• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.259-265
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• 2017

This study reviewed the existing studies in order to set up a strategy that can achieve the trust and business performance of the franchisers, who are actually operating franchised business, breaking from the research trend centered around franchise headquarters and added the factors of the franchise headquarters' strategy for expanding franchises, including word-of-mouth communication and advertising & publicity and added the exercise of recruitment agency outsourcing, flagship store, recently utilized often as preceding variables to verify the causal relation between the trust of the franchiser and the business performance of the franchise. The implications of this study, it can be concluded that the government authority for the attraction of healthy franchises can continuously attract franchises and enter the market can continuously attract franchises by increasing the trust of the franchises, and powerfully investing and managing them for the effort through word-of-mouth marketing. It is expected that this study will be helpful in the establishment of a business strategy for forming a continuous relationship as well as the franchise head office's strategy for the recruitment of new franchises.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1393-1401
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• 2013

What is RFID Microchip tag attached to an object, the reader recognizes technology collectively, through communication with the server to authenticate the object. A variety of RFID tags, 13.56Mhz bandwidth RFID card, ISO/IEC 14443 standards based on NXP's Mifare tag occupies 72.5% of the world market. Of the Mifare tags, low cost tag Mifare Classic tag provided in accordance with the limited hardware-based security operations, protocol leaked by a variety of attacks and key recovery vulnerability exists. Therefore, in this paper, Cryptography Scheme and Secure Protocol for Safety Secure Scheme Construction in 13.56Mhz RFID have been designed. The proposed security scheme that KS generated by various fixed values and non-fixed value, S-Box operated, values crossed between LFSR and S-Box is fully satisfied spoofing, replay attacks, such as vulnerability of existing security and general RFID secure requirement. Also, It is designed by considering the limited hardware computational capabilities and existing security schemes, so it could be suit to Mifare Classic now.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.160-166
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• 2018

The worldwide semi-conductor market has been growing for a long time. Manufacturing lines of semi-conductors need to handle several types of toxic gases. In particular, they need to be controlled accurately in real time. This type of toxic gas control system consists of many different kinds of parts, e.g., fittings, valves, tubes, filters, and regulators. These parts obviously need to be manufactured precisely and be corrosion resistant because they have to control high pressure gases for long periods without any leakage. For this, surface machining and hardening technologies of the metal block and metal gasket need to be studied. This type of study depends on various factors, such as geometric shapes, part materials, surface hardening method, and gas pressures. This paper presents strong concerns on a series of simulation processes regarding the differences between the inlet and outlet pressures considering several different fluid velocity, tube diameters, and V-angles. Indeed, this study will very helpful to determine the important design factors as well as precisely manufacture these parts. The EP (Electrolytic Polishing) process was used to obtain cleaner surfaces, and hardness tests were carried out after the EP process.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.773-782
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• 2019

Basel III (Third Basel Accord or Basel Standards) is a global, voluntary regulatory framework on bank capital adequacy, stress testing, and market liquidity risk. Basel III regulatory ratios include capital adequacy, asset soundness, and liquidity. The capital adequacy variables include BIS capital adequacy ratio, BIS tier 1 capital ratio, and tangible common equity ratio. The asset soundness variables include non-performing loan ratio and non-performing loan coverage ratio. The liquidity regulation variables include KRW liquidity coverage ratio and foreign currency liquidity coverage ratio. This study aims to investigate how capital adequacy standard affects efficiency of internet primary banks. As a result of this study, BIS capital adequacy ratio of domestic internet primary banks is lower than that of commercial banks. In order to maintain sustainable operation considering capital adequacy regulations, it is necessary to expand additional capital. In addition, the delinquency rate and non-performing loan ratio of domestic internet primary banks is gradually increasing due to the maturity of high-yield loans in 2019.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.107-117
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• 2019

In the era of SNS, many people relies on it to express their emotions about various kinds of products and services. Therefore, for the companies eagerly seeking to investigate how their products and services are perceived in the market, emotion mining tasks using dataset from SNSs become important much more than ever. Basically, emotion mining is a branch of sentiment analysis which is based on BOW (bag-of-words) and TF-IDF. However, there are few studies on the emotion mining which adopt feature selection (FS) methods to look for optimal set of features ensuring better results. In this sense, this study aims to propose FS methods to conduct emotion mining tasks more effectively with better outcomes. This study uses Twitter and SemEval2007 dataset for the sake of emotion mining experiments. We applied three FS methods such as CFS (Correlation based FS), IG (Information Gain), and ReliefF. Emotion mining results were obtained from applying the selected features to nine classifiers. When applying DT (decision tree) to Tweet dataset, accuracy increases with CFS, IG, and ReliefF methods. When applying LR (logistic regression) to SemEval2007 dataset, accuracy increases with ReliefF method.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.133-140
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• 2019

Following the recent US trade deficit, the trade war began between Korea and Japan in July. Korea's trade dependence is about 60% or more, indicating high export dependence and import dependence. The purpose of this study is to examine export amount, export volume, export price index, Treasury bond interest rate and analyze how index affects export amount. This study attempts to analyze the comovement and volatility with export amount. For this purpose, monthly data for each indicator were selected for a total of 234 months from January 2000 to June 2019. As a result of analysis, exports amount and exports volume showed very high comovement, exports amount and interest rates showed low comovement, but exports amount and exports prices showed very low comovement. In the future, Korea should continue to increase exports amount in view of its high dependence on trade, along with policies to expand the domestic market. To this end, strategy to increase exports volume should be presented. Korea should increase the logistics environment and competitiveness of each port and airport, improve domestic and overseas network construction and support services of logistics companies.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.261-267
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• 2021

This study aims to explore the effect of beauty lifestyle behaviors on the pursuit of beauty values and cosmetics purchasing behaviors in female college students, identify consumption market of female college students in beauty industry and contribute to the advancement of beauty industry. Data were collected by conducting a survey in 328 students. The survey was performed using self-administered questionnaires answered by the respondents themselves. The survey items were rated on a 5-point Likert scale and multiple choice question type was used. Statistical analyses were done using SPSS Statistics ver. 22.0. The study results are as follows. First, the regression analysis on the effect of beauty lifestyle behaviors on the pursuit of beauty values were found to be impacted on the sub-variables of beauty lifestyle behaviors including manicure, make-up, diet, body-shaping, and shopping behaviors (p<0.01). Second, the results of a difference in the pursuit of beauty values by cosmetics purchasing behavior showed that purchase frequency of cosmetic products for buying cosmetics were found to be statistically significant Third, as the results of a difference in cosmetics purchasing behaviors by beauty lifestyle behavior, reasons for the purchase frequency of cosmetic products, cost of purchasing cosmetics were statistically significant.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.9-16
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• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.73-86
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• 2021

The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.67-78
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• 2022

Interest in bio-signal monitoring of wearable devices is increasing significantly as the next generation needs to develop new devices to dominate the global market of the information and communication technology industry. Accordingly, this research developed a resistive textile strain sensor through a wetting process in a single-wall carbon nanotube dispersion solution using an E-Band with low hysteresis. To measure the resistance signal in the E-Band to which electrical conductivity is applied, a universal material tester, an Arduino, and LCR meters that are microcontroller units were used to measure the resistance change according to the tensile change. To effectively handle various noises generated due to the characteristics of the fabric textile strain sensor, the filter performance of the sensor was evaluated using the moving average filter, Savitsky-Golay filter, and intermediate filters of signal processing. As a result, the reliability of the filtering result of the moving average filter was at least 89.82% with a maximum of 97.87%, and moving average filtering was suitable as the noise filtering method of the textile strain sensor.