• Journal of Korea Society of Industrial Information Systems
• /
• v.12 no.5
• /
• pp.1-13
• /
• 2007

In this research, we found out that bridging nodes have great effect on the robustness of protein-protein interaction networks. Until now, many researchers have focused on node's degree as node's essentiality. Hub nodes in the scale-free network are very essential in the network robustness. Some researchers have tried to relate node's essentiality with node's betweenness centrality. These approaches with betweenness centrality are reasonable but there is a positive relation between node's degree and betweenness centrality value. So, there are no differences between two approaches. We first define a bridging node as the node with low connectivity and high betweenness value, we then verify that such a bridging node is a primary factor in the network robustness. For a biological network database from Internet, we demonstrate that the removal of bridging nodes defragment an entire network severally and the importance of the bridging nodes in the network robustness.

• Journal of Life Science
• /
• v.22 no.10
• /
• pp.1359-1370
• /
• 2012

Arabidopsis AtERF71/HRE2, a transcription activator, is located in the nucleus and is involved in the signal transduction of low oxygen and osmotic stresses. In this study, microarray analysis using AtERF71/HRE2-overexpressing transgenic plants was performed to identify genes downstream of AtERF71/HRE2. A total of 161 different genes as well as AtERF71/HRE2 showed more than a twofold higher expression in AtERF71/HRE2-overexpressing transgenic plants compared with wild-type plants. Among the 161 genes, 24 genes were transcriptional regulators, such as transcription factors and DNA-binding proteins, based on gene ontology annotations, suggesting that AtERF71/HRE2 is an upstream transcription factor that regulates the activities of various downstream genes via these transcription regulators. RT-PCR analysis of 15 genes selected out of the 161 genes showed higher expression in AtERF71/HRE2-overexpressing transgenic plants, validating the microarray data. On the basis of Genevestigator database analysis, 51 genes among the 161 genes were highly expressed under low oxygen and/or osmotic stresses. RT-PCR analysis showed that the expression levels of three genes among the selected 15 genes increased under low oxygen stress and another three genes increased under high salt stress, suggesting that these genes might be downstream genes of AtERF71/HRE2 in low oxygen or high salt stress signal transduction. Microarray analysis results indicated that AtERF71/HRE2 might also be involved in the responses to other abiotic stresses and also in the regulation of plant developmental processes.

• The Journal of Korean society of community based occupational therapy
• /
• v.7 no.1
• /
• pp.59-70
• /
• 2017

Objective : The purpose of this study was to examine the effect of virtual reality-based remote rehabilitation on stroke patients systematically and to look for its effect and how to apply it domestically. Methods : In order to search data, EMBASE and CINAHL database were used. Relevant research used those terms of virtual reality, telerehabilitation, and stroke. A total of 10 studies satisfying the selection criteria was analyzed according to their qualitative level, general characteristics, and PICO method. Results : Based on the selected 10 studies, virtual reality-based telerehabilitation system was applied. Sensory and motor feedback was provided with inputting visual and auditory senses through a video in the home environment, and it stimulated changes in the client's nervous system. Tools to measure the results were upper extremity function, balance and gait, activities of daily living, etc. Those virtual reality-based telerehabilitation method had an effect on upper extremity function and ability of sense of balance in all studies, and on the activities of daily living partially. Telerehabilitation service to make up environmental specificity improved satisfaction of client. That meaned the effect of the intervention to maintain the function. Conclusion : The virtual reality-based telerehabilitation system was applied to upper extremity function, sense of balance, and activities of daily living largely, and it showed that it helped to improve functions through intervention, supervision, and training of therapist in the home environment as well. This study suggests the basis and possibility of clinical application on virtual-reality based telerehabilitation. Additional research is needed to diverse virtual reality intervention methods and the effect of telerehabilitation in the future.

• Journal of Intelligence and Information Systems
• /
• v.23 no.3
• /
• pp.139-153
• /
• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.38 no.2
• /
• pp.42-59
• /
• 2020

The purpose of this study is to examine the actual cases of crane breeding at private homes in the Joseon Dynasty period, thereby identifying the universal meaning and characteristics of this act reflected in these cases. This study is likely to help understand the true nature of garden culture during the period. The study' temporal and spatial scope was limited to the Joseon Dynasty and private homes. As references for the study, translated versions of classical literature were selected from the Database of Korean Classics(http://db.itkc.or.kr). To complement for the data, related researchers' translated materials were also used in part. The study's results are summed up as follows: First, Individuals from various social classes including royal families, noblemen, noble families in countryside, and commoners kept cranes at their homes. These crane breeders included those who left a significant mark in the Joseon Dynasty politically and academically as well as 'cheosa(處士)' that refers to scholars living in seclusion without entering the government throughout their lifetime. Second, Crane breeders were spread all over the country. Notably, various cases of crane breeding were found within the Hanyang Wall and its vicinity. Third, The act of crane breeding was highly associated with blood ties and academic lineages such as friendships and teacher-student relations. In this regard, crane breeding was not just a simple taste or appreciation for the arts, but rather reflective of a person's life attitude and orientation. Forth, The consciousness of Confucian origins based on an ancient story of Limpo (林逋) appears to have a large impact on the act of crane breeding. In addition, some cases exhibited the reflection of Taoistic tastes. Fifth, Some individuals tamed cranes for a living. This proves the presence of steady demand for cranes in this period. The present study's limitation is its reliance on translated materials, which hindered research into various cases. Therefore, the future discovery of additional data and the accumulation of their translations will enable the investigation of a wealth of cases.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.23 no.1
• /
• pp.1-19
• /
• 2018

In order to compare significant wave height (SWH) data from multi-satellites (GFO, Jason-1, Envisat, Jason-2, Cryosat-2, SARAL) and SWH measurements from Ieodo Ocean Research Station (IORS), we constructed a 12 year matchup database between satellite and IORS measurements from December 2004 to May 2016. The satellite SWH showed a root mean square error (RMSE) of about 0.34 m and a positive bias of 0.17 m with respect to the IORS wave height. The satellite data and IORS wave height data did not show any specific seasonal variations or interannual variability, which confirmed the consistency of satellite data. The effect of the wind field on the difference of the SWH data between satellite and IORS was investigated. As a result, a similar result was observed in which a positive biases of about 0.17 m occurred on all satellites. In order to understand the effects of topography and the influence of the construction structures of IORS on the SWH differences, we investigated the directional dependency of differences of wave height, however, no statistically significant characteristics of the differences were revealed. As a result of analyzing the characteristics of the error as a function of the distance between the satellite and the IORS, the biases are almost constant about 0.14 m regardless of the distance. By contrast, the amplitude of the SWH differences, the maximum value minus the minimum value at a given distance range, was found to increase linearly as the distance was increased. On the other hand, as a result of the accuracy evaluation of the satellite SWH from the Donghae marine meteorological buoy of Korea Meteorological Administration, the satellite SWH presented a relatively small RMSE of about 0.27 m and no specific characteristics of bias such as the validation results at IORS. In this paper, we propose a conversion formula to correct the significant wave data of IORS with the satellite SWH data. In addition, this study emphasizes that the reliability of data should be prioritized to be extensively utilized and presents specific methods and strategies in order to upgrade the IORS as an international world-wide marine observation site.

• Journal of KIISE:Databases
• /
• v.33 no.1
• /
• pp.102-116
• /
• 2006

Electronic catalogs (or e-catalogs) hold information about the goods and services offered or requested by the participants, and consequently, form the basis of an e-commerce transaction. Catalog management is complicated by a number of factors and product classification is at the core of these issues. Classification hierarchy is used for spend analysis, custom3 regulation, and product identification. Classification is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. However, product classification has received little formal treatment in terms of underlying model, operations, and semantics. We believe that the lack of a logical model for classification Introduces a number of problems not only for the classification itself but also for the product database in general. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eClass, however, have a lot of limitations to meet these requirements for dynamic features of classification. In this paper, we try to understand what it means to classify products and present how best to represent classification schemes so as to capture the semantics behind the classifications and facilitate mappings between them. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes. And describe the semantic classification model, which satisfies the requirements for dynamic features oi product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph. We believe the model proposed in this paper satisfies the requirements and challenges that have been raised by previous works.

• The KIPS Transactions:PartB
• /
• v.13B no.5 s.108
• /
• pp.561-568
• /
• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.44 no.1
• /
• pp.14-23
• /
• 2015

This study examined the glycemic indices (GIs) and glycemic loads of carbohydrate-rich snacks in Korea according to variety and cooking method. The most popular carbohydrate snacks (corn, potatoes, sweet potatoes, chestnuts, and red beans) from the Korean National Health and Nutrition Examination Survey nutrient database were cooked using a variety of conventional cooking methods (steaming, baking, porridge, puffing, and frying). The GIs of foods were measured in 60 healthy males after receiving permission from the University Hospital institutional review board (KMC IRB 1306-01). Blood glucose and insulin levels were then measured at 0, 15, 30, 60, 90, and 120 min after consuming glucose, and each test food contained 50 g of carbohydrates (corn: 170.0 g, potatoes: 359.7 g, sweet potatoes: 160.3 g, chestnuts: 134.8 g, red beans: 73.1 g). GI values for test foods were calculated based on the increase in the area under the blood glucose response curve for each subject. Steamed potatoes ($93.6{\pm}11.6$), corn porridge ($91.8{\pm}19.5$), baked sweet potatoes ($90.9{\pm}9.6$), baked potatoes ($78.2{\pm}14.5$), steamed corn ($73.4{\pm}9.9$), and steamed sweet potatoes ($70.8{\pm}6.1$) were shown to be considered high GI foods, whereas baked chestnuts ($54.3{\pm}6.3$), red bean porridge ($33.1{\pm}5.5$), steamed red beans ($22.1{\pm}3.2$), fried potatoes ($41.5{\pm}7.8$), and ground and pan-fried potatoes ($28.0{\pm}5.1$) were considered as low GI foods. The results suggest that the cooking method of carbohydrate-rich snacks is an important determinant of GI values.

• Journal of Korea Port Economic Association
• /
• v.37 no.1
• /
• pp.159-178
• /
• 2021

This study analyzed issues and trends related to ports with 86,611 news articles for the 30 years from 1991 to 2020, using BIGKinds, a big data news analysis service. The analysis was based on keyword analysis, word cloud, relationship diagram analysis offered by BIG Kinds. Analysis results of issues and trends on ports for the last 30 years are summarized as follows. First, during Phase 1 (1991-2000), individual ports such as Busan, Incheon, and Gwangyang ports tried to strengthen their own competitiveness. During Phase 2 (2001-2010), efforts were made on gaining more professional and specialized port management abilities by establishing the Busan Port Authority in 2004, the Incheon Port Authority in 2005, and the Ulsan Port Authority in 2007. During Phase 3 (2011-2020), the promotion of future-oriented, eco-friendly, and smart ports was major issues. Efforts to reduce particulate matters and pollutants produced from ports were accelerated, and an attempt to build a smart port driven by port automation and digitalization was also intensified. Lastly, in 2020, when the maritime sector was severely hit by the unexpected shock of the COVID-19 pandemic, a microscopic analysis of trends and issues in 2019 and 2020 was made to look into the impact the pandemic on the maritime industry. It was found that shipping and port industries experienced more drastic changes than ever while trying to prepare for a post-pandemic era as well as promoting future-oriented ports. This study made policy suggestions by analyzing port-related news articles and trends, and it is expected that based on the findings of this research, further studies on enhancing the competitiveness of ports and devising a sustainable development strategy will follow through a comparative analysis of port issues of different countries, thereby making further progress toward academic research on ports.