• The Pure and Applied Mathematics
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• v.31 no.2
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• pp.235-249
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• 2024

We obtain a structured class of frames in separable Hilbert spaces which are generalizations of Gabor frames in L²(ℝ) in their construction aspects. For this, the concept of Gabor type unitary systems in [13] is generalized by considering a system of invertible operators in place of unitary systems. Pseudo Gabor like frames and pseudo Gabor frames are introduced and the corresponding frame operators are characterized.

• Journal of the Korean Mathematical Society
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• v.14 no.2
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• pp.159-165
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• 1978

• IT SoC Magazine
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• s.4
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• pp.34-35
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• 2004

• 시스템엔지니어링워크숍
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• s.7
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• pp.14-18
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• 2006

• Korean Journal of Ecology and Environment
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• v.41 no.4
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• pp.530-540
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• 2008

The temporal and spatial variations of size-structured phytoplankton dynamics in Youngsan Lake were investigated to explore potential mechanims controlling the dynamics in the Youngsan Lake. Field data were collected monthly from February to October, 2003 at 6 stations along the axis of Youngsan Lake. In this study, phytoplankton (chlorophyll $\alpha$) were categorized into three size classes: micro-size ($>20{\mu}m$), nano-size ($2{\sim}20{\mu}m$) and pico-size ($<20{\mu}m$). Water temperature, light attenuation coefficients, PAR (photosynthetically active radiation) and suspended solids were measured to analyze relationship between physical-chemical properties and size structure of phytoplankton. Phytoplankton blooms developed during March, July and October in the upper region of the main stem whereas small-scaled spring bloom was observed in the lower region. The scales of phytoplankton blooms were higher in the upper regions than the lower region and blooms were predominated by micro-size class in upper region but predominated by nano-size class in lower region. Growth of size-structured phytoplankton appeared to be controlled by rather light availability than temperature-dependant metabolisms in the system. Phytoplankton growth may be also supported by ambient nutrients available in the water column from analyses of chlorophyll $\alpha$ vs. nutrient concentrations including nitrite+nitrate and orthophosphate. Growth of nano-sized phytoplankton alone appeared to be supported by orthophosphate as well as nitrite+nitrate indicating that response of phytoplankton to nutrient inputs may be size-dependent.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.151-155
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• 2005

Recently, systems biology has been increasingly applied to gain insights into the complexity of living organisms. Many inaccessible biological information and hidden evidences fur example flux distribution of the metabolites are simply revealed by investigation of artificial cell behaviors. Most bio-models are models of single cell organisms that cannot handle the multi-cellular organisms like plants. Herein, a structured and multi-cellular model of potato was developed to comprehend the root starch biosynthesis. On the basis of simplest plant cell biology, a potato structured model on the platform of Berkley Madonna was divided into three parts: photosynthetic (leaf), non-photosynthetic (tuber) and transportation (phloem) cells. The model of starch biosynthesis begins with the fixation of CO$_2$ from atmosphere to the Calvin cycle. Passing through a series of reactions, triose phosphate from Calvin cycle is converted to sucrose which is transported to sink cells and is eventually formed the amylose and amylopectin (starch constituents). After validating the model with data from a number of literatures, the results show that the structured model is a good representative of the studied system. The result of triose phosphate (DHAP and GAP) elevation due to lessening the aldolase activity is an illustration of the validation. Furthermore, the representative model was used to gain more understanding of starch production process such as the effect of CO$_2$ uptake on qualitative and quantitative aspects of starch biosynthesis.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.2
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• pp.77-82
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• 2015

Big Data technology has been attracted much attention in aspect of fast data processing. Research of practicing Big Data technology is also ongoing to process large-scale structured data much faster in Relatioinal Database(RDB). Although there are lots of studies about measuring analyzing performance, studies about structured data loading performance, prior step of analyzing, is very rare. Thus, in this study, structured data in RDB is tested the performance that loads distributed processing platform Hadoop using Apache sqoop. Also in order to analyze the influence factors of data loading, it is tested repeatedly with different options of data loading and compared with data loading performance among RDB based servers. Although data loading performance of Apache Sqoop in test environment was low, but in large-scale Hadoop cluster environment we can expect much better performance because of getting more hardware resources. It is expected to be based on study improving data loading performance and whole steps of performance analyzing structured data in Hadoop Platform.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.297-306
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• 2002

This paper handles the design and implementation of the system for transforming the XML document bated on XML Schema being different in syntax but similar in logic, with using structured differences analysis. In the system, the merge data is generated from the source and destination documents by utilizing data registry and structured differences analysis, and then XML document is generated from the generated merge data. The XML document transformation system is designed that transformation process to the present application system from the different application system gains advantage in the aspect of time, cost, and reliability. The implementation environment of the system is that it is run on IBM compatible PC and it is developed using the software of visual basic 6.0 with the Platform of Windows 2000.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.381-390
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• 2010

This paper describes a procedure of the map-based localization for mobile robots by using a sensor fusion technique in structured environments. A combination of various sensors with different characteristics and limited sensibility has advantages in view of complementariness and cooperation to obtain better information on the environment. In this paper, for robust self-localization of a mobile robot with a monocular camera and a laser structured light sensor, environment information acquired from two sensors is combined and fused by a Bayesian sensor fusion technique based on the probabilistic reliability function of each sensor predefined through experiments. For the self-localization using the monocular vision, the robot utilizes image features consisting of vertical edge lines from input camera images, and they are used as natural landmark points in self-localization process. However, in case of using the laser structured light sensor, it utilizes geometrical features composed of corners and planes as natural landmark shapes during this process, which are extracted from range data at a constant height from the navigation floor. Although only each feature group of them is sometimes useful to localize mobile robots, all features from the two sensors are simultaneously used and fused in term of information for reliable localization under various environment conditions. To verify the advantage of using multi-sensor fusion, a series of experiments are performed, and experimental results are discussed in detail.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.945-953
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• 2012

A depth map can be obtained by projecting/capturing patterns of stripes using a projector-camera system and analyzing the geometric relationship between the projected patterns and the captured patterns. This is usually called structured light technique. In this paper, we propose a new multi-threading scheme for accelerating a conventional structured light technique. On CPUs and GPUs, multi-threading can be implemented by using OpenMP and CUDA, respectively. However, the problem is that their performance changes according to the computational conditions of partial processes of a structured light technique. In other words, OpenMP (using multiple CPUs) outperformed CUDA (using multiple GPUs) in partial processes such as pattern decoding and depth estimation. In contrast, CUDA outperformed OpenMP in partial processes such as rectification and pattern segmentation. Therefore, we carefully analyze the computational conditions where each outperforms the other and do use the better one in the related conditions. As a result, the proposed method can estimate a depth map in a speed of over 25 fps on $1280{\times}800$ images.