• Tunnel and Underground Space
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• v.33 no.6
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• pp.534-546
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• 2023

If the disc cutter is excessively worn or damaged, it becomes incapable of rotating and efficiently cutting rockmass. Therefore, it is important to appropriately manage the replacement cycle of the disc cutter based on its degree of wear. In general, the replacement cycle is determined based on the results of manual inspection. However, the manual measurements has issues related to worker safety and may lead to inaccurate measurement results. For these reasons, some foreign countries are developing the real-time measurement system of disc cutter wear by using different sensors. The ultrasonic sensors, eddy current sensors, magnetic sensors, and others are utilized for measuring the wear amount of disc cutters. In this study, the applicability of eddy current sensors for real-time measurement of wear amount in TBM disc cutters was evaluated. The distance measurement accuracy of the eddy current sensor was assessed through laboratory tests. In particular, the accuracy of eddy-current sensor was evaluated in various environmental conditions within the cutterhead chamber. In addition, the measurement accuracy of the eddy current sensor was validated using a 17-inch disc cutter.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• Journal of the Korean Society of Radiology
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• v.82 no.5
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• pp.1124-1139
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• 2021

The objective assessment of atrophy and the measurement of brain volume is important in the early diagnosis of dementia and neurodegenerative diseases. Recently, several MR-based volumetry software have been developed. For their clinical application, several issues arise, including the standardization of image acquisition and their validation of software. Additionally, it is important to highlight the diagnostic performance of the volumetry software based on expert opinions. We instituted a task force within the Korean Society of Neuroradiology to develop guidelines for the clinical use of MR-based brain volumetry software. In this review, we introduce the commercially available software and compare their diagnostic performances. We suggest the need for a standard protocol for image acquisition, the validation of the software, and evaluations of the limitations of the software related to clinical practice. We present recommendations for the clinical applications of commercially available software for volumetry based on the expert opinions of the Korean Society of Neuroradiology.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.39-50
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• 2024

Color is an essential visual element that has a significant impact on the formation of a city's image and people's perceptions. Quantitative analysis of color in urban environments is a complex process that has been difficult to implement in the past. However, with recent rapid advances in Machine Learning, it has become possible to analyze city colors using photos shared by tourists. This study selected Dali City, a popular tourist destination in China, as a case study. Photos of Dali City shared by tourists were collected, and a method to measure large-scale city colors was explored by combining machine learning techniques. Specifically, the DeepLabv3+ model was first applied to perform a semantic segmentation of tourist sharing photos based on the ADE20k dataset, thereby separating artificial elements in the photos. Next, the K-means clustering algorithm was used to extract colors from the artificial elements in Dali City, and an adjacency matrix was constructed to analyze the correlations between the dominant colors. The research results indicate that the main color of the artificial elements in Dali City has the highest percentage of orange-grey. Furthermore, gray tones are often used in combination with other colors. The results indicated that local ethnic and Buddhist cultures influence the color characteristics of artificial elements in Dali City. This research provides a new method of color analysis, and the results not only help Dali City to shape an urban color image that meets the expectations of tourists but also provide reference materials for future urban color planning in Dali City.

• The Journal of the Acoustical Society of Korea
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• v.25 no.5
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• pp.213-221
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• 2006

Phone segmentation of speech waveform is especially important for concatenative text to speech synthesis which uses segmented corpora for the construction of synthetic units. because the quality of synthesized speech depends critically on the accuracy of the segmentation. In the beginning. the phone segmentation was manually performed. but it brings the huge effort and the large time delay. HMM-based approaches adopted from automatic speech recognition are most widely used for automatic segmentation in speech synthesis, providing a consistent and accurate phone labeling scheme. Even the HMM-based approach has been successful, it may locate a phone boundary at a different position than expected. In this paper. we categorized adjacent phoneme pairs and analyzed the mismatches between hand-labeled transcriptions and HMM-based labels. Then we described the dominant error patterns that must be improved for the speech synthesis. For the experiment. hand labeled standard Korean speech DB from ETRI was used as a reference DB. Time difference larger than 20ms between hand-labeled phoneme boundary and auto-aligned boundary is treated as an automatic segmentation error. Our experimental results from female speaker revealed that plosive-vowel, affricate-vowel and vowel-liquid pairs showed high accuracies, 99%, 99.5% and 99% respectively. But stop-nasal, stop-liquid and nasal-liquid pairs showed very low accuracies, 45%, 50% and 55%. And these from male speaker revealed similar tendency.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.585-590
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• 2024

In this study, rail surface defects are increasing due to the aging of urban railway rails, but in the detailed guidelines for track performance evaluation established by the country, rail surface damage is inspected with the naked eye of engineers and simple measuring tools. With the recent enactment of the Track Diagnosis Act, a large budget has been invested and the volume of rail diagnosis is rapidly increasing, but it is difficult to secure the reliability of diagnosis results using labor-intensive visual inspection techniques. It is very important to discover defects in the rail surface through periodic track tours and visual inspection. However, evaluating the severity of defects on the rail surface based on the subjective judgment of the inspector has significant limitations in predicting damage inside the rail. In this study, the rail internal crack characteristics due to rail surface damage were studied. In field measurements, rail surface damage locations were selected, samples of various damage types were collected, and the rail surface damage status was evaluated. In indoor testing, we intend to analyze the correlation between rail surface defects and internal defects using a electron scanning microscope (SEM). To determine the crack growth rate of urban railway rails currently in use, the Gaussian probability density function was applied and analyzed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.207-216
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• 2024

As big data was built due to the 4th Industrial Revolution, personalized services increased rapidly. As a result, the amount of personal information collected from online services has increased, and concerns about users' personal information leakage and privacy infringement have increased. Online service providers provide privacy policies to address concerns about privacy infringement of users, but privacy policies are often misused due to the long and complex problem that it is difficult for users to directly identify risk items. Therefore, there is a need for a method that can automatically check whether the privacy policy is safe. However, the safety verification technique of the conventional blacklist and machine learning-based privacy policy has a problem that is difficult to expand or has low accessibility. In this paper, to solve the problem, we propose a safety verification technique for the privacy policy using the GPT-3.5 API, which is a generative artificial intelligence. Classification work can be performed evenin a new environment, and it shows the possibility that the general public without expertise can easily inspect the privacy policy. In the experiment, how accurately the blacklist-based privacy policy and the GPT-based privacy policy classify safe and unsafe sentences and the time spent on classification was measured. According to the experimental results, the proposed technique showed 10.34% higher accuracy on average than the conventional blacklist-based sentence safety verification technique.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.243-250
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• 2024

Biomimetic robots, which emulate characteristics of biological entities such as birds or insects, have the potential to offer a tactical advantage in surveillance and reconnaissance in future battlefields. To effectively utilize these robots, it is essential to develop technologies that emulate the wing flapping of birds or the movements of cockroaches. However, this effort is complicated by the challenges associated with securing the necessary hardware and the complexities involved in software development and validation processes. In this paper, we presents the design and implementation of a multi-HILS based biomimic robot software validation testbed using modeling and simulation (M&S). By employing this testbed, developers can overcome the absence of hardware, simulate future battlefield scenarios, and conduct software development and testing. However, the multi-HILS based testbed may experience inter-device communication delays as the number of test robots increases, significantly affecting the reliability of simulation results. To address this issue, we propose the data distribution service priority (DDSP), a priority-based middleware. DDSP demonstrates an average delay reduction of 1.95 ms compared to the existing DDS, ensuring the required data transmission quality for the testbed.

• Journal of agricultural medicine and community health
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• v.37 no.1
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• pp.1-11
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• 2012

Objectives: To survey the awareness of patient to scrub typhus to provide data for education and communication concerning scrub typhus. Methods: Patients with scrub typhus (case group, n=299) and people without scrub typhus within the previous 2 years (control group, n=598) were matched for age (within 5 years), gender, and occupation (farmer or non-farmer). The participants were recruited from 15 study areas between October and December 2006. Results: The awareness rate of scrub typhus was 75.1%, and was significantly higher than in the case group (79.4% vs. 66.6%, respectively; p<0.01). The major routes of awareness were from 'past history of scrub typhus in family members or neighbors' (54.9%), 'television' (28.3%), and their past history of scrub typhus (5.5%). The average correct rate of scrub typhus was 48.4%, and the correct response rate of cases was significantly higher than controls (p<0.01). Especially, the correct rate of etiology, incubation period, route of transmission, and acquired immunity was <40%. Through conditional logistic regression test, the factor significantly associated with awareness in case group was age (odds ratio [OR], 0.96; 95% confidence interval [CI], 0.94-0.98). And the factors associated with awareness in control group were female (OR, 1.56; 95% CI, 1.03-2.36) age (OR, 0.98; 95% CI, 0.96-0.99), family history of scrub typhus (OR, 10.18; 95% CI, 1.37-75.99), history of receiving prevention education (OR, 8.47; 95% CI, 1.14-63.00). Conclusions: The rate of awareness was relatively low in study population. Thus, effective working guidelines and educational program to prevent scrub typhus must be developed, and publicity activities about the prevention of scrub typhus are needed for high-risk groups.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.4
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• pp.303-308
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• 2016

This study was carried out to determine the effects of application levels of fertilizer and sowing methods on yields and nutritive values of Italian ryegrass (IRG) in early spring. Five fertilizer levels were used: Treatment 1, 100-80-80 kg/ha; Treatment 2, 120-100-100 kg/ha; Treatment 3, 140-120-120 kg/ha; Treatment 4, 160-140-140 kg/ha; Treatment 5, 140-120-120 kg/ha of $N-P_2O_5-K_2O$ with silicate fertilizer 200 kg/ha. Dry matter (DM) yield was 8,330 kg/ha in Treatment 5, 7,686 kg/ha in Treatment 4, and 7,347 kg/ha in Treatment 3. There was no significant difference in total digestible nutrients (TDN) content. The content of crude protein was the highest in Treatment 5. Dry matter ratio was the lowest in Treatment 5. In Treatment 3, DM yield was 7,347 kg/ha, when total amounts of fertilizers were applied at one time. However, DM yield was 7,405 kg/ha, when 50% of pre-planting fertilizer and 50% of supplementary fertilizer were applied at different time. There was no significant difference between total application and split application of fertilizers. However, DM yield was 9,469 kg/ha in application treatment with 100 kg/ha of additional urea at three to four leaf stages of IRG. Regarding DM yield by sowing methods of IRG, the following order was found: drill seeding (8,176 kg/ha) > rotary-broadcast seeding-stamping (7,957 kg/ha) > rotary-broadcast seeding (7,810 kg/ha) > broadcast seeding (7,347 kg/ha) > broadcast seeding-rotary (7,034 kg/ha). DM yield (59.57%) was the lowest in broadcast seeding-rotary. Crude protein content was the highest with rotary work but the lowest with broadcast seeding.