• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2643-2645
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• 2001

In this paper, a problem of limited sampling time that occurs essentially in digital data acquisition system is discussed. Low sampling frequency and a lot of processed data in micro-controller interferes normal operation of the controller from acquiring information in some case. To settle this problem, we design the sub-system which consists of a new simple micro-controller. which is managed the particular sensor making the trouble to main-controller system.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.344-352
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• 2023

The purpose of this study is to empirically grasp the relationship between website immersion and website attitude by the attribute factors of the Taekwondo information website and provide it as basic data for effective operation of the Taekwondo information website. The subjects of this study were Taekwondo athletes enrolled in high schools and universities affiliated with the Korean Taekwondo Association, and the sampling method was sampled using the convient sampling method, a non-probability sampling method. Of the 820 questionnaires finally obtained, 789 were processed using PASW Statistics 20.0 and AMOS, except for 31 that were deemed to have poor respondents' contents or were not valuable as data. For data analysis, the statistical analysis techniques used in this study were frequency analysis, factor analysis, Cronbach's α test, correlation analysis, and structural equation model analysis (SEM), and the significance level of the research hypothesis was α=.It was verified at 05. The following conclusions were drawn through such research methods and procedures. First, information, entertainment, structure, cognition, searchability, and connectivity of Taekwondo information website attributes affect website immersion. Second, website immersion is affecting website attitudes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.218-224
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• 2013

Generally, SAW device, which uses Time Domain Sampling, requires high speed A/D converter because SAW device using TDS needs high sampling speed as much as its high data speed. However, the high price of A/D converter discourages makers from using it. On the other hand, SAW device, which uses Frequency Domain Sampling, does not required high speed A/D converter because SAW device using FDS does not need high sampling speed. It is very efficient in price comparison to its performance because high processing speed of SAW device using FDS can be implemented using low price Embedded Systems. The purpose of the paper is to solve the issues above by designing and realizing SAW device(FDS) using SAW sensor for TDS.

• Ocean and Polar Research
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• v.30 no.2
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• pp.149-158
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• 2008

The characteristic analysis of the estimated population parameters, i.e., standard deviation and error bound of coastal pollutant concentrations (hereafter PC, i.e., COD, TN, and TP concentrations), was carried out by using environmental data with different sampling frequency in Lake Shihwa and Incheon coastal zone. The results clearly show that standard deviation of the PC increases as its mean value increases. The error bounds of the annual mean values based on seasonally measured DO concentrations and PC data in Incheon coastal zone were estimated as ranges 2.26 mg/l, $0.68{\sim}0.86\;mg/l$, $0.62{\sim}0.80\;mg/l$, and $0.074{\sim}0.082\;mg/l$, respectively. In terms of annual mean of the DO concentration and PC in Lake Shihwa, the error bounds based on monthly measured data from 1997 to 2003 were also estimated as ranges 4.0 mg/l, 3.0 mg/l, $0.5{\sim}1.0\;mg/l$, and 0.05 mg/l, respectively. The error bound on the basis of real-time monitoring data is $7{\sim}13%$ only as compared to that of monthly measured data.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.677-682
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• 2012

There are lots of sampling design which is determined for sample survey in various fields. Especially, it is important problem for clinical data because basic characteristic variables by group which consist of experiment group and control group in population should be reflect to sample. Therefore, frequencies, center scales and dispersion scales of variables by group in population should be similar in sample. But usual sampling design is very complicate so it is difficult to use in practice for researcher. In this paper, we consider the sampling method using simulation. We applied the proposed method to colon cancer data from a hospital. We compare basic characteristic variables between population and sample with mean, frequency and statistic hypothesis test.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.211-215
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• 2006

In this paper, design and applications of a generalized, versatile and customizable IF signal generator that can model the modernized GPS and Galileo signal is given. It generates IF sampled data that can be directly used by a software receiver. Entire constellation of satellites which is independent of satellite-user geometry is easily determined using a real or simulated ephemeris data. Since the IF center frequency, sampling frequency and quantization bit number are user location dependent parameters, their effects are also considered in IF signal generator. The generalized IF signal generator will be very well suited for the development phase of a software receiver due to its versatility. The full access to the sampling frequency, front-end filter definition and ADC parameters also offers a great opportunity for cost-effective analysis of tracking loops and error mitigation techniques at the receiver level. Interference sources can be easily added to the generator to simulate specific environments. This software IF signal generator can also be used to feed a multi-frequency multi-system software receiver for the prototyping of a combined GPS/Galileo receiver. The test result using the generated signals and a real software receiver shows the effectiveness of the implemented IF signal generator.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.87-96
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• 2019

Low power issue is one of the most critical problems in the Internet of Things (IoT), which are powered by battery. To solve this problem, various approaches have been presented so far. In this paper, we propose a method to reduce the power consumption by reducing the numbers of accesses into the flash memory consuming a large amount of power for on-chip software execution. Our approach is based on using cooperative logging structure to distribute the sampling overhead in single sensor node to adjacent nodes in case of rare-event applications. The proposed algorithm to identify event occurrence is newly introduced with negative feedback method by observing difference between past data and recent data coming from the sensor. When an event with need of flash access is determined, the proposed approach only allows access to write the sampled data in flash memory. The proposed event detection algorithm (EDA) result in 30% reduction of power consumption compared to the conventional flash write scheme for all cases of event. The sampled data from the sensor is first traced into the random access memory (RAM), and write access to the flash memory is delayed until the page buffer of the on-chip flash memory controller in the micro controller unit (MCU) is full of the numbers of the traced data, thereby reducing the frequency of accessing flash memory. This technique additionally reduces power consumption by 40% compared to flash-write all data. By sharing the sampling information via LoRa channel, the overhead in sampling data is distributed, to reduce the sampling load on each node, so that the 66% reduction of total power consumption is achieved in several IoT edge nodes by removing the sampling operation of duplicated data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.1020-1026
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• 2013

Multirate filtering process on the biological signals like Electrocardiogram (ECG) and Photoplethysmogram (PPG) can be defined as the digital signal processing algorithm in which the sampling rate varies to omit or interpolate the intermediate values between the sampled data. With this aim, we suggest a new multirate filtering algorithm by deleting the extraneous data to eliminate the unwanted degradations such as granular noise due to the usage of high sampling frequency and simultaneously to detect the fiducial features of ECG and PPG with reducing the complexity of resolving fiducial points such as R-peak, Pulse peak and Pulse Transit Time (PTT). After the experimental simulations performed, we can conclude the fact that we can detect the fiducial features of ECG and PPG signal in terms of R-peak, Pulse peak and PTT without the loss of accuracy even if we do not maintain the original sampling frequency.

• Computational Structural Engineering
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• v.9 no.4
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• pp.107-115
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• 1996

Displacement response is one of the important parameter to determine vibration characteristics of bridge structure. Reliable estimate of displacement response is obtained economically from integration of measured acceleration data in frequency domain. Proper sampling rate of frequency in discretization process of measured acceleration is proposed. Comparison of integrated and directly measured displacement response from laboratory experiment for a cantilever beam shows good agreement each other. Mode shape obtained from estimated displacement response also closely match with analytical result, thus the developed method is proved to be effective in practical use.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.15-27
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• 2012

We have studied the realized variance(RV) of intra-day returns and market microstructure noise based on high-frequency stock transaction data for the four largest companies in terms of market capitalization in the KOSPI. First, non-negligible biases are observed for the RV and for the bias-corrected realized variance($RV_{AC_1}$) which is constructed by adjusting RV for the first order autocorrelation in intra-day returns. Bias is more obvious for the RV and the $RV_{AC_1}$ when intra-day returns are sampled more frequently than every 2 minutes. Transaction Time Sampling(TTS) is shown to be better than Calendar Time Sampling(CTS) in terms of biases of the RV and the $RV_{AC_1}$ for the 4 companies. The analysis reveals that market microstructure noise is temporally dependent. Second, by using the Noise-to-Signal Ratio(NSR), we estimate sampling frequencies that are optimal in terms of the Mean Square Errors(MSE) of the RV and the $RV_{AC_1}$. The optimal sampling frequencies are around 200 for RV and is around 5000 for the $RV_{AC_1}$ for all the four stock prices. For the 6 hour transaction period of the Korean stock trading, these correspond to about 2 minutes and 6 seconds.