• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.121-128
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• 2019

An Internet of Things(IoT) technology which provides intelligent services by combining context-awareness based intelligences, inter-communication is made of between things and things or between things and person through the network connected with intelligent things is spreading rapidly. Especially as this technology is converged into smart device, mobile, cloud, big data technologies, it is applied into various domains. Therefore, this is different from existing Web or Mobile Application. New types of IoT applications are emerging by adapting IoT into Web or mobile. Because IoT application is not only focused on software but also considering hardware or things aspect, there are limitations existing development process. Existing development processes don't consider analysis and design techniques considering both hardware and things. We propose not only a meta-model for development process which can support IoT application's development but also meta-models for main activities in this paper. Especially we define modeling elements by using UML's extension mechanisms, provide development process, and suggest design techniques how to apply those elements into IoT application's modeling phase. Because there are many types of IoT application's type, we propose an Android and Arduino-based on IoT application as a case study. We expect that proposed technique can be applied into many of various IoT application development and design with a form of flexible and extensible as well as main functionalities or elements are more concretely described. As a result, it brings IoT application's flexibility and the effect of quality improvement.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.77-100
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• 2018

The objectives of this study is to present a discovering process of interdisciplinary convergence technology using text mining of big data. For the convergence research of biotechnology(BT) and information communications technology (ICT), the following processes were performed. (1) Collecting sufficient meta data of research articles based on BT terminology list. (2) Generating intellectual structure of emerging technologies by using a Pathfinder network scaling algorithm. (3) Analyzing contents with topic modeling. Next three steps were also used to derive items of BT-ICT convergence technology. (4) Expanding BT terminology list into superior concepts of technology to obtain ICT-related information from BT. (5) Automatically collecting meta data of research articles of two fields by using OpenAPI service. (6) Analyzing contents of BT-ICT topic models. Our study proclaims the following findings. Firstly, terminology list can be an important knowledge base for discovering convergence technologies. Secondly, the analysis of a large quantity of literature requires text mining that facilitates the analysis by reducing the dimension of the data. The methodology we suggest here to process and analyze data is efficient to discover technologies with high possibility of interdisciplinary convergence.

• Convergence Security Journal
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• v.15 no.4
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• pp.11-18
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• 2015

The new environments arrive such as ICT convergence, cloud computing, and big data, etc., how to take advanta ge of the existing software engineering technologies has become an important key. In addition, the importance of re quirement analysis for secure software and design phase has been shown in the IoT environment While the existing studies have focused on the utilization of the technique applied to IoT environment, the studies for enhancing analys is and design, the prerequisite steps for safely appling these techniques to the site, have been insufficient. So, we tr y to organize research trends based on software engineering and analyze their relationship in this paper. In detail, w e classify the research trends of software engineering to perform research trends meta-analysis, and analyze an ann ual development by years. The flow of the major research is identified by analyzing the correlation of the key word s. We propose the strategies for enhancing the utilization of software engineering techniques to develop high-quality software in the IoT environment.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.97-113
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• 2016

Due to the growth of internet data and the rapid development of internet technology, "big data" analysis is actively conducted to analyze enormous data for various purposes. Especially in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of existing structured data analysis. Various studies on sentiment analysis, the part of text mining techniques, are actively studied to score opinions based on the distribution of polarity of words in documents. Usually, the sentiment analysis uses sentiment dictionary contains positivity and negativity of vocabularies. As a part of such studies, this study tries to construct sentiment dictionary which is customized to specific data domain. Using a common sentiment dictionary for sentiment analysis without considering data domain characteristic cannot reflect contextual expression only used in the specific data domain. So, we can expect using a modified sentiment dictionary customized to data domain can lead the improvement of sentiment analysis efficiency. Therefore, this study aims to suggest a way to construct customized dictionary to reflect characteristics of data domain. Especially, in this study, movie review data are divided by genre and construct genre-customized dictionaries. The performance of customized dictionary in sentiment analysis is compared with a common sentiment dictionary. In this study, IMDb data are chosen as the subject of analysis, and movie reviews are categorized by genre. Six genres in IMDb, 'action', 'animation', 'comedy', 'drama', 'horror', and 'sci-fi' are selected. Five highest ranking movies and five lowest ranking movies per genre are selected as training data set and two years' movie data from 2012 September 2012 to June 2014 are collected as test data set. Using SO-PMI (Semantic Orientation from Point-wise Mutual Information) technique, we build customized sentiment dictionary per genre and compare prediction accuracy on review rating. As a result of the analysis, the prediction using customized dictionaries improves prediction accuracy. The performance improvement is 2.82% in overall and is statistical significant. Especially, the customized dictionary on 'sci-fi' leads the highest accuracy improvement among six genres. Even though this study shows the usefulness of customized dictionaries in sentiment analysis, further studies are required to generalize the results. In this study, we only consider adjectives as additional terms in customized sentiment dictionary. Other part of text such as verb and adverb can be considered to improve sentiment analysis performance. Also, we need to apply customized sentiment dictionary to other domain such as product reviews.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.301-310
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• 2006

Typically, we needs enormous national budget for the flood control project and so the project usually has big influence on the national economy. Therefore, the reliable estimation of flood damage is the key issue for the economic analysis of the flood control project. This study aims to provide a GIS based technique for distributed flood damage estimation. We consider two aspects of engineering and economic sides, which are the inundation analysis and MD-FDA (Multi-Dimensional Flood Damage Analysis), for the flood damage assessment. We propose the analysis framework and data processing using GIS for assessing flood damages. The proposed methodology is applied to the flood control channel project for flood disaster prevention in Mokgamcheon/Dorimcheon streams and this study presents the detailed GIS database and the assessment results of flood damages. This study may have the worth in improving practical usability of MD-FDA and also providing research direction for combining economic side with the engineering aspect. Also this distributed technique will help decision-making in evaluating the feasibility of flood damage reduction programs for structural and nonstructural measures.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1761-1775
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• 2022

Due to unpredictable climate change, the frequency of occurrence of water-related disasters and the scale of damage are also continuously increasing. In terms of disaster management, it is essential to identify the damaged area in a wide area and monitor for mid-term and long-term forecasting. In the field of water disasters, research on remote sensing technology using Synthetic Aperture Radar (SAR) satellite images for wide-area monitoring is being actively conducted. Time-series analysis for monitoring requires a complex preprocessing process that collects a large amount of images and considers the noisy radar characteristics, and for this, a considerable amount of time is required. With the recent development of cloud computing technology, many platforms capable of performing spatiotemporal analysis using satellite big data have been proposed. Google Earth Engine (GEE)is a representative platform that provides about 600 satellite data for free and enables semi real time space time analysis based on the analysis preparation data of satellite images. Therefore, in this study, immediate water disaster damage detection and mid to long term time series observation studies were conducted using GEE. Through the Otsu technique, which is mainly used for change detection, changes in river width and flood area due to river flooding were confirmed, centered on the torrential rains that occurred in 2020. In addition, in terms of disaster management, the change trend of the time series waterbody from 2018 to 2022 was confirmed. The short processing time through javascript based coding, and the strength of spatiotemporal analysis and result expression, are expected to enable use in the field of water disasters. In addition, it is expected that the field of application will be expanded through connection with various satellite bigdata in the future.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.45-52
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• 2021

Although many studies have been conducted to identify unknown attacks in cyber security intrusion detection systems, studies based on outliers are attracting attention. Accordingly, we identify outliers by defining categories for unknown attacks. The unknown attacks were investigated in two categories: first, there are factors that generate variant attacks, and second, studies that classify them into new types. We have conducted outlier studies that can identify similar data, such as variants, in the category of studies that generate variant attacks. The big problem of identifying anomalies in the intrusion detection system is that normal and aggressive behavior share the same space. For this, we applied a technique that can be divided into clear types for normal and attack by discrete wavelet transformation and detected anomalies. As a result, we confirmed that the outliers can be identified through One-Class SVM in the data reconstructed by discrete wavelet transform.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.819-829
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• 2020

This empirical research is aimed at testing the relationship of the big five personality traits namely openness to experience, extraversion, consciousness, agreeableness, neuroticism, and risk aversion with the investment intention of individual investors belonging to Balochistan, Pakistan. The primary data is collected through a self-administered questionnaire (a structured form that consists of a series of closed-ended and open-ended questions) from a sample of 397 active individual investors belonging to different districts of the province. The data is empirically analyzed by applying the Partial Least Square (PLS) path modeling technique by using the estimation package available in Smart-PLS. The findings of this study suggest that all the variables are statistically significant with investors' investment intention with risk aversion as the strongest predictor. Moreover, openness to experience, extraversion, consciousness, agreeableness, and risk are significantly and positively related to an investor's investment intention, whereas neuroticism is negatively related to an investor's investment intention. The results extended by this study can be used by financial planners and investment bankers to channelize the available financial resources in diversified portfolios. The results will help financial planners to make available diverse investment alternatives for investors in Balochistan, thus catering to their unique needs. Academia must offer courses on contemporary finance paradigm based on behavioral finance to enable future business graduates to make wise financial decisions.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.39 no.4
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• pp.1-9
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• 2021

The purpose of this study was to determine the definition of traditional landscape and the appropriate English notation. To confirm the appropriate concept, the charter's relevant terminology was synthesised and the meaning of the vocabulary used in international studies was examined. ICOMOS The Charter on Historic Gardens(The Florebce Charter, 1981), ICOMOS-IFLA Document on Historic Urban Parks(New Delhi, 2017), and UNESCO Recommendation on The Historic Urban Landscape(Paris, 2011) were analysed to examine the concept, and the words describing definitions, space, objects, value, and activity were arranged. Big data was used to analyse the research literature related to overseas traditional landscapes. This study examined the characteristics of each word and examined the appropriate name for expressing the historic and cultural characteristics of landscape in research literature, which included traditional, historic, cultural, classical, vernacular, landscape-related gardens, parks, and landscape words related to historic culture. Consequently, the International Charter declared the suitability of 'historic' gardens and parks, as well as traditional landscape for expressing unique designs, composition technique, and ecological meaning of Korea, while historic landscape was deemed suitable for explaining gardens and parks in landscape history.