• Journal of Astronomy and Space Sciences
• /
• v.37 no.4
• /
• pp.219-228
• /
• 2020

A CubeSat platform has become a popular choice due to inexpensive commercial off-the-shelf (COTS) components and low launch cost. However, it requires more power-efficient and higher-data rate downlink capability for space applications related to remote sensing. In addition, the platform is limited by the size, weight and power (SWaP) constraints as well as the regulatory issue of licensing the radio frequency (RF) spectrum. The requirements and limitations have put optical communications on promising alternatives to RF communications for a CubeSat platform, owing to the power efficiency and high data rate as well as the license free spectrum. In this study, we analyzed the performance of optical downlink communications compatible with CubeSat platforms in terms of data rate, bit error rate (BER) and outage probability. Mathematical models of BER and outage probability were derived based on not only the log-normal model of atmospheric turbulence but also a transmitter with a finite extinction ratio. Given the fixed slot width, the optimal guard time and modulation orders were chosen to achieve the target data rate. And the two performance metrics, BER and outage data rate, were analyzed and discussed with respect to beam divergence angle, scintillation index and zenith angle.

• Geophysics and Geophysical Exploration
• /
• v.1 no.3
• /
• pp.170-175
• /
• 1998

A systematic methodology is developed for the prediction of the lithology using electrofacies classification from wireline log data. Multivariate statistical techniques are adopted to segment well log measurements and group the segments into electrofacies types. To consider corresponding contribution of each log and reduce the computational dimension, multivariate logs are transformed into a single variable through principal components analysis. Resultant principal components logs are segmented using the statistical zonation method to enhance the quality and efficiency of the interpreted results. Hierarchical cluster analysis is then used to group the segments into electrofacies. Optimal number of groups is determined on the basis of the ratio of within-group variance to total variance and core data. This technique is applied to the wells in the Korea Continental Shelf. The results of field application demonstrate that the prediction of lithology based on the electrofacies classification works well with reliability to the core and cutting data. This methodology for electrofacies determination can be used to define reservoir characterization which is helpful to the reservoir management.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.13 no.3
• /
• pp.118-123
• /
• 1999

Hough transform is well employed to retect or recognize the lines in image processing or in computer vision. Curve of the logarithm of ranges against the bearing does not change its shape according to data trints. This fact suggests that calculation cost can be remarkably reduced. An effective line detection algorithm is represented.sented.

• International journal of advanced smart convergence
• /
• v.7 no.4
• /
• pp.101-107
• /
• 2018

Visitors to a Web site leave access logs documenting their activity in the site. These access logs provide a valuable source of information about the visitors' access patterns in the Web site. In addition to the pages that the user visited, it is generally possible to discover the geographical locations of the visitors. Web servers also records other information such as the entry into the site, the URL, the used operating system and the browser, etc. There are several Web mining techniques to extract useful information from such information and visualization of a Web log is one of those techniques. This paper presents a technique as well as a case a study of visualizing a Web log.

• Journal of the Korean Institute of Gas
• /
• v.20 no.1
• /
• pp.13-22
• /
• 2016

This paper presents development of an appropriate procedure and flow chart to analyze shale gas production data obtained from a multi-fractured horizontal well according to flow characteristics in order to calculate an estimated ultimate recovery. Also, the technical considerations were proposed when a rate transient analysis was performed with field production data occurred to only $1^{st}$ transient flow. If production data show the $1^{st}$ transient flow from log-log and square root time plot analysis, production forecasting must be performed by applying different method as before and after of the end of $1^{st}$ linear flow. It is estimated by an area of stimulated reservoir volume which can be calculated from analysis results of micro-seismic data. If there are no bottomhole pressure data or micro-seismic data, an empirical decline curve method can be used to forecast production performance. If production period is relatively short, an accuracy of production data analysis could be improved by analyzing except the early production data, if it is necessary, after evaluating appropriation with near well data. Also, because over- or under-estimation for stimulated reservoir volume could take place according to analysis method or analyzer's own mind, it is necessary to recalculate it with fracture modeling, reservoir simulation and rate transient analysis, if it is necessary, after adequacy evaluation for fracture stage, injection volume of fracture fluid and productivity of producers.

• The Journal of the Korea Contents Association
• /
• v.18 no.4
• /
• pp.48-59
• /
• 2018

Recently, network technology has been used in various fields due to development of network technology. However, there has been an increase in the number of attacks targeting public institutions and companies by exploiting the evolving network technology. Meanwhile, the existing network intrusion detection system takes much time to process logs as the amount of network log increases. Therefore, in this paper, we propose a Spark-based network log analysis system that detects unstructured network attack pattern. by using Snort. The proposed system extracts and analyzes the elements required for network attack pattern detection from large amount of network log data. For the analysis, we propose a rule to detect network attack patterns for Port Scanning, Host Scanning, DDoS, and worm activity, and can detect real attack pattern well by applying it to real log data. Finally, we show from our performance evaluation that the proposed Spark-based log analysis system is more than two times better on log data processing performance than the Hadoop-based system.

• Korean Journal of Food Science and Technology
• /
• v.21 no.3
• /
• pp.360-363
• /
• 1989

The initial moisture adsorption of soybeans was examined under the conditions : RH, 57-86% ; temperature, $16^{\circ}-34^{\circ}C$, and storage time, 100 hours. The changes in moisture content as a function of time held a relation: log dw/dt=b log t + log a, where w is the moisture content (%, db), t is time (hour) and a and b are the parameters which were calculated from the experimental data. The calculated moisture content from the equation agreed well with the measured moisture content. The activation energy of initial adsorption rate was about 15500cal/g-mole in all soybeans. The initial adsorption rate at temperature $16^{\circ}-28^{\circ}C$ could be estimated from a following equation : log(log dw/dt)=-15500/2.303RT.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.1
• /
• pp.99-111
• /
• 2012

The log-density ratio of the conditional densities of the predictors given the response variable provides useful information for variable selection in the logistic regression model. In this paper, we consider the predictors that are needed and how they should be included in the model. If the conditional distributions are skewed, the distributions can be considered as gamma distributions. Under this assumption, linear and log terms are generally included in the model. The log-odds graph is a very useful graphical tool in this study. A graphical study is presented which shows that if the conditional distributions of x|y for the two groups overlap significantly, we need both the linear and quadratic terms. On the contrary, if they are well separated, only the linear or log term is needed in the model.

• Proceedings of the IEEK Conference
• /
• 2000.06c
• /
• pp.181-184
• /
• 2000

In this paper, we propose new features for describing texture images by using multi-channel Gabor filter and log-polar transform based on human visual system (HVS). Gabor features are extracted by the mean and standard deviation of energy in Gabor response, followed by Fourier series extension. Log-polar features are extracted by log-polar transform and projection. The proposed texture descriptor performs reasonably well with less number of features than other texture descriptors, which has been verified by experiments using some texture images of MPEG-7 data set.

• The Journal of Engineering Geology
• /
• v.27 no.3
• /
• pp.323-330
• /
• 2017

For the formation identification, surface geological survey, drill core analysis, core description and well log analysis are widely used. Among them well log analysis is a popular method with drill core analysis, since it measures continuously physical properties at in-situ. In this study we calculated Thomsen anisotropic parameters (${\varepsilon},\;{\delta},\;{\eta}$) after applying Backus averaging method to the P wave velocity, S wave velocity, and density logs. The well log data application of Blackfoot, Canada, shows the formation could be divided by 12 layers. This shows that Thomsen anisotropic parameters for identifying formation using anisotropic parameters is useful if there is no natural gamma log that is widely used for the formation identification.