• Journal of the Korean GEO-environmental Society
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• v.12 no.5
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• pp.51-57
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• 2011

Generally, ready-mixed concrete(RMC) gets hardened by time, so the remaining concrete in the drum should be cleaned. But if the RMC waste water generated from this is discharged to soil without any treatment, the strong alkaline elements and heavy metals affect water and ecosystem pollution. Although about 10 to 15% of water used for cleaning in the RMC factory is discharged to soil or river, the concrete report of this affecting soil pollution has not been sufficient. Hence, in this study it was analyzed the extraction of cleaning water from RMC factories all over the country and heavy metal and pH components remaining in soil when this is penetrated to various soils having water permeability. The specimens used for the experiment are weathering soil and soils having different particle size, and it is made to be penetrated to those for 24 hours while fixed thickness of the layer is maintained. Cleaning water is divided into that before deposition treatment(sludge water) and that after deposition treatment(upper water) to be penetrated into soil, and according to the result of penetrating sludge water to soil, Cu and Mn, Fe, and Zn were found to be remained over 23 to 90%. However, it is analyzed that in upper water having deposition treatment, Cu and Mn remain as 60% or more only in weathering soil.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.104-112
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• 2021

For extrusion processes in the process industry, the need to build smart factories is increasing. However, in most extrusion production sites, the production method is continuous, and because the properties of the data are undeed, it is difficult to process the data. In order to solve this problem, we present a methodology utilizing a near field communication (NFC) sensor rather than water-based data entry. To this end, a wireless network environment was built, and a data management method was designed. A non-contact NFC method was studied for the production performance-data input method, and an analysis method was implemented using the pivot function of the Excel program. As a result, data input using NFC was automated, obtaining a quantitative effect from reducing the operator's data processing time. In addition, using the input data, we present a case where a bottleneck is improved due to quality problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.85-91
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• 2021

The DAPA (Defense Acquisition Program Administration) has been operating the DQ mark certification since 2012 to certify the superior technology and quality of munitions. On the other hand, the current DQ mark certification can not directly provide DQ mark certification to software because it is impossible to verify the quality of software alone. Therefore, this study analyzed domestic/overseas software quality evaluation/certification standards to find a way to verify the quality of software in the DQ mark certification. Among them, the method of applying the GS certification according to the international standard ISO/IEC 25000 series to the DQ mark certification was suggested as an improvement plan, and DQ mark certification verified the quality of software and provided certification. An attempt was made to expand the certification scope of DQ mark certification. This paper proposes that the DQ mark can be given to the system software by introducing GS certification to the DQ mark certification. To this end, an improved procedure for omitting the factory audit and verification by submitting a GS certificate for product evaluation is proposed. This is expected to increase defense exports using the granted DQ mark and improve the quality of defense software products through GS certification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.888-895
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• 2020

In the construction industry, off-site construction (OSC) is drawing attention as a production method due to changes in working hours and the supply and demand of manpower. In 1991, there was a policy of spreading and expanding the use of precast concrete (PC) apartment homes, but they have not been actively used so far since they were discontinued due to quality problems. In this study, policy tasks were analyzed to motivate the application of OSC-based PCs in the apartment housing sector, and policy directions were derived by conducting focus group interviews (FGI). Nine policies are suggested regarding the following topics: PC apartment supply quantity provision, priority application of public housing, priority supply of public housing, preferential floor area ratio, funding, tax support, improvement of business area structure, improvement of delivery method, factory certification system, and training of experts. The results of the FGIs are as follows. First, in order to revitalize PC apartment homes, leading efforts from the public sector are required. Second, rather than reorganizing the business sector or introducing a new delivery method, a policy direction that induces the strengthening of cooperation is desirable. Third, PC activation should be promoted on an institutional basis for securing appropriate construction costs and quality.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.59-66
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• 2021

Humans mainly recognize surrounding objects using visual and auditory information among the five senses (sight, hearing, smell, touch, taste). Major research related to the latest object recognition mainly focuses on analysis using image sensor information. In this paper, after emitting various chirp audio signals into the observation space, collecting echoes through a 2-channel receiving sensor, converting them into spectral images, an object recognition experiment in 3D space was conducted using an image learning algorithm based on deep learning. Through this experiment, the experiment was conducted in a situation where there is noise and echo generated in a general indoor environment, not in the ideal condition of an anechoic room, and the object recognition through echo was able to estimate the position of the object with 83% accuracy. In addition, it was possible to obtain visual information through sound through learning of 3D sound by mapping the inference result to the observation space and the 3D sound spatial signal and outputting it as sound. This means that the use of various echo information along with image information is required for object recognition research, and it is thought that this technology can be used for augmented reality through 3D sound.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.36-42
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• 2021

With recent developments in the Fourth Industrial Revolution, the manufacturing industry has changed rapidly. Through key aspects of Fourth Industrial Revolution super-connections and super-intelligence, machine learning will be able to make fault predictions during the foam-making process. Polyol and isocyanate are components in polyurethane foam. There has been a lot of research that could affect the characteristics of the products, depending on the specific mixture ratio and temperature. Based on these characteristics, this study collects data from each factor during the foam-making process and applies them to machine learning in order to predict faults. The algorithms used in machine learning are the decision tree, kNN, and an ensemble algorithm, and these algorithms learn from 5,147 cases. Based on 1,000 pieces of data for validation, the learning results show up to 98.5% accuracy using the ensemble algorithm. Therefore, the results confirm the faults of currently produced parts by collecting real-time data from each factor during the foam-making process. Furthermore, control of each of the factors may improve the fault rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.834-841
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• 2022

Recently, applying artificial intelligence technologies in various fields of production has drawn an upsurge of research interest due to the increase for smart factory and artificial intelligence technologies. A great deal of effort is being made to introduce artificial intelligence algorithms into the defect detection task. Particularly, detection of defects on the surface of metal has a higher level of research interest compared to other materials (wood, plastics, fibers, etc.). In this paper, we compare and analyze the speed and performance of defect classification by combining machine learning techniques (Support Vector Machine, Softmax Regression, Decision Tree) with dimensionality reduction algorithms (Principal Component Analysis, AutoEncoders) and two convolutional neural networks (proposed method, ResNet). To validate and compare the performance and speed of the algorithms, we have adopted two datasets ((i) public dataset, (ii) actual dataset), and on the basis of the results, the most efficient algorithm is determined.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.1
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• pp.81-88
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• 2022

In the NRC (New paradigm Reinforced Concrete) beam, steel forms, main angles used as main reinforcements, and shear angles used as basic shear reinforcements are welded and assembled in the form of vierendeel truss structures in a steel factory. After the NRC truss frame is installed at the site, additional main reinforcement and shear reinforcement are distributed. In this study, the shear performance evaluation of the NRC beam was conducted through shear tests in accordance with the type of shear reinforcement of the NRC beam (shear angle, inclined shear reinforcing bar, and U-type cover bar). As a result of the test, the initial stiffness was similar before the initial cracking of each specimen, and all specimens were shear fractured.The shear reinforcements of the specimens exhibited a yielding behavior at the time of the maximum sheat force, and the shear strengths of the specimens increased as the amount of reinforcement of the shear reinforcement increased. These results show that NRC shear reinforcements exhibit shear performance corresponding to their shear strength contribution. As a result of calculating the nominal shear strengths according to KDS 14 20 22, the experimental shear strengths of the NRC beam specimens with shear reinforcement was 37~146% larger than the nominal shear strengths, so It was evaluated as a safety side.

• Tunnel and Underground Space
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• v.32 no.1
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• pp.78-92
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• 2022

In this study, we proposed a diagnostics and assessment model for mining sites that can evaluate the smart mining technology level in a systematic and structured way. For this, the maturity of the smart mining was defined, and detailed assessment items of the diagnostics and assessment model for smart mining were derived by considering the smart factory diagnostics and assessment model (KS X 9001-3) used in the manufacturing industry. While maintaining the existing system, the existing 46 detailed assessment items were modified to be suitable for mining. As a result, a total of 29 detailed assessment items were derived in the areas of promotion strategy, process, information system and automation, and performance. Based on this, a questionnaire was designed to diagnose the level of smart mining technology, and assessment was performed by applying it to domestic iron mines. The level of smart mining technology in the study area was found to be level 2, and it could be inferred that it was about 40% lower than the average smart level of the general manufacturing industry. In addition, by using the developed model, it was possible to recognize the weak points of the mine at each stage of the introduction, operation, and advancement of smart mining, and to suggest investment and improvement directions.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.435-444
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• 2022

There are three focuses in the paper. Firstly, the study identified what channels were most viewed by YouTube users to watch the 'Daejang-dong scandal,' which was the most powerful agenda to influence the candidate preference among voters during the 20th presidential election. Secondly, the study analyzed whether the political tone of the first videos was in line with that of the subsequent videos. Finally, we compared the sentiment of comments on the first and subsequent videos. The results showed that TBS 'News Factory' and 'TV Chosun News' represented liberal and conservative factions, respectively. Secondly, the political tone of channels that were viewed subsequently was neutral, but the conservative channel users left more negative comments and that was significant statistically. In addition, about 80% of the conservative and liberal channel users shared the same political tendency with the channel they watched first, and more than 90% of the comments left at the subsequent videos in line with that of at the first news. Based on these results, the study concluded that the voters tended to seek political news that was similar with their political ideology, and it was considered a sort of echo chamber phenomenon on the YouTube. The study suggests that the performance of high-quality journalism by traditional news outlet might contribute to decrease the negative influence of political contents on YouTube users.