Digital transformation is accelerating in all industries due to COVID-19 and rapidly developing ICT technology. In the field of education, teaching methods that combine various IT devices and software technologies are being applied. The education requires a future learning environment using EduTech such as digital learning tools. We perform a case study on the use of digital learning tools for effective class. In this study, digital learning tools were applied to an university class. The class was held in the second semester of 2022 at A university, with 67 students participating. In our case, QuizN, Mentimeter, and Google Forms were applied as digital learning tools. In order to evaluate our case, a survey was conducted using the Google Questionnaire. From the results of the survey evaluation, more than 85% of all survey questions answered that they were satisfied. From it, digital learning tools were shown to be effective in class operation.

With the increasing advancement of VLSI technology, health care system is also developing to serve the humanity with better care. Therefore, biomedical implantable devices are one of the amazing important invention of scientist to collect data from the body cell for the diagnosis of diseases without any pain. This Biomedical implantable transceiver circuit has several important issues. Oscillator is one of them. For the design flexibility and complete transistor-based architecture ring oscillator is favorite to the oscillator circuit designer. This paper represents the design and analysis of the a 9-stage CMOS ring oscillator using cadence virtuoso tool in 180nm technology. It is also designed to generate the carrier signal of 403.5MHz frequency. Ring oscillator comprises of odd number of stages with a feedback circuit forming a closed loop. This circuit was designed with 9-stages of delay inverter and simulated for various parameters such as delay, phase noise or jitter and power consumption. The average power consumption for this oscillator is 9.32㎼ and average phase noise is only -86 dBc/Hz with the source voltage of 0.8827V.

The purpose of this study was to analyze the effect of the online extracurricular program operated by the university. The program contents applied in the study included learning strategies such as time management, goal setting, note taking, and memorization methods. The program used in the study was operated in an online environment, and the content was developed between 27 and 29 minutes. The developed contents can be taken using the learning management system. The variables selected to analyze the effects of this program were learning strategies and learning flow, and satisfaction was also included to examine the responses of program participants. The results of the study are as follows. First, learning strategies and learning flow showed statistically significant differences. This result is because the content was composed of meaningful sub-topics by selecting the elements necessary for learning activities. Second, as a result of program satisfaction analysis, it was confirmed that the average for all questions was high. Among them, the average of the item that the theme and contents of the program were useful was the highest. Third, open responses were analyzed by classifying them into cognitive and affective domains. In the cognitive domain, meanings such as knowledge, understanding, and application were presented as keywords, and in the affective domain, a number of keywords for motivation and attitude change were presented. This study is significant in that it provided practical programs necessary for university freshmen and analyzed their effects.

The rise in popularity of cloud services has brought about a heightened concern for security in the field of cloud computing. As a response, governments have implemented CSAP(Cloud Security Assurance Program) to ensure the security of these services. However, despite such measures, the emergence of various security vulnerabilities persists, resulting in incidents related to cloud security breaches. To address this, the utilization of Common Vulnerabilities and Exposures (CVE) has been proposed as a means to facilitate the sharing of vulnerability information across different domains. Nevertheless, the unique characteristics of cloud services present challenges in assigning CVE IDs to the diverse range of vulnerabilities within the cloud environment. In this study, we analyzed how CVE can be effectively employed to enhance cloud security. The assignment of a CVE ID is contingent upon the fulfillment of three rules in the Counting Decision and five rules in the Inclusion Decision. Notably, the third rule in the Inclusion Decision, INC3, clashes with the nature of cloud services, resulting in obstacles in assigning CVE IDs to various cloud vulnerabilities. To tackle this issue, we suggest the appointment of designated individuals who would be responsible for overseeing specific areas of cloud services, thereby enabling the issuance of CVE IDs. This proposed approach aims to overcome the challenges associated with the unique characteristics of cloud services and ensure the seamless sharing of vulnerability information. Information sharing regarding vulnerabilities is crucial in the field of security, and by incorporating cloud vulnerabilities into the CVE system, this method can contribute to enhancing the security of cloud services.

Recently, Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. The UWS is a technology that uses an ultrasonic sensor to detect objects at short distances. While it has the advantage of being simple to use, it also has the disadvantage of having a limited detection distance. The LDWS, on the other hand, is a technology that uses front image processing to detect lane departure and ensure the safety of the driving path. However, it may not be sufficient for determining the driving environment around the vehicle. To overcome these limitations, a system that utilizes FMCW radar is being used. The BSD radar system using FMCW continuously emits signals while driving, and the emitted signals bounce off nearby objects and return to the radar. The key technologies involved in designing the BSD radar system are tracking algorithms for detecting the surrounding situation of the vehicle. This paper presents a tracking algorithm for designing a BSD radar system, while explaining the principles of FMCW radar technology and signal types. Additionally, this paper presents the target tracking procedure and target filter to design an accurate tracking system and performance is verified through simulation.

Because salt and pepper noise is a type of impulse, even a small amount of noise could cause a large image degradation. In this paper, we proposed a salt-and-pepper noise removal method using the convolutional neural network. It consists of four phases. In the first step, the proposed method reconstructs noisy image using a traditional salt-and-pepper noise reduction method, and in the second step, the result image of previous step is filtered with Gaussian low pass filter. After that, we reconstruct the filtered image using convolution neural network. In the last step, the pixels with salt-and-pepper noise are replaced with the result of previous phase. Simulation results show that the proposed method yields not only objective image qualities(PSNR, SSIM) but also subjective image qualities for all SAP noise ratios.

In this paper, IO+5G dedicated hardware is developed and an AI device communication system equipped with a 5G is designed and tested. The AI device communication system equipped with a 5G receives the collected real-time images and the information collected from the IoT sensor in real time is to analyze the information and generates the risk detection events in the AI processing board. The event generated in the AI processing board creates a 5G channel in the dedicated hardware equipped with IO+5G. The created 5G channel delivers event video to the control video server. The 5G based dongle network enables faster data collection and more precise data measurement compared to wireless LAN and 5G routers. As a result of the experiment in this paper, the average test result of the 5G dongle network is about 51% faster than the Wi-Fi average test result in downlink and about 40% faster in uplink. In addition, when comparing the test result with terms of the 5G rounter to be set to 80% upload and 20% download, the average test result is that the 5G dongle network is about 11.27% faster when downloading and about 17.93% faster when uploading. when comparing the test result with terms of the the router to be set to 60% upload and 40% download, the 5G dongle network is about 11.19% faster when downlinking and about 13.61% faster when uplinking. Therefore, in this paper it describes that the developed 5G dongle network can improve the results by collecting data and analyzing it faster than wireless LAN and 5G routers.

On-line learning has been adopted as a major educational method due to the COVID-19 pandemic. Students and faculties got accustomed to on-line educational environment as they experienced it during the COVID-19 pandemic. Development of various technologies and social requirement for educational renovation lay groundwork for on-line learning as well. Therefore, on-line learning or blended learning will be likely to go on after the end of COVID-19 pandemic and it is necessary to prepare the guidelines for effective utilizing on-line learning. The primary purpose of this study is to examine the learning behaviors and the learning effects by using LMS data. Learning behaviors were measured in terms of learning time and access frequency for pre-recorded video lectures targeting computer-practice classes. The results of empirical analysis reveal that frequency was the significant predictor of course achievements but learning time was not. The findings of empirical analysis will provide insights that the effective planning and designing on-line classes based on learning behaviors are key to enhancing learning effects and learner's satisfaction.

The purpose of this study is to examine what are the important variables for information security compliance and whether the information security investment by the industry is different. To comply with the information security policies, the organization must establish measures to prevent or resolve information security incidents. This research process consists of four stages, and the analysis method was conducted with the categorical regression analysis and the correspondence analysis. The first analysis analyzed the independent variables that affect security regulations compliance. The rest of the analysis was conducted by industry in the order of security compliance regulations, manpower investment, and budget investment. As a result of the first analysis, this had positive effects on an organization and personal information protection awareness, joint operation organization of information protection, manpower and budget investment, corporate size, and industry. The correspondence analysis was conducted from the second analysis to the fourth analysis and it analyzed the differences in information security investment by industry. The second analysis showed that the construction industry, science and technology industry, and finance industry have higher compliance with security regulations than other industries. The third analysis showed that the financial industry and the science and technology industry were higher than other industries. The last analysis showed that the financial industry was higher than other industries. The theoretical contribution of this study provided the basis for updating the information security theory. The practical contribution of this study requires government support to reduce information security deviations by industry.

This study is to confirm whether SMEs can manage production facilities well and receive help in establishing new product development strategies if they actively engage in external networks. And under this influence, it is to check whether sales growth and financial performance improve. After reviewing the literature and theory, an empirical analysis using the questionnaire method was conducted to verify the research model. To verify statistical significance, programs 'SPSS 20.0' and 'Smart PLS 2.0' were used. The results of the study are summarized as follows. First, the higher the level of technical cooperation external networking of SMEs, the higher the level of management of their production facilities and new product development strategy was confirmed. Second, it was confirmed that the higher the level of production facility management and new product development strategy of SMEs, the higher their financial performance. Third, among the external networking levels of SMEs, the factor that has the greatest influence on management level of production facilities was identified as degree of participation in human network activities to secure technology. And the factor that had the greatest influence on level of new product development strategy was identified as participation in joint research and commissioned research.

Sustainability is bound to be an eternal topic for managers who run companies. This sustainability is required not only by managers but also by various stakeholders. As a result, many companies are implementing sustainable management and are actively utilizing ESG, which has become a hot topic since 2020. In this study, we examined sustainable management and ESG, focusing on LX Hausys, which was the first in the interior industry to write a sustainable management report and received an ESG evaluation grade A for five consecutive years. As LX Hausys promoted sustainable management, it naturally focused on ESG management. As a result of meeting with LX Hausys HR executives and ESG managers for this study, ESG is not accepted as a new one. Rather, he emphasized that there is no need to approach this approach to ESG with grandeur and difficulty. This approach is consistent with the argument that ESG is a true approach to sustainable growth, not a management strategy based on the times. Like LX Hausys, ESG management can be consistently and continuously performed when implementing ESG strategies based on the resources and capabilities of companies, which can be seen as leading to corporate sustainability. This ESG management will be the right way to create a permanent company.

ChatGPT is an artificial intelligence-based conversation agent developed by OpenAI using natural language processing technology. In this study, an empirical study was conducted on incumbent teachers on the intention to use the newly emerged Chat GPT. First, we studied how accuracy, entertainment, system accessibility, perceived usefulness, and perceived ease of use affect ChatGPT's acceptance intention. In addition, we analyzed whether perceived usefulness and perceived ease of use differ in the intention to accept depending on the digital technology of teachers. As a result of the study, the suitability of the structural equation model was generally good. Accuracy and entertainment were found to have a significant effect on perceived usefulness, and system accessibility was found to have a significant effect on perceived ease of use. In the analysis of teachers' digital technology control effects, it was found that perceived usefulness and perceived ease of use had a control effect between acceptance intentions. It was found that the group with high digital skills of teachers was strongly intended to accept the service regardless of perceived usefulness and ease of use. In the group with low digital skills of teachers, it is thought that ChatGPT's service shows the acceptance intention only when the perceived usefulness and ease of use are high. Therefore, in the group with low digital technology, it is necessary to seek teaching activities such as the development of instructional models using ChatGPT.

Unlike other currencies, cryptocurrency is not a currency used for general transactions, but is currently applied to various investment assets and its scope is expanding. The purpose of this study is to the effect of personal characteristics on investment intention. As a theoretical background, it was verified by applying the Extended Technical Acceptance Model (ETAM). self-confidence propensity, bandwagon propensity, risk tolerance propensity, network externality, attitude, and Investment intention were composed of variables. The research method collected data from 871 people who had experience in cryptocurrency investment through a survey and analyzed it after excluding the data of 71 people who were judged to be inappropriate. The structural equation modeling method using AMOS was used. As a result of this paper, five hypotheses were accepted as statistically significant. This study concluded that self-confidence propensity, bandwagon propensity, risk tolerance propensity, network externality, and attitude had statistically significant effects on Investment intention. In this respect, this study will be able to provide useful information for cryptocurrency research.

The purpose of this study is the effects of Social Characteristics and Personal Characteristics on Virtual Asset Purchase Intention. TPB (Theory of Planned Behavior) model is validated as a theoretical background. possessiveness, and innovation tendency, herding, subjective norm, attitude, and Purchase intention were composed of variables. The method of the study collected 474 data of those experienced in NFT through a survey and conducted as a structural equation modeling method using AMOS. The result of this paper shows that 4 hypotheses are accepted statistically significant except 1 hypotheses among 5 hypotheses. Therefore, this study demonstrated the factors that influence the purchase intention of non-fungible tokens. This study concluded that possessiveness, herding, subjective norm, attitude had a statistically significant effect on Purchase intention. NFT research is just getting started, and there are not many empirical studies targeting investors, interested people, and companies. In this respect, this study will be able to provide useful information for NFT research.

This study investigates customers' perceptions of untack services in the hospitality and foodservice industries based on the Technology Acceptance Model (TAM). The study first identifies Perceived Ease of Use, Perceived Usefulness, and Image as antecedents of customers' Behavioral Intention and Recommendation Intention. Second, the structural relationships among them are established and tested. The study adopts a self-administered survey method, uses SmartPLS 4.0, and applies a two-stage approach. After testing the reliability and validity of customers' 429 data on hospitality and foodservice, hypotheses were tested. The results showed that Perceived Ease of Use significantly affects Perceived Usefulness and Image. Perceived Usefulness significantly also affects Image and Behavioral Intention. The Image of untact services also significantly affects Behavioral Intention and Recommendation Intention. And Behavioral Intention significantly affects Recommendation Intention. Finally, the mediation effects are also all significant. The study's findings suggest that researchers and practitioners should consider the management of Image and Recommendation Intention in the untact service environment.