• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.7-10
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• 2000

Studies of prosody and sentence processing have demonstrated that prosodic phrasing can exhibit strong effects on processing decisions in English. In this paper, we tested Korean sentence fragments containing syntactically ambiguous Adj-N1-N2 strings in a cross-modal naming task. Four accentual phrasing patterns were tested: (a) the default phrasing pattern, in which each word forms an accentual phrase; (b) a phrasing biased toward N1 modification; (c) a phrasing biased toward complex-NP modification; and (d) a phrasing used with adjective focus. Patterns (b) and (c) are disambiguating phrasings; the other two are commonly found with both interpretations and are thus ambiguous. The results showed that the naming time of items produced in the prosody contradicting the semantic grouping is significantly longer than that produced in either default or supporting prosody, We claim that, as in English, prosodic information in Korean is parsed into a well-formed prosodic representation during the early stages of processing. The partially constructed prosodic representation produces incremental effects on syntactic and semantic processing decisions and is retained in memory to influence reanalysis decisions.

• Korean Journal of Biological Psychiatry
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• v.24 no.2
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• pp.68-74
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• 2017

Objectives It is well known that problem drinking is associated with alterations of brain structures and functions. Brain functions related to alcohol consumption can be determined by the resting state functional connectivity in various resting state networks (RSNs). This study aims to ascertain the alcohol effect on the structures forming predetermined RSNs by assessing their cortical thickness. Methods Twenty-six abstinent male patients with alcohol dependence and the same number of age-matched healthy control were recruited from an inpatient mental hospital and community. All participants underwent a 3T MRI scan. Averaged cortical thickness of areas constituting 7 RSNs were determined by using FreeSurfer with Yeo atlas derived from cortical parcellation estimated by intrinsic functional connectivity. Results There were significant group differences of mean cortical thicknesses (Cohen's d, corrected p) in ventral attention (1.01, < 0.01), dorsal attention (0.93, 0.01), somatomotor (0.90, 0.01), and visual (0.88, 0.02) networks. We could not find significant group differences in the default mode network. There were also significant group differences of gray matter volumes corrected by head size across the all networks. However, there were no group differences of surface area in each network. Conclusions There are differences in degree and pattern of structural recovery after abstinence across areas forming RSNs. Considering the previous observation that group differences of functional connectivity were significant only in networks related to task-positive networks such as dorsal attention and cognitive control networks, we can explain recovery pattern of cognition and emotion related to the default mode network and the mechanisms for craving and relapse associated with task-positive networks.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.3
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• pp.563-575
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• 2024

This study analyzed 2D bodice sloper changes according to combinations of the lateral neck and shoulder points of a 3D mannequin's shoulder lines. The relationship between the 3D shape and 2D pattern was analyzed. The shoulder line was set to a default of 1cm in front of or behind the lateral neck point, 1cm in front or behind the lateral shoulder point and 1cm vertically above the lateral neck or shoulder point. When the lateral neck point was moved backward, the front neck depth, front and back shoulder height, and shoulder length in the 3D shape increased, whereas the back neck's depth and width decreased. In the 2D pattern, the back shoulder height decreased. As the lateral shoulder point moved backward, all items of the 3D shape showed little change. However, the front shoulder height for the 2D pattern decreased. Consequently, the back shoulder height increased, and the lateral neck point was raised vertically by 1cm. Meanwhile, only the back neck depth and shoulder length decreased while all other items increased; however, in the 2D pattern, the front neck width and shoulder line showed no notable change. The shoulder point was raised vertically by 1cm, and the front and back shoulder heights of the 3D shape and 2D pattern were decreased.

• Convergence Security Journal
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• v.15 no.6_2
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• pp.3-10
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• 2015

Recent massive data breaches or major security incidents show that threats posed by insiders have greatly increased over time. Especially, authorized insiders can cause more serious problems than external hackers can. Therefore there is a growing need to introduce a system that can monitor the insider threats in real time and prevent data breaches or security incidents in early-stage. In this paper, we propose a EITMS(Enterprise Insider-Threats Management System). EITMS detects the abnormal behaviors of authorized insiders based on the normal patterns made from their roles, duties and private activities. And, in order to prevent breaches and incidents in early-stage, a scoring system that can visualize the insider threats is also included.

• Journal of Korean Library and Information Science Society
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• v.21
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• pp.253-289
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• 1994

The purpose of this study is about the search pattern of LINNET (Library Information Network System) OPAC users by transaction log, maintained by POSTECH(Pohang University of Science and Technology) Central Library, to provide feedback information of OPAC system design. The results of this study are as follows. First, for the period of this analysis, there were totally 11, 218 log-ins, 40, 627 transaction logs and 3.62 retrievals per a log-in. Title keyword was the most frequently used, but accession number, bibliographic control number or call number was very infrequently used. Second, 47.02% of OPAC, searches resulted in zero retrievals. Bibliographic control number was the least successful search. User displayed 2.01% full information and 64.27% local information per full information. Third, special or advanced retrieval features are very infrequently used. Only 22.67% of the searches used right truncation and 0.71% used the qualifier. Only 1 boolean operator was used in every 22 retrievals. The most frequently used operator is 'and (&)' with title keywords. But 'bibliographical control number (N) and accessionnumber (R) are not used at all with any operators. The causes of search failure are as follows. 1. The item was not used in the database. (15, 764 times : 79.42%). 2. The wrong search key was used. (3, 761 times : 18.95%) 3. The senseless string (garbage) was entered. (324 times : 1.63%) On the basis of these results, some recommendations are suggested to improve the search success rate as follows. First, a n.0, ppropriate user education and online help function let users retrieve LINNET OPAC more efficiently. Second, several corrections of retrieval software will decrease the search failure rate. Third, system offers right truncation by default to every search term. This methods will increase success rate but should considered carefully. By a n.0, pplying this method, the number of hit can be overnumbered, and system overhead can be occurred. Fourth, system offers special boolean operator by default to every keyword retrieval when user enters more than two words at a time. Fifth, system assists searchers to overcome the wrong typing of selecting key by automatic korean/english mode change.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.3
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• pp.141-149
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• 2008

Most functional programming languages allows programmers to write ambiguous rules, under the strategy that pattern-matching will be performed in a direction of 'from top to bottom' way. While providing programmers with convenience and intuitive understanding of defining default rules, such ambiguous rules may make the semantics of functional languages unclear. More specifically, it may fail to apply the equational reasoning, one of most significant advantage of functional programming, and may cause to obscure finding a formal way of translating functional languages into the ${\lambda}$-calculus; as a result, we only get an ad hoc translation. In this paper, we associate with separability of term rewriting systems, holding purely-declarative property, pattern-matching semantics of lazy functional languages. Separability can serve a formalism for translating lazy functional languages into the ${\lambda}$-calculus.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.9
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• pp.20-27
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• 2014

The power consumption pattern of high-speed railway has rarely during night time. But, during service time, the power is consumed irregularly related to train operation. Especially certain unusual about 1-2 days of service time interval to indicate the power consumption is rapidly growing phenomenon, which causes the capacity of the power contract is the annual electricity bill to rise rapidly as the cause. Normally, amount of peak power consumption bill rate at railway substation is over 20% of total electrical bill. Therefore, high-speed railway substation is expected to be considerably larger savings by reducing the peak power of the default charge(demand power).

• Atmosphere
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• v.25 no.1
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• pp.1-18
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• 2015

The most objective way to overcome the limitation of numerical weather prediction model is to represent the uncertainty of prediction by introducing probabilistic forecast. The uncertainty of the numerical weather prediction system developed due to the parameterization of unresolved scale motions and the energy losses from the sub-scale physical processes. In this study, we focused on the growth of model errors. We performed ensemble forecast to represent model uncertainty. By employing the multi-physics scheme (PHYS) and the stochastic kinetic energy backscatter scheme (SKEBS) in simulating typhoon Rusa (2002), we assessed the performance level of the two schemes. The both schemes produced better results than the control run did in the ensemble mean forecast of the track. The results using PHYS improved by 28% and those based on SKEBS did by 7%. Both of the ensemble mean errors of the both schemes increased rapidly at the forecast time 84 hrs. The both ensemble spreads increased gradually during integration. The results based on SKEBS represented model errors very well during the forecast time of 96 hrs. After the period, it produced an under-dispersive pattern. The simulation based on PHYS overestimated the ensemble mean error during integration and represented the real situation well at the forecast time of 120 hrs. The displacement speed of the typhoon based on PHYS was closest to the best track, especially after landfall. In the sensitivity tests of the model uncertainty of SKEBS, ensemble mean forecast was sensitive to the physics parameterization. By adjusting the forcing parameter of SKEBS, the default experiment improved in the ensemble spread, ensemble mean errors, and moving speed.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.13
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• pp.69-81
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• 2000

Under the co-sponsorship of UNIDROIT and I.C.A.O., a preliminary draft Convention on International Interests in Mobile Equipment and a preliminary draft Protocol on Matters Specific to Aircraft Equipment has been prepared. The purpose of the Convention is to provide for the creation and effect of a new international interest in mobile equipment. The Convention's approach is quite novel in that it purports to create an international interest based upon the convention itself. The Convention is intended to be supplemented by Protocols, each of is intended to provide equipment-specific rules necessary to adapt the rules of the Convention to fit the special pattern of financing for different categories of equipment. To date, two sessions of governmental experts were held in Rome and Montreal. Korean delegations attended the two sessions. One of the members of the Korean delegation published a report on the first session. He expressed his objection to the so called self-help remedy contemplated by the current preliminary draft of the Convention which enables the holder of a security interest to repossess and dispose of the subject of the security interest by private sale rather than public auction on the occurrence of an event of default of the debtor. His view is based upon his understanding that under Korean law, the only remedy available to the holder of a security interest in mobile equipment, such as an airplane, is to apply to the competent court for a public auction. In my view, his understanding is not quite correct and is inconsistent with the current practice in Korea. Under Korean law, the parties' agreement for private sale is in principle valid unless there is an interested party who has acquired a security interest after the creation of the prior security interest or a creditor who has caused the subject of the security interest to be attached by a competent court. In this article, I discuss the current Korean law and practice relating to the enforcement of security interests by private sale in more detail.