• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.55 no.9
• /
• pp.459-464
• /
• 2006

The detent force by end-effect has an undesired influence on moving coil type Permanent Magnet Linear Synchronous Motor(PMLSM). So, the reduction of detent force by end-effect is especially required for the improvement of thrust characteristics. In this paper, in order to reduce detent force by end-effect, the auxiliary-teeth is installed at the end part of mover. It is also analyzed by Finite Element Analysis(FEA) and optimized by using neural network. By comparison, the detent force is reduced about 41.4[%] comparing to that of basic model.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2007.04a
• /
• pp.7-12
• /
• 2007

Swirl injector with multi-stage tangential entry was analyzed to suppress high-frequency combustion instability in Liquid Rocket Engines. In order to analyze the effect of swirl injector as an acoustic absorber, swirl injector was regarded as a quarter-wave resonator and it's damping capacity is verified in atmospheric temperature. It has a finite mode of vibration and natural frequencies which can be tuned to the natural frequencies of a model combustion chamber. When the targeted injector for each modes is located at anti-node point, the amplitude of modes was decreased. And when the injector of large diameter is mounted, the split of mode which accompanies the decrease of amplitude appeared. From the experimental data, it is proved that if the location of injector mounted is located at an anti-node position of the targeted modes with proper volume, the amplitude of modes is decreased and the split of modes occurs at anti-node point.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.05a
• /
• pp.1061-1064
• /
• 2006

Optimal design of functionally graded plates is investigated considering stress and critical temperature. Material properties are assumed to be temperature dependent and varied continuously in the thickness direction. The effective material properties are obtained by applying linear rule of mixtures. The 3-D finite element model is adopted using an 18-node solid element to analyze more accurately the variation of material properties and temperature field in the thickness direction. For stress analysis, the tensile stress ratio and compressive stress ratio of the structure under mechanical load are investigated. In the thermo-mechanical buckling analysis, temperature at each node is obtained by solving the steady-state heat transfer problem and Newton-Raphson method is used for material nonlinear analysis. Finally, the optimal design of FGM plates is studied for stress reduction and improving thermo-mechanical buckling behavior, simultaneously.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2005.04a
• /
• pp.151-158
• /
• 2005

For the safety analysis of large structures such as nuclear containment buildings, we conventionally prefer to use analytical approach using finite element method rather than empirical test. Therefor, this paper is mainly focused to develop low-order solid finite element model with the elasto-plastic material model for the safety analysis of nuclear containment building. Drucker-Prager failure criteria in uncracked concrete and maximum tensile stress criteria in cracked concrete are used to model the constitutive behavior of concrete. The concrete material model takes into account the aspects of tensile strain, compression strength reduction of concrete and shear transfer to improve the accuracy of the finite element analysis. Finally, numerical simulation to compare the performance of the developed model with experimental results is employed. The numerical results in this study agree very well with the experimental data.

• Journal of KIISE:Computer Systems and Theory
• /
• v.30 no.7_8
• /
• pp.331-340
• /
• 2003

Low-cost commodity SMP(Symmetric Multiprocessor) is widely used as a node of cluster system. In this paper, we implement and evaluate the performance of SDSM system for SMP clusters. Our SDSM system provides HLRC(Home-based Lazy Release Consistency) memory consistency model. Our protocol utilize shared memory within same SMP node, so that page fetch and message passing through network can be reduced. It is implemented on 8 node of 2-way Pentium-III SMP interconnected with 100Mbps Fast Ethernet, and uses TCP/IP for transport/network layer protocol. The experiment with eight applications shows that our SMP protocol achieves maximum 33% speedup improvement and 13%-52% reduction of page fetch compared with uniprocessor protocol.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.49 no.6
• /
• pp.47-54
• /
• 2007

This paper is on the research of the special character of the dynamic response according to a design of the clamped reinforced concrete slab. In this study, the 20-node solid element has been used to analyze the dynamic characteristics of RC slabs with clamped edges. The elasto-visco plastic model for material non-linearity and the smeared crack model have been adopted in the finite element formulation. The design factor, which affect the dynamic response of the reinforced concrete slab, are the steel layer thickness, steel layer depth, steel layout method, steel layout angle and the slab thickness and span ratio. The main purpose of this study was to find out the dynamic response of the reinforced concrete slab according to above variables. The reduction of deflection/thickness ratio appeared less than 2% when the slab thickness between 20 and 21cm. It is desirable that the slab thickness must be above 20-21cm. The reduction ratio of deflection is appeared greatly when the value of the span/thickness ratio is between 25 and 30. In conclusion, the steel layer depth and thickness had a little effect on deflection of the dynamic response, but had no effect on the steel layout angle.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.10
• /
• pp.397-402
• /
• 2019

Accurately predicting cancer prognosis to provide appropriate treatment strategies for patients is one of the critical challenges in bioinformatics. Many researches have suggested machine learning models to predict patients' outcomes based on their gene expression data. Gene expression data is high-dimensional numerical data containing about 17,000 genes, so traditional researches used feature selection or dimensionality reduction approaches to elevate the performance of prognostic prediction models. These approaches, however, have an issue of making it difficult for the predictive models to grasp any biological interaction between the selected genes because feature selection and model training stages are performed independently. In this paper, we propose a novel two-dimensional image formatting approach for gene expression data to achieve feature selection and prognostic prediction effectively. Node2Vec is exploited to integrate biological interaction network and gene expression data and a convolutional neural network learns the integrated two-dimensional gene expression image data and predicts cancer prognosis. We evaluated our proposed model through double cross-validation and confirmed superior prognostic prediction accuracy to traditional machine learning models based on raw gene expression data. As our proposed approach is able to improve prediction models without loss of information caused by feature selection steps, we expect this will contribute to development of personalized medicine.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.36 no.1
• /
• pp.62-71
• /
• 2008

Swirl injector with adjustable backhole length was analyzed to suppress high-frequency combustion instability in Liquid Rocket Engines. In order to analyze the effect of swirl injector as an acoustic absorber, swirl injector was regarded as a quarter-wave resonator and its damping capacity is verified in atmospheric temperature. Experiments were carried out with copied tubes on air core because the interior air core volume of injector has a direct effect on damping. From the experimental data, it is proved that increasing the number of injectors mounted at each anti-node point can increase acoustic damping effect. Also, when tuned injectors at 1L, 1T, 1L1T modes simultaneously are installed at each anti-node point of model chamber, the damping effect of tuned injectors with multi modes agree well with it of tuned injectors with single mode.

• Journal of Information Processing Systems
• /
• v.5 no.1
• /
• pp.33-40
• /
• 2009

Ever since the network-based malicious code commonly known as a 'worm' surfaced in the early part of the 1980's, its prevalence has grown more and more. The RCS (Random Constant Spreading) worm has become a dominant, malicious virus in recent computer networking circles. The worm retards the availability of an overall network by exhausting resources such as CPU capacity, network peripherals and transfer bandwidth, causing damage to an uninfected system as well as an infected system. The generation and spreading cycle of these worms progress rapidly. The existing studies to counter malicious code have studied the Microscopic Model for detecting worm generation based on some specific pattern or sign of attack, thus preventing its spread by countering the worm directly on detection. However, due to zero-day threat actualization, rapid spreading of the RCS worm and reduction of survival time, securing a security model to ensure the survivability of the network became an urgent problem that the existing solution-oriented security measures did not address. This paper analyzes the recently studied efficient dynamic network. Essentially, this paper suggests a model that dynamically controls the RCS worm using the characteristics of Power-Law and depth distribution of the delivery node, which is commonly seen in preferential growth networks. Moreover, we suggest a model that dynamically controls the spread of the worm using information about the depth distribution of delivery. We also verified via simulation that the load for each node was minimized at an optimal depth to effectively restrain the spread of the worm.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.12
• /
• pp.1652-1662
• /
• 1995

In this paper, a hybrid neural network is proposed to improve the learning ability of a neural network. The union of the characteristics of a Self-Organizing Neural Network model and of multi-layer perceptron model using the backpropagation learning method gives us the advantage of reduction of the learning error and the learning time. In learning process, the proposed hybrid neural network reduces the number of nodes in hidden layers to reduce the calculation time. And this proposed neural network uses the fuzzy feedback values, when it updates the responding region of each node in the hidden layer. To show the effectiveness of this proposed hybrid neural network, the boolean function(XOR, 3Bit Parity) and the solution of inverse kinematics are used. Finally, this proposed hybrid neural network is applied to the visual tracking control of a PUMA560 robot, and the result data is presented.