• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.10-16
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• 2021

As the implementation of smart factories spreads widely, the need for research to improve data efficiency is raised by prioritizing massive amounts of big data using IoT devices in terms of relevance and quality. The purpose of this study is to investigate whether prioritizing big data in management accounting decisions such as cost volatility estimation and recipe optimization can improve smart solution performance and decision-making effectiveness. Based on the survey answers of 84 decision makers at domestic small and medium-sized manufacturers who operate smart solutions such as ERP and MES that link manufacturing data in real time, empirical research was conducted. As a result, it was analyzed that setting prioritization of big data has a positive effect on decision-making in management accounting. became In addition, it was found that big data prioritization has a mediating effect that indirectly affects smart solution performance by using big data in management accounting decision making. Through the research results, it will be possible to contribute as a prior research to develop a scale to evaluate the correlation between big data in the process of business decision making.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.9-16
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• 2021

In this paper, we propose a building exploration drone that can be used for a digital twin-based building control system. The existing building control system using a fixed position sensor box has a problem that a management blind spot occurs. And because people patrol themselves, it takes a lot of human resources. In this paper, a drone equipped with a temperature and humidity sensor and a gas leak detection sensor is used to search the internal path of the building centering on the control blind spot. It also aims to solve the problem of the building control system by transmitting information in real time along with the video. In addition, it has a stable hovering function using an optical floor sensor and can be applied to an existing digital twin-based building control system. The results of this study are believed to be of great help in improving the quality of digital twin control systems using drones.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.285-292
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• 2019

With the popularization of PC, SNS and IoT, a lot of data is generated and the amount is increasing exponentially. Artificial neural network learning is a topic that attracts attention in many fields in recent years by using huge amounts of data. Artificial neural network learning has shown tremendous potential in speech recognition and image recognition, and is widely applied to a variety of complex areas such as medical diagnosis, artificial intelligence games, and face recognition. The results of artificial neural networks are accurate enough to surpass real human beings. Despite these many advantages, privacy problems still exist in artificial neural network learning. Learning data for artificial neural network learning includes various information including personal sensitive information, so that privacy can be exposed due to malicious attackers. There is a privacy risk that occurs when an attacker interferes with learning and degrades learning or attacks a model that has completed learning. In this paper, we analyze the attack method of the recently proposed neural network model and its privacy protection method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.99-105
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• 2018

This paper proposes multiple access method for smart doorlock system using VLC(Visible Light Communication) with color grid modulation method. The proposed method is to connect multiple visible light signals using color grid modulation method in order to recognize and authenticate multiple users accessing doorlock. In order to enable visible light multiple access with existing infrastructure, the symbol energy interval of signal should be maximized. Thus, performance of system in VLC channel is measured by modulating symbols based on the proposed method. We confirm the actual channel test results of the modulated signal to implement doorlock system that recognizes the number of multiple access users.

• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.105-113
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• 2019

Convergence education, which is operated by many engineering colleges, is mainly led by government-led projects. Convergence majors are established in consideration of the research field of the university professors rather than systematically analyzing the needs of the industry. The purpose of this study is to present the directions of convergence technology education related to new industry fields by analyzing industry needs. Participants were 299 industrial workers in various fields. Instrument consisted of three parts: necessity for convergence education, demand for convergence new technology education from industry perspective, and opinions about undergraduate convergence education. As a result, it was found that the level of awareness of industry needs for fusion technology education was high, and it was confirmed that there is a high demand for IoT convergence, bio-health, advanced new material, and renewable energy fields among convergence technology fields. In addition, the results of the industry demand for convergence new technology education were presented. The suggestions for expectations, problems, and improvements in undergraduate education were presented and implications for convergence technology education were discussed based on the results of the study.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.99-110
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• 2019

As the 4th industrial revolution progressing, manufacturers are trying to apply intelligent information technologies such as IoT(internet of things) and machine learning. In the semiconductor/LCD/tire manufacturing process, schedule plan that minimizes setup change and due date violation is very important in order to ensure efficient production. Therefore, in this paper, we suggest the deep learning based scheduling generation model minimizes setup change and due date violation in parallel machines. The proposed model learns patterns of minimizing setup change and due date violation depending on considered order using the amount of historical data. Therefore, the experiment results using three dataset depending on levels of the order list, the proposed model outperforms compared to priority rules.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.37-42
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• 2019

In this paper, we propose a syndrome decoding scheme that can correct two errors for single error correcting Hamming codes within a code length. The decoding scheme proposed in this paper has the advantage of significantly improving the error rate performance compared to the decoder complexity by correcting multiple errors without substantially increasing the decoding complexity. It is suitable for applications in which the energy use of encoder/decoder is extremely limited and the low error rate performance is required, such as IoT communications and molecular communications. In order to verify the improvement of the error rate performance of the Hamming code with the proposed decoding scheme, we performed simulation on Hamming codes with short code length in the AWGN and BPSK modulation environments. As a result, compared with the conventional decoding method, the proposed decoding scheme showed performance improvement of about 1.1 ~ 1.2[dB] regardless of the code length of the Hamming code.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.139-146
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• 2019

The Fourth Industrial Revolution is the super-connected-based intelligent revolution, which is triggered by intelligence information technology such as AI and IoT. Radical changes in industrial structure being expected, major developed countries are counteracting it by preparing strategies to enhance industrial competitiveness for taking the lead in the Fourth Industrial Revolution. Korea's national preparations, however, are considered to be insufficient, as it ranks only $25^{th}$ in the world. In compliance with the issue, preparing relevant policies and strategies such as establishment of the Fourth Industrial Revolution Committee, government diagnoses the pending issue of information and communication industry and arranges countermeasures so that it intends to gain competitiveness in the industry and lays a foundation for leading the market.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.423-425
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• 2019

Users may experience a sub-type of motion sickness, called cybersickness, when interacting with virtual reality (VR) applications in the state of wearing head mounted display (HMD) devices. Although the root cause of cybersickness is still unclear, it is believed to result from a sensory mismatch between visual and vestibular systems. However, there is a lack of studies developing data collection and analysis systems to measure cybersickness. In this paper, therefore, a system is designed that collects electroencephalography (EEG) and physiological data from a user wearing a VR HMD device through an internet of things (IoT) platform and decides whether a user experiences a symptom of cybersickness, namely dizziness, or not by using a decision threshold. Experimental results showed that the proposed system achieved about 92% accuracy of a dizziness detection when considering 14 participants.

• Journal of the Society of Disaster Information
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• v.15 no.1
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• pp.153-164
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• 2019

Purpose: This paper aims to derive improvement measures, in terms of legal and technical aspects, which can reduce effectively the casualties caused by drowing accidents. Method: Firstly, we checked the status of drowing accident management and carried out the interview of field private safety guards. field private safety guards. In addition, surveys were conducted on safety personnel and managers. Based on survey results, we are lastly analyzed the specific problems and reviews the improvement measures from technical and legal aspects. Result: As an analytical result, it was considered that supplementary supporting tools such as CCTV, monitoring devices using IoT and artificial intelligence technologies were necessary to prevent drowning accident, and qualification with limited authority should be added to the private safety guard because of the lack of regulation. Conclusion: In order to manage water safety effectively, a comprehensive water safety management system should be established that integrates people and equipment through systemic education of security personnel, authorization of enforcement, and introduction of surveillance equipment.