• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.421-433
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• 2012

AMGA service, which is one of the EMI gLite middleware components, is widely used for analysis of distributed large scale experiments data as metadata repository by scientific and technological researchers and the use of AMGA is extended farther to include general industries needing metadata Catalogue as well. However AMGA, based unix and Grid UI, has the weakness of being absence of general-purpose user interfaces in comparison to other commercial database systems and that's why it's difficult to use and diffuse it although it has the superiority of the functionality. In this paper, we developed AMGA GUI toolkit to provide work convenience using object-oriented modeling language(UML). Currently, AMGA has been used as the main component among many user communities such as Belle II, WISDOM, MDM, and so on, but we expect that this development can not only lower the barrier to entry for AMGA beginners to use it, but lead to expand the use of AMGA service over more communities.

• The Journal of Bigdata
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• v.2 no.2
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• pp.33-46
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• 2017

Service part has the attribute causing a difficulty of the systematic management like a kind of diversity, uncertainty of demand, high request for quick response against general complete product. Especially, order picking is recognized as the most important work in the warehouse of the parts since inbound cycle of the service part long but outbound cycle is relatively short. But, increasing work efficiency in the warehouse has a limitation that cycle, frequency and quantity for the outbound request depend on the inherent features of the part. Through this research, not only are the types of the parts classified with the various and specified data but also the method is presented that it minimizes (that) the whole distances of the order picking and store location about both inbound and outbound by developing the model of the demand prediction. Based on this study, I expect that all of the work efficiency and the space utilization will be improved without a change of the inbound and outbound quantity in the warehouse.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.87-91
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• 2017

Recently, several kinds of researches using IoT wearable devices are active in the field of sports, design, emotional sciences and so on. The human bio data such as blood pulse, ECG, SKT signal, and GSR Signal producing from IoT wearable devices such as Watch, Smart-band, Grass can adapt to the meaningful future applications. Using the human's emotional data and a physical status with variation and so on, we can individually get the personal status. Due to knowing the personal emotion or physical status is related and connected to the valuable wallet of customers, the approach is more important in nowadays. Therefore, the personal information can effectively adapt to the marketing of the culture industry, which deals with emotions of customers. The research shows implementation steps for explaining overall architecture of the convergence research between Art and Technologies.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.1
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• pp.101-126
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• 2023

Photographic archives of universities are one of the most valuable types of records that establish the university's identity and provide historical evidence. Unlike text records, however, they are weak in conveying meanings. Therefore, it is difficult to support users' search and utilization unless the information of photo records is comprehensively described. In this study, for the university photo archives, we tried to structure the classification system of photo archives and develop a metadata set that reflects the category characteristics in the classification. To this end, the photo archives classification system and metadata elements of domestic and American university archives were analyzed and based on this, the model of information structure was proposed. The information structure model presented in this study can help university archives improve the data quality of their photo archives and support users with the abundant discovery of photo archives.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.102-110
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• 2023

The MATS(Missile Assembly Test Set) is manufactured and used to check the function of the missile during the period of development for the guided missile system, and the requirements for power and communication are managed for equipment production. The MATS developer implements software according to the proposed communication standard to guarantee the reliability of the data that communicates with the guided missile. The test bed is built and self-performance evaluation is performed after implementation. And the verification process is performed using the standard equipment. The characteristics of periodic delay for data transmission must be reflected when building a test bed. This paper describes a test bed construction method for data processing with periodic delay. Also This paper compares and evaluates the performance by changing the previously designed algorithm.

• Journal of KIISE
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• v.42 no.4
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• pp.475-482
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• 2015

Developing a high-performance Semantic Role Labeling (SRL) system for a domain requires manually annotated training data of large size in the same domain. However, such SRL training data of sufficient size is available only for a few domains. Performances of Korean SRL are degraded by almost 15% or more, when it is directly applied to another domain with relatively small training data. This paper proposes two techniques to minimize performance degradation in the domain transfer. First, a domain adaptation algorithm for Korean SRL is proposed which is based on the prior model that is one of domain adaptation paradigms. Secondly, we proposed to use simplified features related to morphological and syntactic tags, when using small-sized target domain data to suppress the problem of data sparseness. Other domain adaptation techniques were experimentally compared to our techniques in this paper, where news and Wikipedia were used as the sources and target domains, respectively. It was observed that the highest performance is achieved when our two techniques were applied together. In our system's performance, F1 score of 64.3% was considered to be 2.4~3.1% higher than the methods from other research.

• Analytical Science and Technology
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• v.32 no.1
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• pp.7-16
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• 2019

The objective of this study was the development of a discrimination model for the cultivational origin of paper mulberry bast fiber and Hanji using near infrared (NIR) and mid infrared (MIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA). Paper mulberry bast fiber was purchased in 10 different regions of Korea, and used to make Hanji. PLS-DA was performed using pre-treated FT-NIR and FT-MIR spectral data for paper mulberry bast fiber and Hanji. PLS-DA of paper mulberry bast fiber and Hanji samples, using FT-NIR spectral data, showed 100 % performance in cross validation and the confusion matrix (accuracy, sensitivity, and specificity). The discrimination models showed four regional groups which demonstrated clearer separation and much superior score plots in the NIR spectral data-based model than in the MIR spectral data-based model. Furthermore, the discrimination model based on the NIR spectral data of paper mulberry bast fiber had highly similar score morphology to that of the discrimination model based on the NIR spectral data of Hanji.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.501-505
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• 2007

Recently KISTI has developed the KnowlegeMatrix which is a stand-alone type bibliographic data analysis software. In this paper, we try to benchmark test on the performance level of KnowledgeMatrix with well-known S/Ws such as VantagePoint and BibTechMon. We compare distinctive functions and usability of each S/Ws on comparative categories including Data, Matrix, Analysis, Visualization and Preprocessing. Test results show that all S/Ws have differentiated specific feature, but there is some performance gaps. KnowledgeMatrix overally shows better performance than others.

• Journal of the Korean Society of Mineral and Energy Resources Engineers
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• v.55 no.6
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• pp.649-659
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• 2018

In this study, after operational data for a landfill gas power plant were collected, the methane gas concentration was predicted using a deep learning method. Concentrations of methane gas, carbon dioxide, hydrogen sulfide, oxygen concentration, as well as data related to the valve opening degree, air temperature and humidity were collected from 23 pipeline bases for 88 matches from January to November 2017. After the deep learning model learned the collected data, methane gas concentration was estimated by applying other data. Our study yielded extremely accurate estimation results for all of the 23 pipeline bases.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1075-1080
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• 2022

Recently, the effort is continuously applied in machine learning and deep learning algorithm which is represented as artificial intelligence algorithm in the varies field such as prediction, classification and clustering. In this paper, we propose detection algorithm for un-peeling status of PCB protection film by using Dectron2. We use 42 images of data as training and 19 images of data as testing based on 61 images which was taken under the condition of a critical reflection angel of 42.8°. As a result, we get 16 images that was detected and 3 images that was not detected among 19 images of testing data.