• Structural Engineering and Mechanics
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• v.6 no.5
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• pp.571-582
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• 1998

Testing of steel roof purlins is usually performed on full scale models in large vacuum test rigs. To undertake a comparison between web cleat connected purlins and flange bolted purlins a series of tests were performed on a 1:4 small scale model vacuum test rig. Various modelling issues need to be addressed to ensure reasonable comparison with actual constructed roof framing methods but still be suitable for an economical comparison between the connection methods. Model test results were supported by, and found to be in reasonable agreement with, deflection predictions from computer models based on finite element methods. This paper discusses the testing methods adopted and the value of small scale model testing programs as a means of obtaining comparisons between framing options.

• Journal of Korean Society for Quality Management
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• v.34 no.3
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• pp.73-78
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• 2006

In this paper, we propose a software reliability growth model based on the testing domain in the software system, which is isolated by the executed test cases in software testing. In particular, our model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process, and is formulated as a nonhomogeneous Poisson process(NHPP). Further, it is applied to fault-detection data, the results of software reliability assessment are shown, and comparison of goodness-of-fit with the existing software reliability growth model is performed.

• Speech Sciences
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• v.15 no.2
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• pp.55-65
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• 2008

Recently, the multi-model based speech recognizer has been used quite successfully for noisy speech recognition. For the selection of the reference HMM (hidden Markov model) which best matches the noise type and SNR (signal to noise ratio) of the input testing speech, the estimation of the SNR value using the VAD (voice activity detection) algorithm and the classification of the noise type based on the GMM (Gaussian mixture model) have been done separately in the multi-model framework. As the SNR estimation process is vulnerable to errors, we propose an efficient method which can classify simultaneously the SNR values and noise types. The KL (Kullback-Leibler) distance between the single Gaussian distributions for the noise signal during the training and testing is utilized for the classification. The recognition experiments have been done on the Aurora 2 database showing the usefulness of the model compensation method in the multi-model based speech recognizer. We could also see that further performance improvement was achievable by combining the probability density function of the MCT (multi-condition training) with that of the reference HMM compensated by the D-JA (data-driven Jacobian adaptation) in the multi-model based speech recognizer.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.403-414
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• 2000

A diagnostic tool for testing homogeneity for random effects is proposed in unbalanced linear mixed model based on score statistic. The finite sample behavior of the test statistic is examined using Monte Carlo experiments examine the chi-square approximation of the test statistic under the null hypothesis.

• Journal of Information Processing Systems
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• v.4 no.1
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• pp.33-40
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• 2008

Traceability has been held as an important factor in testing activities as well as model-driven development. Vertical traceability affords us opportunities to improve manageability from models and test cases to a code in testing and debugging phase. This paper represents a vertical test method which connects a system test level and an integration test level in testing stage by using UML. An experiment how traceability works to effectively focus on error spots has been included by using concrete examples of tracing from models to the code.

• Journal of Information Processing Systems
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• v.6 no.2
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• pp.197-208
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• 2010

Test scenarios can be derived based on some system models for requirements validation purposes. Model-based test suite reduction aims to provide a smaller set of test scenarios which can preserve the original test coverage with respect to some testing criteria. We are proposing to apply Formal Concept Analysis (FCA) in analyzing the association between a set of test scenarios and a set of transitions specified in a state machine model. By utilizing the properties of concept lattice, we are able to determine incrementally a minimal set of test scenarios with adequate test coverage.

• Journal of Applied Reliability
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• v.15 no.3
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• pp.207-215
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• 2015

Safety' can be used in a variety of ways and may also have different meanings when used in theoretical field and routinely used. In this paper, the 'safety' means that human injury, fire or physical accident condition does not occur while used by the end-user. The meaning of safety may be different by era and culture. Even in contemporary era, the meaning can be used differently by country, region and culture. As the rights of consumers are increasingly reinforced, we can expect the acceptable risk or safety level can rise higher. In this paper, the R-map of Japan and the European risk assessment guidelines (RAPEX) were reviewed considering domestic incidents database status and its applicability. Because it is difficult to make a model based on a R-map, a revised model was developed mainly based on European Assessment Model with a combination of the important characteristics of Japan model R-map. Also utilizing this revised model, the availability as a new risk assessment model was confirmed by comparing the test results for the same scenarios to the other risk assessment model (RAPEX/RAG).

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.17-22
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• 2016

Colorectal cancer is a major cause of mortality worldwide. Fecal occult blood testing has proven a very effective screening tool for early detection and mortality reduction. The aim of this study was to determine predictors factors related to fecal occult blood testing using the Health Belief Model method among residents of Bushehr, Iran. A cross sectional study was performed on a sample of 600 men and women more than 50 years of age. The sample was selected by a convenience method from patients referred to public and private laboratories throughout the city. Each subject filled out a questionnaire which was designed and developed based on Health Belief Model constructs. Statistical analysis was conducted using ANOVA, T-test, chi-square test, and logistic regression. Fecal occult blood tests were performed on 179 (29.8%) out of 600 subjects, of which 95 patients (58.1%) did a periodic examination test and 84 patients (46.9%) had a doctor's advice for testing. According to the logistic regression model, the perceived barriers (P=0.0, Exp(B)= 0.3), perceived benefits (P<0.01, Exp(B)= 1.9) and self-efficacy (P<0.01, Exp(B)= 1.6) were predictive factors related to occult blood testing among subjects. The results showed that reducing people's perception of barriers to testing, increasing perceived benefits of screening, and reinforcing self efficacy can have major effect in increasing the rate of fecal occult blood screening for colorectal cancer prevention.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.451-459
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• 2011

In this paper, a software release model is presented to determine the optimum testing time with consideration of software error type. The software errors are classified into two types, major and minor errors. The software testing is continued until the Nth major error is discovered and corrected. The total cost needed before and after testing time is modeled under nonhomogeneous Poisson error correction model. Numerical examples are presented to demonstrate the results.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.25-34
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• 2012

In this study, in the process of testing before the release of the software products designed, software testing manager in advance should be aware of the testing-information. Therefore, the effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and applied property of learning effect based on truncated time and delayed S-shaped software reliability. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model can be confirmed. This paper, a failure data analysis was performed, using time between failures, according to the small sample and large sample sizes. The parameter estimation was carried out using maximum likelihood estimation method. Model selection was performed using the mean square error and coefficient of determination, after the data efficiency from the data through trend analysis was performed.