• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.861-866
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• 2023

Unlike conventional smart farms that require chemical fertilizers and large spaces, aquaponics farming, which utilizes the symbiotic relationship between aquatic organisms and crops to grow crops even in abnormal environments such as environmental pollution and climate change, is being actively researched. Different crops require different environments and nutrients for growth, so it is necessary to configure the ratio of aquatic organisms optimized for crop growth. This study proposes a method to measure the degree of growth based on area and volume using image processing techniques in an aquaponics environment. Tilapia, carp, catfish, and lettuce crops, which are aquatic organisms that produce organic matter through excrement, were tested in an aquaponics environment. Through 2D and 3D image analysis of lettuce and real-time data analysis, the growth degree was evaluated using the area and volume information of lettuce. The results of the experiment proved that it is possible to manage cultivation by utilizing the area and volume information of lettuce. It is expected that it will be possible to provide production prediction services to farmers by utilizing aquatic life and growth information. It will also be a starting point for solving problems in the changing agricultural environment.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.238-255
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• 2023

In this study, we derived the characteristic factors of the cluster as measurable variables, and attempted to clarify the characteristics of the apparel sewing areas in Changsin-dong, Doksan-dong, and Jangwi-dong. Based on these results, a comparative analysis was conducted to see how the demand for the government's support policy differs for each agglomeration area. Materials were collected through face-to-face questionnaires targeting tenant companies in the three regions. As a result of the analysis, Changsin-dong was identified as an "innovative growth type," Doksan-dong as a "networking type," and Jangwi-dong as a "specialized localization type." As a result of the research on policy demands, the policy demands of the three agglomerations appeared different, but Changsin-dong preferred capacity building, Doksan-dong preferred information provision, and Jangwi-dong favored policy means of benefit. It was confirmed that even among clusters of the same apparel sewing industry, the formation process and characteristics are different, and as a result, the demand for policy instruments is also different. Policy recommendations include understanding the characteristics and policy demands of each agglomeration area through periodic fact-finding surveys, and recommending the establishment and implementation of differentiated support policies that match the characteristics of each agglomeration area.

• Information Systems Review
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• v.25 no.1
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• pp.189-212
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• 2023

This study uses various methods, including media analysis, expert interviews, and large-scale surveys, to derive notable digital business trends in 2023. Most trend studies have yet to deal with digital business trends in Korea. They also often have limitations in the objectivity of the results using unclear methods. On the other hand, this study emphasizes the validity of the results by collecting opinions from Korean digital business experts in various fields. First, Korean IT news articles were collected and analyzed through topic modeling analysis. Then, based on the results, interviews were conducted with 13 academic and industrial experts to derive 16 IT business trend candidates. Then, a survey was conducted on 210 experts to finalize the list of Korean IT business trends. Finally, to compare overseas and domestic views, we conducted an additional survey using the items developed by the Society for Information Management, SIM. This study is meaningful in that it drew prospects for digital business trends in consideration of the domestic business environment by scientifically converging various opinions of Korean digital business leaders. Our study contributes to developing strategies for IT technology and IT service business markets.

• The Transactions of the Korea Information Processing Society
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• v.13 no.9
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• pp.395-403
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• 2024

Recently, with the advancement of technology, the automotive industry has seen an increase in network connectivity. CAN (Controller Area Network) bus technology enables fast and efficient data communication between various electronic devices and systems within a vehicle, providing a platform that integrates and manages a wide range of functions, from core systems to auxiliary features. However, this increased connectivity raises concerns about network security, as external attackers could potentially gain access to the automotive network, taking control of the vehicle or stealing personal information. This paper analyzed abnormal messages occurring in CAN and confirmed that message occurrence periodicity, frequency, and data changes are important factors in the detection of abnormal messages. Through DBC decoding, the specific meanings of CAN messages were interpreted. Based on this, a model for classifying abnormalities was proposed using the GRU model to analyze the periodicity and trend of message occurrences by measuring the difference (residual) between the predicted and actual messages occurring within a certain period as an abnormality metric. Additionally, for multi-class classification of attack techniques on abnormal messages, a Random Forest model was introduced as a multi-classifier using message occurrence frequency, periodicity, and residuals, achieving improved performance. This model achieved a high accuracy of over 99% in detecting abnormal messages and demonstrated superior performance compared to other existing models.

• Korean Security Journal
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• no.36
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• pp.177-200
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• 2013

As we enter a high industrial society that widens the gap between the rich and poor, demand for the security services has grown explosively. With the growth in quantitative expansion of security services, people have also placed increased requirements on more sophisticated and diversified security services. Consequently, market outlook for private security services industry is positive. However, Korea's private security services companies are experiencing difficulties in finding a direction to capture this new market opportunity due to their small sizes and lack of management-strategic thinking skills. Therefore, we intend to offer a direction of development for our private security services industry using a management-strategy theory and the Analytic Hierarchy Process(AHP), a structured decision-making method. A resource-based theory is one of the important management strategy theories. It explains that a company's overall performance is primarily determined by its competitive resources. Using this theory, we could analyze a company's unique resources and core competencies and set a strategic direction for the company accordingly. The usefulness and validity of this theory has been demonstrated as it has often been subject to empirical verification since 1990s. Based on this theory, we outlined a set of basic procedures to establish a management strategy for the private security services companies. We also used the AHP method to identify competitive resources, core competencies, and strategies from private security services companies in contrast with public companies. The AHP method is a technique that can be used in the decision making process by quantifying experts' knowledge and unstructured problems. This is a verified method that has been used in the management decision making in the corporate environment as well as for the various academic studies. In order to perform this method, we gathered data from 11 experts from academic, industrial, and research sectors and drew distinctive resources, competencies, and strategic direction for private security services companies vis-a-vis public organizations. Through this process, we came to the conclusion that private security services companies generally have intangible resources as their distinctive resources compared with public organization. Among those intangible resources, relational resources, customer information, and technologies were analyzed as important. In contrast, tangible resources such as equipment, funds, distribution channels are found to be relatively scarce. We also found the competencies in sales and marketing and new product development as core competencies. We chose a concentration strategy focusing on a particular market segment as a strategic direction considering these resources and competencies of private security services companies. A concentration strategy is the right fit for smaller companies as a strategy to allow them to focus all of their efforts on target customers in a single segment. Thus, private security services companies would face the important tasks such as developing a new market and appropriate products for such market segment and continuing marketing activities to manage their customers. Additionally, continuous recruitment is required to facilitate the effective use of human resources in order to strengthen their marketing competency in a long term.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.199-232
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• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.63-74
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• 2024

The fundamental basis for revitalizing cultural resources and developing content is national heritage(cultural property). In national heritage, cultural heritage is a tangible cultural heritage that represents the uniqueness of history and tradition, identity, and changes in life. In the case of museums, the collections (a museum-owned cultural heritage) represent the unique characteristics of the institution. In South Korea, it is recommended that museum collections be registered and used in the Cultural Heritage Standard Management System so that cultural heritage can be managed and utilized in connection with academics, industry, and administration. However, due to a lack of awareness of modern and contemporary heritage, the thematic classification chronology of the system was set mainly before the Joseon Dynasty, and a cultural heritage classification system suitable for national land information has not been established. Therefore, this study aims to propose a classification system for cadastral cultural heritage, based on the modern era when cadastral terminology was first used, using the cultural heritage owned by the LX Museum. Cadastral cultural heritage is characterized by the fact that although it is a field of specialized technology, the surveying or the production of it is not done by specific individuals only, and that while the production is professional, there are many educational aspects in its use. Therefore, unlike other specialized museum collections that are classified based on the functional aspects of their production methods, intended use, and creators, the classification method for cadastral cultural artifacts should be based on the characteristics of the cadastral tools and the outputs. This classification follows a three-tier stages with reference to the items in the Cultural Heritage Standard Management System. This classification aims at the effective use of knowledge by categorizing concepts and systematizing the subjects of data into a series of orders. A safe conservation and management environment for cadastral cultural heritage can be established, and academic and socio-cultural interpretation of the collection is possible by this classfication. Moreover, It is also expected to serve the basis for the national land information as well as searching for the national land information research, planning a exhibition, and the field of education in museum.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Journal of Plant Biotechnology
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• v.42 no.4
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• pp.326-335
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• 2015

Citrus is an economically important fruit tree with the largest amount of fruit production in the world. It provides important nutrition such as vitamin C and other health-promoting compounds including its unique flavonoids for human health. However, it is classified into the most difficult crops to develop new cultivars through conventional breeding approaches due to its long juvenility and some unique reproductive biological features such as gamete sterility, nucellar embryony, and high level of heterozygosity. Due to global warming and changes in consumer trends, establishing a systematic and efficient breeding programs is highly required for sustainable production of high quality fruits and diversification of cultivars. Recently, reference genome sequences of sweet orange and clementine mandarin have been released. Based on the reference whole-genome sequences, comparative genomics, reference-guided resequencing, and genotyping-by-sequencing for various citrus cultivars and crosses could be performed for the advance of functional genomics and development of traits-related molecular markers. In addition, a full understanding of gene function and gene co-expression networks can be provided through combined analysis of various transcriptome data. Analytic information on whole-genome and transcriptome will provide massive data on polymorphic molecular markers such as SNP, INDEL, and SSR, suggesting that it is possible to construct integrated maps and high-density genetic maps as well as physical maps. In the near future, integrated maps will be useful for map-based precise cloning of genes that are specific to citrus with major agronomic traits to facilitate rapid and efficient marker-assisted selection.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.119-129
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• 2011

Vision-based Human computer interaction is an emerging field of science and industry to provide natural way to communicate with human and computer. Especially, recent increasing demands for mobile augmented reality require the development of efficient interactive technologies between the augmented virtual object and users. This paper presents a novel approach to construct marker-less mobile augmented reality object and control the object. Replacing a traditional market, the human hand interface is used for marker-less mobile augmented reality system. In order to implement the marker-less mobile augmented system in the limited resources of mobile device compared with the desktop environments, we proposed a method to extract an optimal hand region which plays a role of the marker and augment object in a realtime fashion by using the camera attached on mobile device. The optimal hand region detection can be composed of detecting hand region with YCbCr skin color model and extracting the optimal rectangle region with Rotating Calipers Algorithm. The extracted optimal rectangle region takes a role of traditional marker. The proposed method resolved the problem of missing the track of fingertips when the hand is rotated or occluded in the hand marker system. From the experiment, we can prove that the proposed framework can effectively construct and control the augmented virtual object in the mobile environments.