• Biotechnology and Bioprocess Engineering:BBE
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• 제5권2호
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• pp.84-91
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• 2000

Mycopasma contamination of tissue culture cells easily evades detection and, thus, represents a continous therat to cell biologists. In case where infected cell can not simply be replaced, attempts have to be made to eradicate mycoplacma from the tissue culture cells. A variety of anti-microbial agents have been shown to be toxic to mycoplasma strains ; however, cell associated mycoplasma are often protected from antibiotics at concentrations shown to be effective in vitro. Antibiotic concentrations high enough to be lethal to cell as sociated mycoplasmas frequently are also detrimentrations to the host cells, while moderately increased antibiotic levels tolerated by the host cells often lead to only temporary growth suppression and/or to the emergence of mycoplasma strains resistanct even to high concentrations of the antibiotis applied. Hare, a genetic approach for the elimination of mycoplasma from tissue culture cells that overcomes thens limitations is described. By expression of a selection marker conferring resistance to an otherwise toxic agent, Acholeplasma laidlawii infected BHK-21 cells used as the model system were enabled to temporarily tolerate antibiotic concentrations high enough to be lethal to cell associated mycopalsma while leaving the host cells unharmed. Upon successful mycoplasma eradicated, cultvation of the cured host cells in the absence of the selective agent yielded revertant cell clones that had regained susceptibillity to the toxic agent. Cressation of the selection marker expression was shown to result from the loss of the selection marker DNA, which is a consequence of the fact that the stable and permanent integration of foreign DNA in eucaryotic cell chrosomes is highly inefficient. Thus, the cells were cured from mycoplasma yet remained biochemically unaltered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.80-96
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• 2022

Nowadays, artificial intelligence promotes the rapid development of skin cancer detection technology, and the federated skin cancer detection model (FSDM) and dual generative adversarial network model (DGANM) solves the fragmentation and privacy of data to a certain extent. To overcome the problem that the many-objective evolutionary algorithm (MaOEA) cannot guarantee the convergence and diversity of the population when solving the above models, a many-objective evolutionary algorithm based on integrated strategy (MaOEA-IS) is proposed. First, the idea of federated learning is introduced into population mutation, the new parents are generated through sub-populations employs different mating selection operators. Then, the distance between each solution to the ideal point (SID) and the Achievement Scalarizing Function (ASF) value of each solution are considered comprehensively for environment selection, meanwhile, the elimination mechanism is used to carry out the select offspring operation. Eventually, the FSDM and DGANM are solved through MaOEA-IS. The experimental results show that the MaOEA-IS has better convergence and diversity, and it has superior performance in solving the FSDM and DGANM. The proposed MaOEA-IS provides more reasonable solutions scheme for many scholars of skin cancer detection and promotes the progress of intelligent medicine.

• Asian-Australasian Journal of Animal Sciences
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• 제12권2호
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• pp.244-252
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• 1999

Intensive selection for muscle development and against fat deposition in pigs during the last 50 years has contributed to the increased incidence of porcine stress syndrome (PSS) and pale soft exudative pork (PSE). Genetics, nutrition and management, preslaughter animal handling, stunning, dehairing and carcass chilling influence the incidence and magnitude of the PSE condition. The normal incidence of PSE has been reported to range from 10 to 30%, but in some isolated instances is up to 60%. The elimination of halothane-positive pigs in breeding programs has reduced PSS and PSE. Further improvements in meat quality by terminal sire evaluation and selection can be achieved within halothane-negative populations because around 20% of the variation in meat color and water binding capacity seems to be genetically related. Pre-slaughter handling on the farm, during transit to the packing plant and at the packing plant can greatly influence the meat quality, contributing 10 to 25% of the variation. An effective stunning method, skinning instead of scalding/dehairing and rapid post-slaughter chilling further reduce the incidence of PSE pork. In addition to proper care and handling a carcass-merit based marketing system, that reflected the value differential between desirable and undesirable meat quality in the pricing system for pigs, would provide a great incentive to change pork production systems in order to improve meat quality, thus improving the image and usefulness of pork as food.

• 제어로봇시스템학회논문지
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• 제16권2호
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• pp.188-193
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• 2010

With GPS being the primary navigation system, Loran use is in steep decline. However, according to the final report of vulnerability assessment of the transportation infrastructure relying on the global positioning system prepared by the John A. Volpe National Transportation Systems Center, there are current attempts to enhance and re-popularize Loran as a GPS backup system through the characteristic of the ground based low frequency navigation system. To advance the Loran system such as Loran-C modernization and eLoran development, research is definitely needed in the field of Loran-C receiver signal processing as well as Loran-C signal design and the technology of a receiver. We have developed a set of Matlab tools, which implement a software Loran-C receiver that performs the receiver's position determination through the following procedure. The procedure consists of receiving the Loran-C signal, cycle selection, calculation of the TDOA and range, and receiver's position determination through the Least Square Method. We experiences the effect of an incorrect cycle selection and various error factors (ECD, ASF, sky wave, CRI, etc.) from the result of the Loran-C signal processing. It is apparent that researches which focus on the elimination and mitigation of various error factors need to be investigated on a software Loran-C receiver. These aspects will be explored in further work through the method such as PLL and Kalman filtering.

• 한국정보기술학회논문지
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• 제16권12호
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• pp.25-30
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• 2018

유전자 규정 네트워크 (GRN)에 RNA-시퀀싱 데이터를 활용할 때, 해당 유전자와 환경과의 상호 작용에 의해서 생기는 형질들 중에서 연관성이 높은 유전자로 GRN을 구성하는 것은 상당히 어려운 일이다. 본 연구에서는 Big-Data의 RNA-시퀀싱 자료들로, 지지 벡터 머신 회귀 특징 추출(SVM-RFE) 에 근거하여, 연관성이 높은 유전자(maximum-relevancy)는 추출하고, 연관성이 낮은 유전자(minimum-redundancy)는 제거하는 MRMR 필터 방법을 집중도 의존 정규화(intensity-dependent normalization, DEGSEQ)에 기반 하여 데이터의 정밀성을 높여, 소수 연관성 높은 유전자만 판별해 내는 방법을 사용한다. 제안한 방법은 R 언어 패키지를 사용하여 편리함과 동시에, 다른 기존의 방법을 비교하였을 때, Big-Data의 시간 활용도를 높이면서, 동시에 높은 연관성 있는 유전자만을 잘 추출해 냄을 확인하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권10호
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• pp.733-740
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• 2004

In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) is proposed. The whole system consists of two-lead electrocardiogram acquisition (lead Ⅰ and Ⅱ), baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problem of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we proposed a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 subjects, and we could obtain satisfactory respiration signals that shows high correlation (r>0.9) with the signal acquired from the chest-belt respiration sensor.

• 지능정보연구
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• 제26권4호
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• pp.173-198
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• 2020

최근 온라인의 비약적인 활성화로 캠페인 채널들이 다양하게 확대되면서 과거와는 비교할 수 없을 수준의 다양한 유형들의 캠페인들이 기업에서 수행되고 있다. 하지만, 고객의 입장에서는 중복 노출로 인한 캠페인에 대한 피로감이 커지면서 스팸으로 인식하는 경향이 있고, 기업입장에서도 캠페인에 투자하는 비용은 점점 더 늘어났지만 실제 캠페인 성공률은 오히려 더 낮아지고 있는 등 캠페인 자체의 효용성이 낮아지고 있다는 문제점이 있어 실무적으로 캠페인의 효과를 높이고자 하는 다양한 연구들이 지속되고 있다. 특히 최근에는 기계학습을 이용하여 캠페인의 반응과 관련된 다양한 예측을 해보려는 시도들이 진행되고 있는데, 이 때 캠페인 데이터의 다양한 특징들로 인해 적절한 특징을 선별하는 것은 매우 중요하다. 전통적인 특징 선택 기법으로 탐욕 알고리즘(Greedy Algorithm) 중 SFS(Sequential Forward Selection), SBS(Sequential Backward Selection), SFFS(Sequential Floating Forward Selection) 등이 많이 사용되었지만 최적 특징만을 학습하는 모델을 생성하기 때문에 과적합의 위험이 크고, 특징이 많은 경우 분류 예측 성능 하락 및 학습시간이 많이 소요된다는 한계점이 있다. 이에 본 연구에서는 기존의 캠페인에서의 효과성 제고를 위해 개선된 방식의 특징 선택 알고리즘을 제안한다. 본 연구의 목적은 캠페인 시스템에서 처리해야 하는 데이터의 통계학적 특성을 이용하여 기계 학습 모델 성능 향상의 기반이 되는 특징 부분 집합을 탐색하는 과정에서 기존의 SFFS의 순차방식을 개선하는 것이다. 구체적으로 특징들의 데이터 변형을 통해 성능에 영향을 많이 끼치는 특징들을 먼저 도출하고 부정적인 영향을 미치는 특징들은 제거를 한 후 순차방식을 적용하여 탐색 성능에 대한 효율을 높이고 일반화된 예측이 가능하도록 개선된 알고리즘을 적용하였다. 실제 캠페인 데이터를 이용해 성능을 검증한 결과, 전통적인 탐욕알고리즘은 물론 유전자알고리즘(GA, Genetic Algorithm), RFE(Recursive Feature Elimination) 같은 기존 모형들 보다 제안된 모형이 보다 우수한 탐색 성능과 예측 성능을 보임을 확인할 수 있었다. 또한 제안 특징 선택 알고리즘은 도출된 특징들의 중요도를 제공하여 예측 결과의 분석 및 해석에도 도움을 줄 수 있다. 이를 통해 캠페인 유형별로 중요 특징에 대한 분석과 이해가 가능할 것으로 기대된다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.337-339
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• 2004

In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs). Proceeding the layer, this model creates the optimal network architecture through the selection and the elimination of nodes by itself. So, there is characteristic of flexibility. We use a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. GAs is applied to improve the performance with optimal input variables and number of input variables and order. To evaluate the performance of the GAs-based FPNNs, the models are experimented with the use of Medical Imaging System(MIS) data.

• 한국정보과학회논문지:소프트웨어및응용
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• 제29권4호
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• pp.248-257
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• 2002

군집화는 객체들의 특성을 분석하여 유사한 성질을 갖고 있는 객체들을 동일한 집단으로 분류하는 방법이다. 전자 상거래 자료처럼 차원 수가 많고 누락 값이 많은 자료의 경우 입력 자료의 차원축약, 잡음제거를 목적으로 SVD를 사용하여 군집화를 수행하는 것이 효과적이지만, SVD를 통해 변환된 자료는 원래의 속성 정보를 상실하기 때문에 군집 결과분석에서 원본 속성의 가치 해석이 어렵다. 따라서 본 연구는 군집화 수행 후 엔트로피 가중치 및 SVD를 이용하여 군집의 중요한 속성을 발견하기 위한 군집 특징 선택 기법 ENTROPY-SVD를 제안한다. ENTROPY-SVD는 자료의 속성들과 유사객체 군과의 묵시적인 은닉 구조를 활용하기 위하여 SVD를 이용하고 유사객체 군에 포함된 응집도가 높은 속성들을 발견하기 위하여 엔트로피 가중치를 사용한다. 또한 ENTROPY-SVD를 적용한 모델 기반의 협력적 여과기법의 추천 시스템 CFS-CF를 제안하고 그 효용성 및 효과를 평가한다.

• 한국표면공학회지
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• 제35권4호
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• pp.218-231
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• 2002

As the environmental regulation worldwide emerges, most notably in Europe and Japan, the elimination of Pb usage in electronic assemblies has been an important issue for microelectronics assembly due to the inherent toxicity of Pb. This has provided an impetus towards the development of Pb-free solders. A major factor affecting alloy selection is the melting point, since this will have a major impact on the other polymeric materials used in microelectronic assembly and encapsulation. Other important manufacturing issues are cost, availability, and wetting characteristics. Reliability related properties include mechanical strength, fatigue resistance, coefficient of thermal expansion and reactivity with substrate. In this article, Pb-free solder alloys have been proposed so far have been reviewed and are summarized.