• Journal of Information Processing Systems
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• v.11 no.2
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• pp.280-294
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• 2015

This paper presents the infectious watermarking model (IWM) for the protection of video contents that are based on biological virus modeling by the infectious route and procedure. Our infectious watermarking is designed as a new paradigm protection for video contents, regarding the hidden watermark for video protection as an infectious virus, video content as host, and codec as contagion medium. We used pathogen, mutant, and contagion as the infectious watermark and defined the techniques of infectious watermark generation and authentication, kernel-based infectious watermarking, and content-based infectious watermarking. We experimented with our watermarking model by using existing watermarking methods as kernel-based infectious watermarking and content-based infectious watermarking medium, and verified the practical applications of our model based on these experiments.

• Genomics & Informatics
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• v.7 no.2
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• pp.111-121
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• 2009

Cell membrane proteins play crucial roles in the cell's molecular interaction with its environment and within itself. They consist of membrane-bound proteins and many types of transmembrane (TM) proteins such as receptors, transporters, channel proteins, and enzymes. Membrane proteomes of cellular organisms reveal some characteristics in their global topological distribution according to their evolutionary positions, and show their own information transfer complexity. Predicted transmembrane segments (TMSs) in membrane proteomes with HMMTOP showed near power-law distribution and frequency characteristics in 6-TMS and 7-TMS proteins in prokaryotes and eukaryotes, respectively. This reaffirms the important roles of membrane receptors in cellular communication and biological evolutionary history.

• Journal of the Korea Safety Management & Science
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• v.21 no.4
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• pp.1-6
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• 2019

This study relates to acquiring biological signal without attaching directly to the user using UWB(Ultra Wide Band) radar. The collected information is the respiratory rate, heart rate, and the degree of movement during sleep, and this information is used to measure the sleep state. A breathing measurement algorithm and a sleep state detection algorithm were developed to graph the measured data. Information about the sleep state will be used as a personalized diagnosis by connecting with the medical institution and contribute to the prevention of sleep related diseases. In addition, biological signal will be linked to various sensors in the era of the 4th industrial revolution, leading to smart healthcare, which will make human life more enriching.

• Journal of electromagnetic engineering and science
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• v.10 no.4
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• pp.231-236
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• 2010

This study proposes a temperature compensation method of the complex permittivities of biological tissues and organs. The method is based on the temperature dependence of the Debye model of water, which has been thoroughly investigated. This method was applied to measured data at room temperature for whole blood, kidney cortex, bile, liver, and heart muscle. It is shown that our method can compensate for the Cole-Cole model using measured data at 20 $^{\circ}C$, given the Cole-Cole model based on measured data at 35 $^{\circ}C$, with a root-mean-squared deviation of 3~11 % and 2~6 % for the real and imaginary parts of the complex permittivities, respectively, among the measured tissues.

• Genomics & Informatics
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• v.2 no.2
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• pp.99-106
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• 2004

In this paper we introduce PubMiner, an intelligent machine learning based text mining system for mining biological information from the literature. PubMiner employs natural language processing techniques and machine learning based data mining techniques for mining useful biological information such as protein­protein interaction from the massive literature. The system recognizes biological terms such as gene, protein, and enzymes and extracts their interactions described in the document through natural language processing. The extracted interactions are further analyzed with a set of features of each entity that were collected from the related public databases to infer more interactions from the original interactions. An inferred interaction from the interaction analysis and native interaction are provided to the user with the link of literature sources. The performance of entity and interaction extraction was tested with selected MEDLINE abstracts. The evaluation of inference proceeded using the protein interaction data of S. cerevisiae (bakers yeast) from MIPS and SGD.

• Journal of Species Research
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• v.11 no.2
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• pp.102-107
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• 2022

The order Nudibranchia Cuvier, 1817 is among the most colorful gastropod group that lacks an external shell and mantle cavity at their adult stage. They are widely found in the intertidal to subtidal zones of marine habitats worldwide. To date, a total of 58 species are known from Korean waters. In this study, we report seven nudibranch species that are newly reported from Korean waters and provide their color images of external body, morphological description, taxonomic remarks, and mtDNA cox1 barcode sequence information: Dendronotus primorjensis Martynov, Sanamyan & Korshunova, 2015; Doto japonica Odhner, 1936; Trinchesia ornata (Baba, 1937); Antiopella fusca (O'Donoghue, 1924); Cadlina paninae Korshunova, Fletcher, Picton, Lundin, Kashio, N. Sanamyan, K. Sanamyan, Padula, Schrodi & Martynov, 2020; Rostanga bifurcata Rudman & Avern, 1989; and Goniodoridella savignyi Pruvot-Fol, 1933.

• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.102-116
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• 2007

An XML-based mediator system is the one of the methods to virtually integrate distributed heterogeneous information sources. It considers each information source as the virtual XML database and accesses the information source by XML query language. In this paper, we present a design concept and a development result of the graphic user interface that generates XML views for each biological information sources with flexibility and XML queries on the views. In addison to the easy generation of XML views and queries for the integrated schema, the system supports the form of the workflow, in which the part of the query result against biological information sources is used as input data of an another source.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1326-1334
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• 2019

Knowledge base means a library stored in computer system providing useful information or appropriate solutions to specific area. Knowledge base associated with autism is the complex multidimensional information set related to the disease autism for its pathogenic factor and therapy. This paper focuses on the knowledge of biological molecular information extracted from massive biomedical texts with the aid of widespread used machine learning methods. Six classes of biological molecular information (such as protein, DNA, RNA, cell line, cell component, and cell type) are concerned and the probability statistics method, conditional random fields (CRFs), is utilized to discover these knowledges in this work. The knowledge base can help biologists to etiological analysis and pharmacists to drug development, which can at least answer four questions in question-answering (QA) system, i.e., which proteins are most related to the disease autism, which DNAs play important role to the development of autism, which cell types have the correlation to autism and which cell components participate the process to autism. The work can be visited by the address http://134.175.110.97/bioinfo/index.jsp.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.792-793
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• 2016

Recent studies on a fusion of health care system and the information and communication technology of wearable is being developed Anytime and anywhere without being constrained to measure the biological information of the user. However existing wearable monitors the measured biological information. If the user is hard to deal with for the event of dangerous situations. In this paper, it proposes a system that identifies the status of a user to correct the problem it utilizes sensors and algorithms to measure the biological information. This enables the user will be able to respond quickly to dangerous situations. In the event of a dangerous situation, such as falling or stumbling sends an emergency alert to a designated guardian.

• Journal of Korean Society on Water Environment
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• v.24 no.1
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• pp.1-6
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• 2008

Biological and chemical sensors are the two most frequently used sensors to monitor the water resource. Chemical sensor is very accurate to pick up the types and to measure the concentration of the chemical substance. Drawback is that it works for just one type of chemical substance. Therefore a lot of expensive monitoring system needs to be installed to determine the safeness of the water, which costs too much expense. Biological sensor, on the contrary, can judge the degree of pollution of the water with just one monitoring system. However, it is not easy to figure out the type of contaminant with a biological sensor. In this study, an endeavor is made to identify the toxicant in the water using the shape of the chlorophyll fluorescence induction curve (FIC) from a biological monitoring system. Wem-tox values are calculated from the amount of flourescence of contaminated and reference water. Curve fitting is executed to find the representative curve of the raw data of Wem-tox values. Then the curves are digitalized at the same interval to train the neural network model. Taguchi method is used to optimize the neural network model parameters. The optimized model shows a good capacity to figure out the toxicant from FIC.