• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.583-594
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• 2009

Most of the SOA solutions applicable to businesses and organizations are taking a top-down methodology. It starts with an analysis of an organization's requirements, followed by definition of business models and identification of candidate services and ends with finding or developing required services. Challenges in adopting SOA while abandoning legacy systems involve time and cost required during the process. Many businesses and organizations want to gradually migrate into SOA while making the most of the existing system. In this paper, we propose A Method for Migration of Legacy System into Web Service(M-LSWS); it allows legacy system to be migrated into web service accessible by SOA and be used as data repositories. M-LSWS defines procedures for migration into reusable web services through analysis of business processes and identification of candidate services based on design specification and code of legacy system. M-LSWS aims to migrate of legacy system into web service appropriate for SOA. The proposed method consists of four steps: analysis of legacy system, elicitation of reusable service and its specification, service wrapping and service registration. Each step has its own process and guideline. The eligibility of the proposed method will be tested by applying the method to book management system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.37-45
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• 2015

In modern electronic warfare systems, a demand on the more accurate estimation method based on TDOA and FDOA has been increased. TDOA/FDOA localization consists of two-stage procedures: the extraction of information from signals and the estimation of emitter location. Various algorithms based on CAF(complex ambiguity function), which is known as a basic method, has been presented in the area of extractions. When we extract TDOA and FDOA information using a conventional method based on the CAF algorithm from communication signals, considerably long integration time is required for the accurate position estimation of an unknown emitter far from sensors more than 300 km. Such long integration time yields huge amount of transmission data from sensors to a central processing unit, resulting in heavy computiational complexity. Therefore, we theoretically analyze the integration time for TDOA/FDOA information using CRLB and propose a two-stage global optimization algorithm which can minimize the transmission time and a computational complexity. The proposed method is compared with the conventional CAF-based algorithms in terms of a computational complexity and the CRLB to verify the estimation performance.

• Korean Journal of Metals and Materials
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• v.50 no.3
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• pp.256-262
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• 2012

This study investigated the hydrogen storage properties of Zr-Based $AB_{2-x}M_x$ metal hybride made by HCS (Hydriding Combustion Synthesis). The materials were prepared by HCS 80 wt% $AB_2$-15 wt% Mg-5 wt% Mm, HCS 80 wt% $AB_2$-20 wt% Mg and pure Zr-Based $AB_2$, These materials were activated at 298 K under 20 bar. Both HCS 80 wt% $AB_2$-20 wt% Mg and HCS 80 wt% $AB_2$-15 wt% Mg-5 wt% Mm were absorbed within 1 minute. In the case of the $AB_2$, it was perfectly absorbed within 6 minutes. Then, the materials were evaluated to obtain P-C-T (Pressure-Composition-Temperature) curves at 298K. As a result, the hydrogen storage capacity of HCS 80 wt% $AB_2$-20 wt% Mg, HCS 80 wt% $AB_2$-15 wt% Mg-5 wt% Mm and pure Zr-Based $AB_2$ were determined to be 1.2, 1.6 and 1.74 wt%, respectively. The activation energy and rate controlling step were calculated by the Johnson-Mehl Avrami equation. The activation energies of HCS 80 wt% $AB_2$-20 wt% Mg, HCS 80 wt% $AB_2$-15 wt% Mg-5 wt% Mm and pure Zr-Based $AB_2$ were 26.91, 20.45, and 60.41 kJ/mol, respectively. Also, the values of ${\eta}$ in the Johnson-Mehl Avrami equation for HCS 80 wt% $AB_2$-20 wt% Mg, HCS 80 wt% $AB_2$-15 wt% Mg-5 wt% Mm and pure Zr-Based $AB_2$ are 0.60, 0.51, and 0.44. So, the rate controlling steps which indicate hydrogen storage mechanism are an one dimensional diffusion process.

• Journal of Radiation Industry
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• v.6 no.1
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• pp.31-40
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• 2012

There are two methods to fabricate the readout electronic to a large-area CMOS image sensor (LACIS). One is to design and manufacture the sensor part and signal processing electronics in a single chip and the other is to integrate both parts with bump bonding or wire bonding after manufacturing both parts separately. The latter method has an advantage of the high yield because the optimized and specialized fabrication process can be chosen in designing and manufacturing each part. In this paper, LACIS chip, that is optimized design for the latter method of fabrication, is presented. The LACIS chip consists of a 3-TR pixel photodiode array, row driver (or called as a gate driver) circuit, and bonding pads to the external readout ICs. Among 4 types of the photodiode structure available in a standard CMOS process, $N_{photo}/P_{epi}$ type photodiode showed the highest quantum efficiency in the simulation study, though it requires one additional mask to control the doping concentration of $N_{photo}$ layer. The optimized channel widths and lengths of 3 pixel transistors are also determined by simulation. The select transistor is not significantly affected by channel length and width. But source follower transistor is strongly influenced by length and width. In row driver, to reduce signal time delay by high capacitance at output node, three stage inverter drivers are used. And channel width of the inverter driver increases gradually in each step. The sensor has very long metal wire that is about 170 mm. The repeater consisted of inverters is applied proper amount of pixel rows. It can help to reduce the long metal-line delay.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.9
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• pp.251-260
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• 2021

Gait analysis is one of the research fields for obtaining various information related to gait by analyzing human ambulation. It has been studied for a long time not only in the medical field but also in various academic areas such as mechanical engineering, electronic engineering, and computer engineering. Efforts have been made to determine whether there is a problem with gait through gait analysis. In this paper, as a pre-step to find out gait abnormalities, it is investigated whether it is possible to differentiate whether experiment participants wear elderly simulation suit or not by applying gait data to machine learning models for the same person. For a total of 45 participants, each gait data was collected before and after wearing the simulation suit, and a total of six machine learning models were used to learn the collected data. As a result of using an artificial neural network model to distinguish whether or not the participants wear the suit, it showed 99% accuracy. What this study suggests is that we explored the possibility of judging the presence or absence of abnormality in gait by using machine learning.

• Journal of Internet of Things and Convergence
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• v.7 no.3
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• pp.81-90
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• 2021

In this study, the effect of user characteristics and technical characteristics of a blockchain-based financial platform on the intention to use of financial consumers was analyzed. Also, in this influence relationship, we analyzed what kind of causal relationship between relative advantage and perceived risk on intention to use. From June 1 to July 30, 2021, a non-face-to-face self-filling online survey was conducted with a sample of subjects who had experience using a financial platform grafted with blockchain technology, and the study was conducted in 187 copies. For statistical processing, frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis and 3-step mediated regression analysis were performed using SPSS 21.0 program. The significance level of the statistical value was set to less than 95%. The research results are as follows. First, it was found that innovativeness and usefulness affect the intention to use in the user characteristics. Second, in the technical characteristics, compatibility and reliability were found to affect the intention to use. Third, it was found that relative advantage and perceived risk play a partial mediating role in the relationship between user characteristics and intention to use. Fourth, it was found that relative advantage and perceived risk play a partial mediating role in the relationship between technical characteristics and intention to use. Fifth, it was found that there were differences in the ubiquity of user characteristics, compatibility of technical characteristics and intention to use according to the experience of using the certificate. The results of this study can contribute to the development of a financial platform based on the Internet of Things.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.4
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• pp.65-74
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• 2021

In order to efficiently inspect rapidly increasing old tunnels in many well-developed countries, many inspection methodologies have been proposed using imaging equipment and image processing. However, most of the existing methodologies evaluated their performance on a clean concrete surface with a limited area where other objects do not exist. Therefore, this paper proposes a 6-step framework for tunnel crack detection deep learning model development. The proposed method is mainly based on negative sample (non-crack object) training and Cascade Mask R-CNN. The proposed framework consists of six steps: searching for cracks in images captured from real tunnels, labeling cracks in pixel level, training a deep learning model, collecting non-crack objects, retraining the deep learning model with the collected non-crack objects, and constructing final training dataset. To implement the proposed framework, Cascade Mask R-CNN, an instance segmentation model, was trained with 1561 general crack images and 206 non-crack images. In order to examine the applicability of the trained model to the real-world tunnel crack detection, field testing is conducted on tunnel spans with a length of about 200m where electric wires and lights are prevalent. In the experimental result, the trained model showed 99% precision and 92% recall, which shows the excellent field applicability of the proposed framework.

• Journal of Internet of Things and Convergence
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• v.7 no.4
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• pp.85-94
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• 2021

This study verified what differences in screen golf content characteristics, intention to reuse, customer satisfaction and economic value experienced by consumers according to the image feeling, expression method, and image color provided by screen golf graphic content. In addition, the purpose of this study was to analyze what kind of influence the content characteristics of screen golf have on the economic value and what kind of influence the intention to reuse and customer satisfaction have in this process. From September 1, 2021 to September 30, 2021, a survey of 225 copies of consumers using the screen golf course was conducted. For data processing, frequency analysis, factor analysis, reliability analysis, cluster analysis, chi-square analysis and 3-step mediated regression analysis were performed. The research results are as follows. First, the preferred image feeling showed a high level of clean and sophisticated feeling and the preferred expression method showed a high realistic image. In addition, the preferred image color showed a high level of green color. Second, there were differences in competitiveness, ease of use, sense of solidarity and realism according to the degree of consideration of graphic content and differences in consumer's intention to reuse, customer satisfaction, and economic value. Third, in the relationship between screen golf content characteristics and economic value, customer satisfaction and re-use intention had a mediating effect. Through this study, by providing basic data to derive the graphic design model of screen golf, the operating entity suggested a way to improve economic benefits and tried to contribute to the growth of the screen golf industry.

• Journal of Korean Society of Archives and Records Management
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• v.19 no.3
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• pp.223-245
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• 2019

As the foundation for the Fourth Industrial Revolution, blockchain is becoming an essential core infrastructure and technology that creates new growth engines in various industries and is rapidly spreading to the environment of businesses and institutions worldwide. In this study, the characteristics and trends of blockchain technology were investigated and arranged, its application to the records management section of public institutions was required, and the procedures and methods of construction in the records management field of public institutions were studied in literature. Finally, blockchain technology was applied to the records management to propose an archive chain model and describe possible expectations. When the transactions that record the records management process of electronic documents are loaded into the blockchain, all the step information can be checked at once in the activity of processing the records management standard tasks that were fragmentarily nonlinked. If a blockchain function is installed in the electronic records management system, the person who produces the document by acquiring and registering the document enters the metadata and information, as well as stores and classifies all contents. This would simplify the process of reporting the production status and provide real-time information through the original text information disclosure service. Archivechain is a model that applies a cloud infrastructure as a backend as a service (BaaS) by applying a hyperledger platform based on the assumption that an electronic document production system and a records management system are integrated. Creating a smart, electronic system of the records management is the solution to bringing scattered information together by placing all life cycles of public records management in a blockchain.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.27-36
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• 2019

In this study, experiments on the improvement of the emotion classification, analysis and accuracy of EEG data were proceeded, which applied DEAP (a Database for Emotion Analysis using Physiological signals) dataset. In the experiment, total 32 of EEG channel data measured from 32 of subjects were applied. In pre-processing step, 256Hz sampling tasks of the EEG data were conducted, each wave range of the frequency (Hz); Theta, Slow-alpha, Alpha, Beta and Gamma were then extracted by using Finite Impulse Response Filter. After the extracted data were classified through Time-frequency transform, the data were purified through Independent Component Analysis to delete artifacts. The purified data were converted into CSV file format in order to conduct experiments of Machine learning algorithm and Arousal-Valence plane was used in the criteria of the emotion classification. The emotions were categorized into three-sections; 'Positive', 'Negative' and 'Neutral' meaning the tranquil (neutral) emotional condition. Data of 'Neutral' condition were classified by using Cz(Central zero) channel configured as Reference channel. To enhance the accuracy ratio, the experiment was performed by applying the attributes selected by ASC(Attribute Selected Classifier). In "Arousal" sector, the accuracy of this study's experiments was higher at "32.48%" than Koelstra's results. And the result of ASC showed higher accuracy at "8.13%" compare to the Liu's results in "Valence". In the experiment of Random Forest Classifier adapting ASC to improve accuracy, the higher accuracy rate at "2.68%" was confirmed than Total mean as the criterion compare to the existing researches.