Quality Measure of Short-Duration Bicycle Counts

2017 ◽  
Vol 2644 (1) ◽  
pp. 64-71 ◽  
Author(s):  
David Beitel ◽  
Spencer McNee ◽  
Luis F. Miranda-Moreno
Keyword(s):  
Injury Risk ◽  
Large Data ◽  
Quality Measure ◽  
Short Term ◽  
Data Set ◽  
Simple Method ◽  
Counting Period ◽  
Quality Class ◽  
Time Of Year

The average annual daily bicyclists (AADB) measure is commonly used in research and practice as a metric for cycling studies, such as bike ridership analysis, infrastructure planning, and injury risk. It is estimated in one of two ways: by averaging the daily cyclist totals measured throughout the year with a long-term automated bicycle counter, or by using a long-term bicycle counter to extrapolate data from a short-term counting site. Unfortunately, extrapolation of a short-term bicycle counting site can produce inaccurate AADB estimates as a result of different error sources; the range of possible error is highly correlated to several characteristics of the short-term count, such as the counting period, flow intensity, and time of year. This paper proposes a simple method to estimate the quality of a short-term count through a single metric combining five factors associated with the count variation: duration, average demand, time of year, stability, and correlation with the reference count. The method is validated with the use of a relatively large data set of automated bicycle counts. The quality measure, with a range from 0 to 10, is negatively correlated with the absolute relative error (ARE) of the AADB estimation. Results show distinct ARE distributions for different quality measure classes. The average ARE for the lowest quality class is 13.5% compared with an average ARE of 3.0% for the highest quality class. The maximum ARE (95% confidence) is 35% for the lowest quality class compared with 7.5% for the highest quality class.

scholarly journals Investigating the Broken-Heart Effect: a Model for Short-Term Dependence between the Remaining Lifetimes of Joint Lives

2012 ◽  
Vol 7 (2) ◽  
pp. 236-257 ◽  
Author(s):  
Jaap Spreeuw ◽  
Iqbal Owadally
Keyword(s):  
Mortality Rates ◽  
Short Term ◽  
Numerical Work ◽  
Data Set ◽  
Multiple State ◽  
Multiple State Model ◽  
Insurance Data ◽  
Over Time ◽  
Assurance Contracts

AbstractWe analyze the mortality of couples by fitting a multiple state model to a large insurance data set. We find evidence that mortality rates increase after the death of a partner and, in addition, that this phenomenon diminishes over time. This is popularly known as a “broken-heart” effect and we find that it affects widowers more than widows. Remaining lifetimes of joint lives therefore exhibit short-term dependence. We carry out numerical work involving the pricing and valuation of typical contingent assurance contracts and of a joint life and survivor annuity. If insurers ignore dependence, or mis-specify it as long-term dependence, then significant mis-pricing and inappropriate provisioning can result. Detailed numerical results are presented.

scholarly journals Effects of agricultural credit on wheat productivity of small farms in Sindh, Pakistan

2018 ◽  
Vol 78 (5) ◽  
pp. 592-610 ◽  
Author(s):  
Abbas Ali Chandio ◽  
Yuansheng Jiang ◽  
Feng Wei ◽  
Xu Guangshun
Keyword(s):  
Wheat Yield ◽  
Considerable Proportion ◽  
Small Scale ◽  
Small Farms ◽  
Short Term ◽  
Agricultural Credit ◽  
Data Set ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to evaluate the impact of short-term loan (STL) vs long-term loan (LTL) on wheat productivity of small farms in Sindh, Pakistan. Design/methodology/approach The econometric estimation is based on cross-sectional data collected in 2016 from 18 villages in three districts, i.e. Shikarpur, Sukkur and Shaheed Benazirabad, Sindh, Pakistan. The sample data set consist of 180 wheat farmers. The collected data were analyzed through different econometric techniques like Cobb–Douglas production function and Instrumental variables (two-stage least squares) approach. Findings This study reconfirmed that agricultural credit has a positive and highly significant effect on wheat productivity, while the short-term loan has a stronger effect on wheat productivity than the long-term loan. The reasons behind the phenomenon may be the significantly higher usage of agricultural inputs like seeds of improved variety and fertilizers which can be transformed into the wheat yield in the same year. However, the LTL users have significantly higher investments in land preparation, irrigation and plant protection, which may lead to higher wheat production in the coming years. Research limitations/implications In the present study, only those wheat farmers were considered who obtained agricultural loans from formal financial institutions like Zarai Taraqiati Bank Limited and Khushhali Bank. However, in the rural areas of Sindh, Pakistan, a considerable proportion of small-scale farmers take credit from informal financial channels. Therefore future researchers should consider the informal credits as well. Originality/value This is the first paper to examine the effects of agricultural credit on wheat productivity of small farms in Sindh, Pakistan. This paper will be an important addition to the emerging literature regarding effects of credit studies.

scholarly journals Calibration methods for rotating shadowband irradiometers and optimizing the calibration duration

2016 ◽  
Vol 9 (4) ◽  
pp. 1601-1612 ◽  
Author(s):  
Wilko Jessen ◽  
Stefan Wilbert ◽  
Bijan Nouri ◽  
Norbert Geuder ◽  
Holger Fritz
Keyword(s):  
Spectral Response ◽  
Atmospheric Condition ◽  
Resource Assessment ◽  
Data Sets ◽  
Data Set ◽  
Direct Normal Irradiance ◽  
Calibration Methods ◽  
Long Term Result ◽  
Time Of Year

Abstract. Resource assessment for concentrated solar power (CSP) needs accurate direct normal irradiance (DNI) measurements. An option for such measurement campaigns is the use of thoroughly calibrated rotating shadowband irradiometers (RSIs). Calibration of RSIs and Si-sensors is complex because of the inhomogeneous spectral response of these sensors and incorporates the use of several correction functions. One calibration for a given atmospheric condition and air mass might not be suitable under different conditions. This paper covers procedures and requirements of two calibration methods for the calibration of rotating shadowband irradiometers. The necessary duration of acquisition of test measurements is examined with regard to the site-specific conditions at Plataforma Solar de Almería (PSA) in Spain. Seven data sets of long-term test measurements were collected. For each data set, calibration results of varying durations were compared to its respective long-term result. Our findings show that seasonal changes of environmental conditions are causing small but noticeable fluctuation of calibration results. Calibration results within certain periods (i.e. November to January and April to May) show a higher likelihood of deviation. These effects can partially be attenuated by including more measurements from outside these periods. Consequently, the duration of calibrations at PSA can now be selected depending on the time of year in which measurements commence.

scholarly journals Introducing the Dynamic Destination Satisfaction Method: An Analytical Tool to Track Tourism Destination Satisfaction Trends with Repeated Cross-sectional Data

2020 ◽  
pp. 004728752095820
Author(s):  
Andrea Guizzardi ◽  
Marcello M. Mariani
Keyword(s):  
Large Data ◽  
System Level ◽  
Set Covering ◽  
Tourism Destination ◽  
Cross Sectional ◽  
Data Set ◽  
Individual Level ◽  
Specific Attribute ◽  
The Matrix

This study introduces a new method, named Dynamic Destination Satisfaction Method (DDSME), to model tourists’ satisfaction with a destination (and its attributes), breaking it down into an individual-level component (linked to the specific individual tourists’ perceptions) and a system-level (time-related) component (common to all the tourists). Moreover, this work develops a matrix “entropy/trend accuracy” that destination managers can use to understand to what extent managing a specific attribute has increased tourists’ satisfaction with the destination over multiyear time spans. We test the innovative method on a large data set, covering the period 1997-2015 and including almost 0.8 million observations. By doing so, we analyze tourists’ satisfaction with tourism-related sectors and attributes of Italy as an inbound tourism destination and we use the matrix to map out destination attributes over time. The findings indicate that courtesy, art, and food are strategic attributes to enhance satisfaction in the long term.

How loan interest rate liberalization affects firms’ loan maturity structure

2014 ◽  
Vol 4 (2) ◽  
pp. 153-167 ◽  
Author(s):  
Jianfang Zhou ◽  
Jingjing Wang ◽  
Jianping Ding
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Manufacturing Companies ◽  
Short Term ◽  
Data Set ◽  
Content Type ◽  
Interest Rate Liberalization ◽  
Upper Limit ◽  
Maturity Structure

Purpose – After loan interest rate upper limit deregulation in October 2004, the financing environment in China changed dramatically, and the banks were eligible for risk compensation. The purpose of this paper is to focus on the influence of the loan interest rate liberalization on firms’ loan maturity structure. Design/methodology/approach – Based on Rajan's (1992) model, the authors constructed a trade-off model of how the banks choose long-term and short-term loans scales, and further analyzed banks’ loan term decisions under the loan interest rate upper limit deregulation or collateral cases. Then the authors used an unbalanced panel data set of 586 Chinese listed manufacturing companies and 9,376 observations during the period 1996-2011 to testify the theoretical conclusion. Furthermore, the authors studied the effect on firms with different characteristics of ownership or scale. Findings – The results show that the loan interest rate liberalization significantly decreases the private companies’ reliance on short-term loans and increases sensitivity to interest rates of state-owned companies’ long-term loans. But the results also show that the companies’ ownership still plays a key role on the long-term loans availability. When monetary policy tightened, small companies still have to borrow short-term loans for long-term purposes. As the bank industry is still dominated by state-owned banks and the deposit interest rate has upper limits, the effect of the loan interest rate liberalization on easing long-term credit constraints is limited. Originality/value – From a new perspective, the content and findings of this paper contribute to the study of the effect of the interest rate liberalization on China economy.

Methodology of Creep Data Analysis for Advanced High Cr Ferritic Steel

2007 ◽  
Author(s):  
Kouichi Maruyama ◽  
Kyosuke Yoshimi
Keyword(s):  
Data Analysis ◽  
Rupture Life ◽  
Creep Rupture ◽  
Creep Data ◽  
Short Term ◽  
Data Set ◽  
Region Analysis ◽  
Rupture Data ◽  
Term Creep

Long term creep rupture life is usually evaluated from short term data by a time-temperature parameter (TTP) method. The apparent activation energy Q for rupture life of steels sometimes changes from a high value of short term creep to a low value of long term creep. However, the conventional TTP analyses ignore the decrease in Q, resulting in the overestimation of rupture life recognized recently in advanced high Cr ferritic steels. A multi region analysis of creep rupture data is applied to a creep data set of Gr.122 steel; in the analysis a creep rupture data is divided into several data sets so that Q value is unique in each divided data set. The multi region analysis provides the best fit to the data and the lowest value of 105 h creep rupture strength among the three ways of data analysis examined. The conventional single region analysis cannot correctly represent the data points and predicts the highest strength. A half of 0.2% proof stress could not be an appropriate boundary for dividing data to be used in the multi region analysis. In the 2001 Edition of ASME Code an F average concept has been proposed as a substitution for the safety factor of 2/3 for average rupture stress. The allowable stress of Gr.122 steel may decrease significantly when the F average concept and the multi region analysis are adopted.

scholarly journals Re-analysis of ground-based microwave ClO measurements from Mauna Kea, 1992 to early 2012

2013 ◽  
Vol 13 (17) ◽  
pp. 8643-8650 ◽  
Author(s):  
B. J. Connor ◽  
T. Mooney ◽  
G. E. Nedoluha ◽  
J. W. Barrett ◽  
A. Parrish ◽  
...  
Keyword(s):  
Atmospheric Composition ◽  
Composition Change ◽  
Major Focus ◽  
Short Term ◽  
Data Set ◽  
Long Term Changes ◽  
The Difference ◽  
Long Term Trend ◽  
Linear Decline

Abstract. We present a re-analysis of upper stratospheric ClO measurements from the ground-based millimeter-wave instrument from January 1992 to February 2012. These measurements are made as part of the Network for the Detection of Atmospheric Composition Change (NDACC) from Mauna Kea, Hawaii, (19.8° N, 204.5° E). Here, we use daytime and nighttime measurements together to form a day–night spectrum, from which the difference in the day and night profiles is retrieved. These results are then compared to the day–night difference profiles from the Upper Atmosphere Research Satellite (UARS) and Aura Microwave Limb Sounder (MLS) instruments. We also compare them to our previous analyses of the same data, in which we retrieved the daytime ClO profile. The major focus will be on comparing the year-to-year and long-term changes in ClO derived by the two analysis methods, and comparing these results to the long-term changes reported by others. We conclude that the re-analyzed data set has less short-term variability and exhibits a more constant long-term trend that is more consistent with other observations. Data from 1995 to 2012 indicate a linear decline of mid-stratospheric ClO of 0.64 ± 0.15% yr−1 (2σ).

scholarly journals Exploring the role of hydrological pathways in modulating multi-annual climate teleconnection periodicities from UK rainfall to streamflow

2021 ◽  
Vol 25 (4) ◽  
pp. 2223-2237
Author(s):  
William Rust ◽  
Mark Cuthbert ◽  
John Bloomfield ◽  
Ron Corstanje ◽  
Nicholas Howden ◽  
...  
Keyword(s):  
North Atlantic ◽  
Response Times ◽  
Large Data ◽  
Data Set ◽  
The North ◽  
South Wales ◽  
The North Atlantic ◽  
The North Atlantic Oscillation ◽  
The Uk

Abstract. An understanding of multi-annual behaviour in streamflow allows for better estimation of the risks associated with hydrological extremes. This can enable improved preparedness for streamflow-dependant services, such as freshwater ecology, drinking water supply and agriculture. Recently, efforts have focused on detecting relationships between long-term hydrological behaviour and oscillatory climate systems (such as the North Atlantic Oscillation – NAO). For instance, the approximate 7 year periodicity of the NAO has been detected in groundwater-level records in the North Atlantic region, providing potential improvements to the preparedness for future water resource extremes due to their repetitive, periodic nature. However, the extent to which these 7-year, NAO-like signals are propagated to streamflow, and the catchment processes that modulate this propagation, are currently unknown. Here, we show statistically significant evidence that these 7-year periodicities are present in streamflow (and associated catchment rainfall), by applying multi-resolution analysis to a large data set of streamflow and associated catchment rainfall across the UK. Our results provide new evidence for spatial patterns of NAO periodicities in UK rainfall, with areas of greatest NAO signal found in southwest England, south Wales, Northern Ireland and central Scotland, and show that NAO-like periodicities account for a greater proportion of streamflow variability in these areas. Furthermore, we find that catchments with greater subsurface pathway contribution, as characterised by the baseflow index (BFI), generally show increased NAO-like signal strength and that subsurface response times (as characterised by groundwater response time – GRT), of between 4 and 8 years, show a greater signal presence. Our results provide a foundation of understanding for the screening and use of streamflow teleconnections for improving the practice and policy of long-term streamflow resource management.

Prediction of long-term cancer survival from a short-term data set?

2003 ◽  
Vol 48 (12) ◽  
pp. L35-L35
Author(s):  
G Bruggmoser, F Heinemann, N Hodapp R hner
Keyword(s):  
Cancer Survival ◽  
Short Term ◽  
Data Set ◽  
Term Data
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