• Journal of Microbiology and Biotechnology
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• v.14 no.4
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• pp.816-821
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• 2004

A reliable molecular phylogenetic method to identify Hericium erinaceum, the most industrially valuable species in the Hericium genus, was established. Sequencing and phylogenetic analyses of the PCR-amplified ITS and 5.8S rDNA from Hericium fungi, including 6 species and 23 isolates, showed that variation in nucleotide sequences and size exists in both ITS1 and ITS2 regions, but not in the 5.8S region. These two ITS regions provided different levels of information on the relationship of H. erinaceum to other Hericium species. Based on the ITS1 sequence, both the parsimony and neighbor joining trees clearly distinguished Asian H. erinaceum isolates from other Hericium species and isolates. The intraspecific divergence of the ITS2 region was suitable to dissect the Asian H. erinaceum isolates into a few groups.

• Journal of Microbiology
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• v.43 no.1
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• pp.1-10
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• 2005

We isolated and cultured bacteria inhabiting solar saltern ponds in Taean-Gun, Chungnam Province, Korea. All of the isolated 64 strains were found to be moderately halophilic bacteria, growing in a salt range of 2-20 %, with an optimal concentration of 5% salt. Bacterial diversity among the isolated halophiles was evaluated via RFLP analyses of PCR-amplified 16S rDNAs, followed by phylogenetic analysis of the partial 16S rDNA sequences. The combination of restriction enzyme digestions with HaeIII, CfoI, MspI and RsaI generated 54 distinct patterns. A neighbor-joining tree of the partial 16S rDNA sequences resulted in the division of the 64 strains into 2 major groups, 45 strains of ${\gamma}-Proteobacteria$ (70.3%) and 19 strains of Firmicutes (29.7%). The ${\alpha}-Proteobacteria$ and Cytophaga-Flavobacterium-Bacterioides groups, which were repeatedly found to exist in thalassohaline environments, were not represented in our isolates. The ${\gamma}-Proteobacteria$ group consisted of several subgroups of the Vibrionaceae (37.5%), Pseudoalteromonadaceae (10.9%), Halomonadaceae (7.8%), Alteromonadaceae (7.8%), and Idiomarinaceae (6.3%). Members of Salinivibrio costicola (29.7%) were the most predominant species among all of the isolates, followed by Halobacillus treperi (12.5%). Additionally, three new species candidates were found, based on similarities of the 16S rDNA sequences to those of previously published species.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1708-1717
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• 2023

The grade analysis of lead-zinc ore is the basis for the optimal development and utilization of deposits. In this study, a method combining Prompt Gamma Neutron Activation Analysis (PGNAA) technology and machine learning is proposed for lead-zinc mine borehole logging, which can identify lead-zinc ores of different grades and gangue in the formation, providing real-time grade information qualitatively and semi-quantitatively. Firstly, Monte Carlo simulation is used to obtain a gamma-ray spectrum data set for training and testing machine learning classification algorithms. These spectra are broadened, normalized and separated into inelastic scattering and capture spectra, and then used to fit different classifier models. When the comprehensive grade boundary of high- and low-grade ores is set to 5%, the evaluation metrics calculated by the 5-fold cross-validation show that the SVM (Support Vector Machine), KNN (K-Nearest Neighbor), GNB (Gaussian Naive Bayes) and RF (Random Forest) models can effectively distinguish lead-zinc ore from gangue. At the same time, the GNB model has achieved the optimal accuracy of 91.45% when identifying high- and low-grade ores, and the F₁ score for both types of ores is greater than 0.9.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.315-332
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• 2013

This paper presents an approach for improving the use of VP-tree in video indexing and searching. A vantage-point tree or VP-tree is one of the metric space-based indexing methods used in multimedia database searches and data retrieval. Instead of relying on the Euclidean distance as a measure of search space, the proposed approach focuses on the trigonometric inequality for compressing the search range, which thus, improves the search performance. A test result of using 10,000 video files shows that this method reduced the search time by 5-12%, as compared to the existing method that uses the AESA algorithm.

• ETRI Journal
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• v.31 no.5
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• pp.525-533
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• 2009

This paper proposes a distributed borrowing addressing (DIBA) scheme to solve problems of failure in address assignments resulting from limited tree depth and width when the distributed address assignment mechanism is used in a ZigBee/IEEE 802.15.4 wireless sensor network. DIBA is a method of borrowing addresses from neighbor nodes for newly entering nodes and assigning the borrowed addresses. Its network or sensing coverage can increase with almost the same overhead as the existing method. DIBA is a simple and lightweight means of addressing and routing, making it suitable for wireless sensor networks. Simulations showed that DIBA is a distributed addressing scheme with consistently excellent performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.1-5
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• 2008

Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.

• Journal of Korea Game Society
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• v.10 no.5
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• pp.95-102
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• 2010

This paper proposes a parallel algorithm of the flocking behaviors using GPU. To do this, we used CUDA as the parallel processing architecture of GPU and then analyzed its characteristics and constraints. Based on them, the paper improved the performance by parallelizing to find the neighbors for an agent which requires the largest cost in the flocking behaviors. We implemented the proposed algorithm on GTX 285 GPU and compared experimentally its performance with the original spatial partitioning method. The results of the comparison showed that the proposed algorithm outperformed the original method up to 9 times with respect to the execution time.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.31-33
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• 2004

We suggest an enhanced automatic route shortening method for dynamic source routing (DSR) protocol. DSR is a request / response based protocol which has low routing overhead owing to node movement. The original automatic route shortening is performed on the only nodes that belong to the source route of packets. On the contrary, our suggested method allows all neighbor nodes hearing the packet to participate in automatic route shortening. It makes all possible route shortenings be performed. So we maintain maximal short routes of ongoing data connections. Simulation results show that our method pays small extra overhead for ARS, but increases the ratio of packet transmissions and ARS' are performed from 2 to 5 times as much as original ARS.

• Proceedings of the Korean Printing Society Conference
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• 2000.12b
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• pp.5-10
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• 2000

In case of outputting the image with color printer, image is occurred color distortion by characteristics of paper, effect by overlap between neighbor dots and the mechanical characteristics if printer. Color calibration is needed to reduce this color distrotion. To color calibration, we select the color sample in printer color gamut. The accuracy of color calibration is determined by the number of sample, distribution, and calibration method. Generally, color space is selected the color sample dividing equal interval. In this case, the range of gamut of printed color patches is reduced due to the effect of inks overlap. Therefore, error is occurred when color transformation relatively. In this paper, we have the color sampling based on equi-visual perception and then reproduce the color using the Neural-Network and interpolation by LUT.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.1-5
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• 2012

Data reduction has been used widely in data mining for convenient analysis. Principal component analysis (PCA) and factor analysis (FA) methods are popular techniques. The PCA and FA reduce the number of variables to avoid the curse of dimensionality. The curse of dimensionality is to increase the computing time exponentially in proportion to the number of variables. So, many methods have been published for dimension reduction. Also, data augmentation is another approach to analyze data efficiently. Support vector machine (SVM) algorithm is a representative technique for dimension augmentation. The SVM maps original data to a feature space with high dimension to get the optimal decision plane. Both data reduction and augmentation have been used to solve diverse problems in data analysis. In this paper, we compare the strengths and weaknesses of dimension reduction and augmentation for classification and propose a classification method using data reduction for classification. We will carry out experiments for comparative studies to verify the performance of this research.