• Convergence Security Journal
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• v.11 no.3
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• pp.19-24
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• 2011

Software failure time presented in the literature exhibit either constant monotonic increasing or monotonic decreasing, For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, time series analys is used in the simple moving average and weighted moving averages, exponential smoothing method for predict the future failure times, Empirical analysis used interval failure time for the prediction of this model. Model selection using the mean square error was presented for effective comparison.

• Journal of Korean Neurosurgical Society
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• v.53 no.6
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• pp.360-363
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• 2013

We recently experienced self-detachment of the Solitaire stent during mechanical thrombectomy of acute ischemic stroke. Then, we tried to remove the detached stent and to recanalize the occlusion, but failed with endovascular means. The following diffusion weighted image MRI revealed no significant increase in infarction size, therefore, we performed surgical removal of the stent to rescue the patient and to elucidate the reason why the self-detachment occurred. Based upon the operative findings, the stent grabbed the main thrombi but inadvertently detached at a severely tortuous, acutely angled, and circumferentially calcified segment of the internal carotid artery. Postoperative angiography demonstrated complete recanalization of the internal carotid artery. The patient's neurological deficits gradually improved, and the modified Rankin scale score was 2 at three months after surgery. In the retrospective case review, bone window images of the baseline computed tomography (CT) scan corresponded to the operative findings. According to this finding, we hypothesized that bone window images of a baseline CT scan can play a role in terms of anticipating difficult stent retrieval before the procedure.

• Structural Engineering and Mechanics
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• v.76 no.4
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• pp.529-540
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• 2020

Concurrent topology optimization of macrostructure and microstructure has attracted significant interest due to its high structural performance. However, most of the existing works are carried out under deterministic conditions, the obtained design may be vulnerable or even cause catastrophic failure when the load position exists uncertainty. Therefore, it is necessary to take load position uncertainty into consideration in structural design. This paper presents a computational method for robust concurrent topology optimization with consideration of load position uncertainty. The weighted sum of the mean and standard deviation of the structural compliance is defined as the objective function with constraints are imposed to both macro- and micro-scale structure volume fractions. The Bivariate Dimension Reduction method and Gauss-type quadrature (BDRGQ) are used to quantify and propagate load uncertainty to calculate the objective function. The effective properties of microstructure are evaluated by the numerical homogenization method. To release the computation burden, the decoupled sensitivity analysis method is proposed for microscale design variables. The bi-directional evolutionary structural optimization (BESO) method is used to obtain the black-and-white designs. Several 2D and 3D examples are presented to validate the effectiveness of the proposed robust concurrent topology optimization method.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.515-522
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• 2021

It is hard to prepare sufficient training data for speech emotion recognition due to the difficulty of emotion labeling. In this paper, we apply transfer learning with large-scale training data for speech recognition on a transformer-based model to improve the performance of speech emotion recognition. In addition, we propose a method to utilize context information without decoding by multi-task learning with speech recognition. According to the speech emotion recognition experiments using the IEMOCAP dataset, our model achieves a weighted accuracy of 70.6 % and an unweighted accuracy of 71.6 %, which shows that the proposed method is effective in improving the performance of speech emotion recognition.

• Journal of Environmental Science International
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• v.28 no.1
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• pp.19-35
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• 2019

This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

• Journal of Forest and Environmental Science
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• v.35 no.3
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• pp.181-188
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• 2019

This study was performed to construct tree species classification map according to three information types (spectral information, texture information, and spectral and texture information) by altitude (30 m, 60 m, 90 m) using the unmanned aerial vehicle images and the object-based classification method, and to evaluate the concordance rate through field survey data. The object-based, optimal weighted values by altitude were 176 for 30 m images, 111 for 60 m images, and 108 for 90 m images in the case of Scale while 0.4/0.6, 0.5/0.5, in the case of the shape/color and compactness/smoothness respectively regardless of the altitude. The overall accuracy according to the type of information by altitude, the information on spectral and texture information was about 88% in the case of 30 m and the spectral information was about 98% and about 86% in the case of 60 m and 90 m respectively showing the highest rates. The concordance rate with the field survey data per tree species was the highest with about 92% in the case of Pinus densiflora at 30 m, about 100% in the case of Prunus sargentii Rehder tree at 60 m, and about 89% in the case of Robinia pseudoacacia L. at 90 m.

• Journal of the Korea Safety Management & Science
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• v.21 no.1
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• pp.9-16
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• 2019

Logistics companies are worrying about securing of differential competitiveness so as to be competitive companies in keen logistics market. The ground is how users are satisfied by sell-established service system to respond not only economic feasibility of logistics costs but also diversity and advancement of logistics needs. The competitiveness of logistics companies is also caused by customer satisfaction of service and only companies finding and satisfying customer needs continuously may be more competitive. For the competitiveness, it's the most important to analyze demands of current and potential customers and their pursuing value properly. Therefore, this researcher grasped PSL for online logistics service users with 5-point Likert-scale and quality-level decision method that consider the weighted value based on Kano model, measured customer's potential Demand for service through PCDI, and suggested methodology for deciding the priority of the improvement with loss function of Taguchi.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.563-570
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• 2021

This study aims at exploring the corporate social responsibility (CSR) practices in the listed companies of Bangladesh. One hundred eighty-two different companies from fifteen different sectors have been selected as a sample. A weighted disclosure index having fifty-two items has been applied to ensure the degree of CSR practices of the sample companies. Each of the content has been assigned a three-scale value starting from zero to two. After that, eight dimensions of CSR are identified from CSR literature and have been evaluated by the predetermined disclosure index. Finally, a composite CSR disclosure (CSRD) score has been computed to measure the extent of CSR practices of the sample companies. The findings of the study reveal a poor CSRD score by the sample companies. Besides, it has been found that the listed companies provide more CSR activities on employee-related issues and community service-related issues while the listed companies provide less information on energy-related CSRD and customer-related CSRD in the context of Bangladesh. The findings of the study imply that the government and the regulatory authority should give more attention to develop a harmonized standards or policies to measure the degree of CSR practices for comparative purposes.

• Korean Journal of Ecology and Environment
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• v.54 no.1
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• pp.71-77
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• 2021

Using data from flies collected with pitfall traps in 365 forests on a nationwide scale in Korea, the abundance and distribution changes of two families (Phoridae and Lauxaniidae) in Korean forests were predicted at the genus level according to two climate change scenarios: RCP 4.5 and RCP 8.5. The most suitable temperature for the 17 major genera was estimated using a weighted average regression model. Stichillus and Anevrina displayed the lowest optimum temperature with 7.6℃ and 8.5℃ in annual mean temperature, respectively, whereas Chonocephalus had the highest optimum temperature with 12.1℃. Among thirty genera, seven genera (four from Phoridae and three from Lauxaniidae), which showed their abundance in a bell-type or linear pattern along the temperature gradient, were used for predicting the distribution changes according to the future climate change scenarios. All the taxa of this study are expected to decrease in abundance and distribution as a function of temperature increase. Moreover, cold-adapted taxa were found to be more affected than warm-adapted taxa.

• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.1
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• pp.1-7
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• 2023

Purpose: Fine dust is classified as a group 1 carcinogen and poses a significant environmental problem that urgently requires improvement to protect the environmental rights of citizens. Given the difficulty of implementing measures to reduce overseas sources of fine dust, it is essential to first devise specific measures to address domestic emission sources. As such, this study aims to analyze the correlation between earthwork volume control and fine dust concentration as preliminary management measures to reduce the impact of scattering dust at construction sites. Based on real-time air quality information, field management measures will be presented to mitigate the effects of dust emissions. Research design, data and methodology: As examples, we selected construction sites that had recently undergone small-scale environmental impact assessment consultations. The standard earthwork volume was classified into grades using 20% intervals, and we applied AERMOD to predict the weighted concentration of fine dust based on the earthwork volume class and analyzed its correlation. Results: The results of this study demonstrate a strong correlation between earthwork volume and fine dust concentration. By utilizing the correlation analysis between earthwork volume and fine dust concentration on-site, this finding can be utilized as an effective fine dust management plan. Conclusions: This involves determining the daily earthwork intensity based on real-time air quality information and implementing measures to reduce scattering dust.