• Environmental Engineering Research
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• v.22 no.1
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• pp.61-74
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• 2017

This study investigated the effect of various cations ($Ca^{2+}$, $Mg^{2+}$, $Al^{3+}$, $Mn^{2+}$, $Zn^{2+}$) on the autoaggregation (AAg) and surface hydrophobicity (SHb) of three different bacteria (Brevibacillus panacihumi strain (ZB1), Lysinibacillus fusiformis strain (ZB2) and Enterococcus faecalis strain (ZL)) using a 2-level factorial design. The AAg ratio was measured from the changes in the absorbance of the media. Results show that ZB2 had maximum AAg for the three bacteria investigated. A microscopic clustering of cells was observed when $Ca^{2+}$ was added to ZB2. The AAg was in the range of 62%, 58% and 34% for ZB2, ZB1 and ZL, respectively and correlated to the SHb. The aggregation and SHb of the microbial cells increased with increasing ionic strength due to the repulsive steric or overlap forces between the polymer covered surfaces. $Ca^{2+}$ demonstrated a more significant effect on aggregation and SHb of microbial cells due to an attractive binding force.

• Korean Journal of Materials Research
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• v.15 no.6
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• pp.393-398
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• 2005

The crystal structure and magnetic properties of the $Mg_{1-x}Zn_xFeAlO_4\;(0{\leq}x\leq1.0)$ have been investigated by means of x-ray diffractometry and $M\ddot{o}ssbauer$ spectroscopy. The samples$(0{\leq}x\leq1.0)$ have been prepared by the ceramic sintering method. The x-ray diffraction pattern shows that the crystal structure of the samples is a cubic spinel type. The lattice constant has been found by extrapolation using the Nelson-Riley function and it increases slightly from $8.3496\AA\;to\;8.4128\AA$ with Zn concentration. The $M\ddot{o}ssbauer$ spectra for x<0.4 show a superposition of two sextets ana a paramagnetic doublet at room temperature. The superparamagnetic doublet for x<0.4 seems to be due to Al ion in tetrahedral site by the superparamagnetic clustering effect.

• Journal of the Korea Safety Management & Science
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• v.13 no.3
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• pp.115-121
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• 2011

Incheon Port has many advantages for import of log and timber for furniture. More than 50% of lumber which was imported is through Incheon Port. However, most companies move and set up their business by taking lease of workshop. Because of expensive cost of transportation, it is suggested to construct a lumber Industrial district in the North Port in Incheon. By researching the national plans about the North Port and Incheon Ports, an adequate acquaintance of lumber industry in Incheon has been realized. ills study conducted the economic effect analysis for lumber industry clustering and the necessity of cluster composition is derived. Then effectiveness analysis for lumber industry cluster composition is sequentially operated.

• Korean Journal of Childcare and Education
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• v.19 no.2
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• pp.21-42
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• 2023

Objective: This study aims investigate the moderating effect of mothers' overprotective parenting in the influence of young children's competence, as determined by their temperament, on mastery motivation. Methods: An online survey was conducted on 429 mothers with children aged 3-5. The collected data was analyzed using K-means clustering in SPSS 23.0 and the Process macro Model 2. Results: Children's temperaments were categorized into four types : easy-active temperament, easy-inactive temperament, slow temperament, and difficult temperament. It was confirmed that children's competence directly affected their mastery motivation when they had easy-inactive, slow, or difficult temperament. It was also found that mothers' intrusive control had a direct main effect on object persistence when children had easy temperament, while there was no effect on mastery pleasure. The moderating effects of mothers' anxious protection on the pathway from children's competence to object persistence were significant only among children with a slow temperament. Conclusion/Implications: This study highlights the need for mothers to adapt their parenting behavior to their children's temperament type. The study confirmed partial moderating effects of mothers' overprotective parenting in the influence of children's competence, as determined by their temperament, on mastery motivation.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.177-187
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• 2013

Association rule mining is a popular data mining technique with a wide range of application domains, and aims to extract the cause-and-effect relations between the discrete items included in transaction data. However, analysts sometimes have trouble in interpreting and using the plethora of association rules extracted from a large amount of data. To address this problem, this paper aims to propose a novel approach called HTM for extracting the interesting association rules from given transaction data. The HTM approach consists of three main steps, hierarchical clustering, table-view, and mosaic plot, and each step provides the analysts with appropriate visual representation. For illustration, we applied our approach for analyzing the mass health examination data, and the result of this experiment reveals that the HTM approach help the analysts to find the interesting association rules in more effective way.

• Journal of Biomedical Engineering Research
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• v.24 no.2
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• pp.55-60
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• 2003

For quantitative analysis of the cardiac diseases. it is necessary to segment the left-ventricle (LY) in MR (Magnetic Resonance) cardiac images. Snake or active contour model has been used to segment LV boundary. However, the contour of the LV front these models may not converge to the desirable one because the contour may fall into local minimum value due to image artifact inside of the LY Therefore, in this paper, we Propose the Preprocessing method using k-means clustering and merging algorithms that can improve the performance of the active contour model. We verified that our proposed algorithm overcomes local minimum convergence problem by experiment results.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.10
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• pp.575-587
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• 2004

In this paper. a new Fast Expectation-Maximization algorithm(FEM) is proposed. Firstly the K-means algorithm is modified to reduce the number of iterations for finding the initial values that are used as the initial values in EM process. Conventionally the Initial values in K-means clustering are chosen randomly. which sometimes forces the process of clustering converge to some undesired center points. Uniform partitioning method is added to the conventional K-means to extract the proper initial points for each clusters. Secondly the effect of posterior probability is emphasized such that the application of Maximum Likelihood Posterior(MLP) yields fast convergence. The proposed FEM strengthens the characteristics of conventional EM by reinforcing the speed of convergence. The superiority of FEM is demonstrated in experimental results by presenting the improvement results of EM and accelerating the speed of convergence in parameter estimation procedures.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.938-942
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• 2009

In this paper, we propose a novel filtering method for processing continuous skyline queries on wireless sensor network environments. The existing filtering methods use the filter based on router paths. However, because these filters are applied not to a whole area but to a partial area, these methods send almost data of sensor nodes to transmit to the base station and have no sufficient effect in terms of energy efficiency. Therefore, we propose an efficient method to dramatically reduce the transmission data of sensors through applying a low-cost and effective filter to all sensor nodes. The proposed effective filter is generated by using characteristics such as the data locality and the clustering of sensors. An extensive performance study verifies the merits of our new method.

• Molecules and Cells
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• v.43 no.3
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• pp.286-297
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• 2020

Mammalian patatin-like phospholipase domain containing proteins (PNPLAs) play critical roles in triglyceride hydrolysis, phospholipids metabolism, and lipid droplet (LD) homeostasis. PNPLA7 is a lysophosphatidylcholine hydrolase anchored on the endoplasmic reticulum which associates with LDs through its catalytic region (PNPLA7-C) in response to increased cyclic nucleotide levels. However, the interaction of PNPLA7 with LDs through its catalytic region is unknown. Herein, we demonstrate that PNPLA7-C localizes to the mature LDs ex vivo and also colocalizes with pre-existing LDs. Localization of PNPLA7-C with LDs induces LDs clustering via non-enzymatic intermolecular associations, while PNPLA7 alone does not induce LD clustering. Residues 742-1016 contains four putative transmembrane domains which act as a LD targeting motif and are required for the localization of PNPLA7-C to LDs. Furthermore, the N-terminal flanking region of the LD targeting motif, residues 681-741, contributes to the LD targeting, whereas the C-terminal flanking region (1169-1326) has an anti-LD targeting effect. Interestingly, the LD targeting motif does not exhibit lysophosphatidylcholine hydrolase activity even though it associates with LDs phospholipid membranes. These findings characterize the specific functional domains of PNPLA7 mediating subcellular positioning and interactions with LDs, as wells as providing critical insights into the structure of this evolutionarily conserved phospholipid-metabolizing enzyme family.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.57-68
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• 2017

Clustering algorithms attempt to find a partition of a finite set of objects in to a potentially predetermined number of nonempty subsets. Gibbs sampling of a normal mixture of linear mixed regressions with a Dirichlet prior distribution calculates posterior probabilities when the number of clusters was known. Our approach provides simultaneous partitioning and parameter estimation with the computation of classification probabilities. A Monte Carlo study of curve estimation results showed that the model was useful for function estimation. Examples are given to show how these models perform on real data.