• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.451-453
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• 2010

The world is rapidly evolving in the future society is based on intelligence. In such circumstances, USN(Ubiquitous Sensor Network) to implement the future ubiquitous(Ubiquitous) society have been highlighted as a key infrastructure. For realization of Ubiquitous computing(Ubiquitous Computing), The data recognized from each sensors must be collected on real-time and transferred to applied service so that they may be used as data for providing service to users. USN sensor data on the use for using a numerous sensor data provision service, service provider can publish its service in standardized registry for users to search and use the service registry. However, in previous studies using Web services standards WS-Eventing, and UDDI(Universal Description, Discovery, and Integration) as USR(USN Service Registry) for USN Application Service is unnecessary or insufficient. In this paper, data from sensors that provide information to service providers register their services and use the information for service users to explore and views on the registry of the system was designed and implemented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.871-874
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• 2010

Needs for Smart Grid development are increasing all over the world as a solution to its problem according to depletion of energy resources, climatic and environmental rapidly change and growing demand for electrical power. Especially decentralized power is attracting world's attention. In this mood a new era for a unit scale of decentralized power environment is on its way in building. However there is a problem to have to be solved in the uniformity of power quality because the amount of power generated from renewable energy resources such as wind power and solar light is very sensitive to climate fluctuation. And thus this paper tries to suggest an energy management method on basis of real time monitoring for meteorological data. In the current situation of lacking in USN-based killer application in Smart Grid field, this paper proposes the USN-based DER management system which collects the meteorological data and control power system througout utilizing wireless sensor network technique this business. This communication technique is regarded to be efficient in aspects of installation cost and tits maintenance cost. The proposed EMS model embodies the method for predicting the power generation by monitoring and analyzing the climatic data and controling the efficient power distribution between the renewable energy and the existing power. The ultimate goal of this paper is to provide the technological basis for achieving zero-energy house.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2461-2469
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• 1997

Target detection and recognition problems, in which neural networks are widely used, require translation invariant and real-time processing in addition to the requirements that general pattern recognition problems need. This paper presents a novel architecture that meets the requirements and explains effective methodology to train the network. The proposed neural network is an architectural extension of the shared-weight neural network that is composed of the feature extraction stage followed by the pattern recognition stage. Its feature extraction stage performs correlational operation on the input with a weight kernel, and the entire neural network can be considered a nonlinear correlation filter. Therefore, the output of the proposed neural network is correlational plane with peak values at the location of the target. The architecture of this neural network is suitable for implementing with parallel or distributed computers, and this fact allows the application to the problems which require realtime processing. Net training methodology to overcome the problem caused by unbalance of the number of targets and non-targets is also introduced. To verify the performance, the proposed network is applied to detection and recognition problem of a specific automobile driving around in a parking lot. The results show no false alarms and fast processing enough to track a target that moves as fast as about 190 km per hour.

• The Journal of Korean Society for School & Community Health Education
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• v.6
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• pp.89-107
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• 2005

The purposes of this study were to investigate the recognition and the needs and problems of in-service education for school nurse, and to suggest the desirable guidelines, for supples the basic data of in-service education for school nurse to upgraded the quality as school nurse's professional specialist. The subjects of this study were 376 school nurses who were working in Jollanamdo. The research instruments used in this study was 'Needs of In-service Education questionnaire'. 305 collected Data were analyzed with the frequency analysis, $x^2$-test. The conclusions were as follows; First of all, the most important motives for the school nurses to participate in-service education are the enhancement of their specialties on teaching profession, self-realizations as educators, and improvement of health teaching skill. However, the motives to obtain the skill for school management or to obtain a high rank qualification and promotion are quite low. School nurses are generally satisfied with duration, time, place of in-service education, But they are not satisfied with contents of in-service education, professional specialist and understanding of real educational situation of the instructors. On the urgent problem of school nurses, promotion of health teaching skill was highest in the rank, and establishment of firm educational philosophy and a sense of teaching profession, proceed to university and graduate school ranked next, respectively. Second, the need of a school nurses on in-service education direction ranked the application of teachers' character and need, practicable and concrete educational programs, planning of school health development, reinforcement of health education, expansion of practical knowledge and on reflection thought, respectively. The need of a school nurses on in-service education contents(major part) ranked health education, health promoting program of student, knowledge and practice of practical medicine and oriental medicine, consultation process, health education of advanced country, respectively. The need of in-service education supervisory organization, the need for a cities provinces educational office was highest in the rank. The need of in-service education type, duty training ranked high, and abroad training, qualification training, general training ranked next. the need for specialist for lecturer of in-serve education ranked among the highest, along with school nurses and university professor. The need of school nurses on education method(duplication answer), need for conference and discussion teaching was highest in the rank. The need on evaluation method, evaluation through a examination ranked the highest. On the needs of in-service education times, need for vacation during the winter and summer was the highest. As for the duration, 31 to 60 hours in duration of in-service education was need most, and most school nurses need cities and provinces in-service training institute as the location of in-service education. On the organization size, need for 21 to 30 people was the highest, where as need for 41 people was relatively low. Lastly, on the problem of in-service education for school nurses, lack of opportunity of in-service education for school nurses was highest in the rank, and improperness of in-service education contents and method, lack of incentive ranked next, respectively.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.173-184
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• 2008

Development of an accident estimation model based on accident data can be made after accident occurrences. However, the taking of historical accident data is not easy, and there have been differences between real accident data and police-reported accident data. Also, another difficult shortcoming is that historical traffic accident data better consider driver behavior or intersection characteristics. A new method needs to be developed that can predict accident occurrences for traffic safety improvement in black spots. Traffic conflict decision techniques can acquire and analyze data in time and space, requiring less data collection through investigation. However, there are shortcomings: as existing traffic conflict techniques do not operate automatically, the analyst's opinion could easily affect the study results. Also, existing methods do not consider the severity of traffic conflicts. In this study, the authors presented traffic conflict decision criteria which consider conflict severity, including opposing left turn traffic conflict and cross traffic conflict decision criteria. In order to test these criteria, the authors acquired three signalized intersection images (two intersections in Sungnam city and one intersection in Paju) and analyzed the acquired images using image processing techniques based on individual vehicle tracking technology. Within the analyzed images, level 1 conflicts occurred 343 times over three intersections. Some of these traffic conflicts resulted in level 3 conflict situations. Level 3 traffic conflicts occurred 25 times. From the study results, the authors found that traffic conflict decision techniques can be an alternative to evaluate traffic safety in black spots.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.27 no.1
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• pp.70-76
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• 2017

Objectives: This on-site study was performed to evaluate the reduction efficiency of an air cleaner on particulate matters and biological agents in a swine facility. Materials and Methods: Particulate matter was measured using a real-time monitoring recorder and biological agents were sampled with a one-stage impactor and then analyzed based on the microbial culture method. An experimental process for the reduction effect on airborne pollutants through air cleaner operation consisted of three conditions: no treatment, wet scrapper by water spray and wet scrapper by disinfectant spray. Results: Geometric mean levels of particulate matter(TSP, $PM_{10}$, $PM_{2.5}$ and $PM_1$) were presented at $1,608{\mu}g/m^3$, $1,373.8{\mu}g/m^3$, $401.8{\mu}g/m^3$ and $144.5{\mu}g/m^3$ for no treatment; $1,503{\mu}g/m^3$, $1,017{\mu}g/m^3$, $159.4{\mu}g/m^3$ and $69.8{\mu}g/m^3$ for wet scrapper by water spray; and $1,222.17{\mu}g/m^3$, $477.17{\mu}g/m^3$, $33.2{\mu}g/m^3$ and $11.1{\mu}g/m^3$ for wet scrapper by disinfectant spray, respectively. In the case of biological agents, the geometric averaged concentrations of total airborne bacteria and fungi were as follows: $45,371cfu/m^3$ and $13,474cfu/m^3$ for no treatment, $43,286cfu/m^3$ and $8,610cfu/m^3$ for wet scrapper by water spray, and $2,440cfu/m^3$ and 1,867 cfu/ for wet scrapper by disinfectant spray, respectively. Regardless of particulate matter and biological agent, the highest concentrations were found for no treatment, while the lowest concentrations were found with wet scrapper by disinfectant spray. Conclusions: Based on the results obtained from this on-site evaluation, there was a significant reduction effect on particulate matter and biological agents through the application of an air cleaner in this study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.34-42
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• 2017

Since existing nonintrusive appliance load monitoring (NIALM) studies assume that voltage fluctuations are negligible for load identification, and do not affect the identification results, the power factor or harmonic signals associated with voltage are generally not considered parameters for load identification, which limits the application of NIALM in the Smart Home sector. Experiments in this paper indicate that the parameters related to voltage and the characteristics of harmonics should be used to improve the accuracy and reliability of the load monitoring system. Therefore, in this paper, we propose an improved NIALM method that can efficiently analyze the types of household appliances and electrical energy usage in a home network environment. The proposed method is able to analyze the energy usage pattern by analyzing operation characteristics inherent to household appliances using harmonic characteristics of some household appliances as recognition parameters. Through the proposed method, we expect to be able to provide services to the smart grid electric power demand management market and increase the energy efficiency of home appliances actually operating in a home network.

• Resources Recycling
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• v.29 no.1
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• pp.25-34
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• 2020

Electrochemical Quartz Crystal microbalance is a tool that is capable of measuring nanogram-scale mass change on electrode surface. When applying alternating voltage to the quartz crystal with metal electrode formed on both sides, a resonant frequency by inverse piezoelectric effect depends on its thickness. The resonant frequency changes sensitively by mass change on its electrode surface; frequency increase with metal dissolution and decrease with metal deposition on the electrode surface. The relationship between resonant frequency and mass change is shown by Sauerbrey equation so that the mass change during metal dissolution can be measured in real time. Especially, it is effective in the case of reaction mechanism and rate studies accompanied by precipitation, volatilization, compound formation, etc. resulting in difficulties on ex-situ AA or ICP analysis. However, it should be carefully considered during EQCM experiments that temperature, viscosity, and hydraulic pressure of solution, and stress and surface roughness can affect on the resonant frequency. Application of EQCM was shown as a case study on leaching of platinum using aqueous chlorine for obtaining activation energy. A platinum electrode of quartz crystal oscillator with 1000 Å thickness exposed to solution was used as leaching sample. Electrogenerated chlorine as oxidant was purged and its concentration was controlled in hydrochloric acid solution. From the experimental results, platinum dissolution by chlorine is chemical reaction control with activation energy of 83.5 kJ/mol.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1261-1269
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• 1999

다층 퍼셉트론은 다양한 응용 분야에 성공적으로 적용되고 있는 대표적인 신경회로망 모델이다. 그러나 다층 퍼셉트론의 학습에서 나타나는 플라토에 기인한 느린 학습 속도와 지역 극소는 실제 응용문제에 적용함에 있어서 가장 큰 문제로 지적되어왔다. 이 문제를 해결하기 위해 여러 가지 다양한 학습알고리즘들이 개발되어 왔으나, 계산의 비효율성으로 인해 실제 문제에는 적용하기 힘든 예가 많은 등, 현재까지 만족할 만한 해결책은 제시되지 못하고 있다. 본 논문에서는 다층퍼셉트론의 베이시스 함수로 사용되는 시그모이드 함수를 보다 일반화된 형태로 정의하여 사용함으로써 학습에 있어서의 플라토를 완화하고, 지역극소에 빠지는 것을 줄이는 접근방법을 소개한다. 본 방법은 기존의 변형된 가중치 수정식을 사용한 학습 속도 향상의 방법들과는 다른 접근 방법을 택함으로써 기존의 방법들과 함께 사용하는 것이 가능하다는 특징을 갖고 있다. 제안하는 방법의 성능을 확인하기 위하여 간단한 패턴 인식 문제들에의 적용 실험 및 기존의 학습 속도 향상 방법을 함께 사용하여 시계열 예측 문제에 적용한 실험을 수행하였고, 그 결과로부터 제안안 방법의 효율성을 확인할 수 있었다. Abstract A multilayer perceptron is the most well-known neural network model which has been successfully applied to various fields of application. Its slow learning caused by plateau and local minima of gradient descent learning, however, have been pointed as the biggest problems in its practical use. To solve such a problem, a number of researches on learning algorithms have been conducted, but it can be said that none of satisfying solutions have been presented so far because the problems such as computational inefficiency have still been existed in these algorithms. In this paper, we propose a new learning approach to minimize the effect of plateau and reduce the possibility of getting trapped in local minima by generalizing the sigmoidal function which is used as the basis function of a multilayer perceptron. Adapting a new approach that differs from the conventional methods with revised updating equation, the proposed method can be used together with the existing methods to improve the learning performance. We conducted some experiments to test the proposed method on simple problems of pattern recognition and a problem of time series prediction, compared our results with the results of the existing methods, and confirmed that the proposed method is efficient enough to apply to the real problems.

• Journal of the Korean Institute of Gas
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• v.2 no.3
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• pp.54-59
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• 1998

As distributed control systems (DCS) and plant information systems (PIS) are introduced into gas industries, process monitoring systems based on process data have attracted significant interests. However, these technologies have not been fully due to strong nonlinearities of batch processes. The multiway principal component analysis, which has been recently developed, has solved these problems and has been widely used in the industries. However, the lack of statistical background of process operators has been one of major obstacles for maximum utilization of the technology This paper introduces a real time monitoring system for batch gas manufacturing processes that offers a variety of tools that operators can understand and use without serious difficulties. The proposed integrated system covers the whole spectrum of monitoring and diagnosis that include data collection, monitoring and diagnosis. The developed system has been verified to be very effective for monitoring and diagnosis using its application to the construction of monitoring system for a typical industrial batch reactor.