• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1781-1785
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• 2007

We propose a new enhanced graphical user interface and algorithm for dynamic signature verification using Smart-phone. Also, we describe the performance results of our dynamic signature verification system, which determine the authentication of signatures by comparing and analyzing various dynamic data shape of the signature, writing speed, slant of shape, and the order and number of strokes for personal signatures using an electronic pen, expecting the system to be understood and utilized widely in the industrial field.

• Journal of Korean language education
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• v.29 no.3
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• pp.25-53
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• 2018

This study examined the influence of lexical factors on verbal Eojeol recognition. To meet the goal, forty-five L2 Korean learners and twenty-two Korean native speakers took Eojeol decision tasks measured with the lexical factors such as 'number of strokes', 'number of consonants and vowels', 'number of syllables', 'number of morphemes', 'whole Eojeol frequency', 'root frequency', 'first-syllable-sharing frequency', and 'number of dictionary meanings.' As a result, 'whole Eojeol frequency' was the most effective factor to predict Eojeol recognition reaction time for native speakers and L2 learners, which supports the full-list model. Other lexical factors influencing Eojeol recognition reaction time in L2 learners were different following their proficiency level.

• Nuclear Engineering and Technology
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• v.35 no.2
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• pp.133-143
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• 2003

Stem-stem nut coefficient of friction(COF) in motor-operated gate/globe valves is one of the important factors which determine the performance of the valve/actuators. The COF is affected greatly by the type and condition of the stem-stem nut lubricants, environmental parameters, surface condition of the stem/stem-nuts, and the number of strokes after the lubrication. In this paper, the measured data of the COFs at stem threads of some safety-related motor-operated gate/globe valves in domestic nuclear power plants are presented. In addition, the performance of the lubricants is evaluated by comparing the COFs among those valves. The results show that the measured COF at torque switch trip are higher than the unwedging COF and conservatively applicable to the unwedging COF. It is also shown that the lubricating performance based on the measured COFs varies with the lubricants.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.3
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• pp.259-264
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• 2019

In this study, we experiment by making and designing of compression ignition diesel engine witch has air cooling, 2-cylinder and 2-strokes. Also, we make controller witch can control injection timing and period by arbitrary manual operation for change of injection timing. We also study experimentally in change about pressure and power of combustion chamber by increasing density of air which comes into cylinder because of increasing scavenging pressure. Through this, we confirmed that output change and scavenging pressure can develop performance of the engine by scavenging efficiency of a chamber and development of volume efficiency.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.41-46
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• 2018

This paper proposes a new method for the number recognition on dot matrix LED display. The proposed method uses morphological processing that dilates dots of numbers and connects the dots into strokes. The size of numbers is normalized using horizontal projection because the gaps of dots are different according to the size of numbers. The numbers are segmented by connected component analysis and finally, template matching method recognizes the segmented numbers. The proposed method is implemented using C language in Raspberry Pi system with a camera module for a real-time image processing. Experiments were conducted by using various dot matrix LED displays. The results show that the proposed method is successful for the number recognition on dot matrix LED display.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.130-134
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• 2020

This paper proposes a new method for the digit recognition on a 7-segment display. The proposed method uses morphological processing that dilates segments of digits and connects them into strokes. The digits are extracted by connected component analysis and finally, template matching method recognizes the extracted digits. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. Experiments were conducted by using various 7-segment LED displays and 7-segment mono LCD displays. The results show that the proposed method is successful for the digit recognition on the 7-segment displays.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.4
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• pp.19-28
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• 2020

Vehicle license plate recognition system is not generalized in Malaysia due to the loose character layout rule and the varying number of characters as well as the mixed capital English characters and italic English words. Because the italic English word is hard to segmentation, a separate method is required to recognize in Malaysian license plate. In this paper, we propose a mixed character level and word level English license plate recognition algorithm using deep learning neural networks. The difference of Gaussian method is used to segment character and word by generating a black and white image with emphasized character strokes and separated touching characters. The proposed deep learning neural networks are implemented on the LPR system at the gate of a building in Kuala-Lumpur for the collection of database and the evaluation of algorithm performance. The evaluation results show that the proposed Malaysian English LPR can be used in commercial market with 98.01% accuracy.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.1-13
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• 2021

In this research, we study the problem of font image skeletonization using an end-to-end deep adversarial network, in contrast with the state-of-the-art methods that use mathematical algorithms. Several studies have been concerned with skeletonization, but a few have utilized deep learning. Further, no study has considered generative models based on deep neural networks for font character skeletonization, which are more delicate than natural objects. In this work, we take a step closer to producing realistic synthesized skeletons of font characters. We consider using an end-to-end deep adversarial network, SkelGAN, for font-image skeletonization, in contrast with the state-of-the-art methods that use mathematical algorithms. The proposed skeleton generator is proved superior to all well-known mathematical skeletonization methods in terms of character structure, including delicate strokes, serifs, and even special styles. Experimental results also demonstrate the dominance of our method against the state-of-the-art supervised image-to-image translation method in font character skeletonization task.

• Annals of Clinical Neurophysiology
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• v.23 no.1
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• pp.17-28
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• 2021

The pathogenesis of many strokes originates in the vessel wall. Despite this, most traditional imaging focuses on the vascular lumen. Vessel-wall magnetic resonance imaging (VWMRI) is useful for establishing the etiology of intracranial stenosis. It also provides information regarding atherosclerotic plaque composition and thus plaque vulnerability, which is an indication of its potential to cause a stroke. In this review we focus on the characteristics of VWMRI findings in various arteriopathies related to intracranial artery stenosis, and discuss the clinical implications of these findings.

• PNF and Movement
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• v.21 no.2
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• pp.193-202
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• 2023

Purpose: We investigated the effects of transcranial stimulation and task-oriented training on upper extremity and cognitive function in chronic stroke patients. Methods: A total of 30 patients were randomly divided into transcranial stimulation and task-oriented training groups (TT) and task-oriented training groups (TO). The TT group performed 30 min 5 times a week for 4 weeks in task-oriented training combined with transcranial direct current stimulation. The TO group performed 30 min 5 times a week for 4 weeks in task-oriented training. To measure upper extremity function, the Jebsen-Taylor Hand Function Test, Manual Function Test, and Cognitive Function Test were performed using the Stroop Test and the Trail Making Test. Results: There was a significant difference (P < 0.05) before and after training in both groups, and the TT group showed significant improvement in both groups. Conclusion: In this study, we confirmed transcranial stimulation and task-oriented training in upper extremity function and cognitive function in patients with chronic strokes.