• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3221-3242
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• 2021

The purpose of the study is to examine the current study trend of 'QR code' and suggest a direction for the future study of big data analysis: (1) Background: study trend of 'QR code' and analysis of the text by subject field and year; (2) Methodology: data scraping and collection, EXCEL summary, and preprocess and big data analysis by R x 64 4.0.2 program package; (3) the findings: first, the trend showed a continuous increase in 'QR code' studies in general and the findings were applied in various fields. Second, the analysis of frequent keywords showed somewhat different results by subject field and year, but the overall results were similar. Third, the visualization of the frequent keywords also showed similar results as that of frequent keyword analysis; and (4) the conclusions: in general, 'QR code' studies are used in various fields, and the trend is likely to increase in the future as well. And the findings of this study are a reflection that 'QR code' is an aspect of our social and cultural phenomena, so that it is necessary to think that 'QR code' is a tool and an application of information. An expansion of the scope of the analysis is expected to show us more meaningful indications on 'QR code' study trends and development potential.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3793-3814
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• 2021

Most secure solutions like cryptography are software based and they are designed to mainly deal with the outside attacks for traditional networks, but such soft security is hard to be implemented in wireless sensor networks to counter the inside attacks from internal malicious nodes. To address this issue, reputation has been introduced to tackle the inside malicious nodes. Reputation is essentially a stimulating mechanism for nodes' cooperation and is employed to detect node misbehaviors and improve the trust-worthiness between individual nodes. Among the reputation models, binomial distribution based reputation has many advantages such as light weight and ease of implementation in resource-constraint sensor nodes, and accordingly researchers have proposed many insightful related methods. However, some of them either directly use the modelling results, apply the models through simple modifications, or only use the required components while ignoring the others as an integral part of the whole model, this topic still lacks a comprehensive and systematical review. Thus the motivation of this study is to provide a thorough survey concerning each detailed functional components of binomial distribution based reputation for wireless sensor networks. In addition, based on the survey results, we also argue some open research problems and suggest the directions that are worth future efforts. We believe that this study is helpful to better understanding the reputation modeling mechanism and its components for wireless sensor networks, and can further attract more related future studies.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.116-122
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• 2021

This study evaluated the effect of simulation training on cardiac arrest in hospitals for inactive nurses with 360 VR content, and attempted to prepare basic data for simulation training for inactiv nurses in the future. The design of this study is an experiment study before and after a single group. The study period was from October 13, 2020 to December 17, 2020. The subjects of the study were a total of 21 nurses who participated in the education program for inactive nurses. For simulation training for inactive nurses, Microsoft Powerpoint, hybrid simulation, high-fidelity simulation, and 360 VR content were applied for theories education and practical education. As a result of the study, the satisfaction level of the curriculum for the cardiac arrest situation in the hospital for inactive nurses was 4.78±0.36 points out of 5 points. Understanding of education was 4.71±0.46 points out of 5 points. Usefulness of education was 4.80±0.40 points out of 5 points. Confidence in airway maintenance before and after training, BLS review, manual defibrillator, emergency medication administration, airway maintenance, emergency situation simulation, and debriefing were all significant. According to the results of this study, simulation training of the situation of cardiac arrest in the hospitals for inactive nurses was effective. In future studies, it will be necessary to develope and verify specific teaching and learning methods by applying various cases of cardiac arrest situations in consideration of the type of hospitals.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.155-162
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• 2021

With the global COVID-19 pandemic, the tourism sector and all consumption have contracted with the untact era. Wine will also be sold and developed in various ways non-face-to-face in the future. Therefore, it is necessary to develop apps and web servers that focus on health in the era of single-person households and non-face-to-face. This study used facial recognition data based on photos of adult men and women in their 40s and 50s to analyze the Sasang constitution through a mobile app and web server, and suggested wine recommendations suitable for their constitution. First, the user's body information is entered. And through the facial recognition mobile app, recommend the right wine after analyzing the body type. if it's not like the first recommended wine, it is configured to receive another wine recommendation. In the future, the number of single-person households will increase further, and in the age of well-being, wine recommendations that fit my body will be useful. Wine recommendation suitable for Sasang constitution will be a useful mobile application to manage personal healt

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.171-176
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• 2023

What we have in common worldwide today is economic difficulties due to high inflation and uncertainty in the financial industry. The root cause of this is the war between Russia and Ukraine. The war between Russia and Ukraine is not simply a war between two countries. The United States and the European Union are providing military aid such as missiles to Ukraine, and Russia is attacking Ukraine by introducing UAVs (unmanned aerial vehicles) from Iran. A prominent weapon in this Russia-Ukraine war is the UAVs used in Russia. It is predicted that the form of war using UAVs will gradually expand in the future based on stealth. In addition, UAVs will continue to be used due to the fact that they can cause serious damage to the other country without harming their own lives, and because they have good cost-effectiveness. In this study, UAVs based on autonomous driving were studied. The target countries of the study include the United States, the European Union, China, and Iran, and the UAVs used in these countries have characteristics that can represent the world. In this study, the main specifications of major UAVs in use in major countries were investigated. In addition, the future technology and development direction were described through specifications and characteristics of UAVs currently in operation in major countries.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.231-242
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• 2023

Crowd funding faces a number of significant obstacles despite its rapid growth and popularity, with the main one being the possible asymmetric information between fundraisers and potential supporters. A study taxonomy based on signalling theory has been created to compare projects originating from Taiwan and India. This was made possible by obtaining a dataset from the crowd funding website, Kickstarter (Global platform). To make the project effective, the study's goal is to look into how signals (e.g., goal-setting, comments, and updates) might be used to reduce the problem of information asymmetry. Thus, we applied an Ordinary Least Squares (OLS) regression. Both Taiwan and India demonstrated signal mitigation of information asymmetry, but Taiwan showed a stronger relationship between ambitious goals and successful projects than India. The relative importance of project comments has been found to be stronger in Taiwan than in India; the relative importance of project updates has been found to be weaker and negatively correlated with project success in India, in contrast to Taiwan. Notably, our findings provide a theoretical and practical framework for understanding and using signals in successful crowd funding campaigns and activities in these two emerging countries.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.37-45
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• 2023

Adaptive has gained significant attention in Education Technology (EdTech), with personalized learning experiences becoming increasingly important. Next-generation chatbots, including models like ChatGPT, are emerging in the field of education. These advanced tools show great potential for delivering personalized and adaptive learning experiences. This paper reviews previous research on adaptive learning and the role of chatbots in education. Based on this, the paper explores current and future chatbot technologies to propose a framework for using ChatGPT or similar chatbots in adaptive learning. The framework includes personalized design, targeted resources and feedback, multi-turn dialogue models, reinforcement learning, and fine-tuning. The proposed framework also considers learning attributes such as age, gender, cognitive ability, prior knowledge, pacing, level of questions, interaction strategies, and learner control. However, the proposed framework has yet to be evaluated for its usability or effectiveness in practice, and the applicability of the framework may vary depending on the specific field of study. Through proposing this framework, we hope to encourage learners to more actively leverage current technologies, and likewise, inspire educators to integrate these technologies more proactively into their curricula. Future research should evaluate the proposed framework through actual implementation and explore how it can be adapted to different domains of study to provide a more comprehensive understanding of its potential applications in adaptive learning.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.761-770
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• 2021

A study was undertaken to identify variations in the level of awareness, the information collection status, the level of acceptance, and the characteristics of information collection as it pertains to agricultural biotechnology based on information collection in the field of agricultural biotechnology. When examining subjective awareness, objective awareness, and interest in agricultural biotechnology, the results showed that the levels of all three variables were higher in cases where information exploration of agricultural biotechnology had been experienced. Among the participants who have experience in voluntarily collecting information about agricultural biotechnology, helpful information at a rate of 51.6% and harmful information at a rate of 42.0% were acquired, values much higher than the 37% and 30% corresponding rates for participants who had no experience. However, it was also found that harmful information has a significantly greater impact on perceptions of the future. The characteristics of information collection for agricultural biotechnology indicated that those with experience in voluntary information collection particularly preferred the Internet, whereas those without any experience showed little difference with regard to television and/or the internet. According to a survey of participants' interest areas in agricultural biotechnology and their level of information acquisition, "Safety of human bodies" was rated the top interest area at 36.9%, which also had the highest level of information acquisition at 30.0%. In providing and sharing information in the future, this is a direct reference to the priorities and proportions of each field.

• Annual Conference of KIPS
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• 2024.05a
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• pp.183-186
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• 2024

IoT(Internet of Things) 기기가 다양한 산업 분야에 활용되면서, 보안과 유지 보수를 위한 관리의 중요성이 커지고 있다. 편리한 IoT 기기 관리를 위해 무선 네트워크를 통한 펌웨어 업데이트 기술인 FOTA(Firmware Over The Air)가 적용되어 있지만, 컴퓨팅 파워가 제한된 경량 IoT 기기 특성상 취약점 탐지를 수행하기 어렵다. 본 연구에서는 IoT 기기들이 퍼징 테스트 케이스를 분할하여 협력적으로 퍼징하고, 노드 간의 퍼징 결과가 다르면 재검증을 수행하는 협력적 퍼징 기법을 제안한다. 실험 결과에 따르면, 중복되는 테스트 케이스를 2 개나 3 개 퍼징하는 협력적 퍼징 기법은 종래 방식 대비 연산량을 최소 약 16%, 최대 약 48% 줄였다. 또한, 종래 퍼징 기법 대비 취약점 탐지 성공률(Success rate of vulnerability detection)을 최소 약 3 배, 최대 약 3.4 배 개선시켰다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1252-1268
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• 2003

There is a big change in Electronic Commerce. With little or no profit projected for the foreseeable future with the dotcom companies, Internet venture capitalists are looking for new business models. They are now turning to B to B Electronic Commerce. It is expected that B to B Electronic Commerce will be more active than B to C in the very near future. In the future B to B Electronic Commerce will move to include collaborative Electronic Commerce which includes product development, engineering, material procurement, and management. Even though the solution to this multidimensioal and complicated process may take some time, a total solution to this will dramatically change the landscape of Electronic Commerce. Thus the various corporations must work together to find the total solution that will build this infrastructure.