• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.1-9
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• 2004

The important arithmetic operations over finite fields include exponentiation, division, and inversion. An exponentiation operation can be implemented using a series of squaring and multiplication operations using a binary method, while division and inversion can be performed by the iterative application of an AB$^2$ operation. Hence, it is important to develop a fast algorithm and efficient hardware for this operations. In this paper presents new bit-serial architectures for the simultaneous computation of multiplication and squaring operations, and the computation of an $AB^2$ operation over $GF(2^m)$ generated by an irreducible AOP of degree m. The proposed architectures offer a significant improvement in reducing the hardware complexity compared with previous architectures, and can also be used as a kernel circuit for exponentiation, division, and inversion architectures. Furthermore, since the Proposed architectures include regularity and modularity, they can be easily designed on VLSI hardware and used in IC cards.

• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.101-113
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• 2018

Systems such as military inspection equipment which it is important to acquire and evaluate data in real-time should be able to real-time processing at the operating system level. As technology advances, there is a demand for replacing existing equipment with mobile device, but mobile devices with Android are not suitable for systems requiring real-time performance. On Android, garbage collection ensures free memory, while other tasks are interrupted while this task is performed, which cannot guarantee periodicity of particular tasks. In this paper, we designed and implemented a structure to control execution garbage collection of Android to solve this problem. Real-time performance is ensured by controlling garbage collection during the time required for real-time operation, and RTiK(Real-Time implanted Kernel) is applied to ensure real-time performance on Android. In order to evaluate the performance, we measured the call period of the 5ms period task, and, only 34.31% of the task was guaranteed before the control, but the task period of 98.18% was satisfied through control, providing real-time performance to Android.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.471-480
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• 2005

Most questions made for remote examinations on web-based education system use methods of making questions using fixed questions or randomly using item pools or automatically using degree of difficulty. Particularly, automatically selection methods using degree of difficulty is the kernel of a question that objectivity of the first degree of difficulty for questions and an effective questions selection using degree of difficulty and mediateness degree of difficulty based result of examination. This paper is use automatically selection methods for examination on web-based education system. Firstly, we present new question selection algorithms as regards degree of difficulty and distribution between all units. Secondly, we present new algorithms of mediateness degree of difficulty as regards education ability of students for adjust the degree of difficulty. We identified this algorithms is more effective as compared with previously algorithms on web-based education system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.97-103
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• 2020

Linux Cgroups takes a fundamental role for sharing system resources among multiple containers on container-based cloud computing environment. Especially for I/O resource, Linux Cgroups supports a mechanism for sharing I/O bandwidth in proportion to I/O weight. However, the current mechanism of Linux Cgroups using BFQ I/O scheduler seriously degrades the I/O performance with high bandwidth storage device such as NVMe SSDs. In this paper, we proposed a new feedback based I/O bandwidth sharing scheme for Linux Cgroups which allocates I/O credits to containers according to I/O weights and adjusts the amount of credits to performance fluctuation of NVMe SSDs. The proposed scheme is implemented on Linux kernel 5.3 and evaluated. The evaluation results show that it can share the I/O bandwidth among multiple containers proportionally to I/O weights while improving I/O performance more than twice as high as the existing scheme.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.35-41
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• 2014

In this paper, we proposed the implementation of software-based 2D BitBLT engine on the pSOS operating system and the operation of the BitBLT engine on patient monitoring device was verified. To verify the proposed method on the patient monitoring device, we designed prototype PCB board, and verified the operation. We designed the motherboard by using ARM9-based CPU. Because hardware-based BitBLT module was replaced with software-based one, CPU load problem was weighted. To solve this problem, w changed 400Mhz processor instead of 200Mhz processor. We implemented 2D BitBLT kernel module as a device driver which is one of the key elements of a graphics controller GUI in patient monitoring device.

• Journal of IKEEE
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• v.20 no.4
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• pp.398-411
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• 2016

SVM, a machine learning method, is widely used in image processing for it's excellent generalization performance. However, to add other data to the pre-trained data of the system, we need to train the entire system again. This procedure takes a lot of time, especially in embedded environment, and results in low performance of SVM. In this paper, we implemented an SVM trainer and classifier in an FPGA to solve this problem. We parlallelized the repeated operations inside SVM and modified the exponential operations of the kernel function to perform fixed point modelling. We implemented the proposed hardware on Xilinx ZC 706 evaluation board and used TSR algorithm to verify the FPGA result. It takes about 5 seconds for the proposed hardware to train 2,000 data samples and 16.54ms for classification for $1360{\times}800$ resolution in 100MHz frequency, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2067-2073
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• 2001

Biometric systems are forms of technology that use unique human physical characteristics to automatically identify a person. They have sensors to pick up some physical characteristics, convert them into digital patterns, and compare them with patterns stored for individual identification. However, lip-print recognition has been less developed than recognition of other human physical attributes such as the fingerprint, voice patterns, retinal at blood vessel patterns, or the face. The lip print recognition by a CCD camera has the merit of being linked with other recognition systems such as the retinal/iris eye and the face. A new method using multi-resolution architecture is proposed to recognize a lip print from the pattern kernels. A set of pattern kernels is a function of some local lip print masks. This function converts the information from a lip print into digital data. Recognition in the multi-resolution system is more reliable than recognition in the single-resolution system. The multi-resolution architecture allows us to reduce the false recognition rate from 15% to 4.7%. This paper shows that a lip print is sufficiently used by the measurements of biometric systems.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.10
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• pp.516-523
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• 2000

In this paper, intelligent methods using digital protective relay in power supervisory control system is developed in order to protect power systems by means of timely fault detection and diagnosis during operation for induction motor which has various load environments and capacities in power systems. The spectrum pattern of input currents was used to monitor to state of induction motors, and by clustering the spectrum pattern of input currents, the newly occurrence of spectrums pattern caused by faults were detected. For diagnosis of the fault detected, the fuzzy fault tree was derived, and the fuzzy relation equation representing the relation between an induction motor fault and each fault type, was solved. The solution of the fuzzy relation equation shows the possibility of each fault's occurring. The results obtained are summarized as follows: 1) The test result on the basis of KEMC1120 and IEC60255, show that the operation time error of the digital motor protective relay is improved within ${\pm}5%$. 2) Using clustering algorithm by unsupervisory learning, an on-line fault detection method, not affected by the characteristics of loads and rates, was implemented, and the degree of dependency by experts during fault detection was reduced. 3) With the fuzzy fault tree, fault diagnosis process became systematic and expandable to the whole system, and the diagnosis for sub-systems can be made as an object-oriented module.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.1
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• pp.26-33
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• 2007

The intake swirl motion, as one of dominant effects for an engine combustion. is very effective for turbulence enhancement during the compression process in the cylinder of 2-valve engine. Because the combustion flame speed is determined by the turbulence that is mainly generated from the mean flow of the charge air motion in intake port system. This paper describes the experimental results of swirl flow and combustion characteristics by using the oil spot method and back-scattering Laser Doppler velocimeter (LDV) in 2-valve single cylinder transparent LPG engine using the liquid phase LPG injection. For this. various intake port configurations were developed by using the flow box system and swirl ratios for different intake port configurations were determined by impulse swirl meter in a steady flow rig test. And the effects of intake swirl ratio on combustion characteristics in an LPG engine were analyzed with some analysis parameters that is swirl ratio. mean flow coefficient, swirl mean velocity fuel conversion efficiency. combustion duration and cyclic variations of indicated mean effective pressure(IMEP). As these research results, we found that the intake port configuration with swirl ratio of 2.0 that has a reasonable lean combustion stability is very suitable to an $11{\ell}$ heavy-duty LPG engine with liquid phase fuel injection system. It also has a better mean flow coefficient of 0.34 to develope a stable flame kernel and to produce high performance. This research expects to clarify major factor that effects on the design of intake port efficiently with the optimized swirl ratio for the heavy duty LPG engine.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.86-97
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• 2011

This paper presents a novel algorithm to detect more accurate road lane with image sensor-based color classification and directional edge clustering. With treatment of road region and lane as a recognizable color object, the classification of color cues is processed by an iterative optimization of statistical parameters to each color object. These clustered color objects are taken into considerations as initial kernel information for color object detection and recognition. In order to improve the limitation of object classification using the color cues, the directional edge cures within the estimated region of interest in the lane boundary (ROI-LB) are clustered and combined. The results of color classification and directional edge clustering are optimally integrated to obtain the best detection of road lane. The characteristic of the proposed system is to obtain robust result to all real road environments because of using non-parametric approach based only on information of color and edge clustering without a particular mathematical road and lane model. The experimental results to the various real road environments and imaging conditions are presented to evaluate the effectiveness of the proposed method.