• Proceedings of the ESK Conference
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• 1996.04a
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• pp.113-127
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• 1996

In Human Reliability Analysis(HRA), the uncertainties involved in many factors that affect human reliability have to be represented as the quantitative forms. Conventional probability- based human reliability theory is used to evaluate the effect of those uncertainties but it is pointed out that the actual human reliability should be different from that of conventional one. Conventional HRA makes use of error rates, however, it is difficult to collect data enough to estimate these error rates, and the estimates of error rates are dependent only on engineering judgement. In this paper, the error possibility that is proposed by Onisawa is used to represent human reliability, and the error possibility is obtained by use of fuzzy reasoning that plays an important role to clarify the relation between human reliability and human error. Also, assuming these factors are connected to the top event through Fault Tree structure, the influence and correlation of these factors are measured by fuzzy operation. When a fuzzy operation is applied to Fault Tree Analysis, it is possible to simplify the operation applying the logic disjuction and logic conjuction to structure function, and the structure of human reliability can be represented as membership function of the top event. Also, on the basis of the the membership function, the characteristics of human reliability can be evaluated by use of the concept of pattern recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.662-674
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• 1997

In order to post process the vector-quantized images employing the theory of projections onto convex sets or the constrained minimization technique, the the projector onto QCS(quantization constraint set) as well as the filter that smoothes the lock boundaries should be investigated theoretically. The basic idea behind the projection onto QCS is to prevent the processed data from diverging from the original quantization region in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in the vector quantization are arbitrarilly shaped unless the vector quantization has a structural code book, the implementation of the projection onto QCS is very complicate. This paper mathematically analyzes the projection onto QCS from the viewpoit of minimizing the mean square error. Through the analysis, it has been revealed that the projection onto a subset of the QCS yields lower distortion than the projection onto QCS does. Searching for an optimal constraint set is not easy and the operation of the projector is complicate, since the shape of optimal constraint set is dependent on the statistical characteristics between the filtered and original images. Therefore, we proposed a hyper-cube as a constraint set that enables a simple projection. It sill be also shown that a proper filtering technique followed by the projection onto the hyper-cube can reduce the quantization distortion by theory and experiment.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.2
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• pp.83-92
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• 2013

RSA-CRT is a widely used algorithm that provides high performance implementation of the RSA-signature algorithm. Many previous studies on each operation step have been published to verify the physical leakages of RSA-CRT when used in smart devices. This paper proposes SAED (subtraction algorithm analysis on equidistant data), which extracts sensitive information using the event information of the subtraction operation in a reduction algorithm. SAED is an attack method that uses algorithm-dependent power signal changes. An adversary can extract a key using differential power analysis (DPA) of the subtraction operation. This paper indicates the theoretical rationality of SAED, and shows that its results are better than those of other methods. According to our experiments, only 256 power traces are sufficient to acquire one block of data. We verify that this method is more efficient than those proposed in previously published studies.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.273-285
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• 2003

Generally, vector spatial data, with richer information than raster spatial data enabledata, enables a mere flexible and effective manipulation of the data sets. However, one of challenges against the publication of vector spatial information on the Internet is the efficient transmission of the big and complex vector spatial datadata, which is both large and complex, across the narrow-bandwidth of the Internet. This paper proposes a new transmission method, namely, the Scale-Dependent Transmission method, with the purpose of improving the efficiency of vector spatial data transmission on the narrow-bandwidthacross the Internet. Simply put, its nam idea is “Transmit what can be seen””. Scale is regarded as a factor naturally associated with spatial features so that not all features are visible to users at a certain scale. With the aid of the Wavelet-Wavelet-based Map Generalization Algorithm, the proposed method filters out invisible features from spatial objects according to the display scale and then to transmit onlytransmits only the visible features as athe final answer for an individual operation. Experiments show that the response times ofan individual operation has been reducedoperations were substantially by the usage of reduced when using the proposed method.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.51-59
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• 2019

In this paper, we analyzed the relationship between charging operation system and electricity charges connected with charging infrastructure among data of many demonstration projects focused on electric vehicles recently. At this point in time, due to the rapid increase in demand for the electric charging infrastructure that will take place in the future, we can prepare for an upcoming era in the sense of forecasting the demand value. At the same time, demonstrating and modeling optimized system modeling centering on sites is a prerequisite. The modeling based on the existing small - scale simulation and the design of the operating system are based on the data linkage analysis. In this paper, we implemented a new optimized system modeling and introduced it as a standard format to analyze time - dependent time - divisional data for each vehicle and user in each point and node. In order to verify the efficiency of the optimization based on the data linkage analysis for the actual implemented electric car charging infrastructure and operation system.

• Water Engineering Research
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• v.3 no.2
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• pp.143-153
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• 2002

As the natural flows in rivers dramatically decrease during drought season in Korea, a deterioration of river water quality is accelerated. Thus, consideration of downstream water quality responding to changes in reservoir release is essential for an integrated watershed management with regards to water quantity and quality. In this study, water quality models based on artificial neural networks (ANNs) method were developed using historical downstream water quality (rm $\NH_3$-N) data obtained from a water treatment plant in Geum river and reservoir release data from Daechung dam. A nonlinear multiple regression model was developed and compared with the ANN models. In the models, the rm NH$_3$-N concentration for next time step is dependent on dam outflow, river water quality data such as pH, alkalinity, temperature, and rm $\NH_3$-N of previous time step. The model parameters were estimated using monthly data from Jan. 1993 to Dec. 1998, then another set of monthly data between Jan. 1999 and Dec. 2000 were used for verification. The predictive performance of the models was evaluated by comparing the statistical characteristics of predicted data with those of observed data. According to the results, the ANN models showed a better performance than the regression model in the applied cases.

• Journal of Korean Academy of Nursing
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• v.14 no.2
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• pp.12-18
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• 1984

The purpose of this study was to compare educational needs following open heart surgery assessed by nurses & patients themselves, Data were collected from Nov. 1983 to Jan. 1984 through administration of Questionnaire developed for this study by the researcher. The subjects were 45 patients who experienced open heart surgery and 29 nurses who taking care of these patients in chest surgery ward at Seoul National University Hospital. The Data were analyzed by T-test and One Way ANOVA according to dependent variables. The result were as follows 1. There are significant difference between educational needs, assessed by nurses and patients themselves. (p<0.05) The nurses reported higher score of educational needs than patients. 2. In comparison of content area of educational needs, there was significant difference according to respiratory care, fain, chest tube care and operation including heart function between two groups. But, there was no significant difference in diet, activity, complication, emotional care and medication between two groups. 3. The priorities in content area of educational needs rated by nurses and patients were similar.

• Journal of Digital Contents Society
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• v.4 no.2
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• pp.191-202
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• 2003

This paper presents a design and implementation example of intelligent equipment management system that is constructed to manage high price equipment of digital content department effectively. To support system operation we executed data mining and presented various rules that appear in dat3 mining process based on dat3 of user, equipment and using record. We presented personalization plan of web site to offer user dependent administration policy and dynamic interface using analyzed informatio.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.177-180
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• 2008

There are many application areas of sensor networks, such as surveillance, hospital monitoring, and home network. These are dependent on the secure operation of networks, and will have serious outcome if the networks is injured. An adversary can inject false data into the network through the compromising node. Ye et al. proposed a statistical en-route filtering scheme (SEF) to detect such false data during forwarding process. In this scheme, it is important that the choice of the threshold value since it trades off security and overhead. This paper presents an adaptive threshold value determining method in the SEF using fuzzy logic. The fuzzy logic determines a security distance value by considering the situation of the network. The Sensor network is divided into several areas by the security distance value, it can each area to uses the different threshold value. The fuzzy based threshold value can reduce the energy consumption in transmitting.

• Journal of Applied Reliability
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• v.17 no.4
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• pp.316-324
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• 2017

Purpose: The purpose of this study is to determine the replacement cycle applied age replacement policy by reliability analysis based on railway vehicle contactor's failure history data. Method: We performed reliability analysis based on railway vehicle contactor's failure history data. We found a suitable distribution by goodness of fit test and predicted the reliability through estimation of scale & shape parameter. Considering cost information we determined the replacement cycle that minimize the opportunity cost. Result: Suitable distribution was the Weibull and scale parameter & shape parameter are estimated by reliability analysis. The replacement cycle was predicted and MTTF, $B_6$ percentile life were suggested additionally. Conclusion: We confirmed that failure rate type of railway vehicle contactor is degradation model having a time dependent characteristic and examined the replacement cycle in our country's operating environment. We expect that this study result contribute to railway operation agency for maintenance policy decision.