• The Transactions of the Korean Institute of Electrical Engineers B
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• v.50 no.11
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• pp.575-582
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• 2001

This paper presents a calculating method of switching angle for adaptive switched reluctance motor (SRM) drive of a drill. The operation of the SRM is completely characterized by the flux linked by one phase winding which depends only on the current in that same phase winding and the rotor position. An efficiently adaptive SRM drive is possible on appropriately scheduling the commutation angles with accurate rotor position, supplied current value and speed information. An adaptive SRM drive with reduction torque ripple should be controlled by an optimized phase current control along with rotor position. Therefore, we are suggested a computing method of switching turn-on and off angles for adaptationally SRM operation with varied rotor speed and load. To probe the computing method, we have some simulation and experiment, it is shown a good result that can be computing the optimized switching angles for an electric drill motor.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.731-751
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• 2017

The burgeoning distribution of smartphone web applications based on various mobile environments is increasingly focusing on the performance of mobile applications implemented by JavaScript and HTML5 (Hyper Text Markup Language 5). If application software has a simple functional processing structure, then the problem is benign. However, browser loads are becoming more burdensome as the amount of JavaScript processing continues to increase. Processing time and capacity of the JavaScript in current mobile browsers are limited. As a solution, the Web Worker is designed to implement multi-threading. However, it cannot guarantee the computing ability as a native application on mobile devices, and is not sufficient to improve processing speed. The method proposed in this research overcomes the limitation of resources as a mobile client and guarantees performance by native application software by providing high computing service. It shifts the JavaScript process of a mobile device on to a cloud-based computer server. A performance evaluation experiment revealed the proposed algorithm to be up to 6 times faster in computing speed compared to the existing mobile browser's JavaScript process, and 3 to 6 times faster than Web Worker. In addition, memory usage was also less than the existing technology.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1396-1406
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• 2018

Lane detection is a key function in developing autonomous vehicle technology. In this paper, we propose a lane marker detection algorithm robust to environmental variation targeting low cost embedded computing devices. The proposed algorithm consists of two phases: initialization phase which is slow but has relatively higher accuracy; and the tracking phase which is fast and has the reliable performance in a limited condition. The initialization phase detects lane markers using a set of filters utilizing the various features of lane markers. The tracking phase uses Kalman filter to accelerate the lane marker detection processing. In a tracking phase, we measure the reliability of the detection results and switch it to initialization phase if the confidence level becomes below a threshold. By combining the initialization and tracking phases we achieved high accuracy and acceptable computing speed even under a low cost computing resources in which we cannot use the computing intensive algorithm such as deep learning approach. Experimental results show that the detection accuracy is about 95% on average and the processing speed is about 20 frames per second with Raspberry Pi 3 which is low cost device.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.5
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• pp.604-611
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• 2004

Simulation of three-dimensional turbulent flow with LES and DNS lakes much time and expense with currently available computing resources and requires big computing resources especially for high Reynolds number. The emerging alternative to provide the required computing power and working environment is the Grid computing technology. We developed the CFD code which carries out the parallel computing under the Grid environment. We constructed the Grid environment by connecting different PC-cluster systems located at two different institutes of Pusan National University in Busan and KISTI in Daejeon. The specification of PC-cluster located at two different institutes is not uniform. We run our parallelized computer code under the Grid environment and compared its performance with that obtained using the homogeneous computing environment. When we run our code under the Grid environment, the communication time between different computer nodes takes much larger time than the real computation time. Thus the Grid computing requires the highly fast network speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2682-2700
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• 2023

To cope with the risks of climate change and promote the realization of carbon peaking and carbon neutrality, this paper first comprehensively considers the policy background, technical trends and carbon reduction paths of energy conservation and emission reduction in data center server industry. Second, we propose a computing power carbon efficiency of data center server, and constructs the carbon emission per performance of server (CEPS) model. According to the model, this paper selects the mainstream data center servers for testing. The result shows that with the improvement of server performance, the total carbon emissions are rising. However, the speed of performance improvement is faster than that of carbon emission, hence the relative carbon emission per unit computing power shows a continuous decreasing trend. Moreover, there are some differences between different products, and it is calculated that the carbon emission per unit performance is 20-60KG when the service life of the server is five years.

• 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 the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1102-1108
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• 2020

Mobile edge computing is a technology that can prepare for a new era of cloud computing and compensate for shortcomings by processing data near the edge of the network where data is generated rather than centralized data processing. It is possible to realize a low-latency/high-speed computing service by locating computing power to the edge and analyzing data, rather than in a data center far from computing and processing data. In this article, we develop a virtual mobile edge computing testbed environment where the cloud and edge nodes divide computing tasks from mobile terminals using the EdgeCloudSim simulator. Performance of offloading techniques for distribution of computing tasks from mobile terminals between the central cloud and mobile edge computing nodes is evaluated and analyzed under the virtual mobile edge computing environment. By providing a virtual mobile edge computing environment and offloading capabilities, we intend to provide prior knowledge to industry engineers for building mobile edge computing nodes that collaborate with the cloud.

• Electronics and Telecommunications Trends
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• v.33 no.1
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• pp.20-33
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• 2018

The calculation speed of quantum computing is expected to outperform that of existing supercomputers with regard to certain problems such as secure computing, optimization problems, searching, and quantum chemistry. Many companies such as Google and IBM have been trying to make 50 superconducting qubits, which is expected to demonstrate quantum supremacy and those quantum computers are more advantageous in computing power than classical computers. However, quantum computers are expected to be applicable to solving real-world problems with superior computing power. This will require large scale quantum computing with many more qubits than the current 50 qubits available. To realize this, first, quantum error correction codes are required to be capable of computing within a sufficient amount of time with tolerable accuracy. Next, a compiler is required for the qubits encoded by quantum error correction codes to perform quantum operations. A large-scale quantum computer is therefore predicted to be composed of three essential components: a programming environment, layout mapping of qubits, and quantum processors. These components analyze how many numbers of qubits are needed, how accurate the qubit operations are, and where they are placed and operated. In this paper, recent progress on large-scale quantum computing and the relation of their components will be introduced.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.59-66
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• 2017

Cloud computing has evolved into a core computing infrastructure for the internet that encompasses content, as well as communications, applications and commerce. By providing powerful computing and communications capabilities in the palm of the hand everywhere with a variety of smart devices, mobile applications such as virtual reality, sensing and navigation have emerged and radically changed the patterns people live. The data that is generated is getting bigger. Cloud computing, on the other hand, has problems with system load and speed due to the collection, processing and control of remote data. To solve this problem, fog computing has been proposed in which data is collected and processed at an edge. In this paper, we propose a system that dynamically selects a fog server that acts as a cloud in the edge. It serves as a mediator in the cloud, and provides information on the services and systems belonging to the cloud to the mobile device so that the mobile device can act as a fog. When the role of the fog system is complete, we provide it to the cloud to virtualize the fog. The heterogeneous problem of data of mobile nodes can be solved by using mDBaaS (Mobile DataBase as a Service) and we propose a system design method for this.

• Proceedings of the Optical Society of Korea Conference
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• 1997.08a
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• pp.4-4
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• 1997