• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.219-225
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• 2019

There is a problem with the existing method of selecting the difficulty levels of Hanja characters. Some Hanja characters selected by the existing methods are different from Sino-Korean words used in real life and it is impossible to know how many times the Hanja characters are used. To solve this problem, we measure the difficulty of Hanja characters using the multiple regression analysis with the frequency as the features. Based on the elementary textbooks, FWS and FHU are counted. A questionnaire is written using the two frequencies and stroke together to answer the appropriate timing of learning the Hanja characters and use them as target variables for regression. Use stepwise regression to select the appropriate features and perform multiple linear regression. The R² score of the model was 0.1105 and the RMSE was 0.1105.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.107-114
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• 2017

Iris diagnosis is an alternative medicine to diagnose the disease of the patient by using different of the iris pattern, color and other characteristics. This paper proposed a disease prediction algorithm that using the iris regions that analyze iris change to using differential image of iris image. this method utilize as patient's health examination according to iris change. Because most of previous studies only find a sign pattern in a iris image, it's not enough to be used for a iris diagnosis system. We're developed an iris diagnosis system based on a iris images processing approach, It's presents the extraction algorithms of 8 major iris signs and correction manually for improving the accuracy of analysis. As a result, PNSR of applied edge detection image is about 132, and pattern matching area recognition presented practical use possibility by automatic diagnostic that presume situation of human body by iris about 91%.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.50 no.1
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• pp.12-20
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• 2014

The objective of this paper is to aid in basic directions for the countermeasure against marine accidents by using the statistical data of Jeju Coast Guard from 1983 to 2012. Marine accidents of about 600~1,000 vessels was reported in all the waters around South Korea from 2000 to 2008. From 2009, these accidents increased rapidly and reached 1,600~2,000 vessels. Although marine accidents of longline fishing vessels did not show a big change prior to 1993, the number have increased steadily until 2007. This is considered a tendency that appears when longline vessels, using the Port of Sungsanpo as a base and operating in fishing grounds in the East China Sea, are converted to long-term fishing from short-term fishing for reasons such as cost reduction due to the sudden rise of oil prices and the performance improvement of the fishing vessels. The number of vessels in marine accidents decreased gradually from 1999 to 2002 and for nearly 7 years from 2002 to 2008, the annual average of marine accidents stayed at 97 vessels. This is seemed to be the result of a change in the policy of either the central or local government and largely associated with changes in the way of statistical processing. This tendency is resulted in lower number of the accidents due to careless navigation which can be viewed as a human error than the number of marine accidents due to poor maintenance as a cause of mechanical failure in the same period. The increase rate in the marine accidents of Jeju Island-based fishing vessels is greater than that of other area-based fishing vessels among the fishing vessels operating in coastal and near sea around Jeju Island each year.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.561-566
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• 2005

This paper presents a visual tracking algorithm for the golf swing motion analysis by using the information of the pixels of video frames and movement of the golf club to solve the problem fixed center point in model based tracking method. The model based tracking method use the polynomial function for trajectory displaying of upswing and downswing. Therefore it is under the hypothesis of the no movement of the center of gravity so this method is not for the amateurs. we proposed method using the information of pixel and movement, we first detected the motion by using the information of pixel in the frames in golf swing motion. Then we extracted the club head and hand by a properties of club shaft that consist of the parallel line and the moved location of club in up-swing and down-swing. In addition, we can extract the center point of user by tracking center point of the line between center of head and both foots. And we made an experiment with data that movement of center point is big. Finally, we can track the real trajectory of club head, hand and center point by using proposed tracking algorithm.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.5
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• pp.127-136
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• 2018

In this paper, we propose a PIN entry method that combines with machine learning technique on smartphone. We use not only a PIN but also touch time intervals and locations as factors to identify whether the user is correct or not. In the user registration phase, a remote server was used to train/create a machine learning model using data that collected from end-user device (i.e. smartphone). In the user authentication phase, the pre-trained model and the saved PIN was used to decide the authentication success or failure. We examined that there is no big inconvenience to use this technique (FRR: 0%) and more secure than the previous PIN entry techniques (FAR : 0%), through usability and security experiments, as a result we could confirm that this technique can be used sufficiently. In addition, we examined that a security incident is unlikely to occur (FAR: 5%) even if the PIN is leaked through the shoulder surfing attack experiments.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.1
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• pp.9-16
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• 2020

The k-anonymity scheme has been widely used to protect private information when Big Data are distributed to a third party for research purposes. When the scheme is applied, an optimal k value determination is one of difficult problems to be resolved because many factors should be considered. Currently, the determination has been done almost manually by human experts with their intuition. This leads to degrade performance of the anonymization, and it takes much time and cost for them to do a task. To overcome this problem, a simple idea has been proposed that is based on machine learning. This paper describes implementations and experiments to realize the proposed idea. In thi work, a deep neural network (DNN) is implemented using tensorflow libraries, and it is trained and tested using input dataset. The experiment results show that a trend of training errors follows a typical pattern in DNN, but for validation errors, our model represents a different pattern from one shown in typical training process. The advantage of the proposed approach is that it can reduce time and cost for experts to determine k value because it can be done semi-automatically.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.1-8
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• 2017

Lightweight Encryption Algorithm(LEA) was developed by National Security Research Institute(NSRI) in 2013 and targeted to be suitable for environments for big data processing, cloud service, and mobile. LEA specifies the 128-bit message block size and 128-, 192-, and 256-bit key sizes. In this paper, block cipher LEA algorithm which can encrypt and decrypt 128-bit messages is designed using Verilog-HDL. The designed IP for encryption and decryption has a maximum throughput of 874Mbps in 128-bit key mode and that of 749Mbps in 192 and 656Mbps in 256-bit key modes on Xilinx Vertex5. The cryptographic IP of this paper is applicable as security module of the mobile areas such as smart card, internet banking, e-commerce and IoT.

• Proceedings of the Korea Database Society Conference
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• 2008.05a
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• pp.339-347
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• 2008

As a number of product information is increasing in online markets, customers can purchase products with no spatial and time problems. However, in case of an online market, since customers can't see products directly, others' reviews make a big influence to customers. Meanwhile, it is a burden to read all reviews about some products. Therefore, we need to provide refined information to customers as summarizing whole product reviews. In this paper, we explain about the product review summarization system which can provide to customers as show evaluation scores of product features. Natural Language Processing skills and computational statistics are utilized for summarization. Customers can get chances to buy a feasible product that he wants to get through this system. Moreover, Enterprises can find out the needs of customers deeply.

• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.18-24
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• 2020

Recently, research on Society 5.0 has been actively carried out in Japan. The Society 5.0 is used in various areas using IoT sensors. This paper proposes a privacy approach model of multiple approaches to IoT users based on Society 5.0. The proposed model used multiple methods of synchronizing important information of IoT devices with one another in the virtual environment. The proposed model improved the efficiency of IoT information by accumulating the weight of IoT information on a probability-based basis. Further, it improves the accuracy of IoT information by segmenting it so that attribute information is linked to IoT information. As a result of the performance evaluation, the efficiency of IoT devices has improved by an average of 5.6 percent, depending on the number of IoT devices and the number of IoT hub devices. Accuracy has improved by an average of 15.9% depending on information collection and processing.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1237-1244
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• 2018

Currently the bottleneck in virtual reality's commercialization might be that high cost VR equipment is needed and interesting VR contents are not enough. The purpose of this paper is to solve these problems by implementing low-cost VR system with wireless controller and HMD(Head Mounted Display) using a smart phone and PC. The functions of real HMD are simulated by utilizing the display and embedded sensors of a smart phone. In that situation PC is in charge of processing huge data and is communicated with smart phone. And wireless controller is designed to make VR user's movement to be free. In addition, we made the several VR contents for testing our prototype system directly. Easy access to VR equipment could induce increasing number of users and investment. And it will be a big step toward improving VR technology and its commercialization.