• Korean Journal of Human Ecology
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• v.14 no.6
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• pp.1017-1025
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• 2005

The purpose of this paper was to investigate the relationship between customer orientation and sales training. Data were obtained from 297 apparel salespeople working at six department stores in Daegu. Statistics used for data analysis were frequency, factor analysis, correlation, and t-test. The respondents were classified into 3 groups; high, medium, and low customer-oriented groups based on the mean score of customer orientation, and the high and the low were compared in training contents and educational methods. Based on factor analysis, four factors were extracted from 27 items of training content. Two of four factors were significantly correlated with customer orientation. The regression analysis showed that customer service and duration of work had significant effects on customer orientation. Also, the results were found that there were significant differences between the high and the low customer-oriented group in training contents which salespeople want to have in the future. However, there were not significant differences between the two groups in educational methods.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.461-469
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• 2022

This paper presents a novel training data extraction approach using semi-supervised learning (SSL)-based classification without the analyst intervention for time-series land-cover mapping. The SSL-based approach first performs initial classification using initial training data obtained from past images including land-cover characteristics similar to the image to be classified. Reliable training data from the initial classification result are then extracted from SSL-based iterative classification using classification uncertainty information and class labels of neighboring pixels as constraints. The potential of the SSL-based training data extraction approach was evaluated from a classification experiment using unmanned aerial vehicle images in croplands. The use of new training data automatically extracted by the proposed SSL approach could significantly alleviate the misclassification in the initial classification result. In particular, isolated pixels were substantially reduced by considering spatial contextual information from adjacent pixels. Consequently, the classification accuracy of the proposed approach was similar to that of classification using manually extracted training data. These results indicate that the SSL-based iterative classification presented in this study could be effectively applied to automatically extract reliable training data for time-series land-cover mapping.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.317-324
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• 2010

In recent years, many automatic classification approaches have been employed. An automatic classification method can be effective, time-saving and can produce objective results due to the exclusion of operator intervention. This paper proposes a classification method based on automated training for high resolution multispectral images using ancillary data. Generally, it is problematic to automatically classify high resolution images using ancillary data, because of the scale difference between the high resolution image and the ancillary data. In order to overcome this problem, the proposed method utilizes the classification results of a Landsat image as a medium for automatic classification. For the classification of a Landsat image, a maximum likelihood classification is applied to the image, and the attributes of ancillary data are entered as the training data. In the case of a high resolution image, a K-means clustering algorithm, an unsupervised classification, was conducted and the result was compared to the classification results of the Landsat image. Subsequently, the training data of the high resolution image was automatically extracted using regular rules based on a RELATIONAL matrix that shows the relation between the two results. Finally, a high resolution image was classified and updated using the extracted training data. The proposed method was applied to QuickBird and SPOT-5 images of non-accessible areas. The result showed good performance in accuracy assessments. Therefore, we expect that the method can be effectively used to automatically construct thematic maps for non-accessible areas and update areas that do not have any attributes in geographic information system.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1439-1445
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• 2013

We present a Taekwondo training system using a hybrid sensing technique of a body sensor and a visual sensor. Using a body sensor (accelerometer), rotational and inertial motion data are captured which are important for Taekwondo motion detection and evaluation. A visual sensor (camera) captures and records the sequential images of the performance. Motion chunk is proposed to structuralize Taekwondo motions and design HMM (Hidden Markov Model) for motion recognition. Trainees can evaluates their trial motions numerically by computing the distance to the standard motion performed by a trainer. For motion training video, the real-time video images captured by a camera is overlayed with a visualized body sensor data so that users can see how the rotational and inertial motion data flow.

• Speech Sciences
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• v.7 no.1
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• pp.31-37
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• 2000

This paper concerns effective speaker adaptation methods to solve the over-training problem in speaker verification, which frequently occurs when modeling a speaker with sparse training data. While various speaker adaptations have already been applied to speech recognition, these methods have not yet been formally considered in speaker verification. This paper proposes speaker adaptation methods using a combination of MAP and MLLR adaptations, which are successfully used in speech recognition, and applies to speaker verification. Experimental results show that the speaker verification system using a weighted MAP and MLLR adaptation outperforms that of the conventional speaker models without adaptation by a factor of up to 5 times. From these results, we show that the speaker adaptation method achieves significantly better performance even when only small training data is available for speaker verification.

• Journal of Sport and Applied Science
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• v.4 no.4
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• pp.1-6
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• 2020

Purpose: The purpose of this study is to identify the effect of 24-week sensory integration activity training on fitness of children with intellectual disability. Research design, data, and methodology: The subjects were 10 children with intellectual disability, 60 min training of sensory integration activity for 24 weeks. Obesity, cardiovascular endurance, muscular strength and muscle endurance were measured pre and post training. Frist, characteristics of subjects were measured with age, height, weight, IQ and SQ. Second, the subjects then performed sensory integration activity training for 24 weeks. Last, weight, strength, endurance, cardiovascular endurance and flexibility were measured. Data were calculated for average and standard deviation by SPSS 25.0 statistic program, and dependent sample t-test was processed to analyze the change between pre and post training. All statistical significance level was set to 0.5. Results: The result was shown that weight, strength and endurance changes between pre and post were significant. However, cardiovascular endurance, flexibility changes between pre and post were not significant. Conclusions: The lack of training frequency of 60 minute per week were acknowledged per week from this result. In future research, increased intensity and frequency are need for an in-depth and meaningful study and the measured data can be used basic information for the study.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.159-166
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• 2023

Due to the aging workforce in the construction industry in South Korea, the accident rate has been increasing. The cognitive abilities of older workers are closely related to both safety incidents and labor productivity. Therefore, there is a need to improve cognitive abilities through personalized training based on cognitive assessment results, using cognitive training content, in order to enable safe performance in labor-intensive environments. The provided cognitive training content includes concentration, memory, oreintation, attention, and executive functions. Difficulty levels were applied to each content to enhance user engagement and interest. To stimulate interest and encourage active participation of the participants, the difficulty level was automatically adjusted based on feedback from the MMSE-DS results and content measurement data. Based on the accumulated data, individual training scenarios have been set differently to intensively improve insufficient cognitive skills, and cognitive training programs will be developed to reduce safety accidents at construction sites through measured data and research. Through such simple cognitive training, it is expected that the reduction of accidents in the aging construction workforce can lead to a decrease in the social costs associated with prolonged construction periods caused by accidents.

• The Korean Journal of Emergency Medical Services
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• v.28 no.1
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• pp.47-62
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• 2024

Purpose: This study aimed to provide basic data for infection control education plans based on infection control awareness and performance of paramedic students during clinical field training. Methods: Data were collected from paramedic students with experience in clinical field training. The data collection period was from May 4, 2023, to June 4, 2023, and 132 copies of the collected survey were analyzed using the SPSS27.0 program. Results: Infection control awareness and performance were 4.80±0.24 points and 4.49±0.55 points out of 5, respectively. The infection control awareness of the participants according to clinical field training-related characteristics differed significantly in university education before clinical field training (t=2.100, p=.038). In addition, there were significant differences in performance in the number of clinical field training sessions (F=9.149, p=.000), hospital education before clinical field training (t=5.365, p=.000), and hospital education during clinical field training (t=3.094, p=.002). Conclusion: Before clinical field training, schools should provide infection control education that combines theory and practice suitable for hospital practice so that students can complete the infection control education organized by the hospital. Furthermore, if a university develops infection control in the clinical field training guidelines, it will have a positive impact on students' infection control performance through prior education.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.2
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• pp.99-106
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• 2003

Intrusions pose a serious security risk in a network environment. For detecting the intrusion effectively, many researches have developed data mining framework for constructing intrusion detection modules. Traditional anomaly detection techniques focus on detecting anomalies in new data after training on normal data. To detect anomalous behavior, Precise normal Pattern is necessary. This training data is typically expensive to produce. For this, the understanding of the characteristics of data on network is inevitable. In this paper, we propose to use clustering and association rules as the basis for guiding anomaly detection. For applying entropy to filter noisy data, we present a technique for detecting anomalies without training on normal data. We present dynamic transaction for generating more effectively detection patterns.

• Korea Journal of Hospital Management
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• v.17 no.2
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• pp.34-51
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• 2012

This study is an empirical research to identify difference of education training satisfaction by demographic variables, and to investigate the influence of education training satisfaction on the member's organizational commitment in general hospitals. As a result of ANOVA, t-test based on the data of 325 employees in 7 general hospitals in Korea, education training satisfaction has a significant difference by a construct and demographic variables. Education training satisfaction has a significant difference by a construct such as education training system, education training administration and education training practice. Education training satisfaction has a significant difference by occupation, career, scholarship. Education training satisfaction has a partly significant difference by status, age. But it has not a significant difference by sex distinction. Satisfaction of education training system and education training practice has a significantly positive relationship with organizational commitment. But Satisfaction of education training administration has a partly positive relationship with organizational commitment. By these results, the advanced education training structure needs to equipped in order to elevate management performance in general hospitals.