| 1. |
- Naghavi, Mohsen, et al.
(författare)
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Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013
- 2015
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Ingår i: The Lancet. - 1474-547X .- 0140-6736. ; 385:9963, s. 117-171
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Tidskriftsartikel (refereegranskat)abstract
- Background Up-to-date evidence on levels and trends for age-sex-specifi c all-cause and cause-specifi c mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specifi c all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specifi c causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65.3 years (UI 65.0-65.6) in 1990, to 71.5 years (UI 71.0-71.9) in 2013, while the number of deaths increased from 47.5 million (UI 46.8-48.2) to 54.9 million (UI 53.6-56.3) over the same interval. Global progress masked variation by age and sex: for children, average absolute diff erences between countries decreased but relative diff erences increased. For women aged 25-39 years and older than 75 years and for men aged 20-49 years and 65 years and older, both absolute and relative diff erences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10.7%, from 4.3 million deaths in 1990 to 4.8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specifi c mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade.
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| 2. |
- Forouzanfar, Mohammad H, et al.
(författare)
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Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013 : a systematic analysis for the Global Burden of Disease Study 2013.
- 2015
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Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 386:10010, s. 2287-2323
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.METHODS: Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk-outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990-2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol.FINDINGS: All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8-58·5) of deaths and 41·6% (40·1-43·0) of DALYs. Risks quantified account for 87·9% (86·5-89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa.INTERPRETATION: Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.FUNDING: Bill & Melinda Gates Foundation.
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| 3. |
- Wang, Haidong, et al.
(författare)
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Global, regional, and national levels of neonatal, infant, and under-5 mortality during 1990-2013 : a systematic analysis for the Global Burden of Disease Study 2013
- 2014
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Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 384:9947, s. 957-979
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Remarkable financial and political efforts have been focused on the reduction of child mortality during the past few decades. Timely measurements of levels and trends in under-5 mortality are important to assess progress towards the Millennium Development Goal 4 (MDG 4) target of reduction of child mortality by two thirds from 1990 to 2015, and to identify models of success.METHODS: We generated updated estimates of child mortality in early neonatal (age 0-6 days), late neonatal (7-28 days), postneonatal (29-364 days), childhood (1-4 years), and under-5 (0-4 years) age groups for 188 countries from 1970 to 2013, with more than 29 000 survey, census, vital registration, and sample registration datapoints. We used Gaussian process regression with adjustments for bias and non-sampling error to synthesise the data for under-5 mortality for each country, and a separate model to estimate mortality for more detailed age groups. We used explanatory mixed effects regression models to assess the association between under-5 mortality and income per person, maternal education, HIV child death rates, secular shifts, and other factors. To quantify the contribution of these different factors and birth numbers to the change in numbers of deaths in under-5 age groups from 1990 to 2013, we used Shapley decomposition. We used estimated rates of change between 2000 and 2013 to construct under-5 mortality rate scenarios out to 2030.FINDINGS: We estimated that 6·3 million (95% UI 6·0-6·6) children under-5 died in 2013, a 64% reduction from 17·6 million (17·1-18·1) in 1970. In 2013, child mortality rates ranged from 152·5 per 1000 livebirths (130·6-177·4) in Guinea-Bissau to 2·3 (1·8-2·9) per 1000 in Singapore. The annualised rates of change from 1990 to 2013 ranged from -6·8% to 0·1%. 99 of 188 countries, including 43 of 48 countries in sub-Saharan Africa, had faster decreases in child mortality during 2000-13 than during 1990-2000. In 2013, neonatal deaths accounted for 41·6% of under-5 deaths compared with 37·4% in 1990. Compared with 1990, in 2013, rising numbers of births, especially in sub-Saharan Africa, led to 1·4 million more child deaths, and rising income per person and maternal education led to 0·9 million and 2·2 million fewer deaths, respectively. Changes in secular trends led to 4·2 million fewer deaths. Unexplained factors accounted for only -1% of the change in child deaths. In 30 developing countries, decreases since 2000 have been faster than predicted attributable to income, education, and secular shift alone.INTERPRETATION: Only 27 developing countries are expected to achieve MDG 4. Decreases since 2000 in under-5 mortality rates are accelerating in many developing countries, especially in sub-Saharan Africa. The Millennium Declaration and increased development assistance for health might have been a factor in faster decreases in some developing countries. Without further accelerated progress, many countries in west and central Africa will still have high levels of under-5 mortality in 2030.
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| 4. |
- Ma, Shuaiyin, et al.
(författare)
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Data-driven sustainable intelligent manufacturing based on demand response for energy-intensive industries
- 2020
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Ingår i: Journal of Cleaner Production. - : ELSEVIER SCI LTD. - 0959-6526 .- 1879-1786. ; 274
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Tidskriftsartikel (refereegranskat)abstract
- The circular economy plays an important role in energy-intensive industries, aiming to contribute to ethical sustainable societal development. Energy demand response is a key actor for cleaner production and circular economy strategy. In the Industry 4.0 context, the advanced technologies (e.g. cloud computing, Internet of things, cyber-physical system, digital twin and big data analytics) provide numerous opportunities for the implementation of a cleaner production strategy and the development of intelligent manufacturing. This paper presented a framework of data-driven sustainable intelligent/smart manufacturing based on demand response for energy-intensive industries. The technological architecture was designed to implement the proposed framework, and multi-level demand response models were developed based on machine, shop-floor and factory to save energy cost. Finally, an application of ball mills in a slurry shop-floor of a partner company was presented to demonstrate the proposed framework and models. Results showed that the energy efficiency of ball mills can be greatly improved. The energy cost of the slurry shop-floor saved approximately 19.33% by considering electricity demand response using particle swarm optimisation. This study provides a practical approach to make effective and energy-efficient decisions for energy-intensive manufacturing enterprises. (C) 2020 The Author(s). Published by Elsevier Ltd.
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| 5. |
- Ma, Shuaiyin, et al.
(författare)
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Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries
- 2022
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Ingår i: Applied Energy. - : Elsevier Science Ltd. - 0306-2619 .- 1872-9118. ; 326
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Tidskriftsartikel (refereegranskat)abstract
- Internet of Things (IoT) technology, which has made manufacturing processes more smart, efficient and sustainable, has received increasing attention from the industry and academia. As one of the most important applications for IoT, sustainable smart manufacturing enables lower cost, higher productivity and flexibility, better quality and sustainability during the product lifecycle management. Over the years, numerous enterprises have promoted the implementation of both sustainable and smart manufacturing. In the Industry 4.0 context, a digital twin is widely used to achieve smart manufacturing, although this approach often ignores sustainability. This study aims to simultaneously consider digital twin and big data technologies to propose a sustainable smart manufacturing strategy based on information management systems for energy-intensive industries (EIIs) from the product lifecycle perspective. The integration of digital twin and big data provides key technologies for data acquisition in energy-intensive production environments, prediction and mining in uncertain environments as well as real-time control in complex working conditions. Moreover, a digital twin-driven operation mechanism and an overall framework of big data cleansing and integration are designed to explain and illustrate sustainable smart manufacturing. Two case studies from Southern and Northern China demonstrate the efficacy of the strategy, with the results showing that Companies A and B achieved the goals of energy saving and cost reduction after implementing the proposed strategy. By applying an energy management system, the unit energy consumption and energy cost of production in Company A decreased by at least 3%. In addition, the cradle-to-gate lifecycle big data analysis indicates that the costs of environmental protection in Company B decrease significantly. Finally, the effectiveness of the proposed strategy and some managerial insights for EIIs in China are analysed and discussed.
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| 6. |
- Vos, Theo, et al.
(författare)
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Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013
- 2015
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Ingår i: The Lancet. - 1474-547X .- 0140-6736. ; 386:9995, s. 743-800
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Tidskriftsartikel (refereegranskat)abstract
- Background Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013), we estimated these quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013. Methods Estimates were calculated for disease and injury incidence, prevalence, and YLDs using GBD 2010 methods with some important refinements. Results for incidence of acute disorders and prevalence of chronic disorders are new additions to the analysis. Key improvements include expansion to the cause and sequelae list, updated systematic reviews, use of detailed injury codes, improvements to the Bayesian meta-regression method (DisMod-MR), and use of severity splits for various causes. An index of data representativeness, showing data availability, was calculated for each cause and impairment during three periods globally and at the country level for 2013. In total, 35 620 distinct sources of data were used and documented to calculated estimates for 301 diseases and injuries and 2337 sequelae. The comorbidity simulation provides estimates for the number of sequelae, concurrently, by individuals by country, year, age, and sex. Disability weights were updated with the addition of new population-based survey data from four countries. Findings Disease and injury were highly prevalent; only a small fraction of individuals had no sequelae. Comorbidity rose substantially with age and in absolute terms from 1990 to 2013. Incidence of acute sequelae were predominantly infectious diseases and short-term injuries, with over 2 billion cases of upper respiratory infections and diarrhoeal disease episodes in 2013, with the notable exception of tooth pain due to permanent caries with more than 200 million incident cases in 2013. Conversely, leading chronic sequelae were largely attributable to non-communicable diseases, with prevalence estimates for asymptomatic permanent caries and tension-type headache of 2.4 billion and 1.6 billion, respectively. The distribution of the number of sequelae in populations varied widely across regions, with an expected relation between age and disease prevalence. YLDs for both sexes increased from 537.6 million in 1990 to 764.8 million in 2013 due to population growth and ageing, whereas the age-standardised rate decreased little from 114.87 per 1000 people to 110.31 per 1000 people between 1990 and 2013. Leading causes of YLDs included low back pain and major depressive disorder among the top ten causes of YLDs in every country. YLD rates per person, by major cause groups, indicated the main drivers of increases were due to musculoskeletal, mental, and substance use disorders, neurological disorders, and chronic respiratory diseases; however HIV/AIDS was a notable driver of increasing YLDs in sub-Saharan Africa. Also, the proportion of disability-adjusted life years due to YLDs increased globally from 21.1% in 1990 to 31.2% in 2013. Interpretation Ageing of the world's population is leading to a substantial increase in the numbers of individuals with sequelae of diseases and injuries. Rates of YLDs are declining much more slowly than mortality rates. The non-fatal dimensions of disease and injury will require more and more attention from health systems. The transition to non-fatal outcomes as the dominant source of burden of disease is occurring rapidly outside of sub-Saharan Africa. Our results can guide future health initiatives through examination of epidemiological trends and a better understanding of variation across countries.
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| 7. |
- Wang, Haidong, et al.
(författare)
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Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015
- 2016
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Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 388:10053, s. 1459-1544
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures.METHODS: We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).FINDINGS: Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4-61·9) in 1980 to 71·8 years (71·5-72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7-17·4), to 62·6 years (56·5-70·2). Total deaths increased by 4·1% (2·6-5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8-18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6-16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9-14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1-44·6), malaria (43·1%, 34·7-51·8), neonatal preterm birth complications (29·8%, 24·8-34·9), and maternal disorders (29·1%, 19·3-37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death.INTERPRETATION: At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems.
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| 8. |
- Yan, Yinglin, et al.
(författare)
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Waste Office Paper Derived Cellulose-Based Carbon Host in Freestanding Cathodes for Lithium-Sulfur Batteries
- 2022
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Ingår i: ChemElectroChem. - : John Wiley & Sons. - 2196-0216. ; 9:11
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Tidskriftsartikel (refereegranskat)abstract
- Due to large sulfur (S) content and simple manufacturing techniques, free-standing cathodes for lithium-sulfur (Li−S) batteries are gaining a lot of attention recently. Waste office paper, which is consumed in large quantities annually, was used to make a free-standing paper-based carbon (FPC) substrate, which inherited fiber-like morphology. In addition, reduced graphene oxide (rGO) nanosheets modified FPC (rGO@FPC) host was also prepared by a vacuum filtration method. After S impregnation, the FPC/S and rGO@FPC/S free-standing cathodes were employed in Li−S batteries. The rGO@FPC/S free-standing cathode exhibited extremely competitive electrochemical performance, including a reversible discharge capacity of 315 mAh g−1 at 0.5 C after 500 cycles. This is due to the uniform S distribution, which boosts the utilization ratio, and the significant blocking action for polysulfide ions, which prevents the redox shuttle effect.
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| 9. |
- Zhang, Yingfeng, et al.
(författare)
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A big data driven analytical framework for energy-intensive manufacturing industries
- 2018
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Ingår i: Journal of Cleaner Production. - : ELSEVIER SCI LTD. - 0959-6526 .- 1879-1786. ; 197, s. 57-72
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Tidskriftsartikel (refereegranskat)abstract
- Energy-intensive industries account for almost 51% of energy consumption in China. A continuous improvement in energy efficiency is important for energy-intensive industries. Cleaner production has proven itself as an effective way to improve energy efficiency and reduce energy consumption. However, there is a lack of manufacturing data due to the difficult implementation of sensors in harsh production environment, such as high temperature, high pressure, high acid, high alkali, and smoky environment which hinders the implementation of the cleaner production strategy. Thanks to the rapid development of the Internet of Things, many data can be sensed and collected in the manufacturing processes. In this paper, a big data driven analytical framework is proposed to reduce the energy consumption and emission for energy-intensive manufacturing industries. Then, two key technologies of the proposed framework, namely energy big data acquisition and energy big data mining, are utilized to implement energy big data analytics. Finally, an application scenario of ball mills in a pulp workshop of a partner company is presented to demonstrate the proposed framework. The results show that the energy consumption and energy costs are reduced by 3% and 4% respectively. These improvements can promote the implementation of cleaner production strategy and contribute to the sustainable development of energy intensive manufacturing industries.
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| 10. |
- Zhao, Zhuohui, et al.
(författare)
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Ambient carbon monoxide associated with alleviated respiratory inflammation in healthy young adults
- 2016
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Ingår i: Environmental Pollution. - : Elsevier BV. - 0269-7491 .- 1873-6424. ; 208, s. 294-298
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Tidskriftsartikel (refereegranskat)abstract
- There is increasing controversy on whether acute exposure to ambient carbon monoxide (CO) is hazardous on respiratory health. We therefore performed a longitudinal panel study to evaluate the acute effects of ambient CO on fractional exhaled nitric oxide (FeNO), a well-established biomarker of airway inflammation. We completed 4-6 rounds of health examinations among 75 healthy young adults during April to June in 2013 in Shanghai, China. We applied the linear mixed-effect model to investigate the short-term associations between CO and FeNO. CO exposure during 2-72 h preceding health tests was significantly associated with decreased FeNO levels. For example, an interquartile range increase (0.3 mg/m(3)) of 2-h CO exposure corresponded to 10.6% decrease in FeNO. This association remained when controlling for the concomitant exposure to co-pollutants. This study provided support that short-term exposure to ambient CO might be related with reduced levels of FeNO, a biomarker of lower airway inflammation.
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| 11. |
- Cao, Hongru, et al.
(författare)
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Unsupervised domain-share CNN for machine fault transfer diagnosis from steady speeds to time-varying speeds
- 2022
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Ingår i: Journal of manufacturing systems. - : Elsevier. - 0278-6125 .- 1878-6642. ; 62, s. 186-198
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Tidskriftsartikel (refereegranskat)abstract
- The existing deep transfer learning-based intelligent fault diagnosis studies for machinery mainly consider steady speed scenarios, and there exists a problem of low diagnosis efficiency. In order to overcome these limitations, an unsupervised domain-share convolutional neural network (CNN) is proposed for efficient fault transfer diagnosis of machines from steady speeds to time-varying speeds. First, a Cauchy kernel-induced maximum mean discrepancy based on unbiased estimation is developed for improving the efficiency and robustness of feature adaptation. Secondly, an unsupervised domain-share CNN is constructed to simultaneously extract the domain-invariant features from the source domain and the target domain. Finally, adjustable and segmented balance factors are designed to flexibly weigh the distribution-adaptation loss and cross-entropy loss to improve diagnosis accuracy and transferability. The proposed method analyzes raw vibration signals collected from bearings and gears under different rotating speeds. Results of case studies show that the proposed method can achieve higher diagnosis accuracy, faster convergence, and better robustness than the reported methods, which demonstrates its potential applications in machine fault transfer diagnosis from a steady speed condition to a time-varying speed condition.
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| 12. |
- Chen, Fei'er, et al.
(författare)
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The effects of PM2.5 on asthmatic and allergic diseases or symptoms in preschool children of six Chinese cities, based on China, Children, Homes and Health (CCHH) project
- 2018
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Ingår i: Environmental Pollution. - : Elsevier BV. - 0269-7491 .- 1873-6424. ; 232, s. 329-337
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Tidskriftsartikel (refereegranskat)abstract
- The urbanization and industrialization in China is accompanied by bad air quality, and the prevalence of asthma in Chinese children has been increasing in recent years. To investigate the associations between ambient PM2.5 levels and asthmatic and allergic diseases or symptoms in preschool children in China, we assigned PM2.5 exposure data from the Global Burden of Disease (GBD) project to 205 kindergartens at a spatial resolution of 0.1° × 0.1° in six cities in China (Shanghai, Nanjing, Chongqing, Changsha, Urumqi, and Taiyuan). A hierarchical multiple logistical regression model was applied to analyze the associations between kindergarten-level PM2.5 exposure and individual-level outcomes of asthmatic and allergic symptoms. The individual-level variables, including gender, age, family history of asthma and allergic diseases, breastfeeding, parental smoking, indoor dampness, interior decoration pollution, household annual income, and city-level variable-annual temperature were adjusted. A total of 30,759 children (average age 4.6 years, 51.7% boys) were enrolled in this study. Apart from family history, indoor dampness, and decoration as predominant risk factors, we found that an increase of 10 μg/m3 of the annual PM2.5 was positively associated with the prevalence of allergic rhinitis by an odds ratio (OR) of 1.20 (95% confidence interval [CI] 1.11, 1.29) and diagnosed asthma by OR of 1.10 (95% CI 1.03, 1.18). Those who lived in non-urban (vs. urban) areas were exposed to more severe indoor air pollution arising from biomass combustion and had significantly higher ORs between PM2.5 and allergic rhinitis and current rhinitis. Our study suggested that long-term exposure to PM2.5 might increase the risks of asthmatic and allergic diseases or symptoms in preschool children in China. Compared to those living in urban areas, children living in suburban or rural areas had a higher risk of PM2.5 exposure.
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| 13. |
- Fang, Xin, et al.
(författare)
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Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality : a time-series study
- 2016
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Ingår i: BMJ Open. - London, England : BMJ Publishing Group Ltd. - 2044-6055. ; 6:8
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To demonstrate an application of Bayesian model averaging (BMA) with generalised additive mixed models (GAMM) and provide a novel modelling technique to assess the association between inhalable coarse particles (PM10) and respiratory mortality in time-series studies.Design: A time-series study using regional death registry between 2009 and 2010.Setting: 8 districts in a large metropolitan area in Northern China.Participants: 9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010.Main outcome measures: Per cent increase in daily respiratory mortality rate (MR) per interquartile range (IQR) increase of PM10 concentration and corresponding 95% confidence interval (CI) in single-pollutant and multipollutant (including NOx, CO) models.Results: The Bayesian model averaged GAMM (GAMM+ BMA) and the optimal GAMM of PM10, multipollutants and principal components (PCs) of multipollutants showed comparable results for the effect of PM10 on daily respiratory MR, that is, one IQR increase in PM10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory MR. However, GAMM+ BMA gave slightly but noticeable wider CIs for the single-pollutant model (-1.09 to 4.28 vs -1.08 to 3.93) and the PCs-based model (-2.23 to 4.07 vs -2.03 vs 3.88). The CIs of the multiple-pollutant model from two methods are similar, that is, -1.12 to 4.85 versus -1.11 versus 4.83.Conclusions: The BMA method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes.
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| 14. |
- Haidong, Shao, et al.
(författare)
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Enhanced deep gated recurrent unit and complex wavelet packet energy moment entropy for early fault prognosis of bearing
- 2020
-
Ingår i: Knowledge-Based Systems. - : Elsevier. - 0950-7051 .- 1872-7409. ; 188
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Tidskriftsartikel (refereegranskat)abstract
- Early fault prognosis of bearing is a very meaningful yet challenging task to improve the security of rotating machinery. For this purpose, a novel method based on enhanced deep gated recurrent unit and complex wavelet packet energy moment entropy is proposed in this paper. First, complex wavelet packet energy moment entropy is defined as a new monitoring index to characterize bearing performance degradation. Second, deep gated recurrent unit network is constructed to capture the nonlinear mapping relationship hidden in the defined monitoring index. Finally, a modified training algorithm based on learning rate decay strategy is developed to enhance the prognosis capability of the constructed deep model. The proposed method is applied to analyze the simulated and experimental signals of bearing. The results demonstrate that the proposed method is more superior in sensibility and accuracy to the existing methods.
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| 15. |
- Han, Songyu, et al.
(författare)
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End-to-end chiller fault diagnosis using fused attention mechanism and dynamic cross-entropy under imbalanced datasets
- 2022
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Ingår i: Building and Environment. - : Elsevier. - 0360-1323 .- 1873-684X. ; 212
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Tidskriftsartikel (refereegranskat)abstract
- Fault diagnosis techniques play an increasingly important role in the operation and maintenance of smart city systems. Artificial intelligence improves the efficiency of chiller system fault diagnosis, and greatly reduces the energy consumption of urban buildings. The existing intelligent fault diagnosis methods of chiller mostly rely on balanced training datasets; lacking fault samples makes these methods incompetent to extract reliable features to recognize abnormal machine conditions, resulting in the degraded performance. To overcome the deficiencies of reported studies, a new method, called end-to-end chiller fault diagnosis, is proposed using a fused attention mechanism and dynamic cross-entropy. Firstly, a one-dimensional convolution network (1D-CNN) and long-short term memory (LSTM) are combined to capture the spatial-temporal features from the original data directly. Afterwards, a fused attention mechanism is developed to further refine the extracted features to increase the contribution of crucial features and achieve high-quality diagnostic information mining. Finally, the dynamic cross-entropy (DCE) is designed for updating the imbalance factor in real-time, with more focus on the hard-classified types. The experimental analysis results demonstrate the feasibility and superiority of the proposed method in identifying chiller system faults with imbalanced datasets.
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| 16. |
- He, Zhiyi, et al.
(författare)
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Deep transfer multi-wavelet auto-encoder for intelligent fault diagnosis of gearbox with few target training samples
- 2020
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Ingår i: Knowledge-Based Systems. - : Elsevier. - 0950-7051 .- 1872-7409. ; 191
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Tidskriftsartikel (refereegranskat)abstract
- Lack of typical fault samples remains a huge challenge for intelligent fault diagnosis of gearbox. In this paper, a novel approach named deep transfer multi-wavelet auto-encoder is presented for gearbox intelligent fault diagnosis with few training samples. Firstly, new-type deep multi-wavelet auto-encoder is designed for learning important features of the collected vibration signals of gearbox. Secondly, high-quality auxiliary samples are selected based on similarity measure to well pre-train a source model sharing similar characteristics with the target domain. Thirdly, parameter knowledge acquired from the source model is transferred to target model using very few target training samples. Transfer diagnosis cases for different fault severities and compound faults of gearbox confirm the feasibility of the proposed approach even if the working conditions have significant changes.
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| 17. |
- He, Zhiyi, et al.
(författare)
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Kernel flexible and displaceable convex hull based tensor machine for gearbox fault intelligent diagnosis with multi-source signals
- 2020
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Ingår i: Measurement. - : Elsevier. - 0263-2241 .- 1873-412X. ; 163
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Tidskriftsartikel (refereegranskat)abstract
- The methods based on traditional pattern recognition and deep learning have been successfully applied in gearbox intelligent diagnosis. However, traditional pattern recognition methods cannot directly classify feature tensors of multi-source signals, and deep learning networks hardly handle the classification of small samples. Therefore, for the gearbox intelligent diagnosis with multi-source signals, a novel tensor classifier called kernel flexible and displaceable convex hull based tensor machine (KFDCH-TM) is proposed. In KFDCH-TM, the kernel flexible and displaceable convex hull of tensor samples in tensor feature space is defined firstly. Then, an optimal separating hyper-plane between two kernel flexible and displaceable convex hulls is constructed. Meanwhile, feature tensors extracted from multi-source signals through wavelet packet transform (WPT) are used to diagnose gearbox fault by KFDCH-TM. The results of two cases demonstrate that KFDCH-TM can effectively identify gearbox fault with multi-source signals and has better robustness.
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| 18. |
- Kassebaum, Nicholas J., et al.
(författare)
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Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015 : a systematic analysis for the Global Burden of Disease Study 2015
- 2016
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Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 388:10053, s. 1603-1658
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Tidskriftsartikel (refereegranskat)abstract
- Background Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. Findings Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs off set by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2.9 years (95% uncertainty interval 2.9-3.0) for men and 3.5 years (3.4-3.7) for women, while HALE at age 65 years improved by 0.85 years (0.78-0.92) and 1.2 years (1.1-1.3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. Interpretation Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum.
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| 19. |
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| 20. |
- Liu, Biyu, et al.
(författare)
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A min–max solution to optimise planned lead time in a remanufacturing system
- 2019
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Ingår i: International Transactions in Operational Research. - : John Wiley & Sons. - 0969-6016 .- 1475-3995. ; 26:2, s. 485-506
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Tidskriftsartikel (refereegranskat)abstract
- Determining a rational planned lead time (PLT) is a critical and difficult problem in production planning, especially for a remanufacturing system. This paper considers an optimisation problem of the PLT in a make-to-order remanufacturing system to coordinate disassembly–remanufacturing–reassembly and to improve performance. This optimisation model is designed to determine the PLT that minimises the inventory holding and shortage costs. Given the unknown distribution of remanufacturing time but with known first and second moments, this model is solved by a min–max approach, which can capture distributions with the same first and second moments. How the PLT and total cost are affected by yield rate with different first and second moments, unit holding cost, unit shortage cost and purchasing lead time are also investigated through numerical examples in this paper. The results of this study are shown to be consistent with practice and can be a support to decision-making in production planning and scheduling for remanufacturing.
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| 21. |
- Liu, Biyu, et al.
(författare)
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Maintenance service strategy for leased equipment : integrating lessor-preventive maintenance and lessee-careful protection efforts
- 2021
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Ingår i: Computers & industrial engineering. - : Elsevier. - 0360-8352 .- 1879-0550. ; 156
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Tidskriftsartikel (refereegranskat)abstract
- Lessees may abuse equipment during the lease period since lacking of ownership, thereby increasing lessors’ repair cost and lessees’ downtime losses. This study integrates lessees’ effort to protect leased equipment during the lease period with lessors’ preventive maintenance (PM) into maintenance service strategies. It is proved in a non-cooperative game, neither party achieves the cooperative game’s ideal revenue, but improvement in the lessee’s effort level and lessor’s PM degree can increase the other party’s revenue. A cost-sharing contract model is designed to achieve the maximum revenue as in a cooperative game and ensure Pareto improvement of the leasing parties. In the contract, the lessor grants the lessee a rental discount, and the lessor’s PM cost and lessee’s effort cost are shared with cost-sharing coefficients. Conditions under which the ideal revenue and Pareto improvement can be achieved are discussed. Numerical examples are provided to illustrate the effects of contract parameters, unit penalty on the effort level, and revenue. Managerial insights are finally proposed for leasing parties. The results show: the effect of the effort level and PM degree on equipment failures is marginally diminishing; proposed cost-sharing contract model can achieve the ideal revenue and Pareto improvement; the rental discount has a greater impact on the lessee, while the cost-sharing coefficients have a greater impact on the lessor; and increasing the unit penalty decreases (increases) the lessor’s (lessee’s) revenue but maintains the effort level at constant.
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| 22. |
- Liu, Biyu, et al.
(författare)
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Optimal Operational Decision Making of Manufacturers and Authorized Remanufacturers with Patent Licensing under Carbon Cap-and-Trade Regulations
- 2020
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Ingår i: Complexity. - : Hindawi Publishing Corporation. - 1076-2787 .- 1099-0526. ; 2020
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Tidskriftsartikel (refereegranskat)abstract
- Constrained by production capacity and the pressure to reduce emissions, many original equipment manufacturers (OEMs) authorize third-party remanufacturers (TPRs) to remanufacture patented products. We investigate the operational decisions of OEMs and authorized TPRs under carbon cap-and-trade regulations in a two-echelon supply chain. We first formulate an operational decision model for OEMs before a TPR enters. Then, for the cases of centralized and decentralized decision making, we formulate an operational decision-making model for the TPR and, subsequently, establish one for the OEM after the TPR enters. We further analyze the effects of carbon emissions cap, trading price of carbon permits, yield rate, and consumer willingness to pay (WTP) on optimal decisions. Our results indicate: whether TPRs accept authorization remanufacturing depending on the ratio of carbon emissions cap to carbon emissions for producing per remanufactured product; royalty rate is negatively affected by trading price of carbon permits and per remanufactured product’ carbon emissions other than that for per new product, and can offset the threat caused by TPRs; the implementation of carbon cap-and-trade regulations causes OEMs to charge TPRs lower royalty rate; centralized decision making increases the total profit of the supply chain and delivers superior environmental benefits. As yield rate and WTP increase, the total profit increases, increasingly sensitive to WTP.
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| 23. |
- Liu, Biyu, et al.
(författare)
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Supplier evaluation and selection in a sustainable supply chain based on fuzzy-BWM, entropy method and grey relational TOPSIS
- 2023
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Ingår i: Journal of Intelligent & Fuzzy Systems. - : IOS Press. - 1064-1246 .- 1875-8967. ; 44:6, s. 9919-9932
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Tidskriftsartikel (refereegranskat)abstract
- Suppliers significantly affect the effectiveness of sustainable supply chain management. Hence, it is extremely important to evaluate and select suppliers scientifically and objectively. Based on the theory of triple bottom line (economic, social, and environmental dimension) and a balanced scorecard, a measureable supplier evaluation framework in a sustainable supply chain is first formulated. Second, to reduce the defects of the single weight method, the subjective and objective weights of evaluation indicators are determined by combining the fuzzy best-worst method (BWM) and the entropy method, and then the combination weights are obtained through linear weighting. Third, the grey relational technique for order performance by similarity to ideal solution (TOPSIS) method is further adopted to evaluate and rank the suppliers. Finally, a case study illustrates and demonstrates the availability of the proposed supplier evaluation index system and evaluation method. Subsequently, some suggestions are proposed according to the results.
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| 24. |
- Yang, Haidong, et al.
(författare)
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Emergency decision-making model of suppliers with updating information in cases of sudden accidents
- 2021
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Ingår i: Computers & industrial engineering. - : Elsevier. - 0360-8352 .- 1879-0550. ; 162
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Tidskriftsartikel (refereegranskat)abstract
- In view of uncertainties caused by sudden accidents (SAs) and affecting retailers’ demand in many districts, it is difficult for suppliers to determine when and how many products to procure/produce. Considering a supply chain consisting of two types of competing suppliers and multi-retailer, this work studies the suppliers’ optimal emergency procurement/production decision (EPD) with information updating. Firstly, a probability evolution model with information updating to describe the probability of the retailers’ procurement behavior and the occurrence probability of supply disruption (SD) is inferred. Secondly, suppliers’ EPDs regarding retailers’ procurement behavior and occurrence probability of SD are discussed and a real-time updated emergency decision-making model (EDM) is proposed based on Stackelberg game and Bayesian inference. Thirdly, the value of information updating and the critical factors that affect the suppliers’ optimal EPD are quantitatively analysed. Numerical examples are finally provided to verify the EDM. Results indicate that information is the premise and foundation for the suppliers to deal with SA effectively; suppliers can easily determine when and how many products to procure/produce based on the proposed EDM; it is demonstrated that for any chosen supplier strategy, there exists a corresponding optimal procurement/production quantity for the suppliers that maximises the expected profits. Moreover, the suppliers’ EPD with information updating is affected by cost parameters, with the rank of information collection cost coefficient, unit procurement/production cost, unit sales price, unit holding cost and unit shortage cost, from apparently to slightly.
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| 25. |
- Yang, Haidong, et al.
(författare)
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Identification of source information for sudden hazardous chemical leakage accidents in surface water on the basis of particle swarm optimisation, differential evolution and Metropolis-Hastings sampling
- 2021
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Ingår i: Environmental Science and Pollution Research. - : Springer Nature. - 0944-1344 .- 1614-7499. ; 28:47, s. 67292-67309
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Tidskriftsartikel (refereegranskat)abstract
- A quick and accurate identification of source information on sudden hazardous chemical leakage accident is crucial for early accident warning and emergency response. This study firstly regards source identification problem of sudden hazardous chemical leakage accidents as an inverse problem and presents a source identification model based on the Bayesian framework. Secondly, a new identification method is designed on the basis of particle swarm optimisation (PSO), differential evolution (DE) and the Metropolis–Hastings (M–H) sampling method. Lastly, the designed method, i.e. PSO-DE-MH, is verified by an outdoor experiment analyses in a section of the South–North Water Transfer Project. Results show that the number of iterations, the average absolute error, the average relative error and the average standard deviations of the identification results obtained by PSO-DE-MH are less than those of PSO-DE and DE-MH. Moreover, the relative error and the sampling relative error of the identification results under five different measurement errors (MEs) (σ = 0.01, 0.05, 0.1, 0.15, 0.2) are less than 9.5% and 0.2%, respectively. The designed method is effective even when the standard deviation of the ME increases to 0.2. Therefore, the designed method can effectively and accurately obtain the source information of sudden hazardous chemical leakage accidents. This study provides a new idea and method to solve the difficult problems of emergency management.
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| 26. |
- Yang, Haidong, et al.
(författare)
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On source identification method for sudden water pollution accidents
- 2014
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Ingår i: Shui Kexue Jinzhan. - 1001-6791. ; 25:1, s. 122-129
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Tidskriftsartikel (refereegranskat)abstract
- In order to solve the source identification problem of sudden water pollution accident accurately and quickly, a method based on the Differential Evolution and Markov Chain Monte Carlo (MCMC) is presented. First, the problem is considered as a Bayesian estimation problem, and the posterior probability distribution of the unknown parameters that include source's position, intensity and events' initial time are deduced with Bayesian inference. Second, these unknown parameters are estimated by sampling the posterior probability distribution using the Differential Evolution algorithm and Markov Chain Monte Carlo simulation, and the sources are further identified. To test the effectiveness and accuracy of the proposed method, numerical experiments are carried out, and the model result is compared to that of the Bayesian-MCMC method. The conclusions are as following: three fourth of the iterations can be reduced, the average relative error of the source's position, intensity and events initial time are reduced 1.23%, 2.23% and 4.15%, their mean errors are decreased 0.39%, 0.83% and 1.49% by using the proposed method. The latter is thus more stable and robust than the Bayesian-MCMC method, and is able to identify the sudden water pollution accidents' source effectively. Therefore, this study provides a new approach and method to solve the difficult traceability problem of sudden water pollution accidents.
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| 27. |
- Yang, Jiaojiao, et al.
(författare)
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Electrochemically Active, Compressible, and Conducting Silk Fibroin Hydrogels
- 2020
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Ingår i: Industrial & Engineering Chemistry Research. - : AMER CHEMICAL SOC. - 0888-5885 .- 1520-5045. ; 59:19, s. 9310-9317
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Tidskriftsartikel (refereegranskat)abstract
- Silk fibroin-based conducting hydrogels possess hierarchical structural motifs featuring unique properties, but the development of such materials has proven to be challenging. Herein, we develop a novel strategy for the fabrication of a conducting silk fibroin hydrogel based on an interpenetrated network of poly(3,4-ethylene dioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) and silk fibroin. The hydrogel possesses good electrical conductivity and considerable capacitance and cycling stability due to the existence of the PEDOT conducting network, as well as enhanced mechanical properties such as compressibility due to beta-sheets in the silk fibroin network and Ca2+ cross-linking of the PSS components. A symmetric charge storage device based on conductive silk fibroin hydrogel electrodes exhibited a remarkable areal capacitance of 1.1 F cm(-2) at 0.5 mA cm(-2), as well as a good capacitive response under a compressed state. This combination of compression strength and electrochemical properties makes this conducting silk hydrogel a potential material for unconventional energy storage applications.
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| 28. |
- Zhang, Liangwei, et al.
(författare)
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An unsupervised end-to-end approach to fault detection in delta 3D printers using deep support vector data description
- 2024
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Ingår i: Journal of manufacturing systems. - : Elsevier. - 0278-6125 .- 1878-6642. ; 72, s. 214-228
-
Tidskriftsartikel (refereegranskat)abstract
- Fault detection in 3D printers is crucial for safety and quality assurance, emphasizing proactive prediction over reactive rectification based on manufacturing factors. Presently, most detection techniques rely on shallow models with limited representational capabilities, necessitating manual feature extraction from the captured signals. This manual process is not only cumbersome and potentially costly but often requires intricate domain-specific knowledge. Additionally, these handcrafted features might not optimally distinguish between normal and faulty samples, potentially reducing prediction accuracy. In this study, we introduce an end-to-end approach using the Deep Support Vector Data Description model for fault detection in 3D printers. This design inherently facilitates automatic feature learning, where the features are synergistically optimized for fault detection. Our experiments leverage magnetic field signals for fault detection in 3D printers, using 1D convolutional layers to discern temporal signal patterns and wide kernels in the initial layer to mitigate high-frequency noise. Furthermore, our model can be easily adapted to integrate multi-channel signals for enhanced accuracy. Evaluations on real-world data from a delta 3D printer underscore the superiority of our method compared to existing alternatives.
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| 29. |
- Zhang, Liangwei, et al.
(författare)
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Wave-ConvNeXt : An Efficient and Precise Fault Diagnosis Method for IIoT Leveraging Tailored ConvNeXt and Wavelet Transform
- 2024
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Ingår i: IEEE Internet of Things Journal. - 2327-4662. ; , s. 1-1
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Tidskriftsartikel (refereegranskat)abstract
- The burgeoning field of the Industrial Internet of Things (IIoT) necessitates advanced fault diagnosis methods capable of navigating the dual challenges of high predictive accuracy and the constraints of edge computing environments. Our study introduces Wave-ConvNeXt, a novel fault diagnosis model that seamlessly integrates the state-of-the-art ConvNeXt architecture with Wavelet Transform. This innovative model stands out for its lightweight design yet delivers exceptional accuracy in fault diagnosis. In Wave-ConvNeXt, we re-engineer the ConvNeXt model for IIoT applications by adopting onedimensional convolution, tailored for processing high-frequency, non-periodic inputs. This adaptation is complemented by replacing the traditional “patchify” layer with a Wavelet transform layer, which simplifies input signals into sub-signals, thereby easing learning complexities and diminishing the dependence on elaborate deep architectures. Further enhancing this model, we incorporate a squeeze-and-excitation module, enriching its ability to prioritize channel-wise feature relevance, akin to self-attention mechanisms. This integration is rigorously validated through an ablation study. Wave-ConvNeXt epitomizes a holistic approach, enabling an end-to-end optimization of feature learning and fault classification. Our empirical analysis on two real-world IIoT datasets demonstrates Wave-ConvNeXt’s superiority over existing models. It not only elevates prediction accuracy but also significantly curtails computational complexity. Additionally, our exploration into the impact of various mother wavelets reveals the effectiveness of using wavelet basis functions with smaller support, bolstering diagnostic precision. The source code of Wave-ConvNeXt is available at https://github.com/leviszhang/waveConvNeXt.
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| 30. |
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| 31. |
- Zhang, Yingfeng, et al.
(författare)
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Production System Performance Prediction Model Based on Manufacturing Big Data
- 2015
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Ingår i: ICNSC 2015 - 2015 IEEE 12th International Conference on Networking, Sensing and Control. - : IEEE. - 9781479980697 ; , s. 277-280
-
Konferensbidrag (refereegranskat)abstract
- Existing production systems are short of real-time performance status of production process active perception, resulting in the production abnormal conditions processed lag, leading to the frequency problems of deviations in production tasks execution and planning. To address this problem, in this research, an advanced identification technology is extended to the manufacturing field to acquire the real-time performance data. Based on the sensed real-time manufacturing data, this paper presents a prediction method of production system performance by applying the Dynamic Bayesian Networks (DBN) theory and methods. It aims to achieve the prediction of the performance status of production system and potential anomalies, and to provide the important and abundant prediction information for real-time production control.
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| 32. |
- Zhiyi, He, et al.
(författare)
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Transfer fault diagnosis of bearing installed in different machines using enhanced deep auto-encoder
- 2020
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Ingår i: Measurement. - : Elsevier. - 0263-2241 .- 1873-412X. ; 152
-
Tidskriftsartikel (refereegranskat)abstract
- The collected vibration data with labeled information from bearing is far insufficient in engineering practice, which is challenging for training an intelligent diagnosis model. For this purpose, enhanced deep transfer auto-encoder is proposed for fault diagnosis of bearing installed in different machines. First, scaled exponential linear unit is used to improve the quality of the mapped vibration data collected from bearing. Second, nonnegative constraint is adopted for modifying the loss function to improve reconstruction effect. Then, the parameter knowledge of the well-trained source model is transferred to the target model. Finally, target training samples with limited labeled information are adopted for fine-tuning the target model to match the characteristics of the target testing samples. The proposed approach is applied for analyzing the measured vibration signals of bearings installed in different machines. The analysis results show that the proposed approach holds better transfer diagnosis performance compared with the existing approaches.
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