• Journal of Korea Society of Digital Industry and Information Management
• /
• v.4 no.4
• /
• pp.1-8
• /
• 2008

The USN is important in technique, unmanned observation using wireless network camera, detection technique that use intrusion detection sensor. But these encrypted data transmission and processing technique through sensor network, method of the staff's location recognition and arrangement aren't serviced still as a integrated system in facility security industry. This paper proposed that improve facility management, the staff present recognition and system efficiency using RFID, USN and wireless camera.

• Convergence Security Journal
• /
• v.9 no.2
• /
• pp.33-39
• /
• 2009

The problems of current network security system, separated by a single element is checked. To improve this, this thesis is to find vulnerabilities in the network security systems, and network security systems, security equipment, organic to make sure each works is a comprehensive review. Automation also offers a way to check it, it was implemented.

• Proceedings of the KIEE Conference
• /
• 2007.10a
• /
• pp.497-498
• /
• 2007

The most of important thing when we design a Wireless Sensor Network is resources. You have to consider energy efficient operation When you design Wireless Sensor Network. Because Sensor devices have a limited resources. In this paper, we proposed energy efficiency localization technique in Wireless Sensor Network. We used Cell ID technique for location search. This method can reduce power consumption and the network life time will be extension.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1624-1627
• /
• 2005

We proposed a design technique for auto-landing guidance and control system. This technique utilizes linear controller and neural network. Main features of this technique is to use conventional linear controller and compensate for the error coming from the model uncertainties and/or reference model mismatch. In this study, the multi-perceptron neural network with single hidden layer is adopted to compensate for the errors. Glide-slope capture logic for auto-landing guidance and control system is designed in this technique. From the simulation results, it is observed that the responses of velocity and pitch angle to commands are fairly good, which are directly related to control inputs of throttle and elevator, respectively.

• Journal of Korea Multimedia Society
• /
• v.12 no.12
• /
• pp.1769-1777
• /
• 2009

With the advent of the ubiquitous technology age, the progress of network technology has enabled a robust sensor communication, not just in cities, but also in poor surroundings such as deserts, polar regions, or underwater environments. In this paper, we propose a Multiple Acknowledgement (MA) technique to replace the conventional Automatic Repeat request (ARQ) technique. The MA mechanism is to send an Ack to many receivers simultaneously. The CH (master, coordinator) of the unit cluster broadcasts a Beacon frame where Ack information of the previously transmitted data is included. This technique can reduce the number of transmissions and overhead significantly. The proposed technique is a scheme improving the efficiency of an underwater sensor network where the uplink data transmission is the mainstream. The Performance of the ARQ, Block Ack, Pervasive Block Ack and the proposed method were compared with one another and analyzed. The proposed method showed significant performance improvement as compared with the ARQ, BA, and PBA in its channel efficiency.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.6
• /
• pp.524-529
• /
• 2005

In this paper, a novel neural network compensation technique for PD like fuzzy controlled robot manipulators is presented. A standard PD-like fuzzy controller is designed and used as a main controller for controlling robot manipulators. A neural network controller is added to the reference trajectories to modify input error space so that the system is robust to any change in system parameter variations. It forms a neural-fuzzy control structure and used to compensate for nonlinear effects. The ultimate goal is same as that of the neuro-fuzzy control structure, but this proposed technique modifies the input error not the fuzzy rules. The proposed scheme is tested to control the position of the 3 degrees-of-freedom rotary robot manipulator. Performances are compared with that of other neural network control structure known as the feedback error learning structure that compensates at the control input level.

• Proceedings of the IEEK Conference
• /
• 2001.06c
• /
• pp.59-62
• /
• 2001

This paper discusses a data mining technique for time series analysis of traffic data, which provides useful knowledge for network configuration management. Commonly, a network designer must employ a combination of heuristic algorithms and analysis in an interactive manner until satisfactory solutions are obtained. The problem of heuristic algorithms is that it is difficult to deal with large networks and simplification or assumptions have to be made to make them solvable. Various data mining techniques are studied to gain valuable knowledge in large and complex telecommunication networks. In this paper, we propose a traffic pattern association technique among network nodes, which produces association rules of traffic fluctuation patterns among network nodes. Discovered rules can be utilized for improving network topologies and dynamic routing performance.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1961-1965
• /
• 1991

This paper deals with an automatic and precision alignment technique for proximity printing in x-ray lithography, using two pairs of moire gratings, with moire signals from each pair being 180.deg. out of phase with each other. We constructed an automatic and precision alignment experimental system which could measure both transmitted moire signals and reflected moire signals at the same time. The automatic alignment was achieved using transmitted moire signals and also reflected moire signals as a control signal for a stage driver. The alignment position of the system was monitored not only by a control signal but also by a non-control signal. The effect of transmitted and reflected moire signals upon alignment accuracy was discussed. We concluded that the technique using diffracted moire signals is a viable automatic and precision alignment technique.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.9
• /
• pp.1146-1151
• /
• 2018

Recently, researches on the intelligence of electric power facilities have been trying to apply artificial intelligence techniques as computer platforms have improved. In particular, faults occurring in substation should be able to quickly identify possible faults and minimize power fault recovery time. This paper presents fault location technique for 154kV substation using neural network. We constructed a training matrix based on the operating conditions of the circuit breaker and IED to identify the fault location of each component of the target 154kV substation, such as line, bus, and transformer. After performing the training to identify the fault location by the neural network using Weka software, the performance of fault location discrimination of the designed neural network was confirmed.

• 한국가시화정보학회:학술대회논문집
• /
• 2004.12a
• /
• pp.91-110
• /
• 2004

A comprehensive three-dimensional nano-particle tracking technique in micro- and nano-scale spatial resolution using the Total Internal Reflection Fluorescence Microscope (TIRFM) is discussed. Evanescent waves from the total internal reflection of a 488nm argon-ion laser are used to measure the hindered Brownian diffusion within few hundred nanometers of a glass-water interface. 200-nm fluorescence-coated polystyrene spheres are used as tracers to achieve three-dimensional tracking within the near-wall penetration depth. A novel ratiometric imaging technique coupled with a neural network model is used to tag and track the tracer particles. This technique allows for the determination of the relative depth wise locations of the particles. This analysis, to our knowledge is the first such three-dimensional ratiometric nano-particle tracking velocimetry technique to be applied for measuring Brownian diffusion close to the wall.