• Journal of Microbiology
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• 제45권4호
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• pp.350-357
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• 2007

This study was conducted in an effort to evaluate the antimicrobial activity and antibiotic-resistant gene regulation from Saliva miltiorrhiza Bunge on methicillin-resistant Staphylococcus aureus (MRSA). A variety of solvent fractions and methanol extracts of S. miltiorrhiza Bunge were tested in order to determine its antimicrobial activities against S. aureus and MRSA. As a result, the hexane fraction of S. miltiorrhiza Bunge evidenced the highest levels of antimicrobial activity against S. aureus and MRSA. The MICs of the hexane fraction against various MRSA specimens were $64. The hexane fraction evidenced inhibitory effects superior to those of the chloroform fraction. The results showed inhibition zones of hexane (16 mm) and chloroform (14 mm) fractions against MRSA KCCM 40511 at $1,000{\mu}g/disc$. The hexane and chloroform fractions inhibited the expression of the resistant genes, mecA, mecR1, and femA in mRNA. Moreover, the results of Western blotting assays indicated that the hexane and chloroform fractions inhibited the expression of the resistant protein, PBP2a. These results reveal that the hexane and chloroform fractions of S. miltiorrhiza Bunge may prove to be a valuable choice for studies targeted toward the development of new antimicrobial agents.

• 대한전기학회논문지
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• 제45권1호
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• pp.113-122
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• 1996

As integrity of semiconductor device is increased, accurate and efficient modeling and recipe generation of semiconductor fabrication procsses are necessary. Among the major semiconductor manufacturing processes, dry etc- hing process using gas plasma and accelerated ion is widely used. The process involves a variety of the chemical and physical effects of gas and accelerated ions. Despite the increased popularity, the complex internal characteristics made efficient modeling difficult. Because of difficulty to determine the control input for the desired output, the recipe generation depends largely on experiences of the experts with several trial and error presently. In this paper, the optimal control of the etching is carried out in the following two phases. First, the optimal neural network models for etching process are developed with genetic algorithm utilizing the input and output data obtained by experiments. In the second phase, search for optimal control inputs in performed by means of using the optimal neural network developed together with genetic algorithm. The results of study indicate that the predictive capabilities of the neural network models are superior to that of the statistical models which have been widely utilized in the semiconductor factory lines. Search for optimal control inputs using genetic algorithm is proved to be efficient by experiments. (author). refs., figs., tabs.

• 대한산업공학회지
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• 제25권4호
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• pp.411-420
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• 1999

A mixed model production line is a production line where a variety of product models are produced. In U-shaped production lines (called U-lines) used in just-in-time production system, the strategy of mixing product models is often used to provide various types of products to customers in time. Line balancing and model sequencing problems are important for an efficient use of mixed model U-lines. Although the two problems are tightly interrelated with each other, prior researches have considered them separately or sequentially. This paper presents a new method using a coevolutionary algorithm that can solve the two problems at the same time. To promote diversity and search efficiency, in this paper the evolutionary system is based on the localized interactions within and between populations. Methods of selecting environmental individuals and evaluating fitness are developed. Efficient genetic representations and operator schemes are also provided. When designing the schemes, we take into account the features specific to the problems. The experimental results demonstrate that the proposed algorithm is superior to existing approaches.

• Journal of Information Processing Systems
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• 제13권1호
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• pp.40-56
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• 2017

Since the progress of digital medical imaging techniques, it has been needed to compress the variety of medical images. In medical imaging, reversible compression of image's region of interest (ROI) which is diagnostically relevant is considered essential. Then, improving the global compression rate of the image can also be obtained by separately coding the ROI part and the remaining image (called background). For this purpose, the present work proposes an efficient reversible discrete cosine transform (RDCT) based embedded image coder designed for lossless ROI coding in very high compression ratio. Motivated by the wavelet structure of DCT, the proposed rearranged structure is well coupled with a lossless embedded zerotree wavelet coder (LEZW), while the background is highly compressed using the set partitioning in hierarchical trees (SPIHT) technique. Results coding shows that the performance of the proposed new coder is much superior to that of various state-of-art still image compression methods.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2008년도 춘계학술대회 논문집
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• pp.507-511
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• 2008

LTCC (Low Temperature Co-fired Ceramic) has been successfully applied to ceramic substrates for circuits and micro-fluidic systems and has proven its superior performance in a variety of applications. The prediction of shrinkage in LTCC process is an important for dimensional control of micro LTCC products which has influences on electronic characteristics. For avoiding the unpredictable shrinkage of LTCC during the sintering which makes accurate placement of the circuit devices difficult, pre-processes such as WIP (Warm Isostatic Pressing) and lamination must be modified. The objective of the present investigation is to establish a proper WIP conditions for near net shape fabrication of LTCC products. This paper discusses the influence of WIP conditions on the dimensional change of LTCC sheet. In the investigation, it is shown that the shrinkage values of sheets depend on WIP conditions and sheet directions. This work is a quantitative evaluation of the effect of WIP pressure on shrinkage of LTCC sheet. Additionally, the results show anisotropic shrinkage behaviour of sheet during LTCC process.

• Structural Engineering and Mechanics
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• 제19권3호
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• pp.321-336
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• 2005

The structural feasibility of a variety of non-conventional sludge digesters, in the form of thin shells of revolution constructed in concrete, has formed the subject of investigation of a recent programme of research at the University of Cape Town. Such forms are usually known in the literature as "egg-shaped", and the advantages of these over conventional digesters of the wide-cylindrical type are now well-recognised: superior mixing efficiency, less accumulation of deposits at the bottom, easier removal of bottom deposits and surface crust, reduced heat losses, and so forth. With the aim of exploring the structural feasibility of various non-conventional forms for concrete sludge digesters, and making available usable analytical data and practical guidelines for the design of such thin shell structures, a number of theoretical studies have recently been undertaken, and these have covered conical assemblies, spherical assemblies and parabolic ogival configurations. The purpose of the present paper is to bring together the different analytical approaches employed in each of these studies, summarise the main findings in each case, draw comparisons among the various studied configurations with regard to structural efficiency and functional suitability, and make appropriate conclusions and recommendations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2028-2041
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• 2019

Compressed sensing (CS) is a new theory. With regard to the sparse signal, an exact reconstruction can be obtained with sufficient CS measurements. Nevertheless, in practical applications, the transform coefficients of many signals usually have weak sparsity and suffer from a variety of noise disturbances. What's worse, most existing classical algorithms are not able to effectively solve this issue. So we proposed an efficient algorithm based on smoothed ${\ell}_0$ norm for sparse signal reconstruction. The direct ${\ell}_0$ norm problem is NP hard, but it is unrealistic to directly solve the ${\ell}_0$ norm problem for the reconstruction of the sparse signal. To select a suitable sequence of smoothed function and solve the ${\ell}_0$ norm optimization problem effectively, we come up with a generalized approximate function model as the objective function to calculate the original signal. The proposed model preserves sharper edges, which is better than any other existing norm based algorithm. As a result, following this model, extensive simulations show that the proposed algorithm is superior to the similar algorithms used for solving the same problem.

• BioChip Journal
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• 제12권4호
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• pp.257-267
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• 2018

Inertial microfluidics has attracted significant attention in recent years due to its superior benefits of high throughput, precise control, simplicity, and low cost. Many inertial microfluidic applications have been demonstrated for physiological sample processing, clinical diagnostics, and environmental monitoring and cleanup. In this review, we discuss the fundamental mechanisms and principles of inertial migration and Dean flow, which are the basis of inertial microfluidics, and provide basic scaling laws for designing the inertial microfluidic devices. This will allow end-users with diverse backgrounds to more easily take advantage of the inertial microfluidic technologies in a wide range of applications. A variety of recent applications are also classified according to the structure of the microchannel: straight channels and curved channels. Finally, several future perspectives of employing fluid inertia in microfluidic-based cell sorting are discussed. Inertial microfluidics is still expected to be promising in the near future with more novel designs using various shapes of cross section, sheath flows with different viscosities, or technologies that target micron and submicron bioparticles.

• 한국인터넷방송통신학회논문지
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• 제18권6호
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• pp.151-156
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• 2018

필기체 숫자인식은 일반적으로 높은 인식률과 문맥 독립이 요구되고 있고, 쓰는 사람에 따라서 많은 차이점이 있어서 자유 필기체 숫자는 인식이나 알고리즘작성에 아직도 어려운 문제점이 있다. 본 연구에서는, 필기체 숫자의 특성을 분석하고, 구조적 특징기반 자유 필기체 숫자인식 알고리즘을 새롭게 제안한다. 주어진 필기 숫자에 대하여, 끝점과 분기점, 수평선과 함께 숫자의 구조적 특징을 연구한다. 이 방법은 확장된 구조적 특징 알고리즘으로 제안되어 강인하며, 그리고 본 연구에서 제안한 구조적 특징에 기반 한 결정 트리(decision tree)는 필기체 숫자 자동인식방법에 구조적으로 기여한다. 본 알고리즘이 다른 방법과 비교하여 인식률과 강인성이 우수함을 실험결과로 보여주었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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• pp.5765-5781
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• 2018

Extreme learning machine (ELM) is emerging as a powerful machine learning method in a variety of application scenarios due to its promising advantages of high accuracy, fast learning speed and easy of implementation. However, how to select the optimal hidden layer of ELM is still an open question in the ELM community. Basically, the number of hidden layer nodes is a sensitive hyperparameter that significantly affects the performance of ELM. To address this challenging problem, we propose to adopt multiple kernel learning (MKL) to design a multi-hidden-layer-kernel ELM (MHLK-ELM). Specifically, we first integrate kernel functions with random feature mapping of ELM to design a hidden-layer-kernel ELM (HLK-ELM), which serves as the base of MHLK-ELM. Then, we utilize the MKL method to propose two versions of MHLK-ELMs, called sparse and non-sparse MHLK-ELMs. Both two types of MHLK-ELMs can effectively find out the optimal linear combination of multiple HLK-ELMs for different classification and regression problems. Experimental results on seven data sets, among which three data sets are relevant to classification and four ones are relevant to regression, demonstrate that the proposed MHLK-ELM achieves superior performance compared with conventional ELM and basic HLK-ELM.