• Convergence Security Journal
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• v.17 no.2
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• pp.153-158
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• 2017

The robot imitates humans and recognizes the external environment and judges the situation. The robot is a machine that operates autonomously. Robots are divided into manufacturing robots and service robots. Service robots are classified as professional service robots and personal service robots. Because of the intensified competition of productivity in manufacturing industries, rising safety issues, low birth rate and aging, the robots industry is emerging. Recently, the robot industry is a complex of advanced technology fields, and it is attracting attention as a new industry where innovation potential and growth potential are promising. IT, BT, and NT related elements are fused and implemented, and the ripple effect is very large. Due to changes in social structure and life patterns, social interest in life extension and health is increasing. There is much interest in the medical field. Now the artificial intelligence (AI) industry is growing rapidly. It is necessary to secure global competitiveness through strengthening cooperation between large and small companies. We must combine R&D investment capability and marketing capability, which are advantages of large corporations, and robotic technology. We need to establish a cooperative model and secure global competitiveness through M&A.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1176-1182
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• 2021

Recently, with the development of artificial intelligence and IoT technology, automation, and unmanned work are progressing in various fields, and the importance of image processing, which is the basis of AI object recognition, is increasing. In particular, in systems that require detailed data processing, noise removal is used as a preprocessing step, but the existing algorithm does not consider the noise level of the image, so it has the disadvantage of blurring in the filtering process. Therefore, in this paper, we propose a modified Gaussian filter that determines the weight by determining the noise level of the image. The proposed algorithm obtains the noise estimate for the AWGN of the image using quadtree segmentation, determines the Gaussian weight and the pixel weight, and obtains the final output by convolution with the local mask. To evaluate the proposed algorithm, it was simulated compared to the existing method, and superior performance was confirmed compared to the existing method.

• The Journal of Korean Association of Computer Education
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• v.22 no.4
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• pp.35-45
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• 2019

How future generations perceive coexistence with intelligent robots is an important element of how SW and artificial intelligence education should be designed and conducted. This study conducted a survey of 214 first graders in middle school and looked at differences in understanding and perception of coexistence through empathy and expected problem situations depending on the type of intelligent robot. As a result of the analysis, Firstly, if the form was not explicit, it was recognized as a top-down relationship, and Second, in the case of human form, it was ready to recognize intelligent robots and communicate with them. Third, Many people were feeling Emotion in the Robot shape AI. Fourth, there was a vague sense of uneasiness about simple mechanical robots. The study is meaningful as a case study to confirm awareness of intelligent robots and needs to consider and establish awareness of whether they can coexist and live together with robots by age group as well as middle school students.

• Convergence Security Journal
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• v.19 no.1
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• pp.121-126
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• 2019

The big data utilization category in the sports field was mainly focused on the big data analysis to improve the competence of the athlete and the performance. Since then, 'big data technology' which collect and analyze more detailed and diverse data through the application of ICT technology such as IoT and AI has been applied. The use of big data of sports contents in future has value and possibility in the smart environment, but it is necessary to overcome the shortage and limitation of platform to manage and share sports contents. In order to solve such problems, it is important to change the perception of the companies or providers that provide sports contents and cultivate and secure professional personnel capable of providing sports contents. Also, it is necessary to implement policies to systematically manage and utilize big data poured from sports contents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.249-254
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• 2019

The concept of 'Edu-Tech', which is rapidly reorganized around e-Learning, has been spreading along with the development of intelligent information technology according to the fourth industrial revolution such as Artificial Intelligence (AI), Internet of Things (IoT), BigData. Currently, leading companies are conducting online education services, but real-time two-way communication is difficult. In addition, in the case of off-line class, there are many students, and not only the time is limited, but also they often miss the opportunities to ask questions. In order to solve these problems, this paper develops a real - time interactive question and answer management system that can freely questions both on - line and off - line by combining the benefits of offline instant answers and the advantages of online openness. The developed system is a real-time personalized education system that enables the respondent to check the situation of the questioner in real time and provide a customized answer according to the inquirer's request. In addition, by measuring and managing the system usage time in seconds, the questioner and the respondent can efficiently utilize the system.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.175-185
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• 2021

Purpose: Vital sign are used to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery. Researchers are using vital sign data and AI(artificial intelligence) to manage a variety of diseases and predict mortality. In order to analyze vital sign data using AI, it is important to select and extract vital sign data suitable for research purposes. Methods: We developed a method to visualize vital sign and early warning scores by processing retrospective vital sign data collected from EMR(electronic medical records) and patient monitoring devices. The vital sign data used for development were obtained using the open EMR big data MIMIC-III and the wearable patient monitoring device(CareTaker). Data processing and visualization were developed using Python. We used the development results with machine learning to process the prediction of mortality in ICU patients. Results: We calculated NEWS(National Early Warning Score) to understand the patient's condition. Vital sign data with different measurement times and frequencies were sampled at equal time intervals, and missing data were interpolated to reconstruct data. The normal and abnormal states of vital sign were visualized as color-coded graphs. Mortality prediction result with processed data and machine learning was AUC of 0.892. Conclusion: This visualization method will help researchers to easily understand a patient's vital sign status over time and extract the necessary data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1117-1123
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• 2021

Object recognition is to identify the location and class of a specific object by analyzing the given image when a specific image is input. One of the fields in which object recognition technology is actively applied in recent years is autonomous vehicles, and this paper describes the trend of image-based object recognition artificial intelligence technology in autonomous vehicles. The image-based object detection algorithm has recently been narrowed down to two methods (a single-step detection method and a two-step detection method), and we will analyze and organize them around this. The advantages and disadvantages of the two detection methods are analyzed and presented, and the YOLO/SSD algorithm belonging to the single-step detection method and the R-CNN/Faster R-CNN algorithm belonging to the two-step detection method are analyzed and described. This will allow the algorithms suitable for each object recognition application required for autonomous driving to be selectively selected and R&D.

• Explosives and Blasting
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• v.40 no.1
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• pp.1-16
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• 2022

In order to develop effective and safe blasting techniques or to introduce foreign advanced blasting techniques to domestic industry, the analysis of research trend in blasting field in the world is essential. In generally, such a research trend analysis was carried out for limited number of published papers. In this study, a bibliometric analysis was performed using VOSviewer for the overall papers published in international journals to figure out the variation of research trend in blasting area. From the keyword analysis, it was found that the number of published papers and the number of overall keywords was limited in the 2000s. Since 2010, the number of published papers was increased rapidly and the keywords were diversified with the introduction of artificial intelligence(AI). The keyword analysis for 2017~2021 showed that various hybrid AI techniques were actively applied in the evaluation of blasting effect.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.2_2
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• pp.247-255
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• 2022

Robot Process Automation (RPA) is a computer technology called Robotic Process Automation, a form of business process automation based on the concept of software robots or artificial intelligence (AI) walkers. In general, in traditional workflow automation tools, software developers design software that creates a set of actions to automate tasks and interfaces for the back-end systems using internal APIs or dedicated script languages. However, in RPA software, automation can be implemented by configuring an operating processor as if the general user is directly performing the task of the application. In other words, it can be said that it is a suitable development method for automating simply repetitive tasks rather than developing specific programs in which all necessary functions are implemented, as in general software development. Thus, this is more appropriate for configuring and automating RPA software in traditional manufacturing companies that are not easy to develop and apply smart factories or high-end AI software. Therefore, this research aims to analyze the requirements required at the actual manufacturing companies, focusing on the manufacturer's case in Changwon, Gyeongsangnam-do, called SinceWin Co., Ltd., and to examine the possibility of RPA software in the manufacturing companies by implementing actual RPA software that supports office automation. Through the research, it was confirmed that the actually implemented RPA software met the requirements of the company and helped manufacturer practice significantly by automating the parts that were worked error-prone and manually periodically.

• Smart Media Journal
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• v.11 no.4
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• pp.9-18
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• 2022

Recently, research and system using AI is rapidly increasing in various fields. Smart farm using artificial intelligence and information communication technology is also being studied in agriculture. In addition, data-based precision agriculture is being commercialized by convergence various advanced technology such as autonomous driving, satellites, and big data. In Korea, the number of commercialization cases of facility agriculture among smart agriculture is increasing. However, research and investment are being biased in the field of facility agriculture. The gap between research and investment in facility agriculture and open-air agriculture continues to increase. The fields of fruit trees and plant factories have low research and investment. There is a problem that the big data collection and utilization system is insufficient. In this paper, we are proposed the system for determining the fruit tree growth stage using a deep learning-based object detection model. The system was proposed as a hybrid app for use in agricultural sites. In addition, we are implemented an object detection function for the fruit tree growth stage determine.