• KOGO NEWS
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• v.6 no.1
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• pp.29-33
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• 2006

Gene set analysis is a new concept and method. to analyze and interpret microarray gene expression data and tries to extract biological meaning from gene expression data at gene set level rather than at gene level. Compared with methods which select a few tens or hundreds of genes before gene ontology and pathway analysis, gene set analysis identifies important gene ontology terms and pathways more consistently and performs well even in gene expression data sets with minimal or moderate gene expression changes. Moreover, gene set analysis is useful for comparing multiple gene expression data sets dealing with similar biological questions. This review briefly summarizes the rationale behind the gene set analysis and introduces several algorithms and tools now available for gene set analysis.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2562-2567
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• 2008

Jet impingement on a moving plate, which is applicable to cooling of hot metals in a steel-making process, is investigated numerically by solving the Navier-Stokes equations in the liquid and gas phases. The liquid-gas interface or free surface is tracked by a level-set method which is improved by incorporating the ghost fluid approach based on a sharp-interface representation. The computations are made for multiple jets as well as a single jet to compare their flow characteristics. Also, the effects of the nozzle pitch, moving velocity of plate and jet velocity on the interfacial motion and the associated flow and temperature fields.

• Research in Mathematical Education
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• v.14 no.1
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• pp.1-10
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• 2010

The paper focuses on a type of mathematics competence noted as synthetic. It is needed for success in multiple choice competition problems and it is crucial for the further development of advanced school students. The concept of synthetic competence includes a large fraction of mathematical competences, but also competences and skills related to informatics and linguistics. The general structure of a multiple choice competition is considered as the first level of assessment of the mathematics component of the synthetic competence. As the second level under consideration is the set of complex tasks in a competition test any of which is a bouquet of ideas. Our standpoint on the didactic specifics and goals of the two levels in perspective of the gifted education is briefly presented in the article and some examples are given.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.719-732
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• 2006

A set of clustering algorithms with proper weight on the formulation of distance which extend to mixed numeric and multiple binary values is presented. A simple matching and Jaccard coefficients are used to measure similarity between objects for multiple binary attributes. Similarities are converted to dissimilarities between i th and j th objects. The performance of clustering algorithms with balancing weight on different similarity measures is demonstrated. Our experiments show that clustering algorithms with application of proper weight give competitive recovery level when a set of data with mixed numeric and multiple binary attributes is clustered.

• JSTS:Journal of Semiconductor Technology and Science
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• v.6 no.1
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• pp.52-58
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• 2006

Single-electron transistor (SET)-based logic cells and SET/FET hybrid integrated circuits have been fabricated on SOI chips. The input-output voltage transfer characteristic of the SET-based complementary logic cell shows an inverting behavior where the output voltage gain is estimated to be about 1.2 at 4.2K. The SET/FET output driver, consisting of one SET and three FETs, yields a high voltage gain of 13 and power amplification with a wide-range output window for driving next circuit. Finally, the SET/FET literal gate for a multi-valued logic cell, comprising of an SET, an FET and a constant-current load, displays a periodic voltage output of high/low level multiple switching with a swing as high as 200mV. The multiple switching functionality of all the fabricated logic circuits could be enhanced by utilizing a side gate incorporated to each SET component to enable the phase control of Coulomb oscillations, which is one of the unique characteristics of the SET-based logic circuits.

• International Journal of Contents
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• v.15 no.1
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• pp.32-38
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• 2019

In an environment where a large number of weapons are operated compared to a large number of ground targets, it is important to monitor and manage the targets to set up a fire plan, and through their multilateral analysis, to equip them with a priority order process for targets having a high threat level through the quantitative calculation of the threat level. Existing studies consider the anti-aircraft and anti-ship targets only, hence, it is impossible to apply the existing algorithm to ground weapon system development. Therefore, we proposed an effective threat evaluation algorithm for multiple ground targets in multi-target and multi-weapon environments. Our algorithm optimizes to multiple ground targets by use of unique ground target features such as proximity degree, sorts of weapons and protected assets, target types, relative importance of the weapons and protected assets, etc. Therefore, it is possible to maximize an engagement effect by deducing an effective threat evaluation model by considering the characteristics of ground targets comprehensively. We carried out performance evaluation and verification through simulations and visualizations, and confirmed high utility and effect of our algorithm.

• Annual Conference of KIPS
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• 2009.11a
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• pp.335-336
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• 2009

In this paper, I propose an automatic approach to annotating images dynamically based on MBRM(Multiple Bernoulli Relevance Models) using GLCM(Grey Level Co-occurrence Matrix). MBRM is more appropriate to annotate images compare with multinomial distribution. The model is used in limited test set, MSRC-v2 (Microsoft Research Cambridge Image Database). The results show that this model is significantly outperforms previously reported results on the task of image annotation and retrieval.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2406-2412
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• 2015

Multi-user multi-input multi-output (MU-MIMO) system has attracted the 4^th generation wireless network as one of core technique for performance enrichment. In this system rate control is a challenging problem and another problem is optimization. Proper scheduling can resolve these problems by deciding which set of user and at which rate the users send their data. This paper proposes a new multi-parameter based scheduling (MPS) for downlink multi-user multiple-input multiple-output (MU-MIMO) system under space-time block coding (STBC) transmissions. Goal of this MPS scheme is to offer improved link level performance in terms of a low average bit error rate (BER), high packet delivery ratio (PDR) with improved resource utilization and service fairness among the user. This scheme allows the set of users to send data based on their channel quality and their demand rates. Simulation compares the MPS performance with other scheduling scheme such as fair scheduling (FS), normalized priority scheduling (NPS) and threshold based fair scheduling (TFS). The results obtained prove that MPS has significant improvement in average BER performance with improved resource utilization and fairness as compared to the other scheduling scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5A
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• pp.347-354
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• 2009

In this paper, we propose a new transmit diversity technique for multiple-input multiple-output (MIMO) systems to improve the link level performance of open-loop systems. By cyclically applying a predetermined set of preceding weight vectors, artificially induced fluctuation is created to achieve additional diversity gain in flat fading channels. To design the set of the precoding vectors, we exploit the knowledge on the distribution of near optimum Preceding vectors observed in a beamforming scheme based on the rotation transformations. Simulation results demonstrate that the proposed open-loop diversity scheme with an arbitrary number of transmit antennas achieves a full diversity gain with computational complexity comparable to a single-input single-output (SISO) system.

• Annual Conference of KIPS
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• 2021.05a
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• pp.408-410
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• 2021

In the NLP field, the pre-training model BERT launched by the Google team in 2018 has shown amazing results in various tasks in the NLP field. Subsequently, many variant models have been derived based on the original BERT, such as RoBERTa, ERNIEBERT and so on. In this paper, the WWMBERT (Whole Word Masking BERT) model suitable for Chinese text tasks was used as the baseline model of our experiment. The experiment is mainly for "Text-level Chinese text classification tasks" are improved, which mainly combines Tapt (Task-Adaptive Pretraining) and "Multi-Sample Dropout method" to improve the model, and compare the experimental results, experimental data sets and model scoring standards Both are consistent with the official WWMBERT model using Accuracy as the scoring standard. The official WWMBERT model uses the maximum and average values of multiple experimental results as the experimental scores. The development set was 97.70% (97.50%) on the "text-level Chinese text classification task". and 97.70% (97.50%) of the test set. After comparing the results of the experiments in this paper, the development set increased by 0.35% (0.5%) and the test set increased by 0.31% (0.48%). The original baseline model has been significantly improved.