• BMB Reports
• /
• v.54 no.10
• /
• pp.528-533
• /
• 2021

Osteoarthritis (OA) is a degenerative disorder that can result in the loss of articular cartilage. No effective treatment against OA is currently available. Thus, interest in natural health products to relieve OA symptoms is increasing. However, their qualities such as efficacy, toxicity, and mechanism are poorly understood. In this study, we determined the efficacy of avenanthramide (Avn)-C extracted from oats as a promising candidate to prevent OA progression and its mechanism of action to prevent the expression of matrix-metalloproteinases (MMPs) in OA pathogenesis. Interleukin-1 beta (IL-1β), a proinflammatory cytokine as a main causing factor of cartilage destruction, was used to induce OA-like condition of chondrocytes in vitro. Avn-C restrained IL-1β-mediated expression and activity of MMPs, such as MMP-3, -12, and -13 in mouse articular chondrocytes. Moreover, Avn-C alleviated cartilage destruction in experimental OA mouse model induced by destabilization of the medial meniscus (DMM) surgery. However, Avn-C did not affect the expression of inflammatory mediators (Ptgs2 and Nos) or anabolic factors (Col2a1, Aggrecan, and Sox9), although expression levels of these genes were upregulated or downregulated by IL-1β, respectively. The inhibition of MMP expression by Avn-C in articular chondrocytes was mediated by p38 kinase and c-Jun N-terminal kinase (JNK) signaling, but not by ERK or NF-κB. Interestingly, Avn-C added with SB203580 and SP600125 as specific inhibitors of p38 kinase and JNK, respectively, enhanced its inhibitory effect on the expression of MMPs in IL-1β treated chondrocytes. Taken together, these results suggest that Avn-C is an effective candidate to prevent OA progression and a natural health product to relieve OA pathogenesis.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.2
• /
• pp.771-788
• /
• 2020

Detection of abandoned objects for smart video surveillance should be robust and accurate in various situations with low computational costs. This paper presents a new algorithm for abandoned object detection based on the dual background model. Through the template registration of a candidate stationary object and presence authentication methods presented in this paper, we can handle some complex cases such as occlusions, illumination changes, long-term abandonment, and owner's re-attendance as well as general detection of abandoned objects. The proposed algorithm also analyzes video frames at specific intervals rather than consecutive video frames to reduce the computational overhead. For performance evaluation, we experimented with the algorithm using the well-known PETS2006, ABODA datasets, and our video dataset in a live streaming environment, which shows that the proposed algorithm works well in various situations.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.2
• /
• pp.104-110
• /
• 2016

Dense local image descriptors like SIFT are fruitful for capturing salient information about image, shown to be successful in various image-related tasks when formed in bag-of-words representation (i.e., histograms). In this paper we consider to utilize these dense local descriptors in the object tracking problem. A notable aspect of our tracker is that instead of adopting a point estimate for the target model, we account for uncertainty in data noise and model incompleteness by maintaining a distribution over plausible candidate models within the Bayesian framework. The target model is also updated adaptively by the principled Bayesian posterior inference, which admits a closed form within our Dirichlet prior modeling. With empirical evaluations on some video datasets, the proposed method is shown to yield more accurate tracking than baseline histogram-based trackers with the same types of features, often being superior to the appearance-based (visual) trackers.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.18 no.1
• /
• pp.31-36
• /
• 2010

Collecting all failures during life cycle of vehicle is not easy way because its life cycle is normally over 10 years. Warranty period can help gathering failures data because most customers try to repair its failures during warranty period even though small failures. This warranty data, which means failures during warranty period, can be a good resource to predict initial reliability and permanence reliability. However uncertainty regarding reliability prediction remains because this data is censored. University of Wuppertal and major auto supplier developed the reliability prognosis model considering censored data and this model introduce to predict reliability estimate further "failure candidate". This paper predicts reliability of telecommunications system in vehicle using the model and describes data structure for reliability prediction.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.2
• /
• pp.149-154
• /
• 2014

Detection performance of fire detection in the outdoor depends on weather conditions, the shadow by the movement of the sun, or illumination changes. In this paper, a smoke detection in conjunction with a robust background estimate algorithm to environment change in the outdoor in daytime is proposed. Gaussian Mixture Model (GMM) is applied as background estimation, and also, statistical characteristics of smoke is applied to detect the smoke for separated candidate region. Through the experiments with input videos obtained from a various weather conditions, the proposed algorithms were useful to detect smoke in the outdoor.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.19 no.2
• /
• pp.21-43
• /
• 1994

Software acquisition involves purchase of new technology as well as the product itself. Consequently, evaluation of candidate packages or development contractors requires formal models that can objectively compare the candidates' technological characteristics with respect to user requirements. This paper proposes three technological evaluation models for software acquisition : 1) a structural model dthat organizes the technological factors to be evaluated, 2) a scoring model that quantifies the candidates' technological values, and 3) an organization model that orgnizes and assigns responsibilities to technical evaluators. Three models, initially built on expert surveys and later refined through interviews with opinion leaders, are primarily intended for governmental use : the Korean government is expected to use these models as the software acquisition standards starting in 1994.

• The Korean Journal of Applied Statistics
• /
• v.6 no.1
• /
• pp.29-40
• /
• 1993

In a model-based sampling problem, it often happens that the functional form of variance of error terms in regression model cannot be specified in an exact form. The goal of error-robust sampling design will be to minimize the 'ill effects' resulting from a lack of knowledge of the error structure. A sampling criterion, which is optimal if it minimizes the average of an inefficiency measure when taken with respect to all candidate error structures, is proposed and a computer algorithm is developed for construction of optimal sampling plans. Auditing problem is of particular relevance because of the uncertainty that currently clouds specification of the error structure.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.28 no.3
• /
• pp.154-159
• /
• 2015

In this paper, we propose a numerical method to model temperature dependent threshold voltage shift observed in metal oxide thin-film transistors (TFTs). The proposed model is then implemented in AIM-SPICE circuit simulation tool. The proposed method consists of modeling the well-known stretched-exponential time dependent threshold voltage shift and their temperature dependent coefficients. The outputs from AIM-SPICE tool and the stretched-exponential model at different temperatures in the literature are compared and they show a good agreement. Since metal oxide TFTs are the promising candidate for flat panel displays, the proposed method will be a good stepping stone to help enhance reliability of fast-evolving display circuits.

• Journal of Marine Bioscience and Biotechnology
• /
• v.4 no.1
• /
• pp.11-14
• /
• 2010

The genus Porphyra, consisting of 133 species includes several economically valuable species (i.e. P. yezoensis, P. tenera, P. pseudolinearis etc.). They are predominantly consumed and cultivated in East Asian countries such as Japan, Korea and China, and they are regarded as a big commercial market today. In addition to the industrial importance, P. yezoensis is currently regarded as a feasible candidate for a model plant in marine biotechnology, therefore there are a wide range of studies being undertaken: strain-preservation, development of mutant strains and genetic analysis and exhaustive molecular analysis including EST and macro/micro array. Focusing on the activities of our research group, current situation and future perspectives in marine biotechnological studies using P. yezoensis will be discussed in this mini review.

• YAKHAK HOEJI
• /
• v.59 no.4
• /
• pp.151-157
• /
• 2015

The purpose of this study is to demonstrate how lead compounds are best optimized with the application of in silico QSAR and PBPK modeling at the early drug discovery stage. Several predictive QSAR models such as $IC_{50}$ potency model, intrinsic clearance model and brain penetration model were built and applied to a set of virtually synthesized library of the BACE1 inhibitors. Selected candidate compounds were also applied to the PBPK modeling for comparison between the predicted animal pharmacokinetic parameters and the observed ones in vivo. This novel lead optimization strategy using QSAR and PBPK modelings could be helpful to expedite the drug discovery process.