다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Data Mining Practical Machine Learning Tools and Techniques

Statistical Analysis with Missing Data

A freely available dataset produced from three million Landsat satellite images reveals substantial changes in the distribution of global surface water over the past 32 years and their causes, from climate change to human actions. The distribution of surface water has been mapped globally, and local-to-regional studies have tracked changes over time. But to date, there has been no global and methodologically consistent quantification of changes in surface water over time. Jean-Francois Pekel and colleagues have analysed more than three million Landsat images to quantify month-to-month changes in surface water at a resolution of 30 metres and over a 32-year period. They find that surface waters have declined by almost 90,000 square kilometres—largely in the Middle East and Central Asia—but that surface waters equivalent to about twice that area have been created elsewhere. Drought, reservoir creation and water extraction appear to have driven most of the changes in surface water over the past decades. The location and persistence of surface water (inland and coastal) is both affected by climate and human activity1 and affects climate2,3, biological diversity4 and human wellbeing5,6. Global data sets documenting surface water location and seasonality have been produced from inventories and national descriptions7, statistical extrapolation of regional data8 and satellite imagery9,10,11,12, but measuring long-term changes at high resolution remains a challenge. Here, using three million Landsat satellite images13, we quantify changes in global surface water over the past 32 years at 30-metre resolution. We record the months and years when water was present, where occurrence changed and what form changes took in terms of seasonality and persistence. Between 1984 and 2015 permanent surface water has disappeared from an area of almost 90,000 square kilometres, roughly equivalent to that of Lake Superior, though new permanent bodies of surface water covering 184,000 square kilometres have formed elsewhere. All continental regions show a net increase in permanent water, except Oceania, which has a fractional (one per cent) net loss. Much of the increase is from reservoir filling, although climate change14 is also implicated. Loss is more geographically concentrated than gain. Over 70 per cent of global net permanent water loss occurred in the Middle East and Central Asia, linked to drought and human actions including river diversion or damming and unregulated withdrawal15,16. Losses in Australia17 and the USA18 linked to long-term droughts are also evident. This globally consistent, validated data set shows that impacts of climate change and climate oscillations on surface water occurrence can be measured and that evidence can be gathered to show how surface water is altered by human activities. We anticipate that this freely available data will improve the modelling of surface forcing, provide evidence of state and change in wetland ecotones (the transition areas between biomes), and inform water-management decision-making.

High-resolution mapping of global surface water and its long-term changes

Dealing with uncertainty is always a challenging problem, and different tools have been proposed to deal with it. Recently, a new model that is based on hesitant fuzzy sets has been presented to manage situations in which experts hesitate between several values to assess an indicator, alternative, variable, etc. Hesitant fuzzy sets suit the modeling of quantitative settings; however, similar situations may occur in qualitative settings so that experts think of several possible linguistic values or richer expressions than a single term for an indicator, alternative, variable, etc. In this paper, the concept of a hesitant fuzzy linguistic term set is introduced to provide a linguistic and computational basis to increase the richness of linguistic elicitation based on the fuzzy linguistic approach and the use of context-free grammars by using comparative terms. Then, a multicriteria linguistic decision-making model is presented in which experts provide their assessments by eliciting linguistic expressions. This decision model manages such linguistic expressions by means of its representation using hesitant fuzzy linguistic term sets.

/pdf/hesitant-fuzzy-linguistic-term-sets-for-decision-making-4y2hc7e6bo.pdf

Hesitant Fuzzy Linguistic Term Sets for Decision Making

This paper aims to propose a new approach to decompose an overall
data envelopment analysis model into equivalent two-stage models.
In this approach, we use a minimax reference point method to set the
weights and reliabilities of the two stage models so that the combined
efficiency of the two stages is equal to the overall efficiency. The
equivalent multi-stage models are useful to support planning for performance
improvement. An illustrative example is first explored to compare
the results from the new approach with those of four other existing
approaches. The main finding from the comparisons is that the new
decomposition approach of this paper satisfies the proposed assumptions.
A case study is then conducted on a two-stage process of steel manufacturing
to illustrate the validity and applicability of the proposed approach.

Overall Efficiency and its Decomposition in a Two-Stage Network DEA Model

Safety assessment is an important part of maritime safety analysis and management as it can provide decision support to safety-based operations. In this chapter, we first review fire and explosion safety related regulations and assessment approaches, and then present a hierarchical assessment framework for evaluating safety against fire and explosion hazards in container line supply chain (CLSC).Main criteria and factors influencing fire and explosion safety on containerships are investigated, and a safety modeling and synthesis method using the Evidential Reasoning (ER) approach is briefly discussed. The outcomes generated by the proposed safety assessment method are highly consistent with “goal-setting” safety regulations.

Fire and Explosion Safety Assessment in Container Line Supply Chain

Since late January 2020 when the first coronavirus case reached England, United Kingdom, the coronavirus disease 2019 (COVID-19) has spread rapidly and widely across all local authorities (LAs) in ...

https://journals.sagepub.com/doi/pdf/10.1177/0308518X20984165

Visualising regional disparities in the risk of COVID-19 at different phases of lockdown in England

Fire and explosion safety assessment in container line supply chain

This paper aims to contribute to offshore risk analysis by proposing a methodology to model causal relationships focusing on human and organisational errors. The proposed methodology uses James Reason's "Swiss cheese" model to form a generic offshore risk analysis framework and tailors Bayesian Network (BN) to fit into the framework to construct a causal relationship model. A case study of the collision risk between a Floating Production, Storage and Offloading (FPSO) unit and authorised vessels caused by human and organisational factors (HOFs) during operations is used to illustrate the application of the proposed methodology. This paper shows that James Reason's "Swiss cheese" model and BN can be jointly used in offshore risk analysis

Dong-Ling Xu

Papers

Overall Efficiency and its Decomposition in a Two-Stage Network DEA Model

Fire and Explosion Safety Assessment in Container Line Supply Chain

Visualising regional disparities in the risk of COVID-19 at different phases of lockdown in England

Fire and explosion safety assessment in container line supply chain

A Methodology to Model Human and Organisational Errors on Offshore Risk Analysis