• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2004.11a
• /
• pp.265-271
• /
• 2004

The interaction network of protein -protein plays an important role to understand the various biological functions of cells. Currently, the high -throughput experimental techniques (two -dimensional gel electrophoresis, mass spectroscopy, yeast two -hybrid assay) provide us with the vast amount of data for protein-protein interaction at the proteome scale. In order to recognize the role of each protein in their network, the efficient bioinformatical and computational analysis methods are required. We propose a systematic and mathematical method which can analyze the protein -protein interaction network rigorously and enable us to capture the biological and physical essence of a topological character and stability of protein -protein network, and sensitivity of each protein along the biological pathway of their network. We set up a Laplacian matrix of spectral graph theory based on the protein-protein network of yeast proteome, and perform an eigenvalue analysis and apply a perturbation method on a Laplacian matrix, which result in recognizing the center of protein cluster, the identity of hub proteins around it and their relative sensitivities. Identifying the topology of protein -protein network via a Laplacian matrix, we can recognize the important relation between the biological pathway of yeast proteome and the formalism of master equation. The results of our systematic and mathematical analysis agree well with the experimental findings of yeast proteome. The biological function and meaning of each protein cluster can be explained easily. Our rigorous analysis method is robust for understanding various kinds of networks whether they are biological, social, economical...etc

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.6 no.1
• /
• pp.27-33
• /
• 1997

A neural network approach has been developed to determine the depth of a surface breaking crack in a steel plate from ultrasonic backscattering data. The network is trained by the use of feedforward three-layered network together with a back-scattering algorithm for error correction. The signal used for crack insonification is a mode converted 70$^{\circ}$transverse wave. A numerical analysis of back scattered field is carried out based on elastic wave theory, by the use of the boundary element method. The numerical data are calibrated by comparison with experimental data. The numerical analysis provides synthetic data for the training of the network. The training data have been calculated for cracks with specified increments of the crack depth. The performance of the network has been tested on other synthetic data and experimental data which are different from the training data.

• Journal of Korea Society of Industrial Information Systems
• /
• v.2 no.1
• /
• pp.103-123
• /
• 1997

This dissertation provides a theoretic study on the network security in general , the firewall in particular. In fact the firewall has been recognized as a very promising option to obtain the security inthe real work network environment . The dissertation provides a throuth theoretic investigation on the various problems raised in the computer network, and also explores a methodology of the security against IP spoofing. Moreover, it investigates a systematic procddure to make analysis and plans of the firewall configuration . Based on the above investigation and analysis, this dissertation provides two approaches to network security , which address anumber of issuesboth at the network and at applicatino level. At the network level, a new method is proposed which uses packet filtering based on the analysis of the counter plot about the screen router.On the other hand, at the application level, a novel method is explored which employs secureity software. Firewall-1 , on Bastion host. To demonstrate the feasibililty and the effectiveness of the proposed methodologties , a prototype implementation is made The experiment result shows that the screen router employing the proposed anti-IP spoofing method at the network level is effective enough for the system to remain secure without being invaded by any illegal packets entering form external hackers. Meanwhile , at the application level, the proposed software approach employing Firewall-1 is proved to be robust enugh to prevent hackings from the outer point the point protocal connnection . Theoretically, it is not possible to provide complete security to the network system, because the network security involve a number of issues raised form low level network equipments form high level network protocol. The result inthis dissertation provides a very promising solution to network security due to its high efficiency of the implementation and superb protectiveness from a variety of hacking.

• Journal of the Korean Geotechnical Society
• /
• v.15 no.5
• /
• pp.229-240
• /
• 1999

The groundwater flow and grout flow in individual rock joint and jointed rock mass are studied using various methods of analysis such as (i) the finite difference method, (ii) channel network analysis and (iii) joint network analysis. The flow behaviour is investigated in two distinguishable scales of observation: one for a rough joint of a laboratory scale having variable aperture, and the other for field- scale rock masses having three sets of intermittent joints. In the former case, the aperture-dependent channel flow is identified for both water and grout flows. The comparison of the flow rate in a rough joint is made between the finite difference analysis and existing analytical solution. In the latter case, the effects of increasing number of joints on the groundwater inflow into a circular opening of various diameters are analyzed using both the joint network method and Goodman's analytic solution. Comparisons are made between the two methods. The boundary effects in the joint network method are discussed. The inhomogeneity of joint network and its impacts on the groundwater inflow are also discussed.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.9
• /
• pp.2309-2314
• /
• 1997

The study introduces a neural network to predict the bankruptcy of insurance companies. As a method to optimize the network, a genetic algorithm suggests optimal structure and network parameters. The neural network designed by genetic algorithm is compared with discriminant analysis, logistic regression, ID3, and CART. The robust neural network model shows the best performance among those models compared.

• IE interfaces
• /
• v.14 no.1
• /
• pp.30-38
• /
• 2001

Logistics network management has become one of the most important sources of competitive advantage regarding logistics cost and customer service in numerous business segments. Logistics network simulation is a powerful analysis method for designing and planning the logistics network optimally in an integrated way. This paper introduces a logistics network simulator, LONSIM, developed by author. LONSIM deploys a mix of simulation and optimization functions to model and analysis logistics network issues such as facility location, inventory policy, manufacturing policy, transportation mode, warehouse assignment, supplier assignment, order processing priority rule, and vehicle routes. LONSIM is built with AweSim 2.1 and Visual Basic 6.0, and executed in windows environment.

• Journal of Mechanical Science and Technology
• /
• v.16 no.11
• /
• pp.1359-1366
• /
• 2002

The measurement of residual stresses by the hole-drilling method has been used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, we obtained the magnitude of the error due to eccentricity of a hole through the finite element analysis. To predict the magnitude of the error due to eccentricity of a hole in the biaxial residual stress field, it could be learned through the back propagation neural network. The prediction results of the error using the trained neural network showed good agreement with FE analyzed results.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.11 no.3
• /
• pp.58-66
• /
• 2008

In this paper, we have proposed a method and procedure which can find out the unknown network protocol. Although it seems to be difficult to identify the protocol, we can find out the rule in the packet according to the method we have proposed. We have to recognize functions of the system and make the list of events first. Then we capture the network packet whenever the event are occurred. The captured packets are examined by means of the method that is finding repeated parts, changed parts according to the input value, fixed parts and changed parts according to regular rules. Finally we make the test program to verify the protocol. We applied this method and procedure to upgrade Electronic Warfare Test System which is operated by ADD. We have briefly described the redesign of control and analysis software for Electronic Warfare Test System

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.2
• /
• pp.832-854
• /
• 2019

Action recognition has been studied in computer vision field for years. We present an effective approach to recognize actions using a dimension reduction method, which is applied as a crucial step to reduce the dimensionality of feature descriptors after extracting features. We propose to use sparse matrix and randomized kd-tree to modify it and then propose modified Local Fisher Discriminant Analysis (mLFDA) method which greatly reduces the required memory and accelerate the standard Local Fisher Discriminant Analysis. For feature encoding, we propose a useful encoding method called mix encoding which combines Fisher vector encoding and locality-constrained linear coding to get the final video representations. In order to add more meaningful features to the process of action recognition, the convolutional neural network is utilized and combined with mix encoding to produce the deep network feature. Experimental results show that our algorithm is a competitive method on KTH dataset, HMDB51 dataset and UCF101 dataset when combining all these methods.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.394-394
• /
• 2000

This Paper proposes a new nonlinear partial least square method that extends the linear PLS. Proposed nonlinear PLS uses self-organizing feature map as PLS outer relation and multilayer neural network as PLS inner regression method.