• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.2
• /
• pp.149-155
• /
• 2020

The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.3D
• /
• pp.423-429
• /
• 2008

The object of the present study is to estimate the potential effects of climate change and land use on soil erosion in the mid-east Korea. Simulated precipitation by CCCma climate model during 2030-2050 is used to model predicted soil erosion, and results are compared to observation. Simulation results allow relative comparison of the impact of climate change on soil erosion between current and predicted future condition. Expected land use changes driven by socio-economic change and plant growth driven by the increase of temperature and are taken into accounts in a comprehensive way. Mean precipitation increases by 17.7% (24.5%) for A2 (B2) during 2030-2050 compared to the observation period (1966-1998). In general predicted soil erosion for the B2 scenario is larger than that for the A2 scenario. Predicted soil erosion increases by 48%~90% under climate change except the scenario 1 and 2. Predicted soil erosion under the influence of temperature-induced fast plant growth, higher evapotranspiration rate, and fertilization effect (scenario 5 and 6) is approximately 25% less than that in the scenario 3 and 4. On the basis of the results it is said that precipitation and the corresponding soil erosion is likely to increase in the future and care needs to be taken in the study area.

• Asian-Australasian Journal of Animal Sciences
• /
• v.27 no.2
• /
• pp.155-160
• /
• 2014

The purpose of this study was to estimate genetic parameters of ultrasound measurements for longissimus dorsi muscle area (LMA), backfat thickness (BFT), and marbling score (MS) in Hanwoo cows (N = 3,062) at the ages between 18 and 42 months. Data were collected from 100 Hanwoo breeding farms in Gyeongbuk province, Korea, in 2007 and 2008. The cows were classified into four different age groups, i.e. 18 to 22 months (the first pregnancy period), 23 to 27 (the first parturition), 28 to 32 (the second pregnancy), and 33 to 42 (the second parturition), respectively. For each age group, a multi-trait animal model was used to estimate variance components and heritabilities of the three traits. The averages of LMA, BFT, and MS measurements across the cows of all age groups were 50.1 $cm^2$, 4.62 mm, and 3.04, respectively and heritability estimates were 0.09, 0.10, and 0.08 for the respective traits. However, when the data were analyzed in different age groups, heritability estimates of LMA and BFT were 0.24 and 0.47, respectively, for the cows of 18 to 22 months of age, and 0.21 for MS in the 28 to 32 months old cows. When the cows of all age groups were used, the estimates of genetic (phenotypic) correlations were 0.43 (0.35), -0.06 (0.34) and 0.21 (0.32) between LMA and BFT, LMA and MS, and BFT and MS, respectively. However, in the cow age group between 28 and 32 (18 and 22) months, the estimates of genetic (phenotypic) correlations were 0.05 (0.29), -0.15 (0.24) and 0.38 (0.24), for the respective pairs of traits. These results suggest that genetic, environmental, and phenotypic variations differ depending on cow age, such that care must be taken when ultrasound measurements are applied to selection of cows for meat quality.

• Journal of Korean Academy of Nursing
• /
• v.46 no.5
• /
• pp.653-662
• /
• 2016

Purpose: The purpose of this study was to identify the influences of oral health behaviors, depression, and stress on periodontal disease in pregnant women. Methods: The participants in this study were 129 pregnant women. Data were collected using questionnaires which included individual characteristics, oral health care behaviors, the Center for Epidemiological Studies-Depression scale (CES-D), a global measure of perceived stress, and pregnancy stress. A dentist measured periodontal probing depth and classified stages of periodontal disease according to the Community Periodontal Index (CPI). Data were analyzed using descriptive statistics, Pearson correlation, and multiple regression. Results: Periodontal disease had significant correlations with oral health care behaviors (r=-.56, p <.001), perceived stress (r=.44 p <.001), pregnancy stress (r=.37 p <.001), diet (r=-.33, p <.001) and depression (r=.18 p =.046). Factors influencing periodontal disease for these pregnant women were being in the 2nd (${\beta}=.27$, p <.001) or 3rd trimester (${\beta}=.45$, p <.001), having a pregnancy induced disease (${\beta}=.20$, p =.002), performing higher oral health behaviors (${\beta}=-.30$, p <.001), and having higher perceived stress (${\beta}=.17$, p =.028). The explanation power of this regression model was 61.6% (F=15.52, p <.001). Conclusion: The findings of this study indicated that periodic assessment of periodontal disease is essential for pregnant women who are in 2nd or 3rd trimester and have pregnancy induced diseases. Enhancing oral health care behaviors and reducing perceived stress are indicated as effective strategies to reduce periodontal disease in pregnant women.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.34 no.1
• /
• pp.1-8
• /
• 2014

This paper deals with monitoring and analysis of temperature measurement data in concrete pylon of long span cable bridges. During the construction of Geoga Bridge in Busan-Geoje Fixed Link Project, temperature sensors were installed in several sections of hollow box type concrete pylon and temperatures along the depth of the four sides of the section have been recorded along with ambient temperature. Effects of temperature distribution on the pylon are analysed using actual measured data and results are compared with the design guideline. It was found that the temperature load model for concrete girder can be applied to box type concrete pylon. Structural analysis of the pylon due to variation of temperature distribution during the construction is performed using 3D modelling and FE program and the maximum displacements of east-west and north-south side were calculated as 0.056m and 0.121m, respectively.

• Journal of Korean Academy of Nursing
• /
• v.40 no.3
• /
• pp.400-410
• /
• 2010

Purpose: The purpose of this study was to investigate the factors that influenced the health-related quality of life of young-old (65-74 yr) men, old-old (75-84 yr) men, and oldest-old (85 yr or above) men in vulnerable aged received home care from public health center. Methods: The participants for this study were 318 aged Korean men living in D city. The data was collected from August to October, 2009 using structured questionnaires. Chi-square, One way ANOVA, Duncan test, Pearson's Correlation Coefficient and multiple regression with the SPSS WIN 14.0 program were used to analyze the data. Results: There were statistically significant differences among young-old, old-old, and oldest-old men regarding the health-related quality of life, health promoting behavior, IADL (Instrumental Activities of Daily Living), rehabilitation, depression, and social support. The model including variables related to physical, psychological, and social aspects of life, explained variance of the health-related quality of life of aged men differently, such as 39.6% of young-old, 35.4% of old-old, and 47.0% of oldest-old. Finally, IADL and social support were predictors in explaining the level of health-related quality of life among vulnerable old men regardless of age. Conclusion: Based on the findings of the study, nursing interventions should be developed to improve health-related quality of life of vulnerable aged men according to age differences.

• Steel and Composite Structures
• /
• v.17 no.3
• /
• pp.215-236
• /
• 2014

The flexural behaviour of steel beams significantly affects the structural performance of the steel frame structures. In particular, the flexural overstrength (namely the ratio between the maximum bending moment and the plastic bending strength) that steel beams may experience is the key parameter affecting the seismic design of non-dissipative members in moment resisting frames. The aim of this study is to present a new formulation of flexural overstrength factor for steel beams by means of artificial neural network (NN). To achieve this purpose, a total of 141 experimental data samples from available literature have been collected in order to cover different cross-sectional typologies, namely I-H sections, rectangular and square hollow sections (RHS-SHS). Thus, two different data sets for I-H and RHS-SHS steel beams were formed. Nine critical prediction parameters were selected for the former while eight parameters were considered for the latter. These input variables used for the development of the prediction models are representative of the geometric properties of the sections, the mechanical properties of the material and the shear length of the steel beams. The prediction performance of the proposed NN model was also compared with the results obtained using an existing formulation derived from the gene expression modeling. The analysis of the results indicated that the proposed formulation provided a more reliable and accurate prediction capability of beam overstrength.

• Journal of the korean society of oceanography
• /
• v.37 no.1
• /
• pp.1-9
• /
• 2002

Cable voltage was measured simultaneously at Hamada, Japan and Pusan, Korea, using an inservice telephone cable from March to December 1990. The spectral and harmonic analyses of these data sets show that tidal signals are dominant, and that tidal constituents $M_2$ and $O_1$, which are not affected by solar geomagnetic variations, have almost the same amplitude and are of opposite phase to each other. comparing the voltage difference in 1990 with that measured using the now abandoned cable in 1998, there are dominant tidal signals at the same periods in both data sets. They have approximately the same amplitude and phase for $M_2andO_1$. The relationship between the observed voltage and the volume transport through the Korea Strait can be considered robust and stable over time. The conversion factor from voltage to transport is estimated to be $11.9{\times}10^6m^3S^{-1}volt^{-1}$ by comparing the amplitude of model-derived $M_2$ tidal transport with that of the voltage difference in 1998. This value changes to $8.6{\times}10^6m^3S^{-1}volt^{-1}$ when taking into consideration the horizontal electric current effect. This effect depends on the downstream length scale of the flow. To obtain a more reliable and stable conversion factor from voltage to transport, the voltage should be compared with observed sub-tidal transports, which may have long downstream length scales.

• Korean Journal of Remote Sensing
• /
• v.25 no.6
• /
• pp.547-557
• /
• 2009

LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

• Korean Journal of Acupuncture
• /
• v.36 no.2
• /
• pp.93-103
• /
• 2019

Objectives : The aim of this study is to review the current trends in experimental studies on the acupuncture moxibustion treatment for visceral hypersensitivity. Methods : PubMed was searched for experimental studies about visceral hypersensitivity and acupuncture/moxibustion. Data were extracted and tabulated from the selected articles about experimental method, intervention, result and mechanism. Results : Total 23 articles were reviewed. Chronic visceral hypersensitivity animal model was applied in 17 studies (74%). Visceral hypersensitivity was measured by abdominal withdrawal reflex scoring or/and abdominal electromyogram. Acupoints like ST25, ST36, ST37, BL25, LI11, BL32 and PC6 were treated by electroacupuncture or moxibustion. All articles reported that electroacupuncture or moxibustion treatment is significantly effective in reducing visceral hypersensitivity. Treatment mechanisms were studied, related to mast cell, serotonin (5-HT) and receptor (5-HT3R and 5-HT4R), substance P (SP), vasoactive intestinal polypeptide (VIP), c-fos positive cell, corticotropin-releasing hormone (CRH), purinergic 2X (P2X)2, P2X3, P2X4, P2X7, N-methyl-D-aspartate (NMDA) receptor (NR1 and NR2B), prokinectin (PK) 1 and PK2. Conclusions : Evidences on acupuncture/moxibustion treatment for visceral hypersensitivity in animal studies warrant more research on effective acupoins, electro-acupuncture methods and treatment durations.