• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.492-497
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• 2020

Today, banks around the world are making great efforts to adapt to the rapidly changing internal and external environment changes caused by the development of IT technology and to gain a competitive advantage in the market. In particular, in line with the rapid growth of smartphone usage, financial services are also provided in a variety of ways using Fintech, and one of the fastest growing areas is mobile simple payment. Mobile payment service is a financial service that pays the purchase price using a portable mobile device. As fintech, a convergence of financial services and information technology, it is recently used not only in financial services, but also in various industries. It is used in all fields where payment functions such as distribution are available. In the case of mobile cards, it shows that the usage rate of people in their 20s and 30s is increasing very much, so it can be said that the use of mobile payment services will continue to increase in the coming future. We know that simple payments are being used. However, it can be said that the research on the use of mobile payment services by these teenagers is somewhat incomplete. Therefore, this study investigated what factors are important for Korean teenagers to use mobile payment services. As a result, among the five hypotheses presented in this study, all hypotheses were adopted except for , which states that cash usage habits have no effect on innovation.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.426-433
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• 2021

Investment in public sector information services has been on the rise in recent years. The supply of high-speed Internet and smartphones has become more common, and the stability of the information system provided to the public in the public sector has become an important management factor. In other words, tasks such as handling civil complaints and issuing certificates by public institutions, financial transactions by banks, customs clearance work, and e-commerce by individuals or institutions are mostly done online. Therefore, how to deal with obstacles arising from the information system, which is in charge of important civil service affairs, is becoming a very important issue. In other words, in the case of a disability that does not function normally even for a short period of time, various problems can occur when the work is delayed, as well as causing serious financial damage to the civil petitioner. This could be accompanied by a decline in public confidence and various other damages such as filing civil complaints. The reasons for the occurrence of information system failures are very diverse and realistically difficult to predict when. Among the various measures to cope with disability, this paper proposed a plan to establish a disability situation notification system that can minimize confusion caused by disability in the event of a homepage malfunction. The proposed disability situation notification system was established in the public IDC environment to show the possibility of utilization.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.33-39
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• 2021

Speech recognition technology is being combined with deep learning and is developing at a rapid pace. In particular, voice recognition services are connected to various devices such as artificial intelligence speakers, vehicle voice recognition, and smartphones, and voice recognition technology is being used in various places, not in specific areas of the industry. In this situation, research to meet high expectations for the technology is also being actively conducted. Among them, in the field of natural language processing (NLP), there is a need for research in the field of removing ambient noise or unnecessary voice signals that have a great influence on the speech recognition recognition rate. Many domestic and foreign companies are already using the latest AI technology for such research. Among them, research using a convolutional neural network algorithm (CNN) is being actively conducted. The purpose of this study is to determine the non-voice section from the user's speech section through the convolutional neural network. It collects the voice files (wav) of 5 speakers to generate learning data, and utilizes the convolutional neural network to determine the speech section and the non-voice section. A classification model for discriminating speech sections was created. Afterwards, an experiment was conducted to detect the non-speech section through the generated model, and as a result, an accuracy of 94% was obtained.

• Journal of the Korea Society for Simulation
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• v.29 no.4
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• pp.9-19
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• 2020

The number of customers on Social Network Services(SNS) is rapidly increasing with the spread of smartphones. As of 2018, about 2.7 billion people of the world population (about 7.1 billion people) and more than 31.2 million people of the total population of South Korea (about 50.1 million) use SNS. There are several studies have been conducted on increasing SNS market. Most of them, however, were not quantitative but qualitative studies. This study is conducted on domestic SNS market to identify the competitive relationship among SNS platforms with great proportion in South Korea, such as Facebook, Instagram and Twitter. The objective is to suggest some hypotheses of the competitive relations, test them, and finally verify the trend of domestic SNS market. Competitive Lotka-Volterra (LV) model is used to find out the competitive relationships and Moving Window is also used to show the changes of them over time. In order to test the hypotheses on the relationships, some experiments are performed with Moving Window technique. Thus, the relations among the platforms and the changes of them over time are identified.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.620-626
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• 2020

This research propose and simulate a solar power generation system monitoring system based on Modbus TCP communication using RaspberryPi, an IOT equipment, as a master and an inverter as a slave. In this model, various sensors are added to the RaspberryPi to add necessary information for monitoring solar power plants, and power generation prediction and monitoring information are transmitted to the smart phone through real-time power generation prediction. In addition, information that is continuously generated by the solar power plant is built on the server as big data, and a deep learning model for predicting power generation is trained and updated. As a result of the study, stable communication was possible based on Modbus TCP with the Raspberry Pi in the inverter, and real-time prediction was possible with the deep learning model learned in the Raspberry Pi. The server was able to train various deep learning models with big data, and it was confirmed that LSTM showed the best error with a learning error of 0.0069, a test error of 0.0075, and an RMSE of 0.0866. This model suggested that it is possible to implement a real-time monitoring system that is simpler, more convenient, and can predict the amount of power generation for inverters of various manufacturers.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.183-199
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• 2022

With the consumption of smart phone content increasing rapidly, the short clip market in China is rapidly growing. TikTok, a short clip platform, has achieved great business success. However, there is not much research done on TikTok platform from the customers' perspective. To this end, this study aimed to verify the relationship between the social network characteristics on the TikTok platform, attachment toward the TikTok platform, user participation, social identity, psychological distance and reuse intention through an empirical investigation. In August 2021, a survey was conducted on consumers on the subject of TikTok platform in China. The results of the study are as follows. First, the social network characteristics significantly affected the user participation and the attachment. Second, both the attachment and the user participation had a significant impact on reuse intention. Third, user participation had a significant impact on attachment. Fourth, social identity played a significant moderating role in the relationship between social network characteristics and user participation. Fifth, Psychological distance played a significant moderating role in the relationship between social network characteristics and attachment. The results of this study are expected to provide theoretical and practical implications for research on TikTok platform.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.61-70
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• 2022

General users who use smartphone apps often use the Vault app to protect personal information such as photos and videos owned by individuals. However, there are increasing cases of criminals using the Vault app function for anti-forensic purposes to hide illegal videos. These apps are one of the apps registered on Google Play. This paper proposes a methodology for extracting feature points through XML-based keyword frequency analysis to explore Vault apps used by criminals, and text mining techniques are applied to extract feature points. In this paper, XML syntax was compared and analyzed using strings.xml files included in the app for 15 hidden Vault anti-forensics apps and non-hidden Vault apps, respectively. In hidden Vault anti-forensics apps, more hidden-related words are found at a higher frequency in the first and second rounds of terminology processing. Unlike most conventional methods of static analysis of APK files from an engineering point of view, this paper is meaningful in that it approached from a humanities and sociological point of view to find a feature of classifying anti-forensics apps. In conclusion, applying text mining techniques through XML parsing can be used as basic data for exploring hidden Vault anti-forensics apps.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.115-121
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• 2022

As city environments have recently become crowded, there are many obstacles that interfere with the walking of the visually impaired on pedestrian roads. Typical examples include ballads, parking breakers and standing signs, which usually do not get in the way, but blind people may be injured by collisions. To solve such a problem, many solutions have been proposed, but they are limited in applied in practical environments due to the several restrictions such as outside use only, inaccurate obstacle sensing and requirement of special devices. In this paper, we propose a new method to automatically detect obstacles while walking on the pedestrian roads and warn the collision risk in advance by using only sensors embedded in typical mobile phones. The proposed method supports the walking of the visually impaired by notifying the type of obstacles appearing in front of them as well as the distance remaining from the obstacles. To accomplish this goal, we utilized an object recognition technology applying the latest deep learning algorithms in order to identify the obstacles appeared in real-time videos. In addition, we also calculate the distance to the obstacles using the number of steps and the pedestrian's stride. Compared to the existing walking support technologies for the visually impaired, our proposed method ensures efficient and safe walking with only simple devices regardless of the places.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.33-43
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• 2022

In this paper, we propose an ensemble model facilitated by multi-channel palm images with attention U-Net models and pretrained convolutional neural networks (CNNs) for establishing a contactless palm-based user identification system using conventional inexpensive camera sensors. Attention U-Net models are used to extract the areas of interest including hands (i.e., with fingers), palms (i.e., without fingers) and palm lines, which are combined to generate three channels being ped into the ensemble classifier. Then, the proposed palm information-based user identification system predicts the class using the classifier ensemble with three outperforming pre-trained CNN models. The proposed model demonstrates that the proposed model could achieve the classification accuracy, precision, recall, F1-score of 98.60%, 98.61%, 98.61%, 98.61% respectively, which indicate that the proposed model is effective even though we are using very cheap and inexpensive image sensors. We believe that in this COVID-19 pandemic circumstances, the proposed palm-based contactless user identification system can be an alternative, with high safety and reliability, compared with currently overwhelming contact-based systems.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.325-335
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• 2021

Chronic diseases have been increasing recently as the average life expectancy of humans has been extended, and this trend has caused problems such as the widespread demand for health and rehabilitation services and rising medical costs. In order to solve this problem, the community-based rehabilitation has been developed and strengthened in Korea and gradually promoted since 2019. It is important to secure access to clients who want to use services to revitalize community-based rehabilitation. So in this study, as part of the community-based rehabilitation, intends to devise smartphone applications designs and develop a prototype to secure access to community-based occupational therapy services based on occupation and activities. For Occupational Therapy Practice Framework (OTPF), International Classification of Functioning, Disability and Health (ICF), and Allen Diagnostic Module-2 (ADM-2) were used to devise and categorize occupation and activity based application content, and link OTPF, ICF, and ADM-2 through prior research analysis and expert meetings. The derived content was visualized through literature review and activity analysis, and was implemented to enable direct playback within the application using the YouTube API, and finally developed a prototype application. The Android Studio 3.5.2 for Windows 64-bit was used to build the application prototype. In further research, converging various digital technologies for user convenience and additionally researching community-based occupational therapy service providers opinions and service user satisfaction will improve accessibility to community-based occupational therapy services for clients who have difficulty occupational performance in the community.