• Journal of the Economic Geographical Society of Korea
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• v.7 no.1
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• pp.45-63
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• 2004

The main purpose of this article is to suggest policy implications for building innovative cluster in Korea by investigating the operating system and role of the Kanagawa Science Park (KSP) located in Kanagawa prefecture, Japan as a central network agent. The KSP established mainly by private and government partnership has played a critical role for building innovative clusters as a way in which increase national competitiveness. But they also provide variety of real service from R&D to commercialization for local firms by facilitating and coordinating networks among regional economic actors such as firms, universities and public research institutes. The regional policy as a way in which increase national competitiveness in Korea is also the establishment of innovative clusters based on regional and industrial characteristics. However, the main problem with building the innovative cluster is the reduction of policy effectiveness due to duplicated supporting and coordinating institutes and institutions established by the each central administration and local governments, aimed at facilitating networks among regional economic actors. In this context, the article suggests that there is a need to build a regional central network agent by designing an organic operating system for the effective management of each network agent in accordance with the process from R&D to commercialization, i.e. an encompassed supporting system, on the basis of benchmarking the KSP operating system in Japan.

• The KSFM Journal of Fluid Machinery
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• v.19 no.3
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• pp.19-24
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• 2016

Oil sands are a mixture of sand, clay, and a high-viscosity petroleum called bitumen. Steam-Assisted Gravity Drainage (SAGD) is the most viable and environmentally safe recovery technology for extracting bitumen. It extracts the viscosity-lowered bitumen by high pressure, high temperature steam injected into the bitumen reservoir. The steam is produced at the Central Processing Facility (CPF). Typically, more than 90% of the energy consumed in producing bitumen are used to generate the steam. Fuels are employed in the process, which cause economic and environmental problems. This paper explores the retrofit of heat exchanger network to reduce the usage of hot and cold utilities. The hot and cold utilities are reduced respectively 6% and 37.3% which in turn resulted in 5.3% saving of total annual cost by improving the existing heat exchanger network of the CPF.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.971-976
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• 2000

The main objective of this paper is to present the rain cell size distribution observed during squall line episodes in the Sudano-Sahelian region. The used data were collected during the EPSAT Program [Etude des Precipitation par SATellite (Satellites Study of Precipitation)] which has been developed since 1958, on an experimental area located near Niamey, Niger (2 10′32"E, 13 28′38"N). The data were obtained with a C-band radar and a network composed of approximately 100 raingages over a 10,000 $\textrm{km}^2$. In this work a culling of the squall line episodes was made for the 1992 rainy season. After radar data calibration using the raingage network a number of PPI (Plan Position Indicator) images were generated. Each image was then treated in order to obtain a series of radar reflectivity (Z) maps. To describe the cell distribution, a contouring program was used to analyze the areas with rain rate greater than or equal to the contour threshold (R$\geq$$\tau$). 24700 contours were generated, where each iso-pleth belongs to a predefined threshold. Computing each cell surface and relating its area to an equi-circle (a circle having the same area as the cell), a statistical analysis was made. The results show that the number of rain cells having a given size is an inverse exponential function of the equivalent radius. The average and median equivalent radii ate 1.4 and 0.69 In respectively. Implications of these results for the precipitation estimation using threshold methods are discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.378-382
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• 2006

This paper presents an approach to detect premature ventricular contractions(PVC) using the neural network with weighted fuzzy membership functions(NEWFM). NEWFM classifies normal and PVC beats by the trained weighted fuzzy membership functions using wavelet transformed coefficients extracted from the MIT-BIH PVC database. The two most important coefficients are selected by the non-overlap area distribution measurement method to minimize the classification rules that show PVC classification rate of 99.90%. By Presenting locations of the extracted two coefficients based on the R wave location, it is shown that PVC can be detected using only information of the two portions.

• Journal of Construction Engineering and Project Management
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• v.2 no.4
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• pp.11-19
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• 2012

Construction supply chain management (CSCM) has become one of the critical factors that determine the success of a construction project as it becomes increasingly complicated and mega-sized. Particularly for high-rise or mega-sized building construction, just-in-time supply chain management is required due to lack of storage space and effective logistics for construction components and materials at a construction site. Despite the fact that research and development of radio frequency identification (RFID) and wireless sensor network (WSN) technology have been performed, construction project managers still need to carry mobile devices and check material and component flow at each stage of the supply chain process. This research proposes that the equipment used in the construction supply chain process, such as movers, trailers, gates, and hoists, can become main actors in the supply chain process using RFID and WSN technologies. And the proposed equipment and process focused on a solution to the redundancy identification problem, which has been observed in operations that use RFID/WSN-based processes for construction logistics. This paper also presents issues identified through verification and validation of the research results and proposes further studies.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.881-886
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• 2018

Over the last several decades, the advances in computer engineering technology have led a new paradigm of data-intensive research in the field of scientific applications. A collaborative work environment for storing, sharing and analyzing data is required for researchers of geographical distance. The Korean government supports the Research & Education network(KREONET) and the Global Science experimental Data hub Center(GSDC) to strengthen the nation's competitiveness. The KREONET has upgraded its backbone to 100Gbps to accommodate demand to transfer data fast among the global major experimental sites. This paper introduces the test result between high performance nodes reserved for big data transfer.

• Steel and Composite Structures
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• v.39 no.4
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• pp.471-491
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• 2021

In this study, we estimate the ultimate load of rectangular concrete-filled steel tubes (CFST) by developing a novel hybrid predictive model (ANN-BCMO) which is a combination of balancing composite motion optimization (BCMO) - a very new optimization technique and artificial neural network (ANN). For this aim, an experimental database consisting of 422 datasets is used for the development and validation of the ANN-BCMO model. Variables in the database are related with the geometrical characteristics of the structural members, and the mechanical properties of the constituent materials (steel and concrete). Validation of the hybrid ANN-BCMO model is carried out by applying standard statistical criteria such as root mean square error (RMSE), coefficient of determination (R²), and mean absolute error (MAE). In addition, the selection of appropriate values for parameters of the hybrid ANN-BCMO is conducted and its robustness is evaluated and compared with the conventional ANN techniques. The results reveal that the new hybrid ANN-BCMO model is a promising tool for prediction of the ultimate load of rectangular CFST, and prove the effective role of BCMO as a powerful algorithm in optimizing and improving the capability of the ANN predictor.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.206-211
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• 2021

Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: "Sensing opinions and analyzing feelings". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising.

• Journal of the Korean Ceramic Society
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• v.49 no.5
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• pp.475-483
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• 2012

High capacitance X5R MLCCs based on $BaTiO_3$ ceramic dielectric layers exhibit a single broad, asymmetric arc shape impedance and modulus response over the wide frequency range between 1 MHz to 0.01 Hz. Analysis according to the conventional brick-layer model for polycrystalline conductors employing a series connection of multiple RC parallel circuits leads to parameters associated with large errors and of little physical significance. A new parametric impedance model is shown to satisfactorily describe the experimental spectra, which is a parallel network of one resistor R representing the DC conductivity thermally activated by 1.32 eV, one ideal capacitor C exactly representing bulk capacitance, and a constant phase element (CPE) Q with complex capacitance $A(i{\omega})^{{\alpha}-1}$ with ${\alpha}$ close to 2/3 and A thermally activated by 0.45 eV or ca. 1/3 of activation energy of DC conductivity. The feature strongly indicate the CK1 model by J. R. Macdonald, where the CPE with 2/3 power-law exponent represents the polarization effects originating from mobile charge carriers. The CPE term is suggested to be directly related to the trapping of the electronic charge carriers and indirectly related to the ionic defects responsible for the insulation resistance degradation.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.447-458
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• 2008

In this paper, we address an efficient processing scheme for k-nearest neighbor queries to retrieve k static objects in road network databases. Existing methods cannot expect a query processing speed-up by index structures in road network databases, since it is impossible to build an index by the network distance, which cannot meet the triangular inequality requirement, essential for index creation, but only possible in a totally ordered set. Thus, these previous methods suffer from a serious performance degradation in query processing. Another method using pre-computed network distances also suffers from a serious storage overhead to maintain a huge amount of pre-computed network distances. To solve these performance and storage problems at the same time, this paper proposes a novel approach that creates an index for moving objects by approximating their network distances and efficiently processes k-nearest neighbor queries by means of the approximate index. For this approach, we proposed a systematic way of mapping each moving object on a road network into the corresponding absolute position in the m-dimensional space. To meet the triangular inequality this paper proposes a new notion of average network distance, and uses FastMap to map moving objects to their corresponding points in the m-dimensional space. After then, we present an approximate indexing algorithm to build an R*-tree, a multidimensional index, on the m-dimensional points of moving objects. The proposed scheme presents a query processing algorithm capable of efficiently evaluating k-nearest neighbor queries by finding k-nearest points (i.e., k-nearest moving objects) from the m-dimensional index. Finally, a variety of extensive experiments verifies the performance enhancement of the proposed approach by performing especially for the real-life road network databases.