• Journal of Environmental Impact Assessment
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• v.20 no.3
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• pp.337-348
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• 2011

Urban environmental problem became one of major issues during its urbanization processes. Environmental impacts are assessed during recent urban planning and development. Though the environmental impact assessment considers meteorological impact as a minor component, changes in wind environment during development can largely affect the distribution pattern of air temperature, humidity, and pollutants. Impact assessment of local wind is, therefore, a major element for impact assessment prior to any other meteorological impact assessment. Computational Fluid Dynamics (CFD) models are utilized in various fields such as in wind field assessment during a construction of a new building and in post analysis of a fire event over a mountain. CFD models require specially formatted input data and produce specific output files, which can be analyzed using special programs. CFD's huge requirement in computing power is another hurdle in practical use. In this study, a CFD model and related software processors were automated and integrated as a microscale wind environmental impact assessment system. A supercomputer system was used to reduce the running hours of the model. Input data processor ingests development plans in CAD or GIS formatted files and produces input data files for the CFD model. Output data processor produces various analytical graphs upon user requests. The system was used in assessing the impacts of a new building near an observatory on wind fields and showed the changes by the construction visually and quantitatively. The microscale wind assessment system will evolve, of course, incorporating new improvement of the models and processors. Nevertheless the framework suggested here can be utilized as a basic system for the assessment.

• Journal of Korea Water Resources Association
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• v.36 no.1
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• pp.117-128
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• 2003

The objectives of this study are to develop the total maximum daily loads simulation system, TOLOS that is capable of estimating annual nonpoint source pollution from small watersheds, to monitor the hydrology and water quality of the Balkan HP#6 watershed, and to validate TOLOS with the field data. TOLOS consists of three subsystems: the input data processor based on a geographic information system, the models, and the post processor. Land use pattern at the tested watershed was classified from the Landsat TM data using the artificial neutral network model that adopts an error back propagation algorithm. Paddy field components were added to SWAT model to simulate water balance at irrigated paddy blocks. SWAT model parameters were obtained from the GIS data base, and additional parameters calibrated with field data. TOLOS was then tested with ungauged conditions. The simulated runoff was reasonably good as compared with the observed data. And simulated water quality parameters appear to be reasonably comparable to the field data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.425-435
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• 2017

Structural analysis is used not only for large enterprises, but also for small and medium sized ones, as a necessary procedure for strengthening the certification process for product delivery and shortening the time in the process from concept design to detailed design. Open-source solvers that can be used atlow cost differ from commercial solvers. If there is a problem with the input data, such as with the grid, errors or failures can occur in the calculation step. In this paper, we propose a pre- and post-processor that can be easily applied to the analysis of mechanical structural problems by using the existing structural analysis open source solver (Caculix, Code_Aster). In particular, we propose algorithms for analyzing different types of data using open source solvers in order to extract and generate accurate information,such as 3D models, grids and simulation conditions, and develop and apply information analysis. In addition, to improve the accuracy of open source solvers and to prevent errors, we created a grid that matches the solver characteristics and developed an automatic healing function for the grid model. Finally, to verify the accuracy of the system, the verification and utilization results are compared with the software used.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.1
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• pp.156-161
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• 1992

In this research a monitoring system for turning using NC information and the current of feed motor as a monitoring signal was developed. The overall system consists of modules such as learning process, NC data transmission, generation of forecast information, signal acquisition, monitoring and post process. In the learning process, the reference data and the cutting force equation necessary for monitoring are obtained from the accumulated monitoring results. In the generation of forecast information, the information of forecasted cutting forces is acquired from the cutting force equation and NC program and appended to each NC block as a monitor code. Reliability of monitoring is improved by using the monitor code in the real-time monitoring. Monitoring module is divided into two parts : the off-line monitoring where errors of NC program are checked and the on-line monitoring where the level of motor current is monitored during cutting operations. If the actual current level exceeds the limit value provided by the monitor code in the level monitoring, it is recognized as abnormal. In the event of abnormal status, the post processor sends the emergency stop signal to NC controller to stop the operation. Actual experiments have shown that the developed monitoring system works well.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.1-6
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• 2000

In this paper, the hybrid system of HMM and neural network is proposed and show better recognition rate of the post-process procedure which minimizes the process error of recognition than that of HMM(Hidden Markov Model) only used. After the HMM training by training data, testing data that are not taken part in the training are sent to HMM. The output probability from HMM output by testing data is used for the training data of the neural network, post processor. After neural network training, the hybrid system is completed. This hybrid system makes the recognition rate improvement of about $4.5\%$ in MLP and about $2\%$ in RBFN and gives the solution to training time of conventional hybrid system and to decrease of the recognition rate due to the lack of training data in real-time speech recognition system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1160-1167
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• 2013

Web based simulation service is utilized to computationally analyze various phenomena in real world according to the progress of network and computing technology. In this paper, we present an improvement and utilization of e-AIRS (e-Science Aerospace Integrated Research System). e-AIRS, has been utilized to support web based CFD simulation service since 2008. has some problems such as stable system, pre processing, post processing. To solver this problem, we improved e-AIRS such as distributed service processing, personal simulation job assignment control, and faster data loading. After improvement, although users increase from 110 to 606, the priority of user requirements is changed from stable system to pre/post processor. User requirements and statistics about e-AIRS simulation service for each semester is analyzed to support more stable and comfortable service.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.463-471
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• 2021

Since 2016, National Institute of Standards and Technology (NIST) has been conducting a post quantum cryptography standardization project in preparation for a quantum computing environment. Three rounds are currently in progress, and most of the candidates (5/7) are lattice-based. Lattice-based post quantum cryptography is evaluated to be applicable even in an embedded environment where resources are limited by providing efficient operation processing and appropriate key length. Among them, SABER KEM provides the efficient modulus and Toom-Cook to process polynomial multiplication with computation-intensive tasks. In this paper, we present the optimized implementation of evaluation and interpolation in Toom-Cook algorithm of SABER utilizing ARM/NEON in ARMv8-A platform. In the evaluation process, we propose an efficient interleaving method of ARM/NEON, and in the interpolation process, we introduce an optimized implementation methodology applicable in various embedded environments. As a result, the proposed implementation achieved 3.5 times faster performance in the evaluation process and 5 times faster in the interpolation process than the previous reference implementation.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.163-170
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• 2022

With the advent of the 4th Industrial Revolution, solutions that apply AI technology are being actively developed. Since 2017, the introduction of business automation solutions using AI-based Robotic Process Automation (RPA) has begun in the financial sector and insurance companies, and recently, it is entering a time when it spreads past the stage of introducing RPA solutions. Among the business automation using these RPA solutions, it is very important how accurately textual information in the document is recognized for business automation using various documents. Such character recognition has recently increased its accuracy by introducing deep learning technology, but there is still no recognition model with perfect recognition accuracy. Therefore, in this paper, we checked how much accuracy is improved when pre- and post-processor technologies are applied to deep learning-based character recognition engines, and implemented RPA recognition engines and linkage technologies.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.178-185
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• 2021

Sequence to sequence(S2S) 기반 음성인식 후처리기를 훈련하기 위한 학습 데이터 구축을 위해 (음성인식 결과(speech recognition sentence), 전사자(phonetic transcriptor)가 수정한 문장(Human post edit sentence))의 병렬 말뭉치가 필요하며 이를 위해 많은 노동력(human-labor)이 소요된다. BackTranScription (BTS)이란 기존 S2S기반 음성인식 후처리기의 한계점을 완화하기 위해 제안된 데이터 구축 방법론이며 Text-To-Speech(TTS)와 Speech-To-Text(STT) 기술을 결합하여 pseudo 병렬 말뭉치를 생성하는 기술을 의미한다. 해당 방법론은 전사자의 역할을 없애고 방대한 양의 학습 데이터를 자동으로 생성할 수 있기에 데이터 구축에 있어서 시간과 비용을 단축 할 수 있다. 본 논문은 BTS를 바탕으로 제주어 도메인에 특화된 음성인식 후처리기의 성능을 향상시키기 위하여 모델 수정(model modification)을 통해 성능을 향상시키는 모델 중심 접근(model-centric) 방법론과 모델 수정 없이 데이터의 양과 질을 고려하여 성능을 향상시키는 데이터 중심 접근(data-centric) 방법론에 대한 비교 분석을 진행하였다. 실험결과 모델 교정없이 데이터 중심 접근 방법론을 적용하는 것이 성능 향상에 더 도움이 됨을 알 수 있었으며 모델 중심 접근 방법론의 부정적 측면 (negative result)에 대해서 분석을 진행하였다.

• Journal of the Korea Convergence Society
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• v.7 no.1
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• pp.17-23
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• 2016

In this paper, we describe a case of utilizing SaaS technology to build NC Post-processor(WBS) based cloud computing. Developed WPS system was implemented to provide stable and continuous system service by utilizing SCoD methodology. WPS is designed user interface module and control engine module. The interface module is downloaded in a client PC and the control engine is installed in cloud parm area. These modules are connected with computer network. WPS was completed a function test for sheet cutting field and mold manufacturing field, and it is processing a commercial service using with improve the user's convenience and adding a bill charge module.