• 문화기술의 융합
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• 제9권1호
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• pp.691-695
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• 2023

현재 자동화계측 시스템의 계측 결과 활용도는 매우 낮고 단편적인 측정결과 만을 제공하는 수준이다. 본 연구에서는 실시간으로 측정된 방대한 데이터값을 클라우드로 전송하여 빅데이터를 구축하고 파이썬 기반의 알고리즘을 이용하여 획득한 자동화계측 데이터를 고정밀-신뢰도를 갖는 구조물 거동 분석 3D Display 시스템을 연구하고자 한다. 연구결과, 실시간으로 관리자에게 구조물의 거동을 평가할 수 있는 시스템으로서 계측 데이터의 종류 및 센서의 종류와 무관하게 큰 제약 없이 실시간으로 분석데이터를 제공하고 3D Display로 도출하였다. 또한 관리자가 구조물의 거동 그래프를 실시간으로 파악하고 데이터 분석을 통해 구조물의 취약부 도출을 보다 쉽게 파악할 수 있을 것으로 분석되었다. 향후 과거와 현재 데이터를 이용하여 구조물의 거동을 3차원으로 분석함으로써 현실성 있는 구조물의 보수, 보강 및 유지 관리 측면에서 보다 실효성 있는 측정 결과를 확보할 수 있을 것으로 분석되었다.

• Journal of Information Technology Applications and Management
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• 제26권3호
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• pp.121-134
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• 2019

The Fourth Industrial Revolution has differentiated technologies such as artificial intelligence, IoT(Internet of things), big data, and mobile. As the civilization develops more and more, humanity enjoy the cultural activities more than economic activity for the food and shelter. The platform structure based on the advanced information technology of the present will expand the cultural contents area in a variety of ways. Cultural contents respond sensitively to changes in consumer and will be useful experiences of human activities. Therefore, it should be noted again that the contents industry should not be limited to the discussion of the application of the fourth technology, but should be produced with emphasis on useful experiences of human being. In other words, the discussion of human activities around cultural contents should be focused on how to apply beyond the use of fourth industrial technology. Therefore, it is necessary to analyze the basis of the successful storytelling of the planning stage to connect the fourth industrial technology and human useful experience as a method for developing cultural contents, and to build and propose a model as a strategic method. This study analyzes domestic and foreign cases made by using big data among the visual contents which show continuous increase of consumption among culture industry field, and draws success factors and limit points. Next, we extract what is the successful matching factor that influenced consumer 's consciousness, and find out that the structure of culture prototype has been applied in the long history of mankind, and presents it as a storytelling model. Through the above research, this study aims to present a new interpretation and creative activity of cultural contents by presenting a storytelling model as a methodology for connecting creative knowledge, away from the general interpretation of social phenomenon applied with big data.

• 정보보호학회논문지
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• 제33권3호
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• pp.427-435
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• 2023

카디널리티 추정은 실생활의 많은 곳에서 사용되며, 큰 범위의 데이터를 처리하는 데 근본적 문제이다. 인터넷이 빅데이터의 시대로 넘어가며 데이터의 크기는 점점 커지고 있지만, 작은 온칩 캐시 메모리만을 이용하여 카디널리티 추정이 이뤄진다. 메모리를 효율적으로 사용하기 위해서, 지금까지 많은 방법이 제안되었다. 그러나, 이러한 알고리즘에서는 estimator 간의 노이즈 발생으로 인해 정확도가 떨어지는 일이 발생한다. 이 논문에서는 노이즈를 최소화하는데 중점을 뒀다. 우리는 여러 개의 데이터 구조를 제안하여 각 estimator가 데이터 구조 수만큼의 추정값을 가지고, 이 중 가장 작은 값을 선택하여 노이즈를 최소화한다. 실험을 통해 이 방법이 이전의 가장 좋은 방법과 비교했을 때, 플로우당 1 bit와 같은 작은 메모리를 사용하면서 더 좋은 성능을 보이는 것을 확인했다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권4호
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• pp.313-321
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• 2014

In the current era of data-intensive services, the handling of big data is a crucial issue that affects almost every discipline and industry. In this study, we propose a classification method for large volumes of numeric data, which is implemented in a distributed programming framework, i.e., MapReduce. The proposed method partitions the data space into a grid structure and it then models the probability distributions of classes for grid cells by collecting sufficient statistics using distributed MapReduce tasks. The class labeling of new data is achieved by k-nearest neighbor classification based on Bayesian inference.

• 한국인터넷방송통신학회논문지
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• 제14권1호
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• pp.189-193
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• 2014

네트워크 서비스는 로컬서비스와 결합하면서 생활밀착형 서비스로 발전하고 있다. 생활밀착형 서비스는 기존의 모바일 서비스와는 달리, 위치정보와 로컬정보 그리고 소셜 네트워크서비스 정보 등을 모아 개인화된 서비스를 제공할 것으로 예상된다. 여러 정보를 모아 처리하는 과정에서 빅데이터 기술, 클라우드 기술 등이 필요하다. 이미 이에 대한 효율성 높은 알고리즘이 연구되고 있으나 반면, 생활 밀착형 서비스 모델 또는 빅데이터 환경에서의 프라이버시 보호 모델에 대한 연구는 상대적으로 미흡한 편이다. 이 글은 생활밀착형 서비스에 활용될 빅데이터 기술이 야기하는 프라이버시 문제에 대하여 구조혈 중심으로 다룬다.

• International Journal of Internet, Broadcasting and Communication
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• 제14권2호
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• pp.206-211
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• 2022

As the level of consumption is improved and cultural life is pursued, the consumer's consciousness structure is rapidly changing, and the demand for product selection level, variety, and quality is becoming more diverse. The restaurant economy is falling due to the prolonged COVID-19, the economic recession, income decline, and changes in population structure and lifestyle, but the Meal- kit market is growing rapidly. This study aims to identify the consumer perception of Meal-kit, which is rapidly growing as an alternative to existing meals in the fields of dining out, food, and distribution due to the development of technology and social environment using big data. As a result of the analysis, the keywords with the highest frequency of appearance were in the order of Meal-kit, Cooking, Product, Launching, and Market and were divided into 8 groups through the CONCOR analysis. We want to identify consumer trends related to the key keywords of Meal-kit, present effective data related to Meal-kit demand for Meal-kit specialized companies, and provide implications for establishing marketing strategies for differentiated competitive advantage.

• 정보보호학회논문지
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• 제29권2호
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• pp.439-449
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• 2019

ICBMA(IoT, Cloud, Big Data, Mobile, AI)로 대변되는 정보기술의 발전은 데이터의 급증과 이를 수용하기 위한 데이터센터의 수적, 양적 증가로 이어지고 있다. 이에 데이터센터를 사회 중요 기반시설로 인식하고, 테러 공격 대응 등 안전성 확보를 위해서는 사전에 물리보안 위협의 식별이 매우 중요하다. 본 논문에서는 위협의 식별과 분류를 쉽게 처리할 목적으로 물리보안 위협 분할도(PS-TBS)를 개발하고, 전문가 설문조사를 통하여 개발 된 물리보안 위협 분할도의 타당성과 효용성을 검증한다. 또한 위협 분할도의 항목에 대해 상세 정의를 통해 실무 활용을 통한 물리보안 수준 향상에 기여하고자 한다.

• 시스템엔지니어링학술지
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• 제11권2호
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• pp.13-29
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• 2015

With the era of big data, the big data has been expected to have a large impact in the NPP safety areas. Although high interests of the big data for the NPP safety, only a limited researches concerning this issue are revealed. Especially, researches on the logical/physical structure and systematic design methods for the big data platform for the NPP safety were not dealt with. In this research, we design a new big data pilot platform for the NPP safety especially focusing on health monitoring and early warning services. For this, we propose a tailored design process based on SE approaches to manage inherent high complexities of the platform design. The proposed design process is consist of several steps from elicitate stakeholders to integration test via define operational concept and scenarios, and system requirements, design a conceptual functional architecture, select alternative physical modules for the derived functions and assess the applicability of the alternative modules, design a conceptual physical architecture, implement and integrate the physical modules. From the design process, this paper covers until the conceptual physical architecture design. In the following paper, the rest of the design process and results of the field test will be shown.

• 한국정보시스템학회지:정보시스템연구
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• 제30권1호
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• pp.21-44
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• 2021

Purpose The opportunities and approaches to big data have grown in various ways in the digital era. Business analytics is nowadays an inevitable strategy for organizations to earn a competitive advantage in order to survive in the challenged environments. The purpose of this study is to analyze the intellectual structure of business analytics literature to have a better insight for the organizations to the field. Design/methodology/approach This research analyzed with the data extracted from the database Web of Science. Total of 427 documents and 23,760 references are inserted into the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure of the business analytics. We performed clustering analysis, burst detection and timeline analysis with the data. Findings We identified seven sub- areas of business analytics field. The top four sub-areas are "Big Data Analytics Infrastructure", "Performance Management System", "Interactive Exploration", and "Supply Chain Management". We also identified the top 5 references with the strongest citation bursts including Trkman et al.(2010) and Davenport(2006). Through timeline analysis we interpret the clusters that are expected to be the trend subjects in the future. Lastly, limitation and further research suggestion are discussed as concluding remarks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권2호
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• pp.583-600
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• 2014

Social media is considered a valuable platform for gathering and analyzing the collective and subconscious opinions of people in Internet and mobile environments, where they express, explicitly and implicitly, their daily preferences for brands and products. Extracting and tracking the various attitudes and concerns that people express through social media could enable us to categorize brands and decipher individuals' cognitive decision-making structure in their choice of brands. We investigate the cognitive network structure of consumers by building an inter-category map through the mining of big data. In so doing, we create an improved online recommendation model. Building on economic sociology theory, we suggest a framework for revealing collective preference by analyzing the patterns of brand names that users frequently mention in the online public sphere. We expect that our study will be useful for those conducting theoretical research on digital marketing strategies and doing practical work on branding strategies.