• Preventive Nutrition and Food Science
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• v.3 no.3
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• pp.292-294
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• 1998

Surimi sol and gel were prepared by mixing egg albumin, starch, oil and carrageenan, which are used as representative ingredients in the surimi composite, at different ratio. Structural properties in surimi composite were investigated by examining the phase changes and dispersion pattern (average particle size, size range and the averge number of particle) of the particulate ingredients in sol and gel with an image analyzer. A staining technique of the specimen containing egg albumin in surimi gel was developed by adjusting pH of a toluidine staining solution. Image analysis revealed that size and density of ingredient particles were function of the level and dispersion of ingredients except of starch-incorporated surimi gel which showed maximum particle size at 6%.

• Journal of the Semiconductor & Display Technology
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• v.15 no.1
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• pp.27-32
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• 2016

A new lane detection algorithm is proposed for the analysis of DNA fingerprints from a polymerase chain reaction (PCR) gel electrophoresis image. Although several research results have been previously reported, it is still challenging to extract lanes precisely from images having abrupt background brightness difference and bent lanes. We propose an edge based algorithm for calculating the average lane width and lane cycle. Our method adopts sub-pixel algorithm for extracting rising-edges and falling edges precisely and estimates the lane width and cycle by using k-means clustering algorithm. To handle the curved lanes, we partition the gel image into small portions, and track the lane centers in each partitioned image. 32 gel images including 534 lanes are used to evaluate the performance of our method. Experimental results show that our method is robust to images having background difference and bent lanes without any preprocessing.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.551-555
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• 2010

In protein 2-DE image analysis, the accuracy of spot-matching operation which identifies the spot of the same protein in each 2-DE gel image is intensively influenced by the errors caused by the various experimental conditions. This paper proposes an efficient method to find more accurate spot-matching patterns based on multiple reference gel images in spot-matching pattern analysis in protein 2-DE image analysis. Additionally, in order to improve the reduce the execution time which is increased exponentially along with the increasing number of gel images, a "partition then extension" framework is used to find spot-matching pattern of long length and of higher accuracy. In the experiments on real 2-DE images of human liver tissue are used to confirm the accuracy and the efficiency of the proposed algorithm.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05b
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• pp.107-110
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• 2002

The optical memory devices of BST thin films to composite $(Ba_{0.7}\;Sr_{0.3})TiO_{3}$ using sol-gel method were fabricated by changing of the depositing layer number on $Pt/Ti/SiO_{2}/Si$ substrate. The structural properties of optical memory devices to be ferroelectric was investigated by fractal analysis and 3-dimension image processing. The thickness of BST thin films at each coating numbers 3, 4 and 5 times was $2500[\AA]$, $3500[\AA]$ and $3800[\AA]$. BST thin films exhibited the most pronounced grain growth. The surface morphology image was roughness with coating numbers. The thin films increasing with coating numbers shows a more textured and complex configuration.

• Journal of Microbiology and Biotechnology
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• v.16 no.1
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• pp.25-31
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• 2006

Changes of CP4 5-enolpyruvylshikimate-3-phosphate synthase (CP4 EPSPS) in the glyphosate-tolerant Roundup Ready soybean were examined using purified CP4 EPSPS produced in cloned Escherichia coli as a control. CP4 EPSPS in genetically modified soybean was detected by twodimensional gel electrophoresis (2-DE) and identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and electrospray ionization tandem mass spectrometry (ESI-MS/MS) with databases. CP4 EPSPS in soybean products was resolved on 2-DE by first isoelectric focusing (IEF) based on its characteristic pI of 5.1, followed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) based on its molecular mass of 47.5 kDa. We quantified various percentages of soybean CP4 EPSPS. The quantitative analysis was performed using a 2D software program on artificial gels with spots varying in Gaussian volumes. These results suggested that 2-DE image analysis could be used for quantitative detection of GM soybean, unlike Western blotting.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.239-246
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• 2005

Biologist must have to do 2DGE biological experiment for Protein Search and Analysis. This experiment coming into being 2 dimensional image. 2DGE (2D Gel Electrophoresis : two dimensional gel electrophoresis) image is the most widely used method for isolating of the objective protein by comparative analysis of the protein spot pattern in the gel plane. The process of protein spot analysis, firstly segment protein spots that are spread in 2D gel plane by image processing and can find important protein spots through comparative analysis with protein pattern of contrast group. In the algorithm which detect protein spots, previous 2DGE image analysis is applies gaussian fitting, however recently Watersheds region based segmentation algorithm, which is based on morphological segmentation is applied. Watersheds has the benefit that segment rapidly needed field in big sized image, however has under-segmentation and over-segmentation of spot area when gray level is continuous. The drawback was somewhat solved by marker point institution, but needs the split and merge process. This paper introduces a novel marker search of protein spots by watersheds-based hierarchical threshold, which can resolve the problem of marker-driven watersheds.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.323-328
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• 2006

Proteins in a cell appear as spots in a two dimensional gel image which is used in protein analysis. The spots from the same protein are in near position when comparing two gel images. Finding out the different proteins between a normal tissue and a cancer one is important information in drug development. Automatic matching of gel images is difficult because they are made from biological experimental processes. This matching problem is known to be NP-hard. Neural networks are usually used to solve such NP-hard problems. Hopfield neural network is selected since it is appropriate to solve the gel matching. An energy function with location and distance parameters is defined. The two spots which make the energy function minimum are matching spots and they came from the same protein. The energy function is designed to reflect the topology of spots by examining not only the given spot but also neighborhood spots.

• Korean Journal of Materials Research
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• v.29 no.3
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• pp.183-188
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• 2019

Flexible dye-sensitized solar cells using binder free $TiO_2$ paste for low temperature sintering are developed. In this paste a small amount of titanium gel is added to a paste of $TiO_2$ nanoparticle. Analysis of titanium gel paste prepared at $150^{\circ}C$ shows that it has a pure anatase phase in XRD and mesoporous structure in SEM. The formation of the titanium gel 1-2 nm coated layer is confirmed by comparing the TEM image analysis of the titanium gel paste and the pristine paste. This coating layer improves the excited electron transfer and electrical contact between particles. The J-V curves of the organic binder DSSCs fabricated at $150^{\circ}C$ shows a current density of $0.12mA/cm^2$ and an open-circuit voltage of 0.47 V, while the titanium gel DSSCs improves electrical characteristics to $5.04mA/cm^2$ and 0.74 V. As a result, the photoelectric conversion efficiency of the organic binder DSSC prepared at low temperature is as low as 0.02 %, but the titanium gel paste DSSCs has a measured effciency of 2.76 %.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.113-116
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• 2008

In this paper we suggest two novel methods for an implementation of the spot detection phase in the 2-DE gel image analysis program. The one is the adaptive thresholding method for eliminating noises and the other is the asymmetric diffusion model for spot matching. Remained noises after the preprocessing phase cause the over-segmentation problem by the next segmentation phase. To identify and exclude the over-segmented background regions, il we use a fixed thresholding method that is choosing an intensity value for the threshold, the spots that are invisible by one's human eyes but mean very small amount proteins which have important role in the biological samples could be eliminated. Accordingly we suggest the adaptive thresholding method which comes from an idea that is got on statistical analysis for the prominences of the peaks. There are the Gaussian model and the diffusion model for the spot shape model. The diffusion model is the closer to the real spot shapes than the Gaussian model, but spots have very various and irregular shapes and especially asymmetric formation in x-coordinate and y-coordinate. The reason for irregularity of spot shape is that spots could not be diffused perfectly across gel medium because of the characteristics of 2-DE process. Accordingly we suggest the asymmetric diffusion model for modeling spot shapes. In this paper we present a brief explanation ol the two methods and experimental results.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.601-608
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• 2007

2 Dimensional Gel Electrophoresis(2DGE) is an essentialmethodology for analysis on the expression of various proteins. For example, information for the location, mass, expression, size and shape of the proteins obtained by 2DGE can be used for diagnosis, prognosis and biological progress by comparison of patients with the normal persons. Protein spot matching for this purpose is comparative analysis of protein expression pattern for the 2DGE images generated under different conditions. However, visual analysis of protein spots which are more than several hundreds included in a 2DGE image requires long time and heavy effort. Furthermore, geometrical distortion makes the spot matching for the same protein harder. In this paper, an iterative algorithm is introduced for more efficient spot matching. Proposed method is first performing global matching step, which reduces the geometrical difference between the landmarks and the spot to be matched. Thus, movement for a spot is defined by a weighted sum of the movement of the landmark spots. Weight for the summation is defined by the inverse of the distance from the spots to the landmarks. This movement is iteratively performed until the total sum of the difference between the corresponding landmarks is larger than a pre-selected value. Due to local distortion generally occurred in 2DGE images, there are many regions in whichmany spot pairs are miss-matched. In the second stage, the same spot matching algorithm is applied to such local regions with the additional landmarks for those regions. In other words, the same method is applied with the expanded landmark set to which additional landmarks are added. Our proposed algorithm for spot matching empirically proved reliable analysis of protein separation image by producing higher accuracy.