• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.519-525
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• 2013

The traffic classification is a preliminary and essential step for stable network service provision and efficient network resource management. However, the payload signature-based method has a significant drawback in high-speed network environment that the processing speed is much slower than other method such as header-based and statistical methods. In this paper, We propose the server IP, Port cache-based traffic classification method using application traffic locality to improve the processing speed of traffic classification. The suggested method achieved about 10 folds improvement in processing speed and 10% improvement in completeness over the payload-based classification system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.1945-1956
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• 1994

In this paper, a multiaccess network protocol for high-speed communication is proposed, which enables multimedia sevices with integrating the existing networks. We examine the traffic control mechanisms and configurations for the network architecture and compare with various protocols which are suitable to high speed LAN/MAN and propose an adaptive access control mechanism. ATMR has low channel utilization due to window size reset time, and that MetaRing is very sensitive over the change of traffic load. This suggested protocol, however, has quite a good performance for that situation by adding adaptive parameter condition. This mechanism may introduce a model of small-scaled Broadband Integrated Service Network and be used as an internetworking system for the ATM network.

• Proceedings of the KIEE Conference
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• summer
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• pp.1248-1250
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• 2004

This paper is proposed adaptive fuzzy-neural network controller(NFC) for speed control of surface permanent magnet synchronous motor(SPMSM) drive. The design of this algorithm based on NFC that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive NFC is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.48-54
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• 2002

Gigabit Ethernet was advented as Internet's activation from owing to Internet user and the development of its various application and as inevitability the high-speed network as its demand for more and more the bandwidth by much application using the network. This Gigabit Ethernet makes an alternative plan to solve the request traffic by Internet user, because it holds several merits as providing great capacity with the network in the existing Ethernet environment and as displaying highly efficient ability This paper researches into a concept and characters about Gigabit Ethernet technology and raises the stability and efficiency of Gigabit Ethernet with regard of competing against FDDI technology and using Traffic analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.10
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• pp.871-880
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• 2000

A twin-servo mechanism is used to increase the payload capacity and assembling speed of high precision motion control systems such as semiconductor chip mounters. In this paper, we focus on the modeling of the twin-servo system and propose its network representation. And also, we propose a robust synchronizing motion control algorithm to cancel out the skew motion of the twin-servo system caused by different dynamic characteristics of two driving systems and the vibration generated by high accelerating and decelerating motions. The proposed control algorithm consists of separate feedback motion control algorithms for each driving system and a skew motion compensation algorithm. A robust tracking controller based on internal-loop compensation is proposed as a separate motion controller and its disturbance attenuation property is shown. The skew motion compensation algorithm is also designed to maintain the synchronizing motion during high speed operation, and the stability of the whole closed loop system is proved based on passivity theory. Finally, experimental results are shown to illustrate control performance.

• The KIPS Transactions:PartA
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• v.8A no.2
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• pp.157-166
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• 2001

A simulation package has been developed as an event-driven system that can handle the hardware configuration of STC104 and algorithm proposed in the sister paper of ‘Study on High Speed Routers(II).’After various STC104 topology of meshes, torus, and hypercubes are constructed using up to 512 switches, the performance of each topology has been analyzed under different message generation rate in terms of throughputs, latency, and packet blocking time. Modified multicast algorithms for STC104 have been proposed for STC104 after U-mesh and U-torus in order to overcome the multicasting difficulty because of the point-to-point communication method found in STC104. The performance of the multicast algorithms have been analyzed over meshes and torus configuration. Throughput gets higher in the order of mesh, torus, and hypercube. Throughput difference among topology were distinctive in the zone of high message generation rate. Latency and blocking time increased in the order of hypercube, torus, and mesh. U-mesh and U-torus of software multicast showed similar throughput, however, U-mesh peformed slightly better result. These algorithms showed eight to ten times better results compared to individual message pass for 90 destination nodes. Multi-link environment also showed better performance than single-link environment because multi-link network used the extra links for communication.

• Publications of The Korean Astronomical Society
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• v.28 no.1
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• pp.1-6
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• 2013

Real-time data reduction pipeline for the Korea Microlensing Telescope Network (KMTNet) was developed by Korea Astronomy and Space Science Institute (KASI). The main goal of the data reduction pipeline is to find variable objects and to record their light variation from the large amount of observation data of about 200 GB per night per site. To achieve the goal we adopt three strategic implementations: precision pointing of telescope using the cross correlation correction for target fields, realtime data transferring using kernel-level file handling and high speed network, and segment data processing architecture using the Sun-Grid engine. We tested performance of the pipeline using simulated data which represent the similar circumstance to CTIO (Cerro Tololo Inter-American Observatory), and we have found that it takes about eight hours for whole processing of one-night data. Therefore we conclude that the pipeline works without problem in real-time if the network speed is high enough, e.g., as high as in CTIO.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.7
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• pp.15-25
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• 2011

This proposes an online loss minimization algorithm for series PI(SPI) based interior permanent magnet synchronous motor(IPMSM) drive to yield high efficiency and high dynamic performance over wide speed range. The loss minimization algorithm is developed based on the motor model. In order to minimize the controllable electrical losses of the motor and thereby maximize the operating efficiency, the d-axis armature current is controlled optimally according to the operating speed and load conditions. For vector control purpose, a SPI is used as a speed controller which enables the utilization of the reluctance torque to achieve high dynamic performance as well as to operate the motor over a wide speed range. Also, this paper proposes current control of model reference adaptive fuzzy controller(MFC), and estimation of speed using artificial neural network(ANN) controller. The proposed efficiency optimization control, SPI, MFC, ANN in this paper is applied to IPMSM drive system, the validity of this paper is proved by analyzing response characteristics in variety operating conditions.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.14-23
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• 2014

This paper proposed controlling methods for SDN(Software Defined Network) based multiple radio access technology as the solutions of following two issues which were mainly occurred by explosive increasing of video traffic. The first one is a requirement for traffic off-loading caused by 3rd-party video service providers from the mobile network operator's viewpoint. The other one is a provision of high-speed video contents transmission services with low price. Furthermore, the performance evaluation was also conducted on the real test-bed which is composed of OpenStack cloud and SDN technology such as OpenFlow and Open vSwitch. A virtual machine running on the OpenStack provide a video service and the terminal which is able to use multiple radio access technology supports two 2.4GHz WLANs(Wireless Local Area Network) and three 5GHz WLANs, concurrently. Finally, we can get 820Mbps of the maximum transmission speed by using that five WLAN links for the single service at the same time.

• Design & Manufacturing
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• v.17 no.4
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• pp.72-78
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• 2023

Injection molding is a process widely used in various industries because of its high production speed and ease of mass production during the plastic manufacturing process, and the product is molded by injecting molten plastic into the mold at high speed and pressure. Since process conditions such as resin and mold temperature mutually affect the process and the quality of the molded product, it is difficult to accurately predict quality through mathematical or statistical methods. Recently, studies to predict the quality of injection molded products by applying artificial neural networks, which are known to be very useful for analyzing nonlinear types of problems, are actively underway. In this study, structural optimization of neural networks was conducted by applying multi-task learning techniques according to the characteristics of the input and output parameters of the artificial neural network. A structure reflecting the characteristics of each process step was applied to the input parameters, and a structure reflecting the quality characteristics of the injection molded part was applied to the output parameters using multi-tasking learning. Building an artificial neural network to predict the three qualities (mass, diameter, height) of injection-molded product under six process conditions (melt temperature, mold temperature, injection speed, packing pressure, pacing time, cooling time) and comparing its performance with the existing neural network, we observed enhancements in prediction accuracy for mass, diameter, and height by approximately 69.38%, 24.87%, and 39.87%, respectively.