• Title/Summary/Keyword: missing modes

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Missing Modes in Fabry-Perot Laser Diodes (Fabry-Perot 레이저 다이오드의 Missing Mode)

  • Lee, Dong-Soo
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.19 no.1
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    • pp.9-14
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    • 2005
  • Mode missing of Fabry-Perot laser diodes has been modeled using the time domain laser model(TDLM). Fabry-Perot laser diodes that have structure of ripple in the waveguide of active layer or defects inside the active layer were simulated. For accurate simulation, the nonlinear effects were included such as spatial hole burning(SHB) and gain saturation. From the simulation results, it was founded that the defect inside the active layer in laser diodes has a strong influence on mode missing rather than the waveguide ripple. The simulation results are confirmed with the fabricated Fabry-Perot laser diodes by measuring the longitudinal mode spectra as a function of temperature from $25[^{\circ}C]\;to\;85[^{\circ}C]$.

Recovering Incomplete Data using Tucker Model for Tensor with Low-n-rank

  • Thieu, Thao Nguyen;Yang, Hyung-Jeong;Vu, Tien Duong;Kim, Sun-Hee
    • International Journal of Contents
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    • v.12 no.3
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    • pp.22-28
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    • 2016
  • Tensor with missing or incomplete values is a ubiquitous problem in various fields such as biomedical signal processing, image processing, and social network analysis. In this paper, we considered how to reconstruct a dataset with missing values by using tensor form which is called tensor completion process. We applied Tucker factorization to solve tensor completion which was built base on optimization problem. We formulated the optimization objective function using components of Tucker model after decomposing. The weighted least square matric contained only known values of the tensor with low rank in its modes. A first order optimization method, namely Nonlinear Conjugated Gradient, was applied to solve the optimization problem. We demonstrated the effectiveness of the proposed method in EEG signals with about 70% missing entries compared to other algorithms. The relative error was proposed to compare the difference between original tensor and the process output.

Technical Essentials of the Earth's Free Oscillation Mode Computation

  • Chung, Tae-Woong;Shin, Jin-Soo;Na, Sung-Ho
    • Journal of the Korean earth science society
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    • v.38 no.6
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    • pp.427-441
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    • 2017
  • Theory of Earth's free oscillation is revisited. Firstly, we summarized the underlying formulations, such as the equation of motion and its conversion into numerically integrable form and then explained computational procedures including the treatment of inner core-outer core boundary and core-mantle boundary, while the latter information has not been explicitly given in most publications. Secondly, we re-calculated the periods of Earth's free oscillation modes (period >200 s) for PREM model. In doing so we acquired the values of modes missing in Dziewonski and Anderson (1981). As a case observation, one seismogram after 2011 Tohoku earthquake recorded at Daejeon, Korea (KIGAM seismic station) was briefly analyzed to identify free oscillation mode excitations on its spectra. The material in this article will be most clear guide for those on calculating the Earth's free oscillation mode.

Non-contact damage monitoring technique for FRP laminates using guided waves

  • Garg, Mohit;Sharma, Shruti;Sharma, Sandeep;Mehta, Rajeev
    • Smart Structures and Systems
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    • v.17 no.5
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    • pp.795-817
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    • 2016
  • A non-contact, in-situ and non-invasive technique for health monitoring of submerged fiber reinforced polymers (FRP) laminates has been developed using ultrasonic guided waves. A pair of mobile transducers at specific angles of incidence to the submerged FRP specimen was used to excite Lamb wave modes. Lamb wave modes were used for comprehensive inspection of various types of manufacturing defects like air gaps and missing epoxy, introduced during manufacturing of FRP using Vacuum Assisted Resin Infusion Molding (VARIM). Further service induced damages like notches and surface defects were also studied and evaluated using guided waves. Quantitative evaluation of transmitted ultrasonic signal in defect ridden FRPs $vis-{\grave{a}}-vis$ healthy signal has been used to relate the extent of damage in FRPs. The developed technique has the potential to develop into a quick, real time health monitoring tool for judging the service worthiness of FRPs.

Reconstruction of missing response data for identification of higher modes

  • Shrikhande, Manish
    • Earthquakes and Structures
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    • v.2 no.4
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    • pp.323-336
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    • 2011
  • The problem of reconstruction of complete building response from a limited number of response measurements is considered. The response at the intermediate degrees of freedom is reconstructed by using piecewise cubic Hermite polynomial interpolation in time domain. The piecewise cubic Hermite polynomial interpolation is preferred over the spline interpolation due to its trend preserving character. It has been shown that factorization of response data in variable separable form via singular value decomposition can be used to derive the complete set of normal modes of the structural system. The time domain principal components can be used to derive empirical transfer functions from which the natural frequencies of the structural system can be identified by peak-picking technique. A reduced-rank approximation for the system flexibility matrix can be readily constructed from the identified mass-orthonormal mode shapes and natural frequencies.

Variational Mode Decomposition with Missing Data (결측치가 있는 자료에서의 변동모드분해법)

  • Choi, Guebin;Oh, Hee-Seok;Lee, Youngjo;Kim, Donghoh;Yu, Kyungsang
    • The Korean Journal of Applied Statistics
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    • v.28 no.2
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    • pp.159-174
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    • 2015
  • Dragomiretskiy and Zosso (2014) developed a new decomposition method, termed variational mode decomposition (VMD), which is efficient for handling the tone detection and separation of signals. However, VMD may be inefficient in the presence of missing data since it is based on a fast Fourier transform (FFT) algorithm. To overcome this problem, we propose a new approach based on a novel combination of VMD and hierarchical (or h)-likelihood method. The h-likelihood provides an effective imputation methodology for missing data when VMD decomposes the signal into several meaningful modes. A simulation study and real data analysis demonstrates that the proposed method can produce substantially effective results.

IMPLANTS IN PSYCHIATRIC PATIENTS (정신장애 환자의 임프란트 치료)

  • Moon, Sung-Yong;Kim, Su-Gwan
    • The Journal of Korea Assosiation for Disability and Oral Health
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    • v.3 no.1
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    • pp.1-5
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    • 2007
  • Patients of mental disorder have more missing teeth than general population because of the difficulty of oral hygiene management. In addition, especially Down syndrome patients etc., congenital dental problems develop more frequently. Therefore, prosthetic rehabilitation treatments for missing teeth in mental disorder patients are required more urgently. In other words, a removable partial denture may be very difficult for such patients to wear and manage. So in this review article we reviewed implant therapeutic modes for mental disorder patients based on previous reports. It should be understood that implant treatments are not impossible for mental disorder patients, and if implants could be a good method that could provide them good quality care, so implant should be included in treatment plans before surgery. Before surgery it should be evaluated that patients ability to manage themselves their ability to manage themselves should be evaluated and also should be evaluated whether general anesthesia or sedative treatment is required for the treatment, and whether their cooperation is good enough.

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A Real Time Traffic Flow Model Based on Deep Learning

  • Zhang, Shuai;Pei, Cai Y.;Liu, Wen Y.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.8
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    • pp.2473-2489
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    • 2022
  • Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

Audio and Video Bimodal Emotion Recognition in Social Networks Based on Improved AlexNet Network and Attention Mechanism

  • Liu, Min;Tang, Jun
    • Journal of Information Processing Systems
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    • v.17 no.4
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    • pp.754-771
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    • 2021
  • In the task of continuous dimension emotion recognition, the parts that highlight the emotional expression are not the same in each mode, and the influences of different modes on the emotional state is also different. Therefore, this paper studies the fusion of the two most important modes in emotional recognition (voice and visual expression), and proposes a two-mode dual-modal emotion recognition method combined with the attention mechanism of the improved AlexNet network. After a simple preprocessing of the audio signal and the video signal, respectively, the first step is to use the prior knowledge to realize the extraction of audio characteristics. Then, facial expression features are extracted by the improved AlexNet network. Finally, the multimodal attention mechanism is used to fuse facial expression features and audio features, and the improved loss function is used to optimize the modal missing problem, so as to improve the robustness of the model and the performance of emotion recognition. The experimental results show that the concordance coefficient of the proposed model in the two dimensions of arousal and valence (concordance correlation coefficient) were 0.729 and 0.718, respectively, which are superior to several comparative algorithms.

A Study on the Effective Scanning Trajectory using Manipulator for Underground Object Detection (매니퓰레이터를 이용한 지하 매설물 탐지의 효율적 탐지경로에 관한 연구)

  • Lee, Myung-Chun;Shin, Ho-Cheol;Yoon, Jong-Hoon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.15 no.1
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    • pp.9-15
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    • 2012
  • This paper shows an effective scanning trajectory for a mine detection device that is one of the mission equipments of unmanned ground vehicle. The mine detection device is composed of a mine-detection sensor, and a 4 DOF manipulator enabling sensor position control. There are three modes that manage the mine detection device: passive, semi-automatic, and automatic. The automatic mode is used the most. This paper suggests a scanning method that makes shape of 8. This method prevents missing target area and enhances scanning speed when the mine detection device scans the ground surface in automatic mode. The suggested method is verified by simulations and experiments.