• Title/Summary/Keyword: Obstacle model

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A CPU-GPU Hybrid System of Environment Perception and 3D Terrain Reconstruction for Unmanned Ground Vehicle

  • Song, Wei;Zou, Shuanghui;Tian, Yifei;Sun, Su;Fong, Simon;Cho, Kyungeun;Qiu, Lvyang
    • Journal of Information Processing Systems
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    • v.14 no.6
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    • pp.1445-1456
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    • 2018
  • Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

Chemosensitizing effect and mechanism of imperatorin on the anti-tumor activity of doxorubicin in tumor cells and transplantation tumor model

  • Liang, Xin-li;Ji, Miao-miao;Liao, Zheng-gen;Zhao, Guo-wei;Tang, Xi-lan;Dong, Wei
    • The Korean Journal of Physiology and Pharmacology
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    • v.26 no.3
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    • pp.145-155
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    • 2022
  • Multidrug resistance of tumors has been a severe obstacle to the success of cancer chemotherapy. The study wants to investigate the reversal effects of imperatorin (IMP) on doxorubicin (DOX) resistance in K562/DOX leukemia cells, A2780/Taxol cells and in NOD/SCID mice, to explore the possible molecular mechanisms. K562/DOX and A2780/Taxol cells were treated with various concentrations of DOX and Taol with or without different concentrations of IMP, respectively. K562/DOX xenograft model was used to assess anti-tumor effect of IMP combined with DOX. MTT assay, Rhodamine 123 efflux assay, RT-PCR, and Western blot analysis were determined in vivo and in vitro. Results showed that IMP significantly enhanced the cytotoxicity of DOX and Taxol toward corresponding resistance cells. In vivo results illustrated both the tumor volume and tumor weight were significantly decreased after 2-week treatment with IMP combined with DOX compared to the DOX alone group. Western blotting and RT-PCR analyses indicated that IMP downregulated the expression of P-gp in K562/DOX xenograft tumors in NOD/SCID mice. We also evaluated glycolysis and glutamine metabolism in K562/DOX cells by measuring glucose consumption and lactate production. The results revealed that IMP could significantly reduce the glucose consumption and lactate production of K562/DOX cells. Furthermore, IMP could also remarkably repress the glutamine consumption, α-KG and ATP production of K562/DOX cells. Thus, IMP may sensitize K562/DOX cells to DOX and enhance the antitumor effect of DOX in K562/DOX xenograft tumors in NOD/SCID mice. IMP may be an adjuvant therapy to mitigate the multidrug resistance in leukemia chemotherapy.

A Study on the Impact of Covid-19 Pandemic on Korea's Commodity Trade (Covid-19 팬데믹이 한국의 상품무역에 미친 영향에 대한 연구)

  • Ahn, Tae-Kun
    • Journal of Korea Port Economic Association
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    • v.38 no.4
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    • pp.187-198
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    • 2022
  • This study attempted to examine whether the spread of infectious diseases and quarantine measures such as border blockade and restrictions on movement due to the global spread of the COVID-19 pandemic is the cause of a decrease in product trade. To this end, a gravity model analysis was conducted using commodity trade statistics from Korea and major trading partners. As a result of the analysis, it was empirically confirmed that in 2020, the time of the spread of COVID-19, the influence of the COVID-19 pandemic was an obstacle to reducing Korea's trade. However, in the case of 2021, it was not possible to confirm whether the impact of the pandemic had a significant effect on commodity trade. As the impact of the COVID-19 pandemic in 2020 and 2021 is different, the commodity trade situation in 2022 when the COVID-19 epidemic is stably managed is also likely to change. Since factors such as response to COVID-19 and the spread of vaccines vary from country to country, it is thought that such various factors should be fully considered in the process of establishing policies to end the COVID-19 era

Spherical Point Tracing for Synthetic Vehicle Data Generation with 3D LiDAR Point Cloud Data (3차원 LiDAR 점군 데이터에서의 가상 차량 데이터 생성을 위한 구면 점 추적 기법)

  • Sangjun Lee;Hakil Kim
    • Journal of Broadcast Engineering
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    • v.28 no.3
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    • pp.329-332
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    • 2023
  • 3D Object Detection using deep neural network has been developed a lot for obstacle detection in autonomous vehicles because it can recognize not only the class of target object but also the distance from the object. But in the case of 3D Object Detection models, the detection performance for distant objects is lower than that for nearby objects, which is a critical issue for autonomous vehicles. In this paper, we introduce a technique that increases the performance of 3D object detection models, particularly in recognizing distant objects, by generating virtual 3D vehicle data and adding it to the dataset used for model training. We used a spherical point tracing method that leverages the characteristics of 3D LiDAR sensor data to create virtual vehicles that closely resemble real ones, and we demonstrated the validity of the virtual data by using it to improve recognition performance for objects at all distances in model training.

Hybrid machine learning with mode shape assessment for damage identification of plates

  • Pei Yi Siow;Zhi Chao Ong;Shin Yee Khoo;Kok-Sing Lim;Bee Teng Chew
    • Smart Structures and Systems
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    • v.31 no.5
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    • pp.485-500
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    • 2023
  • Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

A Study for an Automatic Calibration of Urban Runoff Model by the SCE-UA (집합체 혼합진화 알고리즘을 이용한 도시유역 홍수유출 모형의 자동 보정에 관한 연구)

  • Kang, Tae-Uk;Lee, Sang-Ho;Kang, Shin-Uk;Park, Jong-Pyo
    • Journal of Korea Water Resources Association
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    • v.45 no.1
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    • pp.15-27
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    • 2012
  • SWMM (Storm Water Management Model) has been widely used in the world as a typical model for flood runoff analysis of urban areas. However, the calibration of the model is difficult, which is an obstacle to easy application. The purpose of the study is to develop an automatic calibration module of the SWMM linked with SCE-UA (Shuffled Complex Evolution-University of Arizona) algorithm. Generally, various objective functions may produce different optimization results for an optimization problem. Thus, five single objective functions were applied and the most appropriate one was selected. In addition to the objective function, another objective function was used to reduce peak flow error in flood simulation. They form a multiple objective function, and the optimization problem was solved by determination of Pareto optima. The automatic calibration module was applied to the flood simulation on the catchment of the Guro 1 detention reservoir and pump station. The automatic calibration results by the multiple objective function were more excellent than the results by the single objective function for model assessment criteria including error of peak flow and ratio of volume between observed and calculated flow. Also, the verification results of the model calibrated by the multiple objective function were reliable. The program could be used in various flood runoff analysis in urban areas.

Application of Image Based VR Technique for Volume Data Web Service (볼륨데이터의 웹 서비스를 위한 이미지 기반 가상현실의 적용)

  • Kim, Yeon-Ho;Park, Jong-Gu
    • The KIPS Transactions:PartB
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    • v.9B no.2
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    • pp.255-262
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    • 2002
  • The Virtual Reality (VR) is an appealing subject which can be applied to various areas because of its merit - removal of time limits and space. Recently, as the technology of xDSL spreads widely, a concern of VR is on the on-line service of 3D model data in real time. But, the immensity of 3D model is an obstacle to achieve these endeavors. To solve these problems, the image based VR technique is applied. The proposed method in this paper is one of solutions on the immensity problem of 3D model data in the on-line services. This paper exploits the mixed technique of image based VR and surface rendering based on volume rendering. By using the proposed method, we can solve the immensity problem. Consequently, tole service user can explore virtual 2D volume model with almost equal to reality of 3D volume model. Furthermore, this paper explains a method to implement this service on general web environments. Of course, to fulfill these procedures, additional skills which reduce consuming time in data mining are also mentioned. The contribution of this paper is to provide a practical method for handling of large volume data web service in real-time. illustrative examples are presented to show the effectiveness of the proposed method.

Decision Support System of Obstacle Avoidance for Mobile Vehicles (다양한 자율주행 이동체에 적용하기 위한 장애물 회피의사 결정 시스템 연구)

  • Kang, Byung-Jun;Kim, Jongwon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.6
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    • pp.639-645
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    • 2018
  • This paper is intended to develop a decision model that can be applied to autonomous vehicles and autonomous mobile vehicles. The developed module has an independent configuration for application in various driving environments and is based on a platform for organically operating them. Each module is studied for decision making on lane changes and for securing safety through reinforcement learning using a deep learning technique. The autonomous mobile moving body operating to change the driving state has a characteristic where the next operation of the mobile body can be determined only if the definition of the speed determination model (according to its functions) and the lane change decision are correctly preceded. Also, if all the moving bodies traveling on a general road are equipped with an autonomous driving function, it is difficult to consider the factors that may occur between each mobile unit from unexpected environmental changes. Considering these factors, we applied the decision model to the platform and studied the lane change decision system for implementation of the platform. We studied the decision model using a modular learning method to reduce system complexity, to reduce the learning time, and to consider model replacement.

Inversion of Small Loop EM Data by Main-Target Emphasizing Approach (주 대상체 강조법에 의한 소형루프 전자탐사 자료의 역산)

  • Cho, In-Ky;Kang, Mi-Kyung;Kim, Ki-Ju
    • Geophysics and Geophysical Exploration
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    • v.9 no.4
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    • pp.299-303
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    • 2006
  • Geologic noise, especially located at shallow depth, can be a great obstacle in the interpretation of geophysical data. Thus, it is important to suppress geologic noise in order to accurately detect major anomalous bodies in the survey area. In the inversion of geophysical data, model parameters at shallow depth, which have small size and low contrast of physical property, can be regarded as one of geologic noise. The least-squares method with smoothness constraint has been widely used in the inversion of geophysical data. The method imposes a big penalty on the large model parameter, while a small penalty on the small model parameter. Therefore, it is not easy to suppress small anomalous boies. In this study, we developed a new inversion scheme which can effectively suppress geologic noise by imposing a big penalty on the slowly varying model parameter and a small penalty on the largely varying model parameter. We call the method MTE (main-target emphasizing) inversion. Applying the method to the inversion of 2.5D small loop EM data, we can ensure that it is effective in suppressing small anomalous boies and emphasizing major anomalous bodies in the survey area.

A Study on the Acceptability for Mobile Payment Platforms by China's Early Elder People (중국 초로(初老) 집단의 모바일 결제 플랫폼에 대한 수용성 연구)

  • Bao, Li Yuan;Pan, Younghwan
    • Journal of the Korea Convergence Society
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    • v.12 no.11
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    • pp.53-67
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    • 2021
  • According to statistics, the number of mobile payment users in China shows an increasing trend year by year. However, less than half of people over 60 years old use mobile payment. The purpose of this study is to explore the reasons for the low usage rate of mobile payment platforms among the elderly in China. Through literature research, questionnaires and interviews, the author found that the main obstacle for the elderly in China to use mobile payment platforms is acceptance barrier. Then, the user experience research method and technology acceptance model (TAM) were combined to construct a new research model and five hypotheses affecting acceptance behavior in the model were summarized. Finally, the Analysis of Covariance(ANCOVA) was used to test the hypotheses and found that satisfaction (SA), perceived usefulness (PU) and job relevance (JR) had significant coefficients of 0.001, 0.000 and 0.004 respectively, all of which were less than 0.05 and therefore had a significant effect on acceptability. The other two elements, perceived ease of use (PE) and self-efficacy (SE), did not have a significant effect on acceptability. Ultimately, a new user experience acceptability model was constructed to provide theoretical support for mobile payment platform developers and designers to develop products from the acceptability perspective, so as to develop more mobile payment methods suitable for elderly users and improve the acceptance of mobile payment by the elderly.