• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.275-292
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• 2022

In order to detect climate changes using satellite imagery, the GCOS (Global Climate Observing System) defines requirements such as spatio-temporal resolution, stability by the time change, and uncertainty. Due to limitation of GK-2A sensor performance, the level-2 products can not satisfy the requirement, especially for spatial resolution. In this paper, we found the optimal pan-sharpening algorithm for GK-2A products. The six pan-sharpening methods included in CS (Component Substitution), MRA (Multi-Resolution Analysis), VO (Variational Optimization), and DL (Deep Learning) were used. In the case of DL, the synthesis property based method was used to generate training dataset. The process of synthesis property is that pan-sharpening model is applied with Pan (Panchromatic) and MS (Multispectral) images with reduced spatial resolution, and fused image is compared with the original MS image. In the synthesis property based method, fused image with desire level for user can be produced only when the geometric characteristics between the PAN with reduced spatial resolution and MS image are similar. However, since the dissimilarity exists, RD (Random Down-sampling) was additionally used as a way to minimize it. Among the pan-sharpening methods, PSGAN was applied with RD (PSGAN_RD). The fused images are qualitatively and quantitatively validated with consistency property and the synthesis property. As validation result, the GSA algorithm performs well in the evaluation index representing spatial characteristics. In the case of spectral characteristics, the PSGAN_RD has the best accuracy with the original MS image. Therefore, in consideration of spatial and spectral characteristics of fused image, we found that PSGAN_RD is suitable for GK-2A products.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.27-37
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• 2022

Virtual private network (VPN) services are used in various environments related to national security, such as defense companies and defense-related institutions where digital communication environment technologies are diversified and access to network use is increasing. However, the number of cyber attacks that target vulnerable points of the VPN has annually increased through technological advancement. Thus, this study identified security requirements by performing STRIDE threat modeling to prevent potential and new vulnerable points that can occur in the VPN. STRIDE threat modeling classifies threats into six categories to systematically identify threats. To apply the proposed security requirements, this study analyzed functions of the VPN and formed a data flow diagram in the VPN service process. Then, it collected threats that can take place in the VPN and analyzed the STRIDE threat model based on data of the collected threats. The data flow diagram in the VPN service process, which was established by this study, included 96 STRIDE threats. This study formed a threat scenario to analyze attack routes of the classified threats and derived 30 security requirements for each element of the VPN based on the formed scenario. This study has significance in that it presented a security guideline for enhancing security stability of the VPN used in facilities that require high-level security, such as the Ministry of National Defense (MND).

• Land and Housing Review
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• v.13 no.3
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• pp.39-55
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• 2022

In this study, we investigate the interrelationship between housing tenure and childbirth by exploiting the correlation probability effect method that accounts for household heterogeneity. Using the newlywed household panel from 2011 to 2022, we find that home ownership has a positive impact on childbirth in newlyweds. Specifically, newlywed households with housing tenure show a 6.2%p higher birth rate and a 5.7%p higher second childbirth than newlywed households living in rented houses. For the case of first childbirth, we employ the probability effect probit model since the endogeneity was not detected between housing tenure and birth rate. We document the differential effects of housing tenure on childbirth in that the first childbirth rate is higher for households without housing tenures. The negative effects on first childbirth could be attributed to the economic burden due to initial housing ownership, while housing tenure could eventually provide housing stability, leading to positive effects on more than one childbirth. Finally, we identify that households with childbirth over the last year show a 4.2%p and 3.9%p lower probabilities of housing tenure in the total sample and second childbirth sample, respectively. This suggests that the increased living cost due to childbirth could delay home ownership.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.67-74
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• 2021

The purpose of this study is to explore the internal foundation of lifelong education for the disabled. The composition system of the meaning of contents for this purpose is divided into three elements: 'of' which means subject based on lifelong education for the disabled, 'for' which means purpose, and 'from' which means practical main base. The research method was to discuss the academic basis, practical application model and plan, or to analyze the literature through the previous studies that were actualized in order to form the internal foundation of the support system for lifelong education for the disabled. Second, the expert meeting was conducted to improve the specificity of the research contents based on the basis of the literature analysis. The contents of this study are presented in two main ways: the foundation of developmental disabilities and the foundation of schools by synthesizing the main bases of subjects, purposes, and practical base required to form the internal foundation of lifelong education for the disabled. The above two factors first establish the internal universality of the support system for lifelong education for the disabled, and in connection with the types of sensory disabilities and the general lifelong education. As a result, the long-term stability of the overall support system for lifelong education for the disabled was analyzed.

• Journal of the Korean GEO-environmental Society
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• v.22 no.12
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• pp.5-13
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• 2021

Expandable steel pipe piles have been developed to ensure stability and reduce construction costs during underground floor remodeling and extension work. Expandable steel pipe piles are more economical and stable than micropiles. Extensible steel pipe pile is a method of improving the performance of steel pipes by expanding steel pipes underground. In this paper, the changes in buckling strength according to the shape of steel pipes in an extended steel pipe pile were identified, a numerical analysis model was developed to determine the expended part effect of bumps due to steel pipe expansion, and the optimal steel pipe expansion was calculated through material tests. The larger the expansion diameter of the steel pipe and the greater the number of expanded part, the greater the buckling strength. Numerical results showed that the number of expanded part has a greater effect on buckling strength than the expansion rate. When the expansion rate is more than 1.2 times, it can be seen that as the number of expanded part increases, the effect of increasing buckling strength increases significantly. It was also noted that the expanded part effect of the bumps occur significantly when the extension angle is less than 45° and the expansion rate is 1.3 times higher. When the steel pipe is failure, the expanded rate is 20 to 32%, averaging 25.4%. Through the material test, it was analyzed that it is desirable to limit the maximum expansion rate for performing steel pipes to 16%.

• Geophysics and Geophysical Exploration
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• v.24 no.4
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• pp.180-193
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• 2021

The complex resistivity method is an exploration technique that can obtain various characteristic information of underground media by measuring resistivity and phase in the frequency domain, and its utilization has recently increased. In this paper, a three-dimensional inversion algorithm for the CR data was developed to increase the utilization of this method. The Poisson equation, which can be applied when the electromagnetic coupling effect is ignored, was applied to the modeling, and the inversion algorithm was developed by modifying the existing algorithm by adopting comlex variables. In order to increase the stability of the inversion, a technique was introduced to automatically adjust the Lagrangian multiplier according to the ratio of the error vector and the model update vector. Furthermore, to compensate for the loss of data due to noisy phase data, a two-step inversion method that conducts inversion iterations using only resistivity data in the beginning and both of resistivity and phase data in the second half was developed. As a result of the experiment for the synthetic data, stable inversion results were obtained, and the validity to real data was also confirmed by applying the developed 3D inversion algorithm to the analysis of field data acquired near a hydrothermal mine.

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

• Explosives and Blasting
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• v.40 no.4
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• pp.15-26
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• 2022

With the recent increase in old and dangerous buildings, the demand for technology in the field of structure demolition is rapidly increasing. In particular, in the case of structures with severe deformation of damage, there is a risk of deterioration in stability and disaster due to changes in the load distribution characteristics in the structure, so rapid structure demolition technology that can be efficiently dismantled in a short period of time is drawing attention. However, structural deformation such as unauthorized extension or illegal remodeling occurs frequently in many old structures, which is not reflected in structural information such as building drawings, and acts as an obstacle in the demolition design process. In this study, as an effective way to overcome the discrepancy between the structural information of old structures and the actual structure, access to actual structures through 3D modeling was considered. 3D point cloud data inside and outside the building were obtained through LiDAR and drone photography for buildings scheduled to be blasting demolition, and precision matching between the two spatial data groups was performed using an open-source based spatial information construction system. The 3D structure model was completed by importing point cloud data matched with 3D modeling software to create structural drawings for each layer and forming each member along the structure slab, pillar, beam, and ceiling boundary. In addition, the modeling technique proposed in this study was verified by comparing it with the actual measurement value for selected structure member.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.340-351
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• 2023

Landslides are major natural geological hazards that cause enormous property damage and human casualties annually. The vulnerability of mountainous areas to landslides is further exacerbated by the impacts of climate change. Soil depth is a crucial parameter in landslide and debris flow analysis, and plays an important role in the evaluation of watershed hydrological processes that affect slope stability. An accurate method of estimating soil depth is to directly investigate the soil strata in the field. However, this requires significant amounts of time and money; thus, numerous models for predicting soil depth have been proposed. However, they still have limitations in terms of practicality and accuracy. In this study, 71 seismic survey results were collected from domestic mountainous areas to estimate soil depth on hill slopes. Soil depth was estimated on the basis of a shear wave velocity of 700 m/s, and a database was established for slope angle, elevation, and soil depth. Consequently, the statistical characteristics of soil depth were analyzed, and the correlations between slope angle and soil depth, and between elevation and soil depth were investigated. Moreover, various soil depth prediction models based on slope angle were investigated, and corrected linear and exponential soil depth prediction models were proposed.

• Journal of Korean Home Economics Education Association
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• v.35 no.2
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• pp.111-132
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• 2023

The objective of this research is to conceptualize care competences for adolescents and to develop a valid measurement tool based on this conceptualization. The primary aim is to establish a solid foundation for effective communication in teaching care competences within the domain of home economics education. To achieve this, a comprehensive review of relevant literature and previous studies was conducted, and consultations with experts were undertaken to assess content and criterion-related validity. Furthermore, exploratory and confirmatory factor analyses were performed. The findings from these analyses resulted in a set of 34 items, which were categorized into five distinctive factors representing care competences in adolescents. These factors encompassed four items of care thinking, seven items of care emotion, six items of care behavior, seven items of self-care and ten items of community-care. Additionally, a reliability analysis was performed on the model, confirming the stability and consistency of the five factor structure and the 34 item scale, which assess care competences in adolescents.