• Journal of the Semiconductor & Display Technology
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• v.7 no.1
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• pp.11-16
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• 2008

Confocal scanning microscopy is a widely used technique for three dimensional measurements because it is characterized by high resolution, high SNR and depth discrimination. Generally an image is generated by moving one optical probe that satisfies the confocal condition on the specimen. Measurement speed is limited by movement speed of the optical probe; scanning speed. To improve measurement speed we increase the number of optical probes. Specimen region to scan is divided by optical probes. Multi-point information each optical probe points to can be obtained simultaneously. Therefore image acquisition speed is increased in proportion to the number of optical probes. And multiple optical probes from red, green and blue laser sources can be used for color imaging and image quality, i.e., contrast, is improved by adding color information by this way. To conclude, this technique contributes to the improvement of measurement speed and image quality.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1623-1628
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• 2004

In the 3-dimensional cyclic Lotka-Volterra equations, we show the solution on the invariant hyperplane. In addition, we show the existence of the invariant hyperplane by the center manifold theorem under the some conditions. With this result, we can lead the hyperplane of the n-dimensional cyclic Lotka-Volterra equaions. In other section, we study the 3- or 4-dimensional Hamiltonian Lotka-Volterra equations which satisfy the Jacobi identity. We analyze the solution of the Hamiltonian Lotka- Volterra equations with the functions called the split Liapunov functions by [4], [5] since they provide the Liapunov functions for each region separated by the invariant hyperplane. In the cyclic Lotka-Volterra equations, the role of the Liapunov functions is the same in the odd and even dimension. However, in the Hamiltonian Lotka-Volterra equations, we can show the difference of the role of the Liapunov function between the odd and the even dimension by the numerical calculation. In this paper, we regard the invariant hyperplane as the important item to analyze the motion of Lotka-Volterra equations and occur the chaotic orbit. Furtheremore, an example of the asymptoticaly stable and stable solution of the 3-dimensional cyclic Lotka-Volterra equations, 3- and 4-dimensional Hamiltonian equations are shown.

• Advances in aircraft and spacecraft science
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• v.2 no.1
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• pp.77-94
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• 2015

The paper focuses on the integration of a non-linear one-dimensional model of Synthetic Jet (SJ) actuator in a well-assessed numerical simulation method for turbulent compressible flows. The computational approach is intended to the implementation of a numerical tool suited for flow control simulations with affordable CPU resources. A strong compromise is sought between the use of boundary conditions or zero-dimensional models and the full simulation of the actuator cavity, in view of long-term simulation with multiple synthetic jet actuators. The model is integrated in a multi-domain numerical procedure where the controlled flow field is simulated by a standard CFD method for compressible RANS equations, while flow inside the actuator is reduced to a one-dimensional duct flow with a moving piston. The non-linear matching between the two systems, which ensures conservation of the mass, momentum and energy is explained. The numerical method is successfully tested against three typical test cases: the jet in quiescent air, the SJ in cross flow and the flow control on the NACA0015 airfoil.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1231-1242
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• 2019

This paper presents a two-dimensional attention-based long short-memory (2D-ALSTM) model for stock index prediction, incorporating input attention and temporal attention mechanisms for weighting of important stocks and important time steps, respectively. The proposed model is designed to overcome the long-term dependency, stock selection, and stock volatility delay problems that negatively affect existing models. The 2D-ALSTM model is validated in a comparative experiment involving the two attention-based models multi-input LSTM (MI-LSTM) and dual-stage attention-based recurrent neural network (DARNN), with real stock data being used for training and evaluation. The model achieves superior performance compared to MI-LSTM and DARNN for stock index prediction on a KOSPI100 dataset.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1833-1848
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• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.6 s.261
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• pp.635-643
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• 2007

As many engineers and technicians are involved in the design process of large scale and/or complex products, there are a lot of miss matches and interferences due to designers' faults and several kinds of CAD systems. Recently, CAD systems are applied to verify and check the assembly process. Digital Mock-Up(DMU) system, a tool to build a virtual mock-up in the design stage, has been used to prevent the interferences and miss matches during precision design processes. Using the virtual assembly tool, engineers are able to design precision and interference free parts without physical mock-ups. Instead of a single CAD source, several CAD systems are used to design a complex product. Several organizations are involved in the distributed design environment for heterogeneous multi-CAD assembly. XML and the lightweight CAD file are proposed for the multi-CAD assembly. XML data contains hierarchy of the heterogenenous multi-CAD assembly. STEP PDM schema and STEP ISO 10303-28 formations are applied to construct the XML data. The lightweight CAD file produced from various CAD files through ACIS kernel and InterOp not only contains mesn, B-Rep and topological data, but also is used to visualize CAD data and to verify dimensions. Developed system is executed on the desktop computers. It does not require commercial CAD systems to visualize 3D assembly data. Real-time interference and fitness checks, dimensional verification, and design and assembly verification are performed on the developed system. Assembly of heterogeneous models for a car is conducted to verify the effectiveness of the developed DMU system on the Internet.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.434-443
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• 2007

Presently, the exploration of an unknown environment is an important task for thee new generation of mobile service robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems. This paper presents a technique for localization of a mobile robot using fusion data of multi-ultrasonic sensors and vision system. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, comers and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD(Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a vision-based environment recognition, phisically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.

• Macromolecular Research
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• v.17 no.3
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• pp.192-196
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• 2009

Recently, the multi-screening of target materials has been made possible by the development of the surface plasmon resonance (SPR) imaging method. To adapt this method to biochemical analysis, the multi-patterning technology of protein microarrays is required. Among the different methods of fabricating protein microarrays, the microfluidic platform was selected due to its various advantages over other techniques. Microfluidic devices were designed and fabricated with polydimethylsiloxane (PDMS) by the replica molding method. These devices were designed to operate using only capillary force, without the need for additional flow control equipment. With these devices, multiple protein-patterned sensor surfaces were made, to support the two-dimensional detection of various protein-protein interactions with SPR. The fabrication technique of protein microarrays can be applied not only to SPR imaging, but also to other biochemical analyses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.12
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• pp.2374-2391
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• 2011

A variety of reconstruction methods has been developed to convert a set of scattered points generated from real models into explicit forms, such as polygonal meshes, parametric or implicit surfaces. In this paper, we present a method to construct multi-scale implicit surfaces from scattered points using multiscale kernels based on kernel and multi-resolution analysis theories. Our approach differs from other methods in that multi-scale reconstruction can be done without additional manipulation on input data, calculated functions support level of detail representation, and it can be naturally expanded for n-dimensional data. The method also works well with point-sets that are noisy or not uniformly distributed. We show features and performances of the proposed method via experimental results for various data sets.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.82-91
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• 2009

Routing (or path selection) is one of the key issues of multi-hop relay networks such as the IEEE 802.16j. Moreover, the allocation of appropriate resource such as bandwidth should not only be made in accordance with the paths selected, but the utilization of radio resource of an entire cell should also be maximized. Due to this interdependency between the problems of resource allocation and routing, it is desired these two problems are addressed simultaneously. In this paper, we propose a joint resource allocation and routing scheme for an OFDMA-based multi-hop cellular system. This scheme uses a polynomial time heuristic algorithm called Multi-Dimensional Multi-choice Knapsack Problem (MMKP) in order to find an approximate solution maximizing the total downlink throughput. In the simulation results, we show that the proposed scheme finds a sub-optimal solution which is superior to a link quality-based routing scheme, but slightly worse than the optimal solution.