• Title/Summary/Keyword: Total variation algorithm

Search Result 103, Processing Time 0.031 seconds

Shape Deformation Monitoring for VLBI Antenna Using Close-Range Photogrammetry and Total Least Squares (근접사진측량과 Total Least Squares를 활용한 VLBI 안테나 형상 변형 모니터링 방안 연구)

  • Kim, Hyuk Gil;Yun, Hong Sik
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.34 no.1
    • /
    • pp.99-107
    • /
    • 2016
  • In order to maintain the precise positioning accuracy of the VLBI system, the shape deformation found in antenna structure should be monitored. In fact, reduced the antenna gaining of an electromagnetic wave reception from the Quasar has been particularly expected due to the shape deformation of main reflector in VLBI antenna. Therefore, the importance of shape deformation monitoring for the main reflector has been significantly increased. The main reflector has come out as the high potential for deformation in the VLBI structure. The fact has led us to investigate the monitoring system for the main reflector based on the efficient algorithm in accordance with the close-range photogrammetry, which of expecting to be utilized as the continuous and automated monitoring system for the structure deformation in the near future. Ten fitting lines were estimated with the TLS for feature points of distributed in all directions from the main reflector. The resultant intersection point of estimated fitting lines was calculated by using the nearest point calculation algorithm, based on those non-intersection lines. Following to the intuitive basis for the time series analysis, the results was able to provide the calculation of numerical variation in the intersection point, which is represented in 3-axis,; that we are expecting to open the way for predicting a deformation rate as well as deformation direction

Development of Vehicle Arrival Time Prediction Algorithm Based on a Demand Volume (교통수요 기반의 도착예정시간 산출 알고리즘 개발)

  • Kim, Ji-Hong;Lee, Gyeong-Sun;Kim, Yeong-Ho;Lee, Seong-Mo
    • Journal of Korean Society of Transportation
    • /
    • v.23 no.2
    • /
    • pp.107-116
    • /
    • 2005
  • The information on travel time in providing the information of traffic to drivers is one of the most important data to control a traffic congestion efficiently. Especially, this information is the major element of route choice of drivers, and based on the premise that it has the high degree of confidence in real situation. This study developed a vehicle arrival time prediction algorithm called as "VAT-DV" for 6 corridors in total 6.1Km of "Nam-san area trffic information system" in order to give an information of congestion to drivers using VMS, ARS, and WEB. The spatial scope of this study is 2.5km~3km sections of each corridor, but there are various situations of traffic flow in a short period because they have signalized intersections in a departure point and an arrival point of each corridor, so they have almost characteristics of interrupted and uninterrupted traffic flow. The algorithm uses the information on a demand volume and a queue length. The demand volume is estimated from density of each points based on the Greenburg model, and the queue length is from the density and speed of each point. In order to settle the variation of the unit time, the result of this algorithm is strategically regulated by importing the AVI(Automatic Vehicle Identification), one of the number plate matching methods. In this study, the AVI travel time information is composed by Hybrid Model in order to use it as the basic parameter to make one travel time in a day using ILD to classify the characteristics of the traffic flow along the queue length. According to the result of this study, in congestion situation, this algorithm has about more than 84% degree of accuracy. Specially, the result of providing the information of "Nam-san area traffic information system" shows that 72.6% of drivers are available.

Development and Basic Experiment of Active Noise Control System for Reduction of Road Noise (도로 소음 저감을 위한 능동소음제어 시스템의 개발 및 기초실험)

  • Moon, Hak Ryong;Kang, Won Pyoung;Lim, You Jin
    • International Journal of Highway Engineering
    • /
    • v.15 no.6
    • /
    • pp.41-47
    • /
    • 2013
  • PURPOSES : The purpose of this study is about noise which is generated from roads and is consist of irregular frequency variation from low frequency to various band. The existing methods of noise reduction are sound barrier that uses insulation material and absorbing material or have applied passive technology of noise reduction by devices. The total frequency band is needed to apply active noise control. METHODS : In this study applies to the field of road traffic environment, signal processing controller and various analog signal input/output, the amplifier module is based on parallel-core embedded processor designed. DSP performs the control algorithm of the road traffic noise. Noise sources in the open space performance of evaluation were applied. In this study, controller of active signal processor was designed based on the module of audio input/output and main controller of embedded process. The controller of active signal processor operates noise reduction algorithm and performance tests of noise reduction in inside and outside environment were executed. RESULTS : The signal processing controller with OMAP-L137 parallel-core processors as the center, DSP processors in the active control operations dealt with quickly. To maximize the operation speed of an object and ARM processor is external function keys and display for functions and evaluating the performance management system was designed for the purpose of the interface. Therefore the reduction of road traffic noise has established an electronic controller-based noise reduction. CONCLUSIONS : It is shown that noise reduction is effective in the case of pour tonal sound and complex tonal sound below 500Hz by appling to Fx-LMS.

Classification of Aβ State From Brain Amyloid PET Images Using Machine Learning Algorithm

  • Chanda Simfukwe;Reeree Lee;Young Chul Youn;Alzheimer’s Disease and Related Dementias in Zambia (ADDIZ) Group
    • Dementia and Neurocognitive Disorders
    • /
    • v.22 no.2
    • /
    • pp.61-68
    • /
    • 2023
  • Background and Purpose: Analyzing brain amyloid positron emission tomography (PET) images to access the occurrence of β-amyloid (Aβ) deposition in Alzheimer's patients requires much time and effort from physicians, while the variation of each interpreter may differ. For these reasons, a machine learning model was developed using a convolutional neural network (CNN) as an objective decision to classify the Aβ positive and Aβ negative status from brain amyloid PET images. Methods: A total of 7,344 PET images of 144 subjects were used in this study. The 18F-florbetaben PET was administered to all participants, and the criteria for differentiating Aβ positive and Aβ negative state was based on brain amyloid plaque load score (BAPL) that depended on the visual assessment of PET images by the physicians. We applied the CNN algorithm trained in batches of 51 PET images per subject directory from 2 classes: Aβ positive and Aβ negative states, based on the BAPL scores. Results: The binary classification of the model average performance matrices was evaluated after 40 epochs of three trials based on test datasets. The model accuracy for classifying Aβ positivity and Aβ negativity was (95.00±0.02) in the test dataset. The sensitivity and specificity were (96.00±0.02) and (94.00±0.02), respectively, with an area under the curve of (87.00±0.03). Conclusions: Based on this study, the designed CNN model has the potential to be used clinically to screen amyloid PET images.

Identification of copy number variations using high density whole-genome single nucleotide polymorphism markers in Chinese Dongxiang spotted pigs

  • Wang, Chengbin;Chen, Hao;Wang, Xiaopeng;Wu, Zhongping;Liu, Weiwei;Guo, Yuanmei;Ren, Jun;Ding, Nengshui
    • Asian-Australasian Journal of Animal Sciences
    • /
    • v.32 no.12
    • /
    • pp.1809-1815
    • /
    • 2019
  • Objective: Copy number variations (CNVs) are a major source of genetic diversity complementary to single nucleotide polymorphism (SNP) in animals. The aim of the study was to perform a comprehensive genomic analysis of CNVs based on high density whole-genome SNP markers in Chinese Dongxiang spotted pigs. Methods: We used customized Affymetrix Axiom Pig1.4M array plates containing 1.4 million SNPs and the PennCNV algorithm to identify porcine CNVs on autosomes in Chinese Dongxiang spotted pigs. Then, the next generation sequence data was used to confirm the detected CNVs. Next, functional analysis was performed for gene contents in copy number variation regions (CNVRs). In addition, we compared the identified CNVRs with those reported ones and quantitative trait loci (QTL) in the pig QTL database. Results: We identified 871 putative CNVs belonging to 2,221 CNVRs on 17 autosomes. We further discarded CNVRs that were detected only in one individual, leaving us 166 CNVRs in total. The 166 CNVRs ranged from 2.89 kb to 617.53 kb with a mean value of 93.65 kb and a genome coverage of 15.55 Mb, corresponding to 0.58% of the pig genome. A total of 119 (71.69%) of the identified CNVRs were confirmed by next generation sequence data. Moreover, functional annotation showed that these CNVRs are involved in a variety of molecular functions. More than half (56.63%) of the CNVRs (n = 94) have been reported in previous studies, while 72 CNVRs are reported for the first time. In addition, 162 (97.59%) CNVRs were found to overlap with 2,765 previously reported QTLs affecting 378 phenotypic traits. Conclusion: The findings improve the catalog of pig CNVs and provide insights and novel molecular markers for further genetic analyses of Chinese indigenous pigs.

Estimation of Family Variation and Genetic Parameter for Growth Traits of Pacific Abalone, Haliotis discus hannai on the 3th Generation of Selection (선발 3세대 북방전복의 성장형질에 대한 가계변이 및 유전모수 추정)

  • Park, Jong-Won;Park, Choul-Ji;Lee, Jeong-Ho;Noh, Jae-Koo;Kim, Hyun-Chul;Hwang, In-Joon;Kim, Sung-Yeon
    • The Korean Journal of Malacology
    • /
    • v.29 no.4
    • /
    • pp.325-334
    • /
    • 2013
  • The purpose of this paper is to compare and analyze family variations for growth-related traits of Pacific abalone, Haliotis discus hannai. Genetic parameters and breeding values were estimated using all measurement data like shell length, shell width, and total weight as 18-month-old growth traits of 5,334 individuals of selected third generation's Pacific abalone produced in 2011. Family variations of 865 individuals of the upper 10 families with the largest number were inspected. Overall mean in phenotypic traits of 18-month-old Pacific abalone which was investigated in this study showed 54.5 mm of shell length, 36.8 mm of shell width and 21.3 g of total weight respectively. And, variation coefficient of total weight was 51.0%, so variability of data was shown to be higher than 21.1% of shell length and 20.7% of shell width. The family effects showed significant difference by each family (p < 0.05), and heritability of shell length, shell width, and total weight was medium with 0.370, 0.382, and 0.367 respectively. So it is considered that family selection is more advantageous than individual selection. On the basis of breeding values of estimated shell length and total weight, to investigate distribution and ranking by each individual about the upper 10 families with the largest number of individuals, the values were used by being changed into standardized breeding values. Based on shell length, it was investigated that the individual number of the upper 5.4% is 152 and the number of the lower 5.4% is 8. In case of total weight, it was inspected that the individual number of the upper 5.4% is 164 and the number of the lower 5.4% is 1. Like these, phenotypic and genetic diverse variations between families could be checked. By estimating genetic parameters and breeding values of a population for production of the next generation, if they are used properly in selection and mating, it is considered that more breeding effects can be expected.

Design of the Broadband TEM Horn Antenna Using a Genetic Algorithm (유전자 알고리즘을 이용한 광대역 TEM 혼 안테나 설계)

  • Na, Young-Sun;Choo, Ho-Sung;Lee, Joo-Gwang;Kang, Jin-Seob
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
    • /
    • v.18 no.4 s.119
    • /
    • pp.430-439
    • /
    • 2007
  • In this paper, we propose a broadband TEM horn antenna optimized using a genetic algorithm. The characteristics required for the TEM horn are the broad matching bandwidth from 2 GHz to 10 GHz and high gain in broadside with a small gain deviation within that bandwidth. In addition, a broadband balun is designed to improve the portability and to reduce the total size of the antenna. The measured return loss of the proposed TEM horn with the broadband balun is less than -10 dB(VSWR<2) from 2 GHz to 10 GHz. Compared to a conventional triangular type TEM horn, the proposed antenna shows about 80 % reduced volume and gives the broadside gain about 12 dBi with a gain deviation less than 6 dB from 2 GHz to 10 GHz. The time domain measurement shows less than 0.4 ns group delay and the pulse measurement using the transmitting signal with the rising time of 58.5 ps shows the received pulse with the rising time of 66.5 ps, which is less than 10 % rising time variation.

Tracking Moving Object using Hierarchical Search Method (계층적 탐색기법을 이용한 이동물체 추적)

  • 방만식;김태식;김영일
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.7 no.3
    • /
    • pp.568-576
    • /
    • 2003
  • This paper proposes a moving object tracking algorithm by using hierarchical search method in dynamic scenes. Proposed algorithm is based on two main steps: generation step of initial model from different pictures, and tracking step of moving object under the time-yawing scenes. With a series of this procedure, tracking process is not only stable under far distance circumstance with respect to the previous frame but also reliable under shape variation from the 3-dimensional(3D) motion and camera sway, and consequently, by correcting position of moving object, tracking time is relatively reduced. Partial Hausdorff distance is also utilized as an estimation function to determine the similarity between model and moving object. In order to testify the performance of proposed method, the extraction and tracking performance have tested using some kinds of moving car in dynamic scenes. Experimental results showed that the proposed algorithm provides higher performance. Namely, matching order is 28.21 times on average, and considering the processing time per frame, it is 53.21ms/frame. Computation result between the tracking position and that of currently real with respect to the root-mean-square(rms) is 1.148. In the occasion of different vehicle in terms of size, color and shape, tracking performance is 98.66%. In such case as background-dependence due to the analogy to road is 95.33%, and total average is 97%.

Development of Remote Sensing Reflectance and Water Leaving Radiance Models for Ocean Color Remote Sensing Technique (해색 원격탐사를 위한 원격반사도 및 수출광 모델의 개발)

  • 안유환
    • Korean Journal of Remote Sensing
    • /
    • v.16 no.3
    • /
    • pp.243-260
    • /
    • 2000
  • Ocean remote sensing reflectance of just above water level was modeled using inherent optical properties of seawater contents, total absorption (a) and backscattering(bb) coefficients ($R_{rs}$=0.046 $b_b$/(a+$b_b$). This modeling was based on the specific absorption and backscattering coefficients of 5 optically active seawater components; phytoplankton pigments, non-chlorophyllous suspended particles, dissolved organic matters, heterotrophic microorganisms, and the other unknown particle components. Simulated remote sensing reflectance($R_{rs}$) and water leaving radiance(Lw) spectra were well agreed with in-situ measurements obtained using a bi-directional fields remote spectrometer in coastal waters and open ocean. $R_{rs}$ values in SeaWiFS bands from the model were analyzed to develop 2-band ratio ocean color chlorophyll with those observed insitu. Also, chlorophyll algorithm based on remote reflectance developed in this study fell in those obtained by a SeaBAM working group. The model algorithms were examined and compared with those observed insitu. Also, chlorophyll algorithm based on remote reflectance developed in this study fell in those obtained by a SeaBAM working group. The remote reflectance model will be very helpful to understand the variation of water leaving radiances caused by the various components in the seawater, and to develop new ocean color algorithm for CASE-II water using neural network method or other analytical method, and in the model of fine atmospheric signal correction.

A Study on GPU-based Iterative ML-EM Reconstruction Algorithm for Emission Computed Tomographic Imaging Systems (방출단층촬영 시스템을 위한 GPU 기반 반복적 기댓값 최대화 재구성 알고리즘 연구)

  • Ha, Woo-Seok;Kim, Soo-Mee;Park, Min-Jae;Lee, Dong-Soo;Lee, Jae-Sung
    • Nuclear Medicine and Molecular Imaging
    • /
    • v.43 no.5
    • /
    • pp.459-467
    • /
    • 2009
  • Purpose: The maximum likelihood-expectation maximization (ML-EM) is the statistical reconstruction algorithm derived from probabilistic model of the emission and detection processes. Although the ML-EM has many advantages in accuracy and utility, the use of the ML-EM is limited due to the computational burden of iterating processing on a CPU (central processing unit). In this study, we developed a parallel computing technique on GPU (graphic processing unit) for ML-EM algorithm. Materials and Methods: Using Geforce 9800 GTX+ graphic card and CUDA (compute unified device architecture) the projection and backprojection in ML-EM algorithm were parallelized by NVIDIA's technology. The time delay on computations for projection, errors between measured and estimated data and backprojection in an iteration were measured. Total time included the latency in data transmission between RAM and GPU memory. Results: The total computation time of the CPU- and GPU-based ML-EM with 32 iterations were 3.83 and 0.26 see, respectively. In this case, the computing speed was improved about 15 times on GPU. When the number of iterations increased into 1024, the CPU- and GPU-based computing took totally 18 min and 8 see, respectively. The improvement was about 135 times and was caused by delay on CPU-based computing after certain iterations. On the other hand, the GPU-based computation provided very small variation on time delay per iteration due to use of shared memory. Conclusion: The GPU-based parallel computation for ML-EM improved significantly the computing speed and stability. The developed GPU-based ML-EM algorithm could be easily modified for some other imaging geometries.