• Air Cleaning Technology
• /
• v.23 no.3
• /
• pp.1-9
• /
• 2010

This study proposed the optimum design values for the biological clean room system observing the regulations of Hazard Analysis Critical Control Point (HACCP). Even though the standard for industrial clean room system has been well established, the basis for biological food clean room system is the first stage. In order to prevent the contaminations in advance for food storages, processes, and distributions, the criterion of Hazard Analysis Critical Control Point is positively required. This study also suggested the possible ways of how to avoid the hazardous contaminations.

• Journal of the Korean Statistical Society
• /
• v.28 no.2
• /
• pp.235-251
• /
• 1999

In this paper we examine extremal behavior of a $textsc{k}$th-order stationary Markov chain {X\ulcorner} by considering excesses over a high level which typically appear in clusters. Excesses over a high level within a cluster define a cluster damage, i.e., a normalized sum of all excesses within a cluster, and all excesses define a damage point process. Under some distributional assumptions for {X\ulcorner}, we prove convergence in distribution of the cluster damage and obtain a representation for the limiting cluster damage distribution which is well suited for simulation. We also derive formulas for the mean and the variance of the limiting cluster damage distribution. These results guarantee a compound Poisson limit for the damage point process, provided that it is strongly mixing.

• Nuclear Engineering and Technology
• /
• v.36 no.3
• /
• pp.229-236
• /
• 2004

Radiation hardening is a multiscale phenomenon involving various processes over a wide range of time and length. We present a multiscale model for estimating the amount of radiation hardening in pressure vessel steel in the environment of a light water reactor. The model comprises two main parts: molecular dynamics (MD) simulation and a point defect cluster (PDC) model. The MD simulation was used to investigate the primary damage caused by displacement cascades. The PDC model mathematically formulates interactions between point defects and their clusters, which explains the evolution of microstructures. We then used a dislocation barrier model to calculate the hardening due to the PDCs. The key input for this multiscale model is a neutron spectrum at the inner surface of reactor pressure vessel steel of the Younggwang Nuclear Power Plant No.5. A combined calculation from the MD simulation and the PDC model provides a convenient tool for estimating the amount of radiation hardening.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.03a
• /
• pp.43-46
• /
• 1998

This paper presents a new parameter tuning method for PID controller. The Ziegler-Nichols Parameter tuning has been widely known as a fairly heuristic method to good determine setting of PID controllers, for a wide range of common industrial processes It has a excessive overshoot in the set point response, set point weighting can reduced the overshoot to specified values. It will also be shown that set point weighting is superior to the conventional solution of reducing large overshoot by other method. In this paper, we will modified the Ziegler-Nichols tuning formula by fuzzy set. These method will give appreciable improvement in the performance of PID controllers.

• 한국정보통신설비학회:학술대회논문집
• /
• 2008.08a
• /
• pp.257-261
• /
• 2008

The Digital Radio Mondiale (DRM) system is a digital broadcasting standard designed for use in the LF, MF and HF bands of the broadcasting bands below 30 MHz. The system provides both superior audio quality and improved user services / operability compared with existing AM transmissions. In this paper, we propose a variable point Prime Factor FFT design method for Digital Radio Mondiale (DRM) system. Proposed method processes a various size IFFT/FFT of Robustness Mode on DRM standard efficiently by composing Radix-Prime Factor FFT Processing Unit of form similar to Radix-4 by insertion of a variable Prime Factor Twiddle Factor and Garbage data. So, we improved limitation that cannot process 112/176/256/288 FFT of each mode of DRM system with a existent Radix Processor and increase memory size and memory access time for IFFT/FFT processing by software processing in case of implementation with a existent high speed DSP.

• Journal of the Korean Society for Precision Engineering
• /
• v.11 no.5
• /
• pp.189-198
• /
• 1994

The achievable machining accuracy depends upon the level of the micro-engineering, and the today's accuracy targets are dimensional tolerances in the order of 10nm and surface roughness in the order of 1nm. Such requirements cannot be satisfied by the conventional machining processes. Single point diamond turning is the one of new techniques which can produce the parts with such accuracy limits. The aims of this thesis are to get a better understanding of the complex cutting process with a diamond tool and, consequently, to develope a predicting model of a turned surface profile. In order to predict the turned surface profile, a numerical model has been developed. By means of this model, the influence of the operational settings-the material properties of the workpiece, the geometry of the cutting tool and the dynamic behaviour of the lathe-and their influences via the cutting forces upon the surface roughness have been estimated.

• Journal of Information Processing Systems
• /
• v.13 no.3
• /
• pp.573-589
• /
• 2017

Cloud computing is an attractive solution that can provide low cost storage and powerful processing capabilities for government agencies or enterprises of small and medium size. Yet the confidentiality of information should be considered by any organization migrating to cloud, which makes the research on relational database system based on encryption schemes to preserve the integrity and confidentiality of data in cloud be an interesting subject. So far there have been various solutions for realizing SQL queries on encrypted data in cloud without decryption in advance, where generally homomorphic encryption algorithm is applied to support queries with aggregate functions or numerical computation. But the existing homomorphic encryption algorithms cannot encrypt floating-point numbers. So in this paper, we present a mechanism to enable the trusted party to encrypt the floating-points by homomorphic encryption algorithm and partial trusty server to perform summation on their ciphertexts without revealing the data itself. In the first step, we encode floating-point numbers to hide the decimal points and the positive or negative signs. Then, the codes of floating-point numbers are encrypted by homomorphic encryption algorithm and stored as sequences in cloud. Finally, we use the data structure of DoubleListTree to implement the aggregate function of SUM and later do some extra processes to accomplish the summation.

• Journal of the Institute of Convergence Signal Processing
• /
• v.19 no.1
• /
• pp.1-6
• /
• 2018

In this paper, we propose the method to eliminate repetitive processes for key-point detection on multi-scale image space. The proposed method detects key-points from the original image, and select a good key-points using the cluster filters, and create the key-point clusters. And it select reference objects by using direction angles of the key-point clusters, predict the scale of the original image by using the distributed distance ratio. It transform the scale of the reference image, and apply the detection of key-points to the transformed reference image. In the results of the experiment, the proposed method can be found to improve the key-points detection time by 75 % and 71 % compared to SIFT method and scaled ORB method using the multi-scale images.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.35 no.4
• /
• pp.118-125
• /
• 2012

When monitoring an instrumental process, one often collects a host of data such as characteristic signals sent by a sensor in short time intervals. Characteristic data of short time intervals tend to be autocorrelated. In the instrumental processes often the practice of adjusting the setting value simply based on the previous one, so-called 'adjacent point operation', becomes more critical, since in the short run the deviations are harder to detect and in the long run they have amplified consequences. Stochastic modelling using ARIMA or AR models are not readily usable here. Due to the difficulty of dealing with autocorrelated data conventional practice is resorting to choosing the time interval where autocorrelation is weak enough then to using I-MR control chart to judge the process stability. In the autocorrelated instrumental processes it appears that using the Shewhart chart and the time interval data where autocorrelation is relatively not existent turns out to be a rather convenient and very useful practice to determine the process stability. However in the autocorrelated instrumental processes we intend to show that one would presumably do better using the EWMA control chart rather than just using the Shewhart chart along with some arbitrarily intervalled data, since the former is more sensitive to shifts given appropriate weights.

• Communications for Statistical Applications and Methods
• /
• v.30 no.1
• /
• pp.95-107
• /
• 2023

Purpose: The statistical analysis of point processes on linear networks is a recent area of research that studies processes of events happening randomly in space (or space-time) but with locations limited to reside on a linear network. For example, traffic accidents happen at random places that are limited to lying on a network of streets. This paper applies techniques developed for point processes on linear networks and the tools available in the R-package spatstat to estimate the intensity of traffic accidents in Leon County, Florida. Methods: The intensity of accidents on the linear network of streets is estimated using log-linear Poisson models which incorporate cubic basis spline (B-spline) terms which are functions of the x and y coordinates. The splines used equally-spaced knots. Ten different models are fit to the data using a variety of covariates. The models are compared with each other using an analysis of deviance for nested models. Results: We found all covariates contributed significantly to the model. AIC and BIC were used to select 9 as the number of knots. Additionally, covariates have different effects such as increasing the speed limit would decrease traffic accident intensity by 0.9794 but increasing the number of lanes would result in an increase in the intensity of traffic accidents by 1.086. Conclusion: Our analysis shows that if other conditions are held fixed, the number of accidents actually decreases on roads with higher speed limits. The software we currently use allows our models to contain only spatial covariates and does not permit the use of temporal or space-time covariates. We would like to extend our models to include such covariates which would allow us to include weather conditions or the presence of special events (football games or concerts) as covariates.