• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.7
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• pp.303-312
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• 2006

This paper proposes the architecture and protocol of a data communication network for the safety system in nuclear power plants. First, we establish four design criteria with respect to determinability, reliability, separation and isolation, and verification/validation. Next we construct the architecture of the safety network for the following systems: PPS (Plant Protection System), ESF-CCS (Engineered Safety Features-Component Control System) and CPCS (Core Protection Calculator System). The safety network consists of 12 sub-networks and takes the form of a hierarchical star. Among 163 communication nodes are about 1600 origin-destination (OD) pairs created on their traffic demands. The OD pairs are allowed to exchange data only during the pre-assigned time slots. Finally, the communication protocol is designed in consideration of design factors for the safety network. The design factors include a network topology of star, fiber-optic transmission media, synchronous data transfer mode, point-to-point link configuration, and a periodic transmission schedule etc. The resulting protocol is the modification of IEEE 802.15.4 (LR-WPAN) MAC combined with IEEE 802.3 (Fast Ethernet) PHY. The MAC layer of IEEE 802.15.4 is simplified by eliminating some unnecessary (unctions. Most importantly, the optional TDMA-like scheme called the guaranteed time slot (GTS) is changed to be mandatory to guarantee the periodic data transfer. The proposed protocol is formally specified using the SDL. By performing simulations and validations using Telelogic Tau SDL Suite, we find that the proposed safety protocol fits well with the characteristics and the requirements of the safety system in nuclear power plants.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.758-767
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• 2017

IoT paradigm which makes a information without direct intervention of a human and interworks with other objects, humans and systems is attracting attention. It will be expected the number of smart devices equipped with sensors and wireless communication capabilities is reached to about 260 billion by 2020. With the vast amount of sending data generated from rapidly increasing number of smart devices, it will bring up the traffic growth over internet and congestion in wireless networks. In this paper, we utilize the smart device as a sink node to collect and forward the sensing data periodically in IoT and propose a heuristic algorithm for a selection of sink nodes' set with each sink node satisfies the QoS its applications because a selection of optimal sink nodes' set is NP-hard problem. The complexity of proposed heuristic algorithm is $O(m^3)$ and faster than the optimal algorithm.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.217-225
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• 2019

The Latent Growth Modeling(LGM) is known as the typical analysis method of longitudinal data and it could be classified into unconditional model and conditional model. It is common to assume that the growth trajectory of unconditional model of LGM is linear. In the case of quasi-linear, the methodology for improving the model fitness using Sequential Pattern of Association Rule Mining is suggested. To do this, we divide longitudinal data into quintiles and extract periodic changes of the longitudinal data in each quintiles and make sequential pattern based on this periodic changes. To evaluate the effectiveness, the LGM module in SPSS AMOS was used and the dataset of the Youth Panel from 2001 to 2006 of Korea Employment Information Service. Our methodology was able to increase the fitness of the model compared to the simple linear growth trajectory.

• Korean Journal of Occupational Health Nursing
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• v.4
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• pp.84-101
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• 1995

The periodic health examination have been shown the important role on early detection, early treatment and prevention of disease. Until now, there have been many studies that showed the effectiveness of the periodic health examination on the early detection and early treatment of disease to some extent. But there are few studies about primary prevention before health problem arise. In this case-control study, 29 newly detected hypertensive cases, 31 liver disease cases and 65 controls which are all available for 6-year data in the periodic health examination of a occupational field were compared to investigate the significant increase trend of health status between the groups. The results will be used for the occupational health nurses to provide appropriate primary prevention to the employees. The hypertensive and liver disease cases were divided observation-needed group and treatment-needed group. The data on systolic blood pressure, diastolic blood pressure, Body Mass Index and Broca Index in hypertensive cases and SGOT, SGPT, Body Mass Index and Broca Index in liver disease cases were analyzed by t-test and ANOVA. The specific findings are summarized as follows. 1. In the comparison between the hypertensive cases and controls, SBP and DBP of the observation-needed group and the treatment-needed group were significantly higher than the data of the controls for past 6 years. It was 2-3 years ago showing increase over 140/90mmHg of blood pressure in the hypertensive cases before they are categorized as hypertensive cases. In the observation-needed group and the treatment-needed group, the trend of the blood pressure for 6 years were significantly higher than the one of the controls. 2. In the comparison between the liver disease cases and controls, SGOT and SGPT of the observation-needed group and the treatment-needed group were significantly higher than the data of the controls for past 6 years. It was 2 years ago showing increase within upper normal limit of SGOT and 5 years ago of SGPT in the liver disease cases before they are categorized as liver disease cases. In the observation-needed group and the treatment-needed group, the trend of the liver enzyme for 6 years were significantly higher than the one of the controls. With these results, the author proposed that intervention for the primary prevention such as continuous follow-up, health education and weight control to the population who has over 140/90mmHg of blood pressure and upper normal limit of AST and ALT.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.1
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• pp.57-69
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• 2020

In general, many IoT devices, including smart phones, use LTE, Wi-Fi, and Bluetooth, and these communication modules generate a lot of energy consumption during periodic data transmission. This paper proposes a method of the data transmission mode change for improving energy efficiency in various communication environments that mobile devices may encounter. We propose an algorithm for setting the mode considering energy efficiency, data transmission performance and cost when the mobile device transmits data, and transmitting the data in an optimized manner according to the state of the mobile device. The proposed algorithm is implemented through experiments on energy efficiency for each communication module, and the scenario is used to verify how efficiently the proposed algorithm uses energy.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.338-341
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• 2005

In this paper, a real-time communication method using a PICNET-NP(Plant Instrumentation and Control Network for Nuclear Power Plant) is proposed with an analysis of the control network requirements of DCS (Distributed Control System) in nuclear power plants. The method satisfies deadline in case of worst data traffics by considering aperiodic and periodic real-time data and others. In addition, the method was used to analyze the data characteristics of the DCS in existing nuclear power plant. The result shows that use of this method meets the response time requirement(100ms).

• Journal of Industrial Technology
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• v.15
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• pp.41-50
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• 1995

This paper presents a technique for estimating distribution of data stored in a database. This technique is very useful for accurate selectivity estimation, which is essential in query optimization and physical database design. To maintain data distribution, we employ the directory of the multilevel grid file, a multidimensional dynamic file organization. The major advantage of our technique is that data distribution information is maintained dynamically in the multilevel grid file. In contrast, other static methods such as the histogram method use static date structures, which requires periodic restructuring. Furthermore, we propose a method for keeping the abstract information of data distribution in main memory. This is advantageous in the situation where the size of main memory is not sufficient. Finally, We also suggest formulas for calculating selectivies of various queries based on our data distribution information.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.569-576
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• 2003

The data link layer of Foundation Fieldbus provides both token-passing and scheduling services for periodic, time-critical and time-available data. This study developed an analytical model that evaluates the delay performance of urgent data when the data link layer of Foundation Fieldbus provides token-passing service. The validity of analytical model is verified using an experimental model that consists of network interface boards of Foundation Fieldbus. Comparison of analytical and experimental models shows that the analytical model can be utilized in the approximate analysis of the delay characteristics of time-critical data in the Foundation Fieldbus. The analytical model can also be used in the basic design stage of Foundation Fieldbus network system.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1171-1173
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• 2003

There are two datasets to estimate the area-mean and time-mean precipitation rate. For one, an array of surface rain gauges represents a series of rods that have to the time axis of the volume. And another data is that of a remote sensing make periodic overpasses at a fixed interval such as radar. The problem of optimally combining data from surface rain gauge data and remote sensed data is considered. In order to combining remote sensed data with Automatic Weather Station (AWS), we use optimal weighting method, which is similar to the method of [2]. They had suggested optimal weights that minimized value of the mean square error. In this paper, optimal weight is evaluated for the cases such as Changma, summer Monsoon, Typhoon and orographic rain.

• Water for future
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• v.15 no.3
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• pp.23-36
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• 1982

The stochastic variations and structures of time series data on water quality were examined by employing the techniques of autocorrelation function, variance spectrum, Fourier series, autoregressive model and ARIMA model. These time series included hourly and daily observation on DO, turbidity, conductivity pH and water temperature. The measurement was made by automatic recording instrument at Noryangjin and Dook-do located in the downstream part of Han River during 1975 and 1976. Hourly water quality time series varied with the dominant 24-hour periodicity, and the 12-hour periodicity was also observed. An important factor affecting 24-hour periodic variation of DO is believed to be photosynthesis by algae. These phenomena might be attributable to periodic discharges of municipal sewage. Noryangjin site showed the more distinct 12-hour periodicity than Dook-do site did, and tidal effect might be responsible for the difference. The water quality, as measured by DO and turbidity, was better in the afternoon compared with the quality in the morning. This change can be explained by the periodic variation of DO, temperature and the amount of municipal wewage discharge. It was also observed that the water temperature at Noryangjin was higher than the temperature at Dook-do. This difference might have been caused by the pollutants that were added to the section between two sites. The correlation coefficients between some of the variables were fairly high. For example, the coefficient was -0.88 between DO and water temperature, 0.75 between turbidity and river flow, and 0.957 between water temperature and air temperature. The lag time of heat transfer from the air to the water was estimated as 24 days. The first order auto-regressive model was appropriate for explaning standardized hourly DO time series. The ARIMA model of (1, 0, 0) type provided relatively satisfactory results for daily DO time series after the removal of significant harmonic value.