• Journal of Korean Home Economics Education Association
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• v.31 no.4
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• pp.97-113
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• 2019

This study is focused on the examination of changes in textbooks of Home Economics in High school from 7^st to 2015 curriculum, especially the 'Food and Nutrition section. We investigated the content elements of the National Curriculum Guide, the changes in learning contents, and the number of pages of Food and Nutrition section. The key words were extracted and the connective relationships between words were visualized using a method of language network analysis through word cloud and Semantic Network Analysis. According to the results of the research, the portion of the Food and Nutrition section has been gradually decreased on the Technology·Home Economics, following the development of the curriculum. Through the whole curriculum, 'invitation', 'Korean food', 'baby·nutrition' are appeared as key words. The education contents of Food and Nutrition section from the 7^th to 2015 revised have been developed and advanced with the changes of social needs. However, the reduction of portion and insufficiency of content elements of Food and Nutrition section bring concerns toward the decline of the quality of education on dietary life.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.261-269
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• 2017

The purpose of this paper is to provide a search system using a method of accessing the web in real time without using a database server in order to guarantee the up-to-date information in a single network, rather than using a plurality of bots connected by a wide area network Design. The method of the research is to design and analyze the system which can search the person and keyword quickly and accurately in crepe system. In the crepe server, when the user registers information, the body tag matching conversion process stores all the information as it is, since various styles are applied to each user, such as a font, a font size, and a color. The crepe server does not cause a problem of body tag matching. However, when executing the crepe retrieval system, the style and characteristics of users can not be formalized. This problem can be solved by using the html_img_parser function and the Go language html parser package. By applying queues and multiple threads to a general-purpose web crawler, rather than a web crawler design that targets a specific site, it is possible to utilize a multiplier that quickly and efficiently searches and collects various web sites in various applications.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.4
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• pp.175-181
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• 2015

In this paper, we propose a design method for a digital filter using software in order to analyze the radio astronomy observation data. Recently the analysis method for radio astronomy observing system is transferring from hardware to software by developing of state-of-the-art of computer system. The existing hardware system is not able to easily change the specification because it is implemented to meet special requirements and it takes a high cost and time. In case of software, however, it has an advantage to implement with small cost if open software is used, and flexibly changes to satisfy the desired specification. But, in order to analyze the massive data like radio astronomy with software, the good performance system is needed for computer. Therefore, this paper proposes a digital filter design method using software with the same performance as that of digital filter implemented with hardware in observation system which is operated by the KVN(Korean VLBI Network). To design a digital filter, the proposed method is performed with standard C language and the simulation is conducted with GNU(GNU's Not Unix) Octave and investigated to show its effectiveness. In addition, for the high speed operation of the designed digital filter, the SSE(Streaming SIMD Extensions) library is adopted for available parallel operation. By the proposed digital filter, the digital filtering is performed for the wide band observation data in the KVN observation mode, the filtering result of narrow band observation has no ripple inside of stop band, and confirmed the effectiveness of the proposed method.

• Journal of KIISE
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• v.42 no.5
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• pp.591-600
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• 2015

SLA (Service Level Agreement) is an essential factor that must be guaranteed to provide a reliable and consistent service to user in cloud computing environment. Especially, a contract between user and service provider with SLA is important in an environment using a cloud service brokerage. The cloud computing is classified into IaaS, PaaS, and SaaS according to IT resources of the various cloud service. The existing SLA is difficult to reflect the quality factors of service, because it only considers factors about the physical Network environment and have no methodological approach. In this paper, we suggested a method to specify the quality characteristics of software and proposed a mechanism and structure that can exchange SLA specification between the service provider and consumer. We defined a meta-model for the SLA specification in the SaaS level, and quality requirements of the SaaS were described by the proposed specification language. Through case studies, we verified proposed specification language that can present a variety of software quality factors. By using the UDDI-based mediation process and architecture to interchange this specification, it is stored in the repository of quality specifications and exchanged during service binding time.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.13-30
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• 1997

Recent improvements of satellite remote sensing sensors which are represented by hyperspectral imaging sensors and high spatial resolution sensors provide a large amount of data, typically several hundred megabytes per one scene. Moreover, increasing information exchange via internet and information super-highway requires the developments of more active service systems for processing and analysing of remote sensing data in order to provide value-added products. In this sense, an advanced satellite data processing system is being developed to achive high performance in computing speed and efficieney in processing a huge volume of data, and to make possible network computing and easy improving, upgrading and managing of systems. JAVA internet programming language provides several advantages for developing software such as object-oriented programming, multi-threading and robust memory managent. Using these features, a satellite data processing system named as GeoPixel has been developing using JAVA language. The GeoPixel adopted newly developed techniques including object-pipe connect method between each process and multi-threading structure. In other words, this system has characteristics such as independent operating platform and efficient data processing by handling a huge volume of remote sensing data with robustness. In the evaluation of data processing capability, the satisfactory results were shown in utilizing computer resources(CPU and Memory) and processing speeds.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.57-65
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• 2021

A hyper-connected intelligence information society is emerging that creates new value by converging IoT, AI, and Bigdata, which are new technologies of the fourth industrial revolution, in all industrial fields. Everything is connected to the network and data is exploding, and artificial intelligence can learn on its own and even intellectual judgment functions are possible. In particular, the Internet of Things provides a new communication environment that can be connected to anything, anytime, anywhere, enabling super-connections where everything is connected. Artificial intelligence technology is implemented so that computers can execute human perceptions, learning, reasoning, and natural language processing. Artificial intelligence is developing advanced technologies such as machine learning, deep learning, natural language processing, voice recognition, and visual recognition, and includes software, machine learning, and cloud technologies specialized in various applications such as safety, medical, defense, finance, and welfare. Through this, it is utilized in various fields throughout the industry to provide human convenience and new values. However, on the contrary, it is time to respond as intelligent and sophisticated cyber threats are increasing and accompanied by potential adverse functions such as securing the technical safety of new technologies. In this paper, we propose a new data modeling method to enable IoT integrated security control by utilizing artificial intelligence technology as a way to solve these adverse functions.

• Information Systems Review
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• v.21 no.1
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• pp.23-38
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• 2019

The social network service (SNS) is one of the important marketing channels, so many companies actively exploit SNSs by posting SNS messages with appropriate content and style for their customers. In this paper, we focused on the psychological distances embedded in the SNS messages and developed a method to measure the psychological distance in SNS message by mixing a traditional content analysis, natural language processing (NLP), and machine learning. Through a traditional content analysis by human coding, the psychological distance was extracted from the SNS message, and these coding results were used for input data for NLP and machine learning. With NLP, word embedding was executed and Bag of Word was created. The Support Vector Machine, one of machine learning techniques was performed to train and test the psychological distance in SNS message. As a result, sensitivity and precision of SVM prediction were significantly low because of the extreme skewness of dataset. We improved the performance of SVM by balancing the ratio of data by upsampling technique and using data coded with the same value in first content analysis. All performance index was more than 70%, which showed that psychological distance can be measured well.

• Journal of The Korean Association For Science Education
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• v.40 no.3
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• pp.321-336
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• 2020

We explore automated scoring models of scientific argumentation. We consider how a new analytical approach using a machine learning technique may enhance the understanding of spoken argumentation in the classroom. We sampled 2,605 utterances that occurred during a high school student's science class on molecular structure and classified the utterances into five argumentative elements. Next, we performed Text Preprocessing for the classified utterances. As machine learning techniques, we applied support vector machines, decision tree, random forest, and artificial neural network. For enhancing the identification of rebuttal elements, we used a heuristic feature-engineering method that applies experts' classification of morphemes of scientific argumentation.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.85-95
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• 2017

The news media report the pledges of presidential candidates, which have important implications for political communication. This study is to investigate the difference between news coverage on the presidential candidate' s pledge and to discuss its implications. The sampled news from the two newspapers were analyzed for content analysis. Frequency analysis and Chi-square analysis are utilized with SPSS. As results, there was no difference in the tone of the article's headlines, but the difference of the tone between the article content was statistically significant. The results means that the media framing affect on the reader's perception. Follow - up study can be suggested a comparative study of past election candidates 'pledge reports, a network analysis for the news language, and a comparative analysis of newspaper coverage and broadcast coverage.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.226-231
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• 2017

Word representation, an important area in natural language processing(NLP) used machine learning, is a method that represents a word not by text but by distinguishable symbol. Existing word embedding employed a large number of corpora to ensure that words are positioned nearby within text. However corpus-based word embedding needs several corpora because of the frequency of word occurrence and increased number of words. In this paper word embedding is done using dictionary definitions and semantic relationship information(hypernyms and antonyms). Words are trained using the feature mirror model(FMM), a modified Skip-Gram(Word2Vec). Sense similar words have similar vector. Furthermore, it was possible to distinguish vectors of antonym words.