• Journal of Internet Computing and Services
• /
• v.21 no.3
• /
• pp.41-51
• /
• 2020

EDISON is a web-based platform that provides easy and convenient use of simulation software on high-performance computers. One of the most important roles of a computational science platform, such as EDISON, is to post-process and represent the simulation results data so that the user can easily understand the data. We interviewed EDISON users and collected requirements for post-processing and represent of simulation results, which included i) flexible data representation, ii) supporting various data representation components, and iii) flexible and easy development of view template. In previous studies, it was difficult to develop or contribute data representation components, and the view templates were not able to be shared or recycled. This causes a problem that makes it difficult to create ecosystems for the representation tool development of numerous simulation software. EDISON-VIEW is a framework for post-processing and representing simulation results produced from the EDISON platform. This paper proposes various methods used in the design and development of the EDISON-VIEW framework to solve the above requirements and problems. We have verified its usefulness by applying it to simulation software in various fields such as material, computational fluid dynamics, computational structural dynamics, and computational chemistry.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.14 no.1
• /
• pp.26-33
• /
• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pas- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this prediction system was acquired $\pm$3.2% error range.

• Spatial Information Research
• /
• v.19 no.2
• /
• pp.19-28
• /
• 2011

Three dimensional modeling for seafloor topography is essential to monitoring displacements in underwater structures as well as all sorts of disasters along the shore. MBES is a system that is capable of high-density water depth measurement for seafloor topography and is in broad uses for gathering 3D data and detecting displacements. MBES data, however, contain random errors that take place in the equipment offset and surveying process and require systematic researches on the correction of wrong depth measurements. Thus this study set out to propose a post-processing technique to eliminate an array of random errors taking place after equipment offset correction and basic noise correction in the MBES system and analyze its applicability to seafloor topography modeling by applying it to the subject area.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.10 no.1
• /
• pp.84-91
• /
• 2007

As GPS equipments improve, one can acquire GPS data easily in the field. To obtain precise and accurate coordinates, however, post processing is additionally required and the processing needs high degree of skills. Besides, it is very common that we cannot operate processing softwares in the field because the required system environment is usually not prepared. The aim of this study is the development of an internet-based GPS data processing service. For post processing, we used GIPSY developed by JPL. It has many advantages such as obtaining coordinates quickly by using precise or predicted ephemeris. This service proceeds as following orders by interlocking GIPSY software and internet service which is operated on a Linux platform: Users upload the raw data file on the internet, then GIPSY runs automatically and then the user gets the result in the field. We use an Apache web server as the hosting program and PHP scripts are used in coding web pages. The total processing time including data-uploading was around 30 seconds for a 24-hour data with a 30-second sampling rate.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.8B
• /
• pp.1518-1531
• /
• 1999

The reconstructed images from highly compressed MPEG or H.263 data have noticeable image degradations, such as blocking artifacts near the block boundaries, corner outliers at cross points of blocks, and ringing noise near image edges, because the MPEG or H.263 quantizes the transformed coefficients of 8$\times$8 pixel blocks. A post-processing algorithm has been proposed by authors to reduce quantization effects, such as blocking artifacts, corner outliers, and ringing noise, in MPEG-decompressed images. Our signal-adaptive post-processing algorithm reduces the quantization effects adaptively by using both spatial frequency and temporal information extracted from the compressed data. The blocking artifacts are reduced by one-dimensional (1-D) horizontal and vertical low pass filtering (LPF), and the ringing noise is reduced by two-dimensional (2-D) signal-adaptive filtering (SAF). A comparison study of the subjective quality evaluation using modified single stimulus method (MSSM), the objective quality evaluation (PSNR) and the computation complexity analysis between the signal-adaptive post-processing algorithm and the MPEG-4 VM (Verification Model) post-processing algorithm is performed by computer simulation with several MPEG-4 image sequences. According to the comparison study, the subjective image qualities of both algorithms are similar, whereas the PSNR and the comparison complexity analysis of the signal-adaptive post-processing algorithm shows better performance than the VM post-processing algorithm.

• The KIPS Transactions:PartB
• /
• v.10B no.1
• /
• pp.33-40
• /
• 2003

Data mining plays an important role in a knowledge discovery process and various algorithms of data mining can be selected for the specific purpose. Most of traditional hierachical clustering methode are suitable for processing small data sets, so they difficulties in handling large data sets because of limited resources and insufficient efficiency. In this study we propose a hybrid neural networks clustering technique, called PPC for Pre-Post Clustering that can be applied to large data sets and find unknown patterns. PPC combinds an artificial intelligence method, SOM and a statistical method, hierarchical clustering technique, and clusters data through two processes. In pre-clustering process, PPC digests large data sets using SOM. Then in post-clustering, PPC measures Similarity values according to cohesive distances which show inner features, and adjacent distances which show external distances between clusters. At last PPC clusters large data sets using the simularity values. Experiment with UCI repository data showed that PPC had better cohensive values than the other clustering techniques.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.3
• /
• pp.242-250
• /
• 2003

We propose the monitoring system scheme for the CPS/INS integrated navigation system. The design requirements of the monitoring system are suggested and the software scheme based on GUI is proposed. The proposed monitoring system consists of an I/O interface part, a navigation data display part, and a post-processing part. The I/O interface part is responsible for data communication between the monitoring system and a navigation computer unit. The navigation data display part provides various display methods to show the navigation data to user in real-time. The post-processing part collects the navigation data to analyze the performance of navigation system. The proposed monitoring system software was developed using the Visual C++ programming language and a van test was carried out to demonstrate the real-time operation of the monitoring system. The test result shows that the proposed monitoring system can be effectively applied to the CPS/INS integrated navigation system.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.20 no.4
• /
• pp.482-490
• /
• 2017

The radar signal processing procedure is divided into the pre-processing such as frequency down converting, down sampling, pulse compression, and etc, and the post-processing such as doppler filtering, extracting target information, detecting, tracking, and etc. The former is generally designed using FPGA because the procedure is relatively simple even though there are large amounts of ADC data to organize very quickly. On the other hand, in general, the latter is parallel processed by multiple DSPs because of complexity, flexibility and real-time processing. This paper presents the radar signal processor design using FPGA which includes not only the pre-processing but also the post-processing such as doppler filtering, bore-sight error, NCI(Non-Coherent Integration), CFAR(Constant False Alarm Rate) and etc.

• Spatial Information Research
• /
• v.18 no.5
• /
• pp.1-11
• /
• 2010

Since January 2009, Seoul Metro Government(SMG) is operating own Network RTK Systems connecting four(4) GNSS Reference Stations which are installed inside Seoul Metro City area. SMG is currently providing VRS data service via wireless internet for Network-RTK and RINEX data observed from GNSS Reference Stations. This paper will discuss utilization of data available from SMG Network-RTK System for various applications, and present the test results on practicalities of Virtual RINEX data. For the utilization of data available from SMG Network- RTK system, 1)NTRIP data delivery of GNSS realtime observables streaming and converting to RINEX at receiving side, 2) monitoring deformation of bulky structures using GNSS observation were discussed. In addition to those discussion, 3) broadcasting VRS correction data for job site via radio modem after acquiring such correction data on-line using NTRIP based GNSS Internet Radio from SMG Network-RTK System were introduced. For the test results on practicalities of Virtual RINEX data, 1) the post-processing results of the GNSS observation data on a certain point with GNSS Reference Station data have been compared to the post-processing results of Virtual RINEX data on the same point generated from SMG Network-RTK System, and 2) VRS RTK positioning results for a certain point and post-processing results of Virtual RINEX data for the point were compared. The results showed only a few mm difference, and the high possibility for using Virtual RINEX data for post-processing applications.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.6
• /
• pp.261-268
• /
• 2015

In spoken chatting systems, users'spoken queries are converted to text queries using automatic speech recognition (ASR) engines. If the top-1 results of the ASR engines are incorrect, these errors are propagated to the spoken chatting systems. To improve the top-1 accuracies of ASR engines, we propose a post-processing model to rearrange the top-n outputs of ASR engines using a ranking support vector machine (RankSVM). On the other hand, a number of chatting sentences are needed to train chatting systems. If new chatting sentences are not frequently added to training data, responses of the chatting systems will be old-fashioned soon. To resolve this problem, we propose a data collection model to automatically select chatting sentences from TV and movie scenarios using a support vector machine (SVM). In the experiments, the post-processing model showed a higher precision of 4.4% and a higher recall rate of 6.4% compared to the baseline model (without post-processing). Then, the data collection model showed the high precision of 98.95% and the recall rate of 57.14%.