The Society of Convergence Knowledge Transactions ISSN:2287-8920(Print) 융복합지식학회논문지

In the rapidly changing technology development, mobile devices are being actively used in a number of specific fields beyond simply providing daily information, which now plays a very important role beyond personal information protection and authentication. Due to this, the user authentication means of the mobile device is being studied and put to practical use from various angles, and is being changed and developed in various ways. In recent years, biomatrix-based authentication has been in the spotlight as a more convenient and safer method than existing knowledge-based authentication methods such as passwords and pattern locks, but it still has vulnerabilities. In this study, first, the classification of user authentication methods is investigated, the social engineering attack type is analyzed, and the existing authentication techniques and the problems of biometric authentication are discussed. After that, considering the efficient method of each authentication method, the pattern is imaged and randomized for the safety of social engineering attacks in the existing pattern-based authentication, and this is used as the authentication value based on the image sequence selected by the user. In addition, fingerprint recognition, one of biometrics, is added to increase the security level, and a new type of convergence strong authentication method is proposed by mixing knowledge-based authentication and biometric-based authentication of user authentication methods.

University graduates are despairing about the employment cliff, and small and medium enterprises are suffering from labor shortages. Is university students have a low perception of employment in SMEs? This study is to investigate the perception of local university students on employment of SMEs. For this purpose, questionnaires were distributed to all students of B university and 562 respondents answered. The results of the survey showed that SMEs were the fourth in the type of job they wanted to work, but the first in the type of job that is likely to work. 76.5% of the respondents said that they are willing to work in SMEs, which means that university students’ perception of employment in SMEs has increased considerably, and it is necessary to reflect it in education and career guidance. The most important things for the employment of SMEs were ‘working environment’, ‘pay level’, ‘appropriation and interest’, ‘employment stability’, and ‘corporate reputation’.

The purpose of this study is to in-depth understanding of the experiences and experiences of distance learning of nursing freshmen in the context of COVID-19. In this study, in which nine new students from the Department of Nursing participated, individual and focus group interviews were conducted, and the content analysis method was applied to analyze their experiences. 172 statements were extracted significantly and analyzed into 5 categories and 10 subcategories. The derived five components are loss of opportunity, delay in adaptation, sense of crisis, situational awareness, acceptance and coping. This study will be able to provide basic data for establishing educational programs, educational policies, and financial support.

As artificial intelligence (AI) emerges as core future technology, the amount of AI training data is increasing exponentially, and the importance of a data platform that can manage the collected or processed data safely is also increasing. For this purpose, cloud platforms with the advantage of data distribution management and service linkage are attracting attention, and various issues such as cloud implementation models and data security are being discussed. In this paper, we review hybrid cloud-related technologies as a sustainable data distribution platform for various institutions and introduce domestic and foreign hybrid/multi-cloud implementation strategies considering the scalability of multi-organizational data sharing. In addition, we discuss strategies to implement public cloud platforms with lower vendor dependence in a situation where the cloud market is expanding by foreign products considering multi-cloud application methods that can be linked with the cloud technology of multiple vendors, such as IaaS development based on domestic communication infrastructure with foreign SaaS.

Compared to general visible light images, infrared images have relatively few available data sets and also have high image acquisition costs. Therefore, in the field of machine learning or simulation, research to generate and utilize infrared images is active. In this paper, a method for generating infrared images based on precise surface temperature calculation and its implementation result are presented. Thermal analysis was performed on a vehicle with a complex shape based on a three-dimensional conjugate heat transfer analysis based on actual physical formulas, and it was confirmed that the error of the proposed method was about 1%. As a result of the implementation, it was confirmed that an infrared image similar to an image captured by an actual infrared camera can be generated when an infrared image is generated using the accurate surface temperature and BRDF (Bi-Directional Reflectance Distribution Function).

In this study, the acryl polymer-transition metal complex catalytic electrode was prepared by one-step plasma process. In details three-type precursors with acrylic acid-Cu complex, acrylic acid-Ni complex, and acrylic acid-Cu/Ni binary complex was synthesized by complexation reaction, after then the acrylic polymer-transition metal complex catalytic electrode was synthesized by one-step plasma process of the synthesized precursors on the surface of ITO glass. The successful preparation of three-type electrodes was conformed via water contact angle analysis SEM (Scanning Electron Microscopy), SEM-EDS (SEM Energy Dispersive X-ray Spectrometry), AFM (Atomic Force Microscope), XPS (X-ray Photoelectron Spectroscopy) and electrochemical analysis, respectively. Furthermore the catalytic efficiency for fuel cell was evaluated via electrochemical oxidation of methanol to know the possibility used by methanol fuel cell catalyst. As results, the catalytic efficiency was as following order: acryl polymer-Cu/Ni binary transition metal complex >> acryl polymer-Cu transition metal complex, while the acryl-Ni transion complex was not obtained the catalytic efficiency for methanol oxidation. From these results the polyacrylic acid-Cu/Ni binary transition metal complex and polyacrylic acid-Cu transition metal complex catalysts could be used as methanol fuel cell catalysts. In addition the one-step plasma process is good method for preparation of the fuel cell catalysts.

The purpose of this study is to examine the problems and issues of casino accounting in Korea forced on the expenses related to promotional activities through reviewing cases of casino promotional accounting in other major countries and tried to suggest improvement plans for casino accounting in Korea. The results of this study are as follows. First, we suggested that the promotional coupons and chips provided by casino marketing activities should be included in the amount of income when the customer drops it, and at the same time include the same amount in the total payment amount so as not to affect the total sales amount. Second, we included the number of promotional chips and coupons in total sales, and suggested that if the customer wins, the amount would be subtracted from total sales. Third, we proposed to include the amount of money to be paid when the customer wins, not including the amount corresponding to the promoted chips and coupon, from the total income collected from the customer.

In terms of the linguistic landscape, attention is paid to the actual condition of road signs, but empirical research on this is insufficient. This study investigated the status and behavior of road signs in marine tourism cities, and examined the trends and patterns of multilingual notation. To this end, 280 road sign users in Busan and Yokohama were empirically verified through structural equation modeling (SEM) on the effect of aesthetics and presence on information usefulness and user satisfaction from a personal characteristic perspective. As a result of the analysis, it was found that both Busan and Yokohama users had a significant positive effect on information usefulness, and information usefulness had a significant positive effect on the relationship between user satisfaction. In particular, it was found that presence had a relatively higher effect than aesthetics. The results of this study not only provide cognitive mechanisms for practitioners to design and apply linguistic landscapes (road signs), but can also be used as a criterion for determining whether linguistic landscapes (road signs) have been effectively implemented. In addition, with a new approach, it will contribute to the management plan of the linguistic landscape that can be actually used for the establishment and operation of strategies in tourist cities through the mechanism of road signs.

The novel infectious disease COVID-19, which started in December 2019, has plunged the world into a pandemic era. As a result, countries around the world took measures to restrict entry for domestic and foreign nationals due to concerns about the spread of COVID-19. As travel restrictions were imposed due to COVID-19, keywords such as ‘corona blue’ surged, and the frequency of depression increased. Previously, the relationship between Corona 19 and stress was about work, and the relationship between Corona 19 and travel is also about analysis data, not about countermeasures. Therefore, this paper is a study that aims to contribute to deriving keywords by analyzing the stress semantic network in the era of COVID-19 and suggesting a new direction related to travel in the post-COVID-19 era. In this paper, stress caused by Corona 19 was analyzed using Textome, a big data analysis tool, and semantic network analysis was performed using UCINET6. In addition, keywords were classified by performing CONCOR analysis to derive clusters of words with similarities. And keyword analysis was performed using TextRank. However, since we have collected travel and stress-focused data from the beginning of COVID-19 to the present, it is necessary to analyze more data in the future by increasing the number of analyzed data.

Purpose: The purpose of this study was to identify factors affecting resilience and to construct a structural model for resilience of new graduate nurses. The model was based on the Polk’s middle-range theory of resilience and literature review. Methods: Data were collected by using a structured questionnaire, which included perceived health status, social support, coping, hope, job-stress, job achievement, post-traumatic growth and resilience. Participants were 211 new graduate nurses. The data were analyzed using SPSS/WIN 26.0 program for descriptive statistics and AMOS 26.0 program for structural equation modeling. Results: Hope, post-traumatic growth and social support had significant direct effect on resilience. But, Social support had no significant total effect on resilience. Job achievement had significant indirect and total effect on resilience. Coping had only significant indirect effect on resilience. Job-stress had only significant direct effect on job achievement. but, Perceived health status was not significant at all. These variables explained 61.7% of total variance of resilience in new graduate nurses. Conclusion: Strategies for improving hope, post-traumatic growth and job achievement will be helpful for enhancing resilience of new graduate nurses.

The development of information and communication technology is bringing huge and rapid changes across society, culture and industry. In addition, the progress of the Fourth Industrial Revolution, represented by intelligence, and the forced introduction of non-face-to-face due to Covid-19 are accelerating the application of ICT applied services to existing offline industries. In particular, museums that will be mainly covered in this study have become places of avoidance due to shutdowns or social distancing. In addition, at the end of the dark tunnel, the era of New-Normal where digital has become commonplace will be in an environment where visitors cannot be treated in the same way as before. These changes are not sudden, but continuous flows, and the introduction speed has only been accelerated due to Covid-19. Therefore, it is essential for museums to provide realistic exhibitions, communication with visitors, and fun factors to enhance visitor satisfaction and revisit by introducing online services. In this study, some methods are proposed to increase the interest and satisfaction of visitors by developing and proposing a technology that provides online experience factors related to exhibition artworks in real time by applying NST, a method of deep learning of an image conversion network using content image and style image as inputs based on a pre-trained model.

Surface runoff on the road flows through gutter drains, collected with street inlet, and drained into sewer pipes. The flow of the road surface shows various aspects depending on the length, width, and slope of the road, the side slope of the gutter, and the change of rainfall intensity. Therefore, it is necessary to analyze the road surface flow according to the change of road conditions and rainfall duration for analysis the storage capacity of the road surface water storage system. In this study, the applicability of fluent model was evaluated to analyze the complex flows such as surface flow on the road and the gutter, stormwater interception at the street inlet, and underground flow through the pipe. As a result of the analysis, the model was simulated appropriately three-dimensional flow of the flow width on the road surface, the inflow and vortex flow at the grate inlet, and inside flow in street inlet. Therefore, the fluent model could be applied to various flow analysis in the gutter reservoir connected to the road.

This study was conducted to verify the effect of MZ generation’s golf practice facility’s selection attributes on customer satisfaction and intention to recommend. The results of this study are as follows. First, Selection attributes (convenience, cost, facility, program) of golf practice facility, only the facility factor was found to have a positive effect on customer satisfaction. Second, Selection attributes (convenience, cost, facility, program) of golf practice facility, only cost, and facility factors were found to have a positive effect on intention to recommend. Third, Customer satisfaction was found to have a positive effect on intention to recommend. Fourth, Selection attributes (convenience, cost, facility, program) of golf practice facility, customer satisfaction was found to have a mediating effect only in the relationship between the cost factor and intention to recommend. As the summary of a characteristic of MZ generation golfers is as follows. First, it was found that the physical environment in golf practice facility was recognized as important because they communicate while actively showing others through SNS. Second, it is the result of the study that because they are familiar with the internet and recognize that rational consumption through price comparison is very important, a strategy such as a price composition is necessary.

With the transition of consumption patterns in the ‘Untact Era’, various types of advertisement have been widely expanded in SNS and portal sites. Through an empirical research on consumer’s perceptions based on Instagram advertising formats, we analyzed the level of interest and favorability. Women tend to have higher purchasing frequency, satisfaction, and reliability than men. People with a high level of interest are more likely to have higher frequency, satisfaction, and reliability. Instagram ads consider typography, illustration, photo, and product review as important factors. Types of advertising formats are mostly focused on intuitive text, product review, and photo. Consumers have a higher preference for reliable quantitative data and reviews. Furthermore, advertisement that visually expresses brand image is preferred. Advertisement based on reviews are preferred in the housewives and over 50s. People with post-graduate degrees showed high preferences in intuitive text advertisement. Teenagers tend to have a low level of interest in using Instagram. The main fields of interest on Instagram are fashion, food, and beauty in order. Men tend to choose a car as a major interest, women choose fashion. Fashion and movies are preferred in teenagers. Their 20s and 30s showed high preferences in fashion. Travel and food are preferred in 40s. Food is preferred in over 50s. We expect that the results presented through this empirical analysis will be used as basic data for SNS advertisement and will help to vitalize the reliable SNS advertisement production.

In this paper, a smart drive system that compensates for the shortcomings of other parking lot applications has been described. The Smart Drive system collects parking information including real-time remaining seats and gas station information from the open API and provides it to users, it predicts and provides real-time remaining seat data by day and hour of the parking lot desired by the user. In addition, by using a recommendation algorithm, it is possible to select a priority among items and recommends parking lots and gas stations that satisfy the user’s requirements. Recommendation service and prediction service, which are the main functions, use chatbots to improve user convenience and intuition. In case the remaining seats are lost while moving to the recommended parking lot, the user can set the remaining seat notification and the number of remaining seats based on the notification on My Page. In this way, when users use the Smart Drive system, they can drive more conveniently and efficiently than they are now. Currently, the number of parking lots provided by the API is small, If future reference materials are used, the number of parking lots that can provide information on remaining seats can be increased.

Up to date, traffic information service provides information about the traffic of the road to the driver, or to give only the statistical data for the management of the road. However, when these information applied to the field of air quality in the close relationship of these traffic, traffic information can provide useful atmospheric environmental Information service. In this paper, we present a method to calculate the pollutant emissions in the exhaust gas of the vehicle, which is the main causes of air pollution, based on the traffic information from the Automatic Vehicle Classification devices installed in road. Also we offers the information service to estimate the emission of pollutants in the exhaust gas of an individual vehicle and provides the amount of air pollutants caused by operation of the vehicle. In order to estimate the emission of pollutants contained in the exhaust gas, the vehicle running speed, type and weight of the vehicle is used to obtain the vehicle-specific emission factors and the pollutant emissions of the individual vehicle is calculated. Data of the calculated pollutant emission is processed in various forms to suit the user's needs and atmospheric environmental service was implemented that is based on the traffic information, which is present the regional/ hourly/ type of vehicle statistics of pollutants.

Most of the small and medium-sized manufacturing companies are considering the introduction of smart facilities to increase productivity and manufacturing competitiveness, but it is difficult to convert to a smart factory due to insufficient investment. However, as ordering companies recently requested information such as production status and defect rate, SMEs are feeling the need to build a smart factory to secure reliability. Therefore, in this paper, aiming at CNC facilities, we designed and implemented a facility monitoring system using power data to support the establishment of smart factories of small and medium-sized enterprises (SMEs). The developed system uses time series data of power supplied to facilities collected from IoT sensor devices to detect abnormal changes in power required for the operation of production facilities, thereby revealing the relationship between abnormal changes in power and quality factors for each product in the future. By providing a power measurement that can be easily measured in almost any field, productivity can be improved.

In predicting stock prices, the biggest obstacle is macro-environment and market volatility. Randomness of stock prices can be resolved to some extent with deep learning algorithms, but external impacts such as the macro-environment surrounding stock prices and rapid changes in the market are factors that make it difficult to predict stock prices, and how to resolve them is the key to the stock price prediction model. Existing stock price prediction research has often used technical indicators. Recently, macroeconomic indicators have also been taken into consideration, and in order to understand the market impact, news information or investor psychology is reflected. There is also a trend to analyze sentiment in the stock community. Therefore, the purpose of this study is to find a deep learning model that uses both internal and external factors that affect stock prices and creates higher predictive power through the inclusion of specific factors or combinations of factors. As a deep learning algorithm, LSTM suitable for time-series data learning was used. As a result of deep learning experiments, it does not seem possible to find a general-purpose model that can be applied to all stocks, but there are combinations of factors that increase the predictive power depending on the industry or price range, and results also shows that the recent data had better predictive power than the past data.