• Journal of Society of Preventive Korean Medicine
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• v.26 no.2
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• pp.25-35
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• 2022

Objectives : This study aims to analyze the patents filed in the clinical diagnosis sector where technologies have been actively developed since the advent of the 4th industrial revolution. Methods : The analysis has been conducted in two ways - the period from 2016 to 2021 and the time points before and after COVID-19 - by visualizing based on the word cloud method. Results : Over two thirds of patents has been filed in the A61B sector (71.8%) and cure, sensor, self diagnosis, control, and breakdown have been observed in the period above. During the overall period (2016~2021), 'ultrasound'(7.5%), 'image'(5.1%), 'skin'(4.0%), 'treatment'(3.4%), and 'artificial intelligence(2.5%)' were the frequently patent applications technologies. In addition, 'ultrasound'(6.2%), 'image'(5.5%), 'skin'(4.0%), 'treatment' (3.7%), and 'portable'(1.7%) appeared most frequently before COVID-19 whereas 'ultrasound(5.5%)', 'artificial intelligence(4.2%)', 'diagnostic device'(1.9%), 'dimentia'(1.6%), and 'diagnostic kit'(1.4%) emerged the most after COVID-19. Conclusion : This study is meaningful in that it showed the technological development trend in the digital diagnosis sector and it was found that the Korean medicine field should contribute to this field more actively in the future.

• Analyses & Alternatives
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• v.8 no.1
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• pp.59-85
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• 2024

This study examines the impact of the development of the artificial intelligence (AI) industry on the economic growth of South Korea. The study uses variables such as the revenue and patent applications of AI-related companies, as well as industry-specific total factor productivity and GDP, to estimate the effects. The results suggest that the growth of the AI industry has a positive effect on the economic growth with a lag of about one year. Specifically, the effect of government AI revenue on GDP growth appears to be greater than that of private companies or consumer-focused AI revenue. This indicates that government policies aimed at promoting the diffusion of the AI industry have had significant effects. The study notes that the period covered by the AI industry survey data is relatively short, and there is a lack of detailed data for the manufacturing sector. I suggest that further improvements and accumulation of data could lead to more robust results.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.113-122
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• 2018

In this paper, IoT(Internet of things) technology, which is the core of the 4th industrial revolution, was applied to the study of reduction of consumption current. The IoT is a sensor that collects data, a sensor communication, a gateway that processes and stores the collected data. Data application of IoT technology is applied to smart home, smart city, healthcare, smart factory, etc. and it needs to be applied to various industrial fields. By sensing the location of the sensor device, the specific functions of the gateway and the platform are turned ON and OFF to reduce the consumption current of the equipment during the OFF period. When the sensor device accesses the gateway, the specific function of the gateway is turned ON and When the device is separated from the gateway, it senses the sensitivity of the wireless signal and automatically turns off the certain functions. As a resurt, it has reduced the consumption of current. In this paper, we propose a novel system for detecting the location of sensor devices by applying IoT technology. The system implementation is realized by software based, and defines the requirements for the implementation of the sensor device gateway. The gateway automatically detects the location, movement of the device and performs necessary functions. Finally verifies the automatic detection performance of the gateway according to the location of the device. It will contribute greatly to the development of the smart city and office.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.29-35
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• 2019

The structure of the machinery industry due to the 4th industrial revolution is changing from precision and durability to intelligent and smart machinery through sensing and interconnection(IoT). There is a growing need for research on prognostics and health management(PHM) that can prevent abnormalities in processing machines and accurately predict and diagnose conditions. PHM is a technology that monitors the condition of a mechanical system, diagnoses signs of failure, and predicts the remaining life of the object. In this study, the vibration generated during machining is measured and a classification algorithm for normal and fault signals is developed. Arbitrary fault signal is collected by changing the conditions of un stable supply cutting oil and fixing jig. The signal processing is performed to apply the measured signal to the learning model. The sampling rate is changed for high speed operation and performed machine learning using raw signal without FFT. The fault classification algorithm for 1D convolution neural network composed of 2 convolution layers is developed.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.35-42
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• 2022

Purpose: The purpose of this study is to examine the characteristics and problems of existing research through various literature investigations on the existing R&D process. Implications are identified through the investigation of existing studies and the characteristics of the digital transformation era are analyzed. We research and propose a new R&D process suitable for the new era of digital transformation. Methods: The research method investigates various literature precedent studies on the existing R&D process and the methods used by companies. Research new R&D processes that reflect the characteristics of the digital transformation era and develop new related models. Results: In the era of digital transformation, the parallel R&D process is being reorganized to respond quickly to the demands of rapid market changes. In order to respond quickly to various customers, the R&D process can respond flexibly in a parallel structure. Conclusion: Along with the development of the R&D process, additional research on indicators and evaluation models that can evaluate them fairly and flexibly is needed. Further research is needed to determine whether the R&D process suitable for the digital transformation era is operating properly.

• Journal of the Korea Safety Management & Science
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• v.23 no.3
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• pp.47-55
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• 2021

Developed countries that have experienced decline in productivity due to the economic crisis in the past have come to recognize the smart factory as an important means to strengthen the competitiveness of the manufacturing industry due to the increase in labor costs, the avoidance of the manufacturing industry, and the resolution of the shortage of skilled manpower. The necessity of nurturing manpower for self-maintenance was felt through identifying factors for successful smart factory introduction by companies and providing smart factory education. Therefore, the effects of educational satisfaction and operational competency on self-efficacy as a parameter and self-efficacy as a parameter were analyzed using research models and hypotheses to determine whether there was an effect between job satisfaction as a dependent variable. As a result of the analysis, it was found that the mediating effect of self-efficacy and self-efficacy on job satisfaction was found to have significant effects on operational competency and self-efficacy as parameters, as well as educational satisfaction and operational competency. The implication of this study is that continuous education and innovation activities are important in order to increase the business performance of companies, and through this, the manufacturing competitiveness of SMEs can be improved.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.181-188
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• 2019

A production system is a management system that supports all activities to perform production operations at the manufacturing site. From the point-of-view of a smart factory, smart manufacturing systems redesigned the concept of onsite production systems to fit the entire system and its necessary functional composition. In this study, we select the key functions needed to build a smart factory for a PCB line and propose a new six-step model for the deployment of a smart manufacturing system by integrating essential functions. The smart manufacturing system newly classified the production and operation tasks of PCB manufacturing and selected necessary functions through requirement analysis and benchmarking of advanced companies. The selected production operation tasks are mapped to the functions of the system and configured into seven modules, and the optimal deployment model is presented to allow flexible responses to the characteristics of the tasks. These methodologies are first presented in this study, and the proposed model was applied to the PCB line to confirm that they had significant changes in the work method, qualitative effects, and quantitative effects. Typically, lead time and WIP have reduced by about 50%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.573-581
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• 2019

In the era of the 4th Industrial Revolution, the necessity of training advanced engineering personnel with convergent creativity to handle technologies such as artificial intelligence, big data, and the internet of things (IoT) is increasing. In this paper, a new approach of engineering education based on academia-industrial cooperation and design-centered teaching technique for the students who need to learn practicable engineering skill with convergent creativity for the fourth industrial age is presented. It analyzes the strengths and weaknesses of the existing engineering education innovation activities, presents the practical necessities based on the experience of the educational system and the requirements of the educational environment, and analyzes the existing activities and the new roles. In particular, we discuss how to combine student-centered teaching methodology for effective design education, which is a key element of innovative engineering education. Most of the presented methods are verified by the authors' needs and effects in the education field.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.8
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• pp.43-49
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• 2020

The growth of the AR/VR market due to the advent of the 4th Industrial Revolution begins with the development of the display industry. The development of OLED and flexible displays is further accelerated by the development of R2R technology. Micro-processing technology using a fast tool servo (FTS), the core technology in R2R processes, is making technological progress in increasingly diverse ways. This paper proposes a method to develop an FTS for horizontal driving and presents this method through experiments and analyses. To develop a swing-type FTS based on a seesaw motion, a rotational moment hinge structure was designed for each type, and research was conducted to determine an effective design method. A cantilever-based swing-type FTS was developed in two variations: one with single-side hinges and another with dual-side hinges. The parameters in the design of the swing-type FTS are rotational moment, natural frequency, and material selection. In conclusion, an FTS with a single-side hinge demonstrates the high performance required for micro processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4400-4419
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• 2021

In the 4th Industrial Revolution, the healthcare industry is undergoing a paradigm shift from post-care and management systems based on diagnosis and treatment to disease prevention and management based on personal precision medicine. To optimize medical services for individual patients, an open ecosystem for the healthcare industry that allows the exchange and utilization of personal health records (PHRs) is required. However, under the current system of hospital-centered data management, it is difficult to implement the linking and sharing of PHRs in practice. To address this problem, in this study, we present the design and implementation of a patient-centered PHR platform using blockchain technology. This platform achieved transparency and reliability in information management by eliminating the risk of leakage and tampering/altering personal information, which could occur when using a PHR. In addition, the patient-consent system was applied to a PHR; thus, the patient acted as the user with ownership. The proposed blockchain-based PHR platform enables the integration of personal medical information with scattered distribution across multiple hospitals, and allows patients to freely use their health records in their daily lives and emergencies. The proposed platform is expected to serve as a stepping stone for patient-centered healthcare data management and utilization.