• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.149-156
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• 2003

This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), an ultra-short baseline (USBL) acoustic navigation sensor and a doppler velocity log (DVL) accompanying a magnetic compass. The errors of inertial measurement units increase with time due to the bias errors of gyros and accelerometers. A navigational system model is derived to include the error model of the USBL acoustic navigation sensor and the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 25 in the order. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o.f. equations of motion of SAUV in a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass and a depth senor. The error of the estimated position still slowly drifts in horizontal plane about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.

• Journal of Preventive Medicine and Public Health
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• v.45 no.1
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• pp.14-20
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• 2012

Objectives: The aim of this study was to evaluate and quantify the risk of both individual and combined health behaviors on premature mortality in middle aged men in Korea. Methods: In total, 14 533 male subjects 40 to 59 years of age were recruited. At enrollment, subjects completed a baseline questionnaire, which included information about socio-demographic factors, past medical history, and life style. During the follow-up period from 1993 to 2008, we identified 990 all-cause premature deaths using national death certificates. A Cox proportional hazard regression model was used to estimate the hazard ratio (HR) of each health risk behavior, which included smoking, drinking, physical inactivity, and lack of sleep hours. Using the Cox model, each health behavior was assigned a risk score proportional to its regression coefficient value. Health risk scores were calculated for each patient and the HR of all-cause premature mortality was calculated according to risk score. Results: Current smoking and drinking, high body mass index, less sleep hours, and less education were significantly associated with all-cause premature mortality, while regular exercise was associated with a reduced risk. When combined by health risk score, there was a strong trend for increased mortality risk with increased score (p-trend < 0.01). When compared with the 1-9 score group, HRs of the 10-19 and 20-28 score groups were 2.58 (95% confidence intervals [CIs], 2.19 to 3.03) and 7.09 (95% CIs, 5.21 to 9.66), respectively. Conclusions: Modifiable risk factors, such as smoking, drinking, and regular exercise, have considerable impact on premature mortality and should be assessed in combination.

• Experimental and Molecular Medicine
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• v.50 no.11
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• pp.9.1-9.10
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• 2018

Although the positive effects of recombinant fibroblast growth factor-2 (rFGF-2) in chronic obstructive pulmonary disease (COPD) have been implicated in previous studies, knowledge of its role in COPD remains limited. The mechanism of FGF2 in a COPD mouse model and the therapeutic potential of rFGF-2 were investigated in COPD. The mechanism and protective effects of rFGF-2 were evaluated in cigarette smoke-exposed or elastase-induced COPD animal models. Inflammation was assessed in alveolar cells and lung tissues from mice. FGF-2 was decreased in the lungs of cigarette smoke-exposed mice. Intranasal use of rFGF-2 significantly reduced macrophage-dominant inflammation and alveolar destruction in the lungs. In the elastase-induced emphysema model, rFGF-2 improved regeneration of the lungs. In humans, plasma FGF-2 was decreased significantly in COPD compared with normal subjects (10 subjects, P = 0.037). The safety and efficacy of inhaled rFGF-2 use was examined in COPD patients, along with changes in respiratory symptoms and pulmonary function. A 2-week treatment with inhaled rFGF-2 in COPD (n = 6) resulted in significantly improved respiratory symptoms compared with baseline levels (P < 0.05); however, the results were not significant compared with the placebo. The pulmonary function test results of COPD improved numerically compared with those in the placebo, but the difference was not statistically significant. No serious adverse events occurred during treatment with inhaled rFGF-2. The loss of FGF-2 production is an important mechanism in the development of COPD. Inhaling rFGF-2 may be a new therapeutic option for patients with COPD because rFGF-2 decreases inflammation in lungs exposed to cigarette smoke.

• Journal of the Korean Society of Propulsion Engineers
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• v.21 no.1
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• pp.51-62
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• 2017

A design optimization method is applied for the flow path design of RBCC engine, an important factor for the determining the propulsion performance operating at air-breathing mode. A design optimization was carried out to maximize the specific impulse of the RBCC engine by using a genetic algorithm based on the Kriging model. Results are analyzed using ANOVA and SOM. Design conditions of ramjet and scramjet mode are selected as Mach number 4 at 20 km altitude and Mach number 7 at 30 km, respectively. The optimized design presents that the specific impulse is increased by 7% and 10% on each condition than the baseline design.

• Smart Structures and Systems
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• v.31 no.4
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• Analyses & Alternatives
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• v.3 no.2
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• pp.59-85
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• 2019

The Hong Kong's Anti-Ordinance Amendment Movement is the most serious radical social movement since the 1997 return, which has served as the promotion of the 2014 Occupy Central Movement and broken through the violence baseline. The movement came from a criminal case committed in Taiwan,which gave a good reason and motivation for the HK government to amend the Fugitive Offenders Ordinance. The HK government has responded to the protests by strictly limiting the legal scope and transfer procedure, even giving up the legislative motion. But the protests still say no and develop into the constantly violent activities. Many of the protests have committed the crimes in HK laws,part of whom have been arrested,prosecuted and under judicially judged. It is necessary for the offenders to be punished to protect the authority of rule of law in HK. Two different paths for HK have fought against each other since the 1997 return: one is the "democratic-welfare" path taken by the Pan-Democratic Camp, the other is the "Legal-development" path taken by the Pan-Establishment Camp. The second path shares some nuclear characteristics of the so-called The China Model mainly shaped from the 40-years Reforms and Openness. However, the HK people can't understand the China Model very well and show great fear and distrust on the judicial system of Mainland China. The foreign powers such as US and UK have illegally interfered the HK issues which are deemed to be the domestic affairs of China. The so-called Sino-UK Joint Declaration can't serve as the legal basis for the interference. Taiwan, as a part of China, also plays a negative role in this movement for its electoral and political interest. Up to now, the movement has gone down and the HK government has the legal capacity to solve the problems under the supports from the central government and the HK people. The HK people love its rule of law and order under the constitutional framework of One Country Two System. After the movement,One Country Two Systems will be go on, and the integrated development under the policies of the central government will be the main stream. However, the relevant problems exposed by this movement muse be checked and solved legally and strictly,especially concerning the social inequality and youth development.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.566-571
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• 2009

This paper proposes noise-robust fast speaker adaptation method based on the eigenvoice framework in various noisy environments. The proposed method is focused on de-noising and environment clustering. Since the de-noised adaptation DB still has residual noise in itself, environment clustering divides the noisy adaptation data into similar environments by a clustering method using the cepstral mean of non-speech segments as a feature vector. Then each adaptation data in the same cluster is used to build an environment-clustered speaker adapted (SA) model. After selecting multiple environmentally clustered SA models which are similar to test environment, the speaker adaptation based on an appropriate linear combination of clustered SA models is conducted. According to our experiments, we observe that the proposed method provides error rate reduction of $40{\sim}59%$ over baseline with speaker independent model.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.646-652
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• 2009

In this paper, welding pitch optimization technique of vehicle subframe is presented considering the fatigue life of spot welding nuggets. Fatigue life of spot welding nuggets is estimated by using the frequency-domain fatigue analysis technique. The input data, which are used in the fatigue analysis, are obtained by performing the dynamic analysis of vehicle model passing through the Belgian road profile and also the modal frequency response analysis of finite element model of vehicle subframe. According to the fatigue life result obtained from the frequency-domain fatigue analysis, the design points to optimize the weld pitch distance are determined. For obtaining the welding pitch combination to maximize the fatigue life of the spot welding nuggets, 4-factor, 3-level orthogonal array experimental design is used. This study shows that the optimized subframe improves the fatigue life of welding nugget with minimum fatigue life about 65.8 % as compared with the baseline design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.980-997
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• 2024

To improve the brightness of images and reveal hidden information in dark areas is the main objective of low-light image enhancement (LLIE). LLIE methods based on deep learning show good performance. However, there are some limitations to these methods, such as the complex network model requires highly configurable environments, and deficient enhancement of edge details leads to blurring of the target content. Single-scale feature extraction results in the insufficient recovery of the hidden content of the enhanced images. This paper proposed an edge detection-based multi-scale feature enhancement network for LLIE (EDMFEN). To reduce the loss of edge details in the enhanced images, an edge extraction module consisting of a Sobel operator is introduced to obtain edge information by computing gradients of images. In addition, a multi-scale feature enhancement module (MSFEM) consisting of multi-scale feature extraction block (MSFEB) and a spatial attention mechanism is proposed to thoroughly recover the hidden content of the enhanced images and obtain richer features. Since the fused features may contain some useless information, the MSFEB is introduced so as to obtain the image features with different perceptual fields. To use the multi-scale features more effectively, a spatial attention mechanism module is used to retain the key features and improve the model performance after fusing multi-scale features. Experimental results on two datasets and five baseline datasets show that EDMFEN has good performance when compared with the stateof-the-art LLIE methods.

• Land and Housing Review
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• v.15 no.2
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• pp.89-106
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• 2024

Apartments constitute 64% of the housing type composition, representing the highest proportion among housing types. This proportion has been increasing annually. Given this trend, apartment prices are likely to have a significant impact on the national economy and people's livelihoods. This study examines the impact of the recent development of Seodaegu Station on the surrounding apartment market, with a specific focus on the effects of the educational environment. To this end, we conduct empirical analysis employing a hedonic price model and spatial autocorrelation analysis, based on actual transaction price data from the Ministry of Land, Infrastructure, and Transport. The study revealed three key findings: first, the development of Seodaegu Station positively impacted apartment prices. Second, this positive effect increases with the proximity to Seodaegu Station. Third, the enhancement of the educational environment nearby the Seodaegu Station development also positively influenced apartment prices. This study aims to serve as baseline research output for the public management of future metropolitan transportation facility development projects and for predicting apartment price trends.