• Korean Journal of Construction Engineering and Management
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• v.22 no.2
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• pp.88-96
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• 2021

There have been many efforts to identify and eliminate the direct causes of the construction accident, but many accidents are still occurring in the construction industry. The main reason for the construction accident is not because of ignorance of the causes, but because of safety insensitivity. This paper analyzes why construction workers feel safety insensitivity and how safety insensitivity varies depending on their age and work experience. A survey of 103 construction workers confirmed that systematic safety education is the most important factor in minimizing safety insensitivity of construction workers. On the other hand, economic reasons such as cost reduction were identified as the most tempting factor to increase safety insensitivity. In addition, the survey results showed that those in their 40s and 50s, the largest proportion of construction workers, have a significantly higher level of safety insensitivity than those in their 20s and 60s. These findings are expected to be valuable source that can be used to prevent construction safety accidents.

• Food Science and Industry
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• v.54 no.2
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• pp.93-101
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• 2021

Hazard Analysis Critical Control Point (HACCP) systems were developed to ensure a high level of food safety and reduced risk of foodborne illness. This paper focuses on significant issues associated with the implementation of HACCP; it provides an overview on recent literature. The structure of the paper follows six groupings of issues in the international literature of HACCP: (1) comparative studies and unification plan between HACCP and other food safety regulations; (2) verification of the HACCP system's effectiveness in improving food safety; (3) establishment of critical control point (CCP) for various foods HACCP model development; (4) expansion of HACCP application in the various fields and small businesses;(5) the impacts of HACCP on consumer's preferences and firms' financial performance in food industry; (6) HACCP and technological changes. The paper concludes with some suggestions for the future research in order to promote safe food supply chain for global customers.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.845-856
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• 2020

This study proposes a bridge evaluation system for indivisible permit vehicles such as hydraulic cranes. The permit loads for the bridge evaluation are divided into three categories: routine permit loads, special permit 1 loads, and special permit 2 loads. Routine permit and special permit 1 vehicles are allowed to cross a bridge with normal traffic. For these two permits, the standard lane model in the Korean Highway Bridge Design Code was adopted to consider normal traffic in the same lane. Special permit 2 vehicles are assumed to cross a bridge without other traffic. Structural analyses of two prestressed-beam bridges and two steel box girder bridges were conducted for the proposed permit loads. The rating factors of the four bridges for all permit loads were calculated as sufficiently large values for the moment and shear force so that crossing the bridges can be permitted. A reliability assessment of the bridges was performed to identify the reliability levels for the permit vehicles. It was confirmed that the reliability level of the minimum required strength obtained by the load-resistance factors yields the target reliability index of the design code for the permit vehicles.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.318-325
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• 2021

The objective of this study was to identify the effect of zebularine, a DNA methylation inhibitor, on the chromosomal association between homoeologous chromosomes in the wheat genetic background. Zebularine at a final concentration of 10 µM was used to treat the spikes of the double monosomic wheat addition line (DMA) with one Leymus mollis chromosome and one Leymus racemosus chromosome, both of which were in a homoeologous relationship. In late prophase, zebularine led to chromosome breakage in the Leymus homoeologous chromosomes. Chromosome breakage caused an increase in the frequency of chromosomal associations between the Leymus homoeologous chromosomes. Ordinary DMA showed 65 cells (35.3%) with chromosomal associations and 119 cells (64.7%) with no association, whereas treated DMA showed 102 cells (60.0%) with chromosomal associations and 67 cells (39.4%) with no association. In diakinesis, the Leymus bivalent showed a chromosomal association in the whole euchromatic region. In metaphase, the Leymus bivalent showed association in the whole chromosomal region, unlike other Leymus bivalents with partial chromosomal association. Chromosomal association by chromosome breakage occurred not only between Leymus chromosomes but also between Leymus and wheat chromosomes. The frequency of other chromosomal association (such as fusion and insert) was increased. Chromosome breakage by zebularine treatment is a useful method at the chromosome level as the spores with others are hereditary stable, although the homologous index (h) was not significantly different between ordinary DMA and treated DMA. It is necessary to study how to control zebularine treatment with a more stable concentration for chromosome breakage during meiosis.

• 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.

• Environmental and Resource Economics Review
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• v.30 no.4
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• pp.607-625
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• 2021

The objective of this study is to estimate the relationship between CO₂ emissions and both nuclear power and renewable energy generation, and compare the cost efficiencies of nuclear power and renewable energy generation in reducing CO₂ emissions in Korea. The results show that nuclear power and renewable energy generation should be increased by 1.344% and 7.874% to reduce CO₂ emissions by 1%, respectively. Using the estimated coefficients and the levelized costs of electricity by source including the external costs, if the current amount of electricity generation is one megawatt-hour, the range of generation cost of nuclear power generation to reduce 1% CO₂ emissions is $0.72~$1.49 depending on the level of external costs. In the case of renewable energy generation, the generation cost to reduce 1% CO₂ emissions is $6.49. That is, to mitigate 1% of CO₂ emissions at the total electricity generation of 353 million MWh in 2020 in Korea, the total generation costs range for nuclear power is $254 million~$526 million for the nuclear power, and the cost for renewable energy is $2.289 billion for renewable energy. Hence, we can conclude that, in Korea, nuclear power generation is more cost-efficient than renewable energy generation in mitigating CO₂ emissions, even with the external costs of nuclear power generation.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.165-175
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• 2022

The objective of this study is to identify the relationships among app attribution(perceived usefulness, design, information quality, and mobility), user satisfaction, trust, and continuous use intention of bus information apps; The structural equation of AMOS 21.0 was used to test the hypothesis of this study. The results of the analysis are as follows. First, perceived usefulness, design, information quality, and mobility positively impact user satisfaction. Second, only mobility has a positive effect on trust, but the remaining perceived usefulness, design, and information quality have no effect at the significance level of 5%. Third, user satisfaction has a positive impact on trust and continuous use intention. Fourth, trust has a positive impact on continuous use intention. Therefore, it was confirmed that the characteristics of the bus information mobile app are important influencing factors for the improvement of user satisfaction, trust, and continuous use intention. Local governments and bus companies will be able to establish strategic directions for the activation of bus information mobile apps. The limitation of this study is that it is somewhat lacking in generalizing the study results, so future research needs to focus on improving this part.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.38-49
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• 2021

This study is single-group pretest-posttest design study to examine the effects of web-based cognitive training program using tablet on cognition and depression in the elderly with high risk of dementia or mild dementia living in a rural area, enrolled in dementia center. Intervention was provided to the 18 participants once a week for 10 weeks within 1 hour. Data was analyzed with SPSS 24.0 and interview data was categorized. The study result proves that after intervention, the participants' cognitive score increased significantly(Z=-3.35, p=.001) and the depression scores were significantly decreased(Z=-3.13, p=.002). Also, interview shows positive effect of the intervention on cognition and depression. It is necessary to improve access environment for smart devices so as not to be restricted by time and place, and to develop and apply various types of web-based programs for each cognitive level. Then, the intervention could be used as a cognitive training program incorporating information and communication technology for the prevention and management of dementia in rural areas.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.19-27
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• 2022

Across the world, 'housing' comprises a significant portion of wealth and assets. For this reason, fluctuations in real estate prices are highly sensitive issues to individual households. In Korea, housing prices have steadily increased over the years, and thus many Koreans view the real estate market as an effective channel for their investments. However, if one purchases a real estate property for the purpose of investing, then there are several risks involved when prices begin to fluctuate. The purpose of this study is to design a real estate price 'return rate' prediction model to help mitigate the risks involved with real estate investments and promote reasonable real estate purchases. Various approaches are explored to develop a model capable of predicting real estate prices based on an understanding of the immovability of the real estate market. This study employs the LSTM method, which is based on artificial intelligence and deep learning, to predict real estate prices and validate the model. LSTM networks are based on recurrent neural networks (RNN) but add cell states (which act as a type of conveyer belt) to the hidden states. LSTM networks are able to obtain cell states and hidden states in a recursive manner. Data on the actual trading prices of apartments in autonomous districts between January 2006 and December 2019 are collected from the Actual Trading Price Disclosure System of the Ministry of Land, Infrastructure and Transport (MOLIT). Additionally, basic data on apartments and commercial buildings are collected from the Public Data Portal and Seoul Metropolitan Government's data portal. The collected actual trading price data are scaled to monthly average trading amounts, and each data entry is pre-processed according to address to produce 168 data entries. An LSTM model for return rate prediction is prepared based on a time series dataset where the training period is set as April 2015~August 2017 (29 months), the validation period is set as September 2017~September 2018 (13 months), and the test period is set as December 2018~December 2019 (13 months). The results of the return rate prediction study are as follows. First, the model achieved a prediction similarity level of almost 76%. After collecting time series data and preparing the final prediction model, it was confirmed that 76% of models could be achieved. All in all, the results demonstrate the reliability of the LSTM-based model for return rate prediction.