Determining Pipeline Depth of Cover at River Crossings by Data Integration

2018 ◽  
Author(s):  
Peter Chan ◽  
Jin Wei
Keyword(s):  
Data Integration ◽  
Survey Data ◽  
Measurement Errors ◽  
Regulatory Requirement ◽  
Dry Land ◽  
Data Errors ◽  
Survey Results ◽  
Inspection Data

Having sufficient depth of cover ensures pipeline protection and is a regulatory requirement. Confirming the pipeline depth of cover on dry land is generally easy and produces accurate results. However, determining the pipeline depth of cover at a river crossing can be problematic because of accessibility difficulties and the increased measurement errors from aboveground surveys. The difficulty of determining the pipeline depth of cover at river crossings can be resolved by integrating both the aboveground survey data and the inline inspection data. By comparing both sets of data, errors from both above survey data and inline inspection data can be detected. This paper describes watercourse management, aboveground DOC surveys, and a spreadsheet based tool developed for both the quick verification of aboveground survey results, and the calculation of the true DOC at water crossings without needing to set new GPS tie-points on both banks of the crossing and running a new ILI.

scholarly journals Adding “Student Voice” to the Mix: Perception Surveys and State Accountability Systems

AERA Open ◽  
2021 ◽  
Vol 7 ◽  
pp. 233285842199072
Author(s):  
Jack Schneider ◽  
James Noonan ◽  
Rachel S. White ◽  
Douglas Gagnon ◽  
Ashley Carey
Keyword(s):  
Survey Data ◽  
Student Voice ◽  
School Quality ◽  
Student Perception ◽  
State Level ◽  
Student Survey ◽  
New School ◽  
State Accountability ◽  
Survey Results ◽  
School Ratings

For the past two decades, student perception surveys have become standard tools in data collection efforts. At the state level, however, “student voice” is still used sparingly. In this study, we examine the ways in which including student survey results might alter state accountability determinations. Reconstructing the accountability system in Massachusetts, we draw on a unique set of student survey data, which we add to the state’s formula at a maximally feasible dosage in order to determine new school ratings. As we find, student survey data shift school accountability ratings in small but meaningful ways and appear to enhance functional validity. Student survey results introduce information about school quality that is not captured by typical accountability metrics, correlate moderately with test score growth, and are not predicted by student demographic variables.

scholarly journals What Do Survey Data Tell Us about US Businesses?

2020 ◽  
Vol 2 (4) ◽  
pp. 443-458
Author(s):  
Anmol Bhandari ◽  
Serdar Birinci ◽  
Ellen R. McGrattan ◽  
Kurt See
Keyword(s):  
Survey Data ◽  
Measurement Errors ◽  
Wealth Inequality ◽  
Business Owners ◽  
Private Business ◽  
Publicly Traded ◽  
Rates Of Return ◽  
Survey Responses ◽  
Survey Designs

This paper examines the reliability of survey data on business incomes, valuations, and rates of return, which are key inputs for studies of wealth inequality and entrepreneurial choice. We compare survey responses of business owners with available data from administrative tax records, brokered private business sales, and publicly traded company filings and document problems due to nonrepresentative samples and measurement errors across several surveys, subsamples, and years. We find that the discrepancies are economically relevant for the statistics of interest. We investigate reasons for these discrepancies and propose corrections for future survey designs. (JEL C82, C83, D22)

scholarly journals An Empirical Analysis of the Perceived Challenges and Benefits of Introducing Biosimilars in Bangladesh: A Paradigm Shift

Biomolecules ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 89 ◽  
Author(s):  
Eva Kabir ◽  
Shannon Moreino ◽  
Mohammad Sharif Siam
Keyword(s):  
Pharmaceutical Industry ◽  
Survey Data ◽  
Paradigm Shift ◽  
Quality Data ◽  
Great Promise ◽  
Financial Success ◽  
High Demand ◽  
Regulatory Guidelines ◽  
Survey Results ◽  
Immense Potential

The high demand for and resulting financial success of biopharmaceutical products over the last three decades have seen the door open for close copies of these biological products, also known as biosimilars. This paper seeks to collate all relevant published intelligence with acquired survey data to assess the weight of available evidence that these products hold immense potential for the pharmaceutical industry in terms of their applications and benefits. Biosimilars also pose to be of great promise to the Bangladesh pharmaceutical industry, with the commitment of drastically reducing its dependence on foreign imports of biopharmaceutics to meet local demand. Our questionnaire based survey involved 100 Clinicians, 50 Industry Experts and 100 Academicians. The study found that majority of Industry Experts (72%) and Academicians (63%) shared a different concept of biosimilars opposed to majority of Clinicians (78%). Majority of Academicians (68%) and Industry Experts (61%) also shared a different belief from that of most Clinicians (61%) regarding the need for updating the existing regulatory guidelines. The study also showed that Clinicians (67%), Industry Experts (83%) and Academicians (80%) highlighted the benefit of lower costs of biosimilars. Furthermore, the quality data obtained from the survey results allowed us to evaluate and provide recommendations for stakeholders on the need for increased biosimilar awareness, pharmacovigilance and safety in Bangladesh.

Quantifying Measurement Errors in Partially Edited Business Survey Data

2017 ◽  
pp. 319-337
Author(s):  
Thomas Laitila ◽  
Karin Lindgren ◽  
Anders Norberg ◽  
Can Tongur
Keyword(s):  
Survey Data ◽  
Measurement Errors ◽  
Business Survey Data ◽  
Business Survey

scholarly journals The Causal Effect of Service Satisfaction on Customer Loyalty

2020 ◽  
Author(s):  
Guofang Huang ◽  
K. Sudhir
Keyword(s):  
Survey Data ◽  
Customer Loyalty ◽  
Measurement Errors ◽  
Causal Effect ◽  
Behavioral Measure ◽  
Service Satisfaction ◽  
Common Source ◽  
Omitted Variables ◽  
Cross Sectional ◽  
Downward Bias

We propose an instrumental-variable (IV) approach to estimate the causal effect of service satisfaction on customer loyalty by exploiting a common source of randomness in the assignment of service employees to customers in service queues. Our approach can be applied at no incremental cost by using routine repeated cross-sectional customer survey data collected by firms. The IV approach addresses multiple sources of biases that pose challenges in estimating the causal effect using cross-sectional data: (1) the upward bias from common-methods variance resulting from the joint measurement of service satisfaction and loyalty intent in surveys, (2) the attenuation bias caused by measurement errors in service satisfaction, and (3) the omitted variable bias that may be in either direction. In contrast to the common concern about the upward common-methods bias in estimates using cross-sectional survey data, we find that ordinary-least-squares substantially underestimates the causal effect, suggesting that the downward bias resulting from measurement errors and/or omitted variables is dominant. The underestimation is even more significant with a behavioral measure of loyalty, where there is no common-methods bias. This downward bias leads to significant underestimation of the positive profit impact from improving service satisfaction and can lead to underinvestment by firms in service satisfaction. Finally, we find that the causal effect of service satisfaction on loyalty is greater for more difficult types of services. This paper was accepted by Juanjuan Zhang, marketing.

Reliability Analysis of Corroding Pipelines Considering the Growth and Generation of Corrosion Defects

2014 ◽  
Author(s):  
H. Qin ◽  
W. Zhou
Keyword(s):  
Poisson Process ◽  
Reliability Analysis ◽  
Measurement Errors ◽  
Gamma Process ◽  
Homogeneous Poisson Process ◽  
Monte Carlo Simulation Technique ◽  
Natural Gas Pipeline ◽  
Corrosion Defects ◽  
Inspection Data ◽  
Non Homogeneous Poisson Process

This paper presents a methodology to evaluate the reliability of corroding pipelines by simultaneously considering the growth and generation of corrosion defects. The non-homogeneous Poisson process is employed to model the generation of corrosion defects, whereas the non-homogeneous gamma process is used to characterize the growth of corrosion defects once generated. The parameters included in the non-homogeneous Poisson process and non-homogeneous gamma process are evaluated from the inline inspection data using a hierarchical Bayesian model. The measurement errors associated with the inline inspection tools are taken into account in the Bayesian updating. The time-dependent failure probability of the corroding pipeline is evaluated using the Monte Carlo simulation technique. The methodology is illustrated using a natural gas pipeline that has been subjected to multiple inline inspections over a period of time. The results illustrate the necessity to incorporate the generation of new corrosion defects in the reliability analysis of corroding pipelines.

scholarly journals Study of measurement errors of Cabinet Office opinion survey

Impact ◽  
2021 ◽  
Vol 2021 (2) ◽  
pp. 6-7
Author(s):  
Harumasa Yoshimura
Keyword(s):  
Public Opinion ◽  
Measurement Errors ◽  
Japanese Society ◽  
Social Research ◽  
Sampling Error ◽  
Opinion Survey ◽  
Community Surveys ◽  
Public Opinion Surveys ◽  
Survey Results ◽  
Negative Impacts

Public opinion surveys are important for gauging the feelings and behaviours of societies. However, there is the possibility of error, which means that the data collected may not accurately reflect the thoughts and opinions of society, which can have dangerous repercussions. In order to minimise such error, with a specific focus on the Japanese Government's Cabinet Office public opinion survey, Professor Harumasa Yoshimura, Nara University, Japan, is investigating measurement error and, in doing so, he hopes to more accurately reflect the true opinions of Japanese society. This research involves integrating the different factors that can affect the reliability of survey results and looking at non-sampling error, which refers to human mistakes. Yoshimura is proposing a new style of social research that integrates psychometric research with sociological community surveys and believes this is the key to enhancing the reliability of public opinion surveys. Ultimately, improving the accuracy of public opinion surveys will have far-reaching benefits that include more accurately depicting thoughts and behaviours and therefore improving awareness of Japanese society, as well as preventing the negative impacts that inaccurate opinion survey results can have, including the political utilisation of academic endeavours.

scholarly journals TREATMENT OF GEODETIC SURVEY DATA AS FUZZY VECTORS

2015 ◽  
Vol XL-3/W3 ◽  
pp. 29-33
Author(s):  
G. Navratil ◽  
E. Heer ◽  
J. Hahn
Keyword(s):  
Normal Distribution ◽  
Least Squares ◽  
Survey Data ◽  
Measurement Errors ◽  
Least Squares Method ◽  
Measurement Data ◽  
Geodetic Survey ◽  
Present Measurement ◽  
A Value ◽  
Light Signals

Geodetic survey data are typically analysed using the assumption that measurement errors can be modelled as noise. The least squares method models noise with the normal distribution and is based on the assumption that it selects measurements with the highest probability value (Ghilani, 2010, p. 179f). There are environment situations where no clear maximum for a measurement can be detected. This can happen, for example, if surveys take place in foggy conditions causing diffusion of light signals. This presents a problem for automated systems because the standard assumption of the least squares method does not hold. A measurement system trying to return a crisp value will produce an arbitrary value that lies within the area of maximum value. However repeating the measurement is unlikely to create a value following a normal distribution, which happens if measurement errors can be modelled as noise. In this article we describe a laboratory experiment that reproduces conditions similar to a foggy situation and present measurement data gathered from this setup. Furthermore we propose methods based on fuzzy set theory to evaluate the data from our measurement.

scholarly journals Diversity and Humanitarian Negotiation

2021 ◽  
Author(s):  
Reem Alsalem ◽  
Rob Grace
Keyword(s):  
Survey Data ◽  
Aid Workers ◽  
Structured Interviews ◽  
Working Paper ◽  
Professional Experiences ◽  
Negotiation Processes ◽  
Survey Results ◽  
Organisational Dynamics

The humanitarian sector has steadily pushed forward with efforts to cultivate negotiation capacity among aid workers. However, considerations of how the profile of the humanitarian negotiator might shape negotiation outcomes have been, at best, in the background of ongoing professional discussions or, at worst, entirely overlooked. This working paper aims to fill this gap. Based on semi-structured interviews and survey data, this working paper assesses the role of identity characteristics in humanitarian negotiation processes. As the interview and survey results suggest, a negotiator’s profile—including identity characteristics and past professional experiences—can shape counterparts’ perceptions of humanitarian negotiators; fuel humanitarians’ own biases and stereotypes of their interlocutors; and feed into challenging internal organisational dynamics, as humanitarian organisations seek to promote diversity and foster inclusion and belonging among staff.

Sign in / Sign up

Export Citation Format

Share Document