• Journal of KSNVE
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• v.11 no.1
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• pp.147-155
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• 2001

This paper is concerned with the real-time automatic tuning of the multi-input multi-output positive position feedback controllers for smart structures by the genetic algorithms. The genetic algorithms have proven its effectiveness in searching optimal design parameters without falling into local minimums thus rendering globally optimal solutions. The previous real-time algorithm that tunes a single control parameter is extended to tune more parameters of the MIMO PPF controller. We employ the MIMO PPF controller since it can enhance the damping value of a target mode without affecting other modes if tuned properly. Hence, the traditional positive position feedback controller can be used in adaptive fashion in real time. The final form of the MIMO PPF controller results in the centralized control, thus it involves many parameters. The bounds of the control Parameters are estimated from the theoretical model to guarantee the stability. As in the previous research, the digital MIMO PPF control law is downloaded to the DSP chip and a main program, which runs genetic algorithms in real time, updates the parameters of the controller in real time. The experimental frequency response results show that the MIMO PPF controller tuned by GA gives better performance than the theoretically designed PPF. The time response also shows that the GA tuned MIMO PPF controller can suppress vibrations very well.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.3
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• pp.25-32
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• 2006

Weapon systems composed of several subsystems execute various engagement missions in distributed combat environments in cooperation with a large number of subordinate/adjacent weapon systems as well as higher echelons through tactical data links. Such distributed weapon systems require distributed real-time simulation test beds to integrate and test their operational software, analyze their performance and effects of cooperated engagement, and validate their requirement specifications. These demands present significant challenges in terms of real-time constraints, time synchronization, complexity and development cost of an engagement simulation test bed, thus necessitate the use of high-performance distributed real-time simulation architectures, and modeling and simulation techniques. In this paper, in order to meet these demands, we presented a distributed real-time simulation system based on High Level Architecture(HLA) and Discrete Event System Specification(DEVS). We validated its performance by using it as a test bed for developing the Engagement Control System(ECS) of a surface-to-air missile system. The proposed technique can be employed to design a prototype or model of engagement-level distributed real-time simulation systems.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.39-56
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• 2015

Continuous multi-interval prediction (CMIP) is used to continuously predict the trend of a data stream based on various intervals simultaneously. The continuous integrated hierarchical temporal memory (CIHTM) network performs well in CMIP. However, it is not suitable for CMIP in real-time mode, especially when the number of prediction intervals is increased. In this paper, we propose a real-time integrated hierarchical temporal memory (RIHTM) network by introducing a new type of node, which is called a Zeta1FirstSpecializedQueueNode (ZFSQNode), for the real-time continuous multi-interval prediction (RCMIP) of data streams. The ZFSQNode is constructed by using a specialized circular queue (sQUEUE) together with the modules of original hierarchical temporal memory (HTM) nodes. By using a simple structure and the easy operation characteristics of the sQUEUE, entire prediction operations are integrated in the ZFSQNode. In particular, we employed only one ZFSQNode in each level of the RIHTM network during the prediction stage to generate different intervals of prediction results. The RIHTM network efficiently reduces the response time. Our performance evaluation showed that the RIHTM was satisfied to continuously predict the trend of data streams with multi-intervals in the real-time mode.

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.143-150
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• 2002

Several researches for site-specific weed control have tried to increase accuracy of weed detection with machine vision technique. However, there is a problem which needs substantial time to perform site-specific spraying. Therefore, new technology for real-time precision spraying system is needed. This research was executed to develope the new technology to estimate weed density and size in real time, and to conduct a real-time site-specific spraying. It would effectively reduce herbicide amounts applied for a crop field. The real-time precision spraying system consisted of a Differential Global Positioning System (DGPS) with an error of 2 cm, a machine vision system, a geomagnetic sensor for correction of view point of CCD camera and an automatic sprayer with separately controlled nozzle. The weed density was calculated with comparison between position information and a pre-designed electronic map. The position information was obtained in real time using the DGPS and the machine vision. The electronic map contained a position database of crops automatically constructed when seeding. The developed system was tested on an experimental field of Seoul National University. Success rate of the spraying was about 61%.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.252-265
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• 2021

Cardiac magnetic resonance imaging (MRI) serves as a clinical gold-standard non-invasive imaging technique for the assessment of global and regional cardiac function. Conventional cardiac MRI is limited by the long acquisition time, the need for ECG gating and/or long breathhold, and insufficient spatiotemporal resolution. Real-time cardiac cine MRI refers to high spatiotemporal cardiac imaging using data acquired continuously without synchronization or binning, and therefore of potential interest in overcoming the limitations of conventional cardiac MRI. Novel acquisition and reconstruction techniques must be employed to facilitate real-time cardiac MRI. The goal of this study is to discuss methods that have been developed for real-time cardiac MRI. In particular, we classified existing techniques into two categories based on the use of non-iterative and iterative reconstruction. In addition, we present several research trends in this direction, including deep learning-based image reconstruction and other advanced real-time cardiac MRI strategies that reconstruct images acquired from real-time free-breathing techniques.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.53-60
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• 2023

Recently, the demand and traffic volume for various multimedia contents are rapidly increasing through real-time streaming platforms. In this paper, we predict real-time streaming traffic to improve the quality of service (QoS). Statistical models have been used to predict network traffic. However, since real-time streaming traffic changes dynamically, we used recurrent neural network-based deep learning models rather than a statistical model. Therefore, after the collection and preprocessing for real-time streaming data, we exploit vanilla RNN, LSTM, GRU, Bi-LSTM, and Bi-GRU models to predict real-time streaming traffic. In evaluation, the training time and accuracy of each model are measured and compared.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1181-1184
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• 2005

In this paper, we proposed small scale real-time operating system for embedded system. Real-time system is characterized by the severe consequences that result if logical as well as timing correctness properties of system are not met. On real-time system, real-time operating system allows real-time applications to be designed and expanded easily. Functions can be added without requiring major changes to the software. We design small scale real-time operating system for preemptive kernel, and design kernel component such as multitasking, scheduler, task priority, semaphore, inter-task communication, clock tick timer, ISR(Interrupt Service Routine) mechanism has low interrupt latency.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.110-116
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• 2017

This paper proposed a new real-time parameter tracking algorithm. Unlike the convenience algorithms, the proposed real-time parameter tracking algorithm can estimate parameters through three-phase voltage and electric current without coordination transformation, and does not need information on magnetic flux. Therefore, it can estimate parameters regardless of the change according to operation point and cross-saturation effect. In addition, as the quasi-real-time parameter tracking technique can estimate parameters through the four fundamental arithmetic operations instead of complicated algorithms such as numerical value analysis technique and observer design, it can be applied to low-performance DSP. In this paper, a new real-time parameter tracking algorithm is derived from three phase equation. The validity and usefulness of the proposed inductance estimation technique is verified by simulation and experimental results.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.519-522
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• 1998

The Constructive Battle simulation Model is very important to the recent military training for the substitution of the field training. However, real battlefield systems operate under rea-time conditions, they are inherently distributed, concurrent and dynamic. In order to reflect these properties by the computer-based simulation systems which represent real world processes, we have been developing constructive simulation model for several years. The constructive simulation system is one of the famous real-time system software, nd the one common feature of all real-time systems is defined as the correctness of the system depend not only on the logical result of computation, but also on the time at which the results are produced. Conventionally, scheduling and resource allocation activities which have timing constraints are major problem of real-time computing systems. To overcome these constraints, we elaborated on these issues and developed the simulation system on commercially available hardware and operating system with lock-free resource allocation scheme and rae monotonic scheduling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.849-859
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• 2013

This paper proposes a real-time simulation technique for thin rods undergoing large rotational deformation. Rods are thin objects such as ropes and hairs that can be abstracted as one-dimensional structures. Development of a real-time physical model that can produce visually convincing animation of thin rods has been a challenging problem in computer graphics. We adopt continuum mechanics to formulate the governing equation, and develop a modal warping technique for rods to integrate the governing equation in real-time; This is a novel extension of the previous modal warping techniques developed for solids and shells. Experimental results show that the proposed method runs in real-time even for large meshes and it can simulate large bending and/or twisting deformations.