• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.17-22
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• 2009

DaVinci processors are popular media processors for implementing embedded multimedia applications. They support dual core architecture: ARM9 core for video I/O handling as well as system management and peripheral handling, and DSP C64+ core for effective digital signal processing. In this paper, we propose our efforts for optimal implementation of object tracking algorithm in DaVinci-based smart camera which is being designed and implemented by our laboratory. The smart camera in this paper is supposed to support object detection, object tracking, object classification and detection of intrusion into surveillance regions and sending the detection event to remote clients using IP protocol. Object tracking algorithm is computationally expensive since it needs to process several procedures such as foreground mask extraction, foreground mask correction, connected component labeling, blob region calculation, object prediction, and etc. which require large amount of computation times. Thus, if it is not implemented optimally in Davinci-based processors, one cannot expect real-time performance of the smart camera.

• Journal of Power Electronics
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• v.10 no.6
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• pp.739-748
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• 2010

The increased integration of fuel cells with power electronics, critical loads, and control systems has prompted recent interest in accurate electrical terminal models of the polymer electrolyte membrane (PEM) fuel cell. Advancement in computing technologies, particularly parallel computation techniques and various real-time simulation tools have allowed the prototyping of novel apparatus to be investigated in a virtual system under a wide range of realistic conditions repeatedly, safely, and economically. This paper builds upon both advancements and provides a means of optimized model construction boosting computation speeds for a fuel cell model on a real-time simulator which can be used in a power hardware-in-the-loop (PHIL) application. Significant improvement in computation time has been achieved. The effectiveness of the proposed model developed on Opal RT's RT-Lab Matlab/Simulink based real-time engineering simulator is verified using experimental results from a Ballard Nexa fuel cell system.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.103-111
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• 2017

The real time scheduling is a key research area in high performance computing and has been a source of challenging problems. A periodic task is an infinite sequence of task instance where each job of a task comes in a regular period. The RMS (Rate Monotonic Scheduling) algorithm has the advantage of a strong theoretical foundation and holds out the promise of reducing the need for exhaustive testing of the scheduling. Many real-time systems built in the past based their scheduling on the Cyclic Executive Model because it produces predictable schedules which facilitate exhaustive testing. In this work we propose hybrid scheduling method which combines features of both of these scheduling algorithms. The original rate monotonic scheduling algorithm didn't consider the uniform sampling tasks in the real time systems. We have enumerated some issues when the RMS is applied to our hybrid scheduling method. We found the scheduling bound for the hard real-time systems which include the uniform sampling tasks. The suggested hybrid scheduling algorithm turns out to have some advantages from the point of view of the real time system designer, and is particularly useful in the context of large critical systems. Our algorithm can be useful for real time system designer who must guarantee the hard real time tasks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.670-686
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• 2017

MapReduce (MRV1), a popular programming model, proposed by Google, has been well used to process large datasets in Hadoop, an open source cloud platform. Its new version MapReduce 2.0 (MRV2) developed along with the emerging of Yarn has achieved obvious improvement over MRV1. However, MRV2 suffers from long finishing time on certain types of jobs. Speculative Execution (SE) has been presented as an approach to the problem above by backing up those delayed jobs from low-performance machines to higher ones. In this paper, an adaptive SE strategy (ASE) is presented in Hadoop-2.6.0. Experiment results have depicted that the ASE duplicates tasks according to real-time resources usage among work nodes in a cloud. In addition, the performance of MRV2 is largely improved using the ASE strategy on job execution time and resource consumption, whether in a multi-job environment.

• Journal of the Optical Society of Korea
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• v.15 no.3
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• pp.264-271
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• 2011

In this paper we examine and compare the computational speeds of three-dimensional (3D) object recognition by use of digital holography based on central unit processing (CPU) and graphic processing unit (GPU) computing. The holographic fringe pattern of a 3D object is obtained using an in-line interferometry setup. The Fourier matched filters are applied to the complex image reconstructed from the holographic fringe pattern using a GPU chip for real-time 3D object recognition. It is shown that the computational speed of the 3D object recognition using GPU computing is significantly faster than that of the CPU computing. To the best of our knowledge, this is the first report on comparisons of the calculation time of the 3D object recognition based on the digital holography with CPU vs GPU computing.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.25-36
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• 2004

This paper proposes and measures the performance of a distributed EIT (Electrical Impedance Tomography) image reconstruction algorithm which has a master-slave structure. The image construction is a computation based application of which the execute time is proportional to the cube of the unknowns. After receiving a specific frame from the master, each computing node extracts the basic elements by executing the first iteration of Kalman Filter in parallel. Then the master merges the basic element lists into one group and then performs the sequential iterations with the reduced number of unknowns. Every computing node has MATLAB functions as well as extended library implemented for the exchange of MATLAB data structure. The master implements another libraries such as threaded multiplication, partitioned inverse, and fast Jacobian to improve the speed of the serial execution part. The parallel library reduces the reconstruction time of image visualization about by half, while the distributed grouping scheme further reduces by about 12 times for the given target object when there are 4 computing nodes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1482-1484
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• 2019

We present a method for transmitting 3D object information in real time in a telepresence system. Three-dimensional object information consists of a large amount of point cloud data, which requires high performance computing power and ultra-wideband network transmission environment to process and transmit such a large amount of data in real time. In this paper, multiple users can transmit object motion and facial expression information in real time even in small network bands by using GANs (Generative Adversarial Networks), a non-supervised learning machine learning algorithm, for real-time transmission of 3D point cloud data. In particular, we propose the creation of an object similar to the original using only the feature information of 3D objects using conditional GANs.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.325-334
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• 2022

Digital twin has the advantages of quality improvement and cost reduction, so it is widely applied to various industries. In this paper, a method to implement the major technologies of digital twin easily and quickly is presented. These include data management and relay servers, real-time monitoring applications including remote control interfaces, and direct connection protocols for video streaming. In addition, an algorithm for controlling a two-wheeled vehicle with a 2D interface is also proposed. The implemented system performs near real-time synchronization between the real environment and the virtual space. The delay time that occurs in remote control of the vehicle in the real environment was compared with the results of applying the proposed delay time reduction method. In addition, in the case of 2D interface-based control, an algorithm that can guarantee the user experience was implemented and applied to the actual environment and verified through experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.587-592
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• 2004

Context-aware computing systems require real-time context reasoning process for context awareness. Context reasoning can be done by comparing input information from sensors with knowledge-base within system. This method is identical with it of rule-based systems. In this paper, we propose hardware rule-based system architecture which can process context reasoning in real-time. Compared to previous architecture, hardware rule-based system architecture can reduce the number of constraints on rule representations and combinations of condition terms in rules. The modified content addressable memory, crossbar switch network and pre-processing module are used for reducing constraints. Using SystemC for description can provide easy modification of system configuration later.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.3
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• pp.186-195
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• 2006

In real-time control systems, the traditional timing analysis based on worst-case response-time(WCRT) is too conservative for the firm and soft real-time control systems, which permit the maximum utilization factor greater than one. We suggested a probabilistic analysis method possible to apply the firm and soft real-time control systems under considering dependency relationship between tasks. The proposed technique determines the deadline miss probability(DMP) of each task from computing the average response-time distribution under a fixed-priority scheduling policy. The method improves the predictable ability forthe average performance and the temporal behavior of real-time control systems.