• Title/Summary/Keyword: Multi-step method

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Parallel Processing of K-means Clustering Algorithm for Unsupervised Classification of Large Satellite Imagery (대용량 위성영상의 무감독 분류를 위한 K-means 군집화 알고리즘의 병렬처리)

  • Han, Soohee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.3
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    • pp.187-194
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    • 2017
  • The present study introduces a method to parallelize k-means clustering algorithm for fast unsupervised classification of large satellite imagery. Known as a representative algorithm for unsupervised classification, k-means clustering is usually applied to a preprocessing step before supervised classification, but can show the evident advantages of parallel processing due to its high computational intensity and less human intervention. Parallel processing codes are developed by using multi-threading based on OpenMP. In experiments, a PC of 8 multi-core integrated CPU is involved. A 7 band and 30m resolution image from LANDSAT 8 OLI and a 8 band and 10m resolution image from Sentinel-2A are tested. Parallel processing has shown 6 time faster speed than sequential processing when using 10 classes. To check the consistency of parallel and sequential processing, centers, numbers of classified pixels of classes, classified images are mutually compared, resulting in the same results. The present study is meaningful because it has proved that performance of large satellite processing can be significantly improved by using parallel processing. And it is also revealed that it easy to implement parallel processing by using multi-threading based on OpenMP but it should be carefully designed to control the occurrence of false sharing.

A Study on the Vibration Characteristics of Attitude Maneuvering of Satellite (위성의 자세기동에 따른 진동특성에 관한 연구)

  • Pyeon, Bong-Do;Bae, Jae-Sung;Kim, Jong-Hyuk;Park, Jung-Sun
    • Journal of Aerospace System Engineering
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    • v.13 no.3
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    • pp.23-31
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    • 2019
  • The design requirements of modern satellites vary depending on the purpose of operation. Like conventional medium and large-scale satellites, small satellites which operate on low orbit may also serve military purposes. As a result, there is increased demand for high-resolution photos and videos and multi-target observation becomes important. The most important design parameter for multi-target observation is the satellites' maneuverability. For increased maneuverability, the miniaturization is required to increase the stiffness of the satellite as this decreases the mass moment of inertia of the satellite. In the case of a solar panel having relatively low stiffness compared to the satellites' body, vibrations are generated when the attitude maneuver is performed, which greatly influences the image acquisition. For verification of such vibrational characteristics, the satellites is modeled as a reduced model, and experimental zig for simulating attitude maneuver is introduced. A rigidity simulator for simulating the stiffness of the satellite is also proposed. Additionally, the objective of the experimental method is to simulate the maneuvering angle of the satellite based on the winding length of the wire using a step motor, and to experimentally verify the vibration characteristics of the satellite body and the solar panel generated during the maneuvering test.

A study on Parallel Interference Cancellation scheme based sorting method for a Multi-carrier DS/CDMA System (MC-DS/CDMA 시스템에서 정렬기법을 이용한 병렬형 간섭제거기법의 성능개선에 관한 연구)

  • Park Jae-Won;Park Yong-Wan
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.42 no.1
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    • pp.17-27
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    • 2005
  • In this paper, we introduce a Parallel Interference Canceller (PIC) based sorting method to improve performance in the MC-DS/CDMA environment. A conventional PIC estimates and subtracts out all of the MAI (Multiple Access Interference) for each user in parallel. The parallel process ensures the low delay for the detection of all users. Also this scheme requires more stages for having better performance. Since the performance of PIC is strongly related to the correct MAI estimation, we introduce the IC (Interference Cancellation) scheme to estimate the accurate weaker signal group than the desired signal using conventional PIC. The principle of the proposed receiver sorts in descending order by the strength of signal and subtracts the MAI of the strong interferers from the desired signal for the accurate estimate of the weaker signals. Following this, the proposed scheme cancels out the improved weaker interference from the desired signal, using the output of the pre-step. In this result, the proposed system obtains better BER performance than the conventional PIC because the accuracy of the strong signal is improved. However, a disadvantage exists in that the processing time has slightly longer delay than the PIC owing to the power sorting and the MAI estimation process. The system performance evaluates and compares other non-liner It according to the number of sub-carriers in the limited-bandwidth.

Further Improvement of Direct Solution-based FETI Algorithm (직접해법 기반의 FETI 알고리즘의 개선)

  • Kang, Seung-Hoon;Gong, DuHyun;Shin, SangJoon
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.35 no.5
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    • pp.249-257
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    • 2022
  • This paper presents an improved computational framework for the direct-solution-based finite element tearing and interconnecting (FETI) algorithm. The FETI-local algorithm is further improved herein, and localized Lagrange multipliers are used to define the interface among its subdomains. Selective inverse entry computation, using a property of the Boolean matrix, is employed for the computation of the subdomain interface stiffness and load, in which the original FETI-local algorithm requires a full matrix inverse computation of a high computational cost. In the global interface computation step, the original serial computation is replaced by a parallel multi-frontal method. The performance of the improved FETI-local algorithm was evaluated using a numerical example with 64 million degrees of freedom (DOFs). The computational time was reduced by up to 97.8% compared to that of the original algorithm. In addition, further stable and improved scalability was obtained in terms of a speed-up indicator. Furthermore, a performance comparison was conducted to evaluate the differences between the proposed algorithm and commercial software ANSYS using a large-scale computation with 432 million DOFs. Although ANSYS is superior in terms of computational time, the proposed algorithm has an advantage in terms of the speed-up increase per processor increase.

Deep Learning-based UWB Distance Measurement for Wireless Power Transfer of Autonomous Vehicles in Indoor Environment (실내환경에서의 자율주행차 무선 전력 전송을 위한 딥러닝 기반 UWB 거리 측정)

  • Hye-Jung Kim;Yong-ju Park;Seung-Jae Han
    • KIPS Transactions on Computer and Communication Systems
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    • v.13 no.1
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    • pp.21-30
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    • 2024
  • As the self-driving car market continues to grow, the need for charging infrastructure is growing. However, in the case of a wireless charging system, stability issues are being raised because it requires a large amount of power compared with conventional wired charging. SAE J2954 is a standard for building autonomous vehicle wireless charging infrastructure, and the standard defines a communication method between a vehicle and a power transmission system. SAE J2954 recommends using physical media such as Wi-Fi, Bluetooth, and UWB as a wireless charging communication method for autonomous vehicles to enable communication between the vehicle and the charging pad. In particular, UWB is a suitable solution for indoor and outdoor charging environments because it exhibits robust communication capabilities in indoor environments and is not sensitive to interference. In this standard, the process for building a wireless power transmission system is divided into several stages from the start to the completion of charging. In this study, UWB technology is used as a means of fine alignment, a process in the wireless power transmission system. To determine the applicability to an actual autonomous vehicle wireless power transmission system, experiments were conducted based on distance, and the distance information was collected from UWB. To improve the accuracy of the distance data obtained from UWB, we propose a Single Model and Multi Model that apply machine learning and deep learning techniques to the collected data through a three-step preprocessing process.

Analysis of RTM Process Using the Extended Finite Element Method (확장 유한 요소 법을 적용한 RTM 공정 해석)

  • Jung, Yeonhee;Kim, Seung Jo;Han, Woo-Suck
    • Composites Research
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    • v.26 no.6
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    • pp.363-372
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    • 2013
  • Numerical simulation for Resin Transfer Molding manufacturing process is attempted by using the eXtended Finite Element Method (XFEM) combined with the level set method. XFEM allows to obtaining a good numerical precision of the pressure near the resin flow front, where its gradient is discontinuous. The enriched shape functions of XFEM are derived by using the level set values so as to correctly describe the interpolation with the resin flow front. In addition, the level set method is used to transport the resin flow front at each time step during the mold filling. The level set values are calculated by an implicit characteristic Galerkin FEM. The multi-frontal solver of IPSAP is adopted to solve the system. This work is validated by comparing the obtained results with analytic solutions. Moreover, a localization method of XFEM and level set method is proposed to increase the computing efficiency. The computation domain is reduced to the small region near the resin flow front. Therefore, the total computing time is strongly reduced by it. The efficiency test is made with a simple channel flow model. Several application examples are analyzed to demonstrate ability of this method.

A Study on the Improvement of Service Quality in Medical Tourism by Combining Service Blueprint and AHP (서비스 청사진과 AHP의 결합에 의한 의료관광서비스 개선방안에 관한 연구)

  • Hyun, Min-Cheol;Cho, Boo-Yun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.4
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    • pp.1895-1904
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    • 2014
  • This study explores the way to improve service quality with the application of Service Blueprint and Analytic Hierarchy Process (hereafter, "AHP") in medical tourism. Service Blueprint has been widely accepted to identify the possible fail points in service delivery system, and AHP analysis has been recognized as beneficial method to rate relative importance in multi-criteria decision making process. We try to understand possible pitfalls to enhance Chinese medical tourists, and propose the priority in the resolution process. In the first step, we reviewed the extant literatures about medical tourism of South Korea, and built initial Service Blueprint. Experts who experienced service delivery process towards Chinese patients participated to review the proposed Service Blueprint in the second step. Thirdly, after extracting the possible fail points from revised Service Blueprint, we asked experts to guess the relative importance of Chinese patient by AHP methodology. Four domains (Arrival and Welcoming, Hospitalization, Process before, operations, and after surgery, Recovery and discharge) were emerged with detail criteria. Results show that operations and treatment is the most important domain not to lose Chinese patient's loyalty with following hospitalization process domain. Also, we suggest the priority among sixteen criteria to prevent service failure.

Detection and Typing of Human Papillomavirus in Cutaneous Common Warts by Multiplex Polymerase Chain Reaction (Multiplex PCR 기법을 이용한 보통사마귀 내 인유두종바이러스 검출 및 분류)

  • Choi, Soon-Yong;Lim, Jong-Ho;Kim, Eun-Jung;Kim, Hei-Sung;Kim, Beom-Joon;Kang, Hoon;Park, Young-Min
    • Journal of Life Science
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    • v.21 no.7
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    • pp.947-952
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    • 2011
  • A number of epidemiological studies have identified human papillomavirus (HPV) types 1, 2, 3, 4, 7, 10, 27, 57, and 65 in cutaneous common warts. However, identification of the HPV subtype by conventional polymerase chain reaction (PCR) is time consuming with its multi-step laboratory process. In this study, we aim to develop a specific one-step multiplex polymerase chain reaction method which capably identifies six different HPV genotypes related to common warts. By HPV DNA sequence analysis, 6 pairs of specific primers were designed from the intergenic regions of genes L1 to E6, and from genes E2 to L2. DNA sequence analysis with the L1 gene sequence of the sample was performed to measure the specificity of multiplex PCR. HPV-1, -2, -3, -4, -27, and -57 were identified without cross amplification in 109 out of 129 samples. The sensitivity and specificity of our set of primers in detecting HPV were 85% and 99.5%, respectively. For the 20 samples where HPV type was not identifiable by our batch of primer sets, multiplex PCR with an additional set of HPV primers was done, where 7 were found positive for HPV-7 or -65. Our results demonstrate that the newly designed multiplex PCR can rapidly detect the specific HPV subtype involved in common warts with high accuracy.

Lip Contour Detection by Multi-Threshold (다중 문턱치를 이용한 입술 윤곽 검출 방법)

  • Kim, Jeong Yeop
    • KIPS Transactions on Software and Data Engineering
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    • v.9 no.12
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    • pp.431-438
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    • 2020
  • In this paper, the method to extract lip contour by multiple threshold is proposed. Spyridonos et. el. proposed a method to extract lip contour. First step is get Q image from transform of RGB into YIQ. Second step is to find lip corner points by change point detection and split Q image into upper and lower part by corner points. The candidate lip contour can be obtained by apply threshold to Q image. From the candidate contour, feature variance is calculated and the contour with maximum variance is adopted as final contour. The feature variance 'D' is based on the absolute difference near the contour points. The conventional method has 3 problems. The first one is related to lip corner point. Calculation of variance depends on much skin pixels and therefore the accuracy decreases and have effect on the split for Q image. Second, there is no analysis for color systems except YIQ. YIQ is a good however, other color systems such as HVS, CIELUV, YCrCb would be considered. Final problem is related to selection of optimal contour. In selection process, they used maximum of average feature variance for the pixels near the contour points. The maximum of variance causes reduction of extracted contour compared to ground contours. To solve the first problem, the proposed method excludes some of skin pixels and got 30% performance increase. For the second problem, HSV, CIELUV, YCrCb coordinate systems are tested and found there is no relation between the conventional method and dependency to color systems. For the final problem, maximum of total sum for the feature variance is adopted rather than the maximum of average feature variance and got 46% performance increase. By combine all the solutions, the proposed method gives 2 times in accuracy and stability than conventional method.

Recurrent Neural Network Models for Prediction of the inside Temperature and Humidity in Greenhouse

  • Jung, Dae-Hyun;Kim, Hak-Jin;Park, Soo Hyun;Kim, Joon Yong
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2017.04a
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    • pp.135-135
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    • 2017
  • Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

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