• Journal of Sensor Science and Technology
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• v.14 no.2
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• pp.116-124
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• 2005

In this paper range measurement systems are designed using an ultrasonic sensor and a camera. An ultrasonic sensor provides the range measurement to a target quickly and simply but its low resolution is a disadvantage. We tackle this problem by employing a camera. Instead using a stereoscopic sensor, which is widely used for 3D sensing but requires a computationally intensive stereo matching, the range is measured by focusing and structured lighting. In focusing a straightforward focusing measure named as MMDH(min-max difference in histogram) is proposed and compared with existing techniques. In the method of structure lighting, light stripes projected by a beam projector are used. Compared to those using a laser beam projector, the designed system can be constructed easily in a low-budget. The system equation is derived by analysing the sensor geometry. A sensing scenario using the systems designed is in two steps. First, when better accuracy is required, measurements by ultrasonic sensing and focusing of a camera are fused by MLE(maximum likelihood estimation). Second, when the target is in a range of particular interest, a range map of the target scene is obtained by using structured lighting technique. The systems designed showed measurement accuracy up to 0.3[mm] approximately in experiments.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.377-387
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• 1998

A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduced latent variables that indicates with component of the Superposition model. This data augmentation approach facilitates specification of the transitional measure in the Markov Chain. Metropolis algorithms along with Gibbs steps are proposed to preform the Bayesian inference of such models. for model determination, we explored the Pre-quential conditional predictive Ordinate(PCPO) criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. To relax the monotonic intensity function assumptions, we consider in this paper Superposition of Musa-Okumoto and Erlang(2) models. A numerical example with simulated dataset is given.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.43-60
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• 2018

This paper considers the use of classical and Bayesian inference methods to analyze data generated by variables whose natural behavior can be modeled using asymmetric distributions in the presence of left censoring. Our approach used a $L{\grave{e}}vy$ distribution in the presence of left censored data and covariates. This distribution could be a good alternative to model data with asymmetric behavior in many applications as lifetime data for instance, especially in engineering applications and health research, when some observations are large in comparison to other ones and standard distributions commonly used to model asymmetry data like the exponential, Weibull or log-logistic are not appropriate to be fitted by the data. Inferences for the parameters of the proposed model under a classical inference approach are obtained using a maximum likelihood estimators (MLEs) approach and usual asymptotical normality for MLEs based on the Fisher information measure. Under a Bayesian approach, the posterior summaries of interest are obtained using standard Markov chain Monte Carlo simulation methods and available software like SAS. A numerical illustration is presented considering data of thyroglobulin levels present in a group of individuals with differentiated cancer of thyroid.

• Journal of Veterinary Clinics
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• v.32 no.4
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• pp.319-323
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• 2015

The performance of diagnostic test accuracy is usually summarized by a variety of statistics such as sensitivity, specificity, predictive value, likelihood ratio, and kappa. These indices are most commonly presented when evaluations of competing diagnostic tests are reported, and it is of utmost importance to compare the accuracies of diagnostic tests to decide on the best available test for certain medical disorder. However, it is important to emphasize that specific point values of these indices are merely estimates. If parameter estimates are reported without a measure of uncertainty (precision), knowledgeable readers cannot know the range within which the true values of the indices are likely to lie. Therefore, when evaluations of diagnostic accuracy are reported the precision of estimates should be stated in parallel. To reflect the precision of any estimate of a diagnostic performance characteristic or of the difference between performance characteristics, the computation of confidential interval (CI), an indicator of precision, is widely used in medical literatures in that CIs are more informative to interpret test results than the simple point estimates. The majority of peer-reviewed journals usually require CIs to be specified for descriptive estimates, whereas domestic veterinary journals seem less vigilant on this issues. This paper describes how to calculate the indices and associated CIs using practical examples when assessing diagnostic test performance.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.145-155
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• 2021

This study examines the export competitiveness of four major natural rubber exporters in the Belt and Road Initiative (BRI) region and investigates the factors affecting bilateral natural rubber export. This study utilized the revealed symmetric comparative advantage (RSCA) to measure export competitiveness. Next, this study employed the gravity model using the Poisson Pseudo Maximum Likelihood (PPML) estimation to analyze the factors affecting bilateral export from the four major natural rubber exporters to 46 countries in the region. The analysis is conducted by using annual data from 2001 till 2018. The findings showed that all four major exporters maintained their export competitiveness. Indonesia and Vietnam notably exhibited increasing trends in the early 2000s. Besides, the market share for Malaysia and Vietnam have increased from 2013 to 2015 with the BRI implementation in 2013. In addition, this study discovered that non-tariff measures (NTM) have a positive and significant impact on the bilateral export of natural rubber. The overall findings strongly indicate that the natural rubber export has increased post BRI announcement. The outcome highlighted the benefits of BRI implementation on the natural rubber export. This study is the first attempt to apply the gravity model on the natural rubber exports within the BRI region.

• The Journal of Industrial Distribution & Business
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• v.12 no.8
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• pp.33-39
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• 2021

Purpose: The influence of age on time preference is not identified in the usual cross-sectional analysis. This study aims to test whether age affects time preference after controlling for the effects of individual heterogeneity including cohort effects. Research design, data and methodology: Drawing on a nationally representative panel dataset of Indonesians, we estimate the effects of age on time preference after controlling for unobserved individual heterogeneity as well as potential cohort effects. We measure time preference exploiting information on two sets of multiple price lists: one for a one-year delay, and the other for a five-year delay. Results: When we controlled for time-invariant individual characteristics, including birth cohort effects in a fixed effects model, the older men and women were more patient in a linear fashion, particularly when the delay was longer. To highlight the importance of controlling for individual fixed effects, we repeated the specification without controlling for individual fixed effects in OLS or censored maximum likelihood regression; we found no relation between age and impatience in men or women and for a one or five-year delay. Conclusions: The older men and women are more patient, and time preferences are correlated with unobserved individual heterogeneity.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.1139-1145
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• 2021

This study is aimed at developing a measurement instrument for the superior product development program of Deli Serdang cassava, Indonesia. This research population is the target population of Deli Serdang Micro, Small and Medium-sized Enterprises (MSMEs) which produces cassava. The sample was randomly selected and consisted of 300 MSMEs. The study method is research and development with confirmatory factor analysis using Amos software. The data collection technique was a questionnaire. Study results used the maximum likelihood method which showed that the validity and reliability instruments met the ideal loading factor value > 0.5 and a significance value of p (0.000). The model built also meets the fit criteria based on the Goodness of Fit Model Standard. All instruments are presented to build and measure the superior cassava product development program by Deli Serdang MSMEs. This superior product development program comprises (1) economic contribution (with a loading factor value of 0.76) (2) social aspects (with a loading factor value of 0.76) (3) cultural aspects (with a loading factor value of 0.99) and (4) institutional (with a loading factor value of 0.87). This result means that all instruments have proven construct validity.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1045-1052
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• 2021

The main purpose of this paper is to explore the relationship between financial inclusion and socio-economic and demographic factors. Ownership of bank accounts, availing of credit facility, and use of mobile banking were considered the major indicators of financial inclusion. To achieved this objective, the present study was conducted in the rural regions of three hill districts of Uttarakhand. 780 rural households were selected by using stratified and judgment sampling technique. To measure the association between the variables, binary logistic regression model was employed. The findings of the study revealed that there is a significant association of socio-economic variables with financial inclusion. The overall analysis of the study indicates that the likelihood of having bank account, usage of mobile banking facility, and availing credit facility increases with the increase in the financial literacy of an individual in hill rural regions of the state. Further, the study also indicates the vulnerability of women relative to that of men in both cases of mobile usage and availing credit. The findings of the study suggest to target the economically vulnerable section of population (as identified in case of having low financial inclusion) and enhancing the financial literacy in these regions.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.1-12
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• 2021

Altman's Z-score is used to measure a company's financial health and to predict the probability that a company will collapse within 2 years. It is proven to be very accurate to forecast bankruptcy in a wide variety of contexts and markets. The goal of this study is to use Altman's Z-score model to forecast insolvency in non-financial publicly traded enterprises. Non-financial firms are a significant industry in Malaysia, and current trends of consolidation and long-term government subsidies make assessing the financial health of such businesses critical not just for the owners, but also for other stakeholders. The sample of this study includes 84 listed companies in the Kuala Lumpur Stock Exchange. Of the 84 companies, 52 are considered high risk, and 32 are considered low-risk companies. Secondary data for the analysis was gathered from chosen companies' financial reports. The findings of this study show that the Altman model may be used to forecast a company's financial collapse. It dispelled any reservations about the model's legitimacy and the utility of applying it to predict the likelihood of bankruptcy in a company. The findings of this study have significant consequences for investors, creditors, and corporate management. Portfolio managers may make better selections by not investing in companies that have proved to be in danger of failing if they understand the variables that contribute to corporate distress.

• Journal of Preventive Medicine and Public Health
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• v.54 no.6
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• pp.461-470
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• 2021

Objectives: The objective of this study was to determine the prevalence of low physical activity (PA) in Peruvian adults and to identify associated factors. Methods: An analytical study was performed using data from the 2017-2018 Nutritional Food Surveillance by Life Stages survey. The outcome variable was low PA (yes or no), assessed using the International Physical Activity Questionnaire-short form. Prevalence ratios were estimated as a measure of association. Results: Among the 1045 persons included in the analysis, the age-standardized prevalence of low PA was 61.9%. The adjusted model showed that being female and migrating from a rural to an urban area in the last 5 years were associated with a higher probability of having low PA than males and individuals who had not migrated, while residing in rural highlands and jungle areas was associated with a reduced probability of having low PA compared to people residing in other geographic domains. Conclusions: Being a female and migration from a rural to an urban area in the last 5 years were associated with a higher likelihood of having low PA. Therefore, promotion and prevention strategies related to PA are required, especially in the female and migrant populations.