• Food Science and Preservation
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• v.5 no.3
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• pp.292-298
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• 1998

The isolates from putrefying soybean curd were identified as Acinetobacter calcoaceticus, Bacillus cereus, Bacillus sp., Cardiobacterium sp., Escherichia coli, Klebsiella pneumoniae, Pantoea sp., Salmonella typhimurium, Staphylococcus aureus, Xenorhabdus luminescens, Yersinia sp.. The existence percentages of the bacteria from putrefying soybean curd at room temperature storage were Bacillus cereus J55 23.57%, Xenorhabdus luminescens J48 22.73%, Acinetobacter calcoaceticus J61 22.26%, Klebsiella pneumoniae J62 21.25%, Salmonella typhimurium J51 2.87%, Pantoea sp. J57 2.65%, Bacillus sp. J58 1.43%, Cardiobacterium sp. J54 1.26%, Escherichia coli J53 1.20%, Staphvlococcus aureus J6O 0.93%, Yersinia sp. J50 0.05%, respectively. Four out of eleven bacteria as B. cereu J55, X. luminescens J48, Ac. calcoaceticus J61, Kl. pneumoniae J62 putrefied soybean curd and those bacteria produce amylase or proteinase as a extracellular enzyme. But S. typhimurium J51, Pantoea sp. J57, Bacillus sp. J58, Cardiobacterium sp. J54, E. coli 153, St. aureus J60, Yersinia sp. J50 were not putrefied soybean curd. The isolates detected to resistant on various antimicrobial agents. The majority were resistant to aminoside antiboitics as amicacin, gentamicin, tobramycin and were susceptible to ${\beta}$-lactamine antibiotics as penicillin G, oxacillin, cephalothin cefazolin, cefamandole.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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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.

• Journal of the Korean Society for Heat Treatment
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• v.8 no.1
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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.

• Journal of the Korean Mathematical Society
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• v.48 no.2
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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.

• Proceedings of the Korean Magnestics Society Conference
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• 2004.12a
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• pp.48-48
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• 2004

• Journal of the Korean GEO-environmental Society
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• v.23 no.3
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• pp.5-13
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• 2022

In this study a test was conducted to identify weak section using 100kJ class rock energy to find out the protection performance of rockfall prevention fences in Korea. Performance rating of the rockfall protection fences is very low (48~61kJ) compared to that of foreign countries and it is necessary to determine whether it can function properly if high rock energy is generated. Furthermore, a reinforcing technology that can improve to 100kJ energy on the existing rockfall protection fences should be developed. Therefore, this study confirmed the protection performance using 100kJ rock energy in the existing rockfall protection fence system (for national road, for highway) and identified weak section of post, wire ropes and nets. Furthermore, it will be used as basic data for developing 100kJ class reinforcement technology without dismantling the existing rockfall protection fence (48-61kJ).

• Proceedings of the Korean Vacuum Society Conference
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• 2005.02a
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• pp.48-48
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• 2005

• Korean Journal of Artificial Intelligence
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• v.4 no.1
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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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• v.5 no.1
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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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• 1999.12a
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• pp.48-48
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• 1999