• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.29-32
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• 2015

It has been a big trend of the convergence technologies about communication systems and vehicular industry to improve safety and convenience. To achieve a number of infotainment vehicular applications, vehicles should transmit information with high reliability. A robust and accurate channel estimation scheme is of great importance to achieve the goal. In this paper, we present a novel enhanced decision-directed channel estimation scheme called FADP (Frequency Averaging Data Pilot) for dynamic time-varying vehicular channels in IEEE 802.11p. We use linear averaging filtering in frequency domain, and utilize the correlation characteristic of the channels between the adjacent two data symbols, update the CR in time domain to get more accuracy. Finally, analysis and simulation results reveal that compared with exist schemes, the proposed scheme has a good performance in mean square error (MSE) and bit error rate (BER).

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.663-668
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• 2024

This paper applies statistical analysis methods in the time domain to the fault diagnosis of wafer transfer robots, and proposes a methodology to discern the critical characteristics of vibration and torque signals. Subsequently, principal component analysis (PCA) is applied to diminish the data's dimensionality, followed by the development of a fault diagnosis algorithm utilizing Euclidean distance and Hotelling's T-square statistics. The algorithm establishes decision boundaries to categorize failure states based on the observed data. Our findings indicate that data classification incorporating velocity parameters enhances diagnostic accuracy. This approach serves to enhance the precision and efficacy of fault diagnosis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1840-1867
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• 2024

In this study, we focus on addressing the functional domain of research related to indexing XML data in wireless networks, emphasizing ensuring data confidentiality. The abstract outlines a novel indexing method designed for broadcasting encrypted XML data over wireless networks. The proposed technique involves two channels: one for indexing and another for transmitting the actual XML data. The method ensures data security by encrypting the XML stream, allowing mobile devices to access only authorized bits based on their access permissions. Despite an increase in data access time and device tuning time, the study concludes that the proposed indexing technique significantly enhances the security of transmitting XML data over mobile wireless networks.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.139-149
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• 2018

The resistivity monitoring is a practical method to resolve changes in resistivity of underground structures over time. With the advance of sophisticated automatic data acquisition system and rapid data communication technology, resistivity monitoring has been widely applied to understand spatio-temporal changes of subsurface. In this study, a new 4D inversion algorithm is developed, which can effectively emphasize significant changes of underground resistivity with time. To overcome the overly smoothing problem in 4D inversion, the Lagrangian multipliers in the space-domain and time-domain are determined automatically so that the proportion of the model constraints to the misfit roughness remains constant throughout entire inversion process. Furthermore, a focusing model constraint is added to emphasize significant spatio-temporal changes. The performance of the developed algorithm is demonstrated by the numerical experiments using the synthetic data set for a time-lapse model.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.221-229
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• 2013

In this paper, the image formation by the motion compensation technique for Synthetic Aperture Radar system(SAR) were realized through the computer simulation. The motion compensation technique performed image data with the range compression, the compensation procedure, the azimuth compensation and the noise elimination procedure. The range compression procedure transform the SAR raw data into the frequency domain and correlate with the range reference function and then inversely transform into the time domain. The compensation procedure contain the aircraft fluctuations compensation and the radar image degrading effect elimination procedure which was caused by image formation algorithm itself. The aircraft fluctuations compensation procedure perform the first stage which correct the phase angle and the second stage which calculate the Doppler frequency and determine the coordinate of the received signal. The radar image degrading effect elimination procedure also perform range migration compensation and the image defocussing effect compensation. The azimuth compression procedure transform the compensation data to the frequency domain and correlate with the azimuth reference function. The azimuth correlated data are inversely transformed to the time domain which is called SAR image data. When the above procedure were completed, the image data contains the received signals mixed with noise. The threshold technique was applied to elimination the noise from the mixed image data.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.258-264
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• 2007

Spatiotemporal changes of brain rhythmic activity at a certain frequency have been usually monitored in real time using scalp potential maps of multi-channel electroencephalography(EEG) or magnetic field maps of magnetoencephalography(MEG). In the present study, we investigate if it is possible to implement a real-time brain activity monitoring system which can monitor spatiotemporal changes of cortical rhythmic activity on a subject's cortical surface, neither on a sensor plane nor on a standard brain model, with a high temporal resolution. In the suggested system, a frequency domain inverse operator is preliminarily constructed, considering the individual subject's anatomical information, noise level, and sensor configurations. Spectral current power at each cortical vertex is then calculated for the Fourier transforms of successive sections of continuous data, when a single frequency or particular frequency band is given. An offline study which perfectly simulated the suggested system demonstrates that cortical rhythmic source changes can be monitored at the cortical level with a maximal delay time of about 200 ms, when 18 channel EEG data are analyzed under Pentium4 3.4GHz environment. Two sets of artifact-free, eye closed, resting EEG data acquired from a dementia patient and a normal male subject were used to show the feasibility of the suggested system. Factors influencing the computational delay are investigated and possible applications of the system are discussed as well.

• Journal of Internet Computing and Services
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• v.5 no.6
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• pp.59-66
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• 2004

In this paper, we propose a transmission rate prediction method of video data. The proposed method checks shot transition characteristics after dividing MPEG video data into a GoP unit and then uses Kalman filter. It used algorithm to detect shot transition information by high speed in compressed domain in order to check a correct shot transition of video data and classified into a abrupt shot transition type and a gradual shot transition type. Information to have been classifying is used as factors of Kalman filter and predicts a transmission rate of video data. Also, the proposed method decreased processing time with detecting shot transition and predicting a transmission rate of video data in compressed domain. It predicted a transmission rate with 96.2- 97.6% in the experiment that used three kinds of 911 1frames of different video data.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.129-136
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• 2023

The government of the Republic of Korea is conducting quality management of public open data by conducting a public data quality management level evaluation. Public open data is provided in various open formats such as XML, JSON, and CSV, with CSV format accounting for the majority. When diagnosing the quality of public open data in CSV format, the quality diagnosis manager determines and diagnoses the domain for each field based on the field name and data within the field of the public open data file. However, it takes a lot of time because quality diagnosis is performed on large amounts of open data files. Additionally, in the case of fields whose meaning is difficult to understand, the accuracy of quality diagnosis is affected by the quality diagnosis person's ability to understand the data. This paper proposes a domain discrimination model for public open data in CSV format using field names and data distribution statistics to ensure consistency and accuracy so that quality diagnosis results are not influenced by the capabilities of the quality diagnosis person in charge, and to support shortening of diagnosis time. As a result of applying the model in this paper, the correct answer rate was about 77%, which is 2.8% higher than the file format open data diagnostic tool provided by the Ministry of Public Administration and Security. Through this, we expect to be able to improve accuracy when applying the proposed model to diagnosing and evaluating the quality management level of public data.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.180-188
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• 2016

In this paper, we propose a fire detection algorithm based on motion information and color information analysis. Conventional fire detection algorithms have as main problem the difficulty to detect fire due to external light, intensity, background image complexity, and little fire diffusion. So we propose a fire detection algorithm that accurate and fast. First, it analyzes the motion information in video data and then set the first candidate. Second, it determines this domain after analyzing the color and the domain. This algorithm assures a fast fire detection and a high accuracy compared with conventional fire detection algorithms. Our algorithm will be useful to real-time fire detection in real world.

• Korean Journal of Hydrosciences
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• v.4
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• pp.33-49
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• 1993

The Purpose of this study is to classify existing hysteresis models and to discuss a possibility of a new type of the hysteresis model. The existing hysteresis models are classified into three types: the interpolation model, the scaling model and the domain model, of which only domain model is to simulate hysteresis curves based on the theoretical approach, It is useful to develop a hysteresis model that requires only one branch of hysteresis curves for the model calibration because obtaining hysteresis curves by experiments is expensive and time-concept by many investigators, however their models are not successful to accurately simulate real data of Rubicon Sandy Loam and Dune Sand. There is a possibility that a new model is based on the dependent domain concept considering the weighting factor, $P_a$($\theta$), which accounts for the pore blockage effect against air entry. Conclusively, a new model where the weighting factor $P_a$($\theta$) in Model III-1 (Mualem, 1984) reduces to a known variable through an appropriate method is an alternative model which required only one branch of main curves for the model calibration.