Diameter Prediction for Correcting Continuous Forest Inventory Data

1991 ◽  
Vol 8 (2) ◽  
pp. 76-82
Author(s):  
Douglas Eberhardt ◽  
Edwin J. Green
Keyword(s):  
Basal Area ◽  
Original Data ◽  
Ordinary Least Squares ◽  
Inventory Data ◽  
Time Intervals ◽  
Data Set ◽  
Advantages And Disadvantages ◽  
Continuous Forest ◽  
Time Period ◽  
Regular Time

Abstract Permanent plot data are used in many studies. Trees are measured for diameter, height, and other characteristics at regular time intervals. Occasionally, errors in the diameter measurements result in a larger diameter reported at the time of the first measurement rather than the second, thus making some of the data apparently unusable. Currently there are at least two basic methods in use to compensate and estimate the growth on trees exhibiting illogical consecutive diameters. This study examines these two techniques in addition to a few others, and evaluates the advantages and disadvantages of each method. A 5% random sample was drawn from a data set void of obviously incorrect diameter measurements. For each tree in the sample, one of the two diameter measurements was assumed to be incorrect and was replaced by a predicted estimate from one of the candidate methods. The sample was then put back into the original data set and the estimated basal area plot growth was calculated for that time period. This was then compared to the true plot growth, and the resulting differences were examined. Based upon these differences, it was concluded that ordinary least squares or the introduced standard deviation technique will provide the best results if applied on a plot by plot basis. North. J. Appl. For. 8(2):76-82.

Rotational Characteristics of the Green Solar Corona: 1947-1991

1994 ◽  
Vol 144 ◽  
pp. 139-141 ◽  
Author(s):  
J. Rybák ◽  
V. Rušin ◽  
M. Rybanský
Keyword(s):  
Solar Corona ◽  
World Wide ◽  
Rotation Period ◽  
Original Data ◽  
Coronal Emission ◽  
Time Intervals ◽  
Data Set ◽  
The World ◽  
Coronal Emission Line ◽  
Homogeneous Data

AbstractFe XIV 530.3 nm coronal emission line observations have been used for the estimation of the green solar corona rotation. A homogeneous data set, created from measurements of the world-wide coronagraphic network, has been examined with a help of correlation analysis to reveal the averaged synodic rotation period as a function of latitude and time over the epoch from 1947 to 1991.The values of the synodic rotation period obtained for this epoch for the whole range of latitudes and a latitude band ±30° are 27.52±0.12 days and 26.95±0.21 days, resp. A differential rotation of green solar corona, with local period maxima around ±60° and minimum of the rotation period at the equator, was confirmed. No clear cyclic variation of the rotation has been found for examinated epoch but some monotonic trends for some time intervals are presented.A detailed investigation of the original data and their correlation functions has shown that an existence of sufficiently reliable tracers is not evident for the whole set of examinated data. This should be taken into account in future more precise estimations of the green corona rotation period.

How local personal vote-earning attributes affect the aggregate party vote share: Evidence from the Belgian flexible-list PR system (2003–2014)

Politics ◽  
2018 ◽  
Vol 39 (4) ◽  
pp. 464-479
Author(s):  
Gert-Jan Put ◽  
Jef Smulders ◽  
Bart Maddens
Keyword(s):  
Regression Models ◽  
Empirical Test ◽  
Original Data ◽  
Ordinary Least Squares ◽  
Vote Share ◽  
District Level ◽  
National Party ◽  
Data Set ◽  
Geographically Distributed ◽  
Party Vote Shares

This article investigates the effect of candidates exhibiting local personal vote-earning attributes (PVEA) on the aggregate party vote share at the district level. Previous research has often assumed that packing ballot lists with localized candidates increases the aggregate party vote and seat shares. We present a strict empirical test of this argument by analysing the relative electoral swing of ballot lists at the district level, a measure of change in party vote shares which controls for the national party trend and previous party results in the district. The analysis is based on data of 7527 candidacies during six Belgian regional and federal election cycles between 2003 and 2014, which is aggregated to an original data set of 223 ballot lists. The ordinary least squares (OLS) regression models do not show a significant effect of candidates exhibiting local PVEA on relative electoral swing of ballot lists. However, the results suggest that ballot lists do benefit electorally if candidates with local PVEA are geographically distributed over different municipalities in the district.

scholarly journals A reality check for students? How participating to the Model United Nations influences skills, IR perceptions, and perspectives on future career

Politics ◽  
2019 ◽  
Vol 40 (2) ◽  
pp. 245-261
Author(s):  
Fabrizio Coticchia ◽  
Enrico Calossi ◽  
Lorenzo Cicchi
Keyword(s):  
United Nations ◽  
Role Playing ◽  
Original Data ◽  
Multivariate Regression Analysis ◽  
Ordinary Least Squares ◽  
Data Set ◽  
Future Career ◽  
Alternative Hypotheses ◽  
University Enrolment ◽  
Personal Skills

Despite a growing number of studies on simulations and International Relations (IR), few analyses investigate how participating in a simulation affects students’ perceptions of relevant IR issues. In addition, almost none of the current analyses on role playing and IR investigate how the involvement in a simulation affects students’ views on university enrolment or future career. This article seeks to fill these gaps, addressing how students’ interpretations and expectations change after participating in the Model United Nations (MUN). This article studies how the MUN is perceived as an experience that helps improve personal skills such as language ability, negotiation skills, and knowledge related to IR issues. This article also analyses how perceptions about selected IR issues and views on future university enrolment or future career vary before and after the MUN. The article is based on an original data set from a survey submitted to high school and university students participating to two MUNs held in Spring 2018. This article also employs ordinary least squares (OLS) multivariate regression analysis to test alternative hypotheses.

Operational implementation of a LiDAR inventory in Boreal Ontario

2011 ◽  
Vol 87 (04) ◽  
pp. 512-528 ◽  
Author(s):  
Murray Woods ◽  
Doug Pitt ◽  
Margaret Penner ◽  
Kevin Lim ◽  
Dave Nesbitt ◽  
...  
Keyword(s):  
Basal Area ◽  
Lidar Data ◽  
Average Height ◽  
Calibration Data ◽  
Inventory Data ◽  
Data Set ◽  
Mean Values ◽  
Statistical Precision ◽  
Regression Estimators ◽  
Mean Square Errors

An existing Light Detection and Ranging (LiDAR) data set captured on the Romeo Malette Forest near Timmins, Ontario, was used to explore and demonstrate the feasibility of such data to enrich existing strategic forest-level resource inventory data. Despite suboptimal calibration data, stand inventory variables such as top height, average height, basal area, gross total volume, gross merchantable volume, and above-ground biomass were estimated from 136 calibration plots and validated on 138 independent plots, with root mean square errors generally less than 20% of mean values. Stand densities (trees per ha) were estimated with less precision (30%). These relationships were used as regression estimators to predict the suite of variables for each 400 m2 tile on the 630 000-ha forest, with predictions capable of being aggregated in any user-defined manner—for a stand, block, or forest—with appropriate estimates of statistical precision. This pilot study demonstrated that LiDAR data may satisfy growing needs for inventory data to scale operational/tactical, through strategic needs, as well as provide spatial detail for planning and the optimization of forest management activities.

Linking service innovation to firm performance

2017 ◽  
Vol 11 (4) ◽  
pp. 730-750 ◽  
Author(s):  
Markus Chiahan Tsai ◽  
Chunhsien Wang
Keyword(s):  
Firm Performance ◽  
Market Orientation ◽  
Service Innovation ◽  
Original Data ◽  
Ordinary Least Squares ◽  
Least Squares Regression ◽  
Data Set ◽  
Content Type ◽  
Marketing Orientation ◽  
Service Oriented

Purpose How in essence a firm’s service innovation affects its performance is always an intriguing and important issue to business researchers and practitioners. However little is known about the moderating effects of a firm’s approach to innovation and capability of marketing orientation that influence this aforementioned relationship and the underlying mechanisms. This paper aims to examine how ambidextrous innovation (exploration and exploitation innovation) and market orientation capabilities (market-sensing and customer-linking capabilities) can shape the relationship between service innovation and firm performance. Research model was developed based on theoretical foundation of the resource-based view and the rationed perspective. Design/methodology/approach Using an original data set comprising 170 service-oriented firms from Taiwan, the authors found that ambidextrous innovation and market orientation capabilities can significantly enhance performance for service-oriented firms. The authors used the traditional ordinary least squares regression and the zero-inflated Poisson regression to test the five hypotheses. Findings The empirical results fully support the hypotheses that ambidextrous innovation and market orientation capabilities can significantly enhance firm performance. These results imply that the benefits of ambidextrous innovation and market orientation capabilities can coexist in a service innovation deployment and that these combined benefit firm performance. Originality/value The ambidextrous innovation and market orientation capabilities play catalytic roles during innovative service implementation in the service-oriented sectors. The roles of these factors have rarely been examined together before. Hence, this study addresses the gaps in current understanding and provides valuable insights, particularly in the context of the future service innovation deployment. In addition, the theoretical and managerial implications of the findings provide useful and valuable information for both the researchers and managers of the service-oriented.

Extra- and within-system electoral volatility

2016 ◽  
Vol 23 (6) ◽  
pp. 623-635 ◽  
Author(s):  
Scott Mainwaring ◽  
Carlos Gervasoni ◽  
Annabella España-Najera
Keyword(s):  
Original Data ◽  
Data Set ◽  
New Parties ◽  
Electoral Success ◽  
Electoral Volatility ◽  
Descriptive Information ◽  
Time Period ◽  
The World ◽  
And Shifts

We analyze the remarkable differences in the electoral success of new parties and compare the determinants of electoral volatility attributable to new versus established parties. We base our findings on an original data set of total volatility, extra-system volatility, and within-system volatility for 67 democratic countries across all regions of the world since 1945. The article makes three contributions. First, we show that it is important to distinguish between electoral volatility that represents vote shifts among established parties (within-system volatility) and shifts to new parties (extra-system volatility). Second, we provide descriptive information about total, within-system, and extra-system volatility for 67 countries. Third, we analyze the determinants of volatility. Our results show that the causes of within- and extra-system volatility differ markedly. In contrast to Powell and Tucker, for our broader range of countries and longer time period, there are several statistically robust positive findings.

Electing the Senate

2017 ◽  
Author(s):  
Wendy J. Schiller ◽  
Charles Stewart III
Keyword(s):  
Original Data ◽  
State Legislators ◽  
Internal Conflict ◽  
Data Set ◽  
Senate Elections ◽  
Political Actors ◽  
The Public ◽  
Seventeenth Amendment ◽  
The People ◽  
Election Process

From 1789 to 1913, U.S. senators were not directly elected by the people—instead the Constitution mandated that they be chosen by state legislators. This radically changed in 1913, when the Seventeenth Amendment to the Constitution was ratified, giving the public a direct vote. This book investigates the electoral connections among constituents, state legislators, political parties, and U.S. senators during the age of indirect elections. The book finds that even though parties controlled the partisan affiliation of the winning candidate for Senate, they had much less control over the universe of candidates who competed for votes in Senate elections and the parties did not always succeed in resolving internal conflict among their rank and file. Party politics, money, and personal ambition dominated the election process, in a system originally designed to insulate the Senate from public pressure. The book uses an original data set of all the roll call votes cast by state legislators for U.S. senators from 1871 to 1913 and all state legislators who served during this time. Newspaper and biographical accounts uncover vivid stories of the political maneuvering, corruption, and partisanship—played out by elite political actors, from elected officials, to party machine bosses, to wealthy business owners—that dominated the indirect Senate elections process. The book raises important questions about the effectiveness of Constitutional reforms, such as the Seventeenth Amendment, that promised to produce a more responsive and accountable government.

Styles of Representation in Constituencies in the Homeland and Abroad: The Case of Italy

2020 ◽  
Author(s):  
Eva Østergaard-Nielsen ◽  
Stefano Camatarri
Keyword(s):  
Original Data ◽  
Role Orientation ◽  
International Mobility ◽  
Data Set ◽  
Democratic Representation ◽  
Public Debates ◽  
At Home

Abstract The role orientation of political representatives and candidates is a longstanding concern in studies of democratic representation. The growing trend in countries to allow citizens abroad to candidate in homeland elections from afar provides an interesting opportunity for understanding how international mobility and context influences ideas of representation among these emigrant candidates. In public debates, emigrant candidates are often portrayed as delegates of the emigrant constituencies. However, drawing on the paradigmatic case of Italy and an original data set comprising emigrant candidates, we show that the perceptions of styles of representation abroad are more complex. Systemic differences between electoral districts at home and abroad are relevant for explaining why and how candidates develop a trustee or delegate orientation.

Do the Heterogeneous Determinants of Repayment Affect Differently across Borrowers of Diverse Credit Sources in Rural Assam? A Double Hurdle Approach

2021 ◽  
pp. 245513332110316
Author(s):  
Tiken Das ◽  
Pradyut Guha ◽  
Diganta Das
Keyword(s):  
Rural Areas ◽  
Probit Model ◽  
Original Data ◽  
Community Based ◽  
Data Set ◽  
Brahmaputra Valley ◽  
Double Hurdle ◽  
Instrumental Variable Probit ◽  
Instrumental Variable Probit Model

This study made an attempt to answer the question: Do the heterogeneous determinants of repayment affect the borrowers of diverse credit sources differently? The study is based on data collected from 240 households from three districts in the lower Brahmaputra valley of Assam through a carefully designed primary survey. Besides, the study uses the double hurdle approach and the instrumental variable probit model to reduce possible selection bias. It observes better repayment performance among formal borrowers, followed by semiformal borrowers, while occupation wise it is prominent among organised employees. It has been found that in general, the household characteristics, loan characteristics and location-specific characteristics significantly affect repayment performance of borrowers. However, the nature of impact of the factors influencing repayment performance is remarkably different across credit sources. It ignores the role of traditional community-based organisations in rural Assam while analysing the determinants of repayment performance. The study also recommends for ensuring productive opportunities and efficient market linkages in rural areas of Assam. The study is based on an original data set that has specially been collected to examine question that—do the heterogeneous determinants of repayment affect the borrowers of diverse credit sources differently in the lower Brahmaputra valley of Assam—which has not been studied before.

scholarly journals Data Augmentation Using Generative Adversarial Network for Automatic Machine Fault Detection Based on Vibration Signals

2021 ◽  
Vol 11 (5) ◽  
pp. 2166
Author(s):  
Van Bui ◽  
Tung Lam Pham ◽  
Huy Nguyen ◽  
Yeong Min Jang
Keyword(s):  
Fault Detection ◽  
Data Augmentation ◽  
Model Performance ◽  
Original Data ◽  
Fault Classification ◽  
Training Process ◽  
Generative Adversarial Network ◽  
Data Set ◽  
Adversarial Network ◽  
Machine Fault

In the last decade, predictive maintenance has attracted a lot of attention in industrial factories because of its wide use of the Internet of Things and artificial intelligence algorithms for data management. However, in the early phases where the abnormal and faulty machines rarely appeared in factories, there were limited sets of machine fault samples. With limited fault samples, it is difficult to perform a training process for fault classification due to the imbalance of input data. Therefore, data augmentation was required to increase the accuracy of the learning model. However, there were limited methods to generate and evaluate the data applied for data analysis. In this paper, we introduce a method of using the generative adversarial network as the fault signal augmentation method to enrich the dataset. The enhanced data set could increase the accuracy of the machine fault detection model in the training process. We also performed fault detection using a variety of preprocessing approaches and classified the models to evaluate the similarities between the generated data and authentic data. The generated fault data has high similarity with the original data and it significantly improves the accuracy of the model. The accuracy of fault machine detection reaches 99.41% with 20% original fault machine data set and 93.1% with 0% original fault machine data set (only use generate data only). Based on this, we concluded that the generated data could be used to mix with original data and improve the model performance.

Sign in / Sign up

Export Citation Format

Share Document