• Title/Summary/Keyword: Information based Industry

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An Analysis of the Influence of Digital Media Device and Communication Utilization Capabilities on Entrepreneurial Intention : Focusing on the Mediating Effect of Risk-Taking and Proactiveness (디지털 미디어 기기 및 커뮤니케이션 활용역량이 창업의도에 미치는 영향에 대한 분석 : 위험감수성 및 진취성의 매개효과를 중심으로)

  • Lee, Sang Gil;Leen, Jae Mahn
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.16 no.1
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    • pp.113-126
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    • 2021
  • After the Corona 19 pandemic in the first half of 2020, the business environment has been changed in a very different way. The convergence in digital device would be the keyword of the future business. Due to the Corona 19 incident, the ability to utilize digital media devices has emerged as an important topic as people are focusing on online. The Corona incident has reminded us of how important digitalization is at all points of contact. This study analyzed the effects of digital media device and communication utilization capabilities on entrepreneurial intention by reflecting the mediating effect of risk-taking and proactiveness. For this study, a survey of 250 ordinary people was conducted and finally 212 valid questionnaires were collected. Statistical techniques were analyzed using Amos23. The analysis of the collected data showed that digital media device utilization and communication utilization did not directly affect entrepreneurship intentions, but it was confirmed that entrepreneurship risk-taking would have an intention to start a business. Through this, it was suggested that the development of start-up programs based on entrepreneurship and digital media utilization capabilities should be strengthened in a smart society centered on information and communication to expand job creation for the digital generation.

Analysis of Intrinsic Patterns of Time Series Based on Chaos Theory: Focusing on Roulette and KOSPI200 Index Future (카오스 이론 기반 시계열의 내재적 패턴분석: 룰렛과 KOSPI200 지수선물 데이터 대상)

  • Lee, HeeChul;Kim, HongGon;Kim, Hee-Woong
    • Knowledge Management Research
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    • v.22 no.4
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    • pp.119-133
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    • 2021
  • As a large amount of data is produced in each industry, a number of time series pattern prediction studies are being conducted to make quick business decisions. However, there is a limit to predicting specific patterns in nonlinear time series data due to the uncertainty inherent in the data, and there are difficulties in making strategic decisions in corporate management. In addition, in recent decades, various studies have been conducted on data such as demand/supply and financial markets that are suitable for industrial purposes to predict time series data of irregular random walk models, but predict specific rules and achieve sustainable corporate objectives There are difficulties. In this study, the prediction results were compared and analyzed using the Chaos analysis method for roulette data and financial market data, and meaningful results were derived. And, this study confirmed that chaos analysis is useful for finding a new method in analyzing time series data. By comparing and analyzing the characteristics of roulette games with the time series of Korean stock index future, it was derived that predictive power can be improved if the trend is confirmed, and it is meaningful in determining whether nonlinear time series data with high uncertainty have a specific pattern.

Prospect Theory and Risk Preferences of Real Estate Development Companies (부동산 개발 및 공급 기업의 손익과 경영진의 위험 선호도)

  • Kim, Byungil;Kim, Won Tae;Chung, Do-Bum
    • Korean Journal of Construction Engineering and Management
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    • v.23 no.1
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    • pp.83-88
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    • 2022
  • Companies make decisions with risks such as choosing an investment plan in order to pursue profits. This study explained the decision making of the management of construction companies in South Korea using the tendency to avoid losses in the Prospect Theory. To this end, 20-year financial data of 2,881 companies engaged in real estate development, which have to bear the greatest risk among the construction industry, were collected. The collected companies were roughly classified based on the reference point, and the causal relationship between average return on equity and risk preference by group was empirically analyzed through regression analysis. As a result, it was confirmed that if the average return on equity of a company decreases for the group above the reference point, it tends to select an investment plan with low uncertainty in order not to lose additional money. In addition, it was confirmed that if the average return on equity of a company decreases for the group below the reference point, it tends to select an investment plan with high uncertainty to move to the profit area. This result is exactly consistent with the loss aversion tendency of the Prospect Theory.

Exploring Issues Related to the Metaverse from the Educational Perspective Using Text Mining Techniques - Focusing on News Big Data (텍스트마이닝 기법을 활용한 교육관점에서의 메타버스 관련 이슈 탐색 - 뉴스 빅데이터를 중심으로)

  • Park, Ju-Yeon;Jeong, Do-Heon
    • Journal of Industrial Convergence
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    • v.20 no.6
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    • pp.27-35
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    • 2022
  • The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.

Social Network Analysis of Long-term Standby Demand for Special Transportation (특별교통수단 장기대기수요에 대한 사회 연결망 분석)

  • Park, So-Yeon;Jin, Min-Ha;Kang, Won-Sik;Park, Dae-Yeong;Kim, Keun-Wook
    • Journal of Digital Convergence
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    • v.19 no.5
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    • pp.93-103
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    • 2021
  • The special means of transportation introduced to improve the mobility of the transportation vulnerable met the number of legal standards in 2016, but lack of development in terms of quality, such as the existence of long waiting times. In order to streamline the operation of special means of transportation, long-term standby traffic, which is the top 25% of the wait time, was extracted from the Daegu Metropolitan Government's special transportation history data, and spatial autocorrelation analysis and social network analysis were conducted. As a result of the analysis, the correlation between the average waiting time of special transportation users and the space was high. As a result of the analysis of internal degree centrality, the peak time zone is mainly visited by general hospitals, while the off-peak time zone shows high long-term waiting demand for visits by lawmakers. The analysis of external degree centrality showed that residential-based traffic demand was high in both peak and off-peak hours. The results of this study are considered to contribute to the improvement of the quality of the operation of special transportation means, and the academic implications and limitations of the study are also presented.

A Study on the Comparison of the Virtual Reality Development Environment in Unity and Unreal Engine 4 (유니티와 언리얼 엔진 4 에서의 가상현실 개발환경에 관한 비교연구)

  • Yunsik, Cho;Jinmo, Kim
    • Journal of the Korea Computer Graphics Society
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    • v.28 no.5
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    • pp.1-11
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    • 2022
  • Game engines have the advantage of enabling efficient content production, such as reducing development time, with minimal visual quality guarantees and support for multi-platforms. Recently, game engines have provided various functions that can easily, quickly, and effectively produce immersive content using virtual reality (VR) HMD. Therefore, this study conducts a comparative study on the development environment in VR content production using Oculus Quest 2 HMD, focusing on Unity and Unreal game engines, which are widely used in the content production industry, including games. First, we compare the basic setup process of building a development environment using Oculus Quest 2 HMD and a dedicated controller based on a VR template project that includes the minimum functions and settings provided by each engine. Next, we present a simple experience environment that can interact in a virtual environment and compare the development environment to use a dedicated controller and the process of building a development environment that directly utilizes hands through the hand tracking function provided by Oculus Quest 2. Through this process, we will understand the basic process of building a VR development environment, and at the same time, we will check the characteristics and differences of the engine and use it as a research that can be applied to various immersive content production.

Experimental Comparison of Network Intrusion Detection Models Solving Imbalanced Data Problem (데이터의 불균형성을 제거한 네트워크 침입 탐지 모델 비교 분석)

  • Lee, Jong-Hwa;Bang, Jiwon;Kim, Jong-Wouk;Choi, Mi-Jung
    • KNOM Review
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    • v.23 no.2
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    • pp.18-28
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    • 2020
  • With the development of the virtual community, the benefits that IT technology provides to people in fields such as healthcare, industry, communication, and culture are increasing, and the quality of life is also improving. Accordingly, there are various malicious attacks targeting the developed network environment. Firewalls and intrusion detection systems exist to detect these attacks in advance, but there is a limit to detecting malicious attacks that are evolving day by day. In order to solve this problem, intrusion detection research using machine learning is being actively conducted, but false positives and false negatives are occurring due to imbalance of the learning dataset. In this paper, a Random Oversampling method is used to solve the unbalance problem of the UNSW-NB15 dataset used for network intrusion detection. And through experiments, we compared and analyzed the accuracy, precision, recall, F1-score, training and prediction time, and hardware resource consumption of the models. Based on this study using the Random Oversampling method, we develop a more efficient network intrusion detection model study using other methods and high-performance models that can solve the unbalanced data problem.

A Study on Online Sharing Platforms and Sub-Contents in the Field of the Performing Arts - Focusing on the Case of 『Cirque du Soleil Entertainment』 (공연예술분야 온라인 공유 플랫폼 및 서브 콘텐츠 연구 - 『태양의 서커스 엔터테인먼트』 사례를 중심으로)

  • Kim, Ga-Eun;Park, Jin-Won
    • The Journal of the Korea Contents Association
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    • v.22 no.2
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    • pp.22-34
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    • 2022
  • This study examines the forms and current status of online performance content production in the field of the performing arts through diversified video media platforms. For this, it studied the leading case of Cirque du Soleil Entertainment and analyzed the unique brand value innovation elements of Cirque du Soleil, the background and current status of the digital hub platform of "Cirque Connect", and its various sub-contents that have diversified original contents. Digital platform applications and sub-content production in the field of the performing arts require an understanding of the needs of the public, who are familiar with media content appreciation, and strategic planning that takes into consideration everything from the initial stages of performance planning to the creation of varied sub-contents. This will promote the improvement of sub-content quality and increase the product value of digital contents in the performing arts through distinctions made from other various forms of cultural and artistic contents. environments in which information from various perspectives related to performance works can easily be accessed through online platforms will enhance the popularity of the performing arts field and allow the performing arts industry to expand its base in rapidly changing cultural enjoyment methods. For the performing arts field to be competitive within cultural trends that are being diversified, the most important tasks to be completed are gaining brand value innovation that enhances the artistic and cultural value of performance works and based on this, producing various sub-contents.

Analysis of Vehicle Selection Factors Using Energy Census (에너지총조사를 이용한 차량 선택 요인 분석)

  • Shin, Him Chul;Won, DooHwan
    • Environmental and Resource Economics Review
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    • v.31 no.2
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    • pp.291-317
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    • 2022
  • This study tried to analyze the factors affecting consumers' vehicle selection for the spread of eco-friendly vehicles. We used the energy census data for this purpose, and although the energy census collects useful information from a large number of samples, it has been limitedly used to create simple statistics in many cases. Based on 2,771 transport sector microdata from the 2017 Energy Census, we collected vehicle price, fuel efficiency, and number of vehicle models, which are alternative characteristic variables that change according to consumers' choice, and converted and analyzed data to enable conjoint analysis. The analysis results in two-folds. First, it was confirmed that the official fuel efficiency of a vehicle and the fuel cost, which is affected by changes in the relative price of each fuel, are important variables in selecting an eco-friendly vehicle. In order to achieve the goal of spread of eco-friendly vehicles, it is necessary to develop technologies to improve fuel efficiency and set appropriate electric rates for charging electric vehicles. Second, an increase in the number of vehicle models through the expansion of the eco-friendly car industry and market also affects consumers' choice of eco-friendly vehicles, so efforts to expand the supply of eco-friendly vehicles will be an important factor. In addition, it is also significant that this study showed that the use of the energy census can be diversified by deriving meaningful policy implications using the results of the energy census periodically conducted in the country without a separate survey.

Development of simultaneous detection method for living modified cotton varieties MON757, MON88702, COT67B, and GHB811 (유전자변형 면화 MON757, MON88702, COT67B, GHB811의 동시검출법 개발)

  • Il Ryong Kim;Min-A Seol;A-Mi Yoon;Jung Ro Lee;Wonkyun Choi
    • Korean Journal of Environmental Biology
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    • v.39 no.4
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    • pp.415-422
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    • 2021
  • Cotton is an important fiber crop, and its seeds are used as feed for dairy cattle. Crop biotechnology has been used to improve agronomic traits and quality in the agricultural industry. The frequent unintentional release of LM cotton into the environment in South Korea is attributed to the increased application of living modified (LM) cotton in food, feed, and processing industries. To identify and monitor the LM cotton, a method for detecting the approved LM cotton in South Korea is required. In this study, we developed a method for the simultaneous detection of four LM cotton varieties, MON757, MON88702, COT67B, and GHB811. The genetic information of each LM event was obtained from the European Commission-Joint Research Centre and Animal and Plant Quarantine Agency. We designed event-specific primers to develop a multiplex PCR method for LM cotton and confirmed the specific amplification. Using specificity assay, random reference material(RM) mixture analysis and limit of detection(LOD), we verified the accuracy and specificity of the multiplex PCR method. Our results demonstrate that the method enabled the detection of each event and validation of the specificity using other LM RMs. The efficiency of multiplex PCR was further verified using a random RM mixture. Based on the LOD, the method identified 25 ng of template DNA in a single reaction. In summary, we developed a multiplex PCR method for simultaneous detection of four LM cotton varieties, for possible application in LM volunteer analysis.