• Proceedings of the Korea Concrete Institute Conference
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• 2001.05a
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• pp.597-602
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• 2001

Most of the predicted shear strength of continuous R.C. beam whitout web reinforcement were accepted by testing simple beams. But the experimental results may show that a differential behavior on simple and continuous R.C. beam. In this study, estimated shear strength of continuous R.C. beam without web reinforcement with internal force state factors by test as purpose to apply available predicted equation to normal continuous R.C. beam. This equation is applied to experimentally tested data and the results were compared with those predicted by the codes. Predicted shear strength using force state factor can provide a tested data rather than codes which like ACI

• Journal of Industrial Technology
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• v.18
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• pp.267-275
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• 1998

Continuous thermodynamics has been applied for modeling of phase equilibria in multicomponent mixtures, to avoid disadvantages of the pseudo-component and key-component method. In this paper continuous thermodynamic relations formulated by using the Pate-Teja equation of state were adopted for calculations of phase equilibria in natural gas mixtures, crude oil mixtures and mixtures extracted by supercritical $CO_2$ fluids. Calculations of phase equilibria were performed by two procedures ; a moment method coupled with the beta distribution function and a quadrature method combined with Gaussian-Legendre polynomials. Calculated results were compared with experimental data. It was showed that continuous thermodynamic frameworks considered in this paper were well-matched to experimental data.

• The KIPS Transactions:PartD
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• v.14D no.5
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• pp.459-470
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• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Query processing for such a data stream should also be continuous and rapid, which requires strict time and space constraints. In most DSMS(Data Stream Management System), the selection predicates of continuous queries are grouped or indexed to guarantee these constraints. This paper proposes a new scheme tailed an ASC(Attribute Selection Construct) that collectively evaluates selection predicates containing the same attribute in multiple continuous queries. An ASC contains valuable information, such as attribute usage status, partially pre calculated matching results and selectivity statistics for its multiple selection predicates. The processing order of those ASC's that are corresponding to the attributes of a base data stream can significantly influence the overall performance of multiple query evaluation. Consequently, a method of establishing an efficient evaluation order of multiple ASC's is also proposed. Finally, the performance of the proposed method is analyzed by a series of experiments to identify its various characteristics.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1311-1317
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• 2010

A continuous time asymmetric power GARCH(1,1) model is suggested, based on a single background driving L$\'{e}$vy process. The stochastic differential equation for the given process is derived and the strict stationarity and kth order moment conditions are examined.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.591-595
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• 2009

Most existing routing protocols for object detection and tracking in wireless sensor networks concentrate on finding ways to detect and track one and more individual objects, e.g. people, animals, and vehicles, but they do not be interested in detecting and tracking of continuous objects, e.g., poison gas and biochemical. Such continuous objects have quite different properties from the individual objects since the continuous objects are continuously distributed across a region and usually occupy a large area, Thus, the continuous objects could be detected by a number of sensor nodes so that sensing data are redundant and highly correlated. Therefore, an efficient data collection and report scheme for collecting and locally aggregating sensing data is needed, In this paper, we propose the Continuous Object Tracking Mechanism based on Dynamic Rectangle Zone for detecting, tracking, and monitoring the continuous objects taking into account their properties.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.393-404
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• 2005

As multi-source spatial data fusion mainly deal with various types of spatial data which are specific representations of real world with unequal reliability and incomplete knowledge, proper data representation and uncertainty analysis become more important. In relation to this problem, this paper presents and applies an advanced data representation methodology for different types of spatial data such as categorical and continuous data. To account for the uncertainties of both categorical data and continuous data, fuzzy boundary representation and smoothed kernel density estimation within a fuzzy logic framework are adopted, respectively. To investigate the effects of those data representation on final fusion results, a case study for landslide hazard mapping was carried out on multi-source spatial data sets from Jangheung, Korea. The case study results obtained from the proposed schemes were compared with the results obtained by traditional crisp boundary representation and categorized continuous data representation methods. From the case study results, the proposed scheme showed improved prediction rates than traditional methods and different representation setting resulted in the variation of prediction rates.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.15-22
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• 2008

This study collected the latest 30-year (1976~2005) continuous rainfall data hourly recorded at 61 meterological observatories in Korea, and the continuous rainfall data was divided into individual rainfall events. In addition, distribution charts of average rainfall event-depth were created to facilitate the application to the overflow risk-based design of detention storage basin. This study shows that 4 hour is appropriate for SST (storm separation time) to separate individual rainfall events from the continuous rainfall data, and the one-parameter exponential distribution is suitable for the frequency distribution of rainfall event depths for the domestic rainfall data. The analysis of the domestic rainfall data using SST of 4 hour showed that the individual rainfall event was 1380 to 2031 times, the average rainfall event-depth was 19.1 to 32.4mm, and ranged between 0.877 and 0.926. Distribution charts of average rainfall event-depth were created for 4hour and 6 hour of SST, respectively. The inland Gyeongsangbuk-do, Western coastal area and inland of Jeollabuk-do had relatively lower average rainfall event-depth, whereas Southern coastal area, such as Namhae, Yeosu, and Jeju-do had relatively higher average rainfall event-depth.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.39-56
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• 2015

Continuous multi-interval prediction (CMIP) is used to continuously predict the trend of a data stream based on various intervals simultaneously. The continuous integrated hierarchical temporal memory (CIHTM) network performs well in CMIP. However, it is not suitable for CMIP in real-time mode, especially when the number of prediction intervals is increased. In this paper, we propose a real-time integrated hierarchical temporal memory (RIHTM) network by introducing a new type of node, which is called a Zeta1FirstSpecializedQueueNode (ZFSQNode), for the real-time continuous multi-interval prediction (RCMIP) of data streams. The ZFSQNode is constructed by using a specialized circular queue (sQUEUE) together with the modules of original hierarchical temporal memory (HTM) nodes. By using a simple structure and the easy operation characteristics of the sQUEUE, entire prediction operations are integrated in the ZFSQNode. In particular, we employed only one ZFSQNode in each level of the RIHTM network during the prediction stage to generate different intervals of prediction results. The RIHTM network efficiently reduces the response time. Our performance evaluation showed that the RIHTM was satisfied to continuously predict the trend of data streams with multi-intervals in the real-time mode.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04d
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• pp.253-255
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• 2003

Electricity is the prime commodity in mobile device, e.g. smart phone, PDA, MP3 player and etc. This strict restriction on power consumption requirement of the mobile device puts unique demand in designing hardware and software components of the device. In this paper, we address the issue of minimizing the power consumption in retrieving the continuous media data from the disk drive for real-time playback purpose. Different from the legacy text based data, real-time multimedia playback requires that the storage supplies the data block continuous fashion. This may put immense burden on the power scarce environment since the disk Is required to be active for the entire playback duration. We develop elaborate algorithm which carefully analyzes the power consumption profile of the disk drive and which establishes the data retrieval schedule for the given playback. It computes the amount of data blocks to read, the length of active and standby period. According to our simulation result, the ARM algorithm exhibits superior performance in continuous media retrieval from the aspect of power consumption to legacy playback scheme.

• Bulletin of the Korean Mathematical Society
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• v.60 no.1
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• pp.93-111
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• 2023

In this paper we study a nudging continuous data assimilation algorithm for the three-dimensional Leray-α model, where measurement errors are represented by stochastic noise. First, we show that the stochastic data assimilation equations are well-posed. Then we provide explicit conditions on the observation density (resolution) and the relaxation (nudging) parameter which guarantee explicit asymptotic bounds, as the time tends to infinity, on the error between the approximate solution and the actual solution which is corresponding to these measurements, in terms of the variance of the noise in the measurements.