• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.75-82
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• 2008

National technical qualification does not recognised degree of working-career in labor market and an industrial field situation. National qualification is supply to nurture expert manpower and accomplish of self-development and a duty accomplishment ability improvement at a side of personal. So, This study is purposed to find that a method for recognition of working-career on the national technical qualification system According to, this study is designed to questionnaire with BSC(Balaced ScoreCard), SEM(Structure Equation Model) with the delphi method, and is analysed using the AMOS 7.0 program package. Finally, This study is suggested growing to qualification standard for an examination a degree of master craftsman only under the change of national qualification systematization as a standard to operation and control.

• Journal of the Korean Society of Safety
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• v.10 no.4
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• pp.60-67
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• 1995

Ocassionally, many chemical plants experienced unexpected shutdown and suffered serious economic loss caused by boiler accidents due to mis-operations during the start-up or shutdown. A strategy to prevent such accidents is proposed here by using the form of frame for the recognition of all needed conditions, i.e., the states of the boiler, hazardous or dangerous conditions, each level conditions, transition network and heuristic knowledge of human operators. The expert system based on this strategy is considered to be an available method to predict all of the hazardous conditions in boiler plants.

• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.275-285
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• 2008

National technical qualification does not recognised degree of working-career in labor market and an industrial field situation. National qualification is supply to nurture expert manpower and accomplish of self-development and a duty accomplishment ability improvement at a side of personal. So, This study is purposed to find that a method for recognition of working-career on the national technical qualification system. According to, this study is designed to questionnaire with BSC(Balaced ScoreCard), SEM(Structure Equation Model) with the delphi method, and is analysed using the AMOS 7.0 program package. Finally, This study is suggested growing to qualification standard for an examination a degree of master craftsman only under the change of national qualification systematization as a standard to operation and control.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.542-546
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• 2007

In the vision of ubiquitous computing environment, smart objects would communicate each other and provide many kinds of information about user and their surroundings in the home. This information enables smart objects to recognize context and to provide active and convenient services to the customers. However in most cases, context-aware services are available only with expert systems. In this paper, we present generalized activity recognition application in the smart home based on a naive Bayesian network(BN) and fuzzy clustering. We quantize continuous sensor data with fuzzy c-means clustering to simplify and reduce BN's conditional probability table size. And we apply mutual information to learn the BN structure efficiently. We show that this system can recognize user activities about 80% accuracy in the web based virtual smart home.

• ETRI Journal
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• v.43 no.5
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• pp.881-890
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• 2021

Photoplethysmography (PPG) is a noninvasive technique that can be used to conveniently measure heart rate (HR) and thus obtain relevant health-related information. However, developing an automated PPG system is difficult, because its waveforms are susceptible to motion artifacts and between-patient variation, making its interpretation difficult. We use deep neural network (DNN) filters to mimic the cognitive ability of a human expert who can distinguish the features of PPG altered by noise from various sources. Systolic (S), onset (O), and first derivative peaks (W) are recognized by three different DNN filters. In addition, the boundaries of uninformative regions caused by artifacts are identified by two different filters. The algorithm reliably derives the HR and presents recognition scores for the S, O, and W peaks and artifacts with only a 0.7-s delay. In the evaluation using data from 11 patients obtained from PhysioNet, the algorithm yields 8643 (86.12%) reliable HR measurements from a total of 10 036 heartbeats, including some with uninformative data resulting from arrhythmias and artifacts.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.716-719
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• 2004

This study proposes an algorithm for recognition of crack patterns, which includes horizontal, vertical, diagonal$(-45^{\circ})$, diagonal$(+45^{\circ})$, and random cracks, based on image processing technique and artificial neural network. A MATLAB code was developed for the proposed algorithm, and then numerical tests were performed on thirty-eight crack images to examine validity of the algorithm. Within the limited tests in the present study, the proposed algorithm was revealed as accurately recognizing the crack patterns when compared to those classified by a human expert.

• Journal of Biosystems Engineering
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• v.19 no.2
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• pp.124-137
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• 1994

Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.3
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• pp.203-216
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• 2003

In this paper a new feature extraction and target classification method is proposed for the recognition part of FLIR(Forwar Looking Infrared)-image-based ATR system. Proposed feature extraction method is "cluster(=set of classes)-based"version of previous fisherfaces method that is known by its robustness to illumination changes in face recognition. Expecially introduced class clustering and cluster-based projection method maximizes the performance of fisherfaces method. Proposed target image classification method is based on the mixture of experts model which consists of RBF-type experts and MLP-type gating networks. Mixture of experts model is well-suited with ATR system because it should recognizee various targets in complexed feature space by variously mixed conditions. In proposed classification method, one expert takes charge of one cluster and the separated structure with experts reduces the complexity of feature space and achieves more accurate local discrimination between classes. Proposed feature extraction and classification method showed distinguished performances in recognition test with customized. FLIR-vehicle-image database. Expecially robustness to pixelwise sensor noise and un-wanted intensity variations was verified by simulation.

• MALSORI
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• no.67
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• pp.181-193
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• 2008

In this paper, we propose a vocabulary coverage improvement method for embedded continuous speech recognition (CSR) using a part-of-speech (POS) tagged corpus. We investigate 152 POS tags defined in Lancaster-Oslo-Bergen (LOB) corpus and word-POS tag pairs. We derive a new vocabulary through word addition. Words paired with some POS tags have to be included in vocabularies with any size, but the vocabulary inclusion of words paired with other POS tags varies based on the target size of vocabulary. The 152 POS tags are categorized according to whether the word addition is dependent of the size of the vocabulary. Using expert knowledge, we classify POS tags first, and then apply different ways of word addition based on the POS tags paired with the words. The performance of the proposed method is measured in terms of coverage and is compared with those of vocabularies with the same size (5,000 words) derived from frequency lists. The coverage of the proposed method is measured as 95.18% for the test short message service (SMS) text corpus, while those of the conventional vocabularies cover only 93.19% and 91.82% of words appeared in the same SMS text corpus.

• Economic and Environmental Geology
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• v.45 no.3
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• pp.335-346
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• 2012

This study investigates the differences of recognition about geo-technologies outcome between experts and nonexperts. Based on these findings, this study would offer suggestions for future communication strategies on research outcome in a various field of scientific research as well as KIGAM. The result shows that there are differences between expert and nonexpert in the level of recognition about geoscience research outcome. The findings of this study emphasize the needs for recognizing the concept that geo-technologies are directly related to people's lives and external communication is necessary.