• Journal of Korean Home Economics Education Association
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• v.13 no.2
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• pp.1-14
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• 2001

The purpose of this study was to find out and advocate the intake of vitamin A and C rich foods in Korean people. Forty kinds of vitamin A and C rich foods were selected by the vitamin quantity in 100g edible portion. in single serving size. and by the 1997 national food supply data. The results were summarized as follows. 1. The vitamin A rich foods 1) The food sources of vitamin A presented in the middle and high school home economics textbooks were liver. egg/egg yolk. milk/dairy products. and green and yellow vegetables. etc. 2) The vitamin A rich foods by 100g edible portion ere in order of red pepper(dried). laver(dried). carrot. meat edible viscera. eel. etc. And the vitamin A rich foods by the vitamin A content in single serving size were in order of carrot. eel. meat edible viscera. water shield. red pepper(dried). etc. 3) The vitamin A suppling foods according to the 1997 national food supply data were in order of red pepper(dried). meat edible viscera. laver. carrot. etc. The green and yellow vegetables. fish and shellfish. and seaweeds were the most important sources of vitamin A in Korean. 2. The vitamin C rich foods 1) The food sources of vitamin C presented in the textbooks of middle and high school were strawberry. citrus fruits. and vegetables such as spinach. chinese cabbage. radish. crown daisy. etc. 2) The vitamin C rich foods on the basis of the vitamin C content in 100g edible portion were in order of sweet pepper. goose berry. citron. strawberry. water shield. etc. And the vitamin C rich foods by the quantity in single serving size were in order of strawberry. goose berry. citron. sweet pepper. lemon. etc. 3) The vitamin C suppling foods according to the 1997 national food supply data were in order of chinese cabbage. radish. citrus fruits. strawberry. etc. Not only vegetables and fruits but also seaweeds like dried laver and sea mustard were the most important source of vitamin C in korean.

• Journal of Preventive Medicine and Public Health
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• v.43 no.3
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• pp.257-264
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• 2010

Objectives: An accurate estimation of cancer patients is the basis of epidemiological studies and health services. However in Korea, cancer patients visiting out-patient clinics are usually ruled out of such studies and so these studies are suspected of underestimating the cancer patient population. The purpose of this study is to construct a more complete, hospital-based cancer patient registry using multiple sources of medical information. Methods: We constructed a cancer patient detection algorithm using records from various sources that were obtained from both the in-patients and out-patients seen at Asan Medical Center (AMC) for any reason. The medical data from the potentially incident cancer patients was reviewed four months after first being detected by the algorithm to determine whether these patients actually did or did not have cancer. Results: Besides the traditional practice of reviewing the charts of in-patients upon their discharge, five more sources of information were added for this algorithm, i.e., pathology reports, the national severe disease registry, the reason for treatment, prescriptions of chemotherapeutic agents and radiation therapy reports. The constructed algorithm was observed to have a PPV of 87.04%. Compared to the results of traditional practice, 36.8% of registry failures were avoided using the AMC algorithm. Conclusions: To minimize loss in the cancer registry, various data sources should be utilized, and the AMC algorithm can be a successful model for this. Further research will be required in order to apply novel and innovative technology to the electronic medical records system in order to generate new signals from data that has not been previously used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1413-1432
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• 2023

Recommender systems aim to recommend items to users by taking into account their probable interests. This study focuses on creating a model that utilizes multiple sources of information about users and items by employing a multimodality approach. The study addresses the task of how to gather information from different sources (modalities) and transform them into a uniform format, resulting in a multi-modal feature description for users and items. This work also aims to transform and represent the features extracted from different modalities so that the information is in a compatible format for integration and contains important, useful information for the prediction model. To achieve this goal, we propose a novel multi-modal recommendation model, which involves extracting latent features of users and items from a utility matrix using matrix factorization techniques. Various transformation techniques are utilized to extract features from other sources of information such as user reviews, item descriptions, and item categories. We also proposed the use of Principal Component Analysis (PCA) and Feature Selection techniques to reduce the data dimension and extract important features as well as remove noisy features to increase the accuracy of the model. We conducted several different experimental models based on different subsets of modalities on the MovieLens and Amazon sub-category datasets. According to the experimental results, the proposed model significantly enhances the accuracy of recommendations when compared to SVD, which is acknowledged as one of the most effective models for recommender systems. Specifically, the proposed model reduces the RMSE by a range of 4.8% to 21.43% and increases the Precision by a range of 2.07% to 26.49% for the Amazon datasets. Similarly, for the MovieLens dataset, the proposed model reduces the RMSE by 45.61% and increases the Precision by 14.06%. Additionally, the experimental results on both datasets demonstrate that combining information from multiple modalities in the proposed model leads to superior outcomes compared to relying on a single type of information.

• Environmental Analysis Health and Toxicology
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• v.30
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• pp.10.1-10.14
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• 2015

Recent cohort studies have relied on exposure prediction models to estimate individual-level air pollution concentrations because individual air pollution measurements are not available for cohort locations. For such prediction models, geographic variables related to pollution sources are important inputs. We demonstrated the computation process of geographic variables mostly recorded in 2010 at regulatory air pollution monitoring sites in South Korea. On the basis of previous studies, we finalized a list of 313 geographic variables related to air pollution sources in eight categories including traffic, demographic characteristics, land use, transportation facilities, physical geography, emissions, vegetation, and altitude. We then obtained data from different sources such as the Statistics Geographic Information Service and Korean Transport Database. After integrating all available data to a single database by matching coordinate systems and converting non-spatial data to spatial data, we computed geographic variables at 294 regulatory monitoring sites in South Korea. The data integration and variable computation were performed by using ArcGIS version 10.2 (ESRI Inc., Redlands, CA, USA). For traffic, we computed the distances to the nearest roads and the sums of road lengths within different sizes of circular buffers. In addition, we calculated the numbers of residents, households, housing buildings, companies, and employees within the buffers. The percentages of areas for different types of land use compared to total areas were calculated within the buffers. For transportation facilities and physical geography, we computed the distances to the closest public transportation depots and the boundary lines. The vegetation index and altitude were estimated at a given location by using satellite data. The summary statistics of geographic variables in Seoul across monitoring sites showed different patterns between urban background and urban roadside sites. This study provided practical knowledge on the computation process of geographic variables in South Korea, which will improve air pollution prediction models and contribute to subsequent health analyses.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.27-33
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• 2009

Content used in mashups is typically obtained from a third party source through a public interface or API (web services). Other methods of obtaining content for mashups include Web feeds (e.g. RSS or Atom), and screen scraping. A mashup or meshup Web application has two parts: A new service delivered through a Web page, using its own data and data from other sources. The blended data, made available across the Web through an API or other protocols such as HlTP, RSS, REST, etc. There are many types of mashups, such as consumer mashups, data mashups, and Business Mashups. The most common mashup is the consumer mashup, which are aimed at the general public. Examples include Google Maps, iGuide, and RadioClouds. 4D Wall-map display is data mashups combine similar types of media and information from multiple sources into a single representation. This technology focus data into a single presentation and allow for collaborative action among ITS-related information sources.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8B
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• pp.1003-1011
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• 2011

In this paper, a real-time multi-source sensor data management system based on wireless sensor network is proposed and implemented. The proposed management system is designed to transmit the wireless data to the server in order to monitor and control the multi-source target's status efficiently by analyzing them. The proposed system is implemented to make it possible to control and transmit the wireless sensor data by classifying them, of which data are issued from the clustered sources composed of a number of the remote multiple sensors. In order to evaluate the performance of the proposed system, we measure and analyze both the transmission delay time according to the distance and the data loss rate issued from multiple data sources. From these results, it is verified that the proposed system has a good performance.

• Korean Journal of Human Ecology
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• v.20 no.5
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• pp.1035-1046
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• 2011

The purpose of this study was to investigate the impulse buying behavior of men and women in their twenties, who have experiences of purchasing on internet shopping malls, when they buy fashion products. The data in this study was statistically analyzed using factor analysis, reliability coefficient, and multiple regression analysis using SPSS 14.0. The findings are as follows. First, factor analysis revealed five factors of impulse buying behavior during the purchase of fashion products on internet shopping malls: affective impulse buying, provocative impulse buying, situational impulse buying, reminder impulse buying, and pure impulse buying. Second, factors of perceived risk when purchasing fashion products on internet shopping malls included product quality, payment, service, and economy. Third, sources of information included personal sources of media for fashion professionals, commercials and sponsorship, and promotion. Fourth, the effect of the perceived risk on impulse buying behavior was investigated and the result showed that the perceived risk had a statistically significant influence on impulse buying behavior. Finally, the effect of the information source on impulse buying behavior was investigated and the results showed that the use of information sources had a statistically significant influence on impulse buying behavior.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.765-774
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• 2004

In order to integrate heterogeneous biological information sources, it is necessary to define the view that represents unified viewpoint for the multiple sources by hiding heterogeneity of the data. We present an XML-based view definition model and show Its operating principles in designing the middleware system to integrate biological information sources. This model supports the user-defined XML view to increase flexibility in constructing the integration system and execute integrated queries on higher level ion. Based on the view-definition model, we present a wrapping model for relational database systems and web resources as well as an application program.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.59.1-59.1
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• 2011

I present an analysis of the long-term evolution of the fluxes of six active galactic nuclei (AGN) - 0923+392, 3C 111, 3C 273, 3C 345, 3C 454.3, and 3C 84 - in the frequency range 80 - 267 GHz using archival calibration data of the IRAM Plateau de Bure Interferometer. Our dataset spans a long timeline of ~14 years with 974 - 3027 flux measurements per source. We find strong (factors ~2-8) flux variability on timescales of years for all sources. The flux density distributions of five out of six sources show clear signatures of bi- or even multimodality. Our sources show mostly steep (alpha~0.5-1), variable spectral indices that indicate outflow dominated emission; the variability is most probably due to optical depth variations. The power spectra globally correspond to red-noise spectra with five sources being located between the cases of white and flicker noise and one source (3C 111) being closer to the case of random walk noise. For three sources the low-frequency ends of their power spectra appear to be upscaled in spectral power by factors ~2-3 with respect to the overall powerlaws. We conclude that the source emission cannot be described by uniform stochastic emission processes; instead, a distinction of "quiescent" and (maybe multiple) "flare" states of the source emission appears to be necessary.

• ETRI Journal
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• v.28 no.5
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• pp.593-606
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• 2006

Thanks to the great possibilities of providing different types of telecommunication traffic to a large geographical area, satellite networks are expected to be an essential component of the next-generation internet. As a result, issues concerning the designing and testing of efficient connection-admission-control (CAC) strategies in order to increase the quality of service (QoS) for multimedia traffic sources, are attractive and at the cutting edge of research. This paper investigates the potential strengths of a generic digital-video-broadcasting return-channel-via-satellite (DVB-RCS) system architecture, proposing a new CAC algorithm with the aim of efficiently managing real-time multimedia video sources, both with constant and high variable data rate transmission; moreover, the proposed admission strategy is compared with a well-known iterative CAC mainly designed for the managing of real-time bursty traffic sources in order to demonstrate that the new algorithm is also well suited for those traffic sources. Performance analysis shows that, both algorithms guarantee the agreed QoS to real-time bursty connections that are more sensitive to delay jitter; however, our proposed algorithm can also manage interactive real-time multimedia traffic sources in high load and mixed traffic conditions.