• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.831-832
• /
• 2006

In this paper, we introduce a canonical framework of the large-scaled web-based sensor gateway and practically implement it as the environment monitoring system. The system consists of a central management server, up to 250 local embedded subsystems and up to 250 sensor or actuator nodes for each subsystem. The node information is gathered periodically through a well-defined protocol on the sensor network and converted to the web contents and the SNMP MIB objects according to its data type. The MIB objects are well-defined and include system, network, sensor, actuator and alarm specific data classes. Because there is an increasing trend that a large number of sites are willing to adapt unmanned sensing and control, the developed system will play a key role to efficiently manage a large scale sensor networked system such as environment monitoring systems or countermeasure systems against disaster and calamities.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.7 no.3
• /
• pp.97-105
• /
• 2011

With the advancement of network, privacy information as well as confidential information that belongs to government and company are exposed to security incident like spreading viruses or DDoS attack. To prevent these security incident and protect information that belongs to government and company, Security system has developed such as antivirus, firewall, IPS, VPN, and other network security system. Network security systems should be selected based on purpose, usage and cost. Verification for network security product's basic features performed in a variety of ways at home and abroad, but consumers who buy these network security product, just rely on the information presented at companies. Therefore, common user doing self performance evaluation for perform Verification before buying network security product but these verification depends on inaccurate data which based on some user's criteria. On this paper, we designing methodology of network security system performance evaluation focused on Korean using other cases of performance evaluation.

• Proceedings of the IEEK Conference
• /
• 2003.07d
• /
• pp.1251-1254
• /
• 2003

In this paper, Experience Sensitive Cumulative Neural Network (ESCNN) is introduced, which can cumulate the same or similar experiences. As the same or similar training patterns are cumulated in the network, the system recognize more important information in the training patterns. The functions of forgetting less important informations and attending more important informations resided in the training patterns are surveyed and implemented by simulations. The system behaves well under the noisy circumstances due to its forgetting and/or attending properties, even in 50 percents noisy environments. This paper also describes the creation of the generalized patterns for the input training patterns.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.146.1-146
• /
• 2001

The researches of science and engineering need the latest information from internet resources. But searching and filtering processes of appropriate web documents from huge internet resources are very complex as well as having some repeated procedures. In this paper, I propose a Personalized Agent System(PAS), which can filter World Wide Web Documents that the user is interested, such as papers. To do this, PAS uses a modified spreading activation neural network which 1 propose here. PAS observes the user´s local paper database to analyze, adapt and learn the user interests, and the then constructs the user-specified neural network model by the analyzed interests ...

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.3
• /
• pp.35-40
• /
• 2014

Many researches have been conducted to achieve improvement in distributed system that connects multiple computer systems via communication lines. Among others, the load balancing and file migration are considered to have significant impact on the performance of distributed system. The dynamic file migration algorithm common in distributed processing system involved complex calculations of decision function necessary for file migration and required migration of control messages for the performance of decision function. However, the performance of this decision function puts significant computational strain on computer. As one single network is shared by all computers, more computers connected to network means migration of more control messages from file migration, causing the network to trigger bottleneck in distributed processing system. Therefore, it has become imperative to carry out the research that aims to reduce the number of control messages that will be migrated. In this study, the learning automata was used for file migration which would requires only the file reference-related information to determine whether file migration has been made or determine the time and site of file migration, depending on the file conditions, thus reflecting the status of current system well and eliminating the message transfer and additional calculation overhead for file migration. Moreover, mathematical model for file migration was described in order to verify the proposed model. The results from mathematical model and simulation model suggest that the proposed model is well-suited to the distributed system.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.18 no.2
• /
• pp.39-47
• /
• 2010

As vehicles become intelligent for convenience and safety of drivers, in-vehicle networking (IVN) systems are essential components of intelligent vehicles. Recently, the chassis networking system which require increased network capacity and real-time capability is being developed to expand the application area of IVN systems. Also, FlexRay has been developed for the chassis networking system. However, FlexRay needs a complex scheduling method of static segment, which is a barrier for implementing the chassis networking system. Especially, if we want to migrate from CAN network to FlexRay network using CAN message database that was well constructed for the chassis networking system by automotive vendors, a novel scheduling method is necessary to be able to reduce design complexity. This paper presents a node-based scheduling method for FlexRay network system. And, in order to demonstrate the method's feasibility, its performance is evaluated through an experimental testbed.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.1
• /
• pp.79-89
• /
• 1993

This paper deals with a computer aided control of an adjustment process for the complete electronic devices by means of an application of artificial neural network and an implementation of neuro-controller for intelligent control. Multi-layer neural network model is employed as artificial neural network with the learning method of the error back propagation. Information initially available from real plant under control are the initial values of plant output, and the augmented plant input and its corresponding plant output at that time. For the intelligent control of adjustment process utilizing artificial neural network, the neural network emulator (NNE) and the neural network controller(NNC) are developed. The initial weights of each neural network are determined through off line learning for the given product and it is also employed to cope with environments of the another product by on line learning. Computer simulation, as well as the application to the real situation of proposed intelligent control system is investigated.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.39 no.12
• /
• pp.1306-1316
• /
• 1990

A controller using a multilayer neural network is proposed to the dynamic control of a PUMA 560 robot arm. This controller is developed based on an error back-propagation (BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it is used as a commanded feedforward torque generator. A Proportional Derivative (PD) feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the manipulator as well as the PD feedback error torque. No a priori knowledge on system dynamics is needed and this information is rather implicitly stored in the interconnection weights of the neural network. In another experiment, the neural network was trained with the current, past and future positions only without any use of velocity sensors. Form this thim window of position values, BP network implicitly filters out the velocity and acceleration components for each joint. Computer simulation demonstrates such powerful characteristics of the neurocontroller as adaptation to changing environments, robustness to sensor noise, and continuous performance improvement with self-learning.

• Journal of Communications and Networks
• /
• v.14 no.4
• /
• pp.461-466
• /
• 2012

Any future heterogeneous overlay network system must be able to support ubiquitous access across multiple wireless networks. To coordinate these diverse network environments, one challenging task is a call admission decision among different types of network. In this paper, we propose a new call admission control scheme to provide quality of service (QoS) while ensuring system efficiency. Based on the interplay between network structure and dynamics, we estimate the network's QoS level and adjust the service price adaptively with the aim of maximizing the network performance. A simulation shows that the proposed scheme can approximate an optimized solution while ensuring a well-balanced network performance in widely different network environments.

• Korean System Dynamics Review
• /
• v.8 no.2
• /
• pp.5-23
• /
• 2007

According to the system dynamics model of this study, if there is a significant network effect on vehicle operating costs, it is difficult to achieve the shift to AFV even in the long term without a policy intervention because the car market is locked in to the current structure. Network effect can be caused by an increasing return to scale in fuel supply sector as well as in maintenance service sector. It is also related to the fact that the reliability and awareness of consumers on new products increases with the growth of the market share of the new products. There are several possible policy options to break the 'locked in' structure of car market, such as subsidy on vehicle price (capital cost), subsidy on fuel (operating cost) and niche management policy. Combined policy options would be more effective than relying on a single policy option to increase the market share of AFV.