted a quantitative assessment of the structure and dynamics of indicators characterizing the state and movement of financial assets.Conclusion. Statistical analysis of economic transactions with financial assets at the level of institutional units and sectors of the economy allows us to identify not only the main trends in the development of the financial sector of the economy, but also makes it possible to comprehensively consider changes in the value and composition of financial assets at the macro level. The change in the value of financial assets is determined on a balance basis, that is, as the difference between the value of acquired and disposed financial assets.The authors examined in detail the methodological basis for forming a financial account in the context of financial instruments and sectors of the national economy. The financial account provides comprehensive information in the sectoral context on transactions with financial assets and liabilities for the reporting period, allows you to reflect the change in their value as a result of economic operations performed by institutional units, as well as to identify sectors of the economy that did not perform transactions with financial assets. The analysis of the financial account data makes it possible to analyze in detail the change in the value of financial assets at the macro level, to assess the share of the impact of each sector of the economy and the type of asset. A similar approach is applied in analytical procedures with respect to the net obligations assumed.Macroeconomic statistics reflect the movement of financial assets and liabilities by sectors of the national economy and characterize Russia’s relations with the “rest of the world” by determining the volume of net lending by Russia to other countries or determining its status as a net borrower.The issues of the theory and practice of presenting data on financial assets and their use are relevant and promising areas for improving national statistical accounting. Work in this direction continues, although the process of active implementation of international standards in statistical practice has been going on for quite a long time. The quality of primary accounting data on financial sector operations has improved significantly recently, but there are still problems with obtaining data in terms of the full coverage of the statistical aggregate under study, as well as the timing of obtaining reporting data. In addition, the appearance of a large number of new financial instruments and transactions, including modified ones, in the business turnover of institutional units makes it difficult to identify and classify them.The authors of the article have repeatedly addressed the issues of macroeconomic calculations in their publications, which allowed them to consider in more detail topical issues related to the processes of reflecting financial assets.
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Tatarinov, A. A., and N. E. Ustinova. "Measuring the ICT Sector in the Digital Economy." Voprosy statistiki 28, no. 6 (December 10, 2021): 5–17. http://dx.doi.org/10.34023/2313-6383-2021-28-6-5-17.
Повний текст джерелаАнотація:
The article addresses the problem of measuring the Information and Communication Technology (ICT) sector and its relationship to the digital economy as defined in the OECD «Guidelines for Supply-Use Tables for the Digital Economy». Analysis of various concepts of the digital economy shows that the ICT sector is its key element. It is stressed that, in line with the OECD recommendations, the measurement of the digital economy should be based on the SNA satellite account, the core element of which are the Digital Supply-Use Tables (Digital SUTs). This approach enables to reflect most fully within a single statistical model integration of all phases of digital products (goods and services) circulation in the national economy.It is noted that the construction of ICT Supply-Use Tables (SUTs) is a critical self-contained task, as it provides a measurement framework for both digital (regardless of the model to be adopted) and (more broadly) information economy.It is stressed that the ability to capture the use of ICT products as well as the cost of their production depends significantly on the identification and valuation of digital products and industries in the Digital SUTs. The identification of such industries is now a major challenge because of the lack of separate activities in the existing industrial classifications that are characteristic for their constituent units.The article concludes with a presentation of the pilot estimates of ICT Sector SUTs core indicators obtained by the authors at the Economic Statistics Centre of Excellence, HSE University. The contribution of the sector to the GDP of the Russian Federation is analysed and its inter-sectoral linkages, both on the demand and supply side, are assessed. It is concluded that the full implementation of the Digital SUTs depends on the inclusion in the new International Standard Industrial Classification (ISIC) the additions necessary to identify and evaluate digital products and industries.
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Livengood, Spencer J., Travis M. Jones, Rebekah W. Moehring, Steven S. Spires, Melissa D. Johnson, April Dyer, Angelina Davis, and Elizabeth Dodds Ashley. "598. Correlation of International Classification of Diseases (ICD) codes to initial provider-selected antibiotic indications in hospitalized adult patients within the Duke Antimicrobial Stewardship Outreach Network (DASON)." Open Forum Infectious Diseases 7, Supplement_1 (October 1, 2020): S362. http://dx.doi.org/10.1093/ofid/ofaa439.792.
Повний текст джерелаАнотація:
Abstract Background Provider-selected antibiotic indications are a measure to help track antibiotic use, and facilitate stewardship activities. International Classification of Diseases 10th version (ICD-10) codes have been widely used in the medical field for a variety of purposes, including billing for reimbursement, disease epidemiology, administration, and research. The ability of these codes to accurately describe the true disease diagnosis has been questioned. The purpose of this study is to provide insight into correlation between ICD-10 codes and provider-selected antibiotic indications recorded upon antibiotic order entry. Methods This multicenter, retrospective cohort study was performed using data from 17 hospitals in the DASON network. Antibiotic orders during calendar year 2019 for inpatients ≥ 18 years of age that included an indication for use were extracted from the DASON antimicrobial stewardship assessment portal. Orders with the antibiotic indication category of prophylaxis (medical or surgical) and other were excluded. The primary outcome was agreement between antibiotic indication and any discharge ICD-10 code from the same hospital admission. Secondary analyses stratified results by antibiotic and indication. Descriptive statistics were used to describe outcomes. Results A total of 246,999 unique antibiotic orders were identified in 180,109 admissions. After removing prophylaxis (n=75,124) and other (n=36,359), 135,516 orders were included. Most orders did not have an ICD-10 code matching the prescriber indication (92,237 [68%]). All indications except HEENT (18% mismatch) and genitourinary infections (46% mismatch) lacked a corresponding diagnosis code in more than 50% of cases (Table 1). Urinary tract infections (93%), bloodstream infections (90%), and central nervous system infections (80%) showed the highest rates of mismatch among indications (Table 1). Table 1: Correlation of ICD-10 Codes to Provider Selected Indications Conclusion We observed a high rate of mismatch between antibiotic indications and ICD-10 codes. Provider-selected antibiotic indications at the time of empiric treatment may be more reflective of diagnostic differential but is a poor indicator of ultimate patient diagnosis. Disclosures Rebekah W. Moehring, MD, MPH, Agency for Healthcare Quality and Research (Grant/Research Support)Centers for Disease Control and Prevention (Grant/Research Support) Melissa D. Johnson, PharmD, MHS, Charles River Laboratories (Grant/Research Support)Cidara (Consultant)Merck & Co (Scientific Research Study Investigator)Paratek (Consultant)Scynexis (Scientific Research Study Investigator)Shionogi (Consultant)UpToDate (Other Financial or Material Support, Royalties)
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Melnyk, Tetiana, Nataliia Reznikova, and Oksana Ivashchenko. "PROBLEMS OF STATISTICAL STUDY OF “GREEN ECONOMICS” AND GREEN GROWTH POTENTIALS IN THE SUSTAINABLE DEVELOPMENT CONTEXT." Baltic Journal of Economic Studies 6, no. 3 (August 5, 2020): 87–98. http://dx.doi.org/10.30525/2256-0742/2020-6-3-87-98.
Повний текст джерелаАнотація:
The purpose of the research. The research subject purpose is theoretical and practical aspects of the statistical assessment of the green economy potential in the sustainable development context. The methods. The article is based on the categories of theoretical (hypothesis, concept, theory, problem) and empirical (facts, empirical summarizations, empirical dependences) level of the issue, distinctive features of which are: objectivity; categorical character; rationality; testability; high level of generalization; universality and use of special tools and methods of cognition. General scientific and special methods of research are used to achieve the article’s purpose and solve its problems, namely: methods of analysis, abstraction and synthesis, induction and deduction, and system structuring method; hypothetico-deductive method; method of historical and logical integrity; method of idealization; methods of classification and system generalization; statistical methods. Considering that further “greening” of socio-economic indicators constitutes a vital problem remaining on the agenda of global and national institutes of development, the article’s objective is to develop an integral approach to the revision of the System of Environmental-Economic Accounting (SEEA) built by the UN approach, through comparing existing approaches to the statistical assessment of the green economy state and the green growth potential, taking into account the proposed energy indices and indicators. Results. It is demonstrated that because none of the integral indicators of “green economy” development has been widely adopted by now, national and international statistics have no grounds for separating green goods and services as a specific sector of the national economy. Practical implications. The System of Environmental- Economic Accounting (SEEA) has been adopted as a basic tool for the assessment of indicators reflecting the causal links between the economy and the environment. It is substantiated that most part of the data for measuring green growth processes has to be possibly collected by SEEA. Value/originality. The importance of the assessment of the dynamics of national economy greening is demonstrated, because this type of analysis enables one to assess the change in the environmental impact of the new economic model by analyzing the factors and identifying most effective methods for decreasing environmental pressures of economic activities. The advantage of such assessment is that it can be made on the basis of the available statistical data. Considering that energy indices and indicators are widely used in many international reporting systems to assess the state of green economy and the potential of green growth in the sustainable development context, we made an attempt to systematize all the indicators by the two main groups: direct and indirect. It is revealed that international organizations (ОЕСР, UNEP and the World Bank) attempt to unify the existing approaches in constructing their own algorithms for the assessment of “green growth”, in particular with the indicators of Sustainable Development Goals. At the same time, national statistical agencies attempt to build a set of statistical indicators for the assessment of green economy development as indicators of demand for green products. It is demonstrated that harmonized definitions of economic activities concerned with the green industry and green jobs and comparable key indicators, if used internationally, will enable for the statistical assessment of the green economic development in space and time.
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Ladonko, L., N. Orlova, A. Chechel, N. Mirko, and I. Kalinko. "FINANCING OF PUBLIC AND LOCAL PROGRAMS AND PROJECTS IN UKRAINE AND POLAND." Financial and credit activity: problems of theory and practice 1, no. 36 (February 17, 2021): 58–67. http://dx.doi.org/10.18371/fcaptp.v1i36.227622.
Повний текст джерелаАнотація:
The article researches financing instruments of public and local programs and projects in Ukraine and Poland (budgetary, grant, financial, credit and investment instruments). The purpose of the article is to determine the possibilities of using financing instruments of public and local programs and projects in Ukraine and Poland for the implementation of national and regional public policy. Research methods — comparative analysis of analytical and official statistics of Ukraine and Poland based on the classification of groups of financing instruments of public and local programs and projects. It has been proved that the main instruments for financing public and local projects and programs in Ukraine and Poland are budget (subventions, local targeted programs) and grant instruments (grant programs, international technical assistance). The evaluation of the distribution structure of funds within the framework of individual programs in Poland and Ukraine made it possible to allocate key objects of grant financing in Ukraine (education, sports, health and social protection) and in Poland (territory planning, road transport infrastructure, business development and innovation). It is determined that international loans from the International Bank for Reconstruction and Development, the European Bank for Reconstruction and Development and the European Investment Bank are an important financial and credit instrument in countries, as evidenced by the total volume of loans attracted by countries from international organizations. The peculiarities of development and implementation of investment instruments of financing of public and local programs and projects were studied: public-private partnership, leasing activities. The conclusions summarize mechanisms for the use of financing instruments in Ukraine and Poland and propose ways to strengthen existing capacities and improve the financing process of public and local programs and projects for Ukraine.
Дисертації з теми "International Classification of Activities for Time-Use Statistics"
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Liangruenrom, Nucharapon. "Trends and Correlates of Physical Activity and Sedentary Behaviour in the Thai Population." Thesis, 2020. https://vuir.vu.edu.au/40725/.
Повний текст джерелаАнотація:
To facilitate the development of effective public health programs and policies to increase physical activity (PA) and reduce sedentary behaviour (SB) in Thailand, there is a need for comprehensive epidemiological evidence and a sound assessment of prevalence, trends, and factors associated with these behaviours. This PhD research therefore aimed to: 1) identify gaps in the available literature on PA and SB in Thailand; 2) determine the prevalence of PA and SB among Thai adults using the validated Global Physical Activity Questionnaire (GPAQ); 3) summarise evidence on individual, social, environmental, and policy correlates of PA and SB in the Thai population; 4) develop criteria to classify the International Classification of Activities for Time-Use Statistics (ICATUS) activities into sleep, SB, light-intensity PA, and moderate-to-vigorous PA categories, based on expert assessment; and 5) establish trends in PA and SB and assess how correlates of these behaviours have changed among Thai adults over 15 years.
To achieve the first aim, we conducted a systematic scoping review according to the Guidance for Conducting Systematic Scoping Reviews. To achieve the second aim, we conducted a secondary analysis of population-representative data from a Thai national survey. To achieve the third aim, we conducted a systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. To achieve the fourth aim, we conducted a Delphi study including 13 content experts. To achieve the fifth aim, trends and sociodemographic correlates of PA and SB in Thailand were examined using Thai national ICATUS-based surveys. Using time-use data from ICATUS allowed for treating PA and SB estimates as integrative parts of a time-use composition, to examine the new holistic 24-hour movement guidelines. Overall, Study 1 found that the interest in research on PA and SB in Thailand has grown in the past two decades. Major research gaps were found for measures and methodology used in previous studies and only limited evidence was found on SB. Findings from Study 2 show low prevalence of PA among Thai adults in 2015 and a declining trend in the prevalence of meeting the PA recommendation since 2004. A range of sociodemographic correlates of PA and SB in the Thai population were identified in Study 3. Study 5 found that more than half of Thai adults engaged in prolonged sitting over a 15-year period. These findings highlight the need of public health programs to promote PA and reduce SB in Thailand. Future interventions and policies to increase PA participation should focus particularly on girls, older women, young adults, urban residents, and those with low education. The interventions to improve self-efficacy for PA and lower perceived barriers for PA should be implemented among all agegroups. Future interventions to reduce SB are also needed among adults, particularly for males, older age groups, obese, and those with higher education. However, more studies are needed to provide a more complete picture of what factors are influencing PA and SB in the population; particularly among children, adolescents, older adults and at social, environmental and policy levels.
Тези доповідей конференцій з теми "International Classification of Activities for Time-Use Statistics"
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Alcalá, Luis, Juan M. García-Gómez, and Carlos Sáez. "Project based learning in Biomedical Data Science using the MIMIC III open dataset." In INNODOCT 2020. Valencia: Editorial Universitat Politècnica de València, 2020. http://dx.doi.org/10.4995/inn2020.2020.11890.
Повний текст джерелаАнотація:
The subjects Health Information Systems and Telemedicine and Data Quality and Interoperability of the Degree and Master in Biomedical Engineering of the Universitat Politècnica de València, Spain, address learning outcomes related to managing and processing biomedical databases, using health information standards for data capture and exchange, data quality assessment, and developing machine-learning models from these data. These learning outcomes cover a large range of distinct activities in the biomedical data life-cycle, what may hinder the learning process in the limited time assigned for the subject. We propose a project based learning approach addressing the full life-cycle of biomedical data on the MIMIC-III (Medical Information Mart for Intensive Care III) Open Dataset, a freely accessible database comprising information relating to patients admitted to critical care units. By means of this active learning approach, students can achieve all the learning outcomes of the subject in an integrated manner: understanding the MIMIC-III data model, using health information standards such as International Classification of Diseases 9th Edition (ICD-9), mapping to interoperability standards, querying data, creating data tables and addressing data quality towards applying reliable statistical and machine learning analysis and, developing predictive models for several tasks such as predicting in-hospital mortality. MIMIC-III is widely used in the academia and science, with a large amount of publicly available resources and scientific articles to support the students learning. Additionally, the students will gain new competences in the use of Open Data and Research Ethics and Compliance Training.
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Shapovalov, Viktor, and Yevhenii Shapovalov. "Automation of the generation of scientific statistics and the development of monitoring publishing activity dashboards in real time." In First International Conference "Open Science and Innovation in Ukraine 2022". State Scientific and Technical Library of Ukraine, 2022. http://dx.doi.org/10.35668/978-966-479-129-5-4-5.
Повний текст джерелаАнотація:
One of the components that creates a burden on scientists is work with documents. Since this is manual work, the typical process involves spending a significant amount of time on agreeing to correct errors. An approach is proposed, which involves the use of a database with information about scientists and document templates to simplify such activities of scientists.
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Bernasconi, Giancarlo, Giuseppe Giunta, and Fabio Chiappa. "Gas Filled Pipelines Monitoring Using Multipoint Vibroacoustic Sensing." In ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/omae2015-41265.
Повний текст джерелаАнотація:
eni S.p.A. has promoted and supported a research project (DIONISIO) for the design of a proprietary pipeline monitoring system, exploiting negative pressure waves and statistical analysis principles. A discrete network of pressure and vibration sensors are installed on the pipeline, at relative distances of tens of kilometers. The acoustic and elastic waves produced by third party interference and by flow variations (leaks, spills, valve regulations, pig operations, etc.), propagate along the pipeline, and they are recorded at the monitoring stations. Multichannel processing of the collected signals enables the real time detection, localization and classification of the triggering event. The system has been tested in single phase and multiphase transportation lines during several field campaigns. This paper collects the results for gas transportation pipelines. The field experience has been used to upgrade the prototypal version of the system to an industrial version, that is currently operative, or in an advanced installation phase, on several pipelines in Italy and in Nigeria, and it has detected tens of bunkering activities with a localization accuracy of about 25 m, from a distance up to 35 km from the sensing point.
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Ayati, Ehsan, and Andrea Schiffauerova. "Study of Cost of Quality Behavior in Manufacturing Supply Chain Based on the Quality Maturity Status." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-39694.
Повний текст джерелаАнотація:
Measuring Cost of Quality (COQ) seems to be a critical factor for organizations in order to keep or grow their market share. However, until now the COQ has been measured almost exclusively only internally, i.e. within a company, while the role of a supply chain in delivering quality product to end users has been ignored. In this paper we argue that all the entities within supply chain affect the quality of a product or a service and their quality related activities should thus be inevitably considered. The objective of this research is to develop a mathematical model to estimate COQ as key performance measurement within manufacturing supply chain while considering quality Excellency status. Using classic PAF (Prevention-Appraisal-Failure) model classification to develop mathematical model and its integration with significant variables in supply chain entities are the key methodology in this work. Perceived quality is assumed as an appropriate definition of quality in manufacturing supply chain. Moreover, proposed model is examined against real time quality cost data of manufacturing supply chain in two intervals, first at quality immaturity period and then at quality maturity period. Statistical tools are used to validate the model and compare its behaviour in the two intervals. The results are then analyzed and discussed, and possible future works are presented.
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Nguyen, Nguyen, V. Sundararajan, and Victor B. Zordan. "Motion Classification Using Wireless Sensors for Activity Monitoring in Firefighting." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35844.
Повний текст джерелаАнотація:
Firefighter’ chief reason for entering a burning structure is to search for and rescue potential victims. Currently, their primary method for communication is an often-congested two-way radio which the firefighters use from within a burning building to relay their activities (and other information) to an external battalion chief. In response to discussions with firefighters in the field, we introduce an approach for automatically segmenting and classifying a select set of activities using wireless accelerometers attached to the human body. The activities we focus on are the ones that are most commonly conducted by firefighters and that are important to the battalion chief for understanding the ongoing search and rescue. In our implementation, sensors continuously measure the acceleration of a small number of body segments and transmit data back to a central base station. At runtime, our system classifies data for short intervals, relying on training examples of the activities of interest. We show that our approach can appropriately detect motions in real-time without significant latency using as few as two accelerometers.
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Musatov, Danila, and Denis Petrusevich. "Modeling of forecasts variance reduction at multiple time series prediction averaging with ARMA (1, q) functions." In V International Scientific Workshop on Modeling, Information Processing and Computing. CEUR-WS.org, 2022. http://dx.doi.org/10.47813/dnit-mip5/2022-3091-1-11.
Повний текст джерелаАнотація:
Combination of time series forecasts is usually considered as good technique in practice. But it has got weak theoretical explanation. In this research variance of time series forecasts and variance of combined models are considered. One is interested in the view of variance of forecasts function over one, two and three periods. Conditions which can lead to improvement of averaged time series predictions are in scope of this research. In this paper a few examples of the most popular time series models are observed: the moving average models MA(q), the autoregressions AR(p) models and their combination in the form of ARIMA(p, d, q) or ARMA(p, q) model. In particular, AR(1) and ARMA(1, q) are investigated. Nowadays there are researches about time series averaging. Approaches based on bagging and boosting are implemented very often in classification and regressions. It’s very appealing to use such strategy in tine series modeling. At the same time it’s easy to construct learning set and test set in classification tasks. But it’s a complex task in case of time series processing. There’s a need of two sets: to train time series models and to construct their combinations. Thus nowadays combination of time series models, combination of their forecasts or of their prediction intervals are in scope of view of a few complex researches. In this paper we investigate behaviour of time series predictions’ variance in order to have another useful approach in time series prediction averaging. Russian macroeconomical time series statistics is used as experimental time series.
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White, James, Katherine Taylor, Jonny Martin, Steven Carrell, and Roland Palmer-Jones. "Estimating Pipeline Probability of Failure Due to External Interference Damage Using Machine Learning Algorithms Trained on In-Line Inspection Data." In 2022 14th International Pipeline Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/ipc2022-87093.
Повний текст джерелаАнотація:
Abstract External interference damage is one of the main causes of pipeline failure reported in publicly available industry statistics from agencies such as the Canada Energy Regulator (CER) and the United States Pipeline and Hazardous Materials Safety Administration (PHMSA). Thus, failures due to external interference are often the most significant contributors to pipeline probability of failure in risk assessments and can play a significant role in operator decisions regarding risk-control expenditures, for example when it comes to the installation of additional impact protection, pipeline diversion or pressure restrictions. The probability of failure due to external interference damage can be estimated by combining the probability that damage occurs (i.e. that the pipeline is hit), the probability that the impact is sufficient to cause instant failure and the probability of degradation to failure, given that damage has occurred. Degradation to failure is assessed using industry standard engineering models (such as the limit state functions given in Annex O of CSA Z662-19 [1]). However, the key challenge is predicting where, when, and with what energy the external interference damage may happen. The prediction of a “hit rate,” or impact frequency, can often be subjective or based on statistics, which may not always be applicable or accurate for use on the pipeline under assessment. Top-of-line (TOL) deformation damage (dents) reported by in-line inspection (ILI) are a clear indicator of past external interference, which could have been introduced by third parties, contractors or the operator themselves. ILI data from ROSEN’s Integrity Data Warehouse (IDW) — which at the time of writing contains results from over 18,000 inspections — has been used to train machine learning models to estimate the frequency of external interference damage (per km-year). The distribution of dent sizes combined with pipe parameters is used to estimate a distribution of dent force. The following may all influence the likelihood and energy of external interference damage and may be considered as predictor variables in a machine learning model: • Local population density • Land use • Excavator types (typical bucket dimensions) • Frequency of crossings (road, rail, other services) • Pipeline burial depth • Additional impact protection • Pipeline markers and warning tape • Patrol and surveillance frequency • Operational control activities • Pipeline material properties This paper presents an approach to estimate the probability of failure due to external interface damage that use more accurate and justifiable impact frequency statistics, which are generated using worldwide ILI data and additional influencing factors based on pipeline exposure, resistance and mitigations.
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Barstow, Stephen F., Gunnar Mo̸rk, Lasse Lo̸nseth, Peter Schjo̸lberg, Ulla Machado, Gerassimos Athanassoulis, Kostas Belibassakis, Theodore Gerostathis, Christos Stefanakos, and Gerard Spaan. "WORLDWAVES: High Quality Coastal and Offshore Wave Data Within Minutes for Any Global Site." In ASME 2003 22nd International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2003. http://dx.doi.org/10.1115/omae2003-37297.
Повний текст джерелаАнотація:
There has been a growing demand for reliable information on the wave conditions, in particular at coastal sites, as a result of increased utilisation of the coastal zone to a multitude of activities including various shoreline developments related to transportation, tourism, fish farming and recently wind and wave energy industries. This trend is likely to continue. Reliable data is also needed with respect to the management and protection of these often fragile environments. Many of those concerned with these wave-impacted environments still use antiquated data sources, usually from offshore waters as, in the absence of long term wave data collected at the site of interest, the calculation of reliable wave statistics at a coastal site is a complicated, time consuming and expensive business, requiring various data sets to be assembled. WORLDWAVES simplifies and speeds up the modelling of wave conditions in coastal waters by integrating the following under a single Matlab toolbox: High quality long-term wave data offshore all global coasts; worldwide bathymetric and coastline data; SWAN and backward raytracing wave models; sophisticated offshore and nearshore wave statistics toolboxes with tabular and graphical presentations, including a facility to export ASCII time series data at offshore or inshore locations; a geographic module with easy zooming to any area worldwide; tools to set up model grids and display and edit bathymetry and coastline; a facility for the import of user offshore data and export of inshore time series data. In this paper we describe the design and implementation of WorldWaves including the fusion of satellite, model and buoy wave and wind data in the global offshore database and the new raytracing model.
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Goh, Thong N. "Efficient Design Testing With Statistical Concept of Degree of Freedom." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49006.
Повний текст джерелаАнотація:
Efficient testing of design prototypes or early batches of products is essential to meeting time-to-market as well as field performance and other requirements such as those specified in environmental and safety standards. Most design engineers are concerned with the technical arrangements and execution of such tests but may not be making use of an approach based on information transformation that is better known to statisticians in the form of experimental design. In this paper, we suggest the use of strategies and tools of experimental design from the perspective of information utilization, and highlight ways in which specific performance characteristics of a new or improved product can be effectively and efficiency tested, quantified, and evaluated. The approach also bridges the usual gap that exists between design engineers and mathematical statisticians, as traditionally each profession tends to have its own parlance and mindset in empirical studies. The techniques illustrated in this paper tend to “fall through the crack” in various texts on empirical product testing; they help put in place a framework that can be fruitfully adopted by design engineers who do not necessarily have an extensive background in statistics. Knowledge of this framework is essential today when on one hand, time for product development, testing and evaluation is short in a globalized market, while on the other is the prevalence of computing hardware and software that has virtually eliminated the chores of data-crunching arising from product evaluation and proofing activities.
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Scott, Colton M., and Jason R. Kolodziej. "A Novelty Detection Approach to Compressor Valve Fault Detection and Localization." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23314.
Повний текст джерелаАнотація:
Abstract Presented in this paper is the development of a vibration-based novelty detection algorithm for locating and identifying valve wear within industrial reciprocating compressors through the combined use of time-frequency analysis, image-based pattern recognition, and one-class support vector machines. A commonly reported cause of valve wear-related machine downtime is wear in the valve seat, causing a change in flow profile into and out of the compression chamber. Seeded faults are introduced into the valve manifolds of the ESH-1 industrial compressor and vibration data collected and separated into individual crank cycles before being analyzed using time-frequency analysis. The result is processed as an image and features used for classification are extracted using 1st and 2nd order images statistics and shape factors. A one-class support vector machine learning algorithm is then trained using data collected during healthy operation and then used to both detect and locate anomalous valve behavior with a greater than 82% success rate.