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Predicting link of R&D network to stimulate collaboration among education, industry, and research (산학연 협업 활성화를 위한 R&D 네트워크 연결 예측 연구)

  • Park, Mi-yeon;Lee, Sangheon;Jin, Guocheng;Shen, Hongme;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.21 no.3
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    • pp.37-52
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    • 2015
  • The recent global trends display expansion and growing solidity in both cooperative collaboration between industry, education, and research and R&D network systems. A greater support for the network and cooperative research sector would open greater possibilities for the evolution of new scholar and industrial fields and the development of new theories evoked from synergized educational research. Similarly, the national need for a strategy that can most efficiently and effectively support R&D network that are established through the government's R&D project research is on the rise. Despite the growing urgency, due to the habitual dependency on simple individual personal information data regarding R&D industry participants and generalized statistical data references, the policies concerning network system are disappointing and inadequate. Accordingly, analyses of the relationships involved for each subject who is participating in the R&D industry was conducted and on the foundation of an educational-industrial-research network system, possible changes within and of the network that may arise were predicted. To predict the R&D network transitions, Common Neighbor and Jaccard's Coefficient models were designated as the basic foundational models, upon which a new prediction model was proposed to address the limitations of the two aforementioned former models and to increase the accuracy of Link Prediction, with which a comparative analysis was made between the two models. Through the effective predictions regarding R&D network changes and transitions, such study result serves as a stepping-stone for an establishment of a prospective strategy that supports a desirable educational-industrial-research network and proposes a measure to promote the national policy to one that can effectively and efficiently sponsor integrated R&D industries. Though both weighted applications of Common Neighbor and Jaccard's Coefficient models provided positive outcomes, improved accuracy was comparatively more prevalent in the weighted Common Neighbor. An un-weighted Common Neighbor model predicted 650 out of 4,136 whereas a weighted Common Neighbor model predicted 50 more results at a total of 700 predictions. While the Jaccard's model demonstrated slight performance improvements in numeric terms, the differences were found to be insignificant.

The Family Caregivers' Stress Pathways by Types of Long Term Care Services for the Elderly (장기요양보호서비스 유형별 가족 부양스트레스 경로)

  • Park, Chang-Je;Lee, Sung-Jin
    • 한국노년학
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    • v.31 no.3
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    • pp.831-848
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    • 2011
  • The purpose of this study is to analyse the family caregivers' stress pathways by types of long term care services for the elderly, and then to discuss the findings of analysis. For this research, primary caregivers that provide care the elderly requiring long term care services sanctioned by National Health Insurance Corporation were drawn and surveyed. Among collected data, data for 258 primary caregivers by type of long term care services were used for this study. The results of this study can be summarized as follows. First, on average, the elders that utilize care service in institutions for the elderly were higher proportion of women, older, higher rate of bereavement, more children than the elders that utilize in-home care service, but some cases were vice-versa. Second, the elders that utilize care service in institutions more ADL dependency, higher proportion of severe dementia or severe stroke, higher care rank by National Health Insurance Corporation than the elders that utilize in-home care service on average. Third, primary caregivers with elders that utilize in-home care service were higher proportion of women, older, lower education level, higher rate of spouse and daughter-in-law in relationship with care recipient, less health, lower income than primary caregivers with elders that utilize care service in institutions. Fourth, subjective indicators representing caregivers' reactions to caregiving for the elderly significantly impact on caregivers' stress(ie, depression), and pathway of caregivers' stress are differentiated by type of long term care services. Fifth, stressors that have direct impacts on depression as caregiving family are differentiated by type of long term care services. Therefore, policies or programs to reduce negative mental health or stress of caregivig families should be designed differently by reflecting pathway of various stressors and stress by use types of long term care services for the elderly.

Korean Sentence Generation Using Phoneme-Level LSTM Language Model (한국어 음소 단위 LSTM 언어모델을 이용한 문장 생성)

  • Ahn, SungMahn;Chung, Yeojin;Lee, Jaejoon;Yang, Jiheon
    • Journal of Intelligence and Information Systems
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    • v.23 no.2
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    • pp.71-88
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    • 2017
  • Language models were originally developed for speech recognition and language processing. Using a set of example sentences, a language model predicts the next word or character based on sequential input data. N-gram models have been widely used but this model cannot model the correlation between the input units efficiently since it is a probabilistic model which are based on the frequency of each unit in the training set. Recently, as the deep learning algorithm has been developed, a recurrent neural network (RNN) model and a long short-term memory (LSTM) model have been widely used for the neural language model (Ahn, 2016; Kim et al., 2016; Lee et al., 2016). These models can reflect dependency between the objects that are entered sequentially into the model (Gers and Schmidhuber, 2001; Mikolov et al., 2010; Sundermeyer et al., 2012). In order to learning the neural language model, texts need to be decomposed into words or morphemes. Since, however, a training set of sentences includes a huge number of words or morphemes in general, the size of dictionary is very large and so it increases model complexity. In addition, word-level or morpheme-level models are able to generate vocabularies only which are contained in the training set. Furthermore, with highly morphological languages such as Turkish, Hungarian, Russian, Finnish or Korean, morpheme analyzers have more chance to cause errors in decomposition process (Lankinen et al., 2016). Therefore, this paper proposes a phoneme-level language model for Korean language based on LSTM models. A phoneme such as a vowel or a consonant is the smallest unit that comprises Korean texts. We construct the language model using three or four LSTM layers. Each model was trained using Stochastic Gradient Algorithm and more advanced optimization algorithms such as Adagrad, RMSprop, Adadelta, Adam, Adamax, and Nadam. Simulation study was done with Old Testament texts using a deep learning package Keras based the Theano. After pre-processing the texts, the dataset included 74 of unique characters including vowels, consonants, and punctuation marks. Then we constructed an input vector with 20 consecutive characters and an output with a following 21st character. Finally, total 1,023,411 sets of input-output vectors were included in the dataset and we divided them into training, validation, testsets with proportion 70:15:15. All the simulation were conducted on a system equipped with an Intel Xeon CPU (16 cores) and a NVIDIA GeForce GTX 1080 GPU. We compared the loss function evaluated for the validation set, the perplexity evaluated for the test set, and the time to be taken for training each model. As a result, all the optimization algorithms but the stochastic gradient algorithm showed similar validation loss and perplexity, which are clearly superior to those of the stochastic gradient algorithm. The stochastic gradient algorithm took the longest time to be trained for both 3- and 4-LSTM models. On average, the 4-LSTM layer model took 69% longer training time than the 3-LSTM layer model. However, the validation loss and perplexity were not improved significantly or became even worse for specific conditions. On the other hand, when comparing the automatically generated sentences, the 4-LSTM layer model tended to generate the sentences which are closer to the natural language than the 3-LSTM model. Although there were slight differences in the completeness of the generated sentences between the models, the sentence generation performance was quite satisfactory in any simulation conditions: they generated only legitimate Korean letters and the use of postposition and the conjugation of verbs were almost perfect in the sense of grammar. The results of this study are expected to be widely used for the processing of Korean language in the field of language processing and speech recognition, which are the basis of artificial intelligence systems.

Discovering Promising Convergence Technologies Using Network Analysis of Maturity and Dependency of Technology (기술 성숙도 및 의존도의 네트워크 분석을 통한 유망 융합 기술 발굴 방법론)

  • Choi, Hochang;Kwahk, Kee-Young;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.101-124
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    • 2018
  • Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

Critical Success Factor of Noble Payment System: Multiple Case Studies (새로운 결제서비스의 성공요인: 다중사례연구)

  • Park, Arum;Lee, Kyoung Jun
    • Journal of Intelligence and Information Systems
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    • v.20 no.4
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    • pp.59-87
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    • 2014
  • In MIS field, the researches on payment services are focused on adoption factors of payment service using behavior theories such as TRA(Theory of Reasoned Action), TAM(Technology Acceptance Model), and TPB (Theory of Planned Behavior). The previous researches presented various adoption factors according to types of payment service, nations, culture and so on even though adoption factors of identical payment service were presented differently by researchers. The payment service industry relatively has strong path dependency to the existing payment methods so that the research results on the identical payment service are different due to payment culture of nation. This paper aims to suggest a successful adoption factor of noble payment service regardless of nation's culture and characteristics of payment and prove it. In previous researches, common adoption factors of payment service are convenience, ease of use, security, convenience, speed etc. But real cases prove the fact that adoption factors that the previous researches present are not always critical to success to penetrate a market. For example, PayByPhone, NFC based parking payment service, successfully has penetrated to early market and grown. In contrast, Google Wallet service failed to be adopted to users despite NFC based payment method which provides convenience, security, ease of use. As shown in upper case, there remains an unexplained aspect. Therefore, the present research question emerged from the question: "What is the more essential and fundamental factor that should takes precedence over factors such as provides convenience, security, ease of use for successful penetration to market". With these cases, this paper analyzes four cases predicted on the following hypothesis and demonstrates it. "To successfully penetrate a market and sustainably grow, new payment service should find non-customer of the existing payment service and provide noble payment method so that they can use payment method". We give plausible explanations for the hypothesis using multiple case studies. Diners club, Danal, PayPal, Square were selected as a typical and successful cases in each category of payment service. The discussion on cases is primarily non-customer analysis that noble payment service targets on to find the most crucial factor in the early market, we does not attempt to consider factors for business growth. We clarified three-tier non-customer of the payment method that new payment service targets on and elaborated how new payment service satisfy them. In case of credit card, this payment service target first tier of non-customer who can't pay for because they don't have any cash temporarily but they have regular income. So credit card provides an opportunity which they can do economic activities by delaying the date of payment. In a result of wireless phone payment's case study, this service targets on second of non-customer who can't use online payment because they concern about security or have to take a complex process and learn how to use online payment method. Therefore, wireless phone payment provides very convenient payment method. Especially, it made group of young pay for a little money without a credit card. Case study result of PayPal, online payment service, shows that it targets on second tier of non-customer who reject to use online payment service because of concern about sensitive information leaks such as passwords and credit card details. Accordingly, PayPal service allows users to pay online without a provision of sensitive information. Final Square case result, Mobile POS -based payment service, also shows that it targets on second tier of non-customer who can't individually transact offline because of cash's shortness. Hence, Square provides dongle which function as POS by putting dongle in earphone terminal. As a result, four cases made non-customer their customer so that they could penetrate early market and had been extended their market share. Consequently, all cases supported the hypothesis and it is highly probable according to 'analytic generation' that case study methodology suggests. We present for judging the quality of research designs the following. Construct validity, internal validity, external validity, reliability are common to all social science methods, these have been summarized in numerous textbooks(Yin, 2014). In case study methodology, these also have served as a framework for assessing a large group of case studies (Gibbert, Ruigrok & Wicki, 2008). Construct validity is to identify correct operational measures for the concepts being studied. To satisfy construct validity, we use multiple sources of evidence such as the academic journals, magazine and articles etc. Internal validity is to seek to establish a causal relationship, whereby certain conditions are believed to lead to other conditions, as distinguished from spurious relationships. To satisfy internal validity, we do explanation building through four cases analysis. External validity is to define the domain to which a study's findings can be generalized. To satisfy this, replication logic in multiple case studies is used. Reliability is to demonstrate that the operations of a study -such as the data collection procedures- can be repeated, with the same results. To satisfy this, we use case study protocol. In Korea, the competition among stakeholders over mobile payment industry is intensifying. Not only main three Telecom Companies but also Smartphone companies and service provider like KakaoTalk announced that they would enter into mobile payment industry. Mobile payment industry is getting competitive. But it doesn't still have momentum effect notwithstanding positive presumptions that will grow very fast. Mobile payment services are categorized into various technology based payment service such as IC mobile card and Application payment service of cloud based, NFC, sound wave, BLE(Bluetooth Low Energy), Biometric recognition technology etc. Especially, mobile payment service is discontinuous innovations that users should change their behavior and noble infrastructure should be installed. These require users to learn how to use it and cause infra-installation cost to shopkeepers. Additionally, payment industry has the strong path dependency. In spite of these obstacles, mobile payment service which should provide dramatically improved value as a products and service of discontinuous innovations is focusing on convenience and security, convenience and so on. We suggest the following to success mobile payment service. First, non-customers of the existing payment service need to be identified. Second, needs of them should be taken. Then, noble payment service provides non-customer who can't pay by the previous payment method to payment method. In conclusion, mobile payment service can create new market and will result in extension of payment market.

Suicide Ideation and the Related Factors among Korean Adults by Gender (한국 성인의 성별 자살생각 관련 요인 분석)

  • Park, Eunok
    • Journal of agricultural medicine and community health
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    • v.39 no.3
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    • pp.161-175
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    • 2014
  • Objectives: This study investigates the prevalence of suicide ideation and its the related factors by gender among Korean adults. Methods: National cross-sectional data from the database of the first and second year of 5th Korean National Health and Nutritional Examination Survey (KNHANES V-1, V-2) were used for this study. 13,165 adults (20 years) were included in this analysis. Results: The prevalence of suicide ideation was 9.8% for men, 18.9% for women. Renal failure, depression, melancholy, stress, perceived health status, and smoking were significant risk factors among both men and women for suicide ideation. Divorced, separated or widowed of marital status and severe physical activity were related factors of suicide ideation for men. Low educational attainment, and alcohol dependency were associated factors of suicide ideation for women. Conclusions: There was gender difference of prevalence and risk factors of suicide ideation. These gender differences should be considered for planning and implementing suicide prevention program.

COMORBIDITY AND RISK FACTORS ASSOCIATED WITH CHILDREN WHO HAVE THE SYMPTOMS OF OPPOSITIONAL DEFIANT DISORDER - COMMUNITY BASED STUDY - (반항성 도전 장애 아동과 연관된 공존 증상 및 위험 요인에 관한 연구 - 지역사회 연구 -)

  • Kim Boong-Nyun;Jung Kwang-Mo;Cho Soo Churl;Hong Kang-E
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • v.16 no.1
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    • pp.79-89
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    • 2005
  • Objectives : To acquire an improved understanding of oppositional defiant disorder, we evaluated the characteristics of children who have the symptoms of ODD in community sample. Methods : 1200 children from an elementary school in Bucheon (an urban community near Seoul) were recruited by randomized sampling method. By Disruptive Behavior Disorder Scale according to DSM-III-R & DSM-IV, we evaluated the symptoms of ODD and selected subjects with ODD. Psychiatric comorbidity, character trait were compared in subjects with ODD and comparison group. Also we examined the association between prenatal/perinatal risk factors, family functions and the symptoms of ODD. Data were analyzed by appropriate statistical method using SPSS 11.5 window version. Result : Children with oppositional defiant disorder were revealed to have significantly higher rates of psychiatric comorbidity and significantly greater family dysfunction compared to comparison group. Among the prenatal/perinatal risk factors, severe emotional stress during pregnancy, postpartum depression, medication during pregnancy were revealed as risk factors of ODD. In character inventory, ODD group were evaluated to have high score in novelty seeking, harm avoidance, but low in reward dependency. Conclusion : These results support that 1) prenatal/perinatal and psycho-social risk factors could be a important role in the progression of ODD, and 2) children with ODD have diverse comorbid psychiatric symptoms.

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The Effect of Firm Characteristics on the Relationship between Managerial Ability and Firm Performance (기업특성이 경영자능력과 경영성과의 관계에 미치는 영향)

  • Cho, Sang-Min;Yoo, Ji-Yeon
    • Management & Information Systems Review
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    • v.37 no.1
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    • pp.103-122
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    • 2018
  • This paper expands the results of previous studies indicating that manager's ability positively affects business performance to analyze whether the degree to which the role of manager's ability improves business performance appears differently according to the characteristics of enterprises. As for the characteristics of enterprises, whether enterprises correspond to enterprises with high levels of funding constraints or late movers in the market is considered. Enterprises with high levels of funding constraints greatly require managers' roles not only for efficient use of funds but also for smooth financing. Late movers require more judgments of professional managers to overcome insufficient resources held and low profitability. In the case of enterprises with corporate characteristics with high dependency on the manager, the business performance is expected to greatly vary with the ability of the manager. The empirical analysis was conducted with listed companies from 2010 to 2014, manager's ability was measured by first measuring the efficiency of the entire enterprise through data envelopment analysis (DEA) using the methodology of Demerjian et al.(2012) and removing enterprise characteristics factors thereafter. Business performance was measured by the return on industrial fixed assets. The results of the empirical analysis indicated that the degree to which manager's ability improves business performance was higher in managerial competence enhances managerial performance in enterprises with high levels of funding constraints and late movers. Business performance is considered to have been improved further in cases where manager's ability is high because investments were made more efficiently through smooth funding. In addition, in the case of late movers in relatively poor environments, business performance was improved further because high manager's ability induced efficient decision making. In this paper, we extend the precedent study that the manager's ability improves the management performance, and confirm that the manager's ability to improve the managerial performance can be different according to the situation of the company. In addition, it is meaningful to analyze empirically whether a company's managerial ability is more important. This paper expanded the results of previous studies indicating that manager's ability improves performance to identify that the degree to which manager's ability improves business performance may appear differently according to situations in which enterprises are placed. In addition, this paper is meaningful in that it empirically analyzed what enterprises require manager's ability more importantly.

Surgical Treatment of Pulmonary Atresia with Intact Ventricular Septum -Effect of the size of tricuspid valve annulus on the surgical outcome- (영아기에 발견된 심실중격이 온전한 폐동맥 폐쇄증의 외과적 수술요법 술전 삼첨판륜 크기 가 수술 결과에 미치는 영향)

  • 이정렬;윤태진
    • Journal of Chest Surgery
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    • v.29 no.10
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    • pp.1081-1089
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    • 1996
  • Pulmonary atresia with intact ventricular septum has continued to have a high surgical mortality and morbidity. This mAy attribute to the non-uniformity of the anomaly. We reviewed a total of 34 infants with pulmonary atresla and intact ventricular septum managed in this hospital between 1987 and 1995. Mean age and body weight were 57.2 (range, 3-208) days and 4.1 (range, B.3∼6.8) kg. The preoperative Z-value of the diameter of the tricuspid valve was less than -2 in 85.2% of patients and less than -4 in 33. 3% . It is well correlated w th right ventricular cavity size (n=27. r10.68, p< 0.05). Coronary artery-right ventricular fistulas were identified in 3 patients, and right ventricular dependency was suspected in 1 Over All hospital mortality was 23.5%(8/34), although it decreased to 16.6%(4124) in 1990s. Subsequent procedures were performed in 6 patients between 3 days and 58 months after Initial palliation : one bidirectional cavopulmonary shunt and 1 Fontan operation after systemic-pulmonary shunt, 3 transannular patch + atrial septal defect closure and 1 additional systemic-pulmonary shunt after polmonary valvectomy or valvotomy. Changes of Z-values of the diameter of tricuspid valve have been followed up in 11 patients between 1 and 66 months postoperatively. Z-values were increased In 5 out of 8 transannular right ventriculAr outflow tract enlargement group and in 1 out of 3 pulmonary valvectomy or valvotomy group. Our data suggest that tailoring a treatment to right ventricular cavity size and coronary anom lies may improve the surgical outcome. A Z-value of the tricuspid valve diameter could be used.

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Tectonic Movement in the Korean Peninsula (II): A Geomorphological Interpretation of the Spatial Distribution of Earthquakes (한반도의 지반운동 (II): 한반도 지진분포의 지형학적 해석)

  • Park, Soo-Jin
    • Journal of the Korean Geographical Society
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    • v.42 no.4
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    • pp.488-505
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    • 2007
  • The purposes of this research are twofold; 1) to verify spatial differences of tectonic movement using the spatial distribution of earthquakes, and 2) to infer mechanisms that generate spatial accumulation patterns of earthquakes in the Korean Peninsula. The first part of this sequential paper (Park, 2007) argues that the Korean Peninsula consists of four geostructural regions in which tectonic deformation and consequent geomorphological development patterns are different from each other Since this conclusion has been made by terrain analyses alone, it is necessary to verify this suggestion using other independent geophysical data. Because earthquakes are results of movement and deformation of land masses moving in different directions, the distribution of earthquake epicenters may be used to identify the direction and rates of land mass movement. This paper first analysed the spatial distribution of earthquakes using spatial statistics, and then results were compared with the spatial arrangement of geostructural regions. The spatial distribution of earthquakes in the Korean Peninsula can be summarized as the followings; firstly, the intensity of earthquakes shows only weak spatial dependency, and shows large difference even at adjacent regions. Secondly, the epicenter distribution has a clear spatial accumulation pattern, even though the intensity of earthquake shows a random pattern. Thirdly, the high density area of earthquakes shows a clear 'L' shape, passing through Pyeongannam-do, centered at Pyeongyang, and Hwanghae-do, Seosan and Pohang. The correlation coefficient between the density of earthquakes and distance from geostructral region boundaries is much higher than those between the density of fault lines and distance from tectonic division boundaries. Since fault lines and tectonic divisions in the Korean Peninsula are the results of long-term geological development, there is an apparent scale discrepancy to find significant correlations with earthquakes. This result verifies the research hypothesis that the Korean Peninsula is divided into four geostructral regions in which each has its own moving direction and spatial deformation characteristics. The existence of geostructural regions is also supported by the movement parrerns of land masses estimated from the GPS measurements. This conclusion is expected to provide a new perspective to understand the geomorphological developments and the earthquake occurrences in the Korean Peninsula.