• Bulletin of the Korean Chemical Society
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• v.35 no.9
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• pp.2665-2668
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• 2014

Aptamers are oligonucleotides or peptide molecules that are able to bind to their specific target molecules with high affinity via molecular recognition. In this study, we present development of aptamer-based precipitation assays (or simply aptamoprecipitation) for His-tagged proteins and thrombin to compare their purification efficiency with other conventional affinity precipitation methods. A crosslinking method was employed to immobilize thiol-functionalized aptamers onto the surface of polystyrene resins, enabling them to specifically bind to His-tag and to thrombin, respectively. The resulting aptamer-functionalized resins were successfully applied via a one-step experiment to purification of His-tagged proteins from complex E. coli and to thrombin extraction, exhibiting superior or at least comparable purification results to the conventional immobilized metal affinity precipitation or immunoprecipitation.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1081-1088
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• 2013

Hyperspectral cameras acquire reflectance values at many different wavelength bands. Dimensions tend to increase because spectral information is stored in each pixel. Several attempts have been made to reduce dimensional problems such as the feature selection using Adaboost and dimension reduction using the Simulated Annealing technique. We propose a novel material detection method that consists of four steps: feature band selection, feature extraction, SVM (Support Vector Machine) learning, and target and specific region detection. It is a combination of the band ratio method and Simulated Annealing algorithm based on detection rate. The experimental results validate the effectiveness of the proposed feature selection and band ratio method.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.115-123
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• 2016

In this study, we collect various side effect pairs which are appeared frequently at many drugs, and select side effect pairs that have higher severity. For every selected side effect pair, we extract common genetic networks which are shared by side effects' genes and drugs' target genes based on PPI(Protein-Protein Interaction) network. For this work, firstly, we gather drug related data, side effect data and PPI data. Secondly, for extracting common genetic network, we find shortest paths between drug target genes and side effect genes based on PPI network, and integrate these shortest paths. Thirdly, we develop a classification model which uses this common genetic network as a classifier. We calculate similarity score between the common genetic network and genetic network of a drug for classifying the drug. Lastly, we validate our classification model by means of AUC(Area Under the Curve) value.

• Journal of Korea Multimedia Society
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• v.25 no.7
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• pp.903-911
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• 2022

A shrimp quality detection model using YOLOv4 deep learning algorithm is designed, which is superior in terms of network architecture, data processing and feature extraction. The shrimp images were taken and data expanded on their own, the LableImage platform was used for data annotation, and the network model was trained under the Darknet framework. Through comparison, the final performance of the model was all higher than other common target detection models, and its detection accuracy reached 93.7% with an average detection time of 47 ms, indicating that the method can effectively detect the quality of shrimp in the production process.

• Applied Chemistry for Engineering
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• v.35 no.3
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• pp.222-229
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• 2024

The use of low-toxic, hypoallergenic, and environmentally friendly natural pigments has increased. With growing interest in health, research on natural extracts containing beneficial substances for the human body is actively underway. In this study, natural pigments were extracted from sprout barley using a solvent extraction method and CCD-RSM was used to optimize the extraction process. The experiment's independent variables included extraction temperature, alcohol/ultra-pure volume ratio, and extraction time. The response variables were set to achieve a target chromaticity (L = 45, a = -35, b = 45), and to maximize DPPH radical scavenging activity evaluating the antioxidant capacity. The statistical significance of the main effect, interaction effect, and effect on the response value was evaluated and analyzed through the F and P values for the regression equation variables calculated using RSM optimization. Additionally, the reliability of the experiment was also confirmed through the P values of the probability plot graph. The extraction conditions for optimizing the four reaction values are 76.1 vol.% alcohol/ultra pure water volume ratio, an extraction temperature of 52.9 ℃ , and an extraction time of 49.6 min. Under these conditions, the theoretical values of the reaction values are L = 45.4, a = -36.8, and b = 45.0 DPPH radical scavenging activity = 30.9%. When the actual experiment was conducted under these optimal extraction conditions and analyzed, the measured values were L = 46.2, a = -36.1, and b = 48.2, and antioxidant capacity = 31.1% with an average error rate of 2.9%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.697-704
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• 2003

In this paper, the visual tracking system for arbitrary shaped moving object is proposed. The established tracking system can be divided into model based method that needs previous model for target object and image based method that uses image feature. In the model based method, the reliable tracking is possible, but simplification of the shape is necessary and the application is restricted to definite target mod el. On the other hand, in the image based method, the process speed can be increased, but the shape information is lost and the tracking system is sensitive to image noise. The proposed tracking system is composed of the extraction process that recognizes the existence of moving object and tracking process that extracts dynamic characteristics and shape information of the target objects. Specially, active contour model is used to effectively track the object that is undergoing shape change. In initializatio n process of the contour model, the semi-automatic operation can be avoided and the convergence speed of the contour can be increased by the proposed effective initialization method. Also, for the efficient solution of the correspondence problem in multiple objects tracking, the variation function that uses the variation of position structure in image frame and snake energy level is proposed. In order to verify the validity and effectiveness of the proposed tracking system, real time tracking experiment for multiple moving objects is implemented.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.3
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• pp.159-167
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• 2017

Software safety is a key issue in embedded system of automotive and aviation industries. Various software testing approaches have been proposed to achieve software safety like ISO26262 Part 6 in automotive environment. In spite of one of the classic and basic approaches, stack memory is hard to estimating exactly because of uncertainty of target code generated by compiler and complex nested interrupt. In this paper, we propose an approach of analyzing the maximum stack usage statically from target binary code rather than the source code that also allows nested interrupts for determining the exact stack memory size. In our approach, determining maximum stack usage is divided into three steps: data extraction from ELF file, construction of call graph, and consideration of nested interrupt configurations for determining required stack size from the ISR (Interrupt Service Routine). Experimental results of the estimation of the maximum stack usage shows proposed approach is helpful for optimizing stack memory size and checking the stability of the program in the embedded system that especially supports nested interrupts.

• ETRI Journal
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• v.38 no.1
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• pp.70-80
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• 2016

This paper addresses the problem of robust waveform design for distributed multiple-radar systems (DMRSs) based on low probability of intercept (LPI), where signal-to-interference-plus-noise ratio (SINR) and mutual information (MI) are utilized as the metrics for target detection and information extraction, respectively. Recognizing that a precise characterization of a target spectrum is impossible to capture in practice, we consider that a target spectrum lies in an uncertainty class bounded by known upper and lower bounds. Based on this model, robust waveform design approaches for the DMRS are developed based on LPI-SINR and LPI-MI criteria, where the total transmitting energy is minimized for a given system performance. Numerical results show the effectiveness of the proposed approaches.

• Journal of Microbiology and Biotechnology
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• v.34 no.3
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• pp.681-688
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• 2024

The accurate and rapid detection of methicillin-resistance of Staphylococcus aureus (SA) holds significant clinical importance. However, the methicillin-resistance detection strategies commonly require complicated cell lysis and gene extraction. Herein, we devised a novel colorimetric approach for the sensitive and accurate identification of methicillin-resistance of SA by combining allosteric probe-based target recognition with self-primer elongation-based target recycling. The PBP2a aptamer in the allosteric probe successfully identified the target MRSA, leading to the initiation of self-primer elongation based-cascade signal amplification. The peroxidase-like hemin/G-quadruplex undergo an isothermal autonomous process that effectively catalyzes the oxidation of ABTS2- and produces a distinct blue color, enabling the visual identification of MRSA at low concentrations. The method offers a shorter duration for bacteria cultivation compared to traditional susceptibility testing methods, as well as simplified manual procedures for gene analysis. The overall amplification time for this test is 60 min, and it has a detection limit of 3 CFU/ml. In addition, the approach has exceptional selectivity and reproducibility, demonstrating commendable performance when tested with real samples. Due to its advantages, this colorimetric assay exhibits considerable potential for integration into a sensor kit, thereby offering a viable and convenient alternative for the prompt and on-site detection of MRSA in patients with skin and soft tissue infections.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.61-64
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• 2007

SAR 영상에 존재하는 군사표적은 광학 영상에 있는 군사표적에 비하여 쉽게 구별하기 힘들다. 이는 전체 영상에서 군사표적을 구성하는 픽셀의 수가 매우 적기 때문이다. 이러한 문제 때문에 SAR 영상 분석가들은 영상을 분석하는 것이 어렵다. 이 문제를 해결하기 위해서는 자동화된 분석 시스템이 필요하다. 본 논문에서는 기존에 연구된 SAR 영상을 이용한 자동표적추출 시스템을 분석하고 구현하였다. 구현된 자동표적추출 시스템을 MSTAR 데이터 셋을 이용하여 실험하여 결과를 도출하고， 그 결과를 분석하여 자동표적추출 시스템 각 단계의 성능을 분석하였다. 분석 결과 각 단계별로 최적의 성능을 보여주는 임계값을 알아낼 수 있었다.