• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1062-1071
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• 2003

A genre-based classification means classifying documents by the purpose for which they were written, not by the semantics or subject areas. Most genre classifying methods in the past were based on the existing documents categorization algorithms and ineffective for feature selections, resulting in low quality classification results. In this research, we propose a new method for automatic classification of digital documents by genre. The genre classifier we developed uses the deviation statistic between the genre-revealing term frequencies and between the subject-revealing term frequencies within a genre. We collected Web documents to evaluate the proposed genre classification method. The experimental results show that the proposed method outperforms a direct application of a kai-square feature selection and bayesian classifier often used for subject classification by proving an excellent accuracy of about 30 percent.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.65-70
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• 2013

Recently, the field of computer vision has been actively researched through digital image which can be easily generated as the development and expansion of digital camera technology. Especially, research that extracts and utilizes the feature in image has been actively carried out. The image stitching is a method that creates the high resolution image using features extract and match. Image stitching can be widely used in military and medical purposes as well as in variety fields of real life. In this paper, we have proposed efficient image stitching method using fast feature descriptor extraction and matching based on SURF algorithm. It can be accurately, and quickly found matching point by reduction of dimension of feature descriptor. The feature descriptor is generated by classifying of unnecessary minutiae in extracted features. To reduce the computational time and efficient match feature, we have reduced dimension of the descriptor and expanded orientation window. In our results, the processing time of feature matching and image stitching are faster than previous algorithms, and also that method can make natural-looking stitched image.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.205-208
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• 2013

Generally, binary pattern transforms have been used in the field of the face recognition and facial expression, since they are robust to illumination. Thus, this paper proposes an illumination-robust face recognition system combining an MLDP, which improves the texture component of the LDP, and a 2D-PCA algorithm. Unlike that binary pattern transforms such as LBP and LDP were used to extract histogram features, the proposed method directly uses the MLDP image for feature extraction by 2D-PCA. The performance evaluation of proposed method was carried out using various algorithms such as PCA, 2D-PCA and Gabor wavelets-based LBP on Yale B and CMU-PIE databases which were constructed under varying lighting condition. From the experimental results, we confirmed that the proposed method showed the best recognition accuracy.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.130-135
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• 2008

An aerodynamic optimization design process of multistage axial turbine is presented in this article: first, applying quasi-three dimensional(Q3D) design methods to conduct preliminary design and then adopting modern optimization design methods to implement multistage local optimization. Quasi-three dimensional(Q3D) design methods, which mainly refer to S2 flow surface direct problem calculation, adopt the S2 flow surface direct problem calculation program of Harbin Institute of Technology. Multistage local optimization adopts the software of Numeca/Design3D, which jointly adopts genetic algorithm and artificial neural network. The major principle of the methodology is that the successive design evaluation is performed by using an artificial neural network instead of a flow solver and the genetic algorithms may be used in an efficient way. Flow computation applies three-dimensional viscosity Navier Stokes(N-S) equation solver. Such optimization process has three features: (i) local optimization based on aerodynamic performance of every cascade; (ii) several times of optimizations being performed to every cascade; and (iii) alternate use of coarse grid and fine grid. Such process was applied to optimize a three-stage axial turbine. During the optimization, blade shape and meridional channel were respectively optimized. Through optimization, the total efficiency increased 1.3% and total power increased 2.4% while total flow rate only slightly changed. Therefore, the total performance was improved and the design objective was achieved. The preliminary design makes use of quasi-three dimensional(Q3D) design methods to achieve most reasonable parameter distribution so as to preliminarily enhance total performance. Then total performance will be further improved by adopting multistage local optimization design. Thus the design objective will be successfully achieved without huge expenditure of manpower and calculation time. Therefore, such optimization design process may be efficiently applied to the aerodynamic design optimization of multistage axial turbine.

• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.121-128
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• 2015

This study aimed to investigate the effects of an unplugged robot education system capable of computerless coding education. Specifically, this study compared this education system with PicoCricket, an educational robot that can also be used with elementary students in lower grades, using assessment tools on perceived usefulness and ease. Using random sampling and randomized assignment for more objective validation, 30 participants were assigned to the unplugged robot education system group (experimental group) and 30 participants were assigned to the PicoCricket group (control group), for a total of 60 study participants. The research procedure included verification of the equivalence of the two groups by conducting a pretest after a 2-hour basic training session on algorithms and programming. The experimental and control groups learned the same content using different educational tools in accordance with software training guidelines for a total of 12 hours. Then, the difference in perceived usefulness and ease between the two groups was examined using a post-treatment test. The study results showed that scores on both dependent variables, perceived usefulness and perceived ease, were significantly higher in the experimental group than the control group. Moreover, scores on all sub-variables of the dependent variables were significantly higher in the experimental group than the control group. These results suggest that learners using the unplugged robot education system found it more useful and easier to use than learners using the existing educational robot, PicoCricket. This study's findings are significant, as according to the technology acceptance model, the perceived usefulness and ease of an educational tool are important variables that determine the acceptance of the tool (i.e., persistence of learning).

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.66-74
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• 2021

With the development of the Internet, user authentication technology that proves me online is improving. Existing ID methods pose a threat of personal information leakage if the service provider manages personal information and security is weak, and the information subject is to the service provider. In this study, as online identification technology develops, we propose a DID-based self-authentication model to prevent the threat of leakage of personal information from a centralized format and strengthen sovereignty. The proposed model allows users to directly manage personal information and strengthen their sovereignty over information topics through VC issued by the issuing agency. As a research method, a self-authentication model that guarantees security and integrity is presented using a decentralized identifier method based on distributed ledger technology, and the security of the attack method is analyzed. Because it authenticates through DID Auth using public key encryption algorithms, it is safe from sniffing, man in the middle attack, and the proposed model can replace real identity card.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.1
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• pp.387-394
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• 2019

Recently, the importance of big data has been increased, and demand for data analysis for the big data is also increased. R language is developed for data analysis, and users are analyzing data by using algorithms of various statistics, machine learning and data mining packages in R language. However, it is difficult to develop an application using R. Early study proposed a method to call R script through another language such as PHP, Java, and so on. However, it is troublesome to write such a development method in addition to R in combination with other languages. In this study, we introduce how to write API using only R language without using another language by using Plumber package. We also propose a solution for security issues related with R API. If we use propose technology for developing web application, we can expect high productivity, easy of use, and easy of maintenance.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.49-57
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• 2021

With the advent of the era of the fourth industry, more and more scientific techniques are being used to solve decision-making problems. In particular, big data analysis technology is developing as it becomes easier to collect numerical data. Therefore, in this study, in order to overcome the limitations of qualitatively analyzing investment trends, the association of various products was analyzed using associated analysis techniques. For the experiment, two experimental periods were divided based on the COVID-19 economic crisis, and sales information from individuals, institutions, and foreign investors was collected, and related analysis algorithms were implemented through r software. As a result of the experiment, institutions and foreigners recently invested in the KOSPI and KOSDAQ markets and bought futures and products such as ETF. Individuals purchased ETN and ETF products together, which is presumed to be the result of the recent great interest in sector investment. In addition, after COVID-19, all investors tended to be passive in investing in high-risk products of futures and options. This paper is thought to be a useful reference for product sales and product design in the financial field.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.405-410
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• 2018

When more parts are mounted in the same time in a surface mount equipment, the total output will increase and will improve productivity. In this paper, we propose a method to reduce the gantry drive time from the suction to the mounting of the component to improve the productivity of the surface mount equipment. The method was to find a way to get the maximum velocity in front of the camera during the vision inspection. In this paper, we have developed a stop-motion, fly1-motion, and fly2-motion drive time calculation algorithms for vision inspection and calculated the driving time of 3 methods and compared them. As a result, the fly1-motion method shortened the time by 13% and the fly2-motion method shortened the time by 18% than the stop-motion method.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.7
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• pp.275-288
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• 2019

In this paper, we consider a rumor source inference problem when sufficiently many nodes heard the rumor in the network. This is an important problem because information spread in networks is fast in many real-world phenomena such as diffusion of a new technology, computer virus/spam infection in the internet, and tweeting and retweeting of popular topics and some of this information is harmful to other nodes. This problem has been much studied, where it has been shown that the detection probability cannot be beyond 31% even for regular trees if the number of infected nodes is sufficiently large. Motivated by this, we study the impact of query that is asking some additional question to the candidate nodes of the source and propose budget assignment algorithms of a query when the network administrator has a finite budget. We perform various simulations for the proposed method and obtain the detection probability that outperforms to the existing prior works.