• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.11-17
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• 2014

As ICT Ecosystem does, electronic government changes in its form. Accordingly, in order to realize Smarter m-Gov, the governments need to vitalize m-Gov services and enact technology policy. Therefor, this manuscript suggests possible model of m-Gov realization and security algorithm as a technology policy which applies quantum cryptography system to server security for the construction of secured m-Gov's infrastructure. What the manuscript suggests seeks administrative ideas of Smarter m-Gov's services which contain security, stability, and economic feasibility for the benefits of nation and enterprises.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.764-785
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• 2018

In this paper, we present a new public key encryption scheme with equality test (PKEwET). Compared to other PKEwET schemes, we find that its security can be improved since the proposed scheme is based on non-Abelian factorization problems. To our knowledge, it is the first scheme regarding equality test that can resist quantum algorithm attacks. We show that our scheme is one-way against chosen-ciphertext attacks in the case that the computational Diffie-Hellman problem is hard for a Type-I adversary. It is indistinguishable against chosen-ciphertext attacks in the case that the Decisional Diffie-Hellman problem is hard in the random oracle model for a Type-II adversary. To conclude the paper, we demonstrate that our scheme is more efficient.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.11
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• pp.1796-1801
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• 2001

For micro-machines, very few design methodologies based on optimization hale been developed so far. To overcome the difficulties of design optimization of micro-machines, the search method for multi-dimensional design window (DW)s is proposed. The proposed method is defined as areas of satisfactory design solutions in a design parameter space, using both continuous evolutionary algorithms (CEA) and the modified K-means clustering algorithm . To demonstrate practical performance of the proposed method, it was applied to an optimal shape design of micro electrostatic actuator of optical memory. The shape design problem has 5 design parameters and 5 objective functions, and finally shows 4 specific design shapes and design characters based on the proposed DWs.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.5 no.1
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• pp.04-10
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• 1987

We consider a time sharing computer system with a single processor where tasks ofK different types arrive at the system according to independent time homogeneous Poisson processes from outside. A task, after given a quantum for processing, leaves the system, or changes the type and rejoins the system according to specified probabilitycs. While many existing priority time sharing models determine the priorities of tasks strictly by their service time requirements, this paper develops a new scheduling rule wherein the importances or urgencies in addition to the service time requirements of tasks are counted, by inposing an appropriate reward structure on the system. Also presented is the algorithm through which to determine the rankings of K types according to this new scheduling rule.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2859-2870
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• 2022

Because nuclear power plants (NPPs) are safety-critical infrastructure, it is essential to increase their safety and minimize risk. To reduce human error and support decision-making by operators, several artificial-intelligence-based diagnosis methods have been proposed. However, because of the nature of data-driven methods, conventional artificial intelligence requires large amount of measurement values to train and achieve enough diagnosis resolution. We propose a graph neural network (GNN) based accident diagnosis algorithm to achieve high diagnosis resolution with limited measurements. The proposed algorithm is trained with both the knowledge about physical correlation between components and measurement values. To validate the proposed methodology has a sufficiently high diagnostic resolution with limited measurement values, the diagnosis of multiple accidents was performed with limited measurement values and also, the performance was compared with convolution neural network (CNN). In case of the experiment that requires low diagnostic resolution, both CNN and GNN showed good results. However, for the tests that requires high diagnostic resolution, GNN greatly outperformed the CNN.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.10
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• pp.468-476
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• 2002

Digital images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in medical radio-fluoroscopy images is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in diagnosis. We proposed adaptive weighed median(AWM) filters based on local statistics. We showed two ways of realizing the AWM filters. One is a simple type of AWM filter, which is constructed by Homogeneous factor(HF). Homogeneous factor(HF) from the noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the diagnostic systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by Visual C++ language on a IBM-PC Pentium 550 for testing purposes and the effects and results of the filter in the various levels of noise and images were proposed by comparing the values of NMSE(normalized mean square error) with the value of the other existing filtering methods.

• Journal of Acupuncture Research
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• v.36 no.1
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• pp.1-11
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• 2019

Models of traditional Chinese medicine (TCM) are still difficult to grasp from the view of a Western-cultural background. For proper integration into science and clinical research, it is vital to think "out of the box" of classical sciences. Modern sciences, such as quantum physics, system theory, and information theory offer new models, that reveal TCM as a method to process information. For this purpose, we apply concepts of information theory to propose a "Chinese black box model," that allows for a non-deterministic, bottom-up approach. Considering a patient as an undeterminable complex system, the process of getting information about an individual in Chinese diagnostics is compared to the input-process-output principle of information theory and quantum physics, which is further illustrated by Wheeler's "surprise 20 questions." In TCM, an observer uses a decision-making algorithm to qualify diagnostic information by the binary polarities of "yang" (latin activity) and "yin" (latin structivity) according to the so called "8 principles" (latin 8 guiding criteria). A systematic reconstruction of ancient Chinese terms and concepts illuminates a scattered scientific method, which is specified in a medical context by Latin terminology of the sinologist Porkert [definitions of the Latin terms are presented in Porkert's appendix [1] (cf. Limitations)].

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.711-718
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• 2022

In this paper, an accurate segmentation algorithm of video dynamic background image (VDBI) based on improved wavelet transform is proposed. Based on the smooth processing of VDBI, the traditional wavelet transform process is improved, and the two-layer decomposition of dynamic image is realized by using two-dimensional wavelet transform. On the basis of decomposition results and information enhancement processing, image features are detected, feature points are extracted, and quantum ant colony algorithm is adopted to complete accurate segmentation of the image. The maximum SNR of the output results of the proposed algorithm can reach 73.67 dB, the maximum time of the segmentation process is only 7 seconds, the segmentation accuracy shows a trend of decreasing first and then increasing, and the global maximum value can reach 97%, indicating that the proposed algorithm effectively achieves the design expectation.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.575-582
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• 2000

Because FIFO thread scheduling used in the existing multithreaded models does not consider locality in programs, it may result in the decrease of the performance of execution, caused by the frequent context switching overhead and delay of execution of relatively short frames. Quantum unit scheduling enhances the performance a little, but it still has the problems such as the decrease in the processor utilization and the longer delay due to its heavy dependency on the priority of the quantum units. In this paper, we propose shortest-frame-first(SFF) thread scheduling algorithm. Our algorithm selects and schedules the frame that is expected to take the shortest execution time using thread size and synchronization information analyzed at compile-time. We can estimate the relative execution time of each frame at compile-time. Using SFF thread scheduling algorithm on the multithreaded models, we can expect the faster execution, better utilization of the processor, increased throughput and short waiting time compared to FIFO scheduling.

• Nuclear Engineering and Technology
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• v.44 no.1
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• pp.61-70
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• 2012

In this study, a simple post-reconstruction dual-energy computed tomography (CT) method is proposed. A dual-energy CT algorithm for monochromatic x-rays was adopted and applied to the dual-energy CT of polychromatic x-rays by assigning a representative mono-energy. The accuracy of algorithm implementation was tested with mathematical phantoms. To test the sensitivity of this algorithm to the inaccuracy of representative energy value in energy values, a simulation study was performed with mathematical phantom. To represent a polychromatic x-ray energy spectrum with a single-energy, mean energy and equivalent energy were used, and the results were compared. The feasibility of the proposed method was experimentally tested with two different micro-CTs and a test phantom made of polymethyl methacrylate (PMMA), water, and graphite. The dual-energy calculations were carried out with CT images of all possible energy pairs among 40, 50, 60, 70, and 80 kVp. The effective atomic number and the electron density values obtained from the proposed method were compared with theoretical values. The results showed that, except the errors in the effective atomic number of graphite, most of the errors were less than 10 % for both CT scanners, and for the combination of 60 kVp and 70 kVp, errors less than 6.0 % could be achieved with a Polaris 90 CT. The proposed method shows simplicity of calibration, demonstrating its practicality and feasibility for use with a general polychromatic CT.