• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.97-121
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• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

• Journal of Korean Orthopaedic Sports Medicine
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• v.1 no.1
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• pp.79-88
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• 2002

Purpose: In this prospective, randomized study, we compared the results of early motion versus conventional immobilization after the arthroscopic Bankart repair. Materilal and Methods : We performed an arthroscopic Bankart repair using suture anchors in 62 patients with traumatic anterior shoulder instability and randomized them into two groups; Group 1 (n=28; mean age, 28 years) underwent three-week of immobilization and conventional rehabilitation program, while Group 2 (n=34; mean age, 29 years) underwent an accelerated rehabilitation program with staged range of motion and strengthening exercises starting from the immediate postoperative day. Selected patients were non-athletes with a classic Bankart lesion and a robust labrum. Analysis of outcome included pain scores (6-week and follow-up: 31(9 months), range of motion, return to activity, recurrence, patients’ satisfaction with each program, and shoulder scores (ASES, UCLA, and Rowe). Results : The recurrent rate was not different between the two groups (2 anterior apprehension from each group) (p=0.842). Patients with accelerated rehabilitation resumed functional range-of-motion faster and returned earlier to the functional level of activity (p<0.05). Accelerated rehabilitation decreased postoperative pain and more patients were satisfied with this program (p<0.05). No differences were found between the two groups at the follow-up with regards to the shoulder scores, return to activity, pain score, and the range-of-motion. Conclusions : Early mobilization after arthroscopic Bankart repair does not increase the recurrence rate in selected patients. Although the final outcomes are similar in both groups, the accelerated rehabilitation program promotes functional recovery and reduces postoperative pain, which enables patients an early institution of desired activities.

• Journal of Technology Innovation
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• v.17 no.2
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• pp.55-80
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• 2009

Technology innovation activity plays a pivotal role in constructing the entrance barrier for other firms and making process improvement and new product. and these activities give a profit increase and growth to firms. Thus, technology innovation activity can reduce the default risk of firms. However, technology innovation activity can also increase the firm's default risk because technology innovation activity requires too much investment of the firm's resources and has the uncertainty on success. The purpose of this study is to examine the effect of technology innovation activity on the default risk of firms. This study's sample consists of manufacturing firms listed on the Korea Securities Market and The Kosdaq Market from January 1,2000 to December 31, 2008. This study makes use of R&D intensity as an proxy variable of technology innovation activity. The default probability which proxies the default risk of firms is measured by the Merton's(l974) debt pricing model. The main empirical results are as follows. First, from the empirical results, it is found that technology innovation activity has a negative and significant effect on the default risk of firms independent of the Korea Securities Market and Kosdaq Market. In other words, technology innovation activity reduces the default risk of firms. Second, technology innovation activity reduces the default risk of firms independent of firm size, firm age, and credit score. Third, the results of robust analysis also show that technology innovation activity is the important factor which decreases the default risk of firms. These results imply that a manager must show continuous interest and investment in technology innovation activity of one's firm. And a policymaker also need design an economic policy to promote the technology innovation activity of firms.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.835-848
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• 2021

In Jeju Island which has peculiarity for its geological features and hydrology system, hydrological factor analysis for the effective water management is necessary. Because in-situ hydro-meteorological data is affected by surrounding environment, the in-situ dataset could not be the spatially representative for the study area. For this reason, remote sensing data may be used to overcome the limit of the in-situ data. In this study, applicability assessment of MOD16 evapotranspiration data, Globas Land Data Assimilation System (GLDAS) based evapotranspiration/soil moisture data, and Advanced SCATterometer (ASCAT) soil moisture product which were evaluated their applicability on other study areas was conducted. In the case of evapotranspiration, comparison with total precipitation and flux-tower based evapotranspiration were conducted. And for soil moisture, 6 in-situ data and ASCAT soil moisture product were compared on each site. As a result, 57% of annual precipitation was calculated as evapotranspiration, and the correlation coefficient between MOD16 evapotranspiration and GLDAS evapotranspiration was 0.759, which was a robust value. The correlation coefficient was 0.434, indicating a relatively low fit. In the case of soil moisture, in the case of the GLDAS data, the RMSE value was less than 0.05 at all sites compared to the in-situ data, and a statistically significant result was obtained as a result of the significance test of the correlation coefficient. However, for satellite data, RMSE over than 0.05 were found at Wolgak and there was no correlation at Sehwa and Handong points. It is judged that the above results are due to insufficient quality control and spatial representation of the evapotranspiration and soil moisture sensors installed in Jeju Island. It is estimated as the error that appears when adjacent to the coast. Through this study, the necessity of improving the existing ground observation data of hydrometeorological factors is emphasized.

• (The) Research of the performance art and culture
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• no.34
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• pp.9-42
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• 2017

Of all Geommu(劍舞, Korean sword dance), Gisaeng-Geommu danced by gisaeng(妓生, Korean female entertainers) for private guests and at the royal court. The Sword dance in the late Joseon Dynasty used to be dynamic exuding menacing "sword spirit(劍氣)." Sword dance being transmitted today is more ritualistic and elegant. This study considers Korean sword dance has a core structure and motifs transcending generational differences, and based on this critical thinking, aims to analyze the structure of Korean sword dance. This study analyzed the prose "Geommugi(劍舞記)" by Park Je-ga(朴齊家) and the poem "Mugeompyeonjeongmiin(舞劍篇贈美人)" by Jeong Yak-yong(丁若鏞) out of literary works from the late Joseon Dynasty, and from official records of rituals(笏記), "Geomgimu(Sword Dance, 劍器舞)" and "Geommu" in "Gyobanggayo(敎坊歌謠)." In the introduction part of Sword dance, a dancer appears, bows and performs a hand dance or hansam(汗衫) dance to and fro. In the development part, a dancer meets with a sword but first hesitates to hold it and dances holding swords in both hands. The climax shows expert sword skills and combat scenes. In the conclusion part, the court dance involves a dancer bidding a formal farewell, while the dance for entertainment, a dance throws away the sword to finish. From literature materials, the structure of Korean sword dance could be divided into an introduction, a development, a climax and a conclusion. Based on this, this study analyzed sword dance movements by linking the beats accompanying the current sword dance, in the order of a Yeombul, the traditional Korean ballad Taryeong or Neujeun Taryeong, Jajin Taryeong, Taryeong and Jajin Taryeong. The introduction part includes a Buddhist prayer and the beginning of Taryeong. Dancers appear, and in two rows they dance facing each other. On the slow beat, their dances are relaxed and elegant. The development part is matched with Jajin Taryeong. Dancers sit in front of swords and grab them, and they dance holding a pair of swords. The beat gradually becomes faster, progressing the development of the dance. But then, the slower Taryeong is placed again. The reason behind it is to create a tension for a little while, before effectively reaching a climax by speeding up the tempo again. Moving on to Jajin Taryeong, dancers' movements are bigger and more dynamic. The highly elated Jajin Taryeong shows dance movements at the climax on fast, robust beats. In the conclusion part, the beat is quick-tempo and on the upbeat again on Jajin Taryeong. Driving on without a stop on the exciting Yeonpungdae(燕風臺) melody, dancers standing in a line dance wielding the swords and bow before finishing.

• Korean Journal of Mineralogy and Petrology
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• v.34 no.1
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• pp.31-40
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• 2021

The hydrogen in nominally anhydrous mineral is known to be associated with lattice defects, but it also can exist in the form of water and hydroxyl groups on the large surface of the nanoscale particles. In this study, we investigate the effectiveness of 1H solid-state nuclear magnetic resonance (NMR) spectroscopy as a robust experimental method to quantify the hydrogen atomic environments of amorphous silica nanoparticles with varying relative humidity. Amorphous silica nanoparticles were packed into NMR rotors in a temperature-humidity controlled glove box, then stored in different atmospheric conditions with 25% and 70% relative humidity for 2~10 days until 1H NMR experiments, and a slight difference was observed in 1H NMR spectra. These results indicate that amount of hydrous species in the sample packed in the NMR rotor is rarely changed by the external atmosphere. The amount of hydrogen atom, especially the amount of physisorbed water may vary in the range of ~10% due to the temporal and spatial inhomogeneity of relative humidity in the glove box. The quantitative analysis of 1H NMR spectra shows that the amount of hydrogen atom in amorphous silica nanoparticles linearly increases as the relative humidity increases. These results imply that the sample sealing capability of the NMR rotor is sufficient to preserve the hydrous environments of samples, and is suitable for the quantitative measurement of water content of ultrafine nominally anhydrous minerals depending on the atmospheric relative humidity. We expect that 1H solid-state NMR method is suitable to investigate systematically the effect of surface area and crystallinity on the water content of diverse nano-sized nominally anhydrous minerals with varying relative humidity.

• Journal of Nutrition and Health
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• v.56 no.2
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• pp.155-167
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• 2023

Purpose: This study investigates the association between seafood consumption and frailty according to gender in the Korean elderly. Methods: Cross-sectional data from the Seventh (2016-2018) Korea National Health and Nutrition Examination Survey was procured for this study. Data from 3,675 subjects (1,643 men and 2,032 women) aged ≥ 65 years were analyzed. Levels of seafood intake were assessed by a one-day 24-hour dietary recall, and subjects were classified into three tertiles by gender according to frailty phenotype: robust, pre-frail, and frail. Multinomial logistic regression analysis was performed to clarify the association between seafood consumption and frailty for each gender. Results: The prevalence of frailty was determined as 13.4% for men and 29.7% for women. Participants with a higher seafood intake had higher intakes of grains, fruits, and vegetables, while the intake of meat was significantly lower. In both men and women, the group with higher seafood intake showed higher energy and micronutrient intakes. The frail prevalence and frailty score were significantly low in the highest tertiles of seafood consumption compared to the lowest tertile in men and women (p < 0.001). After adjusting for confounder, the highest tertile of seafood consumption showed a decreased risk of frailty compared to the lowest tertile only in women (hazard ratio [HR], 0.50; 95% confidence interval [CI], 0.32-0.78; p-trend = 0.008 vs. HR, 0.52; 95% CI, 0.32-0.83; p-trend = 0.008; respectively). Conclusion: Results of this study suggest that seafood consumption potentially decreases the risk of frailty in the elderly.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.