Gli Indici Di Bilancio Per La Valutazione D'Azienda -- Approcci Teorici E Metodologici (Final Balance Index Analysis -- Methods and Techniques)

2015 ◽  
Author(s):  
Marco Berardi
Keyword(s):  
Index Analysis ◽  
Analysis Methods ◽  
Methods And Techniques ◽  
Balance Index

scholarly journals Mobility of Chernobyl137Cs in undisturbed soil : Analysis methods and techniques

2002 ◽  
Vol 37 (C1) ◽  
pp. C1-231-C1-236
Author(s):  
K. G. Andersson ◽  
C. L. Fogh ◽  
J. Roed
Keyword(s):  
Soil Analysis ◽  
Undisturbed Soil ◽  
Analysis Methods ◽  
Methods And Techniques

Incident Investigation and Root Cause Analysis Method and Technology Review

2017 ◽  
Author(s):  
Guan Jianjun ◽  
Che Yinhui ◽  
Ma Lei
Keyword(s):  
Nuclear Power ◽  
Root Cause Analysis ◽  
The United States ◽  
Energy Agency ◽  
Cause Analysis ◽  
Root Cause ◽  
Incident Investigation ◽  
Analysis Methods ◽  
Methods And Techniques ◽  
Application Techniques

Incident investigation and root cause analysis (RCA) are widely used in nuclear power plant incident investigation and root cause confirmation. In this paper, based on the analysis literature reviews of root cause investigation of related incidents in IAEA (International Atomic Energy Agency), Europe and the United States, the analysis methods and techniques or tools of root causes in the world are studied, the incident investigation and analysis methods and techniques for root causes are analyzed and summarized. Through a comparison of various analysis methods and relevant application techniques and tools, differences between these root cause analysis techniques and tools are elaborated in terms of both concept and applicable application. In addition, application of RCA analysis methods and techniques is also briefed based on domestic RCA application practices.

Defining, Understanding, and Addressing Big Data

2016 ◽  
Vol 3 (2) ◽  
pp. 1-32 ◽  
Author(s):  
Trevor J. Bihl ◽  
William A. Young II ◽  
Gary R. Weckman
Keyword(s):  
Big Data ◽  
Best Practices ◽  
Comprehensive Overview ◽  
Analysis Methods ◽  
Methods And Techniques ◽  
Business Engineering ◽  
Societal Problems

“Big Data” is an emerging term used with business, engineering, and other domains. Although Big Data is a popular term used today, it is not a new concept. However, the means in which data can be collected is more readily available than ever, which makes Big Data more relevant than ever because it can be used to improve decisions and insights within the domains it is used. The term Big Data can be loosely defined as data that is too large for traditional analysis methods and techniques. In this article, varieties of prominent but loose definitions for Big Data are shared. In addition, a comprehensive overview of issues related to Big Data is summarized. For example, this paper examines the forms, locations, methods of analyzing and exploiting Big Data, and current research on Big Data. Big Data also concerns a myriad of tangential issues, from privacy to analysis methods that will also be overviewed. Best practices will further be considered. Additionally, the epistemology of Big Data and its history will be examined, as well as technical and societal problems existing with Big Data.

scholarly journals Network Analysis of Political Internet Communities: from Formalized to «Unobserved» Groups

2021 ◽  
pp. 160-182
Author(s):  
Olga Popova ◽  
Sergey Suslov
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Communities ◽  
Latent Dirichlet Allocation ◽  
The Political ◽  
Analysis Methods ◽  
Methods And Techniques ◽  
Political Communities

The article is dedicated to the development of the political communities in social networks analysis methods. Main stages of network approach in the political science is described in the research. Researchers review the most significant methods and techniques in the political online communities studies for the last decade. The article shows the contemporary Russian scientists contribution in the development of online communities learning techniques. Networks and social network analysis methods and techniques become universal scientific approaches for several scientific fields. Boundary-transcending trends were critical means of science integration. Researchers present the results of experiment in which evaluate the possibilities of study unobserved political groups using latent Dirichlet allocation (LDA) model. The brief LDA foundation history and possible modifications for social topic modeling based on social networks data are discribed in the review. Using sample from one feed aggregator telegram channel in period of 2020 autumn, the authors display the most valuable topics in the Russian segment of political communication. Also it provides communities ideological preferences. Modified qualitative sociological methods can be used in online political communities discursive features research without any specific computer science techniques. Since about 70% of the Internet data are generated in the social networks, velocity and volume data necessitate new data mining techniques, databases capacity and computation processes. In other words, it provides a big data approach in social network analysis.

The Probability of Pipe Failure on the Basis of Operating Experience

2007 ◽  
Author(s):  
Bengt Lydell
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Operating Experience ◽  
The Body ◽  
Exploratory Research ◽  
Pipe Failure ◽  
Service Experience ◽  
Analysis Methods ◽  
Methods And Techniques ◽  
Reactor Operating

This paper addresses the progress with piping reliability analysis methods and techniques in the context of probabilistic safety assessment (PSA) to support risk-informed decisions. Piping reliability analysis has been a topic of discussion and concern within the nuclear safety community for a very long time. In part, this concern has been related to the capabilities and limitations of available methods and techniques, as well as with the requirements for how to best perform quantitative analysis in support of safety cases. The team of analysts responsible for the seminal Reactor Safety Study (WASH-1400) performed a limited evaluation of nuclear power plant piping reliability based on service experience from the then approximately 150 U.S. commercial nuclear reactor operating years [1,2]. This evaluation was aimed at estimation of loss-of-coolant-accident (LOCA) frequencies for input to the two PSA models of WASH-1400. After the publication of WASH-1400 in 1975 many other R&D projects have explored the roles of structural reliability models and statistical evaluation models in providing acceptable input to PSA. Furthermore, during the past 15 years efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand the capabilities and limitations of today’s piping reliability analysis frameworks. Against a historical overview of past efforts, this paper addresses the question how to best utilize service experience data for quantitative piping reliability analysis. Significant progress has been made to develop pipe failure databases, as well as analysis methods and techniques to explore and analyze the body of service experience with piping from today’s (February 2007) over 12,500 commercial reactor operating years. Insights from recent pipe failure database applications are utilized to reach some conclusions about the capability of statistical analysis approaches to piping reliability analysis, including Bayesian modeling.

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