• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.1129-1143
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• 2023

Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.

• Journal of Information Technology Applications and Management
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• v.17 no.3
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• pp.1-24
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• 2010

Most of enterprises depend on a data modeler during developing their management information systems. In formulating business requirements for information systems, they widely and naturally use the interview method between a data modeler and a field worker. But, the discrepancy between both parties would certainly cause information loss and distortion that lead to let the systems not faithful to real business works. To improve or avoid modeler-dependant data modeling process, many automated data design CASE tools have been introduced. However, since most of traditional CASE tools just support drawing works for conceptual data design, a data modeler could not generate an ERD faithful to real business works and a user could not use them without any knowledge on database. Although some CASE tools supported conceptual data design, they still required too much preliminary database knowledge for a user. Against these traditional CASE tools, we proposed a Requirement-Oriented Entity Relationship Model for automated data design tool, called ROERM. Based on Non-Stop Methodology, ROERM adopts inner systematic modules for complete and sound ERD that is faithful to real field works, where modules are composed of interaction modules with a user, rules of schema operations and sentence translations. In addition to structure design of ROERM, we also devise detailed algorithms and perform an experiment for a case study.

• Korean Journal of Geomatics
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• v.4 no.2
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• pp.39-45
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• 2004

Building reconstruction attempts to generate geometric and radiometric models of existing buildings usually from sensory data, which have been traditionally aerial or satellite images, more recently airborne LIDAR data, or the combination of these data. Extensive studies on building reconstruction from these data have developed some competitive algorithms with reasonable performance and some degree of automation. Nevertheless, the level of details and completeness of the reconstructed building models often cannot reach the high standards that is now or will be required by various applications in future. Hence, the use of terrestrial sensory data that can provide higher resolution and more complete coverage has been intensively emphasized. We developed a fusion framework for building reconstruction from terrestrial sensory data, that is, points from a laser scanner, images from digital camera, and absolute coordinates from a total station. The proposed approach was then applied to reconstructing a building model from real data sets acquired from a large complex existing building. Based on the experimental results, we assured that the proposed approach cam achieve high resolution and accuracy in building reconstruction. The proposed approach can effectively contribute in developing an operational system producing large urban models for 3D GIS with reasonable resources.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.180-180
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• 2023

To improve global risk management, understanding the characteristics and distribution of precipitation is crucial. However, obtaining spatially and temporally resolved climatic data remains challenging due to sparse gauge observations and limited data availability, despite the use of satellite and reanalysis products. To address this challenge, merging available precipitation products has been introduced to generate spatially and temporally reliable data by taking advantage of the strength of the individual products. However, most of the existing studies utilize all the available products without considering the varying performances of each dataset in different regions. Comprehensively considering the relative contributions of each parent dataset is necessary since their contributions may vary significantly and utilizing all the available datasets for data merging may lead to significant data redundancy issues. Hence, for this study, we introduce a site-specific precipitation merging method that utilizes the Quadruple Collocation (QC) approach, which acknowledges the existence of error-cross correlation between the parent datasets, to create a high-resolution global daily precipitation data from 2001-2020. The performance of multiple gridded precipitation products are first evaluated per region to determine the best combination of quadruplets to be utilized in estimating the error variances through the QC approach and computation of merging weights. The merged precipitation is then computed by adding the precipitation from each dataset in the quadruplet multiplied by each respective merging weight. Our results show that our approach holds promise for generating reliable global precipitation data for data-scarce regions lacking spatially and temporally resolved precipitation data.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.38-43
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• 2015

This paper describes a GPS signal generator that can generate multiple satellite signals in real time at the RF level. It realizes the verified software algorithm on a FPGA. The algorithm models orbits and environmental errors such as ionospheric and tropospheric multipath. The position of a simulated receiver is one of simulation parameters. The hardware which consists of a digital logic board and an analog board can generate 16 simulated satellites signals at the same time. The users can generate spoofing signals and jamming signals as well as satellite signals by using the windows-based control software. In addition, the software provides GIS-based simulation scenarios editing tools. We verified the generator by using commercial receivers. As an application, we configured generators as indoor positioning systems and tested them in a building. To improve the accuracy of indoor systems is our further study.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.147-154
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• 2002

In bulding Intelligent Agent Societies (IAS), it is very important to design and implement coordination in accordance with the known requirement and anticipated working conditions. Coordination consists of a set of mechanisms necessary for the effective operation of IAS. Currently, there is little theoretical support that could help in this research is to generate an empirically-based solving systems in which all agent share an identical goal structure and fully cooperate. And we developed a simulation model called "P-System" which produces basic data to be used for statistical analysis to generate a theory of coordination. Coordination among agent in the P-System is dependent on 23 control variables calld TEs(tweakable emtities.)And the level of coordination is represennted by an independent variabe called QMC (Quality Measure Coordination) expressed in numerical terms according tn the definiion of this study. Also, we have studied how to select unbiased subset from the huge total experimental space of the P-System and how to decide the scale of the subset.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.216-219
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• 2004

In this study, the concept and techniques to generate the level lA, lB and 2A image products have been reviewed. In particular, radiometric and geometric corrections and bands registration used to generate level lA, lB and 2A products have been focused in this study. Radiometric correction is performed to take into account radiometric gain and offset calculated by compensating the detector response non-uniformity. And, in order to compensate satellite altitude, attitude, skew effects, earth rotation and earth curvature, some geometric parameters for geometric corrections are computed and applied. Bands registration process using the matching function between a geometry, which is called 'reference geometry', and another one which is corresponds to the image to be registered is applied to images in case of multi-spectral imaging mode. In order to generate level-lA image products, a simple radiometric processing is applied to a level-0 image. Level-lB image has the same radiometry correction as a level-lA image, but is also issued from some geometric corrections in order to compensate skew effects, Earth rotation effects and spectral misregistration. Level-2A image is generated using some geo-referencing parameters computed by ephemeris data, orbit attitudes and sensor angles. Level lA image is tested by visual analysis. The difference between distances calculated level 1 B image and distances of real coordinate is tested. Level 2A image is tested Using checking points.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.6
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• pp.201-214
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• 2014

In this paper, we propose a test case generation method adequate to destructive test of the BLDC(Brush Less Direct Current) motor controller used for the MDPS(Motor Driven Power Steering) system embedded in an automobile. The proposed method is a modified CTM(Classification Tree Method). CTM generates test cases assuming that all inputs are equally important. Therefore, it is very hard to generate test cases for extreme situations. To overcome the drawback and generate test cases specialized for destructive test. a modified CTM that compensates the limitation of traditional CTM is proposed. The proposed method has an advantage that it can intensively generate the test scenarios adequate to extreme situations by combining the test cases generated by the transitional CTM the while keeping the merit of the traditional CTM. The test scenarios for destructive test for the MDPS system embedded in a commercial automobile are generated utilizing the proposed method. The effectiveness of the proposed algorithm is verified through the test.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.533-542
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• 2006

Lidar point clouds provide three dimensional information of terrain surface and have a great advantage to generate precise digital elevation model (DEM), particularly over forested area where some laser signals are transmitted to vegetation canopy and reflected from the bare ground. This study initially investigates the characteristics of lidar-derived height information as related to vertical structure of forest stands. Then, we propose a new filtering method to separate ground points from Lidar point clouds, which is a prerequisite process both to generate DEM surface and to extract biophysical information of forest stands. Laser points clouds over the forest stands in central Korea show that the vertical distribution of laser points greatly varies by the stand characteristics. Based on the characteristics, the proposed filtering method processes first and last returns simultaneously without setting any threshold value. The ground points separated by the proposed method are used to generate digital elevation model, furthermore, the result provides the possibilities to extract other biophysical characteristics of forest.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.379-381
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• 2008

TETRA(Terrestrial Trunked Radio) is a digital trunked radio standard developed by the ETSI(European Telecommunications Standards Institute). Currently, TETRA was set Digital TRS in electric power If wireless backbone network. In this time, we use many company's TETRA modem. So, TETRA modem performance evaluation is very important. TETRA modem use two type of Data transfer mode. One is Packet Data using UDP/IP. and the other is SDS(Short Data Service). In this paper, We generate Packet Data using Traffic Generator module. Packet Data transfer 1000 times each 10 bytes to 400 bytes. We analyze transmission delay time, success rate and standard deviation.