• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1724-1731
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• 2018

The conventional polynomial neural network (PNN) is a classical flexible neural structure and self-organizing network, however it is not free from the limitation of overfitting problem. In this study, we propose a space search-optimized polynomial neural network (ssPNN) structure to alleviate this problem. Ranking selection is realized by means of ranking selection-based performance index (RS_PI) which is combined with conventional performance index (PI) and coefficients based performance index (CPI) (viz. the sum of squared coefficient). Unlike the conventional PNN, L2-norm regularization method for estimating the polynomial coefficients is also used when designing the ssPNN. Furthermore, space search optimization (SSO) is exploited here to optimize the parameters of ssPNN (viz. the number of input variables, which variables will be selected as input variables, and the type of polynomial). Experimental results show that the proposed ranking selection-based polynomial neural network gives rise to better performance in comparison with the neuron fuzzy models reported in the literatures.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.673-676
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• 2004

To manage and query moving objects efficiently in MMDBMS, a memory index structure should be used. The most popular index structure for storing trajectories of moving objects is 3DR-tree. The 3DR-tree also can be used for MMDBMS. However, the volume of data can exceed the capacity of physical memory since moving objects report their locations continuously. To accommodate new location reports, old trajectories should be migrated to disk or purged from memory. This paper focuses on migration policies of a main memory index structure. Migration policies consist of two steps: (i) node selection, (ii) node placement. The first step (node selection) selects nodes that should be migrated to disk. The criteria of selection are the performance of insertion or query. The second step (node placement) determines the order of nodes written to disk. This step can be thought as dynamic declustering policies.

• Journal of Information Technology Applications and Management
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• v.10 no.2
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• pp.19-31
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• 2003

We propose an indexing technique and an index selection algorithm for optimal OLAP query processing in object database systems, Although there are many research results on the relational database systems for OLAP Query processing, few researches have been done on the object database systems. Since OLAP queries represent complex business logic on a huge data ware-house, object database systems supporting the OLAP queries should have higher performance. Proposed bitmap index structure is an extension of conventional bitmap indexes for adapting object databases and provides higher performance with lower space overhead. We also propose a linear time solution of the index selection problem that will be used in the OLAP query optimization process.

• Animal Bioscience
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• v.37 no.5
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• pp.839-851
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• 2024

Objective: The main goal of our current study was to improve the growth curve of meat animals by decreasing the birth weight while achieving a finishing weight that is the same as that before selection but at younger age. Methods: Random regression model was developed to derive various selection indices to achieve desired gains in body weight at target time points throughout the fattening process. We considered absolute and proportional gains at specific ages (in weeks) and for various stages (i.e., early, middle, late) during the fattening process. Results: The point gain index was particularly easy to use because breeders can assign a specific age (in weeks) as a time point and model either the actual weight gain desired or a scaled percentage gain in body weight. Conclusion: The point gain index we developed can achieve the desired weight gain at any given postnatal week of the growing process and is an easy-to-use and practical option for improving the growth curve.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1999.11a
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• pp.119-124
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• 1999

A selection methodology of liquid levelmeters, especially, level sensors in non-nuclear category, to be installed in nuclear energy facilities is developed using linguistic fuzzy approaches such as fully-linguistic and semi-linguistic methods. Depending on defuzzification techniques, the linguistic fuzzy methodology leads to either linguistic (exactly, fully-linguistic) or cardinal (i.e., semi-linguistic) evaluation. For the linguistic method, for each alternative, fuzzy preference index is converted to linguistic utility value by means of a similarity measure determining the degree of similarity between fuzzy index and linguistic ratings. For the cardinal method, the index is translated to cardinal overall utility value. According to these values, alternatives of interest are linguistically or numerically evaluated and a suitable alternative can be selected. Under given selection criteria, the suitable selections out of some liquid levelmeters for nuclear facilities are dealt with using the linguistic fuzzy methodology proposed. Then, linguistic fuzzy evaluation results are compared with qualitative result available in the literature. It is found that as to a suitable option the linguistic fuzzy selection is in agreement with the qualitative selection. Additionally, the comparative study shows that the fully-linguistic method using adequate scale system facilitates linguistic interpretation regarding evaluation results.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.491-499
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• 2011

In this paper, we offer a new strategic portfolio model for national IT R&D project selection in Korea. A risk and return (R-R) portfolio model was developed using an objectively quantified index on the two axes of risk and return, in order to select a strategic project and allocate resources in compliance with a national IT R&D strategy. We strategize using the R-R portfolio model to solve the non-strategy and subjectivity problems of the existing national R&D project selection model. We also use the quantified evaluation index of the IT technology road map (TRM) and the technical level reports (TLR) for the subjectivity of project selection, and try to discover the weights using the analytic hierarchy process (AHP). In addition, we intend to maximize the chance for a successful national IT R&D project, by selecting a strategic portfolio project and balancing the allocation of resources effectively and objectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.5
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• pp.855-862
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• 2017

The Republic of Korea has achieved rapid growth in economic, cultural and social through the development policy over the past half-century. However, principle of the nodal system has made an overgrown city and underdeveloped regions. A range of policies have been introduced aimed at underdeveloped regions. But many problems were found in policies. Because government ministry and public services were many and various. In addition, development priority are not based on objective index, Distribution business for the local government have been carried out. A study of the Index selection of the existing regions, has been large-scale center analysis. Thus, the difficulty is often in selecting the priorities of small unit operations. It is difficult to reach a selection of business to region priorities. Accordingly I want to be used as material for the efficient development of rural areas through the selection of indicators for a small areas. Intend to use the decision support system for the efficient development of small underdeveloped areas through index selection for a small and underdeveloped regions.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.3
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• pp.437-444
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• 2015

Satellite selection and exclusion techniques have been applied to the global navigation satellite system (GNSS) with the aim of achieving a balance between navigational performance and computational efficiency. Conventional approaches to satellite selection based on the best dilution of precision (DOP) are excessively computational and complicated. This paper proposes a new method that applies a geometric sensitivity index of individual GNSS satellites. The sensitivity index is derived using the inner product of the line of sight (LOS) vector of each satellite. First, the LOS vector is computed, which accounts for the geometry between the satellite and user positions. Second, the inner product of each pair of LOS vectors is calculated, which indicates the proximities of the satellites to one another. The proximity can be determined according to the sensitivity of each satellite. A post-processing test was conducted to verify the reliability of the proposed method. The proposed index and the results of a conventional approach that measures the dilution of precision (DOP) were compared. The test results demonstrate that the proposed index produces results that are within 96% of those of the conventional approach and reduces the computational burden. This index can be utilized to estimate the sensitivity of individual satellites, obtaining a navigation solution. Therefore, the proposed index applies to satellite selection and exclusion as well as to the sensitivity analyses of multiple GNSS applications.

• Korean Journal of Agricultural Science
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• v.20 no.1
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• pp.48-55
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• 1993

This study was conducted to determine the main effect of the breed, parity, forrowing year and month on average daily gain, feed efficiency, backfat thickness, age at 90 Kg body weight and selection index. The data analysis were the record of 115 male pigs producted from Landrace. Large Yorkshire and Duroc purebreds tested at Chungnam Province Animal Breeding Station from 1986 to 1990. The results obtained are summarized as follows : 1. The breed average of daily gain, feed efficiency, backfat thickness, age at 90Kg body weight and selection index were $922.25{\pm}17.2$g, $2.85{\pm}0.04$, $2.03{\pm}0.04$cm, $135.44{\pm}1.38$ days and $168.33{\pm}2.42$, respectively. 2. The effect of breed was highly significant at 1% level in average daily gain, age at 90Kg body weight and selection index, and significant at 5% level in backfat thickness. Among the purebreds, Duroc was superior in average daily gain, age at 90Kg body weight and selection index with 977.22g, 132.47 days and 172.35, respectively. But Large Yorkshire was 1.95cm thiner than other breeds in backfat thickness. 3. The effect of parity was highly significant at 1% level in average daily gain, and significant at 5% level in backfat thickness and selection index. Among the parity, the 3rd and 4th parity were superior in average daily gain and selection index with 974.92g 177.61, 959.48g and 177.84, respectively. 4. The effect of forrowing year was highly significant at 1% level in average daily gain, feed efficiency and selection index, and that of forrowing month was highly significant at 1% level in average daily gain, and significant at 5% level in backfat thickness and selection index, respectively. Among the forrowing month, March was superior in average daily gain and selection index with 968.22g and 174.54, respectively.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.76-81
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• 2015

Research on top-k query processing algorithms for analyzing big data have been spotlighted recently. However, because existing top-k query processing algorithms do not provide an efficient index structure, they incur high query processing costs and cannot support various types of queries. To solve these problems, we propose a top-k query processing algorithm using a view selection method based on a grid index. The proposed algorithm reduces the query processing time by retrieving the minimum number of grid cells for the query range, by using a grid index-based view selection method. Finally, we show from our performance analysis that the proposed scheme outperforms an existing scheme, in terms of both query processing time and query result accuracy.