• Journal of Acupuncture Research
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• v.25 no.6
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• pp.67-76
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• 2008

Objectives : The 7-zone-diagnostic system is a diagnostic device to predetermine bodily locations by measuring the energy of body. This study was to investigate the relation between the different patterns of Zone 1, 2, 3 of Factor AA in CP-6000A(VEGA, Germany), 7-zone-diagnostic system and clinical parameters. The purpose of this study was relation Korean traditional medicine and western medicine with the data from 7-zone-diagnostic system and the clinical parameters. Methods : This study was carried out with the data from some clinical parameters. We made three groups according to the Factor AA patterns of CP-6000A. The Factor AA pattern of Group A is that the red bar graph of zone 1, 2, 3 were higher than the normal range and the others were the normal range. The Factor AA pattern of Group B was that the red bar graph of zone 1, 2, 3 was the normal range and the others were the normal range. The Factor AA pattern of Group C was that the red bar graph of zone 1, 2, 3 was lower than the normal range and the others were the normal range. After the data from clinical parameters to correspond with conditions of each group were selected, the data from clinical parameters among each groups analyzed statistically. Results : The values of GOT, GPT, r-GPT, Triglyceride, BUN, Uric acid of group A was higher than group C. Gastroscope of group A and B was higher than group C. Conclusions : It is thought that the red bar graph of zone 1, 2, 3 is higher, the group has the higher energy and the energy has a character of fire(熱). Those patterns have a high risk of hyperlipermia and liver, stomach disease.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.81-88
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• 2010

Sensors in sensor networks are operated by their embedded batteries and they can not work any more if the batteries run out. The data collected by sensors should be transferred to a sink node through the efficient routes. Many energy efficient routing algorithms were proposed. However, the previous algorithms consume more energy since they did not consider the transmission range and direction. In this paper we propose an algorithm TDRP(Transmission range and Direction Routing Protocol) that considers the transmission range and direction for the efficient data transmission. Since TDRP does not produce clusters or grids but four quadrants and send data to the nodes in one quadrant in the direction of the sink node, it has less network overhead. Furthermore since the proposed algorithm sends data to the smaller number of nodes compared to the previous algorithms, the energy efficiency is better than other algorithms in communication node fields that are located in packet transmit directions.

• Atmosphere
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• v.25 no.4
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• pp.623-637
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• 2015

The accurate analysis of water vapor in initial of numerical weather prediction (NWP) model is required as one of the necessary conditions for the improvement of heavy rainfall prediction and reduction of spin-up time on a very-short-range forecast. To study this effect, the impact of a ground-based Global Positioning System (GPS)-Precipitable Water Vapor (PWV) on very-short-range forecast are examined. Data assimilation experiments of GPS-PWV data from 19 sites over the Korean Peninsula were conducted with Advanced Storm-scale Analysis and Prediction System (ASAPS) based on the Korea Meteorological Administration's Korea Local Analysis and Prediction System (KLAPS) included "Hot Start" as very-short-range forecast system. The GPS total water vapor was used as constraint for integrated water vapor in a variational humidity analysis in KLAPS. Two simulations of heavy rainfall events show that the precipitation forecast have improved in terms of ETS score compared to the simulation without GPS-PWV data. In the first case, the ETS for 0.5 mm of rainfall accumulated during 3 hrs over the Seoul-Gyeonggi area shows an improvement of 0.059 for initial forecast time. In other cases, the ETS improved 0.082 for late forecast time. According to a qualitative analysis, the assimilation of GPS-PWV improved on the intensity of precipitation in the strong rain band, and reduced overestimated small amounts of precipitation on the out of rain band. In the case of heavy rainfall during the rainy season in Gyeonggi province, 8 mm accompanied by the typhoon in the case was shown to increase to 15 mm of precipitation in the southern metropolitan area. The GPS-PWV assimilation was extremely beneficial to improving the initial moisture analysis and heavy rainfall forecast within 3 hrs. The GPS-PWV data on variational data assimilation have provided more useful information to improve the predictability of precipitation for very short range forecasts.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.823-834
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• 2020

In the past, when the personal information leakage incident of the three card companies, the computer program development was followed by the same strict electronic financial supervision regulations as the operating environment. However, when developing a computerized program, the application data is being verified with the integrity of the test data being compromised because the identification of the scope of conversion of the test data associated with the application is unclear. Therefore, in this paper, we proved by presenting a process and algorithm for selecting a range of sufficient test data conversion targets associated with a specific application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.425-429
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• 2014

The visibility range is defined from where one can see. And it can be changed by illuminance, the character size, and eyesight and so on. In this paper the visibility range of 120 students is measured for 4 character sizes and 3 illuminations in a classroom. In order to forecast the visibility range of unmeasured data, using least square approximation theory, functions whose independent variable is illuminance and whose dependent variable is the visibility range is proposed. Because the visibility range is invariant according to illuminance, common logarithmic functions for 4 character sizes are used. The small difference between the postulated functions and the measured data verifies the accuracy of the functions.

• Atmosphere
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• v.29 no.4
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• pp.451-461
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• 2019

Medium-range forecast is highly dependent on ensemble forecast data. However, operational weather forecasters have not enough time to digest all of detailed features revealed in ensemble forecast data. To utilize the ensemble data effectively in medium-range forecasting, representative weather patterns in East Asia in this study are defined. The k-means clustering analysis is applied for the objectivity of weather patterns. Input data used daily Mean Sea Level Pressure (MSLP) anomaly of the ECMWF ReAnalysis-Interim (ERA-Interim) during 1981~2010 (30 years) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Using the Explained Variance (EV), the optimal study area is defined by 20~60°N, 100~150°E. The number of clusters defined by Explained Cluster Variance (ECV) is thirty (k = 30). 30 representative weather patterns with their frequencies are summarized. Weather pattern #1 occurred all seasons, but it was about 56% in summer (June~September). The relatively rare occurrence of weather pattern (#30) occurred mainly in winter. Additionally, we investigate the relationship between weather patterns and extreme weather events such as heat wave, cold wave, and heavy rainfall as well as snowfall. The weather patterns associated with heavy rainfall exceeding 110 mm day^-1 were #1, #4, and #9 with days (%) of more than 10%. Heavy snowfall events exceeding 24 cm day^-1 mainly occurred in weather pattern #28 (4%) and #29 (6%). High and low temperature events (> 34℃ and < -14℃) were associated with weather pattern #1~4 (14~18%) and #28~29 (27~29%), respectively. These results suggest that the classification of various weather patterns will be used as a reference for grouping all ensemble forecast data, which will be useful for the scenario-based medium-range ensemble forecast in the future.

• KIEAE Journal
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• v.16 no.6
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• pp.69-75
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• 2016

Climate change has resulted in the urban heat island (UHI) effect throughout the globe, contributing to heat-related illness and fatalities. In order to reduce such damage, it is necessary to improve the climate observation network for precise observation of the urban thermal environment and quick UHI forecasting system. Purpose: This study analyzed the effective range of the climate observation network and the distribution of the existing Automatic Weather Stations (AWS) in Seoul to propose optimal locations for additional installment of AWS. Method: First, we performed quality analysis to pinpoint missing values and outliers within the high-density temperature data measured. With the result from the analysis, a spatial autocorrelation structure in the temperature data was tested to draw the effective range and correlation distance for each major time period. Result: As a result, it turned out that the optimal effective range for the climate observation network in Seoul in July was a radius of 2.8 kilometers. Based on this result, population density, and temperature data, we selected the locations for additional installment of AWS. This study is expected to be used to generate urban temperature maps, select and move measurement locations since it is able to suggest valid, specific spatial ranges when the data measured in point is converted into surface data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.686-691
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• 2008

This paper proposes the concept of "virtual sensor data" and its application for real time obstacle avoidance. The virtual sensor data is virtual distance which takes care of the movement of the obstacle as well as that of the robot. In practical application, the virtual sensor data is calculated from the odometry data and the range sensor data. The virtual sensor data can be used in all the methods which use distance data for collision avoidance. Since the virtual sensor data considers the movement of the robot and the obstacle, the methods utilizing the virtual sensor data results in more smooth and safer collision-free motion.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.26-29
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• 1987

This paper concerns methods for ${\mu}$-wave imaging. The image reconstruction of an object by range-doppler preceding using the X-Band Linear-FM signal is presented from tile simulated data. The high degree of range resolution is achived using large signal band width and cross-range resolution is obtained by doppler processing.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.428-438
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• 2021

For long-range communication in deep water, low carrier frequency is efficient due to a decrease in transmission loss. However, there is a limitation in that the data rate decreases due to a narrow bandwith. In order to increase the data rate in an environment with a limited bandwidth, it is necessary to design a higher-order modulation scheme. This paper analyzes the long-range communication data modulated by higher-order modulation schemes. The long-range communication experiment (23 km ~) was conducted in East Sea in October 2020. During the experiment, a vertical line array was utilized and communication sequences were modulated by Phase Shift Keying (PSK) and Quadrature Amplitude Modulation (QAM) schemes and transmitted by a towed source. In more detail, PSK modulation consists of quadrature PSK and 8PSK, QAM modulation consists of 8QAM and 16QAM. Time reversal processing is applied to mitigate inter-symbol interference by utilizing the correlation between received signals and channel impulse responses. All modulation schemes show successful results at 23 km range, demonstrating the feasibility of higher-order modulation in long-range communication.