• KIEAE Journal
• /
• v.3 no.2
• /
• pp.59-66
• /
• 2003

To be the design method supporting aesthetic ability of human, CAAD system should essentially recognize architectural form in the same way of human. In this study, visual perception process of human was analyzed to search proper computational method performing similar step of perception of it. Through the analysis of visual perception, vision was separated to low-level vision and high-level vision. Edge detection and neural network were selected to model after low-level vision and high-level vision. The 24 images of building, tree and landscape were processed by edge detection and trained by neural network. And 24 new images were used to test trained network. The test shows that trained network gives right perception result toward each images with low error rate. This study is on the meaning of artificial intelligence in design process rather than on the design automation strategy through artificial intelligence.

• The KIPS Transactions:PartC
• /
• v.15C no.3
• /
• pp.199-204
• /
• 2008

Controller Area Network was developed originally for in-vehicle communication network. But it is now widely used for factory automation because of its properties such as strong noise resistance and high reliabilities. With changing communication environments from peer to peer topology to bus topology, we should check each devices about not only mechanical operations but also electronic or software operations. In this paper, we suggest reliability test environment for CAN based system, which is divided two parts, data correctness and timely delivery.

• The KSFM Journal of Fluid Machinery
• /
• v.3 no.3 s.8
• /
• pp.19-24
• /
• 2000

It is well known that the finite element analysis often has an inaccuracy when it is in conflict with test results. Model updating is concerned with the correction of analytical model by processing records of response from test results. The famous one of the model updating methods is FRF sensitivity method. However, it has demerit that the solution is not unique. So, the neural network is recommended when an unique and exact solution is desired. The generalization ability of radial basis function neural network is used in model updating. As an application model, a cantilever and a rotor system are used. Specially the machined clearance($C_p$) of a journal bearing is updated.

• Journal of Information Processing Systems
• /
• v.8 no.1
• /
• pp.1-20
• /
• 2012

The most important criterion for achieving the maximum performance in a wireless mesh network (WMN) is to limit the interference within the network. For this purpose, especially in a multi-radio network, the best option is to use non-overlapping channels among different radios within the same interference range. Previous works that have considered non-overlapping channels in IEEE 802.11a as the basis for performance optimization, have considered the link quality across all channels to be uniform. In this paper, we present a measurement-based study of link quality across all channels in an IEEE 802.11a-based indoor WMN test bed. Our results show that the generalized assumption of uniform performance across all channels does not hold good in practice for an indoor environment and signal quality depends on the geometry around the mesh routers.

• Korea Journal of Hospital Management
• /
• v.4 no.2
• /
• pp.354-368
• /
• 1999

This research aims to compare between regression and neural network in terms of the predictive ability of the overhead costs in hospitals. For this purpose, this research uses the number of out-patients and complex medical treatments as explaining variables. Thirty-one hospitals were used for the empirical test The test result shows that the regression model has a more predictive ability than the neural network.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.11 no.4
• /
• pp.151-157
• /
• 2003

In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra algorithm of 'NARMAX' form is employed to consider these effects. A numerical example is carried out to verify the developed bushing model.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2004.05a
• /
• pp.1335-1338
• /
• 2004

1990 년대 이후 초고속인터넷 확산으로 인해 전자 상거래 서비스가 급속히 확산되고 있다. SLA란 서비스 제공자와 고객간의 협약으로 서비스 제공자가 서비스 품질을 보증하기 위한 제도이다. 전자 상거래 시스템은 비즈니스 트랜잭션이 처리되어야 하므로 QoS 보장은 매우 중요함에도 불구하고, 전자 상거래를 위한 SLA에 대한 연구는 아직 미진한 상태이다. 본 논문에서는 전자 상거래 서비스의 QoS 측정 지표를 정의한 후 자동화된 처리가 가능한 SLA 관리 프레임워크를 설계하고 서버 환경 장애 발생 시 장애 복구에 대한 처리 흐름을 제안한다.

• Journal of Korea Game Society
• /
• v.9 no.1
• /
• pp.75-84
• /
• 2009

In this paper, we propose a game server using public network library ACE, which has been developed in various fields for a long time. ACE network library has been considered not only in the area of high efficient real-time communication library but also in the area of application development, and it provides various facilities. We logically reorganized the part, which is necessary to develop games, among various functions of ACE and optimized it, and developed real battlenet server using verify the reorganized library. As the method of experiment, the battlenet server and test client were set and interface request test and data electrical transmission test were conducted. As the result of the experiment, the conclusion that it is possible to develop games by using ACE, which is verified network library, has been obtained.

• Transactions of Materials Processing
• /
• v.29 no.5
• /
• pp.272-281
• /
• 2020

As the thickness of mobile communication devices is getting thinner, the size of the internal parts is also getting smaller. Among them, the battery case requires a high-level deep drawing technique because it has a rectangular shape with a large aspect ratio. In this study, the initial blank shape was optimized to minimize earing in a multi-stage deep drawing process using an artificial neural network(ANN). There has been no reported case of applying artificial neural network technology to the initial blank optimal design for a square case with large aspect ratio. The training data for ANN were obtained though simulation, and the model reliability was verified by performing comparative study with regression model using random sample test and goodness-of-fit test. Finally, the optimal design of the initial blank shape was performed through the verified ANN model.

• Journal of the Korea Concrete Institute
• /
• v.17 no.6 s.90
• /
• pp.1075-1084
• /
• 2005

The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network(PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Improved probabilistic neural network was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment (DDA) algorithm. The conventional PNN and the PNN with DDA algorithm(IPNN) were applied to predict the compressive strength of concrete using actual test data of two concrete companies. IPNN showed better results than the conventional PNN in predicting the compressive strength of concrete.