• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.32-40
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• 2011

The tracking and analysis of cell activities in time-lapse sequences plays an important role in understanding complex biological processes such as the spread of the tumor, an invasion of the virus, the wound recovery and the cell division. For automatic tracking of cells, the tasks such as the cell detection at each frame, the investigation of the correspondence between cells in previous and current frames, the identification of the cell division and the recognition of new cells must be performed. This paper proposes an automatic cell tracking algorithm. In the first frame, the marker of each cell is extracted using the feature vector obtained by the analysis of cellular regions, and then the watershed algorithm is applied using the extracted markers to produce the cell segmentation. In subsequent frames, the segmentation results of the previous frame are incorporated in the segmentation process for the current frame. A combined criterion of geometric and intensity property of each cell region is used for the proper association between previous and current cells to obtain correct cell tracking. Simulation results show that the proposed method improves the tracking performance compared to the tracking method in Cellprofiler (the software package for automatic analysis of bioimages).

• Journal of Digital Convergence
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• v.14 no.1
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• pp.203-209
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• 2016

In this paper, we introduce a fuzzy inference systems for nonlinear inference using fuzzy cluster. Typically, the generation of fuzzy rules for nonlinear inference causes the problem that the number of fuzzy rules increases exponentially if the input vectors increase. To handle this problem, the fuzzy rules of fuzzy model are designed by dividing the input vector space in the scatter form using fuzzy clustering algorithm which expresses fuzzy cluster. From this method, complex nonlinear process can be modeled. The premise part of the fuzzy rules is determined by means of FCM clustering algorithm with fuzzy clusters. The consequence part of the fuzzy rules have four kinds of polynomial functions and the coefficient parameters of each rule are estimated by using the standard least-squares method. And we use the data widely used in nonlinear process for the performance and the nonlinear characteristics of the nonlinear process. Experimental results show that the non-linear inference is possible.

• The Research Journal of the Costume Culture
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• v.19 no.5
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• pp.993-1008
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• 2011

Traditional culture could be a wonderful source of inspiration for creative design. Tteoksal, the stamps used for making decorative patterns on traditional rice-cakes, have been used and passed on to generations to show the emotions of our ancestors. Numerous traditional patterns found in Tteoksal can be used to better understand and transmit tradition in modern ways. The purpose of this study was to develop fashion cultural products with a modern sensibility by understanding the origin, types and characteristics of Tteoksal and its patterns. The method of this study was through considering the proceeding studies and the references published by a specialist and museums having some information about further knowledge on Tteoksal. In line with the aforementioned study, neckties, eco-friendly bags and pouches were developed as fashion goods. Among the Tteoksal's patterns selected were lotus, bats, 樂 letters and complex patterns. Using a computer graphic software program such as Adobe Illustrator CS5, archetypes of patterns were traced as vector graphics, and two design motives were developed in every pattern. The patterns were developed into two types: one was a basic pattern faithful to a basic motive pattern, and the other was a varied type that was changed and applied. The fashion products were developed as two styles for basic and varied patterns for neckties, eco-friendly bags and pouch items. Twelve products were made for each pattern, which totals 48 unique products. In conclusion, the study could be a critical step to better understand the traditional culture and its influence to the patterns applied to modern fashion design.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.206-211
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• 2008

Trainee can enhance his perception of and interaction with the real world by displayed virtual objects in simulation using image processing technology. Therefore, it is essential for realistic simulation to determine the occlusion areas of the virtual object produces after registering real image and virtual object exactly. In this paper, we proposed the new method to solve occlusions which happens during virtual target moves according to the simulated route on real image using improved object contour extraction by neighboring edge search and picking algorithm. After we acquire the detailed contour of complex objects by proposed contour extraction algorithm, we extract the three dimensional information of the position happening occlusion by using MER for performance improvement. In the experiment, we compared proposed method with existed method and preyed the effectiveness in the environment which a partial occlusions happens.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.41-50
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• 2004

Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video objects from video sequences. Segmentation algorithms can largely be classified into two different categories: automatic segmentation and user-assisted segmentation. In this paper, we propose a new user-assisted image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is, therefore, applicable to images of complex background. We can also compensate for limitations of the shape matrix with a dynamic graph search algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.3
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• pp.419-429
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• 1999

Identifying the boundary of the effective receiving power of waves is one of the most important factors for cell optimization. In this paper, we introduce a propagation loss prediction model which yields highly accurate prediction in very complex areas as Seoul where a mixture of many large buildings, small buildings, broad streets, narrow alleys, rivers and forests co-exist in an irregular arrangement. This prediction model is based on neural networks trained on field measurement data collected in the past. Using these data along with 3-D digital elevation maps and vector data for building structures, we extract the parameter values which mainly affect the amount of propagation loss. These parameter values are then used as the inputs to the neural network. Trained neural network becomes the approximated function of the propagation loss model which generalizes very well and can predict accurately in the regions not included in training the neural network. The experimental results show a superior performance over the other models in the cells operating in the city of Seoul.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.1
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• pp.45-50
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• 2015

In this paper, we confirm the effective adaptive algorithm for tha active noise contorl (ANC) though the performance comparison between adaptive algorithms. Generally, the normalized least mean square (NLMS) algorithm has been widely used for an adaptive algorithm thanks to its simplicity and having a fast convergence speed. However, the convergence performance of the NLMS algorithms is often deteriorated by colored input signals. To overcome this problem, the affine pojection (AP) algorithm that updates the weight vector based on a number of recent input vectors can be used for allowing a higher convergence speed than the NLMS algorithm, but it is computationally complex. Thus, the proper algorithm were determined by the comparison between NLMS and AP algorithms regarding as the convergence performance and complexity. Simulation results confirmed that the noise reduction performance of NLMS algorithm was comparable to AP algorithm with low complexity. Therefore the NLMS algorithm is more effective for ANC system.

• Biomedical Science Letters
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• v.15 no.1
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• pp.37-45
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• 2009

Insect cell cultures have become important tools in the production of biological substances for use in a variety of research, human and veterinary medicine, and pest control applications. These applications often require the introduction of foreign DNA into the cells and have generally used methods originally developed for use with human and other mammalian cell cultures. While these methods can be successfully employed, they are often less efficient with insect cells and frequently involve complex procedures or require specialized equipment. Even when they do work, they may require substantial modification because of differences in the culture medium or growth patterns of insect cells. In this study, We have optimized transfection conditions of Sf9 cell line using insect expression vector pIZT/V5-His which expresses green fluorescent protein effectively. Human stem cell factor (hSCF) is a glycoprotein that plays a key role in hematopoiesis acting both as a positive and negative regulator, often in synergy with other cytokines. It also plays a key role in mast cell development, gametogenesis, and melanogenesis. It can exist in membrane-bound form and in proteolytically released soluble form. As determined by an enzyme-linked immunosorbent assay performed, hSCF level in supernatant averaged 995ng/ml. The human hSCF was partially purified by immunoaffinity chromatography and analyzed with sodium dodecyl sulfate-polyacrylamide gel electrophoresis and immunoblotting. The results show that the hSCF has N-linked carbohydrate and corresponds to the soluble form, at or about 223 amino acids in length. The findings suggest functional importance for soluble hSCF in cells.

• YAKHAK HOEJI
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• v.39 no.2
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• pp.161-168
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• 1995

Brain dopamine systems play a central role in the control of movement, hormone release, and many complex behavior. The action of dopamine at its synapse is terminated predominately by high affinity reuptake into presynaptic terminals by dopamine transporter (DAT). The dopamine transporter(DAT) is membrane protein localized to dopamine-containing nerve terminals and closely related with cocaine abuse, Parkinsonism, and schizophrenia. In present study, the recombinant plasmid pRc/CMV-DAT, constructed by subcloning of a cDNA encoding a bovine DAT into eukaryotic expression vector pRc/CMV, was stably transfected into CV-1 cells(monkey kidney cell line). The DAT activities in the cell lines selected by Geneticin$^{R}$ were determined by measuring the uptake of $[^3H]$-dopamine. The transfected cell lines showed 30-50 fold higher activities than untransfected CV-1 cell line, and this result implies that DAT is well expressed and localized in transfected cells. The transfected cells accumulated $[^3H]$-dopamine in a dose-dependent manner with a $K_{m}$ of 991.6nM. Even though high doses of norepinephrine, epinephrine, serotonin, and choline neurotransmitters inhibited the uptake of $[^3H]$-dopamine, DAT in transfected cell line was proven to be much more specific to dopamine. The psychotropic drugs such as GBR12909, CFT, normifensine, clomipramine, desipramine, and imipramine inhibited significantly the dopamine uptake in tissue culture cells stably transfected with DAT cDNA. Radioactive in situ hybridization was done to map the cellular localization of DAT mRNA-containing cells in the adult rat central nervous system. The strong hybridization signals were detected only in the substantia nigra pars compacta and ventral tegmental area. The restricted anatomical localization of DAT mRNA-containing cells confirms the DAT as a presynaptic marker of dopamine-containing cells in the rat brain.