• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.69-79
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• 2013

This paper presents a two-stage geostatistical integration approach that aims at downscaling of coarse scale remote sensing data. First, downscaling of the coarse scale sedoncary data is implemented using area-to-point kriging, and this result will be used as trend components on the next integration stage. Then simple kriging with local varying means that integrates sparse precise observation data with the downscaled data is applied to generate thematic information at a finer scale. The presented approach can not only account for the statistical relationships between precise observation and secondary data acquired at the different scales, but also to calibrate the errors in the secondary data through the integration with precise observation data. An experiment for precipitation mapping with weather station data and TRMM (Tropical Rainfall Measuring Mission) data acquired at a coarse scale is carried out to illustrate the applicability of the presented approach. From the experiment, the geostatistical downscaling approach applied in this paper could generate detailed thematic information at various finer target scales that reproduced the original TRMM precipitation values when upscaled. And the integration of the downscaled secondary information with precise observation data showed better prediction capability than that of a conventional univariate kriging algorithm. Thus, it is expected that the presented approach would be effectively used for downscaling of coarse scale data with various data acquired at different scales.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.423-427
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• 2002

Contrary to the traditional text-based information, 4S(GIS,GNSS,SIIS,ITS) information can contribute to the citizen's welfare in upcoming era. Recently, GSIS(Geo-Spatial Information System) has been applied and stressed out in various fields. As analyzed the data from GSIS arena, the position information of objects and targets is crucial and critical. Therefore, several methods of getting and knowing position are proposed and developed. From this perspective, Position collection and processing are the heart of 4S technology. We develop 4S-Van that enables real-time acquisition of position and attribute information and accurate image data in remote site. In this study, the configuration of 4S-Van equipped with GPS, INS, CCD and eye-safe laser scanner is shown and the merits of DGPS/INS integration approach for geo-referencing is briefly discussed. The algorithm of DGPS/INS integration fur determination of six parameters of motion is eccential in the 4S-Van to avoid or simplify the complicated computation such as photogrammetric triangulation. 4S-Van has the application of Laser-Mobile Mapping System for three-dimensional data acquisition that merges the texture information from CCD camera. The technique is also applied in the fields of virtual reality, car navigation, computer games, planning and management, city transportation, mobile communication, etc.

• Journal of Sport and Applied Science
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• v.4 no.4
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• pp.1-6
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• 2020

Purpose: The purpose of this study is to identify the effect of 24-week sensory integration activity training on fitness of children with intellectual disability. Research design, data, and methodology: The subjects were 10 children with intellectual disability, 60 min training of sensory integration activity for 24 weeks. Obesity, cardiovascular endurance, muscular strength and muscle endurance were measured pre and post training. Frist, characteristics of subjects were measured with age, height, weight, IQ and SQ. Second, the subjects then performed sensory integration activity training for 24 weeks. Last, weight, strength, endurance, cardiovascular endurance and flexibility were measured. Data were calculated for average and standard deviation by SPSS 25.0 statistic program, and dependent sample t-test was processed to analyze the change between pre and post training. All statistical significance level was set to 0.5. Results: The result was shown that weight, strength and endurance changes between pre and post were significant. However, cardiovascular endurance, flexibility changes between pre and post were not significant. Conclusions: The lack of training frequency of 60 minute per week were acknowledged per week from this result. In future research, increased intensity and frequency are need for an in-depth and meaningful study and the measured data can be used basic information for the study.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.622-625
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• 2004

This paper presents multi-source spatial data integration models based on probability theory for landslide hazard assessment. Four probabilistic models such as empirical likelihood ratio estimation, logistic regression, generalized additive and predictive discriminant models are proposed and applied. The models proposed here are theoretically based on statistical relationships between landslide occurrences and input spatial data sets. Those models especially have the advantage of direct use of continuous data without any information loss. A case study from the Gangneung area, Korea was carried out to quantitatively assess those four models and to discuss operational issues.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.595-600
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• 1991

A competitive automated manufacturing system integrates the various control processes and data used in service of products. design, manufacturing, and, sale. CIM is a way to achieve such integration through computers and computational techniques in manufacturing, planning, and design. Developing effective CIM architectures is hampered by integration problems. The key to resolving these problems lies in a better understanding of manufacturing function and how it is related to other manufacturing functions. Integration of CIM environment requires coordinated solutions to data management problems for individual application system as well as for exchange of data between these applications. This requires a common framework for data management throughout the CIM environment. This paper discusses the design paradigm as a framework for this purpose. Designing an organizational structure to meet those goals invloves 1) analyzing the functions through functional decomposition, 2) developing a data model to coordinate functions. As a result, we propose an object-oriented design methodology for manufacturing information system.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.2
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• pp.115-129
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• 1991

An ecconomically competitive automated manufacturing system integrates the various control processes and data used in design, manufacturing, sale and service of products. CIM is a way to achieve such integration through computers and computational techniques in design, planning, and manufacturing. Developing effective CIM architectures is hampered by integration problems. The key to resolving these problems lies in a better understanding of manufacturing function and how it is related to other manufacturing functions. Integration of CIM environment requires coordinated solutions to data management problems for individual application system as well as for exchange of data between these applications. This requires a common framework for data management throughout the CIM environment. This paper discusses the design paradigm as a framework for this purpose. Designing an organizational structure to meet those goals involves 1) analyzing the functions through functional decomposition, 2) developing a data model to coordinate functions. As a result, we propose an object-oriented design methodology for manufacturing information system.

• Journal of Information Technology Applications and Management
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• v.26 no.2
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• pp.13-26
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• 2019

The purpose of this study is to examine the effect of each of the two technology acceptance factors(employees' attitude toward smart factory technology, and ease of smart factory technology use) on the introduction level of each of the three smart factory technologies (manufacturing big data technology, automation technology, and supply chain integration technology), and in turn, the effect of each of the three smart factory technologies on manufacturing performance. This study employed PLS statistics software package to empirically validate a structural equation model with survey data from 100 domestic small-and medium-sized manufacturing firms (SMMFs). The analysis results revealed the followings. First, it is founded that employees' attitude toward smart factory technology influenced all of the three smart factory technology introduction levels in a positive manner. In particular, SMMFs of which employees had more favorable attitude toward smart factory technology tended to increase introduction levels of both automation technology and supply chain integration technology more than in the case of manufacturing big data technology. Second, ease of smart factory technology use also had a positive impact on each of the three smart factory technology introduction levels, respectively. A noteworthy finding is this : SMMFs which perceived smart factory technology as easier to use would like to elevate the introduction level of manufacturing big data technology more than in the cases of either automation technology or supply chain integration technology. Third, smart factory technologies such as automation technology and supply chain integration technology had affirmative impacts on manufacturing performance of SMMFs. These results shed some valuable insights on the introduction of smart factory technology : The success of smart factory heavily depends on organization-and people-related factors such as employees' attitude toward smart factory technology and employees' perceived ease of smart factory technology use.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.497-500
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• 2005

Research and development of remote sensing technique is necessary so that more accurate and extensive information may be obtained. To achieve this goal, the synthesized technique which integrates the high resolution optic and SAR image, and topographical information was examined to investigate the quantitative/qualitative characteristics of the Earth's surface environment. For this purpose, high-precision DEMs of Jeju-Island was generated and data fusion algorithm was developed in order to integrate the multi-spectral optic and polarimetric SAR image. Three dimensional land-cover and two dimensional soil moisture maps were generated conclusively so as to investigate the Earth's surface environments and extract the geophysical parameters.

• Journal of Distribution Science
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• v.14 no.4
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• pp.33-38
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• 2016

Purpose - This study purposes to analyze the impact of regional economic integration and macroeconomic on Indonesian FDI inflows. Research design, data, and methodology - Data were collected from bilateral relation between Indonesia and 21 home countries whose dominant share FDI to Indonesia from 2005 to 2013. Analysis method was conducted by panel gravity modeI to find the impact of regional economic integration and macroeconomic on Indonesian FDI inflows. Results - The empirical results show that GDP of the home country and Indonesia have a positive impact on Indonesia FDI. Distance and home country real interest rate have a negative impact on Indonesia FDI. Economic integration of European Union (EU) and Indonesia's cooperation with Japan in ASEAN-Japan Comprehensive Economic Partnership (AJCEP) have created impact of investment creation on Indonesia FDI, unfortunately, economic integration of ASEAN has created impact of investment diversion on Indonesian FDI. Conclusions - In order to increase FDI inflow to Indonesia, Indonesia government should improve the physical and social infrastructures to drive the productivity and economic efficiency. It will increase the GDP and also attract more investors. Low interest rate policy should be considered.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.422-430
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• 2008

Data integration is techniques to combine heterogeneous data from different sources, and to allow users to transparently access all data from multiple sources via a single view. The difficulty with data integration is data heterogeneity (i.e. schema heterogeneity, semantic heterogeneity). Richer semantics of data is a major factor in resolving conflicts among heterogeneous data sources. As UML class model represents only schema-based semantics of data, alternative methods such as ontology is useful for representing additional semantics. This paper proposes a method for integrating two data sources with UML class models by using an analysis of their ontologies. In our framework, ontology will be applied to describe semantics of data in each source. Then the ontologies are analysed and compared to determine their similarities and differences. The result of the comparison is used to devise an integrated ontology that will enable querying on the integrated information.