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The linear-elastic stiffness matrix model analysis of pre-twisted Euler-Bernoulli beam

  • Huang, Ying;Zou, Haoran;Chen, Changhong;Bai, Songlin;Yao, Yao;Keer, Leon M.
    • Structural Engineering and Mechanics
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    • v.72 no.5
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    • pp.617-629
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    • 2019
  • Based on the finite element method of traditional straight Euler-Bernoulli beams and the coupled relations between linear displacement and angular displacement of a pre-twisted Euler-Bernoulli beam, the shape functions and stiffness matrix are deduced. Firstly, the stiffness of pre-twisted Euler-Bernoulli beam is developed based on the traditional straight Euler-Bernoulli beam. Then, a new finite element model is proposed based on the displacement general solution of a pre-twisted Euler-Bernoulli beam. Finally, comparison analyses are made among the proposed Euler-Bernoulli model, the new numerical model based on displacement general solution and the ANSYS solution by Beam188 element based on infinite approach. The results show that developed numerical models are available for the pre-twisted Euler-Bernoulli beam, and which provide more accurate finite element model for the numerical analysis. The effects of pre-twisted angle and flexural stiffness ratio on the mechanical property are investigated.

Occluded Object Motion Estimation System based on Particle Filter with 3D Reconstruction

  • Ko, Kwang-Eun;Park, Jun-Heong;Park, Seung-Min;Kim, Jun-Yeup;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.1
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    • pp.60-65
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    • 2012
  • This paper presents a method for occluded object based motion estimation and tracking system in dynamic image sequences using particle filter with 3D reconstruction. A unique characteristic of this study is its ability to cope with partial occlusion based continuous motion estimation using particle filter inspired from the mirror neuron system in human brain. To update a prior knowledge about the shape or motion of objects, firstly, fundamental 3D reconstruction based occlusion tracing method is applied and object landmarks are determined. And optical flow based motion vector is estimated from the movement of the landmarks. When arbitrary partial occlusions are occurred, the continuous motion of the hidden parts of object can be estimated by particle filter with optical flow. The resistance of the resulting estimation to partial occlusions enables the more accurate detection and handling of more severe occlusions.

Is Axillary Dissection Necessary for Breast Cancer in Old Women? A Meta-analysis of Randomized Clinical Trials

  • Zhang, Pei-Zhen;Chong, Le;Zhao, Ye;Gu, Jing;Tian, Jin-Hui;Yang, Ke-Hu
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.2
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    • pp.947-950
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    • 2013
  • Background: We performed this meta-analysis to assess the effectiveness and safety of axillary dissection in old women. Methods: The Cochrane Library, PubMed, EMBASE and Chinese Biomedical Literature Database were searched and all randomized controlled trials of axillary dissection in old women (at least 60 years old) were considered. Meta-analyses were completed using RevMan5.1. Results: Three eligible randomized controlled trials (RCTs) including 5,337 patients were considered. There was weak evidence in favour of axillary dissection (AD) in old women. The meta-analysis showed that the overall survival (OS) after 1, 3, 5 and 7 years and the disease free survival (DFS) after 1, 3 and 5 year were not statistically significantly different between AD and no AD groups. However, there was a difference in the 7 year DFS. Conclusions: Axillary dissection did not provide survival benefit to the old women with breast cancer analysed. Therefore, axillary dissection is not well-indicated in old women with breast cancer.

Implementation of HMM-Based Speech Recognizer Using TMS320C6711 DSP

  • Bae Hyojoon;Jung Sungyun;Son Jongmok;Kwon Hongseok;Kim Siho;Bae Keunsung
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.391-394
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    • 2004
  • This paper focuses on the DSP implementation of an HMM-based speech recognizer that can handle several hundred words of vocabulary size as well as speaker independency. First, we develop an HMM-based speech recognition system on the PC that operates on the frame basis with parallel processing of feature extraction and Viterbi decoding to make the processing delay as small as possible. Many techniques such as linear discriminant analysis, state-based Gaussian selection, and phonetic tied mixture model are employed for reduction of computational burden and memory size. The system is then properly optimized and compiled on the TMS320C6711 DSP for real-time operation. The implemented system uses 486kbytes of memory for data and acoustic models, and 24.5kbytes for program code. Maximum required time of 29.2ms for processing a frame of 32ms of speech validates real-time operation of the implemented system.

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Web-based Integrated Safety, Health and Environment Management System in Gas Industry (가스공정의 웹기반 통합 안전, 보건, 환경 관리시스템 (WISHE))

  • Yoon En Sup;Han Kyounghoon;Park Jeong Su;Jung Ki Taek;Kim Ku Hwoi;Shin Dongil
    • Journal of the Korean Institute of Gas
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    • v.8 no.1 s.22
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    • pp.48-55
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    • 2004
  • ln this paper, we showed Web-based Integrated Safety, Health and Environment management system(WISHE) in gas industry, which was inspired from the integrated gas safety management system. Using the object oriented information flow to analysis basic modules of safety, health and environment, we made web-based, which enables us to access system anywhere, integrated system and its modules that can meet various laws and rules. This system also can reduce man power and management cost.

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Design of Smart Education e-Board Prototype Based on Internet of Things (사물인터넷 기반 스마트교육 전자보드 프로토타입 설계)

  • Jeon, Minyeong;Cha, Hoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.15-17
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    • 2019
  • Some blind spots of information were occurring because important information such as school events, employment information, attendance information, and major school schedules were currently communicated through home communication messages only. To address this problem, an e-Board prototype was designed to incorporate P2P-based Internet of Things technology in a wired and wireless network based on a survey of data on smart education based on the Internet of Things. In each classroom, necessary information, such as school events, was received in real time from the classroom and shared in the classroom. They also want to design an e-Board prototype for Internet of Things-based smart education because they are easily accessible to anyone even if they do not know how to use e-Board.

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A new structural reliability analysis method based on PC-Kriging and adaptive sampling region

  • Yu, Zhenliang;Sun, Zhili;Guo, Fanyi;Cao, Runan;Wang, Jian
    • Structural Engineering and Mechanics
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    • v.82 no.3
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    • pp.271-282
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    • 2022
  • The active learning surrogate model based on adaptive sampling strategy is increasingly popular in reliability analysis. However, most of the existing sampling strategies adopt the trial and error method to determine the size of the Monte Carlo (MC) candidate sample pool which satisfies the requirement of variation coefficient of failure probability. It will lead to a reduction in the calculation efficiency of reliability analysis. To avoid this defect, a new method for determining the optimal size of the MC candidate sample pool is proposed, and a new structural reliability analysis method combining polynomial chaos-based Kriging model (PC-Kriging) with adaptive sampling region is also proposed (PCK-ASR). Firstly, based on the lower limit of the confidence interval, a new method for estimating the optimal size of the MC candidate sample pool is proposed. Secondly, based on the upper limit of the confidence interval, an adaptive sampling region strategy similar to the radial centralized sampling method is developed. Then, the k-means++ clustering technique and the learning function LIF are used to complete the adaptive design of experiments (DoE). Finally, the effectiveness and accuracy of the PCK-ASR method are verified by three numerical examples and one practical engineering example.

Cointegration based modeling and anomaly detection approaches using monitoring data of a suspension bridge

  • Ziyuan Fan;Qiao Huang;Yuan Ren;Qiaowei Ye;Weijie Chang;Yichao Wang
    • Smart Structures and Systems
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    • v.31 no.2
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    • pp.183-197
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    • 2023
  • For long-span bridges with a structural health monitoring (SHM) system, environmental temperature-driven responses are proved to be a main component in measurements. However, anomalous structural behavior may be hidden incomplicated recorded data. In order to receive reliable assessment of structural performance, it is important to study therelationship between temperature and monitoring data. This paper presents an application of the cointegration based methodology to detect anomalies that may be masked by temperature effects and then forecast the temperature-induced deflection (TID) of long-span suspension bridges. Firstly, temperature effects on girder deflection are analyzed with fieldmeasured data of a suspension bridge. Subsequently, the cointegration testing procedure is conducted. A threshold-based anomaly detection framework that eliminates the influence of environmental temperature is also proposed. The cointegrated residual series is extracted as the index to monitor anomaly events in bridges. Then, wavelet separation method is used to obtain TIDs from recorded data. Combining cointegration theory with autoregressive moving average (ARMA) model, TIDs for longspan bridges are modeled and forecasted. Finally, in-situ measurements of Xihoumen Bridge are adopted as an example to demonstrate the effectiveness of the cointegration based approach. In conclusion, the proposed method is practical for actual structures which ensures the efficient management and maintenance based on monitoring data.

Game Engine Driven Synthetic Data Generation for Computer Vision-Based Construction Safety Monitoring

  • Lee, Heejae;Jeon, Jongmoo;Yang, Jaehun;Park, Chansik;Lee, Dongmin
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.893-903
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    • 2022
  • Recently, computer vision (CV)-based safety monitoring (i.e., object detection) system has been widely researched in the construction industry. Sufficient and high-quality data collection is required to detect objects accurately. Such data collection is significant for detecting small objects or images from different camera angles. Although several previous studies proposed novel data augmentation and synthetic data generation approaches, it is still not thoroughly addressed (i.e., limited accuracy) in the dynamic construction work environment. In this study, we proposed a game engine-driven synthetic data generation model to enhance the accuracy of the CV-based object detection model, mainly targeting small objects. In the virtual 3D environment, we generated synthetic data to complement training images by altering the virtual camera angles. The main contribution of this paper is to confirm whether synthetic data generated in the game engine can improve the accuracy of the CV-based object detection model.

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The Feasibility Study of MRI-based Radiotherapy Treatment Planning Using Look Up Table (Look Up Table을 이용한 자기공명영상 기반 방사선 치료계획의 타당성 분석 연구)

  • Kim, Shin-Wook;Shin, Hun-Joo;Lee, Young-Kyu;Seo, Jae-Hyuk;Lee, Gi-Woong;Park, Hyeong-Wook;Lee, Jae-Choon;Kim, Ae-Ran;Kim, Ji-Na;Kim, Myong-Ho;Kay, Chul-Seung;Jang, Hong-Seok;Kang, Young-Nam
    • Progress in Medical Physics
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    • v.24 no.4
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    • pp.237-242
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    • 2013
  • In the intracranial regions, an accurate delineation of the target volume has been difficult with only the CT data due to poor soft tissue contrast of CT images. Therefore, the magnetic resonance images (MRI) for the delineation of the target volumes were widely used. To calculate dose distributions with MRI-based RTP, the electron density (ED) mapping concept from the diagnostic CT images and the pseudo CT concept from the MRI were introduced. In this study, the look up table (LUT) from the fifteen patients' diagnostic brain MRI images was created to verify the feasibility of MRI-based RTP. The dose distributions from the MRI-based calculations were compared to the original CT-based calculation. One MRI set has ED information from LUT (lMRI). Another set was generated with voxel values assigned with a homogeneous density of water (wMRI). A simple plan with a single anterior 6MV one portal was applied to the CT, lMRI, and wMRI. Depending on the patient's target geometry for the 3D conformal plan, 6MV photon beams and from two to five gantry portals were used. The differences of the dose distribution and DVH between the lMRI based and CT-based plan were smaller than the wMRI-based plan. The dose difference of wMRI vs. lMRI was measured as 91 cGy vs. 57 cGy at maximum dose, 74 cGt vs. 42 cGy at mean dose, and 94 cGy vs. 53 at minimum dose. The differences of maximum dose, minimum dose, and mean dose of the wMRI-based plan were lower than the lMRI-based plan, because the air cavity was not calculated in the wMRI-based plan. These results prove the feasibility of the lMRI-based planning for brain tumor radiation therapy.