• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1671-1676
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• 2017

In theses days, data has been explosively generated in diverse industrial areas. Accordingly, many industries want to collect and analyze these data to improve their products or services. However, collecting user data can lead to significant personal information leakage. Local differential privacy (LDP) proposed by Google is the state-of-the-art approach that is used to protect individual privacy in the process of data collection. LDP guarantees that the privacy of the user is protected by perturbing the original data at the user's side, but a data collector is still able to obtain population statistics from collected user data. However, the prevention of leakage of personal information through such data perturbation mechanism may cause the significant reduction in the data utilization. Therefore, the degree of data perturbation in LDP should be set properly depending on the data collection and analysis purposes. Thus, in this paper, we develop the simulation tool which aims to help the data collector to properly chose the degree of data perturbation in LDP by providing her/him visualized simulated results with various parameter configurations.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.47-54
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• 1998

Underwater robotic vehicles(URVs) have been an important tool for various underwater tasks such as pipe-lining, data collection, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system is one of the most critical subsystems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. It is desirable to have an intelligent vehicle control system because the fixed-parameter linear controller such as PID may not be able to handle these changes promptly and result in poor performance. In this paper we described and analyzed a new type of fuzzy model-based controller which is designed for underwater robotic vehicles and based on Takagi-Sugeno-Kang(TSK) fuzzy model. The proposed fuzzy controller: 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule; 2) can guarantee the stability of the closed-loop fuzzy system; 3) is relatively easy to implement. Its good performance as well as its robustness to parameter changes will be shown and compared with those of the PID controller by simulation.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.204-206
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• 2007

In this study, we introduce the optimization method of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation, The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the optimization process, two general optimization mechanisms are explored. The structural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods. Particularly, in parameter identification, we use the UNDX operator which uses multiple parents and generate offsprings around the geographic center off mass of these parents.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.1025-1034
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• 2015

Traditional Shewhart control charts assume that the observations are independent over time. Current progress in measurement and data collection technology lead to the presence of autocorrelated process data that may affect poor performance in statistical process control. One of the most popular charts for autocorrelated data is to model a correlative structure with an appropriate time series model and apply control chart to the sequence of residuals. Model parameters are estimated by an in-control Phase I reference sample since they are usually unknown in practice. This paper deals with the effects of parameter estimation on Phase II control limits to monitor autocorrelated data.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.287-287
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• 2023

Surface water-groundwater interaction (SWGI) is an important hydrological process that influences both the quantity and quality of water resources. However, regional scale SWGI model calibration and uncertainty analysis have been a challenge because integrated models inherently carry a vast number of parameters, modeling assumptions, and inputs, potentially leaving little time and budget to explore questions related to model performance and forecasting. In this study, we have proposed the application of iterative ensemble smoother (IES) for uncertainty analysis and calibration of the widely used integrated surface-subsurface model, SWAT-MODFLOW. SWAT-MODFLOW integrates Soil and Water Assessment Tool (SWAT) and a three-dimensional finite difference model (MODFLOW). The model was calibrated using a parameter estimation tool (PEST). The major advantage of the employed IES is that the number of model runs required for the calibration of an ensemble is independent of the number of adjustable parameters. The pilot point approach was followed to calibrate the aquifer parameters, namely hydraulic conductivity, specific storage, and specific yield. The parameter estimation process for the SWAT model focused primarily on surface-related parameters. The uncertainties both in the streamflow and groundwater level were assessed. The work presented provides valuable insights for future endeavors in coupled surface-subsurface modeling, data collection, model development, and informed decision-making.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9731-9737
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• 2014

Large scale secular registry or surveillance systems have been accumulating vast data that allow mathematical modeling of cancer incidence and mortality rates. Most contemporary models in this regard use time series and APC (age-period-cohort) methods and focus primarily on predicting or analyzing cancer epidemiology with little attention being paid to implications for designing cancer registry, surveillance or evaluation initiatives. This research models age-specific cancer incidence rates using logistic growth equations and explores their performance under different scenarios of data completeness in the hope of deriving clues for reshaping relevant data collection. The study used China Cancer Registry Report 2012 as the data source. It employed 3-parameter logistic growth equations and modeled the age-specific incidence rates of all and the top 10 cancers presented in the registry report. The study performed 3 types of modeling, namely full age-span by fitting, multiple 5-year-segment fitting and single-segment fitting. Measurement of model performance adopted adjusted goodness of fit that combines sum of squred residuals and relative errors. Both model simulation and performance evalation utilized self-developed algorithms programed using C# languade and MS Visual Studio 2008. For models built upon full age-span data, predicted age-specific cancer incidence rates fitted very well with observed values for most (except cervical and breast) cancers with estimated goodness of fit (Rs) being over 0.96. When a given cancer is concerned, the R valuae of the logistic growth model derived using observed data from urban residents was greater than or at least equal to that of the same model built on data from rural people. For models based on multiple-5-year-segment data, the Rs remained fairly high (over 0.89) until 3-fourths of the data segments were excluded. For models using a fixed length single-segment of observed data, the older the age covered by the corresponding data segment, the higher the resulting Rs. Logistic growth models describe age-specific incidence rates perfectly for most cancers and may be used to inform data collection for purposes of monitoring and analyzing cancer epidemic. Helped by appropriate logistic growth equations, the work vomume of contemporary data collection, e.g., cancer registry and surveilance systems, may be reduced substantially.

• Journal of Veterinary Science
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• v.23 no.6
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• pp.68.1-68.8
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• 2022

Background: Studies on anesthetized dogs regarding pulse pressure variation (PPV) are increasing. The influence of respiratory rate (RR) on PPV, in mechanically ventilated dogs, has not been clearly identified. Objectives: This study evaluated the influence of RR on PPV in mechanically ventilated healthy dogs after hemorrhage. Methods: Five healthy adult Beagle dogs were premedicated with intravenous (IV) acepromazine (0.01 mg/kg). Anesthesia was induced with alfaxalone (3 mg/kg IV) and maintained with isoflurane in 100% oxygen. The right dorsal pedal artery was cannulated with a 22-gauge catheter for blood removal, and the left dorsal pedal artery was cannulated and connected to a transducer system for arterial blood pressure monitoring. The PPV was automatically calculated using a multi-parameter monitor and recorded. Hemorrhage was induced by withdrawing 30% of blood (24 mL/kg) over 30 min. Mechanical ventilation was provided with a tidal volume of 10 mL/kg and a 1:2 inspiration-to-expiration ratio at an initial RR of 15 breaths/min (baseline). Thereafter, RR was changed to 20, 30, and 40 breaths/min according to the casting lots, and the PPV was recorded at each RR. After data collection, the blood was transfused at a rate of 10 mL/kg/h, and the PPV was recorded at the baseline ventilator setting. Results: The data of PPV were analyzed using the Friedman test followed by the Wilcoxon signed-rank test (p < 0.05). Hemorrhage significantly increased PPV from 11% to 25% at 15 breaths/min. An increase in RR significantly decreased PPV from 25 (baseline) to 17%, 10%, and 10% at 20, 30, and 40 breaths/min, respectively (all p < 0.05). Conclusions: The PPV is a dynamic parameter that can predict a dog's hemorrhagic condition, but PPV can be decreased in dogs under high RR. Therefore, careful interpretation may be required when using the PPV parameter particularly in the dogs with hyperventilation.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.7
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• pp.924-929
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• 2004

The objective of this study were to investigate the effect of ejaculation frequency on semen characteristics and to establish a method for quick assessment of sperm concentration in TCC using packed cell volume (PCV) as the parameter (Trial 1). Eighty senior roosters, averaging 61 wk-old, were used and the sperm concentrations were determined using a hemacytometer. The PCV value was measured in a capillary (0.75 mm in inner diameter) by centrifugation. A simple linear regression analysis suggested that the sperm concentrations were significantly correlated with PCV values (r=0.62, p<0.001). Trial 2 was conducted to determine the optimal ejaculation frequency of TCC roosters in a weekly semen collection program. The male birds were subjected to 1, 2, 3 or 6 ejaculations per week for four consecutive weeks and semen characteristics including ejaculation volume (EV, mL), sperm motility (%), PCV (%), sperm concentration (ESC, $\times$10$^{9}$/mL), weekly sperm production (WSP, $\times$10$^{9}$/wk) and average motile sperm numbers (AMSN, $\times$10$^{9}$/ejac) were determined. Average EV was greater in the group with 3 ejac/wk than with only 1 ejac/wk in weeks 1 and 3 of the collection period. WSP increased with ejaculation frequency during the first 3 weeks of collection (p<0.05). Sperm motility was better in the birds with 6 ejac/wk than in single ejaculation group for the first 2 wk and no significant differences were found for the last 2 wk of study. In contrast, the PCV value showed a trend of reduction for the first 2 wks in the 6 ejac/wk group. Surprisingly, no significant differences were detected in the AMSN among treatment groups. The weekly motile sperm production (WMSP) increased with ejaculation frequency. Based on our observation, PCV values could be used for a quick estimation of sperm concentration and an intensive semen collection program enhanced weekly sperm production in TCC roosters.

• Journal of Korean Society of Water and Wastewater
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• v.12 no.3
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• pp.65-74
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• 1998

Life cycle assessment (LCA) on two different sludge treatment systems, on-site treatment and pipe-collected intensive treatment was performed to estimate the environmental impact in the aspect of global warming effect. As a main parameter of the estimation, $CO_2$ was chosen and quantified through the whole life cycle of the treatment systems including construction, operation and dismantlement. In this study, the changes of $CO_2$ production unit (CPU) by up-scaling n currently used sludge treatment processes were also calculated. As the result, a larger amount of $CO_2$ was exhausted from the construction step of intensive treatment system than that of on-site treatment system, because an additional pipe-collection system was needed in intensive treatment system. However, the total amount of $CO_2$ exhausted from whole life cycle including not only construction and dismantlement but also 15 year-operation and maintenance was reduced by appling intensive treatment.

• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.377-390
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• 2011

A common problem encountered in product or process design is the selection of optimal parameter levels which involves simultaneous consideration of multiple response variables. This is called a multiresponse problem. A multiresponse problem is solved through three major stages: data collection, model building, and optimization. Up to date, various methods have been proposed for the optimization, including the desirability function approach and loss function approach. In this paper, the existing studies in multiresponse optimization are reviewed and a future research direction is then proposed.