Evaluation of the economic impacts of length and diameter measurement error on mechanical harvesters and processors operating in pine stands

2006 ◽  
Vol 36 (7) ◽  
pp. 1661-1673 ◽  
Author(s):  
Hamish D Marshall ◽  
Glen E Murphy ◽  
Kevin Boston
Keyword(s):  
Measurement Error ◽  
Simulation Model ◽  
Measurement Errors ◽  
Economic Impacts ◽  
Error Rates ◽  
Potential Value ◽  
Value Recovery ◽  
The World ◽  
Length Measurements ◽  
Value Loss

Value recovery studies from around the world have shown that on average mechanical log-making systems lose 18% of the potential value compared to 11% for motor manual systems. One of the potential reasons for their poor value recovery performance is the level of accuracy of their stem diameter and length measurements. Numerous studies have looked at the level of error in both the diameter and length measurements made by mechanical harvesters and processors; however, few have looked at the economic impacts of these errors. The paper investigates the economic impacts in terms of value loss of six different harvesting operations in three different pine species. The accuracy and precision of the measurements recorded in this study were similar to those of other studies from around the world. A simulation model was developed to estimate the value loss caused by these errors. The results of the simulation model showed that the operations were losing between 3% and 23% of the potential value because of measurement errors. Further analysis showed that the industry should concentrate on increasing the precision of the length and diameter measurements to optimize gains from reducing the measurement error rates.

scholarly journals Improvements in Value Recovery through Low Stump Heights: Mechanized versus Manual Felling

2006 ◽  
Vol 21 (1) ◽  
pp. 33-38 ◽  
Author(s):  
Ryan Hall ◽  
Han-Sup Han
Keyword(s):  
British Columbia ◽  
Picea Glauca ◽  
Stand Density ◽  
Abies Lasiocarpa ◽  
Potential Value ◽  
Value Recovery ◽  
Forest Practices ◽  
Value Loss ◽  
Manual Felling ◽  
Operational Constraints

Abstract Stump heights were measured on two blocks harvested during the summer of 2000 in north-central British Columbia. Each block was of similar stand and terrain characteristics, consisting mainly of subalpine fir (Abies lasiocarpa) with minor components of white spruce (Picea glauca × P. engelmannii) on gentle slopes. The blocks were harvested by two different contractors using different felling methods: mechanized felling with a feller-buncher and manual felling with a chainsaw. The average measured stump height from mechanized felling was 8.8 cm lower than that of manual felling, measuring 21.9 and 13.1 cm, respectively. When the saw kerf of felling equipment and stump-pull were included, the average stump height of mechanized felling was shown to be 5.8 cm (17%) lower than manual felling. High-end and low-end potential value losses were determined based on average sawlog values (Canadian [CN] $60/m 3 ) and pulp log values (CN$40/m 3 ), respectively. The potential value loss from manual felling was estimated to be up to CN$0.33/tree more than from mechanized felling. This result indicated that mechanized felling recovered up to CN$160/ha over manual felling when an average sawlog value and the stand density information from the study site were used in the calculation. The study demonstrated that lower stump heights than the 30 cm maximum stump height set by the Forest Practices Code of British Columbia are attainable with both felling methods. Sensitivity analysis was performed to determine the potential value and volume gains for a range of stump heights from 0 to 30 cm. Operational constraints were identified in the study, and recommendations for minimizing stump heights are presented.

scholarly journals Impact of landmark identification and standard measurement error on cephalometric analysis using a mathematical simulation model

2012 ◽  
Vol 53 (3) ◽  
pp. 1-5
Author(s):  
Eduardo Luiz Delamare ◽  
Gabriela Salatino Liedke ◽  
Mariana Boessio Vizzotto ◽  
Heraldo Luis Dias Da Silveira ◽  
Dalva Maria Pereira Padilha ◽  
...  
Keyword(s):  
Measurement Error ◽  
Simulation Model ◽  
Mathematical Simulation ◽  
Measurement Errors ◽  
Regression Models ◽  
Linear Regression Models ◽  
Standard Measurement ◽  
Landmark Identification ◽  
The Monte Carlo Method ◽  
Impact Coefficient

Objective: To assess, using a mathematical simulation model, the participation of each coordinate involved in the formation of cephalometric angles and to determine the extent to which errors in the identification of cephalometric landmarks can, individually and collectively, influence the measurement of these angles. Material and Methods: The reference values and standard errors of 13 landmarks obtained from the analysis of 30 cephalograms were used. For each landmark, 1000 observations were simulated using the Monte Carlo method. On the basis of linear regression models, equations designed to estimate measurement errors due to landmark identification errors were obtained and analysed. Results: The coordinates most involved in the formation of the angles SNA, SNB, ANB, FMA, PPL, DFC, and AEF were Ny, Ny, Ax, Goy, Poy, Poy, and Ptmx, respectively, and the standard measurement errors for these angles were 1.2, 0.9, 0.8, 1.6, 1.5, 1.5, and 1.4, respectively. Conclusion: The standard measurement error of the angle depends on the geometric impact coefficient and the standard error of the coordinates involved in the formation of the angles, and the geometric impact coefficient varies according to the angle analysed.

Invasive Shot Hole Borers Euwallacea fornicatus, E. kuroshio, and E. perbrevis (Coleoptera: Curculionidae: Scolytinae)

EDIS ◽  
2020 ◽  
Vol 2020 (1) ◽  
pp. 7
Author(s):  
Demian F. Gomez ◽  
Jiri Hulcr ◽  
Daniel Carrillo
Keyword(s):  
South Africa ◽  
Invasive Species ◽  
Prevention And Control ◽  
Economic Impacts ◽  
Forest Resources ◽  
Economic Damage ◽  
Ambrosia Beetles ◽  
Invasive Insects ◽  
The World ◽  
And Control

Invasive species, those that are nonnative and cause economic damage, are one of the main threats to ecosystems around the world. Ambrosia beetles are some of the most common invasive insects. Currently, severe economic impacts have been increasingly reported for all the invasive shot hole borers in South Africa, California, Israel, and throughout Asia. This 7-page fact sheet written by Demian F. Gomez, Jiri Hulcr, and Daniel Carrillo and published by the School of Forest Resources and Conservation describes shot hole borers and their biology and hosts and lists some strategies for prevention and control of these pests. http://edis.ifas.ufl.edu/fr422

Awareness about Covid 19 Pandemic and its Social Impacts on Normal Human Lifestyle Among Chennai Population

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 659-666
Author(s):  
Anu Iswarya Jaisankar ◽  
Raghu Nandhakumar ◽  
Ezhilarasan D
Keyword(s):  
Psychological Stress ◽  
Economic Burden ◽  
Economic Impacts ◽  
Functional Limitations ◽  
Social Impacts ◽  
Biological Processes ◽  
The People ◽  
The World ◽  
Normal Human

Covid 19 pandemic is a terrible ongoing pandemic that has spread worldwide. Covid 19 Pandemic has infected more than 188 countries and territories across the globe. The basic biological processes and functional limitations that govern the development and survival of the particular behaviors of the virus continue to be elucidated. On that note, Prevention is the only cure. The World is facing a great economic turmoil. People suffer from Psychological stress and Economic burden combined. Here assessing the Psychological, Physical, Social, Financial and Economic impacts of the Pandemic on the people becomes really very important in analysing the mindset of the people and in evaluating the significance of implemented changes and in implementing new changes. The current study aims at analysing the various impacts of Covid 19 on the people residing at the Greater Chennai corporation circle.

Features of accumulation of amounts of measurement error

2017 ◽  
Vol 928 (10) ◽  
pp. 58-63 ◽  
Author(s):  
V.I. Salnikov
Keyword(s):  
Measurement Error ◽  
Confidence Interval ◽  
Normal Distribution ◽  
Confidence Level ◽  
Measurement Errors ◽  
Truncated Normal Distribution ◽  
Truncated Normal ◽  
The Law ◽  
Normal Law

The initial subject for study are consistent sums of the measurement errors. It is assumed that the latter are subject to the normal law, but with the limitation on the value of the marginal error Δpred = 2m. It is known that each amount ni corresponding to a confidence interval, which provides the value of the sum, is equal to zero. The paradox is that the probability of such an event is zero; therefore, it is impossible to determine the value ni of where the sum becomes zero. The article proposes to consider the event consisting in the fact that some amount of error will change value within 2m limits with a confidence level of 0,954. Within the group all the sums have a limit error. These tolerances are proposed to use for the discrepancies in geodesy instead of 2m*SQL(ni). The concept of “the law of the truncated normal distribution with Δpred = 2m” is suggested to be introduced.

scholarly journals Formulating the history matching problem with consistent error statistics

2021 ◽  
Author(s):  
Geir Evensen
Keyword(s):  
Simulation Model ◽  
Measurement Errors ◽  
History Matching ◽  
Critical Role ◽  
Bayes Theorem ◽  
Conditional Probability Density ◽  
Model Parameters ◽  
Rate Data ◽  
Matching Problem ◽  
Reservoir Prediction

AbstractIt is common to formulate the history-matching problem using Bayes’ theorem. From Bayes’, the conditional probability density function (pdf) of the uncertain model parameters is proportional to the prior pdf of the model parameters, multiplied by the likelihood of the measurements. The static model parameters are random variables characterizing the reservoir model while the observations include, e.g., historical rates of oil, gas, and water produced from the wells. The reservoir prediction model is assumed perfect, and there are no errors besides those in the static parameters. However, this formulation is flawed. The historical rate data only approximately represent the real production of the reservoir and contain errors. History-matching methods usually take these errors into account in the conditioning but neglect them when forcing the simulation model by the observed rates during the historical integration. Thus, the model prediction depends on some of the same data used in the conditioning. The paper presents a formulation of Bayes’ theorem that considers the data dependency of the simulation model. In the new formulation, one must update both the poorly known model parameters and the rate-data errors. The result is an improved posterior ensemble of prediction models that better cover the observations with more substantial and realistic uncertainty. The implementation accounts correctly for correlated measurement errors and demonstrates the critical role of these correlations in reducing the update’s magnitude. The paper also shows the consistency of the subspace inversion scheme by Evensen (Ocean Dyn. 54, 539–560 2004) in the case with correlated measurement errors and demonstrates its accuracy when using a “larger” ensemble of perturbations to represent the measurement error covariance matrix.

scholarly journals ON THE UNIFORM CONVERGENCE OF DECONVOLUTION ESTIMATORS FROM REPEATED MEASUREMENTS

2021 ◽  
pp. 1-22
Author(s):  
Daisuke Kurisu ◽  
Taisuke Otsu
Keyword(s):  
Multivariate Analysis ◽  
Measurement Error ◽  
Uniform Convergence ◽  
Measurement Errors ◽  
Convergence Rates ◽  
Free Variable ◽  
Error Model ◽  
Repeated Measurements ◽  
Empirical Characteristic Function ◽  
Measurement Error Model

This paper studies the uniform convergence rates of Li and Vuong’s (1998, Journal of Multivariate Analysis 65, 139–165; hereafter LV) nonparametric deconvolution estimator and its regularized version by Comte and Kappus (2015, Journal of Multivariate Analysis 140, 31–46) for the classical measurement error model, where repeated noisy measurements on the error-free variable of interest are available. In contrast to LV, our assumptions allow unbounded supports for the error-free variable and measurement errors. Compared to Bonhomme and Robin (2010, Review of Economic Studies 77, 491–533) specialized to the measurement error model, our assumptions do not require existence of the moment generating functions of the square and product of repeated measurements. Furthermore, by utilizing a maximal inequality for the multivariate normalized empirical characteristic function process, we derive uniform convergence rates that are faster than the ones derived in these papers under such weaker conditions.

Guidelines for choosing volume equations in the presence of measurement error in height

2000 ◽  
Vol 30 (2) ◽  
pp. 306-310 ◽  
Author(s):  
M S Williams ◽  
H T Schreuder
Keyword(s):  
Measurement Error ◽  
Tree Species ◽  
Measurement Errors ◽  
Tree Diameter ◽  
Total Height ◽  
Volume Equations

Assuming volume equations with multiplicative errors, we derive simple conditions for determining when measurement error in total height is large enough that only using tree diameter, rather than both diameter and height, is more reliable for predicting tree volumes. Based on data for different tree species of excurrent form, we conclude that measurement errors up to ±40% of the true height can be tolerated before inclusion of estimated height in volume prediction is no longer warranted.

scholarly journals An improved computational method to assess pituitary responsiveness to secretagogue stimuli

2002 ◽  
pp. 323-332 ◽  
Author(s):  
A Sartorio ◽  
G De Nicolao ◽  
D Liberati
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Pituitary Hormones ◽  
Computational Method ◽  
Kinetics Parameters ◽  
Thyrotrophin Releasing Hormone ◽  
Deconvolution Analysis ◽  
Releasing Hormone ◽  
Sampling Protocols ◽  
Peak Value

OBJECTIVE: The quantitative assessment of gland responsiveness to exogenous stimuli is typically carried out using the peak value of the hormone concentrations in plasma, the area under its curve (AUC), or through deconvolution analysis. However, none of these methods is satisfactory, due to either sensitivity to measurement errors or various sources of bias. The objective was to introduce and validate an easy-to-compute responsiveness index, robust in the face of measurement errors and interindividual variability of kinetics parameters. DESIGN: The new method has been tested on responsiveness tests for the six pituitary hormones (using GH-releasing hormone, thyrotrophin-releasing hormone, gonadotrophin-releasing hormone and corticotrophin-releasing hormone as secretagogues), for a total of 174 tests. Hormone concentrations were assayed in six to eight samples between -30 min and 120 min from the stimulus. METHODS: An easy-to-compute direct formula has been worked out to assess the 'stimulated AUC', that is the part of the AUC of the response curve depending on the stimulus, as opposed to pre- and post-stimulus spontaneous secretion. The weights of the formula have been reported for the six pituitary hormones and some popular sampling protocols. RESULTS AND CONCLUSIONS: The new index is less sensitive to measurement error than the peak value. Moreover, it provides results that cannot be obtained from a simple scaling of either the peak value or the standard AUC. Future studies are needed to show whether the reduced sensitivity to measurement error and the proportionality to the amount of released hormone render the stimulated AUC indeed a valid alternative to the peak value for the diagnosis of the different pathophysiological states, such as, for instance, GH deficits.

Use of simulation–extrapolation estimation in catch–effort analyses

1999 ◽  
Vol 56 (7) ◽  
pp. 1234-1240
Author(s):  
W R Gould ◽  
L A Stefanski ◽  
K H Pollock
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Mean Squared Error ◽  
Estimation Procedure ◽  
Bias Reduction ◽  
Estimation Methods ◽  
Effort Estimation ◽  
Stat Assoc ◽  
General Terms ◽  
Naive Estimator

All catch-effort estimation methods implicitly assume catch and effort are known quantities, whereas in many cases, they have been estimated and are subject to error. We evaluate the application of a simulation-based estimation procedure for measurement error models (J.R. Cook and L.A. Stefanski. 1994. J. Am. Stat. Assoc. 89: 1314-1328) in catch-effort studies. The technique involves a simulation component and an extrapolation step, hence the name SIMEX estimation. We describe SIMEX estimation in general terms and illustrate its use with applications to real and simulated catch and effort data. Correcting for measurement error with SIMEX estimation resulted in population size and catchability coefficient estimates that were substantially less than naive estimates, which ignored measurement errors in some cases. In a simulation of the procedure, we compared estimators from SIMEX with "naive" estimators that ignore measurement errors in catch and effort to determine the ability of SIMEX to produce bias-corrected estimates. The SIMEX estimators were less biased than the naive estimators but in some cases were also more variable. Despite the bias reduction, the SIMEX estimator had a larger mean squared error than the naive estimator for one of two artificial populations studied. However, our results suggest the SIMEX estimator may outperform the naive estimator in terms of bias and precision for larger populations.

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