• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.246-253
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• 2013

Based on the conventional 2-6GHz digital frequency discriminator (DFD) using the phase unwrapping and least-squares techniques, we propose a new 2-18GHz DFD. To compensate for lowered-precision frequency estimation due to the expanded bandwidth, the proposed DFD design employs more delay lines, accordingly accompanying high complexity. Thus, a new computationally efficient frequency estimation algorithm is also presented to overcome such high computational burden. More specifically, the proposed frequency estimation algorithm is basically based on the conventional phase unwrapping technique, along with a new candidates selection for the unwrapped phases under the condition that the phase margin is known. As a result, the computational burden required for the least-squares technique can be reduced. Finally, simulation results are provided to demonstrate the effectiveness of the proposed approach, compared with those of the conventional DFD's.

• BMB Reports
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• v.49 no.9
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• pp.514-519
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• 2016

Korean cattle (Hanwoo) are categorized into three breeds based on color: brown, brindle, and black. Among these breeds, brown Hanwoo has been subjected to intensive selection to improve meat traits. To identify genetic traces driven by recent selection in brown Hanwoo, we scanned the genomes of brown and brindle Hanwoo using a bovine SNP chip. We identified 17 candidate selection signatures in brown Hanwoo and sequenced four candidate regions from 10 individuals each of brown and brindle Hanwoo. In particular, non-synonymous SNPs in the ADSL gene (K88M, L189H, and R302Q) might have had mutational effects on protein structure as a result of altering the purine pathway during nucleotide breakdown. The ADSL gene was previously reported to affect meat quality and yield in livestock. Meat quality and yield are main breeding goals for brown Hanwoo, and our results support a potential causal influence of non-synonymous SNPs in the ADSL gene.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.98-105
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• 2024

This paper proposes a new approach with a distance-based regularization to the entropy applied to the NBV (Next-Best-View) selection with NeRF (Neural Radiance Fields). 3D reconstruction requires images from various viewpoints, and selecting where to capture these images is a highly complex problem. In a recent work, image acquisition was derived using NeRF's ray-based uncertainty. While this work was effective for evaluating candidate viewpoints at fixed distances from a camera to an object, it is limited when dealing with a range of candidate viewpoints at various distances, because it tends to favor selecting viewpoints at closer distances. Acquiring images from nearby viewpoints is beneficial for capturing surface details. However, with the limited number of images, its image selection is less overlapped and less frequently observed, so its reconstructed result is sensitive to noise and contains undesired artifacts. We propose a method that incorporates distance-based regularization into entropy, allowing us to acquire images at distances conducive to capturing both surface details without undesired noise and artifacts. Our experiments with synthetic images demonstrated that NeRF models with the proposed distance and entropy-based criteria achieved around 50 percent fewer reconstruction errors than the recent work.

• Journal of Korean Institute of Industrial Engineers
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• v.3 no.2
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• pp.63-72
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• 1977

The trend of computerization is significant in Korea even at its beginning stage, especially for governmental administration. However, full-fledged success of computerization in an organization is reported to be rare while the cost of computerization has been high and increasing. This paper is concerned with two features for the successful implementation of a computerized system in an organization selection criteria for the computerization among the possible candidate projects and project selection models. Due to the dearth of literature regarding successful implementation of computerization, other sources of literature with respect to R & D management, method engineering, etc. were reviewed to develop a set of factors influencing successful computerization. Thus, project selection criteria for computerization of governmental administration are developed and organized as follows: cost of computerization project including both system development and operating cost, quanitative and qualitative benefits of computerization project, probability of technical and implementation success of computerization and other organizational and political factors to be considered. These criteria are broken down into detailed sets of subcriteria to be measured. To select a project after thorough consideration of the selection criteria, a project selection model which takes into account all criteria together has to be developed. In the study three project selection models are suggested and developed. They are the checklist model, multi-stage cut-off model, and composite criteria model. A detailed procedure for each of the three models is illustrated. Although the project selection criteria and models are developed here primarily for the computerization of governmental administration, they are easily applicable to other settings of computerization. Finally, some caveats for the use of selection criteria and models are discussed.

• Transactions on Electrical and Electronic Materials
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• v.14 no.4
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• pp.187-192
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• 2013

Because of the importance of small target detection in infrared images, many studies have been carried out in this area. Using a Kalman filter and mean shift algorithm, this study proposes an algorithm to track multiple small moving targets even in cases of target disappearance and appearance in serial infrared images in an environment with many noises. Difference images, which highlight the background images estimated with a background estimation filter from the original images, have a relatively very bright value, which becomes a candidate target area. Multiple target tracking consists of a Kalman filter section (target position prediction) and candidate target classification section (target selection). The system removes error detection from the detection results of candidate targets in still images and associates targets in serial images. The final target detection locations were revised with the mean shift algorithm to have comparatively low tracking location errors and allow for continuous tracking with standard model updating. In the experiment with actual marine infrared serial images, the proposed system was compared with the Kalman filter method and mean shift algorithm. As a result, the proposed system recorded the lowest tracking location errors and ensured stable tracking with no tracking location diffusion.

• ETRI Journal
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• v.29 no.6
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• pp.736-744
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• 2007

We propose a fast macroblock (MB) mode prediction and decision algorithm based on temporal correlation for P-slices in the H.264/AVC video standard. There are eight block types for temporal decorrelation, including SKIP mode based on rate-distortion (RD) optimization. This scheme gives rise to exhaustive computations (search) in the coding procedure. To overcome this problem, a thresholding method for fast inter mode decision using a MB tracking scheme to find the most correlated block and RD cost of the correlated block is suggested for early stop of the inter mode determination. We propose a two-step inter mode candidate selection method using statistical analysis. In the first step, a mode is selected based on the mode information of the co-located MB from the previous frame. Then, an adaptive thresholding scheme is applied using the RD cost of the most correlated MB. Secondly, additional candidate modes are considered to determine the best mode of the initial candidate modes that does not satisfy the designed thresholding rule. Comparative analysis shows that a speed-up factor of up to 70.59% is obtained when compared with the full mode search method with a negligible bit increment and a minimal loss of image quality.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.161-169
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• 2016

This paper is intended to propose a novel approach to select an optimal site for a small-scaled artificial recharge system installation using TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) with geospatial data. TOPSIS is a MCDM (Multi-Criteria Decision Making) method to choose the preferred one of derived alternatives by calculating the relative closeness to an ideal solution. For applying TOPSIS, in the first, the topographic shape representing optimal recovery efficiency is defined based on a hydraulic model experiment, and then an appropriate surface slope is determined for the security of a self-purification capability with DEM (Digital Elevation Model). In the second phase, the candidate areas are extracted from an alluvial map through a morphology operation, because local alluvium with a lengthy and narrow shape could be satisfied with a primary condition for the optimal site. Thirdly, a shape file over all candidate areas was generated and criteria and their values were assigned according to hydrogeologic attributes. Finally, TOPSIS algorithm was applied to a shape file to place the order preference of candidate sites.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.27-31
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• 2019

It is well documented that intensive selection in dairy cattle for economic value such as increased milk yield led to a decline in reproductive performance. Recent studies using genome-wide association studies (GWASs) discovered candidate genes involved in the lower fertility including embryo development and conception rates. However, the information, which showed a lower reproductive performance, is limited to dairy cattle, especially Holstein, and the candidate genes were not examined in the Korean native cattle Hanwoo which has been intensively selected and bred for meat in the last few decades. We selected the candidate genes WBP1 and PARM1 reported to be associated with cow and/or heifer conception in dairy cattle and analyzed the genotype because those genes have non-synonymous single nucleotide polymorphisms (SNPs). To determine the single base change, we used the high resolution melting (HRM) assay which is rapid and cost-effective for a small number of genes. We found that most heifers with higher conception (1: service per conception) have the AA genotype coding Threonine rather than Proline in the WBP1 gene. We did not detect an association for a SNP in PARM1 in our analysis. In conclusion, the genetic variation of WBP1 can be used as a selective marker gene to improve reproductive performance, and HRM assay can be used to identify common SNP genotypes rapidly and cost effectively.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.87-94
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• 2004

A number of approximate techniques have been developed to calculate the eigenvalues in a reduced manner. These schemes approximate the lower eigenvalues that represent the global behavior of the structures. In general, sequential elimination has been widely used with reliability. But it takes excessively large amount of time to construct a reduced system. The present study proposes two-level condensation scheme(TLCS). In the first step, the candidate elements are selected by element-level energy estimation. In the second step, master degrees of freedom are selected by sequential elimination from the candidate degrees of freedom linked to the selected elements in the first step. Numerical examples demonstrate that the proposed method saves computational cost effectively and provides a reduced system which predicts the accurate eigenvalues of global system.