• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.774-777
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• 2008

지리정보는 여러 분야에서 활용되고 그 데이터 양도 방대하여 효율적으로 저장하여 관리해야 할 필요가 있다. 본 논문은 균등 분할 방식과 비균등분할 방식에 의한 두 가지 지리정보 표현 및 압축방법을 수행하는 연산회수와 자료의 효율성 등을 중심으로 비교하였다. 두 가지 방법 모두 효율적인 활용이 가능하며 상황에 따라 기본 방법에서 수정을 가하여 사용할 수도 있다.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.41-45
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• 2019

The 1-serving lunchbox app is designed and developed for enabling consumers to order their lunch box by choosing their own lunch side dishes. In modern society, one-person households are growing in larger areas. It is too burdensome to handle alone because it is cumbersome to cook alone and you should order from two people in a restaurant shop. To resolve such inconveniences, it is an app to choose various detailed menus and order personalized lunches. In the process of selecting a detailed menu, information provided by big data is used. You can use the existing order through the bookmark function, or you can use the recommended lunch menu using big data.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.221-228
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• 2005

Data storage was thought to be inside of or next to server cases but advances in networking technology make the storage system to be located far away from the main computer. In Internet era with explosive data increases, balanced development of storage and transmission systems is required. SAN(Storage Area Network) and NAS(Network Attached Storage) reflect these requirements. It is important to know the capacity and limit of the complex storage network system to got the optimal performance from it. The capacity data is used for performance tuning and making purchasing decision of storage. This paper suggests an analytic model of storage network system as queuing network and proves the model though simulation model.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.311-315
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• 2003

Recently, there is asymmetrical transmission in Internet data stream. The asymmetrical transmission has much more downstream than upstream. Owing to this point, it needs to reduce the acknowledgement as element of the obsrtuction in downstream. In this paper, according to simulation's result, we know that Sack has good performance than New Reno in bottleneck environment Comparing two protocols in packet loss rate, NewReno is lower than Sack. And also comparing two protocols in throughput of ack packet, not only NewReno processes ack packet more quickly than Sack, but also NewReno processes more ack packet than Sack protocol during ten seconds in simulation. As a result, NewReno is batter than Sack in throughput of asymmetrical link.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.300-307
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• 2010

According to growth of web, data processing technology is developing. In the Web of next generation, high-speed or high-volume data processing technologies for various wire-wireless users, USN and RFID are developing too. In this paper, we propose a high-volume data processing technology using Complex Event Processing(CEP) engine. CEP is the technology to process complex events. CEP Engine is the following characteristics. First it collects a high-volume event(data). Secondly it analyses events. Finally it lets event connect to new actions. In other words, CEP engine collects, analyses, filters high-volume events. Also it extracts events using pattern-matching for registered events and new events. As the results extracted. We use it by an input event of other work, real-time response for demanded event and can trigger to database for only valid data.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.469-484
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• 2022

Since a large text corpus contains hundred-thousand unique words, text data is one of the typical large-dimensional data. Therefore, various feature selection methods have been proposed for dimension reduction. Feature selection methods can improve the prediction accuracy. In addition, with reduced data size, computational efficiency also can be achieved. The chi-square statistic and the information gain are two of the most popular measures for identifying interesting terms from text data. In this paper, we investigate the theoretical properties of the chi-square statistic and the information gain. We show that the two filtering metrics share theoretical properties such as non-negativity and convexity. However, they are different from each other in the sense that the information gain is prone to select more negative features than the chi-square statistic in imbalanced text data.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.17-22
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• 2024

History, which began with the emergence of mankind, has a means of recording. Today, we can check the past through data. Generated data may only be generated and stored at a certain moment, but it is not only continuously generated over a certain time interval from the past to the present, but also occurs in the future, so making predictions using it is an important task. In order to find out trends in the use of time series data among numerous data, this paper analyzes the concept of time series data, analyzes Recurrent Neural Network and Long-Short Term Memory, which are mainly used for time series data analysis in the machine learning field, and analyzes the use of these models. Through case studies, it was confirmed that it is being used in various fields such as medical diagnosis, stock price analysis, and climate prediction, and is showing high predictive results. Based on this, we will explore ways to utilize it in the future.

• Journal of KIISE
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• v.44 no.4
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• pp.352-362
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• 2017

This paper analyzes security threats in Security Enhanced (SE) Android and proposes a new technique to efficiently protect application data including private information on rooted Android phones. On an unrooted device, application data can be accessed by the application itself according to the access control models. However, on a rooted device, a root-privileged shell can disable part or all of the access control model enforcement procedures. Therefore, a root-privileged shell can directly access sensitive data of other applications, and a malicious application can leak the data of other applications outside the device. To address this problem, the proposed technique allows only some specific processes to access to the data of other applications including private information by modifying the existing SEAndroid Linux Security Module (LSM) Hook function. Also, a new domain type of process is added to the target system to enforce stronger security rules. In addition, the proposed technique separates the directory type of a newly installed application and the directory type of previously installed applications. Experimental results show that the proposed technique can effectively protect the data of each application and incur performance overhead up to or less than 2 seconds.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.55-59
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• 2018

Big-data, a revolutionary technology in the era of the 4th Industrial Revolution, provides services in various fields such as health, public sector, distribution, marketing, manufacturing, etc. It is very useful technology for marketing analysis and future design through accurate and quick data analysis. It is very likely to develop further. However, the biggest problem when using Big-data is privacy and privacy. When various data are analyzed using Big-data, the tendency of each user can be analyzed, and this information may be sensitive information of an individual and may invade privacy of an individual. Therefore, in this paper, we investigate the necessary measures for Personal private information infringement that may occur when using Personal private information in Big-data environment, and propose necessary Personal private information protection technologies to contribute to protection of Personal private information and privacy.

• The Korean Journal of Financial Management
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• v.14 no.1
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• pp.171-205
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• 1997

'80년대 중반 들어 주가지수 예측모형으로 애용되던 시계열 예측모형에 대한 근본적인 의문이 제기되었다. 이것은 기존 예측모형이 선형 데이터 생성과정을 기본가정으로 채택하고 있지만 진정한 데이터 생성과정은 비선형일 수도 있다는 점에서 출발한다. 주가지수의 변동을 유발하는 경제의 기본구조가 비선형임에도 불구하고 이를 선형모형으로 접근한다면 주가의 움직임을 제대로 설명할 수 없을 뿐만 아니라 이러한 설정오류는 모형의 신뢰성을 크게 손상시킨다. 이와 같은 점에 착안하여 본 연구는 업종별 주가지수의 비선형 검정을 통해 주가가 어떠한 형태의 경제구조에서 생성되었는지 여러 가지 방법으로 정정한다. 10개 업종지수의 검정결과 보험업을 제외한 대부분의 업종지수가 카오스 끌개를 보유하고 있다는 증거가 포착되었다. 표본외 예측을 위해서 국지적 가중회귀법을 채택하였는데 예측결과 모형에 따라 $6{\sim}7$개 업종에서 통상최소자승법보다 예측력 우위를 보였다.