• Applied Chemistry for Engineering
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• v.32 no.3
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• pp.320-325
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• 2021

In this study, an optimization for the production of water emulsion was designed by adding an extract of wheat sprout, which is known to contain a large amount of antioxidants. The central composite design of reaction surface analysis method (CCD-RSM) was used for the optimization process. The amount of emulsifier, emulsification time, and added amount of wheat sprout extract were selected as independent variables based on our preliminary experiments. The mean droplet size (MDS), viscosity, and emulsion stability index (ESI) were set as the responses to evaluate the stability of the emulsion. For each independent variable, the P-value and coefficient of determination were evaluated to verify the reliability of the experiments. From the result of CCD-RSM, optimum conditions for the emulsification were determined as 23.6 min, 7.7 wt.%, and 3.9 wt.% for the emulsification time, amount of emulsifier, and amount of sprout, respectively. From the optimized condition obtained, MDS, viscosity, and ESI after 7 days from reaction were estimated as 252.3 nm, 616.7 cP, and 88.7%, respectively. The overall satisfaction was 0.9137, which supported the validity of the experiments, and the error rate was measured at 0.5% or less by advancing the experiments. Therefore, an optimized process for producing an emulsion by adding the malt extract was designed by the CCD-RSM.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.1-11
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• 2021

The Neis System is a system integrating administrative information that was operated in elementary and secondary schools in Korea. Currently, this system is operated by a central server method and contains school administration information and important educational information of students. Among student information, the student life record contains important information for a student to advance to a higher level institution, but problems such as information leakage or manipulation may occur due to malicious attacks. In this paper, we propose a hybrid blockchain system that combines the server and blockchain technology managed by the existing Neis system. The proposed system records the query information of the database in a block when student information is accessed. When a request for correction of student information or issuance of a certificate is received, the query of the blockchain, the information in the database, and the student's key value are checked to determine whether the information has been leaked or manipulated, and only if the data is normal, the request for revision of the record is performed. This process is more secure than the existing central server because it checks the manipulation of data through the blockchain. The proposed system was implemented on the Ethereum platform, and the query information of the blockchain was experimentally verified using smart contracts. This study contributes to enhancing the reliability of the Nice system by strengthening the security against forgery and alteration of student data by combining the existing Nice system with a block chain.

• The Journal of Bigdata
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• v.5 no.2
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• pp.241-255
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• 2020

In Korea, utilizing and protecting the ocean from the sea on three sides can be considered the basis of national power. Recently, it has been distributed to IOT and 5G networks, and attempts to provide various information based on telecommunication infrastructure are continuing in the public and private sectors. In this study, an online survey was conducted with the aim of improving the services of marine information services (KOMC, safe and open seas) provided by the Government Agency for Oceanographic Research. Through an online survey, the survey was conducted on sites that are mainly used to survey people's need for marine information and to collect information. In addition, the survey was conducted on the UX, UI problems and improvements of KOMC, open and safe sea sites provided by the National Oceanographic Research Institute. The awareness and experience of marine information service by the Korea Oceanographic Research Institute were confirmed. Later, the previous steps of FGI also examined the usability of various users after allowing them to use the actual service. Here, the experience of collecting marine information from actual users was investigated, not just by looking at and evaluating the design of the service website and application. As a result, users presented a variety of opinions related to marine information services, including accessibility, reliability of information, providing media, and importance of information provided. The findings could be used as data to identify ocean-related data and ways to provide information required by users of various age groups and occupational groups.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.206-216
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• 2020

As the number of aging railway bridges in Korea increases, maintenance costs due to aging are increasing and continuous management is becoming more important. However, while the number of old facilities to be managed increases, there is a shortage of professional personnel capable of inspecting and diagnosing these old facilities. To solve these problems, this study presents an improved model that can detect Local damage to structures using machine learning techniques of AI technology. To construct a damage detection machine learning model, an analysis model of the bridge was set by referring to the design drawing of a non-ballasted plate-girder railroad bridge. Static strain data according to the damage scenario was extracted with the analysis model, and the Local damage index based on the reliability of the bridge was presented using statistical techniques. Damage was performed in a three-step process of identifying the damage existence, the damage location, and the damage severity. In the estimation of the damage severity, a linear regression model was additionally considered to detect random damage. Finally, the random damage location was estimated and verified using a machine learning-based damage detection classification learning model and a regression model.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.9-18
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• 2021

This study was aimed to investigate the effects of hair dyeing and changes of hair quality by the application of indigo dye. Methods: Indigo dye was used after water bath. After application of the dye to healthy and bleached hair samples, they were treated with heat and remained naturally by different times. Each sample was measured before and after the application and compared for the analysis. To investigate the effects of dyeing, L⁎, a⁎, and b⁎ values and bleaching degree were measured using by color-difference meter. To understand the changes of hair quality, absorbance and gloss were measured using by tensile strength and methylene blue. Results: Upon the results of dyeing, all the samples showed the significant dyeing effects before and after the application in terms of L⁎, a⁎, and b⁎ values. With respect to the bleaching effects, it showed the greatest change on Day 1 and did not show any changes from Day 3. For the measurement of tensile strength, mean values of all the samples were increased. However, the results were not significant, statistically, demonstrating no change of hair quality. No statistically significant results were found in the samples except healthy 7L(3) sample upon the absorbance results using methylene blue. Gloss of samples was changed upon the statistical analysis results. Conclusion: Indigo dye showed the hair dyeing effects, significantly, while gloss was changed and tensile strength and absorbance were not changed in terms of hair quality. Further studies are required on the processing with a variety of dyes and on the measurements for reliability and objectivity.

• Korean Journal of Environment and Ecology
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• v.35 no.4
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• pp.387-397
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• 2021

This study aims to present reference data necessary for developing evaluation indicators to analyze the actual resilience of purchased land by investigating the factors that affect the restoration of the purchased land in the riparian zone and quantitatively calculating its importance. The main results are as follows. Firstly, this study identified 34 potential resilience factors through a literature review encompassing domestic and overseas studies and derived seven ecological responsiveness factors, six physical responsiveness factors, and four managerial responsiveness factors through the Delphi survey. Secondly, reliability analysis and Analytic Hierarchy Process (AHP) analysis derived the following important factors: structural stability of the vegetation restored in the purchased land, species diversity of wildlife, structural stability of wildlife, the size of restored wetland after purchase, number of plant species, and the land cover status adjacent to the purchased land. The study results are expected to be helpful information for ecological restoration and management plans reflecting reinforcing factors for resilience at each stage of land purchase, restoration, and management.

• Journal of Korea Foundry Society
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• v.41 no.6
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• pp.550-557
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• 2021

With the advent of the fourth industrial revolution, the interest in the internet of things (IoT) in manufacturing is growing, even at foundries. There are several types of process data that can be automatically collected at a foundry, but considerable amounts of process data are still managed based on handwriting for reasons such as the limited functions of outdated production facilities and process design based on operator know-how. In particular, despite recognizing the importance of converting process data into big data, many companies have difficulty adopting these steps willingly due to the burden of system construction costs. In this study, the field applicability of IoT-based devices was examined by manufacturing devices and applying them directly to the site of a centrifugal foundry. For the centrifugal casting process, the temperature and humidity of the working site, the molten metal temperature, and mold rotation speed were selected as process parameters to be collected. The sensors were selected in consideration of the detailed product specifications and cost required for each process parameter, and the circuit was configured using a NodeMCU board capable of wireless communication for IoT-based devices. After designing the circuit, PCB boards were prepared for each parameter, and each device was installed on site considering the working environment. After the on-site installation process, it was confirmed that the level of satisfaction with the safety of the workers and the efficiency of process management increased. Also, it is expected that it will be possible to link process data and quality data in the future, if process parameters are continuously collected. The IoT-based device designed in this study has adequate reliability at a low cast, meaning that the application of this technique can be considered as a cornerstone of data collecting at foundries.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.111-123
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• 2022

Artificial intelligence, which is developing as the core of an intelligent information society, is bringing convenience and positive life changes to humans. However, with the development of artificial intelligence, human rights and property are threatened, and ethical problems are increasing, so alternatives are needed accordingly. In this study, the most controversial artificial intelligence ethics problem in the dysfunction of artificial intelligence was aimed at researching and developing artificial intelligence ethical measurement indicators to protect human personality rights and property first under artificial intelligence ethical principles and components. In order to research and develop artificial intelligence ethics measurement indicators, various related literature, focus group interview(FGI), and Delphi surveys were conducted to derive 43 items of ethics measurement indicators. By survey and statistical analysis, 40 items of artificial intelligence ethics measurement indicators were confirmed and proposed through descriptive statistics analysis, reliability analysis, and correlation analysis for ethical measurement indicators. The proposed artificial intelligence ethics measurement indicators can be used for artificial intelligence design, development, education, authentication, operation, and standardization, and can contribute to the development of safe and reliable artificial intelligence.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• Journal of the Korea Society for Simulation
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• v.30 no.4
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• pp.9-19
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• 2021

Electronic voting has been recognized as an alternative to complement the limitations of existing paper voting. At the same time, security concerns are being raised. This paper presents a blockchain-based electronic voting and survey system that can guarantee reliability. Our smart contract was created using Solidity on Ethereum which is a blockchain-based distributed computing platform, and the system was implemented in connection with the Javascript based user interface. In addition, in order to protect the personal information of participants, the system is generating hash of the personal data and storing the hash of users for the contract data. Since we exploited different kinds of languages for the system, we derived items of functionality testing and presented the functionality testing result. Moreover, we made use of the Chrome's performance evaluation functionality to see the response time of the blockchain-based system. In addition, we compared the performance with the system which has the same functionality on database. The contribution of this research is design and implementation of blockchain-based electronic voting system and presentation of the functionality and performance simulation result.