• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1A
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• pp.134-141
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• 2007

This paper presents a frequency synthesizer(FS) for 5.2GHz/2.4GHz dual band wireless applications which is designed in a standard $0.18{\mu}m$ CMOS1P6M process. The 2.4GHz frequency is obtained from the 5.2GHz output frequency of Voltage Controlled Oscillator (VCO) by using the Switched Capacitor (SC) and the divider-by-2. Power dissipations of the proposed FS and VCO are 25mW and 3.6mW, respectively. The tuning range of VCO is 700MHz and the locking time is $4{\mu}s$. The simulated phase noise of PLL is -101.36dBc/Hz at 200kHz offset frequency from 5.0GHz with SCA circuit on.

• International Journal of Automotive Technology
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• v.8 no.2
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• pp.203-209
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• 2007

As the vehicle electronic control technology quickly grows and becomes more sophisticated, a more efficient means than the traditional in-vehicle driving test is required for the design, testing, and tuning of electronic control units (ECU). For this purpose, the hardware-in-the-loop simulation (HILS) scheme is very promising, since significant portions of actual driving test procedures can be replaced by HIL simulation. The HILS incorporates hardware components in the numerical simulation environment, and this yields results with better credibility than pure numerical simulations can offer. In this study, a HILS system has been developed for ESP (Electronic Stability Program) ECUs. The system consists of the hardware component, which that includes the hydraulic brake mechanism and an ESP ECU, the software component, which virtually implements vehicle dynamics with visualization, and the interface component, which links these two parts together. The validity of HIL simulation is largely contingent upon the accuracy of the vehicle model. To account for this, the HILS system in this research used the commercial software CarSim to generate a detailed full vehicle model, and its parameters were set by using design data, SPMD (Suspension Parameter Measurement Device) data, and data from actual vehicle tests. Using the developed HILS system, performance of a commercial ESP ECU was evaluated for a virtual vehicle under various driving conditions. This HILS system, with its reliability, will be used in various applications that include durability testing, benchmarking and comparison of commercial ECUs, and detection of fault and malfunction of ESP ECUs.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.191-200
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• 2009

Location based services (LBSs) have drawn huge attention as the growing number mobile devices and wireless technology demand more pervasive information access. In LBSs, Constraint nearest neighbor queries are one of the important queries of human to fulfill his desired quickly through wireless technology. We propose new query processing of constrained nearest neighbor query on the air to support mobile clients which demand optimal uses of wireless broadcast channel and using minimum battery power of client. First we proposed NN query processing with constrained region and then explain the novel NN query processing with various types of constraints. We have proposed novel algorithms to support Constrained Nearest Neighbor queries on the air based on Distributed Spatial Index and Bitmap-based Spatial Index.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.282-286
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• 2000

In this paper, magneto-rheological(MR) damper is studied for vibration control of large infra structures under earthquake. Generally, active control devices need a large control force and a high power supply system to reduce the vibration effectively. Large and miss tuned control force may induce the dangerous situation such that the generated large control force acts to amplify the structural vibration. Recently, to overcome the weaknesses of the active control, the semi-active control method is suggested by many researchers. Semi-active control uses the passive control device of which the characteristics can be modified. Control force of the semi-active device is not generated from the actuator with power supply. It is generated as a dynamic reaction force of the device same as in the passive control case, so the control system is inherently stable and robust. Unlike the case of passive control, control force of semi-active control is adjusted depending on the measured response of the structure, so the vibration can be reduced more effectively against various unknown environmental loads. Magneto-rheological(MR) damper is one of the semi-active devices. Dynamic characteristics of the MR material can be changed by applying the magnetic fields. So the control of MR damper needs only small power. Response time of MR to the input voltage is very short, so the high performance control is possible. MR damper has a high force capacity so it is adequate to the vibration control of large infra structure. Because MR damper has a nonlinear property, normal control method used in active control may not be effective. Clipped optimal control, modified bang-bang control etc. have been suggested to MR damper by many researchers. In this study, sliding mode fuzzy control(SMFC) is applied to MR damper. Genetic algorithm is used for the controller tuning. To verify the applicability of MR damper and suggested algorithm, numerical simulation on the aseismic control is carried out. Simulation model is three-story building structure, which was used in the paper of Dyke, et al. The control performance is compared with clipped optimal control. The present results indicate that the SMFC algorithm can reduce the earthquake-induced vibration very effectively.

• Advances in aircraft and spacecraft science
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• v.4 no.2
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• pp.145-167
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• 2017

The presented paper gives an overview of several projects addressing the experimental characterization and control of the buffet phenomenon on 3D turbulent wings in transonic flow conditions. This aerodynamic instability induces strong wall pressure fluctuations and therefore limits flight domain. Consequently, to enlarge the latter but also to provide more flexibility during the design phase, it is interesting to try to delay the buffet onset. This paper summarizes the main investigations leading to the achievement of open and closed-loop buffet control and its experimental demonstration. Several wind tunnel tests campaigns, performed on a 3D half wing/fuselage body, enabled to characterize the buffet aerodynamic instability and to study the efficiency of innovative fluidic control devices designed and manufactured by ONERA. The analysis of the open-loop databases demonstrated the effects on the usual buffet characteristics, especially on the shock location and the separation areas on the wing suction side. Using these results, a closed-loop control methodology based on a quasi-steady approach was defined and several architectures were tested for various parameters such as the input signal, the objective function, the tuning of the feedback gain. All closed-loop methods were implemented on a dSPACE device able to estimate in real time the fluidic actuators command calculated mainly from the unsteady pressure sensors data. The efficiency of delaying the buffet onset or limiting its effects was demonstrated using the quasi-steady closed-loop approach and tested in both research and industrial wind tunnel environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5179-5202
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• 2018

Transmission Control Protocol (TCP) is the most widely used protocol in the cloud data centers today. However, cloud data centers using TCP experience many issues as TCP was designed based on the assumption that it would primarily be used in Wide Area Networks (WANs). One of the major issues with TCP in the cloud data centers is the Incast issue. This issue arises because of the many-to-one communication pattern that commonly exists in the modern cloud data centers. In many-to-one communication pattern, multiple senders simultaneously send data to a single receiver. This causes packet loss at the switch buffer which results in TCP throughput collapse that leads to high Flow Completion Time (FCT). Recently, Software-Defined Networking (SDN) has been used by many researchers to mitigate the Incast issue. In this paper, a detailed survey of various SDN based solutions to the Incast issue is carried out. In this survey, various SDN based solutions are classified into four categories i.e. TCP Receive Window based solutions, Tuning TCP Parameters based solutions, Quick Recovery based solutions and Application Layer based solutions. All the solutions are critically evaluated in terms of their principles, advantages, and shortcomings. Another important feature of this survey is to compare various SDN based solutions with respect to different performance metrics e.g. maximum number of concurrent senders supported, calculation of delay at the controller etc. These performance metrics are important for deployment of any SDN based solution in modern cloud data centers. In addition, future research directions are also discussed in this survey that can be explored to design and develop better SDN based solutions to the Incast issue.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.49-55
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• 2021

Recently, with the development of database, it is possible to store a lot of data generated in finance, security, and networks. These data are being analyzed through classifiers based on machine learning. The main problem at this time is data imbalance. When we train imbalanced data, it may happen that classification accuracy is degraded due to over-fitting with majority class data. To overcome the problem of data imbalance, oversampling strategy that increases the quantity of data of minority class data is widely used. It requires to tuning process about suitable method and parameters for data distribution. To improve the process, In this study, we propose a strategy to explore and optimize oversampling combinations and ratio based on various methods such as synthetic minority oversampling technique and generative adversarial networks through genetic algorithms. After sampling credit card fraud detection which is a representative case of data imbalance, with the proposed strategy and single oversampling strategies, we compare the performance of trained classifiers with each data. As a result, a strategy that is optimized by exploring for ratio of each method with genetic algorithms was superior to previous strategies.

• Earthquakes and Structures
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• v.20 no.3
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• pp.353-364
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• 2021

Natural hazards like earthquakes, high winds, and tsunami are a threat all the time for multi-story structures. The environmental forces cannot be clogged but the structures can be prevented from these natural hazards by using protective systems. The structural control can be achieved by using protective systems like the passive, active, semi-active, and hybrid protective systems; but the semi-active protective system has gained importance because of its adaptability to the active systems and reliability of the passive systems. Therefore, a semi-active protective system for the earthquake forces has been adopted in this work. Magneto-Rheological (MR) damper is used in the structure as a semi-active protective system; which is connected to the current driver and proposed controller. The Proportional Integral Derivative (PID) controller and reliable PID controller are two proposed controllers, which will actuate the MR damper and the desired force is generated to mitigate the vibration of the structural response subjected to the earthquake. PID controller and reliable PID controller are designed and tuned using Ziegler-Nichols tuning technique along with the MR damper simulated in Simulink toolbox and MATLAB to obtain the reduced vibration in a three-story benchmark structure. The earthquake is considered to be uncertain; where the proposed control algorithm works well during the presence of earthquake; this paper considers robustness to provide satisfactory resilience against this uncertainty. In this work, two different earthquakes are considered like El-Centro and Northridge earthquakes for simulation with different controllers. In this paper performances of the structure with and without two controllers are compared and results are discussed.

• Journal of IKEEE
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• v.26 no.3
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• pp.349-354
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• 2022

In thermal power plants, boiler models have been used widely in evaluating logic configurations, performing system tuning and applying control theory, etc. Furthermore, proper plant models are needed to design the accurate controllers. Sometimes, mathematical models can not exactly describe a power plant due to time varying, nonlinearity, uncertainties and complexity of the thermal power plants. In this case, a neural network can be a useful method to estimate such systems. In this paper, the models of boiler steam system in a thermal power plant are developed by using a generalized regression neural network(GRNN). The models of the superheater, reheater, attemperator and drum are designed by using GRNN and the models are trained and validate with the real data obtained in 540[MW] power plant. The validation results showed that proposed models agree with actual outputs of the drum boiler well.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.691-708
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• 2022

As the technology of machine learning and deep learning became common, it began to be applied to research on anomaly(abnormal) detection of industrial control systems. In Korea, the HAI dataset was developed and published to activate artificial intelligence research for abnormal detection of industrial control systems, and an AI contest for detecting industrial control system security threats is being conducted. Most of the anomaly detection studies have been to create a learning model with improved performance through the ensemble model method, which is applied either by modifying the existing deep learning algorithm or by applying it together with other algorithms. In this study, a study was conducted to improve the performance of anomaly detection with a post-processing method that detects abnormal data and corrects the labeling results, rather than the learning algorithm and data pre-processing process. Results It was confirmed that the results were improved by about 10% or more compared to the anomaly detection performance of the existing model.