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Assessment of Parallel Computing Performance of Agisoft Metashape for Orthomosaic Generation (정사모자이크 제작을 위한 Agisoft Metashape의 병렬처리 성능 평가)

  • Han, Soohee;Hong, Chang-Ki
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.6
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    • pp.427-434
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    • 2019
  • In the present study, we assessed the parallel computing performance of Agisoft Metashape for orthomosaic generation, which can implement aerial triangulation, generate a three-dimensional point cloud, and make an orthomosaic based on SfM (Structure from Motion) technology. Due to the nature of SfM, most of the time is spent on Align photos, which runs as a relative orientation, and Build dense cloud, which generates a three-dimensional point cloud. Metashape can parallelize the two processes by using multi-cores of CPU (Central Processing Unit) and GPU (Graphics Processing Unit). An orthomosaic was created from large UAV (Unmanned Aerial Vehicle) images by six conditions combined by three parallel methods (CPU only, GPU only, and CPU + GPU) and two operating systems (Windows and Linux). To assess the consistency of the results of the conditions, RMSE (Root Mean Square Error) of aerial triangulation was measured using ground control points which were automatically detected on the images without human intervention. The results of orthomosaic generation from 521 UAV images of 42.2 million pixels showed that the combination of CPU and GPU showed the best performance using the present system, and Linux showed better performance than Windows in all conditions. However, the RMSE values of aerial triangulation revealed a slight difference within an error range among the combinations. Therefore, Metashape seems to leave things to be desired so that the consistency is obtained regardless of parallel methods and operating systems.

Preliminary Uncertainty Analysis to Build a Data-Driven Prediction Model for Water Quality in Paldang Dam (팔당댐 유역의 데이터 기반 수질 예측 모형 구성을 위한 사전 불확실성 분석)

  • Lee, Eun Jeong;Keum, Ho Jun
    • Ecology and Resilient Infrastructure
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    • v.9 no.1
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    • pp.24-35
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    • 2022
  • For water quality management, it is necessary to continuously improve the forecasting by analyzing the past water quality, and a Data-driven model is emerging as an alternative. Because the Data-driven model is built based on a wide range of data, it is essential to apply the correlation analysis method for the combination of input variables to obtain more reliable results. In this study, the Gamma Test was applied as a preceding step to build a faster and more accurate data-driven water quality prediction model. First, a physical-based model (HSPF, EFDC) was operated to produce daily water quality reflecting the complexity of the watershed according to various hydrological conditions for Paldang Dam. The Gamma Test was performed on the water quality at the water quality prediction site (Paldangdam2) and major rivers flowing into the Paldang Dam, and the method of selecting the optimal input data combination was presented through the analysis results (Gamma, Gradient, Standar Error, V-Ratio). As a result of the study, the selection criteria for a more efficient combination of input data that can save time by omitting trial and error when building a data-driven model are presented.

Build-in Wiretap Channel I with Feedback and LDPC Codes

  • Wen, Hong;Gong, Guang;Ho, Pin-Han
    • Journal of Communications and Networks
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    • v.11 no.6
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    • pp.538-543
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    • 2009
  • A wiretap channel I is one of the channel models that was proved to achieve unconditional security. However, it has been an open problem in realizing such a channel model in a practical network environment. The paper is committed to solve the open problem by introducing a novel approach for building wiretap channel I in which the eavesdropper sees a binary symmetric channel (BSC) with error probability p while themain channel is error free. By taking advantage of the feedback and low density parity check (LDPC) codes, our scheme adds randomness to the feedback signals from the destination for keeping an eavesdropper ignorant; on the other hand, redundancy is added and encoded by the LDPC codes such that a legitimate receiver can correctly receive and decode the signals. With the proposed approach, unconditionallysecure communication can be achieved through interactive communications, in which the legitimate partner can realize the secret information transmission without a pre-shared secret key even if the eavesdropper has better channel from the beginning.

A Cylindrical Spindle Displacement Sensor and its Application on High Speed Milling Machine (원통형 주축 변위 센서를 이용한 고속 밀링 가공 상태 감시)

  • Kim, Il-Hae;Jang, Dong-Young
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.16 no.5
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    • pp.108-114
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    • 2007
  • A new cutting force estimating approach and machining state monitoring examples are presented which uses a cylindrical displacement sensor built into the spindle. To identify the tool-spindle system dynamics with frequency up to 2 kHz, a home-built electro-magnetic exciter is used. The result is used to build an algorithm to extract the dynamic cutting force signal from the spindle error motion; because the built-in spindle sensor signal contains both spindle-tool dynamics and tool-workpiece interactions. This sensor is very sensitive and can measure broadband signal without affecting the system dynamics. The main characteristic is that it is designed so that the measurement is irrelevant to the geometric errors by covering the entire circumferential area between the target and sensor. It is also very simple to be installed. Usually the spindle front cover part is copied and replaced with a new one with this sensor added. It gives valuable information about the operating condition of the spindle at any time. It can be used to monitor cutting force and chatter vibration, to predict roughness and to compensate the form error by overriding spindle speed or feed rate. This approach is particularly useful in monitoring a high speed machining process.

Statistics Quality Assessment and Improvement of Monitoring on Soil Quality (토양오염도 현황 통계의 품질 진단과 개선 방안)

  • Kim, Kee-Dae
    • Journal of Environmental Science International
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    • v.18 no.10
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    • pp.1079-1088
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    • 2009
  • The statistics of monitoring on soil quality is a report statistics which is made on the basis of Article 15, Environment Strategy Basic Law and Article 5, Soil Environment Conservation Law. This study was conducted according to quality assessment of Korea National Statistical Office. The assessment of quality infrastructure advised that the authority bring up and increase completely responsible officer and secure the budget. The assessment of user satisfaction and reflection of request propose that the statistics is focused on soil background concentration, decrease soil sampling points and extend survey period. The assessment of error management system per processes of detailed preparation suggest change of the statistics objective, a reduction of sampling points and improvement of survey period and soil measurement properties. Accuracy assessment of data proposed cuts of sampling points, accessibility increment and build up of management system linking subordinates and Ministry of Environment. The substantiality assessment of data service demonstrated information environment improvement for users including reference expression and records of statistics table and figure contents.

A Range-Based Monte Carlo Box Algorithm for Mobile Nodes Localization in WSNs

  • Li, Dan;Wen, Xianbin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.8
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    • pp.3889-3903
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    • 2017
  • Fast and accurate localization of randomly deployed nodes is required by many applications in wireless sensor networks (WSNs). However, mobile nodes localization in WSNs is more difficult than static nodes localization since the nodes mobility brings more data. In this paper, we propose a Range-based Monte Carlo Box (RMCB) algorithm, which builds upon the Monte Carlo Localization Boxed (MCB) algorithm to improve the localization accuracy. This algorithm utilizes Received Signal Strength Indication (RSSI) ranging technique to build a sample box and adds a preset error coefficient in sampling and filtering phase to increase the success rate of sampling and accuracy of valid samples. Moreover, simplified Particle Swarm Optimization (sPSO) algorithm is introduced to generate new samples and avoid constantly repeated sampling and filtering process. Simulation results denote that our proposed RMCB algorithm can reduce the location error by 24%, 14% and 14% on average compared to MCB, Range-based Monte Carlo Localization (RMCL) and RSSI Motion Prediction MCB (RMMCB) algorithm respectively and are suitable for high precision required positioning scenes.

Application of artificial neural network for the critical flow prediction of discharge nozzle

  • Xu, Hong;Tang, Tao;Zhang, Baorui;Liu, Yuechan
    • Nuclear Engineering and Technology
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    • v.54 no.3
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    • pp.834-841
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    • 2022
  • System thermal-hydraulic (STH) code is adopted for nuclear safety analysis. The critical flow model (CFM) is significant for the accuracy of STH simulation. To overcome the defects of current CFMs (low precision or long calculation time), a CFM based on a genetic neural network (GNN) has been developed in this work. To build a powerful model, besides the critical mass flux, the critical pressure and critical quality were also considered in this model, which was seldom considered before. Comparing with the traditional homogeneous equilibrium model (HEM) and the Moody model, the GNN model can predict the critical mass flux with a higher accuracy (approximately 80% of results are within the ±20% error limit); comparing with the Leung model and the Shannak model for critical pressure prediction, the GNN model achieved the best results (more than 80% prediction results within the ±20% error limit). For the critical quality, similar precision is achieved. The GNN-based CFM in this work is meaningful for the STH code CFM development.

The Effects of Age, Gender, and Target Force Level on Controlled Force Exertion Tasks

  • Kong, Yong-Ku;Lee, Sung Yong;Kim, Dae-Min;Choi, Kyeong-Hee
    • Journal of the Ergonomics Society of Korea
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    • v.36 no.1
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    • pp.53-67
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    • 2017
  • Objective: The purpose of this study is to build basic data to systematically develop a hand function evaluation tool by determining the effects of age, gender and target force level on the difference in hand function according to the target force level. Background: Precise and objective evaluation of hand functionality is a very important factor in quantifying treatment progress in patients or elderly people, and in verifying treatment effects. However, most hand function evaluations lack objectivity and accuracy, and therefore it is difficult to properly treat patients according to the given situation. Method: Sixteen healthy subjects (eight elderly and eight young people) participated in this study to evaluate the effects of age, gender, and target force level on tracking performance through rRMSE in terms of the tracking force and actual exerted force, by carrying out a task of maintaining six different target force levels for 20 seconds. Results: The result of this experiment indicated that elderly people and women had a lower ability to maintain a certain level of force than young people and men by 16% and 10%, respectively. The target force level results showed that the tracking error of the lowest force level (5% MVC) was significantly higher than that of 15% MVC, which in turn showed a higher tracking error than that of the higher target force levels. Conclusion: The results of this study can thus be utilized to develop a rehabilitation program for elderly people or other patients. Application: The authors expect that the results of the present study will be valuable to develop a rehabilitation program and hand function evaluation tool.

Design and Performance Analysis of Quadrature-Amplitude-Position-Modulation Method for the High Power Efficiency (고전력 효율 Quadrature-Amplitude-Position-Modulation 변조 방식과 성능 평가)

  • Choi, Jae-Hoon;Ryu, Heung-Gyoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.2A
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    • pp.108-113
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    • 2011
  • In this paper, we propose QAPM(Quadrature Amplitude Position Modulation) modulation scheme for improving power efficiency and we compare existing PSSK(Phase Silence Shift Keying) and QAPM. An existing PSSK Modulation is extension from PSK modulation technique. The conventional PSSK modulation technique can be regarded as an extension from PSK modulation. And this PSSK has better power efficiency than PSK modulation. The Bandwidth efficiency of PSSK is half than PSK, but improved BER(Bit Error Rate) performance. A propose QAPM scheme is build on QAM. And BER performance of QAPM is better than PSSK because BER performance of QAM is better than PSK. In this paper, we compare PSSK and QAPM regard to bit error rate and throughput.

Solar Power Generation Forecast Model Using Seasonal ARIMA (SARIMA 모형을 이용한 태양광 발전량 예보 모형 구축)

  • Lee, Dong-Hyun;Jung, Ahyun;Kim, Jin-Young;Kim, Chang Ki;Kim, Hyun-Goo;Lee, Yung-Seop
    • Journal of the Korean Solar Energy Society
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    • v.39 no.3
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    • pp.59-66
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    • 2019
  • New and renewable energy forecasts are key technology to reduce the annual operating cost of new and renewable facilities, and accuracy of forecasts is paramount. In this study, we intend to build a model for the prediction of short-term solar power generation for 1 hour to 3 hours. To this end, this study applied two time series technique, ARIMA model without considering seasonality and SARIMA model with considering seasonality, comparing which technique has better predictive accuracy. Comparing predicted errors by MAE measures of solar power generation for 1 hour to 3 hours at four locations, the solar power forecast model using ARIMA was better in terms of predictive accuracy than the solar power forecast model using SARIMA. On the other hand, a comparison of predicted error by RMSE measures resulted in a solar power forecast model using SARIMA being better in terms of predictive accuracy than a solar power forecast model using ARIMA.