• 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.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.733-742
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• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Due to this reason, memory usage for data stream analysis should be confined finitely although new data elements are continuously generated in a data stream. To satisfy this requirement, data stream processing sacrifices the correctness of its analysis result by allowing some errors. The old distribution statistics are diminished by a predefined decay rate as time goes by, so that the effect of the obsolete information on the current result of clustering can be eliminated without maintaining any data element physically. This paper proposes a grid based clustering algorithm for a data stream. Given a set of initial grid cells, the dense range of a grid cell is recursively partitioned into a smaller cell based on the distribution statistics of data elements by a top down manner until the smallest cell, called a unit cell, is identified. Since only the distribution statistics of data elements are maintained by dynamically partitioned grid cells, the clusters of a data stream can be effectively found without maintaining the data elements physically. Furthermore, the memory usage of the proposed algorithm is adjusted adaptively to the size of confined memory space by flexibly resizing the size of a unit cell. As a result, the confined memory space can be fully utilized to generate the result of clustering as accurately as possible. The proposed algorithm is analyzed by a series of experiments to identify its various characteristics

• Tunnel and Underground Space
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• v.34 no.2
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• pp.154-168
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• 2024

The Tunnel Boring Machine (TBM) disc cutter is subjected to wear and damage during the rock excavation process, and the worn disc cutter should be replaced on time. The manual inspection by workers is generally required to determine the disc cutter replacement. In this case, the workers are exposed to dangerous environments, and the measurements are sometimes inaccurate. In this study, we developed a technology that measures the disc cutter wear in real time. From a series of laboratory tests, a magnetic sensor was selected as the wear sensor, and the real-time disc cutter measurement system was developed integrating wireless communication modules, power supply and data processing board. In addition, the measurement system was verified in actual TBM excavation circumstances. As a result, it was confirmed that the accuracy and stability of the system.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.359-365
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• 2021

GEO-KOMPSAT-2A (GK2A) AMI (Advanced Meteorological Imager) Best Detector Select (BDS) map is pre-determined and uploaded before the satellite launch. After the launch, there is some possibility of a detector performance change driven by an abrupt temperature variation and thus the status of BDS map needs to be evaluated and updated if necessary. To investigate performance of entire elements of the detectors, AMI BDS analyses were conducted based on a technical note provided from the AMI vendor (L3HARRIS). The concept of the BDS analysis is to investigate the stability of signals from detectors while they are staring at targets (deep space and internal calibration target). For this purpose, Long Time Series (LTS) and Output Voltage vs. Bias Voltage (V-V) methods are used. The LTS for 30 secs and the V-V for two secs are spanned respectively for looking at the targets to compute noise components of detectors. To get the necessary data sets, these activities were conducted during the In-Orbit Test (IOT) period since a normal operation of AMI is stopped and special mission plans are commanded. With collected data sets during the GK2A IOT, AMI BDS map was intensively examined. It was found that about 1% of entire detector elements, which were evaluated at the ground test, showed characteristic changes and those degraded elements are replaced by alternative best ones. The stripping effects on AMI raw images due to the BDS problem were clearly removed when the new BDS map was applied.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.173-184
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• 2002

This paper discuss an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, Kim et al. suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multidimensional index using a feature vector as indexing attributes. For query processing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verify the superiority of our approach, we perform extensive experiments. The results reveal that our approach achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.201-214
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• 2020

This study proposes a bias correction method of dual-pol radar rain rate in real time using the dual Kalman filter. Unlike the conventional Kalman filter, the dual Kalman filter predicts state variables with two systems (state estimation system and model estimation system) at the same time. Bias of rain rate is corrected by applying the bias correction ratio to the rain rate estimate. The bias correction ratio is predicted from the state-space model of the dual Kalman filter. This method is applied to a storm event with long duration occurred in July 2016. Most of the bias correction ratios are estimated between 1 and 2, which indicates that the radar rain rate is underestimated than the ground rain rate. The AR (1) model is found to be appropriate for explaining the time series of the bias correction ratio. The time series of the bias correction ratio predicted by the dual Kalman filter shows a similar tendency to that of observation data. As the variability of the bias correction increases, the dual Kalman filter has better prediction performance than the Kalman filter. This study shows that the dual Kalman filter can be applied to the bias correction of radar rain rate, especially for long and heavy storm events.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.459-466
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• 2001

The floor vibration aspect for building structures which are in need of large open space are influenced by the interrelation between natural frequency and working loads. Structures with a long span and low natural frequency have a higher possibility of experiencing excessive vibration induced by dynamic excitation such as human activities. These excessive vibrations make the residents uncomfortable and the serviceability deterioration. Need formulation of loads data through actual measurement to apply walking loads that is form of dynamic load in structure analysis. The loads induced by human activities were classified into two types. First type is in place loads. the other type is moving loads. A series of laboratories experiments had been conducted to study the dynamic loads induced by human activities. The earlier works were mainly concerned to parameters study of dynamic loads. In this Paper, the walking loads have been directly measured by using the measuring plate in which two load cells were placed, the parameters, the load-time history of walking loads, and the dynamic load factors have been analyzed. Moreover, the shape of the harmonic loads which were gotten by decomposition the walking loads have been analyzed , and the walking loads modeling have been carried out by composition these harmonic loads derived by functional relation.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.667-669
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• 2003

A bio-optical model was developed specific for turbid and shallow waters. Special studies were carried out to estimate absorption and scattering properties as well as backscattering probability of suspended matter. The inversion of bio-optical model allows for direct retrieval of turbidity and chlorophyll- a from the visible-near infrared (VNIR) range sensor. Time-series satellite imagery from ASTER AM-1 sensor, were used to monitor the Laguna de Bay water quality condition. Spatial distribution of temperature for the lake was extracted from the thermal infrared (TIR) sensor. Corresponding field surveys were conducted to parameterize the bio -optical model. In-situ measurements include suspended particle and chlorophyll-a concentrations profiles from nephelometric devices and processing of water samples. Hyperspectral measurements were used to validate results of the bio -optical model and satellite- based estimation. This study provides a theoretical basis and a practical illustration of applying space- based measurements on an operational basis.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.91-98
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• 2021

One of the concerns in the economic policy circle is the fiscal sustainability. This current research revisit the notion of fiscal sustainability for Malaysia using the Indicator of Fiscal Sustainability (IFS) developed by Croce and Juan-Ramón (2003) where we employ samples of time-series data from 1970 to 2017. The findings reveal that 40 out of 48 years, during which the calculated IFS algorithm is above the threshold of 1, imply Malaysia was fiscally unsustainable. Despite having been fiscally unsustainable, Malaysia's fiscal stance shows improvement as a result of fiscal consolidation and fiscal reforms during the sample period. This is shown by the improved calculated IFS algorithm on average, which the value improved from 1.465 in 1970-1993 to 1.377 in 1998-2004 and to 1.146 in the 2006-2013. From the policy front, this indicator can serve as a precautionary early warning measure in formulating future fiscal path for Malaysia. This can be executed by targeting debt ratio and shifting the allocation of expenditures away from less efficient toward more growth-enhancing ones, which eventually would regain fiscal space to counter any incoming economic shocks in the future. This can enhance the fiscal transparency and assist in formulating a fiscal policy strategy in Malaysia.

• Journal of the Korean Society of Visualization
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• v.19 no.3
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• pp.92-98
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• 2021

Large Eddy Simulation (LES) has been popularly applied and used in the last several decades to simulate turbulent boundary layer in the numerical domain. A fully developed turbulent boundary layer has also been applied to predict the complicated wake flow behind bluff bodies. In this study we aimed to generate an artificial turbulent boundary layer, which is based on an exponential correlation function, and generates a series of realistic three-dimensional velocity data in two-dimensional inlet section which are correlated both in space and in time. The results suggest its excellent capability for high Reynolds number flows. To make an effective generation, a hexahedral mesh has been used and Cholesky decomposition was applied to possess suitable turbulent statistics such as the randomness and correlation of turbulent flow. As a result, the flow characteristics in the domain and fluctuating pressure near the wall are very close to those of fully developed turbulent boundary layers.