• 한국전산유체공학회:학술대회논문집
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• 2003.08a
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• pp.11-17
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• 2003

The new multi-dimensional higher order interpolation scheme called MHIS is developed. Firstly, multi-dimensional TVD condition is derived based on one-dimensional TVD condition. Using multi-dimensional TVD condition, 2nd, 3rd and 5th order MHIS are presented. By help of multi-dimensional TVD condition, it is possible to captured a discontinuity monotonically even in a multi-dimensional flow. It is verified through several test cases that the accuracy and the robustness of MHIS are enhanced in regions of shock discontinuities as well as boundary-layers.

• Bulletin of the Korean Chemical Society
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• v.10 no.2
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• pp.172-177
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• 1989

Stereoselective solvolyses of optically active activated esters in the aggregate system of optically active polymeric surfactants containing imidazole and benzene moieties were performed. The catalyst polymers employed were copolymers of N-methacryloyl-L-histidine methyl ester (MHis) with N,N-dimethyl-N-hexadecyl-N-[10-(p-methacryloylo xyphenoxycarbonyl)-decyl]ammonium bromide(DEMAB). In the solvolyses of N-carbobenzoxy-D- and L-phenylalanine p-nitrophenyl esters (D-NBP and L-NBP) by polymeric catalysts, copoly(MHis-DEMAB) exhibited not only increased catalytic activity but also enhanced enantioselectivity as the mole ${\%}$ of surfactant monomers in the copolymers increased. The polymeric catalysts showed noticeable enantioselective solvolyses toward D- and L-NBP of the substrates employed. As the reaction temperature was lowered for the solvolyses of D- and L-NBP with the catalyst polymer containing 3.5 mole ${\%}$ of MHis, the increased reaction rate and enhanced enantioselectivity were observed. The coaggregative systems of the polymer and monomeric surfactants were also investigated. In the case of coaggregate system consisted of 70 mole ${\%}$ of cetyldimethylethylammonium bromide with polymeric catalyst showed maximum enantioselective catalysis, viz., $k_{cat}(L)/k_{cat}(D)$ = 2.85. The catalyst polymers in the sonicated solvolytic solutions were confirmed to form large aggregate structure by electron microscopic observation.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.217-228
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• 2023

Video instance segmentation is an intelligent visual task with high complexity because it not only requires object instance segmentation for each image frame constituting a video, but also requires accurate tracking of instances throughout the frame sequence of the video. In special, human instance segmentation in drama videos has an unique characteristic that requires accurate tracking of several main characters interacting in various places and times. Also, it is also characterized by a kind of the class imbalance problem because there is a significant difference between the frequency of main characters and that of supporting or auxiliary characters in drama videos. In this paper, we introduce a new human instance datatset called MHIS, which is built upon drama videos, Miseang, and then propose a novel video data augmentation method, CDVA, in order to overcome the data imbalance problem between character classes. Different from the previous video data augmentation methods, the proposed CDVA generates more realistic augmented videos by deciding the optimal location within the background clip for a target human instance to be inserted with taking rich spatio-temporal context embedded in videos into account. Therefore, the proposed augmentation method, CDVA, can improve the performance of a deep neural network model for video instance segmentation. Conducting both quantitative and qualitative experiments using the MHIS dataset, we prove the usefulness and effectiveness of the proposed video data augmentation method.

• Journal of the Health Care and Life Science
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• v.10 no.1
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• pp.61-68
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• 2022

Korea's suicide rate is 23.0 people per 100,000 OECD standard population (as of 2017), the highest among OECD member countries, 2.1 times higher than the OECD average of 11.2. The suicide rate in Gangwon-do is the fourth highest in the country and the number of suicides is 507, with a suicide rate of 26.1 per 100,000 people. As basic data for reducing the suicide rate in Gangwon-do, the National Statistical Office, National Health Statistics, Community Health Survey, Health Insurance Corporation DB, Mental Health Case Management System (MHIS), and previous studies were analyzed in relation to suicide. Based on this, it is intended to provide basic data for reducing the suicide rate in Gangwon-do and to provide basic data for the design and use of an effective social intervention model.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.739-748
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• 2014

In this paper, we propose pyramid appearance and global structure action descriptors on both RGB and depth motion history images and a model-free method for human action recognition. In proposed algorithm, we firstly construct motion history image for both RGB and depth channels, at the same time, depth information is employed to filter RGB information, after that, different action descriptors are extracted from depth and RGB MHIs to represent these actions, and then multimodality information collaborative representation and recognition model, in which multi-modality information are put into object function naturally, and information fusion and action recognition also be done together, is proposed to classify human actions. To demonstrate the superiority of the proposed method, we evaluate it on MSR Action3D and DHA datasets, the well-known dataset for human action recognition. Large scale experiment shows our descriptors are robust, stable and efficient, when comparing with the-state-of-the-art algorithms, the performances of our descriptors are better than that of them, further, the performance of combined descriptors is much better than just using sole descriptor. What is more, our proposed model outperforms the state-of-the-art methods on both MSR Action3D and DHA datasets.

• Journal of Preventive Medicine and Public Health
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• v.35 no.4
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• pp.313-321
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• 2002

Objectives : To identify the risk factors of dementia among the elderly in a large city. Methods : A cross-sectional study was conducted in July 2001, with potential participants selected by stratified two stage cluster sampling of the elderly population of Keumgog dong, Busan. A total of 452 elderly people aged 65 years and over, underwent a two phase diagnostic procedure. Mini-mental State Examination-Korean (MMSE-K) and Samsung Dementia Questionnaire were used for the 1st stage, and the Clinical Dementia Rating Scale (CDR), the Bartel ADL, and IADL Index, the Korean Geriatric Depression Scale (KGDS), the Modified Hatchinski Ischemic Scale (MHIS), and other laboratory tests were used for the 2nd stage. Results : Of the 446 participants finally chosen, 45 were confirmed with dementia, and 363 as normal, with the rests not confirmed with dementia or as normal, were excluded from the analysis. According to the logistic regression analysis, the risk of dementia was significantly higher In: people aged 80 and above (OR=4.36, 95% CI=1.97-9.62), illiterate (OR=3.58, 95% CI=1.71-7.46), who had a history of strokes (OR=6.35, 95% CI=2.71-14.87), or who had 3 history of hyperlipidemia (OR=4.74, 95% CI=1.65-13.61), compared to their counterparts. Conclusions : These results suggest that efforts to prevent strokes and hyperlipidemia can significantly decrease the risk of dementia.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.518-528
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• 2014

In this paper, we propose a method to recognize the action direction of human by developing 4D space-time (4D-ST, [x,y,z,t]) features. For this, we propose 4D space-time interest points (4D-STIPs, [x,y,z,t]) which are extracted using 3D space (3D-S, [x,y,z]) volumes reconstructed from images of a finite number of different views. Since the proposed features are constructed using volumetric information, the features for arbitrary 2D space (2D-S, [x,y]) viewpoint can be generated by projecting the 3D-S volumes and 4D-STIPs on corresponding image planes in training step. We can recognize the directions of actors in the test video since our training sets, which are projections of 3D-S volumes and 4D-STIPs to various image planes, contain the direction information. The process for recognizing action direction is divided into two steps, firstly we recognize the class of actions and then recognize the action direction using direction information. For the action and direction of action recognition, with the projected 3D-S volumes and 4D-STIPs we construct motion history images (MHIs) and non-motion history images (NMHIs) which encode the moving and non-moving parts of an action respectively. For the action recognition, features are trained by support vector data description (SVDD) according to the action class and recognized by support vector domain density description (SVDDD). For the action direction recognition after recognizing actions, each actions are trained using SVDD according to the direction class and then recognized by SVDDD. In experiments, we train the models using 3D-S volumes from INRIA Xmas Motion Acquisition Sequences (IXMAS) dataset and recognize action direction by constructing a new SNU dataset made for evaluating the action direction recognition.