• Journal of the Korean Society of Safety
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• v.11 no.2
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• pp.150-159
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• 1996

In this paper, an A-team(Asynchronous Team ) based approach for Reactive power and volage control considering static security assessment in a power system with infrastructural deficiencies is proposed. Reactive power and voltage control problem is the one of optimally establishing voltage level given several constraints such as reactive generation, voltage magnitude, line flow, and other switchable reactive power sources. It can be formulated as a mixed-integer linear programming(MILP) problem without deteriorating of solution accuracy to a certain extent. The security assessment is to estimate the relative robustness of the system in Its present state through the evaluation of data provided by security monitoring. Deterministic approach based on AC load flow calculations is adopted to assess the system security, especially voltage security. A security metric, as a standard of measurement for power system security, producting a set of discrete values rather than binary values, is employed. In order to analyze the above two problems, reactive power/voltage control problem and static security assessment problem, in an integrated fashion for real-time operations, a new organizational structure, called an A-team, is adopted. An A-team is an organization for agents which ale all autonomeus, work in parallel and communicate asynchronously, which is well-suited to the development of computer-based, multi-agent systems for operations. This A-team based approach, although it is still in the beginning stage, also has potential for handling other difficult power system problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.300-309
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• 2016

Curved beams are increasingly used in buildings, vehicles, ships, and aircraft, which has resulted in considerable effort towards developing an accurate method for analyzing the dynamic behavior of such structures. The stability behavior of elastic curved beams has been the subject of many investigations. Solutions to the relevant differential equations have traditionally been obtained by the standard finite difference or finite element methods. However, these techniques require a great deal of computer time for a large number of discrete nodes with conditions of complex geometry and loading. One efficient procedure for the solution of partial differential equations is the differential quadrature method (DQM). This method has been applied to many cases to overcome the difficulties of complex algorithms and high storage requirements for complex geometry and loading conditions. Out-of-plane buckling of curved beams with rotatory inertia were analyzed using DQM under uniformly distributed radial loads. Critical loads were calculated for the member with various parameter ratios, boundary conditions, and opening angles. The results were compared with exact results from other methods for available cases. The DQM used only a limited number of grid points and shows very good agreement with the exact results (less than 0.3% error). New results according to diverse variation are also suggested, which show important roles in the buckling behavior of curved beams and can be used for comparisons with other numerical solutions or experimental test data.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.55-64
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• 2013

Due to the popularization of digital high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy for anyone to make a high-quality counterfeit money. However, the probability of detecting a counterfeit money to the general public is extremely low. In this paper, we propose a counterfeit money detection algorithm using a general purpose scanner. This algorithm determines counterfeit money based on the different features in the printing process. After the non-local mean value is used to analyze the noises from each money, we extract statistical features from these noises by calculating a gray level co-occurrence matrix. Then, these features are applied to train and test the support vector machine classifier for identifying either original or counterfeit money. In the experiment, we use total 324 images of original money and counterfeit money. Also, we compare with noise features from previous researches using wiener filter and discrete wavelet transform. The accuracy of the algorithm for identifying counterfeit money was over 94%. Also, the accuracy for identifying the printing source was over 93%. The presented algorithm performs better than previous researches.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.113-129
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• 1999

It is widely recognized that the value of travel time (VOT) plays an important role both in choosing the transportation alternatives on an individual level, and in analyzing and evaluating transportation plans and other public policy makings on a collective level. There is, however, a great deal of difficulties to correctly estimate the VOT. In addition, although there are lots of methods to estimate the VOT so for, not many recommendations have been presented to reflect the localities associated with the VOT derivation in Korea. This study aims at deriving the VOT for different trip purposes and travel modes with their significances tested. To accomplish this purposes, a logit-based travel mode choice model based on revealed preference (RP) data has been formulated, calibrated using the discrete choice model of LIMDEP package for various trip purpose models. For each trip purpose and travel mode, the VOT has been calculated along with the significance testing of the derived VOTs. From the results given in this research, the VOTs for different purposes and modes are identified different, and they are statistically significant. The updated results here in this paper may be a yardstick in evaluating the transportation plans and policies by providing more detailed VOT information for different categories, especially in urban context.

• Korean Journal of Social Welfare Studies
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• v.40 no.3
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• pp.377-406
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• 2009

This study used laten class growth analysis to identify discrete developmental patterns of delinquent behaviors in adolescence. This present article also examined associations among these trajectories to determine how the development of delinquent behaviors relates to protective and risk factors, which include parental monitoring, attachment with parent, association with deviant peers, self-control, and negative stigma from others. Four-wave panel data from a Korea Youth Panel Study were used for the latent class growth model analysis. The sample consisted of 3,446 adolescents who were assessed at 4 measurement waves with approximately 1-year interval. Four trajectories of delinquent behaviors emerged: delinquency persistence, delinquency increaser, delinquency decreaser, normative group(almost no delinquent behaviors). Association with deviant peers had the most proximal strong influence on the probability of being in the delinquency increaser and delinquency persistence group compared, noed to the normative group. Parental monitoring, self-efficacy and negative stigma also differentiated the four delinquent behavior trajectories from one another after controllig for socio-demographic variables. The study suggested that there is a significant heterogeneity in the timing and change rate of delinquency progression. Adolescent delinquency prevention and intervention programs will need to consider this heterogeneity and enhance attention to protective and risk factors depending on the subpopulation.

• International Area Studies Review
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• v.12 no.3
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• pp.321-339
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• 2008

The purpose of this study to the analyze characteristics and purchasing activities of consumers by using the Multinomial Logit model, which is a well-known discrete selection model to explain and forecast consumers' selection activities(patterns). The study aims to determine the state of competition between National Brand and Private Band and how some demographic characters and marketing variables influence consumers' brand selections within the facial tissue market. Our analysis process includes reorganization of panel data(individuals' purchasing record at each point) to fit the purpose of our study as well as analysis of probability and influencing factors of consumers' brand selection at each point of purchases. The result showed that consumers at higher age and with higher income hold better probability to purchase National Brand. Likewise, locations also had considerable effect on selecting brand, and Private Brand was preferred in department store and discount stores. On the other hand, consumers loyal to National Brand reported higher probability to purchase if the product prices were higher while Private Brand buyers were more promoted the purchase under price discount.

• Asian Spine Journal
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• v.12 no.6
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• pp.1043-1052
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• 2018

Study Design: Level III retrospective cross-sectional study. Purpose: To define and characterize the presentation, symptom duration, and patient/surgical risk factors associated with 'post-decompressive neuropathy (PDN).' Overview of Literature: PDN is characterized by lower extremity radicular pain that is 'different' from pre-surgical radiculopathy or claudication pain. Although it is a common constellation of postoperative symptoms, PDN is incompletely characterized and poorly understood. We hypothesize that PDN is caused by an intraoperative neuropraxic event and may develop early (within 30 days following the procedure) or late (after 30 days following the procedure) within the postoperative period. Methods: Patients who consented to undergo lumbar laminectomy with or without an instrumented fusion for degenerative lumbar spine disease were followed up prospectively from July 2013 to December 2014. Relevant data were extracted from the charts of the eligible patients. Patient demographics and surgical factors were identified. Patients completed postoperative questionnaires 3 weeks, 3 months, 6 months, and 1 year postoperatively. Questions were designed to characterize the postoperative pain that differed from preoperative pain. A diagnosis of PDN was established if the patient exhibited the following characteristics: pain different from preoperative pain, leg pain worse than back pain, a non-dermatomal pain pattern, and nocturnal pain that often disrupted sleep. A Visual Analog Scale was used to monitor the pain, and patients documented the effectiveness of the prescribed pain management modalities. Patients for whom more than one follow-up survey was missed were excluded from analysis. Results: Of the 164 eligible patients, 118 (72.0%) completed at least one follow-up survey at each time interval. Of these eligible patients, 91 (77.1%) described symptoms consistent with PDN. Additionally, 75 patients (82.4%) described early-onset symptoms, whereas 16 reported symptoms consistent with late-onset PDN. Significantly more female patients reported PDN symptoms (87% vs. 69%, p=0.03). Patients with both early and late development of PDN described their leg pain as an intermittent, constant, burning, sharp/stabbing, or dull ache. Early PDN was categorized more commonly as a dull ache than late-onset PDN (60% vs. 31%, p=0.052); however, the difference did not reach statistical significance. Opioids were significantly more effective for patients with early-onset PDN than for those with late-onset PDN (85% vs. 44%, p=0.001). Gabapentin was most commonly prescribed to patients who cited no resolution of symptoms (70% vs. 31%, p=0.003). Time to symptom resolution ranged from within 1 month to 1 year. Patients' symptoms were considered unresolved if symptoms persisted for more than 1 year postoperatively. In total, 81% of the patients with early-onset PDN reported complete symptom resolution 1 year postoperatively compared with 63% of patients with late-onset PDN (p=0.11). Conclusions: PDN is a discrete postoperative pain phenomenon that occurred in 77% of the patients who underwent lumbar laminectomy with or without instrumented fusion. Attention must be paid to the constellation and natural history of symptoms unique to PDN to effectively manage a self-limiting postoperative issue.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.25-36
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• 2020

An increasing frequency and intensity of natural disasters have been observed due to climate change. To better prepare for these, the MOIS (ministry of the interior and safety) announced a comprehensive plan for minimizing damages associated with natural disasters, including drought and heavy snowfall. The spatial-temporal pattern of snowfall is greatly influenced by temperature and geographical features. Heavy snowfalls are often observed in Gangwon-do, surrounded by mountains, whereas less snowfall is dominant in the southern part of the country due to relatively high temperatures. Thus, snow depth data often contains zeros that can lead to difficulties in the selection of probability distribution and estimation of the parameters. A generalized mixture distribution approach to a maximum snow depth series over the southern part of Korea (i.e., Changwon, Tongyeoung, Jinju weather stations) are located is proposed to better estimate a threshold (𝛿) classifying discrete and continuous distribution parts. The model parameters, including the threshold in the mixture model, are effectively estimated within a Bayesian modeling framework, and the uncertainty associated with the parameters is also provided. Comparing to the Daegwallyeong weather station, It was found that the proposed model is more effective for the regions in which less snow depth is observed.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1037-1051
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• 2021

Biochemical oxygen demand (BOD) concentration, one of important water quality indicators, is treated as the measuring item for the ecological chapter in lakes and rivers. This investigation employed novel two-stage hybrid paradigm (i.e., wavelet-based gated recurrent unit, wavelet-based generalized regression neural networks, and wavelet-based random forests) to predict BOD concentration in the Dosan and Hwangji stations, South Korea. These models were assessed with the corresponding independent models (i.e., gated recurrent unit, generalized regression neural networks, and random forests). Diverse water quality and quantity indicators were implemented for developing independent and two-stage hybrid models based on several input combinations (i.e., Divisions 1-5). The addressed models were evaluated using three statistical indices including the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and correlation coefficient (CC). It can be found from results that the two-stage hybrid models cannot always enhance the predictive precision of independent models confidently. Results showed that the DWT-RF5 (RMSE = 0.108 mg/L) model provided more accurate prediction of BOD concentration compared to other optimal models in Dosan station, and the DWT-GRNN4 (RMSE = 0.132 mg/L) model was the best for predicting BOD concentration in Hwangji station, South Korea.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.115-132
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• 2008

Metal industry is one of the most representative heavy industries and the median sales volume of steel and nonferrous metal companies is over one billion dollars in the case America [Forbes 2006]. As seen in the recent business market situation, an increasing number of industrial manufacturers and suppliers are moving from adversarial to cooperative exchange attitudes that support the long-term relationships with their customers. This article presents the results of an empirical study of the antecedent factors of business relationships in metal industry of the United States. Commitment has been reviewed as a significant and critical variable in research on inter-organizational relationships (Hong et al. 2007, Kim et al. 2007). The future stability of any buyer-seller relationship depends upon the commitment made by the interactants to their relationship. Commitment, according to Dwyer et al. [1987], refers to "an implicit or explicit pledge of relational continuity between exchange partners" and they consider commitment to be the most advanced phase of buyer-seller exchange relationship. Bonds are made because the members need their partners in order to do something and this integration on a task basis can be either symbiotic or cooperative (Svensson 2008). To the extent that members seek the same or mutually supporting ends, there will be strong bonds among them. In other words, the principle that affects the strength of bonds is 'economy of decision making' [Turner 1970]. These bonds provide an important idea to study the causes of business long-term relationships in a sense that organizations can be mutually bonded by a common interest in the economic matters. Recently, the framework of structural bonding has been used to study the buyer-seller relationships in industrial marketing [Han and Sung 2008, Williams et al. 1998, Wilson 1995] in that this structural bonding is a crucial part of the theoretical justification for distinguishing discrete transactions from ongoing long-term relationships. The major antecedent factors of buyer commitment such as technology, CLalt, transaction-specific assets, and importance were identified and explored from the perspective of structural bonding. Research hypotheses were developed and tested by using survey data from the middle managers in the metal industry. H1: Level of technology of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H2: Comparison level of alternatives is negatively related to the level of structural bonding between the buyer and the seller. H3: Amount of the transaction-specific assets is positively related to the level of structural bonding between the buyer and the seller. H4: Importance of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H5: Level of structural bonding is positively related to the level of commitment to the relationship. To examine the major antecedent factors of industrial buyer's structural bonding and long-term relationship, questionnaire was prepared, mailed out to the sample of 400 purchasing managers of the US metal industry (SIC codes 33 and 34). After a follow-up request, 139 informants returnedthe questionnaires, resulting in a response rate of 35 percent. 134 responses were used in the final analysis after dropping 5 incomplete questionnaires. All measures were analyzed for reliability and validity following the guidelines offered by Churchill [1979] and Anderson and Gerbing [1988]., the results of fitting the model to the data indicated that the hypothesized model provides a good fit to the data. Goodness-of-fit index (GFI = 0.94) and other indices ( chi-square = 78.02 with p-value = 0.13, Adjusted GFI = 0.90, Normed Fit Index = 0.92) indicated that a major proportion of variances and covariances in the data was accounted for by the model as a whole, and all the parameter estimates showed statistical significance as evidenced by large t-values. All the factor loadings were significantly different from zero. On these grounds we judged the hypothesized model to be a reasonable representation of the data. The results from the present study suggest several implications for buyer-seller relationships. Theoretically, we attempted to conceptualize the antecedent factors of buyer-seller long-term relationships from the perspective of structural bondingin metal industry. The four underlying determinants (i.e. technology, CLalt, transaction-specific assets, and importance) of structural bonding are very critical variables of buyer-seller long-term business relationships. Our model of structural bonding makes an attempt to systematically examine the relationship between the antecedent factors of structural bonding and long-term commitment. Managerially, this research provides industrial purchasing managers with a good framework to assess the interaction processes with their partners and, ability to position their business relationships from the perspective of structural bonding. In other words, based on those underlying variables, industrial purchasing managers can determine the strength of the company's relationships with the key suppliers and its state of preparation to be a successful partner with those suppliers. Both the supplying and customer companies can also benefit by using the concept of 'structural bonding' and evaluating their relationships with key business partners from the structural point of view. In general, the results indicate that structural bonding gives a critical impact on the level of relationship commitment. Managerial implications and limitations of the study are also discussed.