• 한국정보교육학회:학술대회논문집
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• 2006.08a
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• pp.263-268
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• 2006

토론학습시 보다 자발적인 아동의 참여를 향상시킬 수 있는 웹토론시스템은 시간의 편의성을 제공하고 학습자간의 상호작용을 활발하게 한다. 그러나 기존 웹토론시스템은 능숙한 자판사용능력과 물리적인 교육적 환경을 요구한다. Wiki는 하와이어로 '빨리'라는 뜻으로 누구나 '자유롭게' 정보와 지식을 편집할 수 있는 동적 프로그래밍 도구이다. Wiki를 사용하여 기존의 웹토론시스템의 단점을 보안한 본 시스템의 목적은 학습자의 자발적인 토론참여와 토론학습에 대한 흥미를 유발하는 것이다. 본 시스템의 특징은 다음과 같다. 첫째, 본 시스템은 웹토론에 대한 학생들의 흥미를 높일수 있다. 즉 누구나 관리자가 될 수 있는 기능을 이용해서 학생들의 흥미를 유발하였기 때문이다. 둘째, Wiki 웹토론시스템은 기존의 웹토론시스템보다 사용이 편리하여 학생의 참여도를 향상시키고 토론학습에 대한 관심을 증대시킬 수 있다. 기존의 웹토론시스템은 회원가입을 해야하고 로그인을 해야만 토론학습에 참여할 수 있지만 본 시스템은 웹페이지접속만으로도 가능하게 하였다. 셋째, Wiki 웹토론시스템은 웹토론를 학습하는 과정을 공개하여 올려지는 자료나 다른 사람의 의견을 통해 지식공유를 가능하게 한다. 즉, 자신이 찾은 주장의 근거을 찾는 과정에서나 또 그 근거를 통해 새로운 지식을 알게 되고 본 시스템에서 의견을 개진하고 다른 사람의 의견의 근거를 살펴보면서 지식을 공유하게 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.498-501
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• 2002

In the process of Log-In to the system, clear User authentication is the beginning of the information protection service. In the open communication system of today, it is true that a password as security instrument and the inner mechanism of the system and cryptography algorithm for the support of this are also poor. For this reason, this dissertation had a final aim to design the user authentication system, which offer the accuracy and safety. It used RSA and CBC mode of DES as cryptography algorithm and used the Challenge-Response scheme at a authentication protocol and designed the User authentication system to which user access using one time password, output of token to guarantee the safety of the authentication protocol. Alto by using the Public key cryptography algorithm, it could embody the more safe User authentication system.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.781-784
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• 2019

최근 AI를 산업 서비스에 적용하기 위해 많은 회사들이 활발히 연구를 하고 있다. 아마존과 넷플릭스 같은 거대 기업들은 이미 빅데이터와 AI 머신러닝을 이용한 추천 시스템을 구현하였고 아마존은 매출의 35%가 추천에 의해 발생하고 넷플릭스 75%의 사용자가 추천을 통해 영화를 선택한다고 보고되었다. 이러한 두 기업의 높은 추천 효율성의 이유는 협업 필터링(Collaborative filtering)과 같은 다양한 추천 알고리즘과 방대한 상품 및 고객 행동(구매, 시청 등) 데이터 등이 존재하고 있기 때문이다. 기계학습에서 알고리즘 학습을 위한 데이터의 양이 많지 않을 경우 알고리즘의 성능을 보장할 수 없다는 것이 일반적인 의견이다. 방대한 데이터를 가진 기업에서 추천 알고리즘을 적극적으로 활용 및 연구하고 있는 것도 이러한 이유 때문이다. 반면, 오프라인 및 여행사 기반에서 온라인 기반으로 영역을 차츰 확대하고 있는 항공 서비스 고객 데이터의 경우, 산업의 특성상 많은 회원에 비해 고객 1명당 온라인에서 활동하는 이력이 많지 않은 것이 특징이다. 이는, 추천 알고리즘을 통한 서비스 제공에서 큰 제약사항으로 작용한다. 본 연구에서는, 이러한 희박한 고객 활동 데이터에서 최신성 기반의 추천 시스템을 통하여 제약사항을 극복하고 추천 효율을 높이는 방법을 제안한다. 고객의 최근 접속 이력 로그를 시간 기준으로 데이터 셋을 분할하여 추천 알고리즘에 반영하였을 때, 추천된 노선에 대한 고객의 반응을 추천 성능 지표인 CTR(Click-Through Rate)로 측정하여 성능을 확인해 보았다.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.58-66
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• 2021

The user's password must be encrypted one-way through the hash function and stored in the database. Widely used hash functions such as MD5 and SHA-1 have also been found to have vulnerabilities, and hash functions that are considered safe can also have vulnerabilities over time. Salt enhances password security by adding it before or after the password before putting it to the hash function. In the case of the existing Salt, even if it is randomly assigned to each user, once it is assigned, it is a fixed value in a specific column of the database. If the database is exposed to an attacker, it poses a great threat to password cracking. In this paper, we suggest variable-dynamic Salt that dynamically changes according to the user's password during the login process. The variable-dynamic Salt can further enhance password security during login process by making it difficult to know what the Salt is, even if the database or source code is exposed.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.95-100
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• 2019

In this paper, we propose a simple hardware reporting method for errors in soft-RAID systems of Linux OS. Compared with other reporting methods, the proposed method displays error status intuitively without any additional access process such as log-in process or home-page access. In particular, the server actively displays the error status, so the administrator can take immediate action. In order to confirm the effectiveness of the proposed method, the experimental circuit was constructed and the experimental results showed that the error was actively displayed when an error occurred in the storage device. As such, a soft-RAID system can perform almost the same function as a hardware RAID system, thereby ensuring server data reliability at low cost.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.4
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• pp.189-212
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• 2021

The purpose of this study is to analyze an usage behavior for the public library website through web traffic. For this purpose, using Google Analytics and growth hacking technique, the data of A public library website log was analyzed for three months from August 1, 2021 to October 31, 2021. As a result of the study, the young age group of 18-24 years old and 25-34 years old recorded a high rate of new member registration, & it was found that the inflow rate through SNS was high for external inflows. As a result of analysis for the access rate by time, it was found that the time with the highest inflow rate was between 10 am and 11 am both on Wednesday and Friday. As a access channel, the access rate using mobile (64.90%) was quite high, but at the same time, the bounce rate (27.20%) was higher than the average (24.93%), & the rate of duration time (4 minutes 33 seconds) was lower than thee average (5 minutes 22 seconds). Finally, it was found that the utilization rate of reading program events and online book curation service, which the library focuses on producing and promoting, is very low. These research results can be used as basic data for future improvement of public library websites.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.334-348
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• 2015

Widespread use of smart devices accompanies increase of use of access point (AP), which enables the connection to the wireless network. If the appropriate security is not served when a user tries to connect the wireless network through an AP, various security problems can arise due to the rogue APs. In this paper, we are going to examine the threat by evil-twin, which is a kind of rogue APs. Most of recent researches for detecting rogue APs utilize the measured time difference, such as round trip time (RTT), between the evil-twin and authorized APs. These methods, however, suffer from the low detection rate in the network congestion. Due to these reasons, in this paper, we suggest a new factor, packet inter-arrival time (PIAT), in order to detect evil-twins. By using both RTT and PIAT as the learning factors for the support vector machine (SVM), we determine the non-linear metric to classify evil-twins and authorized APs. As a result, we can detect evil-twins with the probability of up to 96.5% and at least 89.75% even when the network is congested.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.1-8
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• 2009

In this paper, we propose a home medical system that integrates a self-diagnosing disease classification system and a tele-consulting system by communication technology. The proposed disease classification system supports to self-diagnose the health condition based on oriental medical science using fuzzy neural network algorithm. The prepared database includes 72 different diseases and their associated symptoms based on a famous medical science book "Dong-eui-bo-gam". The proposed system extracts three most prospective diseases from user's symptoms by analyzing disease database with fuzzy neural network technology. Technically, user's symptoms are used as an input vector and the clustering algorithm based upon a fuzzy neural network is performed. The degree of fuzzy membership is computed for each probable cluster and the system infers the three most prospective diseases with their degree of membership. Such information should be sent to medical doctors via our tele-consulting system module. Finally a user can take an appropriate consultation via video images by a medical doctor. Oriental medical doctors verified the accuracy of disease diagnosing ability and the efficacy of overall system's plausibility in the real world.

• The Korean Journal of Applied Statistics
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• v.37 no.4
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• pp.525-539
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• 2024

Massive multiplayer online role playing game (MMORPG) is a common type of game these days. Predicting user churn in MMORPG is a crucial task. The retention rate of users is deeply associated with the lifespan and revenue of the service. If the churn of a specific user can be predicted in advance, targeted promotions can be used to encourage their stay. Therefore, not only the accuracy of churn prediction but also the speed at which signs of churn can be detected is important. In this paper, we propose methods to identify early signs of churn by utilizing the daily predicted user retention probabilities. We train various deep learning and machine learning models using log data and estimate user retention probabilities. By analyzing the change patterns in these probabilities, we provide empirical rules for early identification of users at high risk of churn. Performance evaluations confirm that our methodology is more effective at detecting high risk users than existing methods based on login days. Finally, we suggest novel methods for customized marketing strategies. For this purpose, we provide guidelines of the percentage of accessed users who are at risk of churn.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.63-68
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• 2013

Recently, companies seek a way to overcome their financial crisis by reducing costs in the field of IT. In such a circumstance, cloud computing is rapidly emerging as an optimal solution to the crisis. Even in a digital forensic investigation, whether users of an investigated system have used a cloud service is a very important factor in selecting additional investigated subjects. When a user has used cloud services, such as Daum Cloud and Google Docs, it is possible to connect to the could service from a remote place by acquiring the user's log-in information. In such a case, evidence data should be collected from the remote place for an efficient digital forensic investigation, and it is needed to conduct research on the collection and analysis of data from various kinds of cloud services. Thus, this study suggested a digital forensic framework considering cloud environments by investigating collection and analysis techniques for each cloud service.