• Journal of KIISE
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• v.42 no.12
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• pp.1495-1502
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• 2015

Data compression involves a trade-off between delay time and data size. Greater delay times require smaller data sizes and vice versa. There have been many studies performed in the field of wireless sensor networks on increasing network life cycle durations by reducing data size to minimize energy consumption; however, reductions in data size result in increases of delay time due to the added processing time required for data compression. Meanwhile, as energy generation occurs periodically in solar energy-based wireless sensor networks, redundant energy is often generated in amounts sufficient to run a node. In this study, this excess energy is used to reduce the delay time between nodes in a sensor network consisting of solar energy-based nodes. The energy threshold value is determined by a formula based on the residual energy and charging speed. Nodes with residual energy below the threshold transfer data compressed to reduce energy consumption, and nodes with residual energy above the threshold transfer data without compression to reduce the delay time between nodes. Simulation based performance verifications show that the technique proposed in this study exhibits optimal performance in terms of both energy and delay time compared with traditional methods.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.199-204
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• 2002

Since motion estimation and motion compensation methods remove the redundant data to employ the temporal redundancy in images, it plays an important role in digital video compression. Because of its high computational complexity, however, it is difficult to apply to high-resolution applications in real time environments. If we have information about the motion of an image block before the motion estimation, the location of a better starting point for the search of an exact motion vector can be determined to expedite the searching process. In this paper, we present an adaptive motion estimation approach bated on temporal correlations of consecutive image frames that defines the search pattern and determines the location of the initial search point adaptively. Through experiments, compared with DS(Diamond Search) algorithm, the proposed algorithm is about 0.1∼0.5(dB) better than DS in terms of PSNR(Peak Signal to Noise Ratio) and improves as high as 50% compared with DS in terms of average number of search point per motion vector estimation.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.131-136
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• 2005

Motion Estimation (ME) has been developed to remove redundant data contained in a sequence of image. And ME is an important part of video encoding systems, since it can significantly affect the qualify of an encoded sequences. Generally, ME consists of two stages, the integer pixel motion estimation and the half pixel motion estimation. Many methods have been developed to reduce the computational complexity at the integer pixel motion estimation. However, the studies are needed at the half pixel motion estimation to reduce the complexity. In this paper, a method based on the correlations between integer pixel motion vectors and half pixel motion vectors is proposed for the half pixel motion estimation. The proposed method has less computational complexity than the full half pixel search method (FHSM) that needs the bilinear interpolation of half pixels and examines nine half pixel points to the find the half pixel motion vector. Experimental results show that the speedup improvement of the proposed method over FHSM can be up to $2.5\~80$ times faster and the image quality degradation is about to $0.07\~0.69(dB)$.

• Journal of Korean Clinical Nursing Research
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• v.25 no.2
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• pp.170-178
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• 2019

Purpose: The purpose of this study was to determine the mediating effects of self-efficacy and the belief about medication on the association between depression and medication adherence in patients with systemic lupus erythematosus. Methods: 128 patients aged ${\geq}19years$, who were regular outpatients or admitted patients diagnosed with systemic lupus erythematosus at a tertiary hospital in B city, participated in this study. Data were collected by using a self-administered questionnaire. Testing of mediating effects was analyzed by a parallel redundant mediated model using the PROCESS macro for SPSS version 3.3. Results: They scored an average of $16.71{\pm}11.13$ for depression, $694.14{\pm}170.68$ for self-efficacy, $3.05{\pm}4.60$ for the belief about medication, and $90.14{\pm}15.37$ for medication adherence. The direct effect of depression on medication adherence was not statistically significant, but the indirect effects of depression mediated with self-efficacy and belief about medication were statistically significant. Conclusion: It is necessary to develop and apply a nursing intervention program that can not only relieve depression but also promote self-efficacy and the belief about medication with the objective of improving medication adherence among patients with systemic lupus erythematosus.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.35-45
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• 2018

Motion Estimation(ME) has been developed to reduce the redundant data in digital video signal. ME is an important part of video encoding system, However, it requires huge computational complexity of the encoder part, and fast motion search methods have been proposed to reduce huge complexity. Multi- view video is obtained by capturing on a three-dimensional scene with many cameras at different positions and its complexity increases in proportion to the number of cameras. In this paper, we proposed an efficient motion method which chooses a search pattern adaptively by using the temporal-spatial correlation of the block and the characteristics of the block. Experiment results show that the computational complexity reduction of the proposed method over TZ search method and FS method can be up to 70~75% and 99% respectively while keeping similar image quality and bit rates.

• Health Policy and Management
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• v.31 no.3
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• pp.261-271
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• 2021

Background: In 2018, the government increased the fee for the magnetic resonance imaging (MRI) image deciphering services of the external hospital to discourage the redundant MRI scan and to induce appropriate use of the MRI services. It is important to evaluate the effect of the policy to provide the basis for establishing other MRI-related policies. Methods: The healthcare data of the patients who had brain MRI scans were organized by episode and analyzed using the panel study in order to find out the effect of the MRI-related policy on the substitution effect and the medical expenses. Results: As a result of the increase in the fee of deciphering the MRI image, there has been an uplift in deciphering the MRI scan of the external hospital. It implies that more hospitals chose to use the MRI scan taken by other clinics or hospitals, rather than the MRI scan taken at their own facilities. Conclusion: The research results imply that a policy that facilitates the exchange of the medical image data between the hospitals is needed in order to establish an efficient management system of the healthcare resources. Such improvement is expected to reduce the social cost and contribute to the stability in the finance of national health insurance.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.63-74
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• 2021

Location-based services (LBSs) are expected to process a large number of spatial queries, such as shortest path and k-nearest neighbor queries that arrive simultaneously at peak periods. Deploying more LBS servers to process these simultaneous spatial queries is a potential solution. However, this significantly increases service operating costs. Recently, batch processing solutions have been proposed to process a set of queries using shareable computation. In this study, we investigate the problem of batch processing moving k-nearest neighbor (MkNN) queries in dynamic spatial networks, where the travel time of each road segment changes frequently based on the traffic conditions. LBS servers based on one-query-at-a-time processing often fail to process simultaneous MkNN queries because of the significant number of redundant computations. We aim to improve the efficiency algorithmically by processing MkNN queries in batches and reusing sharable computations. Extensive evaluation using real-world roadmaps shows the superiority of our solution compared with state-of-the-art methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.6
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• pp.1375-1391
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• 2012

Smart grid is a next-generation intelligent power grid that applying ICT to power grid to maximize the energy efficiency ratio. Recently, technologies and standards for smart grid are being developed around the world. Information security which is an essential part of smart grid development has to be managed continuously. Information security management system certification for organizational risk management has been implemented in Korea. Although preparation for information security management system certification which is applicable to smart grid is considered, there are no specific methods. This paper is to propose core and added evaluation criteria for Korean smart grid based on K-ISMS through comparative analysis between ISMS operated in Korea and smart grid information security management system developed in the United States. Added evaluation criteria enable smart grid related business that certified existing ISMS to minimize redundant and unnecessary certification assessment work.

• The Korea Journal of Herbology
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• v.33 no.5
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• pp.19-37
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• 2018

Objectives : Oryeong-san was composed of Alismatis Rhizoma, Atractylodis Rhizoma Alba, Poria Sclerotium, Polyporus, Cinnamomi Cortex, and known to have hundreds of chemical compounds. The aim of this study was to screen chemical compounds constituting Oryeong-san with the drug-likeness and oral bioavailability from the analysis of their physicochemical properties. Methods : A list of chemical compounds of Oryeong-san was obtained from TM-MC(database of medicinal materials and chemical compounds in Northeast Asian traditional medicine). To remove redundant compounds, the SMILES (Simplified Molecular Input Line Entry System) strings of each compound were identified. All of the physicochemical properties for the compounds were calculated using the DruLiTo(Drug Likeness Tool). Drug-likeness was estimated by QED(Quantitative Estimate of Druglikeness) and OB(Oral bioavailability) was checked based on the Veber's rules. Results : A total of 475 compounds were obtained by eliminating duplication among 544 compounds of 5 medicinal materials. Analysis of the physicochemical properties revealed that the most common values were MW(molecular weight) 200~300 g/mol, ALOGP(octanol-water partition coefficient) 1~2, HBA(number of hydrogen bond acceptors) 0~1, HBD(number of hydrogen bond donors) 0, PSA(polar surface area) 0~50 angstrom, ROTB(number of rotatable bonds) 1, AROM(number of aromatic rings) 0, and ALERT(number of structural alerts) 1. QED had 93% of the values between 0.2 and 0.7, and OB had 90% of the value of TRUE. Conclusions : We in this paper screened the candidate active compounds of Oryeong-san using the QED and Veber's rules. In the future, we will use the screening results to analyze the mechanism of Oryeong-san based on systems pharmacology.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.501-514
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• 2023

When analyzing high dimensional data such as text data, if we input all the variables as explanatory variables, statistical learning procedures may suffer from over-fitting problems. Furthermore, computational efficiency can deteriorate with a large number of variables. Dimensionality reduction techniques such as feature selection or feature extraction are useful for dealing with these problems. The sparse principal component analysis (SPCA) is one of the regularized least squares methods which employs an elastic net-type objective function. The SPCA can be used to remove insignificant principal components and identify important variables from noisy observations. In this study, we propose a dimension reduction procedure for text data based on the SPCA. Applying the proposed procedure to real data, we find that the reduced feature set maintains sufficient information in text data while the size of the feature set is reduced by removing redundant variables. As a result, the proposed procedure can improve classification accuracy and computational efficiency, especially for some classifiers such as the k-nearest neighbors algorithm.