• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1165-1172
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• 2023

Recently, Korea has declared carbon neutrality by 2050. The Korea Forest Service is promoting the precision and high technology of forest resource surveys. As such, the demand for forest resource management is increasing, and the need to build a digital twin of forest space is increasing. However, to date, digital twin has only built and provided virtual city services, which are city and nationwide digital twin environments. Three-dimensional digital twin services targeting forest space are not operated and provided. Therefore, in this study, we aimed to implement a forest digital twin environment to provide 3D forest spatial information services corresponding to vertical information such as tree-level height and thorax diameter. By lightweighting realistic 3D tree models and applying 3D Tiles, we confirmed the feasibility of implementing a forest digital twin environment for 3D forest spatial information services. Through continuous research, we plan to implement a forest digital twin that can deploy and service 3D tree models for trees nationwide, including street trees in urban areas. This is expected to enable the development of forest digital twin services for forest resource management.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.57-68
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• 2023

With the technological development in the era of the 4th Industrial Revolution, technologies using HMD are being applied in various fields. HMD is especially useful in virtual reality fields such as AR/VR, and is very effective in receiving vivid impressions from users located in remote locations. According to these characteristics, the frequency of using HMD is increasing in the field related to collaboration. However, when HMD is applied to collaboration, communication between experts located in remote locations and workers located in the field is not smooth, causing various problems in terms of usability. In this paper, remote experts and workers in the field use HMD to solve various problems arising from collaboration, design/propose new types of HMD structures and functions that enable more efficient collaboration, and verify their usability using SUS evaluation techniques. As a result of the SUS evaluation, the new type of HMD structure and function proposed in this paper was 86.75points, which is believed to have greatly resolved the restrictions on collaboration and inconvenience in use of the existing HMD structure. In the future, when the HMD structure and design proposed in this paper are actually applied, it is expected that the application technology using HMD will expand rapidly.

• Journal of Industrial Convergence
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• v.21 no.11
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• pp.13-27
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• 2023

This study aims to contribute to the reduction of the failure rate and social costs resulting from business failures by analyzing factors that affect the insolvency of social enterprises, as the role of social enterprises is increasing in our economy. The data used in this study were classified as normal and insolvent companies among social enterprises (including prospective social enterprises) that were established between 2009 and 2018 and received credit guarantees from credit guarantee institutions as of the end of June 2022. Among the collected data, 439 social enterprises with available financial information were targeted; 406 (92.5%) were normal enterprises, and 33 (7.5%) were insolvent enterprises. Through a literature review, eight non-financial factors commonly used for insolvency prediction were selected. The cross-analysis results showed that four of these factors were significant. Logistic regression analysis revealed that two variables, including corporate credit rating and the personal credit rating of the representative, were significant. Financial factors such as debt ratio, sales operating profit rate, and total asset turnover were used as control variables. The empirical analysis confirmed that the two independent variables maintained their influence even after controlling for financial factors. Given that government-led support and development policies have limitations, there is a need to shift policy direction so that various companies aspiring to create social value can enter the social enterprise sector through private and regional initiatives. This would enable the social economy to create an environment where local residents can collaborate to realize social value, and the government should actively support this.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.689-693
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• 2023

Domestic bridges with a service life of more than 30 years are expected to account for approximately 54% of all bridges within the next 10 years. As bridges rapidly deteriorate, it is necessary to establish an appropriate maintenance plan. Recent domestic and international research have focused on the integration of BIM to digitize bridge maintenance information and then enhance accessibility and usability of the information. Accordingly, this study developed a BIM-FEM interoperability algorithm for bridge decks to convert maintenance information into data and efficiently manage the history of maintenance. After creating an initial crack BIM based on an exterior damage map, bridge specification and damage information were linked to a numerical analysis that performs damage analysis considering damage scenarios and design loads. The spread of cracks obtained from the analysis results were updated into the BIM. Based on the damage spread information on the BIM, an automated technology was also developed to assess both the current and future condition ratings of the bridge deck. This approach can enable an efficient maintenance of the deck using the history data from bridge inspection and diagnosis as well as future information on cracks and defects. The expected early detection and prevention would ultimately improve the lifespan and safety of bridges.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.883-896
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• 2023

As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.161-168
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• 2023

This study attempted to determine the relationship between college students' motivation for major selection (personal motivation, social motivation), academic performance, and career maturity, and to identify the influencing factors of career maturity in order to provide basic data for improving career maturity. Data were collected through a structured questionnaire from 199 university students in C city. As a result of examining the correlation between personal motivation for major selection, social motivation, academic achievement, and career maturity, career maturity showed a significant positive correlation with personal motivation for major selection (r=.417, p=.00) and no significant correlation with social motivation for major selection and academic achievement. The influencing factors of career maturity were personal motivation for major selection, economic activity, and major department, and the explanatory power was 24%. Therefore, it seems that university-level support is needed to enable students to engage in economic activities in fields related to their majors. Since personal motivation is important in major selection, we should focus on increasing personal motivation for major selection by providing high school students with a wide range of opportunities, such as career experience and future work experience.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of Public Diplomacy
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• v.2 no.2
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• pp.1-26
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• 2022

Since the seminal publication of Joseph Nye's Soft Power, soft power became the central concept to public diplomacy. However, over-emphasis on soft power, which is still controversial, deterred academics from producing valuable knowledge that can be applied to practices in the field. Soft power is a cause and effect at the same time and thus it makes systematic analysis almost implausible because it is not only a tool for successful public diplomacy, but it is a result of successful diplomacy. This study aims at offering a theoretical framework linking soft power and public diplomacy by including various factors that may affect the outcomes of effective public diplomacy. This theoretical framework assessing the effectiveness of public diplomacy will make it possible to explore how and when new public diplomacy was adopted in a certain country and examine hard and soft power resources. The model also includes political system variables such as ideas and values, institutions, governance, leadership, and communication system, which are expected to influence public diplomacy effectiveness rather than soft power itself. The model yields the effectiveness of public diplomacy by assessing outcome and impact relative to input and output that are applicable to practices. The model is expected to enable both quantitative and qualitative studies generating possible propositions from the model with some preliminary outcomes of comparative case studies.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.40-48
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• 2023

In this paper, a sensor-based monitoring system was established to analyze the long-term behavioral characteristics of the caisson quay wall, a representative structural type in port facilities. Data was collected over a period of approximately 10 months. Based on existing literature, anomalous behaviors of port facilities were classified, and a measurement system was selected to detect them. Monitoring systems were installed on-site to periodically collect data. The collected data was transmitted and stored on a server through LTE network. Considering the site conditions, inclinometers for measuring slope and crack meters for measuring spacing and settlement were installed. They were attached to two caissons for comparison between different caissons. The correlation among measured data, temperature, and tidal level was examined. The temperature dominated the spacing and settlement data. When the temperature changed by approximately 50 degrees, the spacing changed by 10 mm, the settlement by 2 mm, and the slope by 0.1 degrees. On the other hand, there was no clear relationship with tidal level, indicating a need for more in-depth analysis in the future. Based on the characteristics of these collected database, it will be possible to develop algorithms for detecting abnormal states in gravity-type quay walls. The acquisition and analysis of long-term data enable to evaluate the safety and usability of structures in the event of disasters and emergencies.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1321-1330
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• 2023

This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.