• Journal of Korea Multimedia Society
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• v.8 no.1
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• pp.79-87
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• 2005

In e-commerce applications, a public key cryptosystem is an important and indispensible element for the basic security operations such as authentication, digital signaturing, and key distribution. In wired network environments, the public key infrastructure certificate, which is based on X.509 specification, has been widely used. On the other hand, it still remains difficult to use the certificate information in wireless network environments due to the inherent limitations of the hand-held devices such as low computational power and short battery life. In this paper, we facilitate a codesign approach by implementing a software public-key cryptosystem and classifying its internal computation overheads quantitatively using a software profiling technique. Moreover, we propose a method to analyze the profiled data and apply it to the problem of software/hardware partitioning in a codesign approach. As an illustrative example, we analyze the computational overheads of an EC-Elfagamal application and examine a critical computational path.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.61-74
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• 2015

Structural equation modeling (SEM) is a widely used in social sciences such as education, business administration, and psychology. In SEM, the latent variable score is the estimate of the latent variable which cannot be observed directly. This study uses stagewise structural equation modeling(stagewise SEM; SSEM) by partitioning the whole model into several stages. The traditional estimation method minimizes the discrepancy function using the variance-covariance of all observed variables. This method can lead to inappropriate situations where exogenous latent variables may be affected by endogenous latent variables. The SSEM approach can avoid such situations and reduce the complexity of the whole SEM in estimating parameters.

• Current Optics and Photonics
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• v.5 no.4
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• pp.431-443
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• 2021

Sparse unmixing has been proven to be an effective method for hyperspectral unmixing. Hyperspectral images contain rich spectral and spatial information. The means to make full use of spectral information, spatial information, and enhanced sparsity constraints are the main research directions to improve the accuracy of sparse unmixing. However, many algorithms only focus on one or two of these factors, because it is difficult to construct an unmixing model that considers all three factors. To address this issue, a novel algorithm called multiview-based spectral weighted and low-rank row-sparsity unmixing is proposed. A multiview data set is generated through spectral partitioning, and then spectral weighting is imposed on it to exploit the abundant spectral information. The row-sparsity approach, which controls the sparsity by the l_2,0 norm, outperforms the single-sparsity approach in many scenarios. Many algorithms use convex relaxation methods to solve the l_2,0 norm to avoid the NP-hard problem, but this will reduce sparsity and unmixing accuracy. In this paper, a row-hard-threshold function is introduced to solve the l_2,0 norm directly, which guarantees the sparsity of the results. The high spatial correlation of hyperspectral images is associated with low column rank; therefore, the low-rank constraint is adopted to utilize spatial information. Experiments with simulated and real data prove that the proposed algorithm can obtain better unmixing results.

• Economic and Environmental Geology
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• v.36 no.3
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• pp.243-255
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• 2003

The mathematical models for GIS-based spatial data integration have been developed for geological applications such as mineral potential mapping or landslide susceptibility analysis. Among various models, the effectiveness of fuzzy logic based integration of multiple sets of geological data is investigated and discussed. Unlike a traditional target-driven fuzzy integration approach, we propose a data-driven approach that is derived from statistical relationships between the integration target and related spatial geological data. The proposed approach consists of four analytical steps; data representation, fuzzy combination, defuzzification and validation. For data representation, the fuzzy membership functions based on the likelihood ratio functions are proposed. To integrate them, the fuzzy inference network is designed that can combine a variety of different fuzzy operators. Defuzzification is carried out to effectively visualize the relative possibility levels from the integrated results. Finally, a validation approach based on the spatial partitioning of integration targets is proposed to quantitatively compare various fuzzy integration maps and obtain a meaningful interpretation with respect to future events. The effectiveness and some suggestions of the schemes proposed here are illustrated by describing a case study for landslide susceptibility analysis. The case study demonstrates that the proposed schemes can effectively identify areas that are susceptible to landslides and ${\gamma}$ operator shows the better prediction power than the results using max and min operators from the validation procedure.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.9
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• pp.1520-1532
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• 2020

Objective: Due to rapid economic return, mixed crop-swine farming systems in Korea have become more intensive. Intensive farming practices often cause nutrient surpluses and lead to environmental pollution. Nutrient budgets can be used to evaluate the environmental impact and as a regulatory policy instrument for nutrient management. This study was conducted to select a nutrient budgeting approach applicable to the mixed crop-swine farms in Korea and suggest an effective manure treatment method to reduce on-farm nutrient production. Methods: In this study, we compared current and ideal gross nutrient balance (GNB) approaches of Organisation for Economic Co-operation and Development and soil system budget (SSB) approach with reference to on-farm manure treatment processes. Data obtained from farm census and published literature were used to develop the farm nutrient budgets. Results: The average nitrogen (N) and phosphorus (P) surpluses were approximately 11 times and over 7 times respectively higher in the GNB approaches than the SSB. After solid-liquid separation of manure, during liquid composting a change in aeration method from intermittent to continuous reduced the N and P loading about 50% and 47%, respectively. Although changing in solid composting method from turning only to turning+aeration improved the N removal efficiency by 30.5%, not much improvement in P removal efficiency was observed. Conclusion: Although the GNB approaches depict the impact of nutrients produced in the mixed crop-swine farms on the overall agricultural environment, the SSB approach shows the partitioning among different nutrient loss pathways and storage of nutrients within the soil system; thus, can help design sustainable nutrient management plans for the mixed cropswine farms. The study also suggests that continuous aeration for liquid composting and turning+aeration for solid composting can reduce nutrient loading to the soil.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.8
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• pp.22-30
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• 2009

Due to high levels of integration and complexity, the Network-on-Chip (NoC) approach has emerged as a new design paradigm to overcome on-chip communication issues and data bandwidth limits in conventional SoC(System-on-Chip) design. In particular, exponentially growing of energy consumption caused by high frequency, synchronization and distributing a single global clock signal throughout the chip have become major design bottlenecks. To deal with these issues, a globally asynchronous, locally synchronous (GALS) design combined with low power techniques is considered. Such a design style fits nicely with the concept of voltage-frequency-islands (VFI) which has been recently introduced for achieving fine-grain system-level power management. In this paper, we propose an efficient design methodology that minimizes energy consumption by VFI partitioning on an NoC architecture as well as assigning supply and threshold voltage levels to each VFI. The proposed algorithm which find VFI and appropriate core (or processing element) supply voltage consists of traffic-aware core graph partitioning, communication contention delay-aware tile mapping, power variation-aware core dynamic voltage scaling (DVS), power efficient VFI merging and voltage update on the VFIs Simulation results show that average 10.3% improvement in energy consumption compared to other existing works.

• Journal of Chest Surgery
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• v.13 no.3
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• pp.243-249
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• 1980

Truncus ateriosus is one of the cyanotic congenital heart disease. The incidence is relatively uncommon, as 0.4% of totoal congenital heart disease. Embryologically the defect is due to a lack of partitioning of the embryonic truncus and conus during the first few weeks of fetal life. The ventricular septal defect is invariable present. A single arterial vessel arises from the heart and supplies blood to the aorta, the lung, and the coronary arteries. In 1949, collett and Edwards classified this defect according to anatomic variation to four major types, such as type I, II, III, and IV. Type IV is defined that pulmonary arteries are absent, and the pulmonary arterial supply arises from the descending thoracic aorta. This patients often have a continuous murmur head particularly well in the interscapular area. No effective surgical treatment is available. We have experienced one case of truncus arteriosus, type IV of Collett and Edwards in the Department of Thoracic and Cardiovascular Surgery, Kyungbook National University Hospital. This patient was 10 year-old girl. The chief complaints were cyanosis and dyspnea on exertion since birth. She was admitted at this hospital on April 16, 1980. The continous machinery murmur was heard loudest at the interscapular area. The chest X-ray films revealed cardiomegaly with an increase in pulmonaryvascular markings. The pulmonary secotr was significantly concave. No filling of pulmonary arteries noticed by the right ventriculogram. There was possible biventricular hypertrophy in EKG. The echocardiogram showed that the demension of the aortic root was larger than normal and minimal increase of the left ventricular internal dimension. The cardiac catheterization data was obtained by use of the great saphenus vein approach. The systolic pressure of the right ventricular outflow tract was 80 mmHg and was similar to that of the aorta. The oxygen saturation data revealed the evidence of the left to right shunt at the level of ventricular septum. The patient was operated and the diagnosis was confirmed as trucus arteriosus, type IV. No effective surgical interventins were performed.

• Journal of Korea Spatial Information System Society
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• v.5 no.1 s.9
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• pp.65-74
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• 2003

Location-based service is an important spatiotemporal database application area that provides the location-aware information of wireless terminals via positioning devices such as GPS. With the rapid advances of wireless communication systems, the requirement of mobile application areas including traffic, mobile commerce and supply chaining management became the center of attention for various research issues in spatiotemporal databases. In this paper we present the A-Quadtree, an efficient indexing method for answering location-based queries where the movement vector information (e.g., speed and velocity) is not presented. We implement the A-Quadtree with an index structure for object identifiers as a.Net component to apply the component to multiplatforms. We present our approach and describe the performance evaluation through various experiments. In our experiments, we compare the performance with previous approaches and show the enhanced efficiency of our method.

• Journal of KIISE
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• v.44 no.4
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• pp.383-391
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• 2017

As we enter a new era of Big Data, the amount of semantic data has rapidly increased. In order to derive meaningful information from this large semantic data, studies that utilize the SWRL(Semantic Web Rule Language) are being actively conducted. SWRL rules are based on data extracted from a user's empirical knowledge. However, conventional reasoning systems developed on single machines cannot process large scale data. Similarly, multi-node based reasoning systems have performance degradation problems due to network shuffling. Therefore, this paper overcomes the limitations of existing systems and proposes more efficient distributed inference methods. It also introduces data partitioning strategies to minimize network shuffling. In addition, it describes a method for optimizing the incremental reasoning process through data selection and determining the rule order. In order to evaluate the proposed methods, the experiments were conducted using WiseKB consisting of 200 million triples with 83 user defined rules and the overall reasoning task was completed in 32.7 minutes. Also, the experiment results using LUBM bench datasets showed that our approach could perform reasoning twice as fast as MapReduce based reasoning systems.

• The KIPS Transactions:PartA
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• v.13A no.1 s.98
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• pp.79-86
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• 2006

Recently the tagSNP selection problem has been researched for reducing the cost of association studies between human's diversities and SNPs. General approach for this problem is that all of SNPs are separated into appropriate blocks and then tagSNPs are chosen in each block. Marsel in this paper is the system that involved the concept of linkage disequilibrium for overcoming the problem that the existing block partitioning approaches have short of biological meanings. In most approaches, the contiguous regions, which recombinations have LD coefficient |D'| and then tagSNP selection step is performed. And MarSel guarantees the minimum tagSNP selection using entropy-based optimal selection algorithm when tagSNPs are chosen in each block, and enables chromosome-level association studies using efficient memory management technique when input is very large-scale dataset that is impossible to be processed in the existing systems.