• Genomics & Informatics
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• v.15 no.1
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• pp.11-18
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• 2017

Nowadays, huge volumes of chromatin immunoprecipitation-sequencing (ChIP-Seq) data are generated to increase the knowledge on DNA-protein interactions in the cell, and accordingly, many tools have been developed for ChIP-Seq analysis. Here, we provide an example of a streamlined workflow for ChIP-Seq data analysis composed of only four packages in Bioconductor: dada2, QuasR, mosaics, and ChIPseeker. 'dada2' performs trimming of the high-throughput sequencing data. 'QuasR' and 'mosaics' perform quality control and mapping of the input reads to the reference genome and peak calling, respectively. Finally, 'ChIPseeker' performs annotation and visualization of the called peaks. This workflow runs well independently of operating systems (e.g., Windows, Mac, or Linux) and processes the input fastq files into various results in one run. R code is available at github: https://github.com/ddhb/Workflow_of_Chipseq.git.

• The Journal of Society for e-Business Studies
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• v.10 no.3
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• pp.21-36
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• 2005

Current web search includes a lot of different results with information that user does not want, because it searches information using keyword mapping. Ontology can describe the correct meaning of web resource and relationships between web resources. And we can extract suitable information that user wants using Ontology Accordingly, we need the ontology to represent knowledge. W3C announced OWL(Web Ontology Language), meaning description technology for such web resource. However, the development of a special tool that can effectively compose and edit OWL is inactive. In this paper, we designed and developed an OWL authoring system that can effectively provide the generation and edit about OWL.

• Journal of Biomedical Engineering Research
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• v.29 no.5
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• pp.355-363
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• 2008

In order to extract only the alpha activity related signals from EEG recordings, we have applied Constrained Independent Component Analysis (cICA), a new extension of ICA in which some a priori knowledge of the alpha activity is utilized to extract only desired components. Its extraction (or filtering) performance has been compared to that of the conventional band-pass filtering via the scalp alpha power maps and cortical source maps of the alpha activity. Our results demonstrate that the alpha power maps and cortical source maps from the cICA-extracted alpha signals reveal more focalized alpha generating regions of the brain than those from the band-pass filtered alpha EEG signals. Furthermore they match more closely the activated regions of the brain mapped using fMRI, validating our results. We believe that the cICA-based filtering approach of EEG signals is a more effective means of extracting a specific brain activity reflected in EEG signals that will result in more accurate source localization or imaging maps.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.266-269
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• 2002

This paper explores a fundamental study of acquiring the users' KANSEI information regarding the recognition of shape models. Since there are many differences such as background differences and knowledge differences among users, they will produce different evaluations based on their KANSEI even when an identical shape model is presented. Cluster analysis is proved to be available for catching a group tendency and for constructing a mapping relation between a description of the shape model and the HANSEl database. In order to investigate an analogical relation and a mutual influence in our consciousness, first, we made a questionnaire that asked subjects to represent images having different colors and shape cones by using 4 pairs of adjectives (KANSEI words). Next, based on the cluster analysis of the questionnaire using a fuzzy set theory, we proposed a hypothesis showing how the analogical relation and the mutual influence work in our mind while viewing the shape models. Furthermore, how the properties of KANSEI depend on their descriptions was also investigated by virtue of the cluster analysis. This work will be valuable to construct a personal KANSEI database regarding the Shape Model Processing System.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.705-709
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• 1995

The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it was used as a commanded feedforward input generator. A PD feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the excavator as well as the PD feedback error. By using the BP network as a feedforward controller, no a priori knowledge on system dynamics is need. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbancen and performance improvement with the on-line learning in the position control of excavator attachment.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.75-78
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• 2015

A growing body of evidence has been supporting the existence of so-called "dark molecular gas" (DMG), which is invisible in the most common tracer of molecular gas, i.e., CO rotational emission. DMG is believed to be the main gas component of the intermediate extinction region from Av~0.05-2, roughly corresponding to the self-shielding threshold of $H_2$ and $^{13}CO$. To quantify DMG relative to $H{\small{I}}$ and CO, we are pursuing three observational techniques; $H{\small{I}}$ self-absorption, OH absorption, and THz $C^+$ emission. In this paper, we focus on preliminary results from a CO and OH absorption survey of DMG candidates. Our analysis shows that the OH excitation temperature is close to that of the Galactic continuum background and that OH is a good DMG tracer co-existing with molecular hydrogen in regions without CO. Through systematic "absorption mapping" by the Square Kilometer Array (SKA) and ALMA, we will have unprecedented, comprehensive knowledge of the ISM components including DMG in terms of their temperature and density, which will impact our understanding of galaxy evolution and star formation profoundly.

• Journal of Information Science Theory and Practice
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• v.7 no.4
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• pp.6-19
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• 2019

The purpose of this article is to problematize the existence of a possible Ibero-American informational thinking. It was initially observed that a relative absence of Ibero-America in the international presentations and mappings of information science exists. Below, the reality of the 22 countries that compose Ibero-America is discussed, a region that can be understood from a sociocultural and geopolitical perspective. Then, a mapping of the information science research in these countries is made. The main research topics found are: epistemological studies, relationships with library science, information literacy, representation and organization, bibliometric studies, information management, user studies, technological dimensions, and relationships with archival science and museum studies. Finally, a general epistemological configuration of information science is presented at a global level, highlighting the great trends of study of information that marked the decades of the 1960s and 1970s (physical model), 1980s and 1990s (cognitive model), and the 21st century (sociocultural model), and which manifested themselves in the different subareas that make up the field. The most recent research in information science, in addition to addressing information transfer (physical dimension) and its relationship with data and knowledge (cognitive dimension), has also incorporated aspects related to the social effects of information, its role in the constitution of identities and culture, and the importance of its material conformations. Such expansion reflects attempts to address the complexity of informational phenomena. Therefore, it is concluded that it is important to place the specific contributions of Ibero-America in this context.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1964-1966
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• 2001

Active Noise control(ANC) is rapidly becoming the most effective way to reduce noises that can otherwise be very difficult and expensive to control. This research presents ANFIS (Adaptive Network Fuzzy Inference System) controller for adaptively noise cancelling in a duct. ANC system generates secondary control sound pressure with same amplitude and with opposite phase as noise to be eliminated. ANFIS controller is trained to optimize its parameters for adaptively cancelling noise. That is ANFIS train its parameters by gradient descent and LSE method so called hybrid method. This paper present ANFIS in active noise control which provides an improvement convergence speed and limitation of linearity condition. It can model nonlinear functions of arbitrary complexity and ANFIS can construct an input-ouput mapping based on both human knowledge in the form of Takagi and Sugeno's fuzzy if-then rules and stipulated input-output data pairs. This paper also shows that the proposed ANFIS active noise control system successfully cancelled noise.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.78-81
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• 2017

Augmented Reality(AR) is the core technology of the future knowledge service industry. It is expected to be used in various fields such as medical, education, entertainment etc. Briefly, augmented reality technology is a technique in which a mapped virtual object is augmented when a real-world object is viewed through a device after mapping a real-world object and a virtual object. In this paper, we implemented object detection and tracking system, which is a key technology of augmented reality. To speed up the object tracking, the ORB algorithm, which is a lightweight algorithm compared to the detection algorithm, is applied. In addition, KNN classifier, which is a machine learning algorithm, was applied to detect a single object by learning multiple images.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.247-266
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• 2019

The purpose of this study is to propose a W3C standard, DCAT, to manage and service dataset that is becoming increasingly important as new knowledge information resources. To do this, we first analyzed the class and properties of the four core classes of DCAT. In addition, I modeled and presented a system that can manage and service various data sets based on DCAT in digital library. The system is divided into source data, data set management, linked data connection, and user service. Especially, the DCAT mapping function is suggested in dataset management. This feature can ensure interoperability of various datasets.