• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.115-120
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• 1998

In this paper, a depth-averaged two-dimensional transport model is introduced, and its error bound is presented as the results of sensitivity analysis. The results show that the calculated SS concentration is highly dependant on Manning roughness coefficient, mixing coefficient. fall velocity. and critical shear stress. On the other hand, water level and dispersion coefficient are proved to be less significant in the variation of SS concentration.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.11 no.2
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• pp.127-133
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• 1999

The MOSU model, a depth-averaged two-dimensional sediment transport model, is applied to simulate the bed level changes before and after dock construction in Daemyung site. The model is a semi¬coupled finite difference model that can be applied to a river, a reservoir, a lake, estuaries, or coastal regions, The model is able to simulate the transport of fine sand, silt, and clay. The model parameters are estimated by qualitative calibration. A prediction result of the numerical model shows that the bed level changes due to dock construction are little.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.31-37
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• 2018

Recently, the safety in vehicle also has become a hot topic as self-driving car is developed. In passive safety systems such as airbags and seat belts, the system is being changed into an active system that actively grasps the status and behavior of the passengers including the driver to mitigate the risk. Furthermore, it is expected that it will be possible to provide customized services such as seat deformation, air conditioning operation and D.W.D (Distraction While Driving) warning suitable for the passenger by using occupant information. In this paper, we propose robust vehicle occupant detection algorithm based on RGB-Depth-Thermal camera for obtaining the passengers information. The RGB-Depth-Thermal camera sensor system was configured to be robust against various environment. Also, one of the deep learning algorithms, OpenPose, was used for occupant detection. This algorithm is advantageous not only for RGB image but also for thermal image even using existing learned model. The algorithm will be supplemented to acquire high level information such as passenger attitude detection and face recognition mentioned in the introduction and provide customized active convenience service.

• Journal of the Korean GEO-environmental Society
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• v.6 no.3
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• pp.55-61
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• 2005

Dynamic compaction is a ground improvement technique which is particularly effective for loose granular soils. It has also been used successfully to the cohesive soils with high void ratio, and wastes and fills. For the design of dynamic compaction method, prediction of depth of improvement is very important. The depth of improvement is influenced not only by compaction energy but also by many parameters such as grid spacing, soil property, degree of saturation and site conditions. Based on the test results, the depth of improvement were evaluated with considering compaction energy, soil type and ground water level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1245-1252
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• 2013

As the usage of digital image contents increase, a security problem for the payed image data or the ones requiring confidentiality is raised. This paper propose a depth-map image contents encryption methodology to hide the depth information. This method is performed on the frequency coefficients in the Wavelet domain. This method, by selecting the level and threshold value for the wavelet transform, encryption at various strengths are possible. The experimental results showed that encrypting only 0.048% of the entire data was enough to hide the constants of the depth-map. The encryption algorithm expected to be used effectively on the researches on encryption and others for image processing.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.113-121
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• 2020

Human Pose Estimation (HPE) which localizes the human body joints becomes a high potential for high-level applications in the field of computer vision. The main challenges of HPE in real-time are occlusion, illumination change and diversity of pose appearance. The single RGB image is fed into HPE framework in order to reduce the computation cost by using depth-independent device such as a common camera, webcam, or phone cam. However, HPE based on the single RGB is not able to solve the above challenges due to inherent characteristics of color or texture. On the other hand, depth information which is fed into HPE framework and detects the human body parts in 3D coordinates can be usefully used to solve the above challenges. However, the depth information-based HPE requires the depth-dependent device which has space constraint and is cost consuming. Especially, the result of depth information-based HPE is less reliable due to the requirement of pose initialization and less stabilization of frame tracking. Therefore, this paper proposes a new method of HPE which is robust in estimating self-occlusion. There are many human parts which can be occluded by other body parts. However, this paper focuses only on head self-occlusion. The new method is a combination of the RGB image-based HPE framework and the depth information-based HPE framework. We evaluated the performance of the proposed method by COCO Object Keypoint Similarity library. By taking an advantage of RGB image-based HPE method and depth information-based HPE method, our HPE method based on RGB-D achieved the mAP of 0.903 and mAR of 0.938. It proved that our method outperforms the RGB-based HPE and the depth-based HPE.

• Atmosphere
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• v.24 no.1
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• pp.1-15
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• 2014

This study compared ensemble mean and probability forecasts of snow depth amount associated with winter storm over South Korea on 28 December 2012 at five operational forecast centers (CMA, ECMWF, NCEP, KMA, and UMKO). And cause of difference in predicted snow depth at each Ensemble Prediction System (EPS) was investigated by using THe Observing system Research and Predictability EXperiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data. This snowfall event occurred due to low pressure passing through South Sea of Korea. Amount of 6 hr accumulated snow depth was more than 10 cm over southern region of South Korea In this case study, ECMWF showed best prediction skill for the spatio-temporal distribution of snow depth. At first, ECMWF EPS has been consistently enhancing the indications present in ensemble mean snow depth forecasts from 7-day lead time. Secondly, its ensemble probabilities in excess of 2~5 cm/6 hour have been coincided with observation frequencies. And this snowfall case could be predicted from 5-day lead time by using 10-day lag ensemble mean 6 hr accumulated snow depth distribution. In addition, the cause of good performances at ECMWF EPS in predicted snow depth amounts was due to outstanding prediction ability of forming inversion layer with below $0^{\circ}C$ temperature in low level (below 850 hPa) according to $35^{\circ}N$ at 1-day lead time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3018-3038
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• 2020

In the stereoscopic or multiview display, the depth video illustrates visual distances between objects and camera. To promote the computational efficiency of depth video encoder, we exploit the intra prediction of depth videos under Versatile Video Coding (VVC) and observe a diverse distribution of intra prediction modes with different coding unit sizes. We propose a hybrid scheme to further boost fast depth video coding. In the first stage, we adaptively predict the HADamard (HAD) costs of intra prediction modes and initialize a candidate list according to the HAD costs. Then, the candidate list is further improved by considering the probability distribution of candidate modes with different CU sizes. Finally, early termination of CU splitting is performed at each CU depth level based on the Bayesian theorem. Our proposed method is incorporated into VVC intra prediction for fast coding of depth videos. Experiments with 7 standard sequences and 4 Quantization parameters (Qps) validate the efficiency of our method.

• Journal of Periodontal and Implant Science
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• v.45 no.6
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• pp.193-204
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• 2015

Purpose: With the increasing prevalence of orthodontic treatment in adults, clear aligner treatments are becoming more popular. The aim of this study was to evaluate the effect of orthodontic treatment on periodontal tissue and to compare orthodontic treatment with fixed appliances (FA) to clear aligner treatment (CAT) in periodontitis patients. Methods: A total of 35 patients who underwent orthodontic treatment in the Department of Periodontology were included in this study. After periodontal treatment with meticulous oral hygiene education, patients underwent treatment with FA or CAT, and this study analyzed patient outcomes depending on the treatment strategy. Clinical parameters were assessed at baseline and after orthodontic treatment, and the duration of treatment was compared between these two groups. Results: The overall plaque index, the gingival index, and probing depth improved after orthodontic treatment (P<0.01). The overall bone level also improved (P=0.045). However, the bone level changes in the FA and CAT groups were not significantly different. Significant differences were found between the FA and CAT groups in probing depth, change in probing depth, and duration of treatment (P<0.05). However, no significant differences were found between the FA and CAT groups regarding the plaque index, changes in the plaque index, the gingival index, changes in the gingival index, or changes in the alveolar bone level. The percentage of females in the CAT group (88%) was significantly greater than in the FA group (37%) (P<0.01). Conclusions: After orthodontic treatment, clinical parameters were improved in the FA and CAT groups with meticulous oral hygiene education and plaque control. Regarding plaque index and gingival index, no significant differences were found between these two groups. We suggest that combined periodontal and orthodontic treatment can improve patients' periodontal health irrespective of orthodontic techniques.

• Journal of Korean Society of Water and Wastewater
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• v.24 no.4
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• pp.377-386
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• 2010

To identify operating parameters of the up-flow filtering system, which is available to discharge filtering residue after the rain, developed for treatment of urban storm runoff, lab scale test was carried out. Removal efficiency of SS was 68.7%, 62.2%, and 58.6% at the area roading rate of 2.46m/h, 4.68m/h, and 10m/h, respectively, filtering device is desirable to operate at the lower than 4.68m/h of area roading rate to get higher level of 60% SS removal efficiency. The removal efficiency of SS was 57.1% ~ 68.7% at the raw water SS of 100mg/L ~ 600mg/L, and the SS in treated water was maintained at the constant level through the elapsed time. It is indicate that filtering device can guarantee a certain level of effluent water quality at various raw water quality. The removal efficiency of SS to the depth of filter media was 68.3%, 78.6% at the filter depth of 10 cm, 20cm respectively. The final treated water quality was showed 30.2mg/L of CODMn, 1.60mg/L of TN and 0.25mg/L of TP. The average removal efficiencies by filtering device developed in this research were recorded slightly lower levels than other research. The main reason of these results were the first, the filter depth of the media used in this test was shallow, the second, the kind of filter media in discharge port of residue. More research to kind of filter media, filter packing rate, select of media for residue discharge port should be go on to produce optimum operating condition. The result of this study would be valuable for the application of filtration device to control of urban storm water.