In case of cut-slopes or shallow-depth tunnels, sliding along with discontinuities or rotation could play a critical role in judging stability. Although numerical analysis is widely used to check the stability of these cut-slopes and shallow-depth tunnels in early design process, common analysis programs are based on continuum model. Performing continuum model analysis regarding discontinuities is possible by reducing overall strength of jointed rock mass. It is also possible by applying ubiquitous joint model to Mohr-Coulomb failure criteria. In numerical analysis of cut-slope, main geotechnical properties such as cohesion, friction angle and elastic modulus can be evaluated by empirical equations. This study tried to compare two main systems, RMR and GSI system by applying them to in-situ hazardous cut-slopes. In addition, this study applied ubiquitous joint model to simulation model with inputs derived by RMR and GSI system to compare with displacements obtained by in-situ monitoring. To sum up, numerical analysis mixed with GSI inputs and ubiquitous joint model proved to provide most reliable results which were similar to actual displacements and their patterns.
Purpose - This study empirically analyzes the consumer value of risk management associated with illegal, unreported, and unregulated (IUU) fishing of fishery products imported to Korea. The global regulatory paradigm for IUU fishing has shifted from production-centered to market-centered. As a result, changes in the international fisheries trade environment emphasizing "transparency" and "legality" of the production process are accelerating. Therefore, changes in the management systems of fishery products entering the country are also needed. Accordingly, this study estimated the consumer value for risk management of IUU fishing, targeting major fish species imported to Korea, and derived the feasibility of introducing related policies. Design/methodology - This study used the choice experiment as an analysis model to estimate consumers' willingness to pay for the "possibility to check for IUU fishing." The choice experiment assumes that the value of a good or service is composed of separable attributes and that the sum of the part-worth of these individual attributes becomes the total value. In this study, respondents were presented with profiles comprising three attributes (country of origin, price, and possibility of checking IUU fishing) and the levels of frozen poulp squid, the subject of the analysis. The participants were asked to select their preferred profile. The marginal willingness to pay for each attribute was derived from the results of the respondents' choices using conditional logit model estimates. Findings - There is a marked difference in utility based on the preference of the country of origin of fishery products among consumers. In addition, the utility of fishery products that have undergone IUU fishing verification was observed to be higher, with the utility marked to be higher for lower prices. Originality/value - Estimating the policy value of the risk management in IUU fishing of imported fisheries products in this study is a novel attempt that has never been conducted before. Several studies have been conducted to assess the risk of IUU fishing associated with the import of fishery products internationally. However, such studies are yet to be conducted in Korea. Instead, policies and studies have focused on issues related to complying with trading partners' legal and transparent standards for exporting fishery products. This study should be the beginning of more in-depth empirical and theoretical explorations to establish order in the domestic seafood market and respond to changes in international regulations on IUU fishing.
Park, Jwa-Woo;Lee, Bum-Hee;Park, Seung-Hwan;Park, Su-Young;Jung, Chan-Wook;Ryu, Hyung-Gi;Kim, Ho-Shin
The Korean Journal of Nuclear Medicine Technology
/
v.18
no.1
/
pp.76-81
/
2014
Purpose: Diversity and the lachrymal duct deformities and the passage inside the nasal cavity except for anterior image such as epiphora happens during the test were able to express more precisely during the dacryoscintigraphy. Also, we thought about the necessity of a method to classify the passage into the naso-lachrymal duct from epiphora. Therefore, we are to find the validity of the method to obtain both oblique views except for anterior views. Materials and Methods: The targets of this research are 78 patients with epiphora due to the blockage at the lachrymal duct from January 2013 to August 2013. Average age was $56.96{\pm}13.36$. By using a micropipette, we dropped 1-2 drops of $^{99m}TcO4^-$ of 3.7 MBq (0.1 mCi) with $10{\mu}L$ of each drop into the inferior conjunctival fold, then we performed dynamic check for 20 minutes with 20 frames of each minute. In case of we checked the passage from both eyes to nasal cavity immediately after the dynamic check, we obtained oblique view immediately. If we didn't see the passage in either side of the orbit, we obtained oblique views of the orbit after checking the frontal film in 40 minutes. The instrument we used was Pin-hole Collimator with Gamma Camera(Siemens Orbiter, Hoffman Estates, IL, USA). Results: Among the 78 patients with dacryoscintigraphy, 35 patients were confirmed with passage into the nasal cavity from the anterior view. Among those 35 patients, 15 patients were confirmed with passage into the nasal cavity on both eyes, and it was able to observe better passage patterns through oblique view with a result of 8 on both eyes, 2 on left eye, and 1 on right eye. 20 patients had passage in left eye or right eye, among those patients 10 patients showed clear passage compared to the anterior view. 13 patients had possible passage, and 30 patients had no proof of motion of the tracer. To sum up, 21 patients (60%) among 35 patients showed clear pattern of passage with additional oblique views compared to anterior view. People responded obtaining oblique views though 5 points scale about the utility of passage identification helps make diagnoses the passage, passage delayed, and blockage of naso-lachrymal duct by showing the well-seen portions from anterior view. Also, when classifying passage to naso-lachrymal duct and flow to the skin, oblique views has higher chance of classification in case of epiphora (anterior:$4.14{\pm}0.3$, oblique:$4.55{\pm}0.4$). Conclusion: It is considered that if you obtain oblique views of the bilateral orbits in addition to anterior view during the dacryoscintigraphy, the ability of diagnose for reading will become higher because you will be able to see the areas that you could not observe from the anterior view so that you can see if it emitted after the naso-lachrymal duct and the flow of epiphora on the skin.
Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.
Regarding the [Government Organization Act; which is legislated on 19th November, 2014] Korea Coast Guard(KCG) has been re-organized and belong from Korea Coast Guard shall be established under the Minister of Oceans and Fisheries to Ministry of Public Safety and Security. Furthermore, National Police Agency(NPA) Commissioner has the right for administer duties concerning investigation and information by succession from Korea Coast Guard Commissioner. That means that main rule has been moved from prior KCG to Ministry of Public Safety and Security(MPSS) and NPA currently which is dual structure. Meanwhile, This kind of organization change has been effective to investigative agency which exert KCG's call of duty and causes needs of variety problems. In other words, There are quite huge changes such as KCG's reduction of their work, call of duty and re-organization regarding revised government organization act. However this change - including re-organization by government, was not able to take current MPSS's special features such as organization specialty and legal rights. It means, the current change has not been taken present law system CRIMINAL PROCEDURE LAW and there was no preparation to stable maritime police authority action as well. To sum up, this revised GOVERNMENT ORGANIZATION ACT is supposed to provide total, quick security service by establishing strong disasters and safety control tower. However they only contains few area such as organization revision regarding 'Sewol Ferry Disaster', they was not able to contain the other parts of Society. Therefore, in this article I would like to check the part of re-evaluation of current change made by KCC's organization revision. It is supposed to provide better legal stability by making clear of work area by government agencies who acts maritime police authority.
This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.
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