• Korean Journal of Childcare and Education
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• v.9 no.2
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• pp.97-115
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• 2013

The present study examined the relationships between work related flow (i.e., absorption, work enjoyment, and intrinsic work motivation) and role conflict causes (i.e., teacher's belief, teaching and interaction with young children, comradeship, relationships with parents, workload, supervision, and social awareness of the job). A canonical correlation analysis was performed on the data from a sample of 154 childcare teachers. The results are as follows (1) there was a reciprocal-causal relationship between teachers' role conflict causes and their work-related flow; (2) canonical function 1 showed that absorption and work enjoyment are strongly associated to a teacher's belief and supervision of conflict causes; and (3) canonical function 2 showed that intrinsic motivation has a relatively strong relationship with workload and supervision of conflict causes. It can be concluded that it is important for childcare teachers to have sufficient job resources to promote their flow at work. Further research is needed for investigation of teacher's flow at various conditions of work.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1872-1879
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• 2016

The techniques to recycle and reuse plastics attract public attention. These public attraction and needs result in improving the recycling technique. However, the identification technique for black plastic wastes still have big problem that the spectrum extracted from near infrared radiation spectroscopy is not clear and is contaminated by noise. To overcome this problem, we apply Raman spectroscopy to extract a clear spectrum of plastic material. In addition, to improve the classification ability of fuzzy Radial Basis Function Neural Networks, we apply supervised learning based clustering method instead of unsupervised clustering method. The conditional fuzzy C-Means clustering method, which is a kind of supervised learning based clustering algorithms, is used to determine the location of radial basis functions. The conditional fuzzy C-Means clustering analyzes the data distribution over input space under the supervision of auxiliary information. The auxiliary information is defined by using k Nearest Neighbor approach.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1335-1341
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• 2016

For the safety of train operation, monitoring & supervisory systems for train, signal, power, communication and facilities is operating independently in another place, so, its sensors are interdependently connected from each other to transfer gathering datas of sensing to control center. A Goal of Real-time railway safety supervision system is to improve the safety oversight efficiency and to prevent accidents by means of hazard prediction based on big data by integrating all of safety sensing data in wayside of railway, and the System is requested acquisition of all of sensing data of safety. So, we need special method of protocol converting for the purpose of integrating all of detecting data concerning safety without any changing application. In this paper we investigate the existing converting method in communication field, and propose a new progress to converting protocol adding function of transfer using XML file, and implemented this algorithm, and tested with example packets, finally.

• Journal of the Korea Computer Graphics Society
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• v.30 no.1
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• pp.11-17
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• 2024

Lung cancer segmentation in chest CT images is challenging due to the varying sizes of tumors and the presence of surrounding structures with similar intensity values. To address these issues, we propose a lung cancer segmentation network that incorporates deep supervision and utilizes UNet3+ as the backbone. Additionally, we propose a hybrid lesion focal loss function comprising three components: pixel-based, region-based, and shape-based, which allows us to focus on the smaller tumor regions relative to the background and consider shape information for handling ambiguous boundaries. We validate our proposed method through comparative experiments with UNet and UNet3+ and demonstrate that our proposed method achieves superior performance in terms of Dice Similarity Coefficient (DSC) for tumors of all sizes.

• Smart Structures and Systems
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• v.32 no.3
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• pp.135-151
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• 2023

Using 3D asphalt pavement surface data, a deep and multiscale network named CrackNet-M is proposed in this paper for pixel-level crack detection for improvements in both accuracy and robustness. The CrackNet-M consists of four function-specific architectural modules: a central branch net (CBN), a crack map enhancement (CME) module, three pooling feature pyramids (PFP), and an output layer. The CBN maintains crack boundaries using no pooling reductions throughout all convolutional layers. The CME applies a pooling layer to enhance potential thin cracks for better continuity, consuming no data loss and attenuation when working jointly with CBN. The PFP modules implement direct down-sampling and pyramidal up-sampling with multiscale contexts specifically for the detection of thick cracks and exclusion of non-crack patterns. Finally, the output layer is optimized with a skip layer supervision technique proposed to further improve the network performance. Compared with traditional supervisions, the skip layer supervision brings about not only significant performance gains with respect to both accuracy and robustness but a faster convergence rate. CrackNet-M was trained on a total of 2,500 pixel-wise annotated 3D pavement images and finely scaled with another 200 images with full considerations on accuracy and efficiency. CrackNet-M can potentially achieve crack detection in real-time with a processing speed of 40 ms/image. The experimental results on 500 testing images demonstrate that CrackNet-M can effectively detect both thick and thin cracks from various pavement surfaces with a high level of Precision (94.28%), Recall (93.89%), and F-measure (94.04%). In addition, the proposed CrackNet-M compares favorably to other well-developed networks with respect to the detection of thin cracks as well as the removal of shoulder drop-offs.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2098-2106
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• 2014

In the area of clustering, there are numerous approaches to construct clusters in the input space. For regression problem, when forming clusters being a part of the overall model, the relationships between the input space and the output space are essential and have to be taken into consideration. Conditional Fuzzy C-Means (c-FCM) clustering offers an opportunity to analyze the structure in the input space with the mechanism of supervision implied by the distribution of data present in the output space. However, like other clustering methods, c-FCM focuses on the distribution of the data. In this paper, we introduce a new method, which by making use of the ambiguity index focuses on the boundaries of the clusters whose determination is essential to the quality of the ensuing classification procedures. The introduced design is illustrated with the aid of numeric examples that provide a detailed insight into the performance of the fuzzy classifiers and quantify several essentials design aspects.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.554-556
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• 2005

Distribution Automation System (DAS) will provide supervision and remote control of switches and reclosers such as pole pounted switches and pad-mounted switchgears on high voltage distribution line. Kepco had developed basic function such as remote monitoring, remote control, remote measuring and remote setting at first. As a next step, Kepco has been developed diverse application programs such as single line diagram drawing program, relay coordination program, feeder reconfiguration program, over load elimination program, bad data detection program, section load management program, fault processing program and so on. Kepco is examining to develop more powerful functions for special specification of foreign distribution automation system. This paper explains what is the target for overseas DAS market.

• Journal of Korean Public Health Nursing
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• v.3 no.1
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• pp.18-37
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• 1989

This study was done in order to analyze the factors which influenced the performance level of community health practitioners' task. Interview survey was done during the period from August to October, 1986. Interviewee were 166 CHPs among total of 217 CHPs in Kyonggi province area. Multiple stepwise regression and canonical correlation analysis were used to identify major factors influenced to perform community health practitioners' task. The results of this study were summarized as follows: 1. General characteristics of CHPs 1) Personal characteristics The average age of CHPs was 37.8 years and their marital status was $77.6\%$ of married, educational back-ground was $65.3\%$ of junior college graduation. Their job career was $38.6\%$ of between 1-3 years, $33.3\%$ of between 3-5 years, $22.2\%$ of less than 1 years. Most of CHPs$(62.8\%)$ were fully satisfied with their job, $33.3\%$ were moderately, and $3.8\%$ were not satisfied. 2) Working environmental condition Only $31.7%$ of CHPs were satisfied with their working condition of primary health post, $26.6\%$ were not satisfied. Half of CHPs$(52.5\%)$ replied having good cooperation with health center, $10.1\%$ replied bad. Cooperation with health subcenter was good in $32.9\%$, and bad in $21.9%$. Cooperation with private health institutions was good in $34.2\%$, bad in $21.6%$. 2. Performance level of community health practitioners' task Among a total of 52 contents of their functions medical history taking. physical examination, referral of diagnostic laboratory work-up($(86.4\%)$, health assessment of pregnant women$(82.1\%)$, development of health information system$(79.4\%)$, supervision of health workers $(78.4\%)$, follow-up of family planning acceptors$(77.3\%)$, and follow-up of family planning acceptors' side effects$(77.3\%)$ were actively performed. Diagnosis of pregnancy$(62.1\%)$, sampling of drinking water for quality test$(52.5\%)$, making list of equipment' & supplies $(51.5\%)$, evaluation of primary health post activities $(37.6\%)$, organization of village health workers$(32.4\%)$ and management of village health workers $(30.1\%)$ were poorly performed. 3. Stepwise multiple regression analysis of job function The factors which influenced the performance level of community health practitioners' function were age, marital status, educational level, job career, job satisfaction, satisfaction of working environment of primary health post, cooperation of health center, cooperation of health center, cooperation of private health instiutions in orders. These 9 variables were able to explain job function from $25.7\%$ of program planning to $6.7\%$ of management of common disease. 4. Canonical correlation analysis between the performance of function and general characteristics of CHPs. Cooperation of private health institutions was found to be the factor influencing task performance of community organization, management of primary health post, technical supervision of health personnels. Job satisfaction of CHPs was also found to be the factor influencing task performance of family planning, management of common disease and maintenance of health information system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2433-2440
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• 2009

Whole system and network for supply of electric power and electricity safety are essential element. Electricity safety technology need rating for product and research about certification as product development that is done electric power u-IT cotton flannel mixed with development of u-IT, u-City base technology consists. Study on serve to develop electricity safety integration supervision system to apply product to u-City electric power appliance and cotton flannel mixed of u-IT appliance, Connection badness sensing instrument made device built-in electric power u-IT cotton flannel mixed in outlet that is used most in electric power appliance terminal. Using sensor on ZigBee, RFID performance estimation of communication module about function of product for remote safety check of electricity safety integration supervision system. A performance experiment and estimation in electric leakage, high voltage, Arc, fire detection diagnosis system and certification KS, electricity safety about product that get fitness finding.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.1
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• pp.88-95
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• 2015

For the frequency-domain spectral fatigue analysis, the probability density function of stress range needs to be estimated based on the stress spectrum only, which is a frequency domain representation of the response. The probability distribution of the stress range of the narrow-band spectrum is known to follow the Rayleigh distribution, however the PDF of wide-band spectrum is difficult to define with clarity due to the complicated fluctuation pattern of spectrum. In this paper, efforts have been made to figure out the links between the probability density function of stress range to the structural response of wide-band Gaussian random process. An artificial neural network scheme, known as one of the most powerful system identification methods, was used to identify the multivariate functional relationship between the idealized wide-band spectrums and resulting probability density functions. To achieve this, the spectrums were idealized as a superposition of two triangles with arbitrary location, height and width, targeting to comprise wide-band spectrum, and the probability density functions were represented by the linear combination of equally spaced Gaussian basis functions. To train the network under supervision, varieties of different wide-band spectrums were assumed and the converged probability density function of the stress range was derived using the rainflow counting method and all these data sets were fed into the three layer perceptron model. This nonlinear least square problem was solved using Levenberg-Marquardt algorithm with regularization term included. It was proven that the network trained using the given data set could reproduce the probability density function of arbitrary wide-band spectrum of two triangles with great success.