• Journal of Preventive Medicine and Public Health
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• v.41 no.1
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• pp.30-38
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• 2008

Objectives : The aim of this study was to determine the relationship between the core properties of professional socialization and social status satisfaction, economic reward satisfaction, and subjective class identification. Methods : Medical knowledge and skill, autonomy, and professional value factors were used as essential properties of professional socialization to determine the association with job satisfaction and subjective class identification. The authors used a self-administered questionnaire survey and collected nationwide data between July and August 2003, with 211 responses used for final analysis. Results : 'Age' and 'trust and respect' were positively associated with social status satisfaction, and 'occupation' was negatively associated. 'Income' and 'trust and respect' were positively related to economic reward satisfaction, and 'practicing for oneself', and 'a sense of duty and attendance' were negatively related. 'Practicing for oneself', 'not believing explanations', and 'a sense of duty and attendance' had a positive relationship with subjective class identification. 'Income', 'knowledge system', 'medical mistakes', 'treating like goods', 'meaning and joy', and 'trust and respect' had a negative relationship. Conclusions : The core property variables of professional socialization had a different relationship with social status satisfaction, economic reward satisfaction and subjective class identification. In particular, many core property variables were associated with subjective class identification positively or negatively. The development of professional socialization would help promote job satisfaction and subjective class identification.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4684-4692
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• 2022

Radionuclide identification is an important part of the nuclear material identification system. The development of artificial intelligence and machine learning has made nuclide identification rapid and automatic. However, many methods directly use existing deep learning models to analyze the gamma-ray spectrum, which lacks interpretability for researchers. This study proposes an explainable radionuclide identification algorithm based on the convolutional neural network and class activation mapping. This method shows the area of interest of the neural network on the gamma-ray spectrum by generating a class activation map. We analyzed the class activation map of the gamma-ray spectrum of different types, different gross counts, and different signal-to-noise ratios. The results show that the convolutional neural network attempted to learn the relationship between the input gamma-ray spectrum and the nuclide type, and could identify the nuclide based on the photoelectric peak and Compton edge. Furthermore, the results explain why the neural network could identify gamma-ray spectra with low counts and low signal-to-noise ratios. Thus, the findings improve researchers' confidence in the ability of neural networks to identify nuclides and promote the application of artificial intelligence methods in the field of nuclide identification.

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.655-664
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• 2019

In this paper, we propose a novel way of combining multiple deep convolutional neural network (DCNN) architectures which work well for accurate video face identification by adopting a serial combination of 3D and 2D DCNNs. The proposed method first divides an input video sequence (to be recognized) into a number of sub-video sequences. The resulting sub-video sequences are used as input to the 3D DCNN so as to obtain the class-confidence scores for a given input video sequence by considering both temporal and spatial face feature characteristics of input video sequence. The class-confidence scores obtained from corresponding sub-video sequences is combined by forming our proposed class-confidence matrix. The resulting class-confidence matrix is then used as an input for learning 2D DCNN learning which is serially linked to 3D DCNN. Finally, fine-tuned, serially combined DCNN framework is applied for recognizing the identity present in a given test video sequence. To verify the effectiveness of our proposed method, extensive and comparative experiments have been conducted to evaluate our method on COX face databases with their standard face identification protocols. Experimental results showed that our method can achieve better or comparable identification rate compared to other state-of-the-art video FR methods.

• The KIPS Transactions:PartA
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• v.15A no.3
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• pp.155-160
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• 2008

RFID technology has been gradually expanding its application. One of the important performance issues in RFID systems is to resolve the collision among multi-tags identification on restricted area. We consider a new anti-collision scheme based on Class Identification algorithm using Depth-First scheme. We evaluate how much performance can be improved by Class identification algorithm in the cases of Query-tree more then 17% identification rate and 150% performance.

• Korea journal of population studies
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• v.29 no.3
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• pp.89-109
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• 2006

The 'Joongsancheung(JSC)', a unique term for the middle class in Korea, is defined as a stratum sharing common lifestyles and a certain level of life chances. It involves non-economic factors such as life chance, educational attainment, occupational groups as well as economic factor. Such objective measures as the occupational status of the main breadwinner, family income, and the educational level of respondent, and subjective measures of class identification are used for the operational definition of the JSC. Data from a national survey of 1,515 respondents is analyzed to investigate the change of the JSC in size and the major determinants of class identification. The results show that while there is no strong evidence of any significant change of the JSC by the objective measures during the recent decade, there seems to be a slight decrease in the subjective class identification. In addition, binary logistical regression analysis reveals that self-identification of JSC is heavily influenced by house ownership, along with subjective evaluation of one's own income and property ownership. This study demonstrates that the apparent class polarization in Korean society reflects not so much objective conditions but subjective perception of respondent of his or her circumstance. It is suggested that problems of housing and relative derivation people have as regards income and property should be resolved to alleviate such class polarization in Korean society.

• Journal of Gifted/Talented Education
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• v.20 no.1
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• pp.257-287
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• 2010

The purpose of this study is to develop an identification model for gifted students, based on class observations and nominations. The definition, issues and methods of identification were examined to achieve the research goal. Gifted identification model based on class observations and nominations consists of 4 steps: The first is the collection of multidimensional information on students, and the second is the evaluation of the students' portfolios with the rubric that has the criteria of rating scales on each information. At the third, students are observed in the class. Then the students are interviewed for the evaluation of their cognitive and non-cognitive characteristics. At the fourth, the identification committee makes a final decision for the selection of gifted students, after considering all the results from the steps. This model will be helpful to identify gifted students who are regarded to have potential abilities, especially economically disadvantaged students.

• Journal of Korea Game Society
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• v.13 no.6
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• pp.53-64
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• 2013

This study investigated how parents' parenting attitude and youth's subjective class identification influence on game addiction. Total 177 youths from 16 to 24 participated an online survey. According to the results, parents' excessive expectation and youths' high level of self-control were associated with low level of game addiction. We divided a total into two groups; low subjective class identification group vs. high subjective class identification group based on the subjective class identification(SCI) scores. In low SCI group, excessive expectation and high level of self-control were associated with low level of game addiction. On the contrary, in high SCI group, only interference was associated with low level of game addiction. Parents' certain parenting attitude variables and individuals' level of SCI is strongly related to addictive use of game media and other various type of new media.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6B
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• pp.450-455
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• 2008

We analyze the tag identification procedure of conventional EPC Class 1 RFID system and propose the fast anti-collision algorithm for the performance improvement of the system. In the proposed algorithm, the reader uses information of tag collisions and reduces unnecessary procedures of the conventional algorithm. We evaluate the performance of the proposed anti-collision algorithm and the conventional algorithm using mathematical analysis and simulation. According to the results, the fast anti-collision algorithm shows greatly better performance than conventional algorithm.

• Proceedings of the ESK Conference
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• 1996.10a
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• pp.197-205
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• 1996

Unification of neural network with a hierarchical pattern recognition is presented for recognizing large set of objects. A two-step identification procedure is developed for pattern recognition: coarse and fine identification. The coarse identification is designed for finding a class of object while the fine identification procedure is to identify a specific object. During the training phase a course neural network is trained for clustering larger set of reference objects into a number of groups. For training a fine neural network, expert neural network is also trained to identify a specific object within a group. The presented idea can be interpreted as two step identification. Experimental results are given to verify the proposed methodology.

• Journal of Electrochemical Science and Technology
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• v.1 no.1
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• pp.39-44
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• 2010

1.5 V and 3.0 V-class film-type primary batteries were designed for radio frequency identification (RFID) tag. Efficient fabrication processes such as screen-printings of conducting layer ($25{\mu}m$), active material layer ($40{\mu}m$ for anode and $80{\mu}m$ for cathode), and electrolyte/separator/electrolyte layer ($100{\mu}m$), were adopted to give better performances of the 1.5 V-class film-type Leclanch$\acute{e}$ primary battery for battery-assisted passive (BAP) RFID tag. Lithium (Li) metal is used as an anode material in a 3.0 V-class film-type $MnO_2||$Li primary battery to increase the operating voltage and discharge capacity for application to active sensor tags of a radio frequency identification system. The fabricated 3.0 V-class film-type Li primary battery passes several safety tests and achieves a discharge capacity of more than 9 mAh $cm^{-2}$.