• Journal of Biosystems Engineering
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• v.27 no.5
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• pp.451-458
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• 2002

This paper introduces that livestock can be effectively managed by an individual electronic identification system. The proposed system was composed of the original code transmitter, receiver, personal computer, micro-processor, and RS485 telecommunications module. In the individual electronic identification system, the signal including encoded information of a milk-cow was transmitted from an original code transmitter to a micro-processor through RS485 telecommunications module. The transmitted signal can be successfully displayed in a personal computer. This system can be managed by 9999 individuals with a original code transmitter. The recognition rate of an individual electronic identification system was 98.5% and also auto-feeder operates very well. an individual electronic identification system was developed for automation of stockbreeding management. To automate the breeding management, it is necessary to obtain and analyze the individual information distinguished from others preferentially.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.242-247
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• 2008

As an absolute positioning system, iGS is designed based on ultrasonic signals whose speed can be formulated clearly in terms of time and room temperature, which is utilized for a mobile robot localization. The iGS is composed of an RFID receiver and an ultra-sonic transmitter, where an RFID is designated to synchronize the transmitter and receiver of the ultrasonic signal. The traveling time of the ultrasonic signal has been used to calculate the distance between the iGS system and a beacon which is located at a pre-determined location. This paper suggests an effective operation method of iGS to estimate position of the mobile robot working in unstructured environment. To expand recognition range and to improve accuracy of the system, two strategies are proposed: utilization of beacons belonging to neighboring blocks and removal of the environment-reflected ultrasonic signals. As the results, the ubiquitous localization system based on iGS as a pseudo-satellite system has been developed successfully with a low cost, a high update rate, and relatively high precision.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.6
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• pp.8-14
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• 2014

Pulverized coal (PC) has become an important auxiliary fuel in the iron and steel industry since the technique of pulverized coal injection (PCI) was developed for iron making. The combustion efficiencies of pulverized coal in blowpipes and tuyeres under various operational conditions are numerically predicted to determine the performance levels with regard to different locations of the nozzles in a blast furnace. A variety of parameters, including the pulverized coal quantities, oxygen amounts, inlet temperatures of the tuyeres, and the mass flow rate of coal carrier gas are taken into consideration. Also, in order to develop greater efficiency than those of existing coal injection systems, this study applies a flame measurement system using a charge-coupled device (CCD) camera and a frame grabber. It uses auto sampling algorithms from the flame shape information to determine the device for the optimal location control for PCI. This study finds further improvements of the blast furnace performance via the control of the PCI locations.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.3163-3168
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• 2008

Pulverized coal (PC) has become an important auxiliary fuel in the iron and steel industry since the technique of pulverized coal injection (PCI) system was developed for iron making. Combustion efficiencies of pulverized coal in blowpipes and tuyeres under various operational are numerically predicted to recognize the performance with the locations of nozzles in a blast furnace. A variety of parameters including the pulverized coal quantities, oxygen amounts, inlet temperature of the tuyeres and mass flow rate of coal carrier gas are taken into consideration. Also In order to develop more efficient than existing coal injection system, this study applies a flame measurement system using a charge couple device (CCD) camera and frame grabber. And it has used algorithms of auto sampling from flame shape information and composed the device for location control of PCI. This study find to further improve the blast furnace performance by the control of PCI locations.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.269-272
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• 2000

It is need to develop and apply a human pulse diagnosis system providing a quantitative and automatic analysis in the the oriental medicine. In order to analyze quantitatively the characteristic of pulsation, each of points had to be recognized accurately notifying the existence and the position of feature point in the wave form. And getting the period of human pulse. Thus, in this paper, it is proposed the preprocessing method of human pulse and the detection method of period by Wavelet Transformation. The human pulse is seprated from each band through Wavelet Transformation and feature points can be recognized through over the fact, and then the parameter of proposed Mac-Jin parameter is measured. Commonly, Human pulse signal has often various noises which are baseline drift, high frequency noise and so on. So it is significant to remove that noises. Thus, in this paper, the one period of human pulse is deciede and the feature points are detected after doing the preprocessing by wavelet transformation. As a result, it could be confirmed that this method is effective as a real program for the auto-diagnosis of human pulse.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2927-2941
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• 2022

The primary task of machine fault diagnosis is to judge whether the current state is normal or damaged, so it is a typical binary classification problem with mutual exclusion. Mutually exclusive events and out-of-domain detection have one thing in common: there are two types of data and no intersection. We proposed a fusion model method to improve the accuracy of machine fault diagnosis, which is based on the mutual exclusivity of events and the commonality of out-of-distribution detection, and finally generalized to all binary classification problems. It is reported that the performance of a convolutional neural network (CNN) will decrease as the recognition type increases, so the variational auto-encoder (VAE) is used as the primary model. Two VAE models are used to train the machine's normal and fault sound data. Two reconstruction probabilities will be obtained during the test. The smaller value is transformed into a correction value of another value according to the mutually exclusive characteristics. Finally, the classification result is obtained according to the fusion algorithm. Filtering normal data features from fault data features is proposed, which shields the interference and makes the fault features more prominent. We confirm that good performance improvements have been achieved in the machine fault detection data set, and the results are better than most mainstream models.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.89-103
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• 2020

As we face an aging society, the demand for personal mobility for disabled and aged people is increasing. In fact, as of 2017, the number of electric wheelchair in the country continues to increase to 90,000. However, people with disabilities and seniors are more likely to have accidents while driving, because their judgment and coordination are inferior to normal people. One of the causes of the accident is the interference of personal vehicle steering control due to unbalanced road surface conditions. In this paper, we introduce a encoder type semantic segmentation algorithm that can recognize road conditions at high speed to prevent such accidents. To this end, more than 1,500 training data and 150 test data including road surface damage were newly secured. With the data, we proposed a deep neural network composed of encoder stages, unlike the Auto-encoding type consisting of encoder and decoder stages. Compared to the conventional method, this deep neural network has a 4.45% increase in mean accuracy, a 59.2% decrease in parameters, and an 11.9% increase in computation speed. It is expected that safe personal transportation will be come soon by utilizing such high speed algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.507-515
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• 2015

This paper suggests 6 cases of TFA parameters algorithm(Mean, VA, RS, SKEW, UN, EN) to search for the detection of recognition rates regarding breast disease using CAD on ultrasound images. Of the patients who visited a university hospital in Busan city from August 2013 to January 2014, 90 cases of breast ultrasound images based on the findings in breast US and pathology were selected. $50{\times}50$ pixel size ROI was selected from the breast US images. After pre-processing histogram equalization of the acquired test images(negative, benign, malignancy), we calculated results of TFA algorithm using MATLAB. As a result, in the TFA parameters suggested, the disease recognition rates for negative and malignancy was as high as 100%, and negative and benign was approximately 83~96% for the Mean, SKEW, UN, and EN. Therefore, there is the possibility of auto diagnosis as a pre-processing step for a screening test on breast disease. A additional study of the suggested algorithm and the responsibility and reproducibility for various clinical cases will determine the practical CAD and it might be possible to apply this technique to range of ultrasound images.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.573-585
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• 2018

Services for navigation and entertainment through AI-based voice user interface devices are becoming popular in the connected car system. Given the classification of VUI agent developers as IT companies and automakers, this study explores attributes of agent persona and user experience that impact the driver's perceived safety and satisfaction. Participants of a car simulator experiment performed entertainment and navigation tasks, and evaluated the perceived safety and satisfaction. Results of regression analysis showed that credibility of the agent developer, warmth and attractiveness of agent persona, and efficiency and care of the UX dimension showed significant impact on the perceived safety. The determinants of perceived satisfaction were unity of auto-agent makers and gender as predisposing factors, distance in the agent persona, and convenience, efficiency, ease of use, and care in the UX dimension. The contributions of this study lie in the discovery of the factors required for developing conversational VUI into the autonomous driving environment.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.694-701
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• 2016

The smart phone application to provide auto identification and answer explanation of multiple choice answer for each OMR answer item in the test paper different from ordinary OMR test by using smart phone is very useful in terms of a self learning and a smart learning. In this paper, smart phone application of OMR mark identification for each question item in test paper is proposed. QR code for each OMR answer is provided for the encrypted correct answer and the reference location of multiple choice answer rectangle location. The OMR answer region is extracted and the marked answer is identified in each question of test paper, in order to compare between the marking answer and the correct answer. Experimental result of smart phone application of the proposed algorithm for the OMR answer images with various size and direction shows excellent recognition performance.