• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.97-107
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• 2017

In the field of automatic door, the infrared rays and microwave sensor are much used as the important components in charge of the motor's operation control of open and close through the incoming signal of object recognition. In case of existing system that the sensor of the infrared rays and microwave are applied to the automatic door, there are many malfunctions by the infrared rays and visible rays of the sun. Because the automatic doors are usually installed outside of building in state of exposure. The environmental change by temperature difference occurs the noise of object recognition detection signal. With this problem, the hardware fault that the detection sensor is unable to follow the object moving rapidly within detection area makes the sensing blind spot. This fault should be improved as soon as possible. Because It influences safety of passengers who use the automatic doors. This paper conducted an experiment to improve the detection area by installing extra ultrasonic sensor besides existing detection sensor. So, this paper realize the computing circuit and detection algorithm which can correctly and rapidly process the access route of objects moving fast and the location area of fixed obstacles by applying detection and advantages of ultrasonic signal to the automatic doors. With this, It is proved that the automatic door applying ultrasonic sensor is improved detection area of blind spot sensing through field test and improvement plan is proposed.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.562-567
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• 2009

As a key mechanism of the human emotion interaction, Facial Expression is a powerful tools in HRI(Human Robot Interface) such as Human Computer Interface. By using a facial expression, we can bring out various reaction correspond to emotional state of user in HCI(Human Computer Interaction). Also it can infer that suitable services to supply user from service agents such as intelligent robot. In this article, We addresses the issue of expressive face modeling using an advanced active appearance model for facial emotion recognition. We consider the six universal emotional categories that are defined by Ekman. In human face, emotions are most widely represented with eyes and mouth expression. If we want to recognize the human's emotion from this facial image, we need to extract feature points such as Action Unit(AU) of Ekman. Active Appearance Model (AAM) is one of the commonly used methods for facial feature extraction and it can be applied to construct AU. Regarding the traditional AAM depends on the setting of the initial parameters of the model and this paper introduces a facial emotion recognizing method based on which is combined Advanced AAM with Bayesian Network. Firstly, we obtain the reconstructive parameters of the new gray-scale image by sample-based learning and use them to reconstruct the shape and texture of the new image and calculate the initial parameters of the AAM by the reconstructed facial model. Then reduce the distance error between the model and the target contour by adjusting the parameters of the model. Finally get the model which is matched with the facial feature outline after several iterations and use them to recognize the facial emotion by using Bayesian Network.

• Fire Science and Engineering
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• v.24 no.2
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• pp.145-153
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• 2010

Korea was experienced more forest fire occurrence compared to an area. As a forest fire occurrence from man caused burning for a farming increased and was one of the main reasons of forest fire occurrence in Korea, agriculturist-was a main reason of forest fire occurrence-opinion analysis was needed for forest fire prevention from this reason. Therefore, we asked agriculturist who live in province frequently experienced a forest fire from the burning for farming to answer questions. In result, a half of the respondents have a burning experience for farming and the main reason of the burning was the clearance around farmlands. In result of survey about recognition rate of forest fire prevention policy (forest fire season, incineration inhibition within 100 m from forest, license system for burning, joint burning system by a rural community, imposing a fine for burning) was almost high except license system for the burning, In the result about analysis according to ages and provinces, the recognition rate was high in province experienced severe forest fire damage and low in below 40 years group. So, the direction of forest fire prevention policy would need to be mediated in the view of agriculturist who need to use a fire because of farming labor shortage and higher age. And a consolidated education of forest fire prevention would be needed to agriculturist who live in province experienced rarely forest fire and in below 40 years group.

• Journal of Sasang Constitutional Medicine
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• v.19 no.2
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• pp.22-29
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• 2007

1. Objectives Sasang Contitutional Medicine, a part of the traditional Korean medical lore, treats illness through a constitutional typing system that categorizespeople into four constitutional types. A few of the important criteria for differentiating the constitutional types are external appearances, inner state of mind, and pathological patterns. We had been developing a 3D Automatic Face Recognition Apparatus (3D-AFRA) in order to evaluate the external appearances with more objectivity. This apparatus provides a 3D image and numerical data on facial configuration, and this study aims to evaluate the mechanical accuracy of the 3D-AFRA hardware. 2. Methods Several objects of different shapes (cube, cylinder, cone, pyramid) were each scanned 10 times using the 3D Automatic Face Recognition Apparatus (3D-AFRA). The results were then compared and analyzed with data retrieved through a laser scanner known for its high accuracy. The error rates were analyzed for each grid point of facial contour scanned with Rapidform2006 (Rapidform2006 is a 3D scanning software that collects grid point data for contours of various products and products and product parts through 3D scanners and other 3D measuring devices; the grid point data thusly acquired is then used to reconstruct highly precise polygon and curvature models). 3. Results and Conclusions The average error rate was 0.22mm for the cube, 0.22mm for the cylinder, 0.125mm for the cone, and 0.172mm for the pyramid. The visual data comparing error rates for measurement figures retrieved with Rapidform2006 is shown in $Fig.3{\sim}Fig.6$. Blue tendency indicates smaller error rates, while red indicates greater error rates The protruding corners of the cube display red, indicating greater error rates. The cylinder shows greater error rates on the edges. The pyramid displays greater error rates on the base surface and around the vertex. The cone also shows greater error around the protruding edge.

• Culinary science and hospitality research
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• v.15 no.1
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• pp.169-180
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• 2009

Nowadays the pursuit of health among people leads to the unceasing pursuit of healthy dishes. Although many kinds of ingredients which are not fatty are used in Korean dishes, Korean dishes has not been approved as healthy ones in foreign countries yet. This study considers the recognition of Korean dishes and Bibimbap. 299 Chinese students in Shenyang, China took part in this investigation. The results of this study state that 25 percent of respondents do not like Korean dishes while 27 percent of respondents do not like Bibimbap. And the respondents who dislike Korean dishes cite the reasons of its 'bad taste' and 'bad looks'. That is, in order to increase the popularity of Bibimbap and make Korean dishes as a domestic diet culture in China, we should know about the tastes and kinds of dishes that Chinese people like. Also, we should consider the reasons why Chinese people like and do not like, and then develop Bibimbap to make the majority of Chinese people like it.

• Culinary science and hospitality research
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• v.16 no.4
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• pp.177-189
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• 2010

This study investigates the perceptual differences on geographical indications among consumers, producers, and government employees. First, in terms of the recognition of the geographical indication certification mark, approximately 56% of consumers showed no experience to recognize the mark, indicating their low level of recognition. Besides, some respondents among producers and government employees indicated no experience or no recollection on the certification mark. In terms of the vitalization of geographical indications, consumers and government employees showed positive responses while producers were negative on it. Consumers and government employees attributed the reasons for the low level of vatalization of geographical indications to the low level of consumer recognition. On the other band, producers indicated that the complicated registration procedure and incidental expenses were the main reasons for this issue. Lastly, this study examined if there were significant differences on the perceived consumer preferences on the domestic and imported agricultural and processed products among the three groups. The results found that producers and government employees perceived that consumers preferred the imported products to the domestic products than customers actually did, indicating the lack of understanding of these two groups on consumer preferences on agricultural and processed products.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.530-536
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• 2021

Recently, due to the development of deep learning, end-to-end speech recognition, which directly maps graphemes to speech signals, shows good performance. Especially, among the end-to-end models, conformer shows the best performance. However end-to-end models only focuses on the probability of which grapheme will appear at the time. The decoding process uses a greedy search or beam search. This decoding method is easily affected by the final probability output by the model. In addition, the end-to-end models cannot use external pronunciation and language information due to structual problem. Therefore, in this paper conformer with lexicon transducer is proposed. We compare phoneme-based model with lexicon transducer and grapheme-based model with beam search. Test set is consist of words that do not appear in training data. The grapheme-based conformer with beam search shows 3.8 % of CER. The phoneme-based conformer with lexicon transducer shows 3.4 % of CER.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.1
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• pp.93-114
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• 2023

Information extraction can facilitate the intensive analysis of documents by providing semantic triples which consist of named entities and their relations recognized in the texts. However, most of the research so far has been carried out separately for named entity recognition and relation extraction as individual studies, and as a result, the effective performance evaluation of the entire information extraction systems was not performed properly. This paper introduces two models of end-to-end information extraction that can extract various entity names in clinical records and their relationships in the form of semantic triples, namely pipeline and joint models and compares their performances in depth. The pipeline model consists of an entity recognition sub-system based on bidirectional GRU-CRFs and a relation extraction module using multiple encoding scheme, whereas the joint model was implemented with a single bidirectional GRU-CRFs equipped with multi-head labeling method. In the experiments using i2b2/VA 2010, the performance of the pipeline model was 5.5% (F-measure) higher. In addition, through a comparative experiment with existing state-of-the-art systems using large-scale neural language models and manually constructed features, the objective performance level of the end-to-end models implemented in this paper could be identified properly.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.143-151
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• 2010

Fingerprint classification is a step to increase the efficiency of an 1:N fingerprint recognition system and plays a role to reduce the matching time of fingerprint and to increase accuracy of recognition. It is difficult to classify fingerprints, because the ridge pattern of each fingerprint class has an overlapping characteristic with more than one class, fingerprint images may include a lot of noise and an input condition is an exceptional case. In this paper, we propose a novel approach to design a stochastic model and to accomplish fingerprint classification using a directional characteristic of fingerprints for an effective classification of various qualities. We compute the directional value by searching a fingerprint ridge pixel by pixel and extract a directional characteristic by merging a computed directional value by fixed pixels unit. The modified Markov model of each fingerprint class is generated using Markov model which is a stochastic information extraction and a recognition method by extracted directional characteristic. The weight list of classification model of each class is decided by analyzing the state transition matrixes of the generated Markov model of each class and the optimized value which improves the performance of fingerprint classification using GA (Genetic Algorithm) is estimated. The performance of the optimized classification model by GA is superior to the model before the optimization by the experiment result of applying the fingerprint database of various qualities to the optimized model by GA. And the proposed method effectively achieved fingerprint classification to exceptional input conditions because this approach is independent of the existence and nonexistence of singular points by the result of analyzing the fingerprint database which is used to the experiments.

• Korean Journal of Forensic Psychology
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• v.12 no.2
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• pp.171-197
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• 2021

The purpose of this study is to examine empirically how the lay people judge self-defense and what factors could affect it. A total of 651 participants aged 20 years and over were asked to answer, attitude toward interpersonal violence, and legal attitude questionnaire, all divided by the type of self-defense. Participants were assigned one of the three types of situations that were claimed to be self-defense, and were given articles and scenarios related to each type of self-defense before making self-defense judgments. In addition, the impact of personal factors on self-defense judgment was analyzed after the legal attitude, and the attitude toward interpersonal violence, which are personal factors, was also measured. The results showed that the rate of recognition of self-defense was the highest in the type of self-defense for oneself, but the rate of denial of self-defense against state agencies was much higher, indicating the opposite. Furthemore, negative articles on self-defense were found to affect the judgment of self-defense. In addition, it was found that the level of the attitude toward interpersonal violence and legal attitude of individual participants could affect the judgment of self-defense. The general public's judgment process and the factors that affect self-defense judgment may be considered to prevent biased judgment in actual jury trials. Finally, influence, and limitations of this study and suggestions of subsequent study were also discussed.