• Journal of Digital Convergence
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• v.13 no.2
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• pp.35-42
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• 2015

As the value of Bigdata has been recognized importantly, public agencies including the government, private sector, etc. began to have an interest in Big Data. As there are sources of various data, and a variety of planning and analysis methods based on these sources has emerged, It is true that Bigdata will become a tool for creation of the new high qualitied information and decision making based on new insights. The purpose of this study is to find an alternative to the subway congestion problem that is not improved even though the various measures. In this study, we tried to explore approaches for ways to improve the congestion of the Seoul Subway using Seoul Metropolitan public data. Lastly, this study derived a policy alternative to establish new bus route that runs around the metro station that have a high level of congestion.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.95-107
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• 2022

With the rapid development of Internet of Things sensor devices and big data processing techniques, Internet of Things sensor-based information systems have been applied in various industries. Depending on the industry in which the information systems are applied, the accuracy of the information derived can affect the industry's efficiency and safety. Therefore, security techniques that protect sensing data from security attacks and enable information systems to derive accurate information are essential. In this paper, we examine security threats targeting each processing step of an Internet of Things sensor-based information system and propose security mechanisms for each security threat. Furthermore, we present an Internet of Things sensor-based information system structure that is robust to security attacks by integrating the proposed security mechanisms. In the proposed system, by applying lightweight security techniques such as a lightweight encryption algorithm and obfuscation-based data validation, security can be secured with minimal processing delay even in low-power and low-performance IoT sensor devices. Finally, we demonstrate the feasibility of the proposed system by implementing and performance evaluating each security mechanism.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.299-300
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• 2014

생명과학분야에서는 생명현상을 이해하기 위해 신호 전달 네트워크에 대한 연구가 진행되고 있다. 하지만 신호전달 네트워크와 임상 정보를 결합하여 질병관점에서 신호 전달 네트워크를 통합하고 결합하는 관점의 연구가 부족하다. 따라서 본 논문에서는 빅데이터 기술을 활용하여 임상 및 신호전달 정보를 연계 분석할 수 있는 시스템을 구축하고자 빅데이터 분석을 위한 임상 및 바이오 정보 통합 데이터베이스를 설계한다. 설계한 임상 및 바이오 정보 통합 데이터베이스는 빅데이터 분석 기술을 적용한 확장 분석 기법 및 통합 분석 시스템 개발에 활용할 수 있다.

• Journal of Industrial Convergence
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• v.18 no.1
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• pp.73-78
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• 2020

To analyze the main topics related to the use of blockchain technology, the Topic Modeling Technique was applied to the 'Blockchain Technology Utilization' big data shown in newspaper articles. To this end, from 2013 to 2019, when newspaper articles on the use of blockchain technology first appeared, the topics were extracted from 21 newspapers and analyzed by time to 15,537 articles. As a result of the analysis, articles related to the utilization of blockchain technology have increased exponentially since 2015 and focused on IT_science and economics. Key words related to cryptocurrency, bitcoin and virtual currency were weighted high, although they differed depending on time. Blockchain technology, which had focused on financial transactions, gradually expanded to big data, Internet of Things and artificial intelligence. As a result, changes in corporate topics were also made together to expand into various fields at banks for financial transactions, focusing on large and global companies. The study showed how these topics were changing, along with the main topics in newspaper articles related to the use of blockchain technology.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.76-76
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• 2021

물정보 중 가뭄 정보가 상대적으로 부족한 원인은 무엇을 가뭄으로 볼 것인지 정의하기 어렵기 때문이다. 특히 우리나라와 같이 댐 및 저수지, 광역상수도 등 수자원시스템 네트워크를 기반으로 물공급이 이루어지는 경우, 개별 요소만을 고려한 기존 가뭄모니터링 및 전망은 현실적이지 못하며, 가뭄 위험도 관리 측면에서도 부족한 부분이 있다. 가뭄 현상의 경우 기상학적 영향인 강수의 부족이 가장 큰 요소로 기여하지만 실질적으로 국민에 필요한 양보다 적은 양의 물이 공급될 때 국민들은 가뭄을 체감한다. 이러한 점을 보완하기 위하여 지역별로 사용하는 수원 및 물수급 시설 등을 세분화하고, 실적기반 분석을 통해 분석대상 지역의 가뭄을 정확히 판단하기 위한 합리적인 물수급 분석 모형 개발이 필요하다. 즉, 공간분석단위를 표준유역 단위 이하의 취방류 시설물을 기준으로 구성하고, 이들 시설물의 운영정보와 수문기상 빅데이터를 연계한 물순환 모형을 구현함으로써 댐, 저수지, 하천 등 다양한 수원을 가지는 유역 내 가용 수자원량을 준실시간 개념으로 평가하는 시스템의 개발이 필요하다. 본 연구에서는 하천을 중심으로 물수급 관련 수요·공급 시설의 위치를 절점으로 부여하고 연결하는 물수급 네트워크 알고리즘을 통해 빅데이터 기반 물수급 분석 모형을 개발하였다. 주요 모니터링 지점 및 모든 이수 시설의 위치를 유역분석 기법을 통하여 점(point), 선(line), 면(shape)으로 구성된 지형공간정보의 위상(topology) 관계를 설정하여 물수급 분석의 계산순서를 선정하고, 시계열 DB를 입력하여 지점별 물수급 분석 결과를 도출하였다. 권역별 주요 수위-유량관측소 1:1 Nash 계수를 검증한 결과 저유량에서 0.8 이상의 높은 재현 성능을 보이는 것으로 나타났다. 이에 따라 본 연구에서 개발된 물수급 분석 모형은 향후 물관련 이슈 지역의 용수공급능력 평가 및 수자원장기종합계획 등 다양한 수자원 정책평가에 활용될 것으로 기대된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.781-786
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• 2019

We should give a realistic value on the large amounts of relevant data obtained from these studies to achieve effective objectives of the disease study which is dealing with various vital phenomenon today. In this paper, the proposed MKSV algorithm is estimated by optimal probability distribution, and the input pattern is determined. After classifying it into data mining, it is possible to obtain efficient computational quantity and recognition rate. MKSV algorithm is useful for studying the relationship between disease and gene in the present society by simulating the probabilistic flow of gene data and showing fast and effective performance improvement to classify data through the data mining process of big data.

• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.795-835
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• 2019

Big data has been generated in various fields. Many companies have now tried to make profits by building a system capable of analyzing big data based on artificial intelligence (AI) techniques. Integrating AI technology has made analyzing and utilizing vast amounts of data increasingly valuable. In particular, demand forecasting with maximum accuracy is critical to government and business management in various fields such as finance, procurement, production and marketing. In this case, it is important to apply an appropriate model that considers the demand pattern for each field. It is possible to analyze complex patterns of real data that can also be enlarged by a traditional time series model or regression model. However, choosing the right model among the various models is difficult without prior knowledge. Many studies based on AI techniques such as machine learning and deep learning have been proven to overcome these problems. In addition, demand forecasting through the analysis of stereotyped data and unstructured data of images or texts has also shown high accuracy. This paper introduces important areas where demand forecasts are relatively active as well as introduces machine learning and deep learning techniques that consider the characteristics of each field.

• Journal of Convergence Society for SMB
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• v.5 no.1
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• pp.1-6
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• 2015

Recently the disease by eating of the modern prevention, management, and trends in the u-healthcare service that provides healthcare services including health promotion is changing rapidly. However, u-healthcare service is a healthcare information that provides users of the disease can not be analyzed even if the service is stored or not stored in the management server status is giving the inconvenience caused to users of the health services. In this paper, we propose a management method of health care services and a big data formation information that provides users of the disease to facilitate the users of health care services through the use magazine big data information regardless of time and place. The proposed method has the user's bio-information and the measured health information and transmits data through a wired or wireless communication to the medical institution and the user's health information data formation by the big user of the analysis of the health information and the disease of the user feedback to the user.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.385-391
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• 2013

Big Data is data of big size which is not processed, collected, stored, searched, analyzed by the existing database management system. The parallel genetic algorithm using the Hadoop for BigData technology is easily realized by implementing GA(Genetic Algorithm) using MapReduce in the Hadoop Distribution System. The previous study that the genetic algorithm using MapReduce is proposed suitable transforming for the GA by MapReduce. However, they did not show good performance because of frequently occurring data input and output. In this paper, we proposed the MRPGA(MapReduce Parallel Genetic Algorithm) using improvement Map and Reduce process and the parallel processing characteristic of MapReduce. The optimal solution can be found by using the topology, migration of parallel genetic algorithm and local search algorithm. The convergence speed of the proposal method is 1.5 times faster than that of the existing MapReduce SGA, and is the optimal solution can be found quickly by the number of sub-generation iteration. In addition, the MRPGA is able to improve the processing and analysis performance of Big Data technology.

• Informatization Policy
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• v.27 no.2
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• pp.66-83
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• 2020

Local issues that occur in cities typically garner great attention from the public. While local governments strive to resolve these issues, it is often difficult to effectively eliminate them all, which leads to complaints. In tackling these issues, it is imperative for local governments to use big data to identify the nature of complaints, and proactively provide solutions. This study applies the LDA topic modeling technique to research and analyze trends and patterns in complaints filed online. To this end, 9,625 cases of online complaints submitted to the city of Busan from 2015 to 2017 were analyzed, and 20 topics were identified. From these topics, key topics were singled out, and through analysis of quarterly weighting trends, four "hot" topics(Bus stops, Taxi drivers, Praises, and Administrative handling) and four "cold" topics(CCTV installation, Bus routes, Park facilities including parking, and Festivities issues) were highlighted. The study conducted big data analysis for the identification of trends and patterns in civil affairs and makes an academic impact by encouraging follow-up research. Moreover, the text mining technique used for complaint analysis can be used for other projects requiring big data processing.