• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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• pp.396-399
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• 2008

Kalman Filter is an efficient recursive filter that estimates the state of a dynamic system from a series of incomplete and noisy measurement. The filter is very powerful in the field of autonomous and assisted navigation. In this paper, we carry out comparative stduy to validate the performance of the application of Kalman Filter. We will build personal localization system based on Cricket mote, our system can present the real-time position of person when the man with PDA moves around. The proposed system is composed of cricket sensor networks, PDA and host computer. There is one listener attached to the PDA. The PDA will get the distance data from the listener synchronously. It will calculate the position of the person in the coordinate of the Cricket system with the trilateration method. Furthermore, it sends the real-time position information to the host computer by Bluetooth. The host computer will use Kalman Filter to process data and get the final estimated track of the person.

• Journal of the Korean Data and Information Science Society
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• 제16권1호
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• pp.95-106
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• 2005

Complete-case analysis is easy to carry out and it may be fine with small amount of missing data. However, this method is not recommended in general because the estimates are usually biased and not efficient. There are numerous alternatives to complete-case analysis. A natural alternative procedure is available-case analysis. Available-case analysis uses all cases that contain the variables required for a specific task. The EM algorithm is a general approach for computing maximum likelihood estimates of parameters from incomplete data. These methods and multiple imputation(MI) are reviewed and the performances are compared by simulation studies in monotone missing pattern.

• Journal of the Korean Data and Information Science Society
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• 제23권2호
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• pp.365-374
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• 2012

Weather derivatives designed to manage casual changes of weather, as opposed to catastrophic risks of weather, are relatively a new class of financial instruments. There are still many theoretical and practical challenges to the effective use of these instruments. The objective of this paper is to develop a pricing approach for valuing weather derivatives and presents a case study that is practical enough to be used by the risk managers of electrical utility firms. Utilizing daily average temperature data of Guangzhou, China from $1^{st}$ January 1978 to $31^{st}$ December 2010, this paper adopted a univariate time series model to describe weather behavior dynamics and calculates equilibrium prices for weather futures and options for an electrical utility firm in the region. The results imply that the risk premium is an important part of derivatives prices and the market price of risk affects option values much more than forward prices. It also demonstrates that weather innovation as well as weather risk management significantly affect the utility's financial outcomes.

• 한국지능시스템학회논문지
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• 제18권4호
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• pp.537-542
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• 2008

Cricket is an excellent indoor location system and it can successfully solve many critical problems such as user privacy, decentralized administration. But in some practical applications, Cricket sometimes didn't provide location with enough accuracy, and was unable to determine when it was giving inaccurate information. For getting high-accuracy tracking performance from location data contaminated with noise, some types of filters are required. Kalman Filter is an efficient recursive filter that estimates the state of a dynamic system from a series of incomplete and noisy measurement. The filter is very powerful in the field of autonomous and assisted navigation. In this paper, we carry out comparative studies to validate the performance of the application of Kalman Filter to Cricket based localization system.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2003년도 춘계학술대회
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• pp.474-483
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• 2003

A number of studies for corporate bond rating classification problems have demonstrated that artificial intelligence approaches such as Case-based reasoning (CBR) can be alternative methodologies to statistical techniques. CBR is a problem solving technique in that the case specific knowledge of past experience is utilized to find a most similar solution to the new problems. To build a successful CBR system to deal with human information processing, the representation of knowledge of each attribute is an important key factor We propose a hybrid approach of using fuzzy sets that describe the approximate phenomena of the real world because it handles inexact knowledge represented by common linguistic terms in a similar way as human reasoning compared to the other existing techniques. Integration of fuzzy sets with CBR is important to develop effective methods for dealing with vague and incomplete knowledge to statistical represent using membership value of fuzzy sets in CBR.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 춘계학술발표대회
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• pp.971-974
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• 2011

본 논문에서는 대용량 네트워크에 비정상적인 트래픽이 유입이 되거나 나가는 경우 패킷 기반의 비정상 트래픽의 탐지와 분석이 가능토록 하는 시스템을 설계하고 구현하였다. 본 논문에서 구현한 시스템은 네트워크상의 이상 행위를 탐지하기 위하여, DDoS HTTP Get Flooding 공격 탐지 알고리즘을 적용하고, NetFPGA를 이용하여 라우터 단에서 패킷을 모니터링하며 공격을 탐지한다. 본 논문에서 구현한 시스템은 Incomplete Get 공격 타입의 Slowloris 봇과, Attack Type-2 공격 타입의 BlackEnergy, Netbot Vip5.4 봇에 높은 탐지율을 보였다.

• Asia pacific journal of information systems
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• 제31권4호
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• pp.527-542
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• 2021

The government-driven open data policies are on the rise to protect consumers from misunderstandings and monitor the companies. However, in contract-based industries such as insurance, the contract-inherent characteristics make information asymmetry between consumers and companies. Our paper focuses on insurance contracts where the contingency has high uncertainty of occurrence, and the clauses may incur high costs of reading. Given those contracts, we hypothesized that the contract's clear statement decreases customer dissatisfaction and lowers the number of complaints. To empirically support the claim, we collected customers' complaint documents of insurance companies and insurance contracts from 2005 until 2017. Our econometric models showed that clearer statements and words significantly reduce the complaints after controlling for firm-specific heterogeneity and time-specific heterogeneity. We identify that insurance companies' complaint ratio significantly differ depending on the insurance contract, including specific clauses and words.

• 한국한의학연구원논문집
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• 제16권3호
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• pp.141-147
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• 2010

In this paper, we designed and implemented an integrated search and collaboration system. Users can search the traditional korean medicine knowledge in our system, which consists of medicinal materials, formulas, diseases, terminology, and clinical information. In general, the existing information systems providing the korean medicine knowledge do not provide the update function. Thus, it can be a problem if there are incomplete information. In order to solve this problem, our system implements the functions that users can work together to improve the knowledge. Therefore, wrong information can be updated easily so that flexible management about the korean medicine information is possible.

• 한국인터넷방송통신학회논문지
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• 제14권6호
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• pp.47-54
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• 2014

러프집합을 구성하는 식별불가능 관계를 표현하는 정보시스템에서 데이터의 중복이나 비일관성은 피할 수 없기 때문에 속성의 감축은 매우 중요하다. 러프집합이론에 있어서 일관적인 정보시스템과 비일관적인 정보시스템의 속성감축의 차이를 극복하고 자, 본 연구에서는 조건 및 결정속성에 대한 상관분석에 베이지언 사후확률을 적용한 새로운 불확실성 척도와 속성감축 알고리즘을 제안한다. 정보시스템의 불확실성에 대하여 제안된 척도와 기존의 조건부 정보엔트로피 척도를 비교해 본 결과, 정보시스템의 조건속성과 결정속성의 상호정보를 이용하여 속성간의 불확실성을 측정하는데 있어 제안된 방법이 조건부 정보엔트로피에 의한 방법보다 정확성이 있음을 보여준다.

• Journal of Information Science Theory and Practice
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• 제1권3호
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• pp.33-46
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• 2013

Despite limited success, today's information retrieval (IR) systems are not intelligent or reliable. IR systems return poor search results when users formulate their information needs into incomplete or ambiguous queries (i.e., weak queries). Therefore, one of the main challenges in modern IR research is to provide consistent results across all queries by improving the performance on weak queries. However, existing IR approaches such as query expansion are not overly effective because they make little effort to analyze and exploit the meanings of the queries. Furthermore, word sense disambiguation approaches, which rely on textual context, are ineffective against weak queries that are typically short. Motivated by the demand for a robust IR system that can consistently provide highly accurate results, the proposed study implemented a novel topic detection that leveraged both the language model and structural knowledge of Wikipedia and systematically evaluated the effect of query disambiguation and topic-based retrieval approaches on TREC collections. The results not only confirm the effectiveness of the proposed topic detection and topic-based retrieval approaches but also demonstrate that query disambiguation does not improve IR as expected.