• Journal of the Korea Computer Industry Society
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• v.2 no.8
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• pp.1075-1088
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• 2001

In this paper, we propose a method for dynamic selection of unrestricted motion vector(UMV) or default prediction mode(DPM) in H.263 bit stream. For this, we use the error of compensated image and the magnitude of motion vector. In the proposed strategy, the UMV mode is dynamically applied in a frame according to average magnitude of motion vector and error of compensated image. This scheme has improved the quality of image compared to the fixed mode UMV or DPM only. Number of searching points are greatly reduced when comparing to UMV The proposed method is more profitable to long video sequences having camera movement locally.

• Journal of the Korea Computer Industry Society
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• v.2 no.7
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• pp.997-1014
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• 2001

In this paper, we propose a method for dynamic selection of unrestricted motion vector(UMV) or default prediction mode(DPM) in H.263 bit stream. For this, we use the error of compensated image and the magnitude of motion vector. In the proposed strategy, the UMV mode is dynamically applied in a frame according to average magnitude of motion vector and error of compensated image. This scheme has improved the quality of image compared to the fixed mode UMV or DPM only. Number of searching points are greatly reduced when comparing to UMV. The Proposed method is more profitable to long video sequences having camera movement locally.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.479-484
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• 2010

Researches of Healthcare have been fulfilled lively with an advanced age and change of lifestyles. Especially, medical field has focused on researches of Healthcare due to that reasons. The Healthcare service requires the foundation technologies, such as sensor aggregating, data saving and data transmitting/analysis. In this research, we proposed the unrestricted equipment which can save a lot of aggregated patient's medical data to guarantee the patient's movement in Healthcare service. Moreover, we research the method which can transmit the aggregated data as soon as possible. Also, we implemented the system which can transmit the patient's medical data automatically for convenient use.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.725-730
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• 1998

Recently we extended the fuzzy model for rule based systems incorporating an importance factor for each rule. The model permits for both unrestricted as well as non-negative importance factors. We use this extended model to design a fuzzy rule based classifier system which uses both the firing strength of the rule and the importance factor to decide the class label. The effectiveness of the scheme is established using several data sets.

• Journal of the Korean Society of Radiology
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• v.11 no.1
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• pp.1-8
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• 2017

The U.S. NRC establishes a radiological criteria with regard to restricted or unrestricted use of nuclear plant site after decommissioning in NUREG-1757. According to this, a nuclear plant site can be released in a restricted way or unrestricted way only if a licensee demonstrates that the dose criteria is fulfilled after the site decontamination and remediation. In order to prove compliance with the radiological criteria of site release, LTP(License Termination Plan) must include the site release criteria, site characterization, final survey plan with major radionuclides and DCGL(Derived Concentration Guideline Levels), etc. Based on the decommissioning case of Rancho Seco nuclear power plant in the United States, this paper analyzed a method of setting the DCGL that can be applied to Kori NPP Unit 1 which will be permanently disabled in 2017.

• Journal of the Korean Chemical Society
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• v.63 no.2
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• pp.73-77
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• 2019

We compared methodologies based on the density functional theory (DFT), e.g., time-dependent DFT (TD-DFT), TD-DFT within Tamm-Dancoff approximation (TDA-DFT), and spin-unrestricted DFT (UDFT), that are usually employed to optimize the geometries of ${\pi}$-conjugated molecules in their lowest lying triplet excited ($T_1$) state. As a model system for ${\pi}$-conjugated molecules, we employed 1,2,3,4,5-pentacyano-6-phenyl-benzene. In conjunction with 6-31G(d) basis sets, we made use of gap-tuned range-separated ${\omega}B97X$ functional which is often employed recently in the calculations of molecular excited states. Near the equilibrium geometries, we found that the important difference between the geometries derived at UDFT level and those at TD-DFT or TDA-DFT methods: more stable ground-state energies but higher triplet excitation energies for UDFT derived geometries. In the studies, we discuss such differences in more detail.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.43-46
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• 2000

In this paper, we propose a fast adaptive diamond search algorithm(FADS) for block matching motion estimation. Fast motion estimation algorithms reduce the computational complexity by using the UESA (Unimodal Error Search Assumption) that the matching error monotonically increases as the search moves away from the global minimum error. Recently many fast BMAs(Block Matching Algorithms) make use of the fact that the global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the adjacent blocks. We change the origin of search window according to the spatially adjacent motion vectors and their MAE(Mean Absolute Error). The computer simulation shows that the proposed algorithm has almost the same computational complexity with UCBDS(Unrestricted Center-Biased Diamond Search)〔1〕, but enhance PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS(Full Search), even for the large motion case, with half the computational load.

• Journal of Radiation Protection and Research
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• v.15 no.2
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• pp.67-74
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• 1990

A methodology for calculating acceptable levels of contamination of radionuclides in soil for unrestricted use was described. Pathways of exposure include direct radiation from ground surfaces, ingestion of contaminated food and inhalation of resuspended radionuclides. Results calculated using site-specific data for Korean environment were discussed and compared with those estimated by other guidelines.

• Bulletin of the Korean Chemical Society
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• v.34 no.1
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• pp.179-187
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• 2013

We describe newly developed software named KPACK for relativistic electronic structure computation of molecules containing heavy elements that enables the two-component ab initio calculations in Kramers restricted and unrestricted formalisms in the framework of the relativistic effective core potential (RECP). The spin-orbit coupling as relativistic effect enters into the calculation at the Hartree-Fock (HF) stage and hence, is treated in a variational manner to generate two-component molecular spinors as one-electron wavefunctions for use in the correlated methods. As correlated methods, KPACK currently provides the two-component second-order M${\o}$ller-Plesset perturbation theory (MP2), configuration interaction (CI) and complete-active-space self-consistent field (CASSCF) methods. Test calculations were performed for the ground states of group-14 elements, for which the spin-orbit coupling greatly influences the determination of term symbols. A categorization of three procedures is suggested for the two-component methods on the basis of spin-orbit coupling manifested in the HF level.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.2-4
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• 2023

Sequence data plays an important role in the field of intelligence, especially for industrial control, traffic control and other aspects. Finding abnormal parts in sequence data has long been an application field of AI technology. In this paper, we propose an anomaly detection method for sequence data using a diffusion model. The diffusion model has two major advantages: interpretability derived from rigorous mathematical derivation and unrestricted selection of backbone models. This method uses the diffusion model to predict and reconstruct the sequence data, and then detects the abnormal part by comparing with the real data. This paper successfully verifies the feasibility of the diffusion model in the field of anomaly detection. We use the combination of MLP and diffusion model to generate data and compare the generated data with real data to detect anomalous points.