• Convergence Security Journal
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• v.20 no.4
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• pp.61-70
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• 2020

The unmanned aerial vehicle that emerged with the 4th Industrial Revolution attracts attention not only from Korea but also from around the world, and its utilization and market size are gradually expanding. For the first time, it was used for military purposes, but it is currently used for transportation, investigation, surveillance, and agriculture. China, along with the US and Europe, is emerging as a leader in the commercial unmanned aerial vehicle market, and Korea, which has the world's seventh-largest technology in related fields, is striving to promote various technology development policies and system improvement related to unmanned aerial vehicles. Military drones will revolutionize the means of war by using a means of war called an unmanned system based on theories such as network-oriented warfare and effect-oriented warfare. Mobile equipment, including drones, is greatly affected by environmental factors such as terrain and weather, as well as technological developments and interests in the field. Now, drones are being used actively in many fields, and especially in the military field, the use of advanced drones is expected to create a new defense environment and provide a new paradigm for war.

• Journal of Korea Trade
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• v.26 no.2
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• pp.84-99
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• 2022

Purpose - This study carried out an empirical study of the impact of sustainability - which has been gaining attention as challenges are arising in supply chains based on existing trade networks due to the impact of the COVID-19 pandemic - on SCM performance and financial performance of Korean SMEs. The study seeks to propose a measurement model to enhance the SCM performance and financial performance of Korean SMEs and to identify the relationship between sustainability, SCM performance and financial performance to suggest implications to SMEs, governments, and relevant organizations. Design/methodology - Our Analysis established hypotheses that economic sustainability, environmental sustainability, and other factors related to sustainability have a positive impact on SCM performance and financial performance as well as SCM performance has a positive impact on financial performance, making empirical validations by utilizing Structural Equation Modeling based on data collected through survey from Korean SMEs. Findings - According to an empirical study, although environmental sustainability and economic sustainability among factors of sustainability had a positive influence on SCM performance, social sustainability did not have a statistically significant influence. Furthermore, it was learned that only economic sustainability had a positive influence on financial performance while SCM performance has a positive influence on financial performance. Originality/value - This empirical study explored the relationship between SCM performance and financial performance of Korean SMEs with a high tendency to depend on specific supply chains when the international trade network is in confusion and/or the global supply chain has collapsed. If Korean SMEs allocate management resources to the factors deducted from this study, they would be able to build more efficient supply chains and improve financial performance to improve sustainability.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.529-536
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• 2022

In the past two years, Severe Acute Respiratory Syndrome Coronavirus-2(SARS-CoV-2) has been hitting more and more to people. This paper proposes a novel U-Net Convolutional Neural Network to classify and segment COVID-19 lung CT images, which contains Sub Coding Block (SCB), Atrous Spatial Pyramid Pooling(ASPP) and Attention Gate(AG). Three different models such as FCN, U-Net and U-Net-SCB are designed to compare the proposed model and the best optimizer and atrous rate are chosen for the proposed model. The simulation results show that the proposed U-Net-MMFE has the best Dice segmentation coefficient of 94.79% for the COVID-19 CT scan digital image dataset compared with other segmentation models when atrous rate is 12 and the optimizer is Adam.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.187-194
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• 2022

LNG is known as the transitional energy source for the future eco-friendly, attracting enormous market attention due to global eco-friendly regulations, Covid-19 Pandemic, Russia-Ukraine War. In addition, since new LNG suppliers such as the U.S. and Australia are also diversifying, the LNG spot market is expected to grow. On the other hand, research on the LNG transportation market has been marginalized. Therefore, this study attempted to predict short-term LNG 160K spot rates and compared the prediction performance between artificial neural networks and the ARIMA model. As a result of this paper, while it was difficult to determine the superiority and superiority of ARIMA and artificial neural networks, considering the relative free of ANN's contraints, we confirmed the feasibility of ANN in LNG 160K spot rate prediction. This study has academic significance as the first attempt to apply an artificial neural network to forecasting LNG 160K spot rates and are expected to contribute significantly in practice in that they can improve the quality of short-term investment decisions by market participants by increasing the accuracy of short-term prediction.

• Journal of Periodontal and Implant Science
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• v.52 no.3
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• pp.183-193
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• 2022

Purpose: We retrospectively analysed patients' dental and periodontal status according to the presence of non-communicable diseases (NCDs) and the effects of NCDs on periodontal treatment outcomes. Factors influencing disease recurrence were investigated using decision tree analysis. Methods: We analysed the records of patients who visited the Department of Periodontology, Pusan National University Dental Hospital from June 2014 to October 2019. As baseline subjects, 1,362 patients with periodontitis and who underwent full-mouth periodontal examinations before periodontal treatment were selected. Among them, 321 patients who underwent periodontal examinations after the completion of periodontal treatment and 143 who continued to participate in regular maintenance were followed-up. Results: Forty-three percent of patients had a NCD. Patients without NCDs had more residual teeth and lower sum of the number of total decayed, missing, filled teeths (DMFT) scores. There was no difference in periodontal status according to NCD status. Patients with a NCD showed significant changes in the plaque index after periodontal treatment. The decision tree model analysis demonstrated that osteoporosis affected the recurrence of periodontitis. Conclusions: The number of residual teeth and DMFT index differed according to the presence of NCDs. Patients with osteoporosis require particular attention to prevent periodontitis recurrence.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.476-487
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• 2022

International research cooperation is emerging as one of the strategies for improving research performance. Therefore, in this study, through the analysis of research reports on the theme of international research cooperation, the subject and issues of international research cooperation were identified and the characteristics of these studies were confirmed. To this end, related report data were constructed, statistical data analysis and big data analysis of the data were performed. Considering the current international research cooperation network, it is necessary to conduct international research cooperation centered on developing countries while paying attention to the increase in China's proportion of international research cooperation. Second, it is necessary to emphasize the importance of international research cooperation in various countries, including developing countries, in that the interdependence of research between countries increases and the citation index of actual joint research is higher. Third, it can be seen that the subject field in which international research cooperation can be activated may vary depending on the type of support project. Therefore, it suggests that in order for international research cooperation on more diverse topics to be carried out, projects supporting them must also be diversified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3991-4010
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• 2021

The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.365-372
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• 2022

South Korea is entering an aging society, and since the musculoskeletal system directly affects elders' daily life, muscle exercise and flexibility are required. In particular, yoga relaxes the mind and the body and heightens stress coping ability. To investigate keywords about yoga, news articles provided by BIGKinds, a news analysis system, was applied to collect articles from January 1, 2019, to December 31, 2021, and an analysis was conducted about the monthly keywords and the relationship followed by the weighted degree. Based on the research findings, first, it showed that there is high interest in yoga during the spring and autumn seasons. Second, yoga is offered in non-contact methods nowadays, and various social network services are applied for the operation. Third, there was high public attention to articles on yoga instructors and trainers, and this revealed the importance and interest in online coaching. It is anticipated to apply it for the development of yoga workout programs and base data to develop sports for all.

• The Journal of Information Systems
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• v.31 no.4
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• pp.75-100
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• 2022

Purpose Recently, hyper-realistic virtual influencers have received much attention in the field of corporate marketing. However, there is a lack of research that suggests specific processes affecting behavioral intentions through trust and attachment between virtual influencers and consumers. In addition, previous studies have failed to consider the characteristics of hyper-realistic virtual influencers. Therefore, this study investigates the effects of trust and attachment to hyper-realistic virtual influencers on consumers' behavioral intentions based on the trust-building model. Design/methodology/approach Based on the previous research, seven antecedent factors for trust-building were derived: Reality, Attractiveness, Awareness, Interactivity, Professionalism, Social Presence, and Predictability. Next, the survey was conducted on Chinese people who had experienced interacting with hyper-realistic virtual influencers on social network services within the last 3 months at the time of data collection. A total of 326 respondents were used for the final analysis and hypotheses were tested using a structural equation model technique. Findings The results of this study are as follows. First, this study confirmed that reality, attractiveness, awareness, social presence, and predictability as antecedent factors for trust-building of hyper-realistic virtual influencers have a positive effect on trust. Second, this study confirmed that trust in hyper-realistic virtual influencers has a significant positive effect on attachment. Lastly, this study confirmed that trust and attachment to the hyper-realistic virtual influencer significantly and positively affect relationship retention and purchase intentions.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1039-1046
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• 2022

After the COVID-19 pandemic, the spread of the untact culture and the Fourth Industrial Revolution, which generates various types of data, generated so much data that it was not compared to before. This led to higher data throughput, revealing little by little the limitations of the existing network system centered on vendors and hardware. Recently, SDN technology centered on users and software that can overcome these limitations is attracting attention. In addition, SDN-based load balancing techniques are expected to increase efficiency in the load balancing area of the server cluster in the data center, which generates and processes vast and diverse data. Unlike existing SDN load distribution studies, this paper proposes a load distribution technique in which a controller checks the state of a server according to the occurrence of an event rather than periodic confirmation through a monitoring technique and allocates a user's request by weighting it according to a load ratio. As a result of the desired experiment, the proposed technique showed a better equal load balancing effect than the comparison technique, so it is expected to be more effective in a server cluster in a large and packet-flowing data center.