• 디지털산업정보학회논문지
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• 제4권3호
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• pp.33-43
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• 2008

As internet is spreaded widely, the number of cyber terror using hacking and virus is increased. Also the hacking to the internet shopping mall go on increasing. If the large shopping mall is attacked by the hacker, a number of user's information are exposed to the hacker. The private information as like a resident registration number, user's real name, the date of user's birth, the mobile phone number, the office phone number / address, the home phone number / address and so on include the information. These information are used in the phishing e-mails / call and spam. And them are selling and buying maliciously. The large internet shopping mall 'auction' was hacked in April, 2008. After the incident, this paper suggested a countermeasures on the hacking for the internet shopping mall. The technical item and political item are included among the countermeasures. The countermeasures can protect the hacking not only the internet shopping mall but also the web sites basically.

• International Journal of Precision Engineering and Manufacturing
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• 제4권6호
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• pp.5-11
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• 2003

The number of the enterprises which utilize network technology has been increasing for solving problems such as productivity improvement, market trend analysis, and material collection for making decision. Especially, the management of equipment and the recovery time reduction when machines break down are very important factors in productivity improvement of the enterprise. Currently, most of the remote trouble diagnosis of equipment using the internet have just one function of transmitting the trouble information to the user. Therefore it does not directly reflect the user's recovery experience or the developer's new recovery methods. If the user's experienced recovery methods or the developer's recovery methods as well as the basic recovery methods are reflected online or on the internet, it makes it possible to recover faster than before. In this paper, we develop a Remote Monitoring Server (RMS) for chip mounters, and make it possible to reduce the recovery time by reflecting the user's experience and developer's new methods in addition to presenting the basic recovery methods. For this, trouble recovery concept will be defined. Based on this, many functions(trouble diagnosis, the presentation of the basic recovery methods, user's and developer's recovery method, counting function of the trouble number of each code, and presentation of usage number of each recovery methods) were developed. By utilizing the reports of the actual results of chip mounter and the notice function of the parts change time, the rate of operation of the chip mounter can be improved.

• 한국통신학회논문지
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• 제40권4호
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• pp.646-652
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• 2015

본 논문은 다중 사용자 MIMO 시스템에서 사용자 선택을 위해 필요한 precoding matrix index (PMI)/channel quality indication (CQI)의 보고 방식에 따른 성능을 분석한다. 이러한 분석을 통해 셀 내의 단말의 수, 선택되는 사용자의 수, 그리고 코드북(codebook)의 크기가 Best Companion Grouping (BCG)방식 스케쥴링의 성능에 복잡하게 영향을 미치는 것을 확인한다. 이에 따라 셀 내의 사용자 수와 코드북의 크기에 따라 동시에 스케쥴링 되는 사용자들의 그룹이 형성될 수 있는 확률이 달라지는 것을 확인할 수 있으며, 피드백 오버헤드가 주어졌을 때 이에 따라 피드백하는 PMI의 수와 사용하는 코드북의 크기를 적응적으로 선택함으로써 시스템의 평균 수율 성능을 최적화할 수 있음을 보였다.

• 디지털산업정보학회논문지
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• 제8권4호
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• pp.99-105
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• 2012

Recently, there are many user selection algorithms in multi user multiple-input multiple-output (MU-MIMO) systems. One of well-known user selection methods is Semi orthogonal user selection (SUS). It is an algorithm maximizing channel capacity. However, it is applicable only when user's antenna is one. We propose a generalized user selection algorithm regardless of the number of user's antennas. In the proposed scheme, Base station (Bs) selects the first user who has the highest determinant of channel and generates a user group that correlation with first user's channel is less than allowance of correlation. Then, each determinant of channels made up of first user's channel and a user's channel in the generated group is calculated and BS selects the next user who has the highest determinant of that. BS selects following users by repeating above procedure. In this paper, we get better performance because of selecting users who have the highest determinant of channel as well as allowance of correlation optimally calculated through matrix operations.

• 디지털산업정보학회논문지
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• 제19권1호
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• pp.91-107
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• 2023

With the recent expansion of the commerce ecosystem, a large number of user evaluations have been produced. Accordingly, attempts to create business insights using user evaluation data have been actively made. However, since user evaluation can change after the user experiences the product, it is difficult to say that the analysis based only on reviews immediately after purchase fully reflects the user's evaluation of the product. Moreover, studies conducted so far on user evaluation have overlooked the fact that the length of time a user has used a product can affect the user's product evaluation. Therefore, in this study, we build a model that predicts the direction of change in the user's rating after use from the user's rating and reviews immediately after purchase. In particular, the proposed model reflects the product's period of use in predicting the change direction of the star rating. However, since the posterior information on the duration of product use cannot be used as input in the inference process, we propose a structure that utilizes information about the product's period of use using an auxiliary classifier. As a result of an experiment using 599,889 user evaluation data collected from the shopping platform 'N' company, we confirmed that the proposed model performed better than the existing model in terms of accuracy.

• 지식경영연구
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• 제17권4호
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• pp.129-145
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• 2016

Nowadays, owing to the diffusion of smartphones and the growth of social networking services (SNS), the number of people who share their life with other SNS users by posting photos is increasing. The number of Instagram users has been particularly increasing since Instagram started its service in 2010. Compared to other SNS such as Facebook and Twitter, Instagram runs its service by focusing solely on photos, which is a major differentiation factor compared with other existing SNS. Previous studies, however, do not examine SNS that focus on photo sharing adequately. Therefore, we establish a hypothesis relating to the motivations behind a user's photo sharing attitude and posting intention through Instagram. Moreover, this will be achieved by employing TRA(Theory of Reasoned Action) and focusing on intrinsic and extrinsic motivations. The analysis results show that intrinsic motivation influences a user's sharing attitude and subjective norms. Apart from this, Instagram's expressivity influences a user's photo sharing attitude and posting intention.

• 지능정보연구
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• 제19권3호
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• pp.45-55
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• 2013

최근 모바일 디바이스와 휴대기기의 발달로 원격접속이 늘어남에 따라 보안의 중요성도 점차 증가되었다. 그러나 기존 패스워드나 패턴과 같은 보안 프로그램은 지나치게 단순할 뿐 아니라 다른 사용자가 쉽게 취득하여 악용할 수 있다는 단점이 있다. 생체인식을 활용한 보안 시스템은 보안성이 강화 되었지만 위조 및 변조가 가능하기 때문에 완전한 해결책을 제시하지 못한다. 본 논문에서는 이러한 문제점을 해결하기 위해 지문인식과 패스워드를 결합하여 보안성을 향상시킬 수 있는 방안을 연구하였다. 제안한 시스템은 하나의 지문이 아니라 다수의 지문을 이용하는 방법으로, 사용자가 패스워드를 입력할 때 여러 지문 중에서 정확한 지문의 순서를 제공하도록 한다. 오늘날 스마트폰은 패스워드나 패턴, 지문을 이용할 수 있지만 패스워드의 강도가 낮거나 패턴이 쉽게 노출되는 등의 문제가 있다. 반면에 제안한 시스템은 다양한 지문의 이용과 패스워드의 연계, 또는 다른 생체인식 시스템과 연결함으로써 매우 강력한 보안장치가 될 수 있다.

• Journal of the Korean Data and Information Science Society
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• 제17권3호
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• pp.775-784
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• 2006

This study is to investigate the effect of the number of co-rated users to the MAE. User based collaborative algorithm generally uses similarity weight to compute the relation of active user and other users. The original estimation algorithm of the GroupLens used the Pearson's correlation coefficient, soon after other researchers used various weighting. The Pearson’s correlation coefficient and Vector similarity, which is used in the field of information retrieval, are commonly used to the estimation algorithm. In prediction, we analyze the effect of the number of co-rated users on the user based recommender system.

• 한국산업정보학회논문지
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• 제19권6호
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• pp.63-76
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• 2014

최근 많은 사람들이 스마트폰을 이용해 다양한 방법으로 원하는 정보를 추천 받고 있다. 그와 관련해 추천을 위한 많은 어플리케이션이 존재하지만, 현재 사용자 상황에 맞는 정보를 추천해 주는 것은 없다. 자동으로 사용자의 상황에 맞는 추천을 하기 위해서는 사용자의 과거 행위이력으로 부터 미래의 행위를 예측할 필요가 있다. 이에 본 논문에서는 스마트폰을 이용해 사용자의 현재 상황을 수집하고, 수집된 데이터를 라이프로그를 분석하여 구축한 베이지안 네트워크에 적용하여 현 행동을 판별한 후 연관분석을 통해 사용자가 미래에 하게 될 행동을 예측하는 방법을 제안한다. 5명의 실제 학생과 5명의 가상의 직장인에 대해서 실험 및 분석해 본 결과 그 유용성을 확인할 수 있었다.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2001년도 춘계학술대회 논문집
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• pp.131-135
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• 2001

Recently, Internet is used widely. Many Web sites, however, are not designed based on user's view. So, this research aimed at grasping the user needs and structure of Web site which user used easily. First, to grasp user needs, questionnaires about the motivation, the purpose and the evaluation items of Web page were done. As a result, we found the easiness for the user. Next, we made subjects operated test pages in which the number of classes and the amount of information were changed. We collected the quantitative data of the optimum number of classes, amount of information and retrieval time. As a result, there was a significant difference in each numerical value. The results of this research are available when constructing a web site. so, usability of Web site can be improved by them.