• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.65-71
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• 2017

Since existing Internet of Things(IoT) is vulnerable, it may cause property damage due to the information leakage. Especially, the smart door lock system built on the IoT can cause more damage. To solve these problems, this paper classify the data generated by the sensor according to the condition and send an alarm message to the user's smartphone through Google Cloud Message (GCM). We made it possible to check the images in real time through the smartphone application and control the door lock using the TCP / IP protocol. Also, we applied OTP-Based Matrix SEED algorithm to door lock system to improve security.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.106-114
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• 2016

In this paper, we propose an efficient integer inverse transform structure for vp9 decoder. The proposed structure is a hardware structure which is easy to control and requires less hardware resources, and shares algorithms for realizing entire DCT(Discrete Cosine Transform), ADST(Asymmetric Discrete Sine Transform) and WHT(Walsh-Hadamard Transform) in vp9. The integer inverse transform for vp9 google model has a fast structure, named butterfly structure. The integer inverse transform for google C model, unlike universal fast structure, takes a constant rounding shift operator on each stage and includes an asymmetrical sine transform structure. Thus, the proposed structure approximates matrix coefficient values for all transform mode and is used to matrix operation method. With the proposed structure, shared operations for all inverse transform algorithm modes can be possible with reduced number of multipliers compared to the butterfly structure, which in turn manages the hardware resources more efficiently.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.420-422
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• 2007

In order to support wind power development in Jejudo, the island of winds, the wind resource database KIER-WindJeju has been established by meteor-statistical analysis on met-mast measurements of KIER. The analysis includes tower shading, exposure category, wind profile exponent for wind speed extrapolation to hub height of wind turbine, and correlation matrix between neighboring sites to assist choice of appropriate reference site for long-term correlation. KIER-WindJeju will be provided as an add-on of Google $Earth^{TM}$ and will be used as a guideline of future wind resource assessment in Jejudo.

• Review of KIISC
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• v.24 no.6
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• pp.31-36
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• 2014

클라우드 컴퓨팅 서비스는 자원 공유와 가상화 기술 및 자원의 서비스화 등 기존 컴퓨팅 환경과 다른 특성으로 인해 클라우드 컴퓨팅 환경에 적합한 식별/접근제어 기술 및 보안 통제 사항이 요구된다. 그러므로 기존 컴퓨팅 자원을 클라우드 컴퓨팅 환경으로 변경하는 서비스 제공자나 클라우드 서비스로 이동하는 서비스 사용자는 특정한 보안 요건을 검토해야 한다. Cloud Security Alliance에서 배포한 Cloud Control Matrix와 ISO/IEC 27001을 비교 분석하여, 클라우드 컴퓨팅 환경에서 특별히 요구되는 식별 및 접근제어의 보안 통제 요건을 확인하였다. 또한, 주요 클라우드 컴퓨팅 서비스인 아마존의 AWS, 구글의 Google Cloud Platform과 VMware의 vCloud 서비스의 식별 및 접근제어 기술을 조사하였다. 이를 기반으로 클라우드 컴퓨팅 환경의 식별 및 접근제어 기술에서 필요한 보안 요건을 확인하였다.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.179-184
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• 2021

In our study we performed a sentiments analysis from the images. For this purpose, we used 153 images that contain: people, animals, buildings, landscapes, cakes and objects that we divided into two categories: images that suggesting a positive or a negative emotion. In order to classify the images using the two categories, we created two models. The SAI-G model was created with Google's AutoML Vision service. The SAI-C model was created on the Clarifai platform. The data were labeled in a preprocessing stage, and for the SAI-C model we created the concepts POSITIVE (POZITIV) AND NEGATIVE (NEGATIV). In order to evaluate the performances of the two models, we used a series of evaluation metrics such as: Precision, Recall, ROC (Receiver Operating Characteristic) curve, Precision-Recall curve, Confusion Matrix, Accuracy Score and Average precision. Precision and Recall for the SAI-G model is 0.875, at a confidence threshold of 0.5, while for the SAI-C model we obtained much lower scores, respectively Precision = 0.727 and Recall = 0.571 for the same confidence threshold. The results indicate a lower classification performance of the SAI-C model compared to the SAI-G model. The exception is the value of Precision for the POSITIVE concept, which is 1,000.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.66-71
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• 2021

The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.41-46
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• 2022

The purpose of this study is to confirm and analyze the impact on consumers through big data keyword analysis on weak food. For data collection, web documents, blogs, news, cafes, intellectuals, academic information, and Google Web, news, and Facebook provided by Naver and Daum were used as analysis targets. The data analysis period was set from January 2018 to December 2021. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analyzed and visualized using the Netdraw function among UCINET6 programs. In addition, CONCOR analysis was conducted to derive clusters for similar keywords. As a result of analyzing yakseon food with keywords, a total of 35,985 cases of collected data were derived. Through this, it was confirmed that medicinal food affects consumers. Furthermore, if a business model is created and developed through yakseon food, it will be possible to lead the popularization of yakseon food.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.851-860
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• 2009

Recently, among the computational methods of protein-protein interaction prediction, vast amounts of domain based methods originated from domain-domain relation consideration have been developed. However, it is true that multi domains collaboration is avowedly ignored because of computational complexity. In this paper, we implemented a protein interaction prediction system based the Interaction Significance matrix, which quantified an influence of domain combination pair on a protein interaction. Unlike conventional domain combination methods, IS matrix contains weighted domain combinations and domain combination pair power, which mean possibilities of domain collaboration and being the main body on a protein interaction. About 63% of sensitivity and 94% of specificity were measured when we use interaction data from DIP, IntAct and Pfam-A as a domain database. In addition, prediction accuracy gradually increased by growth of learning set size, The prediction software and learning data are currently available on the web site.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.708-714
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• 2006

The World Wide Web has become an entrenched global medium for storing and searching information. Most people begin at a Web search engine to find information, but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is Web spamming as Google bombing that is based on the PageRank algorithm, one of the most famous Web structuring techniques. In this paper, we regard the Web as a directed labeled graph that Web pages represent nodes and the corresponding hyperlinks edges. In the present work, we define the label of an edge as having a link context and a similarity measure between link context and the target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. A motivating example is investigated in terms of the Singular Value Decomposition with which our algorithm can outperform to filter the Web spamming pages effectively.

• Communications of Mathematical Education
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• v.26 no.4
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• pp.351-362
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• 2012

Until the 1950s, linear algebra was considered only as one of abstract and advanced mathematics subject among in graduate mathematics courses, mainly dealing with module in algebra. Since the 1960s, it has been a main subject in undergraduate mathematics education because matrices has been used all over. In Korea, it was considered as a course only for mathematics major students until 1980s. However, now it is a subject for all undergraduate students including natural science, engineering, social science since 1990s. In this paper, we investigate the early history of linear algebra and its development from a historical perspective and mathematicians who made contributions. Secondly, we explain why linear algebra became so popular in college mathematics education in the late 20th century. Contributions of Chinese and H. Grassmann will be extensively examined with many newly discovered facts.