• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.17 no.3
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• pp.254-260
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• 2007

Trichloroethylene(TCE) is widely used as a degreasing solvent in workplaces. TCE is primarily toxic to the nervous system, however, systemic disorder like Stevens-Johnson syndrome has been recently reported in small-scale factories, where the government has had limited information of chemical use. A survey was performed to investigate the actual condition of using TCE and to provide practical information to occupational health service agencies and professionals. This survey was carried out on 103 factories out of 430 factories which were conducted periodic work environment measurement for TCE. Degreasing was the most popular reason for using TCE in Korea, which reached to 94%. TCE was also used as a solvent for rubber in the coating or molding process, and adhesives in the bonding process. Metal fabrication was the most common as 23%, followed by assembling automobile parts (17%), and machinery (12%). Workers exposed to TCE during full-shift were 52% while 48% were exposed during short period of the shift or intermittently. Manual or semi-automatic work occupied 87% while automatic work was just 13%. Though automatic work by a closed system was generally lower exposed to TCE, compared to manual work, it can cause a high exposure when the maintenance system is improper. Semi-automatic work especially like open-top degreasing process can cause a high exposure when local exhaust system with condensing and refrigerating coils in the degreaser does not work well. In conclusion, the survey showed nationwide status of TCE exposure in various aspects. It can be used to monitor workplaces and workers exposed to TCE to prevent occupational diseases.

• The Journal of the Acoustical Society of Korea
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• v.19 no.4
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• pp.31-36
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• 2000

This paper describes the implementation and the evaluation of the speech recognition automatic exchange system. The system provides government or public offices, companies, educational institutions that are composed of large number of members and parts with exchange service using speech recognition technology. The recognizer of the system is a Speaker-Independent, Isolated-word, Flexible-Vocabulary recognizer based on SCHMM(Semi-Continuous Hidden Markov Model). For real-time implementation, DSP TMS320C32 made in Texas Instrument Inc. is used. The system operating terminal including the diagnosis of speech recognition DSP and the alternation of speech recognition candidates makes operation easy. In this experiment, 8 speakers pronounced words of 1,300 vocabulary related to automatic exchange system over wire telephone network and the recognition system achieved 91.5% of word accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1284-1297
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• 2019

The network environment is presently becoming very increased. Accordingly, the study of traffic classification for network management is becoming difficult. Automatic signature extraction system is a hot topic in the field of traffic classification research. However, existing automatic payload signature generation systems suffer problems such as semi-automatic system, generating of disposable signatures, generating of false-positive signatures and signatures are not kept up to date. Therefore, we provide a fully automatic signature update system that automatically performs all the processes, such as traffic collection, signature generation, signature management and signature verification. The step of traffic collection automatically collects ground-truth traffic through the traffic measurement agent (TMA) and traffic management server (TMS). The step of signature management removes unnecessary signatures. The step of signature generation generates new signatures. Finally, the step of signature verification removes the false-positive signatures. The proposed system can solve the problems of existing systems. The result of this system to a campus network showed that, in the case of four applications, high recall values and low false-positive rates can be maintained.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.267-274
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• 2017

Recently, several researches have been studied on agricultural automation system according to convergence of IT technology with agriculture. An automatic control system of the growth environment in crops is one of the these researches. The controls of damages caused by diseases and insects pest in crops are mainly carried out by manual mode or semi-automatic mode because of farmer's concerns for poor efficiency. But, this situation needs to be improved because it occurs various problems, such as human exposure to toxic pesticides, environmental pollution and waste due to drug overuse. In order to solve these problems, we developed an automatic quantity control system which based on the amount of pesticides for area under cultivation. The amount of pesticides is calculated according to the manufacturer's instruction for pesticides. To verify the effectiveness of our developed automatic system, we also compared with the systems of manual mode and the semi-automatic mode. The experimental results of a pest control performance of an automatic quantity control system showed that automatic system can reduce overuse of drugs. These results suggested that it can be expected to replace the existing system, with equivalent effectiveness to the manual mode.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.124-131
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• 2024

Breast cancer classification using ultrasound, while widely employed, faces challenges due to its relatively low predictive value arising from significant overlap in characteristics between benign and malignant lesions, as well as operator-dependency. To alleviate these challenges and reduce dependency on radiologist interpretation, the implementation of automatic breast cancer classification in ultrasound image can be helpful. To deal with this problem, we propose a semi-supervised deep learning framework for breast cancer classification. In the proposed method, we could achieve reasonable performance utilizing less than 50% of the training data for supervised learning in comparison to when we utilized a 100% labeled dataset for training. Though it requires more modification, this methodology may be able to alleviate the time-consuming annotation burden on radiologists by reducing the number of annotation, contributing to a more efficient and effective breast cancer detection process in ultrasound images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.167-168
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.333-334
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• 2009

• 한국신재생에너지학회:학술대회논문집
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• 2007.11a
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• pp.259-259
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• 2007

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.256-256
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• 2004

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11a
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• pp.31-75
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• 2000

The tractor is the most important machine for farming keeping probably this position also for feeding the future fast growing world population. Band width of power and functions continues to increase worldwide, examples are given. Regarding the high developed countries, general farming demands as well as precision farming issues require closed loop control principles for the system "driver-tractor-implement". Progress in information technologies supports this trend, but comprehensive component and system developments are necessary to make the tractor ready for automatic or semi-automatic controls. The following technical highlights are, for example, discussed for Europe: hydropneumatic front axle suspensions, 50 km/h top speed, front brakes, electronically controlled multivalve diesel engines, automatic hydrostatic power split CVTs, load sensing hydraulics with proportional valves, improved cab and working places with "operations by wire" and more electronics on board than ever before.