• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.321-339
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• 2021

Response Surface Method (RSM) has been widely used for flammable cloud size prediction as it can reduce computational intensity for further Explosion Risk Analysis (ERA) especially during the early design phase of offshore platforms. However, RSM encounters the overfitting problem under very limited simulations. In order to overcome the disadvantage of RSM, Bayesian Regularization Artificial Neural (BRANN)-based model has been recently developed and its robustness and efficiency have been widely verified. However, for ERA during the early design phase, there seems to be room to further reduce the computational intensity while ensuring the model's acceptable accuracy. This study aims to develop an integrated method, namely the combination of Center Composite Design (CCD) method with Bayesian Regularization Artificial Neural Network (BRANN), for flammable cloud size prediction. A case study with constant and transient leakages is conducted to illustrate the feasibility and advantage of this hybrid method. Additionally, the performance of CCD-BRANN is compared with that of RSM. It is concluded that the newly developed hybrid method is more robust and computational efficient for ERAs during early design phase.

• Fourth Industrial Review
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• v.3 no.2
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• pp.1-10
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• 2023

Purpose - The main purpose of the paper is to examine the variables affecting carbon emissions in different nations around the world. Research design, data, and methodology - To measure its impact on carbon emissions, secondary data has data of the top 50 Countries have been taken. The stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model have been used to quantify the factors that affect carbon emissions. A modified version using Industry 4.0 and region in fundamental STIRPAT model has been applied with the ordinary least square approach. The outcome has been measured using both the basic and extended STIRPAT models. Result - Technology found a positive determinant as well as statistically significant at the alpha level of 0.001models indicating that technological innovation helps reduce carbon emissions. In total, 4 models have been derived to test the best fit and find the highest explaining capacity of variance. Model 3 is found best fit in explanatory power with the highest adjusted R2 (97.95%). Conclusion - It can be concluded that the selected explanatory variables population and Industry 4.0 are found important indicators and causal factors for carbon emission and found constant with all four models for total CO2 and Co2 per capita.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.534-542
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• 1999

A sell-designed rate control strategy can improve overall picture quality for video transmission over a constant bit rate channel and the rate control method is not a normative part of MPEG-video standard, the performance of MPEG video codec can be quite different depends on how to implement the rate control scheme. The rate control scheme proposed in MPEG show good results when scene changes is not occurred. But it has weakness that it does not properly handle scene-changed pictures. Therefore picture quality after scene change is deteriorated, and possibility of overflow occurrence becomes high. In this paper, a new method for detection of scene change occurrence using local variance and a new determination scheme for adaptive quantization parameter, mqunt, which can consider local characteristic of an image by using previously computed the local variance from the scene change detection part are proposed. IN addition, and adaptive rate control scheme which can handles scene changed picture very efficiently by scene-changed picture is proposed. Computer simulations are performed to verify the performance of the proposed algorithm. The suggested detection algorithm precisely detected scene change. And the proposed rate control scheme shows better rate control performance as compared with that of the conventional MPEG scheme.

• Smart Structures and Systems
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• v.32 no.4
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• pp.267-279
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• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

• Journal of Veterinary Clinics
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• v.7 no.2
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• pp.471-487
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• 1990

Present experiment was performed in order to establish the optimum conditions for quantitation of ${\gamma}$-GTP and AGS activities in rat urine and investigate the applicability of the these enzymes in experimental assessment of nephrotoxicity in rats. The results obtained were as follows. 1. The optimal pH of Tris-BCI buffer containing glycylglycine for determination of urinary ${\gamma}$-GTP activity was 7.6(37$^{\circ}C$). 2. The Michaelis constant of urinary ${\gamma}$-GTP ranged from 1.1 to 1.2 mmol/$\ell$. 3. The optimal pH of citrate buffer for determination of urinary AGS activity was 3.6(37$^{\circ}C$). 4. The Michaelis constant of urinary AGS ranged from 0.8 to 0.9mmo1/$\ell$. 5. Coefficient of variance for within-run imprecision of urinary ${\gamma}$-GTP ranged from 3.8 to 6.4％ and that of urinary AGS ranged from 2.5 to 4.1％. 6. There was no significant difference between gel-filtered samples and crude samples in the mean activity of urinary ${\gamma}$-GTP and the intra-individual differences by gel-filtration were either increased or decreased. Mean values of ${\gamma}$ -GTP activities in gel-filtered samples and crude samples were 1570 and 1590 U/$\ell$, repectively. 7. The mean activity of urinary AGS increased significantly after gel-filtration and all the individual urines revealed higher activities after gel-filtration. 8. ${\gamma}$-GTP and AGS activities were linear to 135 and 7U/$\ell$, respectively. 9. Urinary ${\gamma}$-GTP and AGS excretion before administration of potassium dichromate were 22.1 ${\pm}$ 11.2 and 0.5${\pm}$0.2 U/24hrsㆍkg body weight respectively and increased significantly to 102.3${\pm}$44.5 and 5.8${\pm}$3.30/24hrsㆍkg body weight respectively within 24 hours after administration. 10. BUN increased continuously from 24 hours following exposure to potassium dichromate in all 10 rats. From these findings it is concluded that the urinary ${\gamma}$-GTP and AGS excretions are early and sensitive indicators for nephrotoxicity assessment in rat.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.199-226
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• 2009

We examine the intertemporal relation between risk and return in the Korean stock market and foreign exchange market based on the two factor ICAPM framework. The standard GARCH model and the GJR(1993) model are employed to estimate conditional variances of the stock returns and foreign exchange rates. The covariance between the rates of stock returns and changes in the exchange rates are estimated by the constant conditional correlation model of Bollerslev(1990) and the dynamic conditional correlation model of Engle(2002). The multivariate GARCH in mean model and quasi-maximum likelihood estimation method, consequently, are applied to investigate riskreturn relation jointly. We find that the estimated coefficient of relative risk aversion is negative and statistically significant in the post-financial crisis sample period in the Korean stock market. We also show that the expected stock returns are negatively related to the dynamic covariance with foreign exchange rates. Both estimated parameters of conditional variance and covariance in the foreign exchange market, however, are not statistically significant. The GJR model is better than the standard GARCH model to estimate the conditional variances. In addition, the dynamic conditional correlation model has higher explanatory power than the constant correlation model. The empirical results of this study suggest following two points to investors and risk managers in hedging and diversifying strategies for their portfolios in the Korean stock market: first, the variability of foreign exchange rates should be considered, and second, time-varying correlation between stock returns and changes in foreign exchange rates supposed to be considered.

• Health Policy and Management
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• v.24 no.2
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• pp.136-142
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• 2014

Background: This study is to research on how hypertension control is associated with adherence in newly diagnosed hypertension patients. Methods: The study is based on 255,916 patients who were diagnosed with hypertension in 2009 and didn't have any previous medical history of hypertension or associated complication for the past year using data collected by National Health Insurance Corporation. Newly diagnosed hypertension patients are divided into two group by visiting medical center numbers (more than 300 days was adherence group, if not non-adherence group). Patients are considered to have successfully controlled their hypertension based on blood pressure measured by health examination. Chi-square test and logistic regression, repeated measured analysis of variance was used to analyze. Results: The relations between adherence and hypertension control show that 1.12 times of patients in adherence group was able to control their hypertension. The additional analysis proves that adherence group are more decreased level of blood pressure than non-adherence group except for patients who are over 70. Comparison of the average of systolic blood pressure and diastolic blood pressure between adherence and non-adherence groups shows that the blood pressure has been significantly among the adherence group. Conclusion: The study proves that constant treatment for hypertension could control the blood pressure and encourages patients to put more effort for persistent treatment. It also shows that hypertension treatment are more effective in younger patients than the elderly and strategies of approaching are different depending on age.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.18 no.3
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• pp.239-247
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• 2008

Low back disorders (LBDs) have been the most common musculoskeletal problem in Korean workplaces. It affects many workers, and is associated with high costs to many companies as well as the individual, which can negatively influence even the quality of life of workers. The _evaluation of low back disorder risk associated with manual materials handling tasks can be performed using variety of ergonomic assessment tools such as National Institute for Occupational Safety and Health (NIOSH) Revised Lifting Equation (NLE), the Washington Administrative Code 296-62-0517 (WAC), the Snook Tables etc. But most of these tools provide limited information for choosing the most appropriate assessment method for a particular job and in finding out advantage and disadvantage of the methods, and few have been assessed for their predictive ability. The focus of this study was to _evaluate spinal loads in real time with lifting and pulling heavy cow leathers in variety of postures. Data for estimating mean trunk motions were collected as employees did their work at the job site, using the Lumbar Motion Monitor. Eight employees (2 males, 6 females) were selected in this study, in which the load weight and the vertical start and destination heights of the activity remained constant throughout the task. Variance components (three dimensional spaces) of mean trunk kinematic measures were estimated in a hierarchical design. They were used to compute velocity and acceleration of multiple employees performing the same task and to repetitive movements within a task. Therefore, a results of this study could be used as a quantitative, objective measure to design the workplace so that the risk of occupationally related low back disorder should be minimized.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.7
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• pp.478-488
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• 2009

Using solar power in wireless sensor networks (WSNs) requires adaptation to a highly varying energy supply and to a battery constraint. From an application's perspective, however, it is often preferred to operate at a constant quality level as opposed to changing application behavior frequently. Reconciling the varying supply with the fixed demand requires good tools for allocating energy such that average of energy supply is computed and demand is fixed accordingly. In this paper, we propose a probabilistic observation-based model for harvested solar energy. Based on this model, we develop a time-slot-based energy allocation scheme to use the periodically harvested solar energy optimally, while minimizing the variance in energy allocation. We also implement the testbed and demonstrate the efficiency of the approach by using it.

• Journal of Korea Game Society
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• v.6 no.2
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• pp.51-60
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• 2006

Smoothing is a transmission plan where variable rate video data is converted to a constant bit rate stream. Among them are CBA, MCBA, MVBA, PCRTT and others. But, in these algorithm, a transmission plan is made in according to stored frame sequence in these algorithms. In case that the number of bytes in frames in GOP differs greatly each other, this may cause unnecessary transmission rate changes and may require high transmission rates abruptly when frame's byte is large. In result, it is difficult to use efficient network resource. In this paper, we proposed a smoothing algorithm that find the optimal frame sequence in short time by using backtracking method and smoothing's structure for the proposed smoothing algorithm. This algorithm decides the sequence of frames which requires the lowest variance of frame's bytes in GOP and make a transmission plan. In order to show the performance, we compared with MVBA algorithm by various evaluation factors such as the number of rate changes, peak rate, rate variability.