• Journal of Microbiology and Biotechnology
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• v.14 no.1
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• pp.134-139
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• 2004

Hybrid cluster protein (HCP) was investigated because of its unique iron-sulfur clusters, which have been found in bacteria and archaea. Here, HCP homologous proteins from the third domain, 'eukarya'(3 amitochondriate protozoans, Giardia lamblia, Entamoeba histolytica, and Trichomonas vaginalis), were identified. All three amitochondriate protozoan HCPs (GlHCP, EhHCP, and TvHCP) belonged to Class I on the basis of two key characters, the cysteine spacing, Cys-(Xaa)₂Cys(Xaa)/sub 7-8/-Cys(Xaa)/sub 5/-Cys, and the absence of N-terminal deletion characteristic to the Class III. In phylogenetic analysis performed with amino acid sequences of 3 eukaryal, 5 bacterial, and 4 archaeal HCPs, the maximum likelihood (ML) tree indicated that TvHCP was clustered with Class I HCPs, whereas the other two HCPs (GlHCP and EhHCP) formed an independent clade with a high bootstrapping value (96%) not belonging to any previously recognized HCP class. In spite of the relatively lower bootstrapping value (61%), the position of the new eukaryal GlHCP-EhHCP clade was close to Class I, including the TvHCP, and Classes II and III were closely related with each other. The finding of eukaryal HCPs would help to understand the evolutionary history of HCP.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.125-140
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• 2013

We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.811-818
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• 2016

This paper suggests a structure of power control system in floating wave-offshore wind hybrid power generation system. We have developed an unified SCADA(Supervisory Control and Data Acquisition) system which can be used to monitor and control PCS(Power Conversion System) based on IEC61850. The SCADA system is essential to perform the algorithm like proportional distribution and data acquisition, monitoring, active power, reactive power control in hybrid power generation system. IEC61850 is an international standard for electrical substation automation systems. It was made to compensate the limitations of the legacy industrial protocols such as Modbus. In order to test the proposed SCADA system and algorithm, we have developed the wind-wave simulator based Modbus. We have designed a protocol conversion device based on real-time Linux for the communication between Modbus and IEC61850. In this study, SCADA system consists of four 3MW class wind turbines and twenty-four 100kW class wave force generator.

• Journal of Information Technology Applications and Management
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• v.29 no.6
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• pp.81-93
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• 2022

As deep learning technology in natural language and visual processing has rapidly developed, collaborative filtering-based recommendation systems using deep learning technology are being actively introduced in the recommendation field. In this study, OCF-GAN, a hybrid collaborative filtering model using GAN, was proposed to solve the one-class and cold-start problems, and its usefulness was verified through performance evaluation. OCF-GAN based on conditional GAN consists of a generator that generates a pattern similar to the actual user preference pattern and a discriminator that tries to distinguish the actual preference pattern from the generated preference pattern. When the training is completed, user preference vectors are generated based on the actual distribution of preferred items. In addition, the cold-start problem was solved by using a hybrid collaborative filtering recommendation method that additionally utilizes user and item profiles. As a result of the performance evaluation, it was found that the performance of the OCF-GAN with additional information was superior in all indicators of the Top 5 and Top 20 recommendations compared to the existing GAN-based recommender. This phenomenon was more clearly revealed in experiments with cold-start users and items.

• Communications of the Korean Mathematical Society
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• v.28 no.1
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• pp.135-141
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• 2013

In this paper, we first talk about a more wide class of nonlinear mappings, Then, we deal with weak convergence theorems for generalized hybrid mappings in a Hilbert space.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.517-522
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• 2000

When a real robot manipulator is mathematically modeled. uncertainties are not avoidable. The uncertainties are often nonlinear and time-varying. The uncertain factors collie from imperfect knowledge ok system parameters. payload change. friction. external disturbance. and etc. In this paper. we propose a class of robust hybrid controls of manipulators without knowing the exact stiffness and provide the stability analysis. Simulation results are provided to show the effectiveness of the algorithms.

• Restorative Dentistry and Endodontics
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• v.27 no.1
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• pp.34-43
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• 2002

The purpose of this study was to compare microleakage and marginal hybrid layer in class V restorations using two one-bottle adhesives and one self-etching adhesive. Class V cavity preparations with occlusal margins in enamel and gingival margins in dentin were pre-pared on buccal and lingual surfaces of 30 extracted human molar teeth. Prepared teeth were randomly divided into three treatment groups (n=30) and restored with three adhesives and composites: Single Bond/Filtek Z-250 (Group 1), Prime&BondNT/Esthet.X (Group 2), UniFil Bond/UniFil F (Group 3). For microleakage, samples were stored in room temperature water for 24 hours, thermocycled stained with 2% methylene blue dye, sectioned into halves, scored and analysed using Mann-whitney test and Wilcoxon signed rank sum test. For marginal hybrid layer, samples were sectioned into halves, treated with 10% phosphoric acid for 5 seconds, stored in 5% NaOCL solution for 24 hours, dried and gold coated. Occlusal and gingival margins of each sample were inspected under SEM. The results of this study were as follows ; 1. Microleakage at the occlusal margins was not evident in group 1 and group 2, but it showed in group 3 (p<0.05). 2. Microleakage in group 1 and group 3 was significantly lower than in group 2 at gingival margins (p<0.05). 3. Microleakage at gingival margins was greater than at occlusal margins in group 1 and group 2, but microleakage at occlusal margins was greater than at gingival margins in group 3 (p<0.05). 4. In group 1 and group 2, no gaps at occlusal margins showed. But gaps showed in group 3. Occlusal margins were free from a hybrid layer in all groups 5. The thickness of the marginal hybrid layers was 2.5~5 $\mu\textrm{m}$ thick in group 5 $\mu\textrm{m}$ thick in group 2 and 1.5 $\mu\textrm{m}$ thick in group 3. 6 There was no corelation between microleakage and thickness of marginal hybrid layer. In coclusion, the effect of dentin adhesives on microleakge in class V composite restorations was excellent when one-bottle adhesives were applied on enamel margin, and it was good when a self-etching adhesive was applied on dentinal margin. There was no corelation between microleakage and thickness of marginal hybrid layer.

• The korean journal of orthodontics
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• v.49 no.5
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• pp.338-346
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• 2019

In this report, we describe the successful use of alternate rapid maxillary expansions and constrictions with a hybrid hyrax-mandibular miniplate combination and simultaneous orthodontic treatment for the management of severe Class III malocclusion due to maxillary hypoplasia in an 11-year-old girl. The devices were removed after 20 months of treatment, and the family was instructed about a careful control and retention program that should be followed in accordance with the patient's growth. The final result included the correction of Class III malocclusion with adequate function and excellent facial esthetics, which restored the patient's self-esteem and provided personal motivation. The outcomes showed good stability after 24 months of retention. The decrease in the duration of active treatment is the most important finding from the present case. Considering that facial esthetics in adolescence is a determining factor for the development of a personality and interpersonal relationships, we recommend the use of this protocol for growing patients, who will exhibit not only an improved physical appearance but also a better quality of life.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.683-696
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• 2020

The aim of this research is to find an optimal gene set that provides highly accurate multi-class classification with a minimum number of genes. A two-stage procedure is proposed: Based on minimum redundancy and maximum relevance (mRMR) framework, several statistics to rank differential expression genes and K-means clustering to reduce redundancy between genes are used for data filtering procedure. And a particle swarm optimization is modified to select a small subset of informative genes. Two well known multi-class microarray data sets, ALL and SRBCT, are analyzed to indicate the effectiveness of this hybrid method.

• Restorative Dentistry and Endodontics
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• v.47 no.1
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• pp.5.1-5.11
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• 2022

Objectives: This study aimed to assess the clinical longevity of a bulk-fill resin composite in Class II restorations for 3-year. Materials and Methods: Patient record files acquired from the 40 patients who were treated due to needed 2 similar sizes Class II composite restorations were used for this retrospective study. In the experimental cavity, the flowable resin composite SDR was inserted in the dentinal part as a 4 mm intermediate layer. A 2 mm coverage layer with a nano-hybrid resin composite (CeramX) was placed on SDR. The control restoration was performed by an incremental technique of 2 mm using the nano-hybrid resin composite. The restorations were blindly assessed by 2 calibrated examiners using modified United States Public Health Service criteria at baseline and 1, 2, and 3 years. The data were analyzed using non-parametric tests (p = 0.05). Results: Eighty Class II restorations were evaluated. After 3-years, 4 restorations (5%) failed, 1 SDR + CeramX, and 3 CeramX restorations. The annual failure rate (AFR) of the restorations was 1.7%. The SDR + CeramX group revealed an AFR of 0.8%, and the CeramX group an AFR of 2.5% (p > 0.05). Regarding anatomical form and marginal adaptation, significant alterations were observed in the CeramX group after 3-years (p < 0.05). The changes in the color match were observed in each group over time (p < 0.05). Conclusions: The use of SDR demonstrated good clinical durability in deep Class II resin composite restorations.