• Microbiology and Biotechnology Letters
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• v.42 no.1
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• pp.25-31
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• 2014

Fractional precipitation is a simple method for purifying (+)-dihydromyricetin extracted from biomass. However, the fractional precipitation process has been inherently problematic due to the lengthy precipitation time that is required. The fractional precipitation time was shortened and (+)-dihydromyricetin yield was improved by increasing the surface area per working volume (S/V) of the reacting solution through the addition of a cation exchange resin (Amberlite 200, Amberlite IR 120Na, Amberlite IR 120H, or Amberlite IRC 50). Most of the (+)-dihydromyricetin (>90%) could be obtained after about 16 h of fractional precipitation using Amberlite 200. Since high-purity (+)-dihydromyricetin can be obtained at a high yield and the precipitation time can be reduced by increasing the surface area available for precipitation, this improved method is expected to minimize solvent usage and the size and complexity of the high performance liquid chromatography operation required for (+)-dihydromyricetin purification.

• Journal of IKEEE
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• v.19 no.1
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• pp.45-51
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• 2015

Recently, as WPAN (Wireless Personal Area Network) becomes the necessary feature in IoT (Internet of Things) devices, the importance of data security also hugely increases. In this paper, we present the low-complexity 128-bit AES-$CCM^*$ hardware IP for IEEE 802.15.4 standard. For low-cost and low-power implementation which is essentially required in IoT devices, we propose two optimization methods. First, the folded AES(Advanced Encryption Standard) processing core with 8-bit datapath is presented where composite field arithmetic is adopted for reduced hardware complexity. In addition, to support $CCM^*$ mode defined in IEEE 802.15.4, we propose the mode-toggling architecture which requires less hardware resources and processing time. With the proposed methods, the gate count of the proposed AES-$CCM^*$ IP can be lowered up to 57% compared to the conventional architecture.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.8
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• pp.818-822
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• 2008

The purpose of this study is to develop realistic painting simulation in real-time as well as to represent the thickness of the deposited paint on the surface. The Gaussian model is used for a painting deposition model to calculate the thickness of paints. For a painting simulation, rather than implementing particle systems, we propose a new heuristic algorithm for painting process based on a few number of rays. After we find the collision points of the rays with an environment, we compute the painted area using flood-fill searching method on the texture map and visualize paint effects. We analyzed time complexity of our method to verify that our system is suitable for real-time VR applications.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.91-100
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• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes a service prediction-based job scheduling model and present its scheduling algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts the next processing time of each processing component and distributes a job to a processing component with minimum processing time. This paper implements the job scheduling model on the DEVS modeling and simulation environment and evaluates its efficiency and reliability. Empirical results, which are compared to conventional scheduling policies, show the usefulness of service prediction-based job scheduling.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.29-33
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• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes the service prediction-based job scheduling model and present its algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts a processing time of each processing component and distributes a job to processing component with minimum processing time. This paper implements the job scheduling model on the DEVSJAVA modeling and simulation environment and simulates with a case study to evaluate its efficiency and reliability Empirical results, which are compared to the conventional scheduling policies such as the random scheduling and the round-robin scheduling, show the usefulness of service prediction-based job scheduling.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.3
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• pp.441-450
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• 2022

The introduction of autonomous underwater gliders (AUGs) specifically addresses the reduction of operational costs that were previously prohibited with conventional autonomous underwater vehicles (AUVs) using a "scaling-down" design philosophy by utilizing the characteristics of autonomous drifters to far extend operation duration and coverage. Long-duration, wide-area missions raise the cost and complexity of in-water testing for novel approaches to autonomous mission planning. As a result, a simulator that supports the rapid design, development, and testing of autonomy solutions across a wide range using software-in-the-loop simulation at faster-than-real-time speeds becomes critical. This paper describes a faster-than-real-time AUG simulator that can support high-resolution bathymetry for a wide variety of ocean environments, including ocean currents, various sensors, and vehicle dynamics. On top of the de facto standard ROS-Gazebo framework and open-sourced underwater vehicle simulation packages, features specific to AUGs for ocean mapping are developed. For vehicle dynamics, the next-generation hybrid autonomous underwater gliders (Hybrid-AUGs) operate with both the buoyancy engine and the thrusters to improve navigation for bathymetry mappings, e.g., line trajectory, are is implemented since because it can also describe conventional AUGs without the thrusters. The simulation results are validated with experiments while operating at 120 times faster than the real-time.

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.54-62
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• 2000

Adaptive filtering method is one of signal processing area which is frequently used in the case of statistical characteristic change in time-varing situation. The performance of adaptive filter is usually evaluated with complexity of its structure, convergence speed and misadjustment. The structure of adaptive filter must be simple and its speed of adaptation must be fast for real-time implementation. In this paper, we propose chirp discrete cosine transform (CDCT), which has the characteristics of CZT (chrip z-transform) and DCT (discrete cosine transform), and then CDCTLMS (chirp discrete cosine transform LMS) using the above mentioned algorithm for the improvement of its speed of adaptation. Using loaming curve, we prove that the proposed method is superior to the conventional US (normalized LMS) algorithm and DCTLMS (discrete cosine transform LMS) algorithm. Also, we show the real application for the ultrasonic signal processing.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.592-595
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• 2009

In this paper, we propose a face detection technique for still pictures which sequentially uses a skin-color model and a support vector machine (SVM). SVM is a learning algorithm for solving the classification problem. Some studies on face detection have reported superior results of SVM over neural networks. The SVM method searches for a face in a picture while changing the size of the window. The detection accuracy and the processing time of SVM vary largely depending on the complexity of the background of the picture or the size of the face. Therefore, we apply a face candidate area detection method using a skin-color model as a preprocessing technique. We compared the method using SVM alone with that of the proposed method in respect to face detection accuracy and processing time. As a result, the proposed method showed improved processing time while maintaining a high recognition rate.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.5
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• pp.313-318
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• 2014

Recently, Ethernet-based Diagnostic Over Internet Protocol (DoIP) was applied to automotive systems, and in-vehicle gateways have been introduced to integrate Ethernet with traditional in-vehicle networks, such as the local interconnect network (LIN), controller area network (CAN) and FlexRay. The introduction of in-vehicle gateways and of Ethernet based diagnostic protocols not only decreases the complexity of the networks, but also reduces the update time for ECU software reprogramming while enabling the use of a range of services, including remote diagnostics. In this paper, a diagnostic gateway was implement for an automotive system, and the performance measurements are presented. In addition, a range of applications provided by the diagnostic gateway are proposed.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.418-424
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• 2005

The complexity of the biological system/biological systems has been fascinating and challenging for a long time. With the advent of mathematical tools with various omics technology, systems biology was born and is already ubiquitous in every area of biology and biotechnology. Microalgal biotechnology is no exception in this new trend. As tens of microalgal genomes become publicly available on the Internet, vast amounts of data from genomics, transcriptomics, and proteomics are reported everyday. Though there has not yet been enough data gathered on microalgal metabolomics, the in silica models for relatively simple cyanobacteria or for organelles, such as chloroplasts, will appear presently. With the help of systems biology, a more in-depth understanding of microalgae will be possible. Consequently, most industrially-interested microalgae can be metabolically redesigned/reconfigured as cell factories. Microalgae will be served as the hosts in white biotechnology.