• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.4
• /
• pp.489-496
• /
• 2019

This paper is a study on the evaluation of loss factor of damping treatment materials to reduce the noise and vibration for panels of railway vehicles and automobiles. In order to determine the modal parameters of damping materials, beam excitation tests were carried out using different type PVC coated aluminum and steel base beam specimens. The specimens were excited from 10 Hz to 1000 Hz frequency range using sinusoidal force, and transfer mobility data were measured by using an accelerometer. The loss factors were determined by using integrated program, based on theories of Half Power Method, Minimum Tangent Error Method, Minimum Angle Error Method and Phase Change Method, which enable to evaluate the parameters using modal circle fit and least squares error method. In the case of lower loss factor and data of linear characteristics, any method could be applied for evaluation of parameters, however the case of higher loss factor or data including non-linear characteristics, the minimum angle error method could reduce the loss factor evaluation. The obtained dynamic properties of the coating material could be used for application of Finite Element Method analyzing the noise control effects of complex structures such as carbody or under-floor boxes of rolling stock. The damping material will be very useful to control the structural noise, because the obtained modal loss factors of each mode show very good effect on over $2^{nd}$ mode frequency range.

• KIPS Transactions on Software and Data Engineering
• /
• v.9 no.12
• /
• pp.387-402
• /
• 2020

Conventional automotive development has mainly focused on ensuring correctness and safety and security has been relatively neglected. However, as the number of automotive hacking cases has increased due to the increased Internet connectivity of automobiles, international organizations such as the United Nations Economic Commission for Europe(UNECE) are preparing cybersecurity regulations to ensure security for automotive development. As with other IT products, automotive cybersecurity regulation also emphasize the concept of "Security by Design", which considers security from the beginning of development. In particular, since automotive development has a long lifecycle and complex supply chain, it is very difficult to change the architecture after development, and thus Security by Design is much more important than existing IT products. The problem, however, is that no specific methodology for Security by Design has been proposed on automotive development process. This paper, therefore, proposes a specific methodology for Security by Design on Automotive development. Through this methodology, automotive manufacturers can simultaneously consider aspects of functional safety, and security in automotive development process, and will also be able to respond to the upcoming certification of UNECE automotive cybersecurity regulations.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.2
• /
• pp.651-658
• /
• 2021

Because bolts with anti-loosening coatings are used mainly for joining safety-related components in automobiles, accurate automatic screening of these coatings is essential to detect defects efficiently. The performance of the convolutional neural network (CNN) used in a previous study [Identification of bolt coating defects using CNN and Grad-CAM] increased with increasing number of data for the analysis of image patterns and characteristics. On the other hand, obtaining the necessary amount of data for coated bolts is difficult, making training time-consuming. In this paper, resorting to the same VGG16 model as in a previous study, transfer learning was applied to decrease the training time and achieve the same or better accuracy with fewer data. The classifier was trained, considering the number of training data for this study and its similarity with ImageNet data. In conjunction with the fully connected layer, the highest accuracy was achieved (95%). To enhance the performance further, the last convolution layer and the classifier were fine-tuned, which resulted in a 2% increase in accuracy (97%). This shows that the learning time can be reduced by transfer learning and fine-tuning while maintaining a high screening accuracy.

• Journal of the Korean Recycled Construction Resources Institute
• /
• v.8 no.4
• /
• pp.483-489
• /
• 2020

Particulate matter is divided into PM10 (particle diameter of 10 ㎛ or less) and PM2.5 (particle diameter of 2.5 ㎛ or less), which are approximately 1/5 of the thickness of the hair. Due to its effect on the human body, lung disease, arteriosclerosis and heart It is known as a carcinogen that causes various diseases such as diseases. It is known that the main cause of such fine dust is nitrogen dioxide (NOx), which is emitted from automobiles in about 57.3% of urban roadsides. Therefore, in this study, as part of the development of functional construction materials to reduce NOx generated from road transport pollutants, comparative evaluation of NOx reduction performance was conducted according to the replacement rate of cement mortar in which cement was replaced with a porous material. In addition, the NOx reduction performance of cement mortar according to the photocatalyst application method and the number of applications was compared an d evaluated. As a result of the experiment, when activated ocher was substituted by 30%, it showed a reduction effect of about 32.7%, showing the best reduction performance.

• Journal of the Institute of Convergence Signal Processing
• /
• v.21 no.1
• /
• pp.13-20
• /
• 2020

In shipyards, internal materials are assembled after designing and manufacturing each ship's block. Internal material assembly means the installation of parts and equipment except ship's body. In this process, if the assembly of pipes and equipment existing in the block is not done correctly during the assembly between blocks, this causes a lot of costs. In addition, even if the assembly of the internal materials already completed, the production efficiency of the ship is reduced due to rework when problems such as space arrangement of the internal materials occurs. Therefore, this study introduces space arrangement and inspection system before and after hull outfitting work based on coexistence reality technology using 3D design drawing to solve these problems. The various coexistence reality algorithms and inspection systems developed and introduced in this study are based on AR service, which has never been introduced in Korea. So it will be widely applicable to various manufacturing industries using design drawings such as automobiles and architectures as well as ship building process.

• Journal of Convergence for Information Technology
• /
• v.12 no.4
• /
• pp.103-110
• /
• 2022

Online transactions are more familiar in various fields due to the development of the ICT and the increase in trading platforms. In particular, the amount of transactions is increasing due to the increase in used transaction platforms and users, and reliability is very important due to the nature of used transactions. Among them, the used car market is very active because automobiles are operated over a long period of time. However, used car transactions are a representative market to which information asymmetry is applied. In this paper presents a DID-based transaction model that guarantees reliability to solve problems with false advertisements and false sales in used car transactions. In the used car transaction model, sellers only register data issued by the issuing agency to prevent false sales at the time of initial sales registration. It is authenticated with DID Auth in the issuance process, it is safe from attacks such as sniping and middleman attacks. In the presented transaction model, integrity is verified with VP's Proof item to increase reliability and solve information asymmetry. Also, through direct transactions between buyers and sellers, there is no third-party intervention, which has the effect of reducing fees.

• Journal of the Korean Regional Science Association
• /
• v.38 no.3
• /
• pp.51-63
• /
• 2022

COVID-19 has had a detrimental effect on urban vibrancy, particularly in urban commercial districts. Against this backdrop, the goal of this study is to examine the changes in social and economic vitality in Seoul's commercial area before and after the COVID-19 outbreak, and to identify influential factors for the changes in vitality using multinomial logistic analysis. The following are the key findings derived from the study. First, an examination of the changes in the vitality of commercial districts by type revealed that the decline in economic vitality was greater than the decline in social vitality. Second, the greater the residential ratio, the less harmful the impact of COVID-19 on urban vibrancy. Third, unlike other types of commercial districts, traditional markets had a minor increase in credit card sales even though the floating population fell during the COVID-19 pandemic. Fourth, the accessibility of the subway did not play a positive role in reversing the decline in social and economic vitality caused by the pandemic in the commercial district of Seoul; rather, the accessibility of private automobiles contributed to the increase in social and economic vitality. These results imply that the development and activation of commercial areas accessible by non-motorized modes in the residential neighborhood are becoming crucial in the post pandemic era.

• Journal of the Korean Institute of Gas
• /
• v.26 no.4
• /
• pp.58-63
• /
• 2022

With the emergence of environmental problems caused by fine dust worldwide, LNG, which is cheaper and less pollution than diesel, is attracting attention as the next generation energy of automobiles and is expanding its supply. However, it is difficult to operate smoothly due to the lack of infrastructure for LNG charging stations in Korea and the limited size of containers that can be installed according to regulations. In Korea, research and development on the contents of containers for the smooth operation of natural gas vehicles are underway, but there is a problem that the container directly receives the impact of the vehicle collision and explodes, causing a major disaster. Therefore, in this study, the safety of the container was verified by deriving the strain and stress values through ANSYS Explicit Dynamics analysis. As a result, a maximum stress of 565.37MPa occurred in the container, and it is expected that plastic deformation will occur as it exceeds the yield stress of STS304 used as a material for the container, which is beyond 505MPa. When an impact caused by a collision between a vehicle and a container is applied, it is considered necessary to design a support or reinforcement because the container may be damaged or defective.

• Environmental and Resource Economics Review
• /
• v.31 no.3
• /
• pp.419-449
• /
• 2022

This paper aims to quantify the potential economic burdens of EU's carbon border adjustment mechanisms faced by Korean domestic industries. In addition, this study tries to compare and analyzes changes in the burden of each industry resulted from the implementation of the domestic low-carbon policy. Based on the quantitative findings, we intend to suggest policy implications for establishing mid- to long-term strategies in response to climate change risks. Based on the environmentally extended input-output analysis, the total economic burdens of the domestic industries due to the EU's carbon border adjustment mechanisms are estimated to be approximately KRW 8,245.6 billion in 2030. Looking at the impacts by industry, it is found that major industries such as petrochemicals, petroleum refining, transportation equipment, steel, automobiles, and electric/electronic equipment industries are expected to account for 84.3% of the total potential burdens. In addition, in multiple policy scenarios assuming technological developments and energy transition following the implementation of domestic low-carbon policies, the total economic burden of carbon border adjustment is expected to decrease by about 11.7% to 15.0%. The main result of this study suggests that we should not view EU EU's carbon border adjustment mechanism as a trade regulation, but to use it as a momentum for more effective implementation of the low-carbon and energy transition strategies in the global carbon neural era.

• Journal of the Korean Society of Industry Convergence
• /
• v.24 no.6_2
• /
• pp.729-735
• /
• 2021

Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.