• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.93-100
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• 2024

Pore water freezes in low-temperature compaction, which leads to different compaction characteristics compared to room temperature conditions. In regions like Alberta, Canada, where organic soils are prevalent, compaction performance is influenced by the high water retention and compressibility of organic soils, as well as their sensitivity to freezing and thawing. Alberta's strict environmental regulations demand the reuse of excavated soil for backfill, and the long winter season creates challenging conditions for civil engineering projects. In this study, a laboratory compaction test was conducted to evaluate the low-temperature compaction characteristics of organic soils with varying organic content. The results indicate that the optimum moisture content increases as the organic content increases, and the maximum dry unit weight decreases by up to 21.9%. In addition, under temperature conditions below -4℃, no optimum moisture content was observed, and the dry unit weight decreased as the moisture content increased.

• Journal of The Korean Association For Science Education
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• v.26 no.2
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• pp.200-211
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• 2006

The purpose of this study was to analyze Korean middle school student achievement in environmental science based on the TIMSS 2003 (Trends in International Mathematics and Science Study), a student comparison of 46 participating nations. Korea ranked the fourth with a mean score of 554 in environmental science. However, all 3 environment science topics assessed in TIMSS are not included in the Korean science curriculum through 8th grade, even though they are included in most other participating nations' curricula. The average percent correct of items was analyzed according to the main topic, the item type and the cognitive domain. Items that showed differences between the average percent correct of Korea and the international average as well as differences between the average percent correct of boys and girls were further analyzed. Results revealed that Korean students performed better than the international average, especially in 'use and conservation of natural resources', multiple-choice items, and items requiring 'factual knowledge'. Also, male students demonstrated significantly higher achievement than female students. On the other hand, Korean students showed relatively lower achievement in constructed-response items, items that contained content they had not learned in science lessons and items requiring descriptions of the uses and effect of science and technology. Moreover, Korean student lacked understanding about acid rain, global warming, and ozone layer destruction. Korean female students showed relatively lower environmental conceptions and lower performance on items requiring data analysis than Korean male students. On the basis of these results, this study suggested that topics of environmental science be included in the science curriculum and taught in the science classroom to help middle school students more fully comprehend environmental issues.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.302-314
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• 2024

Purpose: This study proposes a fall detection model based on a top-down deep learning pose estimation model to automatically determine falls of multiple workers in an underground utility tunnel, and evaluates the performance of the proposed model. Method: A model is presented that combines fall discrimination rules with the results inferred from YOLOv8-pose, one of the top-down pose estimation models, and metrics of the model are evaluated for images of standing and falling two or fewer workers in the tunnel. The same process is also conducted for a bottom-up type of pose estimation model (OpenPose). In addition, due to dependency of the falling interference of the models on worker detection by YOLOv8-pose and OpenPose, metrics of the models for fall was not only investigated, but also for person. Result: For worker detection, both YOLOv8-pose and OpenPose models have F1-score of 0.88 and 0.71, respectively. However, for fall detection, the metrics were deteriorated to 0.71 and 0.23. The results of the OpenPose based model were due to partially detected worker body, and detected workers but fail to part them correctly. Conclusion: Use of top-down type of pose estimation models would be more effective way to detect fall of workers in the underground utility tunnel, with respect to joint recognition and partition between workers.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.117-137
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• 2024

ESG has become a necessity for all companies, and major Korean banks are actively practicing ESG management. Banks are playing a role in providing ESG finance as intermediaries in the supply of funds. Recently, they have launched ESG digital banking products that offer preferential interest rates for eco-friendly activities in combination with digital technologies. However, indiscriminate provision of preferential interest rates can adversely affect profitability of banks, and they may face the problem of 'Greenwashing' if they do not contribute to improving environmental awareness. Therefore, this study selected ESG digital savings products linked to electricity savings as the subject of the study, and empirically analyzed consumers' environmental awareness and savings behavior through actual data of consumers (N=2,478). The main findings of this study are as follows First, the analysis of the consumer status of ESG digital banking products shows that the 30-50s are the main consumer base, and the MZ generation shows relatively high performance in achieving preferential interest rates through electricity saving practices. Second, consumers' environmental awareness has a significant impact on achieving the goals of ESG banking products. ESG banking products can contribute to environmental awareness while fulfilling the basic function of saving. Third, environmental awareness did not drive consumers' savings contribution behavior, suggesting the need for continued consumer engagement. Based on environmental awareness and the theory of saving behavior, this study provides a theoretical explanation in ESG financial products. The results suggest that the appropriateness of the preferential interest rate design of ESG financial products is important.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.21-30
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• 2024

In this paper, we propose a method to build a sample dataset of the features of eight sensor-only facilities built as infrastructure for autonomous cooperative driving. The feature extracted from point cloud data acquired by LiDAR and build them into the sample dataset for recognizing the facilities. In order to build the dataset, eight sensor-only facilities with high-brightness reflector sheets and a sensor acquisition system were developed. To extract the features of facilities located within a certain measurement distance from the acquired point cloud data, a cylindrical projection method was applied to the extracted points after applying DBSCAN method for points and then a modified OTSU method for reflected intensity. Coordinates of 3D points, projected coordinates of 2D, and reflection intensity were set as the features of the facility, and the dataset was built along with labels. In order to check the effectiveness of the facility dataset built based on LiDAR data, a common CNN model was selected and tested after training, showing an accuracy of about 90% or more, confirming the possibility of facility recognition. Through continuous experiments, we will improve the feature extraction algorithm for building the proposed dataset and improve its performance, and develop a dedicated model for recognizing sensor-only facilities for autonomous cooperative driving.

• Journal of the Korean Society of Radiology
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• v.18 no.1
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• pp.37-44
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• 2024

Even though MR can reveal excellent soft-tissue contrast and functional information, CT is also required for electron density information for accurate dose calculation in Radiotherapy. For the fusion of MRI and CT images in RT treatment planning workflow, patients are normally scanned on both MRI and CT imaging modalities. Recently deep-learning-based generations of CT images from MR images became possible owing to machine learning technology. This eliminated CT scanning work. This study implemented a CycleGan deep-learning-based CT image generation from MR images. Three CT generators whose learning is based on T1- , T2- , or T1-&T2-weighted MR images were created, respectively. We found that the T1-weighted MR image-based generator can generate better than other CT generators when T1-weighted MR images are input. In contrast, a T2-weighted MR image-based generator can generate better than other CT generators do when T2-weighted MR images are input. The results say that the CT generator from MR images is just outside the practical clinics and the specific weight MR image-based machine-learning generator can generate better CT images than other sequence MR image-based generators do.

• The Journal of the Acoustical Society of Korea
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• v.26 no.6
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• pp.250-258
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• 2007

Current speech recognition technology s achieved high performance with the development of hardware devices, however it is insufficient for some applications where high reliability is required, such as voice control of powered wheelchairs for disabled persons. For the system which aims to operate powered wheelchairs safely by voice in real environment, we need to consider that non-voice commands such as user s coughing, breathing, and spark-like mechanical noise should be rejected and the wheelchair system need to recognize the speech commands affected by disability, which contains specific pronunciation speed and frequency. In this paper, we propose non-voice rejection method to perform voice/non-voice classification using both YIN based fundamental frequency(F0) extraction and reliability in preprocessing. We adopted a multi-template dictionary and acoustic modeling based speaker adaptation to cope with the pronunciation variation of inarticulately uttered speech. From the recognition tests conducted with the data collected in real environment, proposed YIN based fundamental extraction showed recall-precision rate of 95.1% better than that of 62% by cepstrum based method. Recognition test by a new system applied with multi-template dictionary and MAP adaptation also showed much higher accuracy of 99.5% than that of 78.6% by baseline system.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.437-447
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• 2023

By actively adopting technologies from the Fourth Industrial Revolution, the port industry is trending toward new types of ports, such as automated and smart ports. However, behind the development of these ports, there is an increasing risk of cyber security incidents and threats within ports and container terminals, including information leakage through cargo handling equipment and ransomware attacks leading to disruptions in terminal operations. Despite the necessity of research to enhance cyber security within ports, there is a lack of such studies in the domestic context. This study focuses on Busan Port, a representative port in South Korea that actively incorporates technology from the Fourth Industrial Revolution, in order to discover variables for improving cyber security in container terminals. The research results categorized factors for enhancing cyber security in Busan Port's container terminals into network construction and policy support, standardization of education and personnel training, and legal and regulatory factors. Subsequently, multiple regression analysis was conducted based on these factors, leading to the identification of detailed factors for securing and enhancing safety, reliability, performance, and satisfaction in Busan Port's container terminals. The significance of this study lies in providing direction for enhancing cyber security in Busan Port's container terminals and addressing the increasing incidents of cyber security attacks within ports and container terminals.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.147-157
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• 2023

This paper investigates the financial factors affecting angel investors' investment decisions for 818 firms from 2009 to 2018 in the Korean venture investment market. We construct a quasi-experimental design using propensity scoring matching and compare the investment determinants between investment firms and matching firms. The main empirical findings are as follows. First, we find that angel investors are more likely to choose firms based on a firm's growth such as profit and assets rather than profitability or financial stability. In addition, we identify that they prefer the firm not only higher intangible assets but also higher R&D expenditures. Second, we find that angel investors consider both growth and activity ratios in the firms for over three years and have entered the mid-stage of startups. Overall, we confirm that the investment decision of angel investors mainly focuses on the venture startups' growth trend or future growth potential rather than the realized profitability or financial stability. We also infer that the possibility of performance creation is an important investment factor along with growth for the mid-stage startup.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.541-554
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• 2023

The utilization of underground spaces in relation to tunnels and energy/waste storage is on the rise. To ensure the stability of underground spaces, it is crucial to reinforce rock fractures and discontinuities. Discontinuities, such as joints, can weaken the strength of the rock and lead to groundwater inflow into underground spaces. In order to enhance the strength and stability of the area around these discontinuities, rock grouting techniques are employed. However, during rock grouting, it is impossible to visually confirm whether the grouting material is being smoothly injected as intended. Without proper injection, the expected increases in strength, durability, and degree of consolidation may not be achieved. Therefore, it is necessary to predict in advance whether the grouting material is being injected as designed. In this study, we aimed to assess the injection performance based on injection variables such as the water/cement mixture ratio, injection pressure, and injection flow using UDEC (Universal Distinct Element Code) numerical program. Additionally, numerical results were validated by the lab experiment. The results of this study are expected to help optimize variables such as injection material properties, injection time, and pump pressure in the grouting design in the field.