• Food Science and Biotechnology
• /
• v.17 no.6
• /
• pp.1214-1220
• /
• 2008

Secondary metabolites from the fruit body of Phellinus linteus were evaluated for their proliferative effect on human osteoblast-like cells. 3-[4,5-Dimethylthiazole-2-y1]-2,5-diphenyl-tetraxolium bromide (MTT) assay and alkaline phosphatase (ALP) activity assay were used to assess the effect those isolates on the human osteoblast-like cell line (Saos-2). Activity-guided fractionation led to the isolation of ALP-activating phenolic compounds through the extraction of P. linteus, solvent partitioning, and repeated silica gel and octadecyl silica gel (ODS) column chromatographic separations. From the result of spectroscopic data including nuclear magnetic resonance (NMR), mass spectrometry (MS), and infrared spectroscopy (IR), the chemical structures of the compounds were determined as 4-(4-hydroxyphenyl)-3-buten-2-one(1), 2-(3',4'-dihydroxyphenyl)-1,3-benzodioxole-5-aldehyde (2), 4-(3,4-dihydroxyphenyl)-3-buten-2-one (3), 3,4-dihydroxybenzaldehyde (4), and protocatechuic acid methyl ester (5), respectively. This study reports the first isolation of compounds 1-3 and 5 from P. linteus. In addition, all phenolic compounds stimulated proliferation of the osteoblast-like cells and increased their ALP activity in a dose-dependent manner ($10^{-8}$ to $10^{-1}\;mg/mL$). The present data demonstrate that phenolic compounds in P. linteus stimulated mineralization in bone formation caused by osteoporosis. The bone-formation effect of P. linteus seems to be mediated, at least partly, by the stimulating effect of the phenolic compounds on the growth of osteoblasts.

• Journal of Aerospace System Engineering
• /
• v.13 no.5
• /
• pp.1-8
• /
• 2019

Recently, avionics has been migrating from a federated architecture to an integrated modular architecture based on a multi-core to reduce the number of systems, weight, power consumption, and platform redundancy. The volume of data which must bo provided to the pilot through the display device has increased, because an integrated single device performs multiple functions. For this reason, the volume of data processed by the graphic processor within a fixed operation period has increased. In this paper, we provide a multi-core-based rendering engine in to perform more graphics processing within a fixed operation period. We assume the proposed method uses a multi-core-based partitioning operating system using the AMP (Asymmetric Multi-Processing) architecture.

• Current Optics and Photonics
• /
• v.5 no.4
• /
• pp.431-443
• /
• 2021

Sparse unmixing has been proven to be an effective method for hyperspectral unmixing. Hyperspectral images contain rich spectral and spatial information. The means to make full use of spectral information, spatial information, and enhanced sparsity constraints are the main research directions to improve the accuracy of sparse unmixing. However, many algorithms only focus on one or two of these factors, because it is difficult to construct an unmixing model that considers all three factors. To address this issue, a novel algorithm called multiview-based spectral weighted and low-rank row-sparsity unmixing is proposed. A multiview data set is generated through spectral partitioning, and then spectral weighting is imposed on it to exploit the abundant spectral information. The row-sparsity approach, which controls the sparsity by the l_2,0 norm, outperforms the single-sparsity approach in many scenarios. Many algorithms use convex relaxation methods to solve the l_2,0 norm to avoid the NP-hard problem, but this will reduce sparsity and unmixing accuracy. In this paper, a row-hard-threshold function is introduced to solve the l_2,0 norm directly, which guarantees the sparsity of the results. The high spatial correlation of hyperspectral images is associated with low column rank; therefore, the low-rank constraint is adopted to utilize spatial information. Experiments with simulated and real data prove that the proposed algorithm can obtain better unmixing results.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.05a
• /
• pp.357-359
• /
• 2023

This paper proposes a hybrid recommendation system (RS) model that overcomes the limitations of traditional approaches such as data sparsity, cold start, and scalability by combining collaborative filtering and context-aware techniques. The objective of this model is to enhance the accuracy of recommendations and provide personalized suggestions by leveraging the strengths of collaborative filtering and incorporating user context features to capture their preferences and behavior more effectively. The approach utilizes a novel method that combines contextual attributes with the original user-item rating matrix of CF-based algorithms. Furthermore, we integrate k-mean++ clustering to group users with similar preferences and finally recommend items that have highly rated by other users in the same cluster. The process of partitioning is the use of the rating matrix into clusters based on contextual information offers several advantages. First, it bypasses of the computations over the entire data, reducing runtime and improving scalability. Second, the partitioned clusters hold similar ratings, which can produce greater impacts on each other, leading to more accurate recommendations and providing flexibility in the clustering process. keywords: Context-aware Recommendation, Collaborative Filtering, Kmean++ Clustering.

• Journal of the Korean earth science society
• /
• v.24 no.5
• /
• pp.428-439
• /
• 2003

Landslides, as a geological hazard, have caused extensive damage to property and sometimes result in loss of life. Thus, it is necessary to assess vulnerable areas for future possible landslides in order to mitigate the damage they cause. For this purpose, spatial data integration has been developed and applied to landslide hazard mapping. Among various models, this paper investigates and discusses the effectiveness of the Bayesian spatial data integration approach to landslide hazard mapping. In this study, several data sets related to landslide occurrences in Jangheung, Korea were constructed using GIS and then digitally represented using the likelihood ratio function. By computing the likelihood ratio, we obtained quantitative relationships between input data and landslide occurrences. The likelihood ratio functions were combined using the Bayesian combination rule. In order for predicted results to provide meaningful interpretations with respect to future landslides, we carried out validation based on the spatial partitioning of the landslide distribution. As a result, the Bayesian approach based on a likelihood ratio function can effectively integrate various spatial data for landslide hazard mapping, and it is expected that some suggestions in this study will be helpful to further applications including integration and interpretation stages in order to obtain a decision-support layer.

• Journal of KIISE:Databases
• /
• v.34 no.2
• /
• pp.166-178
• /
• 2007

The ALE specification of EPCglobal is leading the development of RFID standards, includes the Event Cycle Specification (ECSpec) describing how long a cycle is, how to filter RFID tag data and which reader is interested in. The ECSpec is a specification for filtering and collecting RFID tag data. It is registered to a middleware for long time and is evaluated to return results satisfying the requirements included in it. Thus, it is quite similar to the continuous query. It can be transformed into a continuous query as its predicate in WHERE clause is characterized by the long interval. Long intervals cause problems deteriorating insertion and search performance of existing query indices. In this paper, we propose a TLC-index as a new query index structure for long interval data. The TLC-index has hybrid structure that uses the cell construct of CQI-index with the virtual construct of VCR-index for partitioning long intervals. The TLC-index can reduce the storage cost and improve the insertion performance through decomposing long intervals into one or more cell constructs that have long size. It can also improve the search performance through decomposing short intervals into one or more virtual constructs that have short size enough to fit into those intervals.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.4B
• /
• pp.708-714
• /
• 2000

In this paper, an one-dimensional VLSI array for high speed processing of fractal image compression algorithm based the quad-tree partitioning method is proposed. First of all, the single assignment code algorithm is derived from the sequential Fisher's algorithm, and then the data dependence graph(DG) is obtained. The two-dimension array is designed by projecting this DG along the optimal direction and the one-dimensional VLSI array is designed by transforming the obtained two-dimensional array. The number of Input/Output pins in the designed one-dimensional array can be reduced and the architecture of process elements(PEs) can he simplified by sharing the input pins of range and domain blocks and internal arithmetic units of PEs. Also, the utilization of PEs can be increased by reusing PEs for operations to the each block-size. For fractal image compression of 512X512gray-scale image, the proposed array can be processed fastly about 67 times more than sequential algorithm. The operations of the proposed one-dimensional VLSI array are verified by the computer simulation.

• Food Science and Biotechnology
• /
• v.15 no.5
• /
• pp.781-785
• /
• 2006

The chemical compositions of the seeds of the safflower (Carthamus tinctorius L.) plant were evaluated to determine possible compound having proliferative effects on human osteoblast cells. Three-[4,5-dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide (MTT) test and alkaline phosphatase (ALP) activity were used to assess the effects of the isolates on the human osteoblast-like line (Saos-2). Activity guided fractionation led to the isolation of ALP activating lignin and alkaloid glycosides through the extraction of the seeds, solvent partitioning and repeated silica gel and octadecyl silica (ODS) column chromatographic separations. The data from Nuclear Magnetic Resonance (NMR), Mass (MS), and Infrared (IR) analyses enabled the determination of the chemical structure and characterization of two compounds as a tracheloside and an N-(p-coumaroyl)-serotonin mono-${\beta}$-D-glucopyranoside. These two compounds showed respectively $149.2{\pm}4.2$ and $138.9{\pm}3.5%$ ALP activity compared to the control when evaluated at a concentration of $100\;{\mu}g/mL$.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.11
• /
• pp.5379-5388
• /
• 2012

In fuzzy modeling for nonlinear process, the fuzzy rules are typically formed by selection of the input variables, the number of space division and membership functions. The Generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, complex nonlinear process can be modeled by generating the fuzzy rules by means of fuzzy division of input space. Therefore, in this paper, rules of non-fuzzy inference systems are generated by partitioning the input space in the scatter form using HCM clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of HCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the consequence parameters of each rule are identified by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process. Through this experiment, we showed that high-dimensional nonlinear systems can be modeled by a very small number of rules.

• Asian-Australasian Journal of Animal Sciences
• /
• v.24 no.11
• /
• pp.1525-1528
• /
• 2011

The purpose of this study was to detect SNPs that were responsible for a carcass trait in Hanwoo populations. A non-parametric model applying a restricted partition method (RPM) was used, which exploited a partitioning algorithm considering statistical criteria for multiple comparison testing. Phenotypic and genotypic data were obtained from the Hanwoo Improvement Center, National Agricultural Cooperation Federation, Korea, in which the pedigree structure comprised 229 steers from 16 paternal half-sib proven sires that were born in Namwon or Daegwanryong livestock testing station between spring of 2002 and fall of 2003. A carcass trait, longissimus dorsi muscle area for each steer was measured after slaughter at approximately 722 days. Three SNPs (19_1, 18_4 and 28_2) near the microsatellite marker ILSTS035 on BTA6, around which the quantitative trait loci (QTL) for meat quality were previously detected, were used in this study. The RPM analyses resulted in two significant interaction effects between SNPs (19_1 and 18_4) and (19_1 and 28_2) at ${\alpha}$ = 0.05 level. However, under a general linear (parametric) model no interaction effect between any pair of the three SNPs was detected, while only one main effect for SNP19_1 was found for the trait. Also, under another non-parametric model using a multifactor dimensionality reduction (MDR) method, only one interaction effect of the two SNPs (19_1 and 28_2) explained the trait significantly better than the parametric model with the main effect of SNP19_1. Our results suggest that RPM is a good alternative to model choices that can find associations of the interaction effects of multiple SNPs for quantitative traits in livestock species.