• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.370-377
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• 2018

Focus level has been important mental state in user study. Cardiac response has been related to focus and less clarified. The study was to determine cardiac parameters for recognizing focus level. The sixty participants were asked to play shooting game designed to control two focus levels. Electrocardiogram was measured during task. The parameters of time domain and frequency domain were determined from ECG. As a result of independent t-test, RRI, SDNN, rMSSD and pNN50 of time domain indicator were statistically significant in recognizing focus level. LF, HF, lnLF and lnHF of frequency domain were observed to be significant indicator. The rule base for recognition has been developed by the combination of RRI, rMSSD and lnHF. The rule base has been verified from another sixty data samples. The recognition accuracy were 95%. This study proposed significant cardiac indicators for recognizing focus level. The results provides objective measurement of focus in user interaction design in the fields of contents industry and service design.

• The Korean Journal of Food And Nutrition
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• v.24 no.3
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• pp.282-290
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• 2011

This study was performed to investigate the level and recognition and interest in nutrition labeling in restaurants according to consumer interest levels in health and to suggest its application to restaurant lunches. By considering various statistics and data on the frequency of reasons for dining-out, this study examined worker restaurant lunches and investigated the level of recognition of interest in nutrition labeling, the type of nutrition information that is of interest and the preferred format of labeling according to the level of interest in health. According to the results, while the frequency of dining-out by workers was high, their consideration for health and nutrition labeling in restaurants was low. However, a high percentage of consumers responded that nutrition labeling was a customer right and necessary to improve the quality of menu items as well as public health. Therefore, active promotion of nutrition labeling in the dining industry is necessary. Interest levels in additives, product origin and menu ingredients indicated in restaurant menus were higher than for nutritional information such as nutrients and calories. When the preferred format for providing nutrition information was investigated, consumers preferred information written on a menu board, and they wanted to broaden the range of information included in nutrition labeling for menu items beyond calories and nutritional facts. Based on these results, recognition of nutrition labeling in restaurants was found to below and the interest level in health was also lower than expected. However, most consumers responded that nutrition labeling was helpful in choosing menu items can be a tool for nutrition education and can play a role in improving the recognition of nutrition. Therefore, active promotion of nutrition labeling by the dining industry is necessary.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.792-798
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• 2004

In this paper, we will introduce a new corner detector for the wafer die position recognition. The die position recognition procedure is necessary for WSCSP(Wafer Scale Chip Scale Packaging) technology, decide the accuracy of post-procedure. We present a hierarchical gray level corner detection method for the recognition of the die position from a wafer image. The new corner detector divides the corner region into many homocentric circles, and calculates the comer response and the angle of direction about each circle to get an accurate toner point. The new corner detector has a hierarchical structure so it can detect comer point more quickly than general gray level corner detector.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.219-222
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• 2009

Rapid object recognition is one of the main stream research themes focusing to reveal how human recognizes object and interacts with environment in natural world. This field of study is of consequence in that it is highly important in evolutionary perspective to quickly see the external objects and judge their characteristics to plan future reactions. In this study, we investigated how human detect natural scene objects and categorize them in a limited time frame. We applied Magnetoencepahlogram (MEG) while participants were performing detection (e.g. object vs. texture) or basic-level categorization (e.g. cars vs. dogs) tasks to track the dynamic interaction in human brain for rapid object recognition process. The results revealed that detection and categorization involves different temporal and functional connections that correlated for the successful recognition process as a whole. These results imply that dynamics in the brain are important for our interaction with environment. The implication from this study can be further extended to investigate the effect of subconscious emotional factors on the dynamics of brain interactions during the rapid recognition process.

• Korean Journal of Human Ecology
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• v.12 no.2
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• pp.225-236
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• 2003

The purposes of this study were to promote the consumer's recognition on the internet purchase of fashion products and to provide useful information which would help web-site plan design, product composition, and service of internet shopping mall. The subjects were consisted of 693 students who had experiences of the accesses to internet fashion shopping mills or experiences of purchasing through internet in Cheongju and Daejeon region. Data were analyzed by factor analysis, frequency, percentage, mean, standard deviation, t-test, ANOVA, and LSD. The Results were as follows: 1. Merit factors of the internet shopping were found to be shopping convenience and pursuit of product information. Whereas, demerit factors of the internet shopping to be complexity of order, delivery, functional and economic riskiness, and services. 2. Gender was the only factor differentiating the level of recognition toward the internet fashion shopping mall. And the level of recognition also showed significant differences according to period, time, purpose of access, type of shopping mall, purchase experience, and average purchase price.

• Journal of the Korea Fashion and Costume Design Association
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• v.9 no.3
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• pp.87-97
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• 2007

This study is to investigate the KS size recognition and mother's preference of female children's apparel. The practical research is performed for 150 mothers lived in Seoul and are randomly selected to their age, female children's number, education and income level. For statistical analysis and evaluation of survey data, frequency and percentage use contingency table. Findings in this study as follow: 1. Mother's preference for purchasing the girl's garments shows the significant differences of their subject characteristics such as age, girl's number, education and income level. 2. Mother's recognition about KSK 9403: 2004 sizing system for girl's garments does not show the significant differences of their subject properties. Most mothers only know the part of the KS size specifications because KS sizing systems are complex. So KS sizing systems must be simplified and respecified to understand the KS for mothers easily when purchasing their girl's garments. In summary this paper investigates mother's preference and recognition about KS sizing system for the girl's garments.

• ETRI Journal
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• v.44 no.3
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• pp.462-475
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• 2022

Although researchers have proposed numerous techniques for speech emotion recognition, its performance remains unsatisfactory in many application scenarios. In this study, we propose a speech emotion recognition model based on a genetic algorithm (GA)-decision tree (DT) fusion of deep and acoustic features. To more comprehensively express speech emotional information, first, frame-level deep and acoustic features are extracted from a speech signal. Next, five kinds of statistic variables of these features are calculated to obtain utterance-level features. The Fisher feature selection criterion is employed to select high-performance features, removing redundant information. In the feature fusion stage, the GA is is used to adaptively search for the best feature fusion weight. Finally, using the fused feature, the proposed speech emotion recognition model based on a DT support vector machine model is realized. Experimental results on the Berlin speech emotion database and the Chinese emotion speech database indicate that the proposed model outperforms an average weight fusion method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3211-3229
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• 2022

To solve the problems existing in the process of Weibo disaster rumor recognition, such as lack of corpus, poor text standardization, difficult to learn semantic information, and simple semantic features of disaster rumor text, this paper takes Sina Weibo as the data source, constructs a dataset for Weibo disaster rumor recognition, and proposes a deep learning model BERT_AT_Stacked LSTM for Weibo disaster rumor recognition. First, add adversarial disturbance to the embedding vector of each word to generate adversarial samples to enhance the features of rumor text, and carry out adversarial training to solve the problem that the text features of disaster rumors are relatively single. Second, the BERT part obtains the word-level semantic information of each Weibo text and generates a hidden vector containing sentence-level feature information. Finally, the hidden complex semantic information of poorly-regulated Weibo texts is learned using a Stacked Long Short-Term Memory (Stacked LSTM) structure. The experimental results show that, compared with other comparative models, the model in this paper has more advantages in recognizing disaster rumors on Weibo, with an F1_Socre of 97.48%, and has been tested on an open general domain dataset, with an F1_Score of 94.59%, indicating that the model has better generalization.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.569-577
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• 2000

The position of tobacco leaves is affluence to the quality. To evaluate its quality, sample leaves was collected according to the position of attachment. In Korea, the position was divided into four classes such as high, middle, low and inside positioned leaves. Until now, the grade of standard sample was determined by human expert from korea ginseng and tobacco company. Many research were done by the chemical and spectrum analysis using NIR and computer vision. The grade of tobacco leaves mainly classified into 5 grades according to the attached position and its chemical composition. In high and low positioned leaves shows a low level grade under grade 3. Generally, inside and medium positioned leaf has a high level grade. This is the basic research to develop a real time tobacco leaves grading system combined with portable NIR spectrum analysis system. However, this research just deals with position recognition and grading using the color machine vision. The RGB color information was converted to HSI image format and the sample was all investigated using the bundle of tobacco leaves. Quality grade and position recognition was performed through well known general error back propagation neural network. Finally, the relationship about attached leaf position and its grade was analyzed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.549-551
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• 2006

Vehicle License Plate Recognition System reads information from vehicles license plate using image detection devices. Of many applications provided by Vehicle License Plate Recognition System, some, such as speed enforcing system, can be problematic when the system incorrectly scans letters or numbers from a vehicle's license plate. Using Cautious Classifier avoids such problems by discarding the scanned information when the confidence level is doubted to be low. This study develops the License Plate Recognition System using Cautious Classifier and investigates effectiveness of applying the Weighted Instance Method to improve the performance of Cautious Classifier.