• Korean Journal of Remote Sensing
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• v.19 no.1
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• pp.61-70
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• 2003

This paper proposes an autonomous approach to localize the center of fiducial marks included in aerial photographs without precise geometric information and human interactions. For this localization, we present a conceptual model based on two assumptions representing symmetric characteristics of fiducial area and fiducial mark. The model makes it possible to locate exact center of a fiducial mark by checking the symmetric characteristics of pixel value distribution around the mark. The proposed approach is composed of three steps: (a) determining the symmetric center of fiducial area, (b) finding the center of a fiducial mark with unit pixel accuracy, and finally (c) localizing the exact center up to sub-pixel accuracy. The symmetric center of the mark is calculated tv successively applying three geometric filters: simplified ${\nabla}^2$G (Laplacian of Gaussian) filter, symmetry enhancement filter, and high pass filter. By introducing a self-diagnosis function based on the self-similarity measurement, a way of rejecting unreliable cases of center calculation is proposed, as well. The experiments were done with respect to 284 samples of fiducial marks composed of RMK- and RC-style ones extracted from 51 scanned aerial photographs. It was evaluated in the visual inspection that the proposed approach had resulted the erroneous identification with respect to only one mark. Although the proposed approach is based on weak constraints, being free from the exact geometric model of the fiducial marks, experimental results showed that the proposed approach is sufficiently robust and reliable.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1494-1507
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• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

• Journal of Microbiology and Biotechnology
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• v.34 no.3
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• pp.681-688
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• 2024

The accurate and rapid detection of methicillin-resistance of Staphylococcus aureus (SA) holds significant clinical importance. However, the methicillin-resistance detection strategies commonly require complicated cell lysis and gene extraction. Herein, we devised a novel colorimetric approach for the sensitive and accurate identification of methicillin-resistance of SA by combining allosteric probe-based target recognition with self-primer elongation-based target recycling. The PBP2a aptamer in the allosteric probe successfully identified the target MRSA, leading to the initiation of self-primer elongation based-cascade signal amplification. The peroxidase-like hemin/G-quadruplex undergo an isothermal autonomous process that effectively catalyzes the oxidation of ABTS2- and produces a distinct blue color, enabling the visual identification of MRSA at low concentrations. The method offers a shorter duration for bacteria cultivation compared to traditional susceptibility testing methods, as well as simplified manual procedures for gene analysis. The overall amplification time for this test is 60 min, and it has a detection limit of 3 CFU/ml. In addition, the approach has exceptional selectivity and reproducibility, demonstrating commendable performance when tested with real samples. Due to its advantages, this colorimetric assay exhibits considerable potential for integration into a sensor kit, thereby offering a viable and convenient alternative for the prompt and on-site detection of MRSA in patients with skin and soft tissue infections.

• Journal of Gifted/Talented Education
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• v.23 no.2
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• pp.257-273
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• 2013

The purpose of this study was to explore a more useful identification method by comparing diverse selection approaches for the gifted education programs at the each elementary school. Diverse selection methods examined in the study include 'written examinations', 'mixed evaluation', 'achievement test scores', and 'self-recommendation'. For the study, each identification group's gifted students' characteristics, such as intelligence, creativity, motivation and self-regulated learning strategies, were compared. The subjects of the study were a total of 594 gifted and normal students. The results of this study were as follows: First, there were no statistically significant differences between students in each gifted education class and gifted students who belong to the regional gifted education programs which are considered higher level of gifted education programs. While, there were statistically significant differences between two groups of gifted students and general students in all aspects examined, such as intelligence, creativity, motivation and learning strategies. In addition and most importantly, diverse identification method utilized in each school showed differences in gifted students' characteristics. Especially, students who were selected through the self-recommendation showed significantly lower intelligence, creativity, motivation and learning strategies. The implications of the study related to the identification and education for the gifted at each elementary school were discussed in depth.

• The Journal of Information Systems
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• v.30 no.4
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• pp.119-152
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• 2021

The concept of Self-Sovereign Identity (SSI) has emerged to overcome the limitations of traditional centralized personal identity management systems in our society. Therefore, in this study, 36 seminal researches out of 112 collected studies were investigated with a systematic literature review method to deliver a core common definition as well as the research trends on SSI in the socioeconomic, legal and technological fields. SSI studies in the legal field have mainly considered the conflicts with relevant laws such as General Data Protection Regulation (GDPR) and privacy protection laws. The study of SSI in the technology field have looked at the trends of the technical components to implement SSI and discussed the necessities of establishing standards to increase interoperability for SSI diffusion worldwide. This study ultimately derived the core definition of SSI from a various academic fields as "a trust-based personal identity management system that enables autonomous self-identification by a identity owner without a centralized system or 3rd party intervention". The results of this study contribute to the understanding of the essential SSI concept which were varied on different research fields and industries. The results also provide a foundation for discovering various SSI-based business models, applications as well as future research opportunities. Furthermore, this study suggested that SSI must be developed with interdisciplinary manner among the socioeconomic, legal, and technological fields to be practically applicable system to enable autonomous self-identification by a identity owner in our society.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.79-103
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• 2022

COVID-19 is forcing people to minimize face-to-face networking activities between members of society, and they are increasing their use of online platforms. In particular, interest in the metaverse, a virtual community with enhanced realism, is growing. Specifically, this study suggests a mechanism to improve the intention to continuous use of metaverse users by using the self-determination theory, and confirms that trust between metaverse members moderates the relationship between self-determination and intrinsic motivation. We obtained 353 samples through a questionnaire targeting those who have used metaverse and verified the hypothesis through structural equation modeling. As a result of the analysis, individual self-determination of the metaverse formed intrinsic motivation such as identification and enjoyment, which affected the intention to continue use, and the trust of metaverse members partially moderated the relationship between self-determination and motivation. The result contributes to the sustainability of the metaverse platform by suggesting an approach to users and the environment to improve the intention of continuous use of metaverse.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.243-246
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• 1994

In this paper, a self-learning fuzzy controller is designed with a fuzzy approximation of an inverse model. The aim of an identification is to find an input command which is control of a system output. It is intuitional and easy to use a classical adaptive inverse modeling method for the identification, but it is difficult and complex to implement it. This problem can be solved with a fuzzy approximation of an inverse modeling. The fuzzy logic effectively represents the complex phenomena of the real world. Also fuzzy system could be represented by the neural network that is useful for a learning structure. The rule of a fuzzy inverse model is modified by the gradient descent method. The goal is to be obtained that makes the design of fuzzy controller less complex, and then this self-learning fuzz controller can be used for nonlinear dynamic system. We have applied this scheme to a nonlinear Ball and Beam system.

• Journal of Power Electronics
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• v.15 no.6
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• pp.1567-1576
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• 2015

Offline inductance identification of a permanent magnet synchronous motor (PMSM) is essential for the design of the closed-loop controller and position observer in sensorless vector controlled drives. On the base of the offline inductance identification method combining direct current (DC) offset and high frequency (HF) voltage injection which is fulfilled at standstill, this paper investigates the inverter nonlinearity effects on the inductance identification while considering harmonics in the induced HF current. The negative effects on d-q axis inductance identifications using HF signal injection are analyzed after self-learning of the inverter nonlinearity characteristics. Then, both the voltage error and the harmonic current can be described. In addition, different cases of voltage error distribution with different injection conditions are classified. The effects of inverter nonlinearities on the offline inductance identification using HF injection are validated on a 2.2 kW interior PMSM drive.

• 한국전자현미경학회:학술대회논문집
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• 2007.05a
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• pp.94-95
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• 2007

• Korean Medical Education Review
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• v.19 no.2
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• pp.101-108
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• 2017

When participating in problem-based learning (PBL), it is important for medical students to generate claims and provide justifications for their claims in small group discussions. This study aimed to investigate the effect of argumentation instruction on medical student learning experiences with PBL. A total of one hundred first-year preclinical students from Inje University College of Medicine, who had attended argumentation instruction, participated in this study. All of the participants completed a 5-point Likert scale questionnaire regarding their learning experiences with PBL, before and after the argumentation instruction. The questionnaire comprised 22 items with eight subcategories: argumentation activity, reflection, integration of basic and clinical science, identification of lack of knowledge, logical thinking, self-directed study, communication, and attitude toward discussion. The collected data were analyzed through a paired-sample t-test. The results of this study found that the argumentation instruction promoted the preclinical students' experiences with argumentation activities, reflection, an integration of basic and clinical science, the identification of their lack of knowledge, logical thinking, and self-directed study, and it increased positive attitudes toward group discussion. The findings suggest argumentation instruction can enhance medical student group discussions and help students achieve the objectives of PBL, including acquisition of basic and clinical science knowledge and development of clinical reasoning and self-directed learning abilities, which can highlight the meaningful learning experiences students have with PBL.