• 한국식품저장유통학회지
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• 제5권3호
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• pp.292-298
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• 1998

부패하는 두부에서부터 각종 미생물 18종을 분리하여 동정한 결과, B. cereus, X. luminescens, A. calcoaceticus, Kl. pneumoniae, S. typhimurium, Pantoea sp., Bacillus sp., Cardiobacterium sp., E. coli, St. aureus, Yersinia sp. 등 11종의 각기 다른 미생물로 나타났다. 실온에서 두부의 부패 과정중 이들 미생물의 존재 함량은 B. cereus J55 23.37%, X. luminescens J48 22.37%, A. calcoaceticus J61 22.26%, X. Luminescens J48 22.73%, A. calcoaceticus J61 22.26%, Kl. pneumoniae J62 21.25%, S. typhimurium J51 2.87%, Pantoea sp. J57 2.65%, S. typhimurium J51 2.87%, Pantoea sp. J57 2.65%, Bacillus sp. J58 1.43%, Cardiobacterium sp. J54 1.26%, E. coli J53 1.20%, St. aureus J60 0.93%, Yersinia sp. J50 0.05%로 존재하였다. 이들 미생물을 각각 두부에 접종하여 두부 부패성을 조사한 결과, B. cereus J55, X. luminescens J48, Ac. calcoaceticus J61, Kl. pneumoniae J62 등 4종류의 균주는 두부부패를 진행시켰으며 심한 변패취를 내었고 액즙이 혼탁하여 미생물의 증식을 인지할 수 있었으며 또한 proteinase의 활성 및 amylase의 활성이 비교적 높게 나타났다. 그러나 나머지 7균주는 두부 부패에 큰 영향을 나타내지 않았다. 11종의 미생물에 대하여 각종 항생제 내성을 조사한 결과, amicacin, gentamicin, tobramycin 등 aminoside계 항생물질에 대해서는 높은 감수성을 나타내는 반면, penicillin G, oxacillin, cephalothin, cefazolin, cefamandole 등 $\beta$-lactamine계 항생제에 대해서 높은 내성을 가지고 있었다.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.89-95
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• 2023

Analyzing breast cancer patient files is becoming an exciting area of medical information analysis, especially with the increasing number of patient files. In this paper, breast cancer data is collected from Khartoum state hospital, and the dataset is classified into recurrence and no recurrence. The data is imbalanced, meaning that one of the two classes have more sample than the other. Many pre-processing techniques are applied to classify this imbalanced data, resampling, attribute selection, and handling missing values, and then different classifiers models are built. In the first experiment, five classifiers (ANN, REP TREE, SVM, and J48) are used, and in the second experiment, meta-learning algorithms (Bagging, Boosting, and Random subspace). Finally, the ensemble model is used. The best result was obtained from the ensemble model (Boosting with J48) with the highest accuracy 95.2797% among all the algorithms, followed by Bagging with J48(90.559%) and random subspace with J48(84.2657%). The breast cancer imbalanced dataset was classified into recurrence, and no recurrence with different classified algorithms and the best result was obtained from the ensemble model.

• 열처리공학회지
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• 제8권1호
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• pp.84-88
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• 1995

Various heat-treatments were conducted to Ti-48.1at%Al and Ti-48.3at%Al-1.2at%Mn alloys casted by plasma arc melting system. Mechanical properties, microstructure and high temperature oxidizing behaviors of as-casted and heat-treatment alloys were investigated. Ti-48.1Al and Ti-48.3Al-1.2Mn alloys were decreased in strength according to increased of heattreatment temperature. Oxidizing weight gain of Ti-48.1Al alloy which conducted at $1273^{\circ}K$ was linearly increased. In case of adding Mn to alloy, there was no rapid increase of oxidizing weight gain during early time.

• 대한수학회지
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• 제48권2호
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• pp.341-365
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• 2011

In this paper, we establish general stratawise higher jet evaluation transversality of J-holomorphic curves for a generic choice of almost complex structures J (tame to a given symplectic manifold (M, $\omega$)). Using this transversality result, we prove that there exists a subset $\cal{J}^{ram}_{\omega}\;{\subset}\;\cal{J}_{\omega}$ of second category such that for every $J\;{\in}\;\cal{J}^{ram}_{\omega}$, the dimension of the moduli space of (somewhere injective) J-holomorphic curves with a given ramication prole goes down by 2n or 2(n - 1) depending on whether the ramication degree goes up by one or a new ramication point is created. We also derive that for each $J\;{\in}\;\cal{J}^{ram}_{\omega}$ there are only a finite number of ramication profiles of J-holomorphic curves in a given homology class $\beta\;{\in}\;H_2$(M; $\mathbb{Z}$) and provide an explicit upper bound on the number of ramication proles in terms of $c_1(\beta)$ and the genus g of the domain surface.

• 한국자기학회:학술대회 개요집
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• 한국자기학회 2004년도 동계학술연구발표회 논문개요집
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• pp.48-48
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• 2004

• 한국지반환경공학회 논문집
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• 제23권3호
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• pp.5-13
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• 2022

본 논문은 기존에 설치되어있는 국내 일반도로용, 고속도로용 낙석방지울타리의 방호성능을 알아보기 위해 100kJ급의 낙석에너지를 이용한 취약부위를 파악하기 위한 시험을 실시하였다. 국내의 경우 국외에 비해 낙석방지울타리의 성능 등급(48~61kJ)이 매우 낮은 편이다. 만약 높은 낙석에너지가 발생했을 시 기능을 제대로 할 수 있는지 파악할 필요가 있으며, 또한 더 나아가 기존에 설치된 낙석방지울타리에 100kJ급으로 향상시킬 수 있는 보강 기술이 개발되어야 한다. 따라서 본 연구는 기존의 낙석방지울타리 시스템(일반도로용, 고속도로용)에 100kJ급 낙석에너지를 이용하여 방호성능을 확인하고, 지주 및 와이어로프, 망의 취약부위를 파악하며, 나아가 기존 설치되어있는 낙석방지울타리(48~61kJ)를 해체하지 않고 100kJ급의 보강 기술을 개발하기 위한 기초 자료로 사용될 예정이다.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2005년도 제28회 학술발표회 초록집
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• pp.48-48
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• 2005

• 한국인공지능학회지
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• 제4권1호
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• pp.11-13
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• 2016

These days, medical technology has been developed rapidly to meet desire of living healthy life. Average lifespan was extended to let people see a doctor because of many reasons. This study has shown rate of leaving of hospitals to investigate the rate of not only department of surgery but also department of internal medicine. Linear model, tree, classification rule, association and algorithm of data mining were used. This study investigated by using J48 and AD tree of decision-making tree In this study, J48 and AD tree of decision-making tree of data mining were used to investigate based on result of both data. Both algorithms were found to have similar performance. Both algorithms were not equivalent to require detailed experiment. Collect more experimental data in the future to apply from various points of view. Development of medical technology gives dream, hope and pleasure. The ones who suffer from incurable diseases need developed medical technology. Environment being similar to the reality shall be made to experiment exactly to investigate data carefully and to let the ones of various ages visit hospital and to increase survival rate.

• International journal of advanced smart convergence
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• 제5권1호
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• pp.30-33
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• 2016

With the advent of big data, data mining is more increasingly utilized in various decision-making fields by extracting hidden and meaningful information from large amounts of data. Even as exponential increase of the request of unrevealing the hidden meaning behind data, it becomes more and more important to decide to select which data mining algorithm and how to use it. There are several mainly used data mining algorithms in biology and clinics highlighted; Logistic regression, Neural networks, Supportvector machine, and variety of statistical techniques. In this paper it is attempted to compare the classification performance of an exemplary algorithm J48 and REPTree of ML algorithms. It is confirmed that more accurate classification algorithm is provided by the performance comparison results. More accurate prediction is possible with the algorithm for the goal of experiment. Based on this, it is expected to be relatively difficult visually detailed classification and distinction.

• 대한임상약리학회:학술대회논문집
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• 대한임상약리학회 1999년도 제8차 추계학술대회 및 정기총회
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• pp.48-48
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• 1999