• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.450-453
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• 2012

We must be the best choice in a variety of situations in decision every time. If you need to select one of several alternatives in a variety of fields, In this paper, we implement the system using AHP to analyze the results with the highest priority. AHP is one of the decision-making techniques. When Decision-makers making decisions, AHP would be useful if you need to select the alternative conflicting purpose. Excel using AHP software, or software for the PC exist. Recently, Smartphone and tablet PC is the modern man's necessities and has shown remarkable penetration. In this paper, we have developed a priority investigation Mobile Application.

• Korean Journal of Applied Biomechanics
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• v.12 no.2
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• pp.307-318
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• 2002

To provide a guideline for the development of a web-based sport biomechanics class in undergraduate program, thirty web sites, searched via search engines in May 2002, were analyzed intensively. In terms of requirement of log-in, only one site of 30 sites required user name and password. Seventeen(57%) sites provided the lecture note, which had various file formats such as 59% if PDF, 29% of HTML, and 12% of PPT. Fourteen(47%) sites provided the assignment and grade information on web. Eleven(37%) sites provided various resource and links which were related in sports biomechanics. Only four(13%) sites provided discussion or online digitizing or kinematic analysis program. Based on above results, a guideline for the development of a virtual classroom for college level sport biomechanics. A web-based sport biomechanics class should be developed with consideration of several functions as follows; homepage design, lecture note, measurement of class attendance, collaborative research system, and web-based data collection and analysis software for biomechanics laboratory.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.1-11
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• 2017

Recently that require digital signatures handwritten for personal use customer information and agree to the Terms of Service agreement or a general sign up. Signature system including an existing handwritten signature are a problem, which may be a platform-dependent, as well as the environment in which to perform the signature vary according to device Status of presence because it is being utilized is implemented on the service platform itself within each company. In this paper, we designed and implemented an integrated system handwritten signature as possible using a cross-browser way to store the handwritten two-dimensional coordinates based on the jQuery it is interspecific directly integrated browser environment. iOS, Android, was tested in an integrated web browser in heterogeneous environments, including PC, it was confirmed that all handwritten signature function is working properly.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1092-1100
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• 2004

An E-mails have regarded as one of the most popular methods for exchanging information because of easy usage and low cost. Meanwhile, exponentially growing unwanted mails in user's mailbox have been raised as main problem. Recognizing this issue, Korean government established a law in order to prevent e-mail abuse. In this paper we suggest hybrid spam mail filtering system using weighted Bayesian classifier which is extended from naive Bayesian classifier by adding the concept of preprocessing and intelligent agents. This system can classify spam mails automatically by using training data without manual definition of message rules. Particularly, we improved filtering efficiency by imposing weight on some character by feature extraction from spam mails. Finally, we show efficiency comparison among four cases - naive Bayesian, weighting on e-mail header, weighting on HTML tags, weighting on hyperlinks and combining all of four cases. As compared with naive Bayesian classifier, the proposed system obtained 5.7% decreased precision, while the recall and F-measure of this system increased by 33.3% and 31.2%, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.681-683
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• 2016

Recently, sharing economy is getting the attention of the public. So this phenomenon to share their goods, home, gifts, etc. in various fields has been increased. Typically when traveling away from home to host as "Airbnb", the share house to share their homes are traded most actively. Through a share house host can make money using house empty, customers can take advantage of the hostel while traveling at low prices. The existing share house system must ensure that every time they empty the house Customers, host had the inconvenience of having to wait for the application of the tenant customers. To solve this problem and to implement a service platform based on the waiting list. Through this platform, customers will be able to eliminate the inconvenience of having to find the house every time you want to apply for a tenant waiting to get home, give the order to wait.

• Journal of Korea Multimedia Society
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• v.5 no.6
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• pp.625-637
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• 2002

The Internet had been taken properties which were both a slow speed and low-bandwidth of the first time. It was impossible to transmit large multimedia data because of a Internet properties. After tens of Year Passed, many people began to transmit multimedia data in the Internet which had fast-speed and high-bandwidth. Some people want to team classes to be taught in school through the Internet. And, educators wish to use multimedia data in the educational field. Due to previous reasons, many parts in the educational field had tried to join real-time objects to multimedia objects. But, real-time data didn’t appear easily due to many faults like network errors and system bugs if we want to control data in order to teach and learn classes. Then, this paper separates real-time and unreal-time data and controls these data that aye made a time scheduler to have time information in the extended SMIL-file for deceasing these faults.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.677-680
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• 2000

웹이 등장하면서 지금까지 인터넷 상에서 텍스트와 이미지를 이용하여 정보를 표현하고 전달하는 방법이 가장 많이 사용되어왔다. 그러나 웹 관련 기술의 비약적인 발달과 네트워크 속도의 증가 및 인터넷의 급속한 보급으로 단순한 텍스트와 이미지 중심의 HTML 문서를 이용한 정보의 전달이 아닌 멀티미디어 데이터를 이용한 정보의 표현과 전달이 점차 증대되고 있다. 이에 따라 멀티미디어 데이터를 전송하기 위한 스트리밍 프로토콜도 등장하였다. 최근에는 컴퓨터의 성능 증가 및 네트워크 속도의 증가(초고속 통신 서비스의 보급)에 의해 멀티미디어 데이터의 전송이 가능하게됨으로써 기존의 공중파나 CATV 방송국의 형태 지니고 인터넷 상에서 실시간 생방송 서비스와 VOD(Video On Demand) 서비스를 제공하는 인터넷 방송국이 급속하게 생겨나고 있다.[11] 인터넷 방송은 동영상과 오디오의 실시간 전달을 가능하게 하는 멀티미디어 스트리밍 기술과 멀티미디어를 실시간으로 전송할 수 있는 실시간 전송 프로토콜을 기반으로 발전하고 있다. 인터넷 상에서 멀티미디어 스트리밍 서비스를 하는 대부분의 인터넷 방송은 스트리밍 서버로서 RealNetworks사의 RealSystem과 Microsoft사의 WMT(Windows Media Technologies)를 사용하고 있다. 본 논문은 Real Server와 WMT의 비교 분석을 통해 실시간 전송 프로토콜을 지원하고, 멀티미디어 스트리밍 기술을 지원하는 자바를 기반으로 한 분산 서버 구조의 스트리밍 서버, 서버간의 부하를 제어하는 미들웨어, 멀티미디어 스트림을 재생할 수 있는 클라이언트를 설계하고 구현한다. 방법에 대해서 자세히 살펴보고 실제 SQL Server 7.0 환경에서 구축된 공간 엔진 및 OLE DB 제공자 컴포넌트의 구현 예에 대하여 살펴볼 것이다. 혈액내방사선 조사량이 안전용량 범위(200rad)에 속하며 48시간 후 체내잔류량은 서양인과 큰 차이가 없었다.비출현의 소견을 보이는 악성종양 환자의 골 신티그람 53개중 44개 (83.0%)에서 척추 및 늑골에 미만성, 또는 다발성 침습이 관찰되었다. 또 골전이 부위를 두개골, 척추, 견대부, 늑골, 골반, 사지의 근위부 장골의 6개 부위로 나누어 분석할 경우 49개(92.5%)에서 3부위 이상에 전이가 발견되었고, 35개(66.0%)에서 4부위 이상에 전이가 발견되었으며, 5부위 이상, 6개 부위에 모두 전이가 발견된 것은 각각 20개 (37 7%), 11개(20.8%)이었다. 이상의 성적으로 보아 악성종양 환자의 골 신피그라피에서 신장 영상의 비출현은 종양의 광범위한 골전이를 간접적으로 시사하는 소견으로 생각된다. 여러 악성종양중 전립선암에서 신장 영상 비출현의 빈도가 가장 높았으며, 특히 위암에서 골전이 및 신장 영상 비출현의 빈도가 높음은 주목할 만한 것이라 하겠다.출한 결과 인,규소 증가와 자가영양성 미소플랑크톤(ANP)증가에 미치는 요인이 해안과 외해에서 동일하게 가장 큰 설명력을 보였다. N:P 비도 해안에서 36.4, 외해에서 32.6을 보이고 있어 인이 상당히 부족한 것으로 나타났다. 따라서 조사해역은 인이 식물플랑크톤 성장에 중요한 제한요인으로 작용하고 있다고 판단된다.의 회전. 전위력의 강도, 적용시점, 그리고 키, 체중등의 신체적 요인 등이 있으나 능숙한 기계사

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.265-270
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• 2014

Hearing-impaired people have difficulty in hearing, so it is also hard for them to learn letters that represent sound and text that conveys complex and abstract concepts. Therefore it has been natural choice for the hearing-impaired people to use sign language for communication, which employes facial expression, and hands and body motion. However, the major communication methods in daily life are text and speech, which are big obstacles for the hearing-impaired people to access information, to learn and make intellectual activities, and to get jobs. As delivering information via internet become common the hearing-impaired people are experiencing more difficulty in accessing information since internet represents information mostly in text forms. This intensifies unbalance of information accessibility. This paper reports web-based text-to-sign language translating system that helps web designer to use sign language in web page design. Since the system is web-based, if web designers are equipped with common computing environment for internet browsing, they can use the system. The web-based text-to-sign language system takes the format of bulletin board as user interface. When web designers write paragraphs and post them through the bulletin board to the translating server, the server translates the incoming text to sign language, animates with 3D avatar and records the animation in a MP4 file. The file addresses are fetched by the bulletin board and it enables web designers embed the translated sign language file into their web pages by using HTML5 or Javascript. Also we analyzed text used by web pages of public services, then figured out new words to the translating system, and added to improve translation. This addition is expected to encourage wide and easy acceptance of web pages for hearing-impaired people to public services.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.