• Journal of the Korea Furniture Society
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• v.28 no.3
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• pp.248-258
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• 2017

A study was carried out to observe the 1% aqueous safranine solution flow speed in longitudinal and radial directions of softwood Thuja orientalis L., diffuse-porous wood Gmelina arborea Roxb., and ring-porous wood Phellodendron amurense Rupr., Longitudinal flow was considered from bottom to top while the radial flow was considered from bark to pith directions. In radial direction, ray cells and in longitudinal direction tracheids, vessel and wood fiber were considered for the measurement of liquid penetration speed at less than 12% moisture contents(MC). The variation of penetration speed for different species was observed and the reasons behind for this variation were explored. The highest radial penetration depth was found in ray parenchyma of T. orientalis but the lowest one was found in ray parenchyma of P. amurense. The average liquid penetration depth in longitudinal trachied of T. orientalis was found the highest among all the other cells. The penetration depth in fiber of G. arborea was found the lowest among the other longitudinal cells. It was found that cell dimension and also meniscus angle of safranine solution with cell walls were the prime factors for the variation of liquid flow speed in wood. Vessel was found to facilitate prime role in longitudinal penetration for hardwood species. The penetration depth in vessel of G. arborea was found highest among all vessels. Anatomical features like ray parenchyma cell length and diameter, end-wall pits number were found also responsible fluid flow differences. Initially liquid penetration speed was high and the nit gradually decreased in an uneven rate. Liquid flow was captured via video and the penetration depths in those cells were measured. It was found that even in presence of abundant rays in hardwood species, penetration depth of liquid in radial direction of softwood species was found high. Herein the ray length, lumen area, end wall pit diameter determined the radial permeability. On the other hand, vessel and fiber structure affected the longitudinal flow of liquids. Following a go-stop-go cycle, the penetration speed of a liquid decreased over time.

• Molecules and Cells
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• v.40 no.2
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• pp.117-122
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• 2017

Despite the fact that porcine embryonic stem cells (ESCs) are a practical study tool, in vitro long-term maintenance of these cells is difficult in a two-dimensional (2D) microenvironment using cellular niche or extracellular matrix proteins. However, a three-dimensional (3D) microenvironment, similar to that enclosing the inner cell mass of the blastocyst, may improve in vitro maintenance of self-renewal. Accordingly, as a first step toward constructing a 3D microenvironment optimized to maintain porcine ESC self-renewal, we investigated different culture dimensions for porcine ICM-derived cells to enhance the maintenance of self-renewal. Porcine ICM-derived cells were cultured in agarose-based 3D hydrogel with self-renewal-friendly mechanics and in 2D culture plates with or without feeder cells. Subsequently, the effects of the 3D microenvironment on maintenance of self-renewal were identified by analyzing colony formation and morphology, alkaline phosphatase (AP) activity, and transcriptional and translational regulation of self-renewal-related genes. The 3D microenvironment using a 1.5% (w/v) agarose-based 3D hydrogel resulted in significantly more colonies with stereoscopic morphology, significantly improved AP activity, and increased protein expression of self-renewal-related genes compared to those in the 2D microenvironment. These results demonstrate that self-renewal of porcine ICM-derived cells can be maintained more effectively in a 3D microenvironment than in a 2D microenvironment. These results will help develop novel culture systems for ICM-derived cells derived from diverse species, which will contribute to stimulating basic and applicable studies related to ESCs.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.596-608
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• 2004

A lot of work has been done to reduce disk access time in I/O intensive systems, which store and handle massive amount of data, by distributing data across multiple disks and accessing them in parallel. Most of the previous work has focused on an efficient mapping from a grid cell to a disk number on the assumption that data space is regular grid-like partitioned. Although we can achieve good performance for low-dimensional data by grid-like partitioning, its performance becomes degenerate as grows the dimension of data even with a good disk allocation scheme. This comes from the fact that they partition entire data space equally regardless of distribution ratio of data objects. Most of the data in high-dimensional space exist around the surface of space. For that reason, we propose a new declustering algorithm based on the partitioning scheme which partition data space from the surface. With an unbalanced partitioning scheme, several experimental results show that we can remarkably reduce the number of data blocks touched by a query as grows the dimension of data and a query size. In this paper, we propose disk allocation schemes based on the layout of the resultant data blocks after partitioning. To show the performance of the proposed algorithm, we have performed several experiments with different dimensional data and for a wide range of number of disks. Our proposed disk allocation method gives a performance within 10 additive disk accesses compared with strictly optimal allocation scheme. We compared our algorithm with Kronecker sequence based declustering algorithm, which is reported to be the best among the grid partition and mapping function based declustering algorithms. We can improve declustering performance up to 14 times as grows dimension of data.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.105-112
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• 2006

In this study, we propose a simple preprocessing method for classification of basal cell carcinoma (BCC), which is one of the most common skin cancer. The preprocessing step consists of data clipping with a half Hanning window and dimension reduction with principal components analysis (PCA). The application of the half Hanning window deemphasizes the peak near $1650cm^{-1}$ and improves classification performance by lowering the false negative ratio. Classification results with various classifiers are presented to show the effectiveness of the proposed method. The classifiers include maximum a posteriori probability (MAP), k-nearest neighbor (KNN), probabilistic neural network (PNN), multilayer perceptron(MLP), support vector machine (SVM) and minimum squared error (MSE) classification. Classification results with KNN involving 216 spectra preprocessed with the proposed method gave 97.3% sensitivity, which is very promising results for automatic BCC detection.

• Korean Journal of Veterinary Research
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• v.36 no.1
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• pp.101-108
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• 1996

This study was desinged to investigate the effect of estrogen(Est) on the proliferating of progesterone(Prog) target cells. The spayed 13 rats(Wistar, approximately 300gm) were randomly alloted into 3 groups. One group was the control group and another Prog-treated group was injected with 1mg of Prog/rat/day for 2 consecutive days, and Estand Prog-treated group was injected intramuscularly with $17{\beta}$-estradiol $20{\mu}g/rat/day$ for 3 consecutive days and then with Prog for 2 days as above from 4th day. Rats were administrated intraperitoneally with bromodeoxyuridinc(Brdur,0.2mg/BW once) befero 2 hours of exanguination. In gross finding, the groups with more level of dimension and weight on the uterus were ordered as Est- and Prog-treated group, Prog-treated group and control group. The investigation by immunohistochemical methods using paraffin sections of the uteri was performed by using anti-Brdur antibody for labeling proliferating cells of Prog target cells. The groups with higher labeling index(LI) were ordered as Prog-treated grop, Est- and Prog- treated group and control group. The number of proliferating cells from Prog target cells in the rats were rather deceased by Prog injection following Est injection than prog injection only. The cell types with higher LI in the wall layers of all 3 groups were ordered as endometrial stromal cells, glandular epithelial cells, luminal epithelial cells, myometrial muscle cells and serosa methodelial cells, and the region with highest LI was functional zone of the endometrium and the region with lower LI was muscular layer and then those with lowest LI was serosa and also the considerable different LI from individual rat were observed.

• Journal of the Mineralogical Society of Korea
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• v.12 no.2
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• pp.55-65
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• 1999

Spotted cordierite occurs as the result of intrusion of Wolaksan Granite of Cretaceous age in the northern part of the Ogcheon Metamorphic Belt, forming a contact metamorphic zoning in accordance with the distance from the granite body: a cordierite-muscovite-biotite-quartz assemblage and the higher-temperature cordierite-biotite-quartz-(cummingtonite). These quartz-ubiquitous mineral assemblages identified in the cordierite spot seem to reflect Al-deficient condition of the protolith. TEM observations of textural relations between the cordierite and mica within the cordierite spot clearly reflect that cordierite was formed at the expense of micaceous matrix. A structure refinement of the poikiloblastic cordierite was performed by the Rietveld refinement method. Unit cell of the cordierite was determined to be as follows : lower-temperature type: a=17.1480(9)${\AA}$, b=9.7743(6)${\AA}$, c=9.3184(5)${\AA}$, V=1561.9(4)${\AA}$3, higher-temperature type: a=17.136(2)${\AA}$, b=9.751(1)${\AA}$, c=9.322(1)${\AA}$, V=1557.7(4)${\AA}$3. They show a remarkable difference in the unit cell dimension. The refinement results indicate that structural sites of lower-temperature cordierite are wholly occupied by appropriating ions. Compared to this, tetrahedral sites of the higher-temperature type exhibit an order/disorder ranging about 5-8% as the result of substitution between Si4+ and Al3+, except for T26 site occupied wholly by Al3+. These structural differences seem to be related to the formation temperatures of both cordierite types.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.5
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• pp.681-688
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• 2000

In this paper, a planar antenna that is small and light, is designed and analyzed aiming handset antenna of IMT-2000. Employing the Ensemble simulator based on a MoM, design-parameters are found to determine a resonant frequency. Therefore, it is analyzed with the Ensemble simulation and FDTD numerical for resonating at the allocated frequency for IMT-2000 in the fixed antenna dimension of 21$^{\circ}$wing angle that is a design parameter. Analyzing with FDTD method, Though the results of FDTD are very exact, this analysis introduces errors due to the staircasing approximation in the slope of bowtie. To reduce this error, it is divided to 4-ranges where the cell contains the boundary of perfect conductor/free space. Then, each range is calculated by different by different equation, which modify the H-field to add the component of the area and length of the cell filled with free space. Therefore, the modified FDTD algorithm provided with a narrow bandwidth of return loss calculated with a standard FDTD algorithm that can be extended to the desired ranges.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2795-2799
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• 2016

Purpose: To study histomorphological and immunohistochemical patterns of gastro-intestinal stromal tumours (GISTs) in Malaysia. Materials and Methods: A total of 29 GIST cases from Hospital Tuanku Ja'afar, Seremban, were studied retrospectively over a period of 10 years from January 2002 to December 2011. Patient demographic data like age, sex and etnicity were collected. Tumour characteristics like site, maximum dimension and specimen type were analysed. Evaluation was according to established criteria into very low, low, intermediate and high-risk categories. Immunohistochemical characteristics were also analysed. Results: The mean age of patients was 59.7 years. Males (59%) were found to be more commonly affected than females (41%). The Chinese (45%) were commonly affected than Malays (41%), and Indians (10%). The most common symptom was pain in the abdomen (13.8%). More than half of the cases were seen in stomach (53%). The tumour size ranged from 1.5 cm to 17 cm with a mean of 6.94cm. Microscopic findings revealed that the spindle cell type was the most common (76%). It was observed that the majority of the cases (48%) were categorised in the intermediate risk group. Immunohistochemical staining showed positivity for CD117 (78.6%), CD34 (71.4%), vimentin (86.2%), S-100 (27.6%), SMA (35.7%), PKC THETA (46.4%) and PDGRFA (67.9%).

• ALGAE
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• v.37 no.1
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• pp.1-14
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• 2022

Cyanobacteria are distributed worldwide, and many new cyanobacterial species are discovered in tropical region. The Nostoc-like genus Amazonocrinis has been separated from the genus Nostoc based on polyphasic methods. However, species diversity within this genus remains poorly understood systematically because only one species (Amazonocrinis nigriterrae) has been described. In this study, two novel strains (NUACC02 and NUACC03) were isolated from moist rice field soil in Thailand. These two strains were characterized using a polyphasic approach, based on morphology, 16S rRNA phylogenetic analysis, internal transcribed spacer secondary structure and ecology. Phylogenetic analyses based on 16S rRNA gene sequences confirmed that the two novel strains formed a monophyletic clade related to the genus Amazonocrinis and were distant from the type species A. nigriterrae. The 16S rRNA gene sequence similarity (<98.1%) between novel strains and all other closely related taxa including the Amazonocrinis members exceeded the cutoff for species delimitation in bacteriology, reinforcing the presence of a new Amazonocrinis species. Furthermore, the novel strains possessed unique phenotypic characteristics such as the presence of the sheath, necridia-like cells, larger cell dimension and akinete cell arrangement in long-chains and the singularity of D1-D1', Box-B, V2, and V3 secondary structures that distinguished them from other Amazonocrinis members. Considering all the results, we described our two strains as Amazonocrinis thailandica sp. nov. in accordance with the International Code of Nomenclature for Algae, Fungi and Plants.