• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.235-242
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• 2018

The interest about 4th Industrial Revolution was impressively increased from newspapers, iindustry, government and academic sectors. Especially AI what could be felt by the skin of many peoples, already overpassed the ability of the human's even in creative areas. Namely, now many people start fo feel that the effect of the revolution is just infront of themselves. There were several issues in this trend, the ability of deep learning by machine, the identity of the human, the change of job environment and the concern about the social change etc. Recently many studies have been made about the 4th industrial revolution in many fields like as AI(artificial intelligence), CRISPR, big data and driverless car etc. As many positive effects and pessimistic effects are existed at the same time and many preventing actions are being suggested recently, these opinions will be compared and analyzed and better solutions will be found eventually. Several educational, political, scientific, social and ethical effects and solutions were studied and suggested in this study. Clear implication from the study is that the world we will live from now on is changing faster than ever in the social, industrial, political and educational environment. If it will reform the social systems according to those changes, a society (nation or government) will grasp the chance of its development or take-off, otherwise, it will consume the resources ineffectively and lose the competition as a whole society. But the method of that reform is not that apparent in many aspects as the revolution is progressing currently and its definition should be made whether in industrial or scientific aspect. The person or nation who will define it will have the advantage of leading the future of that business or society.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.54-62
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• 2018

As a part of realization of artificial intelligence signal(AI Signal), this study proposed an actuated signal algorithm based on vehicle queue length that estimates in real time by deep learning. In order to implement the algorithm, we built an API(COM Interface) to control the micro traffic simulator Vissim in the tensorflow that implements the deep learning model. In Vissim, when the link travel time and the traffic volume collected by signal cycle are transferred to the tensorflow, the vehicle queue length is estimated by the deep learning model. The signal time is calculated based on the vehicle queue length, and the simulation is performed by adjusting the signaling inside Vissim. The algorithm developed in this study is analyzed that the vehicle delay is reduced by about 5% compared to the current TOD mode. It is applied to only one intersection in the network and its effect is limited. Future study is proposed to expand the space such as corridor control or network control using this algorithm.

• Journal of the HCI Society of Korea
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• v.13 no.2
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• pp.31-44
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• 2018

In the IoT environment, various things could be connected. Those connected things learn and operate themselves, by acquiring data. As human being, they have self-learning and self-operating systems. In the field of IoT study, therefore, the key issue is to design communication system connecting both of the two different types of subjects, human being(user) and the things. With the advent of the IoT environment, much research has been done in the field of UI design. It can be seen that research has been conducted to take complex factors into account through keywords such as multi-modality and interusability. However, the existing UI design method has limitations in structuring or testing interaction between things and users of IoT environment. Therefore, this paper suggests a new UI prototyping method. In this paper, the major analysis and studies are as follows: (1) defined what is the behavior process of the things (2) analyzed the existing IoT product (3) built a new framework driving personality types (4) extracted three representative personality models (5) applied the three models to the smart home service and tested UI prototyping. It is meaningful with that this study can confirm user experience (UX) about IoT service in a more comprehensive way. Moreover, the concept of the personality of things will be utilized as a tool for establishing the identity of artificial intelligence (AI) services in the future.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.51-58
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• 2018

The late 20th century saw the industrial period end only to transform into the digital era where people have begun to pay attention to craft because it a field that respects emotion as the essential value, an alternative to overcome the side effect that people have created. Today a new world - where the virtual and the real co-exist through artificial intelligence (AI) - has suddenly approached us and the future of craft is faced with a new situation as it needs to present a new creative solution as a tool that is necessary for human way of life - a tool that has been a necessity throughout history and the evolution of life. As a result for a continued development, craft attempts to establish a new paradigm through current trends represented by our modern society, which is the emergence of creative development through convergence. This study presents creative experiments attempted through the convergence of craft with other heterogeneous tendencies connected to the field. The objective of the study is to enable makers to acquire a more creative way of thinking at the same time as inspiring them and suggesting new creative possibilities in order to develop their work through creative convergence. In Chapter 2, the study investigates on the current status of craft in general, and compares it with what is taking place in Korea; in Chapter 3 the significance of convergence in craft and the process of creating is addressed through case studies. Lastly in Chapter 4, with the basis on analytical case studies, the attribute and the potential of convergence in the field of craft is observed. By analyzing different phenomena presented through attempts to converge in contemporary craft, it has been possible to view the future of the 21st century craft through assessments on what is active and what is as yet hidden potential.

• Journal of the Korean Society of Radiology
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• v.14 no.2
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• pp.121-127
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• 2020

The era of the Fourth Industrial Revolution is increasingly demanding mathematical competencies for virtual reality (VR), artificial intelligence (AI) and the like. In this context, this study intended to identify the basic mathematical competency levels of university freshman students in radiology department and to provide basic data thereon. For this, the diagnostic assessment of basic learning competencies for the domain of mathematics was conducted from June 17, 2019 to June 28, 2019 among 78 freshman students of radiology department at S university and D university. As a result, the university students' overall basic mathematical competency levels were diagnosed to be excellent. However, their levels in the sectors of the geometry and vector and the probability and statistics were diagnosed to be moderate, with the mean scores of 2.61 points and 2.64 points, respectively, which were found to be lower than those of the other sections. As for basic mathematical competency levels according to genders, the levels of male students and female students were diagnosed to be excellent, with the mean scores of 17.48 points and 16.29 points, respectively, showing no statistically significant difference (p>0.05). Given the small number of subjects and regional restriction, there might be some limitations in the generalization of the findings of the present study to all university freshman students and all departments. The above results suggest that it is necessary to implement various programs such as student level-based special lectures for enhancing basic mathematical competencies relating to major in order to improve the basic mathematical competencies of freshman students in radiology department, and that it is necessary to increase the students' mathematical competencies by offering major math courses in the curriculum and applying teaching-learning methods matching students' levels.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.789-795
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• 2020

Many deaths have been reported due to the worldwide pandemic of COVID-19. In order to prevent the further spread of COVID-19, it is necessary to quickly and accurately read images of suspected patients and take appropriate measures. To this end, this paper introduces a deep learning-based COVID-19 chest X-ray reading technique that can assist in image reading by providing medical staff whether a patient is infected. First of all, in order to learn the reading model, a sufficient dataset must be secured, but the currently provided COVID-19 open dataset does not have enough image data to ensure the accuracy of learning. Therefore, we solved the image data number imbalance problem that degrades AI learning performance by using a Stacked Generative Adversarial Network(StackGAN++). Next, the DenseNet-based classification model was trained using the augmented data set to develop the reading model. This classification model is a model for binary classification of normal chest X-ray and COVID-19 chest X-ray, and the performance of the model was evaluated using part of the actual image data as test data. Finally, the reliability of the model was secured by presenting the basis for judging the presence or absence of disease in the input image using Grad-CAM, one of the explainable artificial intelligence called XAI.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.53-59
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• 2021

In this paper, we propose a BERGPT-chatbot, a domestic AI chatbot that can alleviate negative emotions based on text input such as 'Replika'. We made BERGPT-chatbot into a chatbot capable of mitigating negative emotions by pipelined two models, KR-BERT and KoGPT2-chatbot. We applied a creative method of giving emotions to unrefined everyday datasets through KR-BERT, and learning additional datasets through KoGPT2-chatbot. The development background of BERGPT-chatbot is as follows. Currently, the number of people with depression is increasing all over the world. This phenomenon is emerging as a more serious problem due to COVID-19, which causes people to increase long-term indoor living or limit interpersonal relationships. Overseas artificial intelligence chatbots aimed at relieving negative emotions or taking care of mental health care, have increased in use due to the pandemic. In Korea, Psychological diagnosis chatbots similar to those of overseas cases are being operated. However, as the domestic chatbot is a system that outputs a button-based answer rather than a text input-based answer, when compared to overseas chatbots, domestic chatbots remain at a low level of diagnosing human psychology. Therefore, we proposed a chatbot that helps mitigating negative emotions through BERGPT-chatbot. Finally, we compared BERGPT-chatbot and KoGPT2-chatbot through 'Perplexity', an internal evaluation metric for evaluating language models, and showed the superity of BERGPT-chatbot.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.109-126
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• 2018

With massive and dense production, the livestock industry is rapidly moving into a large-scale, capital-intensive industry especially in swine, poultry, and ducks. However, livestock epidemics can pose a serious threat to the livestock industry and the lives of the people. The government has established and operates the National Animal Protection and Prevention System (KAHIS) since 2013 in order to control the threat, in accordance with the five stages. The digitalized data and information are excellent in ease of management, but it is also pointed out that it is difficult to take countermeasures through linkage with the data in an emergency situation. Recently, the technology of the fourth industrial revolution such as Internet of Things (IoT), Big Data, Artificial intelligence (AI) has been rapidly implemented to the livestock industry, which makes smart livestock disease control system possible. Therefore, this study investigated the domestic and overseas cases which apply 4th Industrial Revolution technology in the industry, and derived 13 possible candidate tasks in the near future. In order to ascertain the priority of policy formulation, we surveyed the expert groups and examined the priority of each of the five stages of the prevention and the priority of each stage. The results of this study are expected to contribute to the establishment of policies for the advancement of smart livestock disease control research and livestock protection.

• Informatization Policy
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• v.26 no.3
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• pp.69-89
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• 2019

In order to implement smart cities that will become living spaces in the fourth industrial revolution era, detailed privacy information such as residents' living information, buildings and facilities information must be collected and processed in real time. While city functions and convenience for individuals are being facilitated, threats to personal information exposure and leakage are also likely to increase at the same time. Therefore, the design concept for personal information protection should be considered and accordingly reflected from the stages of smart city design, technology development and operation planning of intelligent information (AI) facilities. The results of the analysis show that for activation of smart cities and operation of data-driven cities, the concept of Privacy by Design (PbD) has already been introduced in the institutional, industrial and technological aspects, particularly in the cases of European countries and the US. In order to strengthen the local and global competitiveness of smart cities and the country, Korea also needs to actively deploy PbD as a strategy to secure a data-driven economy, which is the core strategy for smart cities. Therefore, the study suggests policy implications focused on approaches to legislative improvement and technology development support, which reflect the basic properties of PbD as defined in the study.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.9-21
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• 2021

The study aims to identify convergence and trends in technology-based patent data for the biohealth sector in IP5 countries (KR, EP, JP, US, CN) and present the direction of development in that industry. We used patent co-classification analysis-based network analysis and TF-IDF-based text mining as the principal methodology to understand the current state of technology convergence. As a result, the technology convergence cluster in the biohealth industry was derived in three forms: (A) Medical device for treatment, (B) Medical data processing, and (C) Medical device for biometrics. Besides, as a result of trend analysis based on technology convergence results, it is analyzed that Korea is likely to dominate the market with patents with high commercial value in the future as it is derived as a market leader in (B) medical data processing. In particular, the field is expected to require technology convergence activation policies and R&D support strategies for the technology as the possibility of medical data utilization by domestic bio-health companies expands, along with the policy conversion of the "Data 3 Act" passed by the National Assembly in January 2019.