• ETRI Journal
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• v.29 no.3
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• pp.399-401
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• 2007

With a growing emphasis on human identification, iris recognition has recently received increasing attention. Iris recognition includes eye imaging, iris segmentation, verification, and so on. In this letter, we propose a novel and efficient iris recognition method which employs a cumulative-sum-based grey change analysis. Experimental results demonstrate that the proposed method can be used for human identification in efficient manner.

• Journal of Information Technology Services
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• v.9 no.3
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• pp.179-191
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• 2010

Service identification and composition is one of the key characteristics for a successful Service-Oriented Computing, being receiving a lot of attention from researchers in recent years. In the Service-Oriented Analysis, the identification of business services has to be preceded before application services are identified. Most approaches addressing the derivation of business services are based on heuristic methods and human experts. The manual identification of business services is highly expensive and ambiguous task, and it may result in the service design with bad quality because of errors and misconception. Although a few of approaches of automatic service identification are proposed, most of them are in focus on technical architectures and application services. In this paper, we propose a model on the automatic identification of business services by horizontal and vertical service alignment using Enterprise Architecture as an ontology. We verify the effectiveness of the proposed model of business services identification through a case study based on Department of Defense Enterprise Architecture.

• Journal of Industrial Technology
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• v.31 no.B
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• pp.45-50
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• 2011

Recently, machine olfactory systems that have been proposed as an artificial substitute of the human olfactory system are being studied by many researchers because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. The design method adopted the sequential combination between genetic algorithms and TSK fuzzy logic system. First, the proposed method allowed the designed gas identification system effectively performing the pattern analysis because it was able to avoid the curse of dimensionality caused by use of a large number of sensors. Secondly, the method led the gas identification system to good performance because it was able to deal with drift characteristics of the sensor data by using description ability of the fuzzy system for nonlinear data. In simulation, we demonstrated the effectiveness of the designed gas identification system by using the simulation results of five types of gases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3055-3073
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• 2019

In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability. User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc. To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm. Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data. All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm. Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data. Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window. Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.187-189
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• 2004

This paper presents the system widely used for extraction of human body recognition system in the field of bio-metric identification. The Human body recognition system is used in many fields. This biological is appled to the human recognition in banking and the access control with security. The important algorithm of the identification software usese hand lines and hand shape geometry. We used the simple algorithm and recognizing the person by their hand image from the input camera. The geometrical characteristics in hand shape such as length of finger to whole hand length thickness of finger to length, etc are used.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.27-36
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• 2013

Objective: This paper describes an analysis of electroencephalography(EEG) signals to identify human errors during using digital devices in nuclear power plants(NPPs). Background: The application of an advanced main control room(MCR) has accompanied with lots of changes in different forms and features by virtue of new digital technologies. The characteristics of these digital technologies and devices provide several opportunities for the use of interface management. It can integrate into a compact single workstation in an advanced MCR, allowing workers to operate the plant with minimum physical burden under any operating condition. However these devices may introduce new types of human errors, and thus we need a means to assess and prevent such errors especially those related to digital devices. Method/Conclusion: The EEG data are relatively objective, and thus we introduce several measures to EEG analysis for obtaining the feasibility of human error identification. Application: This study may support to ensure the safety when applying digital devices in NPPs.

• The Zoological Society Korea : Newsletter
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• v.12 no.2
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• pp.130.1-130
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• 1995

No Abstract, See Full Text

• Proceedings of the Zoological Society Korea Conference
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• 1995.10b
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• pp.306.1-306
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• 1995

No Abstract, See Full Text

• Molecules and Cells
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• v.44 no.9
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• pp.647-657
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• 2021

As a pancreatic inflammatory marker, regenerating islet-derived protein 3A (Reg3A) plays a key role in inflammation-associated pancreatic carcinogenesis by promoting cell proliferation, inhibiting apoptosis, and regulating cancer cell migration and invasion. This study aimed to reveal a novel immuno-regulatory mechanism by which Reg3A modulates tumour-promoting responses during pancreatic cancer (PC) progression. In an in vitro Transwell system that allowed the direct co-culture of human peripheral blood-derived dendritic cells (DCs) and Reg3A-overexpressing/ silenced human PC cells, PC cell-derived Reg3A was found to downregulate CD80, CD83 and CD86 expression on educated DCs, increase DC endocytic function, inhibit DC-induced T lymphocyte proliferation, reduce IL-12p70 production, and enhance IL-23 production by DCs. The positive effect of tumour-derived Reg3A-educated human DCs on PC progression was demonstrated in vivo by intraperitoneally transferring them into PC-implanted severe combined immunodeficiency (SCID) mice reconstituted with human T cells. A Reg3A-JAK2/STAT3 positive feedback loop was identified in DCs educated with Reg3A. In conclusion, as a tumour-derived factor, Reg3A acted to block the differentiation and maturation of the most important antigen-presenting cells, DCs, causing them to limit their potential anti-tumour responses, thus facilitating PC escape and progression.

• Anatomy and Cell Biology
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• v.56 no.3
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• pp.293-298
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• 2023

The mentalis muscle is a paired muscle originating from the alveolar bone of the mandible. This muscle is the main target muscle for botulinum neurotoxin (BoNT) injection therapy, which aims to treat cobblestone chin caused by mentalis hyperactivity. However, a lack of knowledge on the anatomy of the mentalis muscle and the properties of BoNT can lead to side effects, such as mouth closure insufficiency and smile asymmetry due to ptosis of the lower lip after BoNT injection procedures. Therefore, we have reviewed the anatomical properties associated with BoNT injection into the mentalis muscle. An up-to-date understanding of the localization of the BoNT injection point according to mandibular anatomy leads to better injection localization into the mentalis muscle. Optimal injection sites have been provided for the mentalis muscle and a proper injection technique has been described. We have suggested optimal injection sites based on the external anatomical landmarks of the mandible. The aim of these guidelines is to maximize the effects of BoNT therapy by minimizing the deleterious effects, which can be very useful in clinical settings.