• Journal of KIISE:Computer Systems and Theory
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• v.36 no.4
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• pp.247-258
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• 2009

Distributed file systems running on a cluster of inexpensive commodity hardware are being recognized as an effective solution to support the explosive growth of storage demand in large-scale Internet service companies. This paper presents the design and implementation of BeanFS, a distributed file system for large-scale e-mail services. BeanFS is adapted to e-mail services as follows. First, the volume-based replication scheme alleviates the metadata management overhead of the central metadata server in dealing with a very large number of small files. Second, BeanFS employs a light-weighted consistency maintenance protocol tailored to simple access patterns of e-mail message. Third, transient and permanent failures are treated separately and recovering from transient failures is done quickly and has less overhead.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.11
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• pp.658-672
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• 2004

Multimedia applications are required to process the huge amount of data at high speed in real time. The memory reference instructions such as loads and stores are the main factor which limits the high speed execution of processor. To enhance the memory reference speed, cache prefetch schemes are used so as to reduce the cache miss ratio and the total execution time by previously fetching data into cache that is expected to be referenced in the future. In this study, we present an advanced data cache prefetching scheme that improves the conventional RPT (reference prediction table) based scheme. We considers the cache line size in calculation of the address stride referenced by the same instruction, and enhances the prefetching algorithm so that the effect of prefetching could be maintained even if an irregular address stride is inserted into the series of uniform strides. According to experiment results on multimedia benchmark programs, the cache miss ratio has been improved 29% in average compared to the conventional RPT scheme while the bus usage has increased relatively small amount (0.03%).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.856-859
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• 2010

WSN is composed of a lot of small sensors with the limited hardware resources. In WSN, at the initial stage, sensor nodes are randomly deployed over the region of interest, and self-configure the clustered networks by grouping a bunch of sensor nodes and selecting a cluster header among them. Specially, in Mobile-WSN environment, in which the administrator's intervention is restricted, the self-configuration capability is essential to establish a power-conservative Mobile-WSN which provides broad sensing coverage and communication coverage. In this paper, we propose a self-configuration routing protocol for Mobile-WSN, which consists of step-wise novel protocols for initial deployment, effective joining and removal of sensor nodes, which result in reducing overall power consumption, and extending the lifetime of network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.581-583
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• 2017

Elliptic curve cyptography is relatively a current cryptography based on point arithmetic on elliptic curves and the Elliptic Curve Discrete Logarithm Problem (ECDLP). This discrete logarithm problems enables perfect forward secrecy which helps to easily generate key and almost impossible to revert the generation which is a great feature for privacy and protection. In this paper, we provide a lightweight Elliptic Curve Diffie-Hellman (ECDH) Key exchange generator that creates a 163 bit long shared key that can be used in an Elliptic Curve Integrated Encryption Scheme (ECIES) as well as for key agreement. The algorithm uses a fast multiplication algorithm that is small in size and also implements the extended euclidean algorithm. This proposed architecture was designed using verilog HDL, synthesized with the vivado ISE 2016.3 and was implemented on the virtex-7 FPGA board.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.1121-1129
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• 1988

An economic and efficient system for measuring drop sizes was developed. Pattern recognition technique was used with conventional oil-bath sampling and photographic method. The system was designed to measure and count relatively large number of drops in a very short time, and also to filter out abnormal images such as drops in contact or overlap as well as odd-shaped foreign materials. In this measuring system, most important error originates from the process of converting the original image to the binary image. If the photograph contains a large number of spray drops, the relative size of the pixel to the drops is not infinitesimally small; thus the proper choice of threshold level to convert the original image to the binary image becomes very important. In present case, most of the images lay in one of the two separate bands of brightness level and the arithmetic mean of the most popular brightness levels from each band was chosen as the threshold level. Present image processing system reduces the subjective error by the observers in counting and measuring drops and turns out to be substantially effective. The processing time can be further reduced by improving the hardware system concerned with the digital image coding.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.4
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• pp.9-16
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• 2020

Pronunciation recognition systems that use only video information and ignore voice information can be applied to various customized services. In this paper, we develop a system that applies a Bayesian classifier to distinguish Korean vowels via lip shapes in images. We extract feature vectors from the lip shapes of facial images and apply them to the designed machine learning model. Our experiments show that the system's recognition rate is 94% for the pronunciation of 'A', and the system's average recognition rate is approximately 84%, which is higher than that of the CNN tested for comparison. Our results show that our Bayesian classification method with feature values from lip region landmarks is efficient on a small training set. Therefore, it can be used for application development on limited hardware such as mobile devices.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.547-557
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• 2009

LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.101-107
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• 2019

This paper proposes a method for detecting faults in conveyor systems used for transportation of raw materials needed in the thermal power plant and cement industries. A small drone was designed in consideration of the difficulty in accessing the industrial site and the need to use it in wide industrial site. In order to apply the system to the embedded microprocessor, hardware and algorithms considering limited memory and execution time have been proposed. At this time, the failure determination method measures the peak frequency through the measurement, detects the continuity of the high frequency, and performs the failure diagnosis with the high frequency components of noise. The proposed system consists of experimental environment based on the data obtained from the actual thermal power plant, and it is confirmed that the proposed system is useful by conducting virtual environment experiments with the drone designed system. In the future, further research is needed to improve the drone's flight stability and to improve discrimination performance by using more intelligent methods of fault frequency.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.103-111
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• 2019

The IoT-driven large-scaled systems consist of connected things with on-chip executable embedded software. These light-weighted embedded things have limited hardware space, especially small size of on-chip flash memory. In addition, on-chip embedded software in flash memory is not easy to update in runtime to equip with latest services in IoT-driven applications. It is becoming important to develop light-weighted IoT devices with various software in the limited on-chip flash memory. The remote instruction execution in cloud via IoT connectivity enables to provide high performance software execution with unlimited software instruction in cloud and low-power streaming of instruction execution in IoT edge devices. In this paper, we propose a Cloud-IoT asymmetric structure for providing high performance instruction execution in cloud, still low power code executable thing in light-weighted IoT edge environment using remote instruction execution. We propose a simulated approach to determine efficient partitioning of software runtime in cloud and IoT edge. We evaluated the instruction cloudification using remote instruction by determining the execution time by the proposed structure. The cloud-connected instruction set simulator is newly introduced to emulate the behavior of the processor. Experimental results of the cloud-IoT connected software execution using remote instruction showed the feasibility of cloudification of on-chip code flash memory. The simulation environment for cloud-connected code execution successfully emulates architectural operations of on-chip flash memory in cloud so that the various software services in IoT can be accelerated and performed in low-power by cloudification of remote instruction execution. The execution time of the program is reduced by 50% and the memory space is reduced by 24% when the cloud-connected code execution is used.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.139-143
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• 2018

Arduino, based on open source hardware, is used in many IoT devices, and IoT devices require multitasking for various inputs and outputs. Among the several methods used for multitasking based on Arduino, we compare three methods: Timing Call by using millis(), Simple Timer library method, and Timer library method. In order to measure the execution error caused by measurement and time delay of each method, two situations are created and analyzed. In the first case, 10 random tasks of a certain size are generated to measure the time delay of each method. In the second situation, 10 random tasks of a certain size are generated to compare execution errors caused by the time lag of the Timer library. In the first case, the millis() timing call method and the Simple Timer library method have a similar time delay and the Timer library method has more time delay. In the second situation, an execution error occurred in which small-size tasks were not called back at the correct timing due to the time delay.