• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.176-183
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• 2006

A novel intelligent anti-collision decision-making supporting system is addressed in this paper. To obtain precise anti-collision information capability, an innovative neurofuzzy network is proposed and applied. A fuzzy set interpretation is incorporated into the network design to handle imprecise information. A neural network architecture is used to train the parameters of the Fuzzy Inference System (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data are obtained by trial manoeuvre. This neurofuzzy network can be considered to be a self-learning system with the ability to learn new information adaptively without forgetting old knowledge. This supporting system can decrease ship operators' burden to deal with bridge data and help them to make a precise anti-collision decision.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.1
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• pp.98-104
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• 2012

In RFID Systems, collisions between multiple tags frequently arise due to simultaneous responses from multiple tags using the same communication channel. Most of anti-collision protocols such as QT regard these collisions as useless cycles, thereby wasting the channel bandwidth. In this paper, we propose a new anti-collision protocol, namely ASP (Adjustable splitting by patterns of collisions) protocol that utilizes the patterns collision for noticeable performance enhancements.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.346-349
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• 2003

For a traveling crane, various control methods such as neural network predictive control and TDOFPID(Two Degree of Freedom Proportional Integral Derivative) are studied. So in this paper, we proposed improved navigation method to reduce transfer time and sway with anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the NNPPID(Neural Network Predictive PID) controller to control the precise move and speedy navigation. The proposed predictive control system is composed of the neural network predictor, TDOFPID controller, and neural network self-tuner. We analyzed ASC(Automated Stacking Crane) system and showed some computer simulations to prove excellence of the proposed controller than other conventional controllers.

• Journal of the Korean Ceramic Society
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• v.44 no.11
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• pp.597-606
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• 2007

With the advent of ubiquitous age, the high quality dielectric materials have been required for the wireless communications available to the millimeterwave as well as microwave frequencies. The utilizable region for the frequency has been expanding to the millimeter-wave region because of the shortage of radio frequency (RF) resources. These high frequencies would be expected for ultra high speed LAN, ETS and car anti-collision system on the intelligent transport system (ITS) and so on. Silicates are good candidates for microwave/millimeterwave dielectrics, because of their low dielectric constant ${\epsilon}_r$ and high quality factor (High Q). Forsterite ($Mg_2SiO_4$) is one of the silicates with low ${\epsilon}_r$ of 6.8 and Q f of 240000 GHz. In this paper, we reviewed following three categories for synthesis of forsterite: (1) Synthesis of high Q forsterite (2) Adjust the temperature coefficient of resonant frequency $TC_f$ (3) Diffusion of $SiO_{4^-}$ and Mg-ions on the formation of forsterite.