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SSRN 2022年

作者： Ma, Jian Wang, Qiao Chen, Juan Jiang, Rui Song, Weiguo Li, Ruoyu Lian, Liping School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application Technology National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Chengdu610031 China Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University Chengdu610031 China Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Ministry of Transport Beijing Jiaotong University Beijing100044 China State Key Laboratory of Fire Science University of Science and Technology of China Hefei230027 China School of Urban Planning and Design Peking University Shenzhen Graduate School School of Architectural Engineering Shenzhen Polytechnic Shenzhen518055 China

Slow transportation mode, consisting of walking and cycling, plays an important role in urban traffic system. Based on the fact that bicycles and pedestrians often share the common road facility, we conducted bicycle-pedestrian mixed flow experiments to investigate the interaction effect among individuals in a 10 m-long, 3 m-wide passageway, mimicking the zebra crossing area. The goal is to explore the influence of bicycles proportion ( p ) on traffic efficiency and investigate the spatial distribution of agents in the mixed flow. Our analyses showed that the increase of bicycle proportion results in longer passing time and less travel time because of large personal space requirements of cyclists. When the bicycle proportion is small or large, the majority pedestrians (bicycles) were divided into several parts by minor bicycles (pedestrians) along the motion direction. We also recorded the following- and lateral- distance between two nearest individuals to calculate the theoretical formula of the passing time for unidirectional bicycle-pedestrian mixed flow based on the existing formula. Comparing the passing time between numerical calculation and experimental data, the effect coefficients for bicycle and pedestrian were obtained. Focusing on the overtaking bicycles, the through gap, lateral and headway distance that decide the overtaking behavior were analyzed. These findings are the first step toward the development of bicycle-pedestrian mixed flow on zebra crossing, which is contribute to provide practical implications for the planning and design of bicycle and pedestrian shared infrastructures. © 2022, The Authors. All rights reserved.

关键词： Travel time

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Experimental Study on the Zebra Crossing Behavior of Mixed Bicycles and Pedestrians

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SSRN 2022年

关键词： Travel time

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ExpoNAS: Using Exposure-based Candidate Exclusion to Reduce NAS Space for Heterogeneous Pipeline of CNNs

ExpoNAS: Using Exposure-based Candidate Exclusion to Reduce ...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Huijuan Duan Danghui Wang Xingting Zhao Kuizhi Mei Jihe Wang School of Computer Science Northwestern Polytechnical University Xi'an China Engineering Research Center of Embedded System Integration Ministry of Education Northwestern Polytechnical University Xi'an China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Northwestern Polytechnical University Xi'an China

Efficiently deploying neural network models on heterogeneous edge systems faces unique challenges. Two major issues are underutilized pipelines caused by hardware heterogeneity and explosive growth of architecture search space. To address these challenges, we propose ExpoNAS, a framework enabling fast deployment-oriented neural architecture search on heterogeneous platforms. ExpoNAS evaluates model partitioning and deployability before search to meet accuracy and latency constraints. However, repeated partitioning leads to exponential growth in architecture search space. We first observe a strong correlation between operational exposure and accuracy improvement, and then we propose an exposure-based reduction technique that excludes the operations of low exposure. By removing these non-critical operations, the exposure-based pruning successfully reduces architecture search time. Our experiments on popular datasets show that the ExpoNAS pipelined design improves execution efficiency by a factor of 2 compared to traditional batch processing. Without compromising accuracy, ExpoNAS is able to reduce the architecture search time by 47.5% for discovering high-accuracy networks, compared to the SOTA NAS strategies.

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Domain and Content Adaptive Convolution based Multi-Source Domain Generalization for Medical Image Segmentation

arXiv

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arXiv 2021年

作者： Hu, Shishuai Liao, Zehui Zhang, Jianpeng Xia, Yong The National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi'An710072 China

The domain gap caused mainly by variable medical image quality renders a major obstacle on the path between training a segmentation model in the lab and applying the trained model to unseen clinical data. To address this issue, domain generalization methods have been proposed, which however usually use static convolutions and are less flexible. In this paper, we propose a multi-source domain generalization model based on the domain and content adaptive convolution (DCAC) for the segmentation of medical images across different modalities. Specifically, we design the domain adaptive convolution (DAC) module and content adaptive convolution (CAC) module and incorporate both into an encoder-decoder backbone. In the DAC module, a dynamic convolutional head is conditioned on the predicted domain code of the input to make our model adapt to the unseen target domain. In the CAC module, a dynamic convolutional head is conditioned on the global image features to make our model adapt to the test image. We evaluated the DCAC model against the baseline and four state-of-the-art domain generalization methods on the prostate segmentation, COVID-19 lesion segmentation, and optic cup/optic disc segmentation tasks. Our results not only indicate that the proposed DCAC model outperforms all competing methods on each segmentation task but also demonstrate the effectiveness of the DAC and CAC modules. Code is available at https://***/DCAC. © 2021, CC BY-NC-ND.

关键词： Convolution

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Identification of Seed Maize Fields from Hyperspectral Imagery by Fusion of Spectral and Spatial Features

SSRN

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SSRN 2024年

作者： Cheng, Jinpeng Yang, Hao Cao, Xiaoyu Wu, Qiang Zhang, Na Yan, Zhiyu Wang, Hongbin Huang, Linsheng Ma, Xinming Xiong, Shuping Yang, Guijun College of Agronomy Henan Agricultural University Zhengzhou450046 China Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs Information Technology Research Center Beijing Academy of Agriculture and Forestry Sciences Beijing100097 China National Engineering Research Center for Agro-Ecological Big Data Analysis & Application Anhui University Hefei230601 China Zhuhai Orbita Aerospace Science &Technology Co. Ltd Zhuhai519080 China Sinochem Modern Agriculture Co. Ltd. Beijing100031 China College of Geological Engineering and Geomatics Chang’an University Xi’an710054 China

Grasping the planting information of seed maize is utterly important for strengthening the macro-control of the seed industry market and ensuring the safe production of conventional maize. At present, the traditional ground survey is the main method for surveying the planting distribution of seed maize, which is inefficient and expensive. And in the existing remote sensing classification methods of seed maize, most of them use texture information, and seldom use hyperspectral information. Here, we studied the "Zhuhai-1" satellite hyperspectral data to construct the spectral and spatial features of seed maize identification, and then used the Support Vector Machine (SVM) classifier to prepare the planting pattern map of seed maize, and finally an efficient and economical identification model for seed maize based on hyperspectral satellite images was proposed. The classification uses a multi-layer mask method to classify seed corn and conventional corn in the scene of corn planting distribution. The spectral feature extraction method of the classification model compares the two methods of Class Means Matrix Clustering Feature (CMMCF) and PCA-LDA (Principal Component analysis -Linear Discriminant analysis), and the extraction of spatial features uses Multiscale Extended Morphological Profile method (MEMP). Then, four feature combinations of PCA-LDA, CMMCF, PCA-LDA-MEMP and CMMCF-MEMP were constructed for classification. The classification results use overall accuracy (OA), mapping accuracy (PA), and user accuracy (UA) to evaluate the model accuracy;Fisher discriminant ratio (FR) evaluates feature separability. The results of the model show that the FR value of the texture feature in the model is higher than that of the spectral feature, and the texture feature plays an important role in the extraction of seed maize. CMMCF-MEMP-SVM model was the best, OA reached 94.10%, PA and UA extracted from seed maize were 91.28% and 92.43%, respectively. In addition, the CMMCF-MEMP

关键词： Morphology

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Phase Difference Network for Efficient Differentiation of Hepatic Tumors with Multi-Phase CT

Phase Difference Network for Efficient Differentiation of He...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Yuanfeng Wu Geng Chen Zhan Feng Heng Cui Fan Rao Yangfan Ni Zhongke Huang Wentao Zhu Zhejiang Lab Hangzhou China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an China Department of Radiology College of Medicine The First Affiliated Hospital Zhejiang University China Sir Run Run Shaw Hospital School of Medicine Zhejiang University Hangzhou China

Liver cancer has been one of the top causes of cancer-related death. For developing an accurate treatment strategy and raising the survival rate, the differentiation of liver cancers is essential. Multiphase CT recently acts as the primary examination method for clinical diagnosis. Deep learning techniques based on multiphase CT have been proposed to distinguish hepatic cancers. However, due to the recurrent mechanism, RNN-based approaches require expensive calculations whereas CNN-based models fail to explicitly establish temporal correlations among phases. In this paper, we proposed a phase difference network, termed as Phase Difference Network (PDN), to identify two liver cancer, hepatocellular carcinoma and intrahepatic cholangiocarcinoma, from four-phase CT. Specifically, the phase difference was used as interphase temporal information in a differential attention module, which enhanced the feature representation. Additionally, utilizing a multihead self-attention module, a transformer-based classification module was employed to explore the long-term context and capture the temporal relation between phases. Clinical datasets are used in experiments to compare the performance of the proposed strategy versus conventional approaches. The results indicate that the proposed method outperforms the traditional deep learning based methods.

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Characterizing Flight Delay Profiles with a Tensor Factorization Framework

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engineering 2021年第4期7卷 465-472页

作者： Mingyuan Zhang Shenwen Chen Lijun Sun Wenbo Du Xianbin Cao School of Electronic and Information Engineering Beihang UniversityBeijing 100191China National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology Beijing 100191China Department of Civil Engineering and Applied Mechanics McGill UniversityMontrealQC H3A 0C3Canada

In air traffic and airport management,experience gained from past operations is crucial in designing appropriate strategies when facing a new ***,this paper uses massive spatiotemporal flight data to identify similar traffic and delay patterns,which become critical for gaining a better understanding of the aviation system and relevant ***,as the datasets imply complex dependence and higher-order interactions between space and time,retrieving significant features and patterns can be very *** this paper,we propose a probabilistic framework for highdimensional historical flight *** apply a latent class model and demonstrate the effectiveness of this framework using air traffic data from 224 airports in China during 2014–*** find that profiles of each dimension can be clearly divided into various patterns representing different regular *** prove the effectiveness of these patterns,we then create an estimation model that provides preliminary judgment on the airport delay *** outcomes of this study can help airport operators and air traffic managers better understand air traffic and delay patterns according to the experience gained from historical scenarios.

关键词： Air traffic management Flight delay Latent class model Tensor decomposition

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Game Theoretic application to Intersection Management: A Literature Review

arXiv

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arXiv 2023年

作者： Qin, Ziye Ji, Ang Sun, Zhanbo Wu, Guoyuan Hao, Peng Liao, Xishun The School of Transportation and Logistics Southwest Jiaotong University Sichuan Chengdu611756 China The National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan Chengdu611756 China The College of Engineering Center for Environmental Research and Technology University of California at Riverside RiversideCA92507 United States The University of California at Los Angeles Los AngelesCA90095 United States

The emergence of vehicle-to-everything (V2X) technology offers new insights into intersection management. This, however, has also presented new challenges, such as the need to understand and model the interactions of traffic participants, including their competition and cooperation behaviors. Game theory has been widely adopted to study rationally selfish or cooperative behaviors during interactions and has been applied to advanced intersection management. In this paper, we review the application of game theory to intersection management and sort out relevant studies under various levels of intelligence and connectivity. First, the problem of urban intersection management and its challenges are briefly introduced. The basic elements of game theory specifically for intersection applications are then summarized. Next, we present the game-theoretic models and solutions that have been applied to intersection management. Finally, the limitations and potential opportunities for subsequent studies within the game-theoretic application to intersection management are discussed. Copyright © 2023, The Authors. All rights reserved.

关键词： Game theory

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Effect of calcium alumina silicate hydrate nano-seeds on the hydration of low clinker cement

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Journal of Building engineering 2023年 66卷

作者： Liu, Xiao Luo, Qifeng Xie, Hui Li, Shiyu Zhang, Jiale Xia, Chunlei Ding, Yungchin Chen, Yichen Gao, Ruijun Wei, Zhongyuan Zhou, Wu Wang, Ziming Cui, Suping Faculty of Materials and Manufacturing Key Laboratory of Advanced Functional Materials Ministry of Education Beijing University of Technology Beijing100124 China Faculty of Materials and Manufacturing National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of Technology Beijing100124 China Beijing Municipal Engineering Research Institute Beijing100037 China Institute of Mineral Resources Engineering National Taipei University of Technology Taipei10608 China China Building Materials Academy Beijing100024 China Tangshan Longyi Tech. Co Ltd. Tangshan063004 China Guangxi Keda Building Material Chemicals Co Ltd. Nanning530221 China

The replacement of cement clinker with supplementary cementitious materials (SCMs) is considered a very effective way of carbon reduction. However, the slow pozzolanic reaction of SCMs weakens the early strength, which hinders its application. In this study, the dedicated nucleating agents for Al-rich SCMs, C-A-S-H nano-seeds, were synthesized by co-precipitation using polycarboxylate superplasticizer (PCE) as dispersant. The performances of four nano-seeds with different Al/Si and their effects on hydration in 50% metakaolin cement (MK50) were investigated in detail. The results showed that C-A-S-H nano-seeds had a greater strengthening effect than C-S-H nano-seeds especially at early ages, and also accelerated setting, with Al/Si = 0.10 being the most significant. The Al/Si = 0.10 nano-seeds advanced the second main exothermic peak by 6.7 h, promoting the production of stratlingite and causing the highest contents of CH and bound water in hydrated samples. It was also demonstrated by 27Al NMR that C-A-S-H nano-seeds enhanced the reaction degree of metakaolin by producing more C-A-S-H than AFt or AFm. The pozzolanic activity was further explored in the reaction between metakaolin and CH. This study aims to develop an efficient strengthening agent (i.e., C-A-S-H nano-seeds) for low clinker cement, and to reveal the mechanistic difference between them and common C-S-H seeds from the perspectives of hydration and pozzolanic reactions, which is of great significance for the carbon emission reduction of cement industries and solid waste utilization. © 2023 Elsevier Ltd

关键词： Hydration

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A Stepwise Path Selection Scheme Based on Multiple QoS Parameters Evaluation in SDN 17th

A Stepwise Path Selection Scheme Based on Multiple QoS Param...

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17th EAI International Conference on Collaborative Computing: Networking, applications, and Worksharing, CollaborateCom 2021

作者： Liu, Lin Zhou, Jian-Tao Xing, Hai-Feng Guo, Xiao-Yong College of Computer Science Ecological Big Data Engineering Research Center of the Ministry of Education Cloud Computing and Service Software Engineering Laboratory of Inner Mongolia Autonomous Region National and Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Social Computing and Data Processing Key Laboratory of Inner Mongolia Autonomous Region Big Data Analysis Technology Engineering Research Center of Inner Mongolia Autonomous Region Inner Mongolia University Inner Mongolia Hohhot China College of Computer Science and Technology Inner Mongolia Normal University Inner Mongolia Hohhot China College of Computer Information and Management Inner Mongolia University of Finance and Economics Inner Mongolia Hohhot China

ISBN: (纸本)9783030926342

Nowadays, the best-effort service can not guarantee the quality of service (QoS) for all kinds of services. QoS routing is an important method to guarantee QoS requirements. It involves path selection for flows based on the current network status and the performance criteria of the service requirements. However, it is difficult for proposed solutions to obtain all the available paths owing to not fully considering all the QoS parameters of paths. In this paper, we propose SWQoS, a novel, universal, and stepwise QoS guarantee scheme based on multiple QoS parameter evaluation for selecting the available paths including preferred paths, satisfied paths and reluctant paths in SDN. The experiments show that SWQoS can select all the available paths that meet the performance criteria of the service requirements and have better QoS parameter performance compared with other path selection methods. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Quality of service

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