检索结果-内蒙古大学图书馆

Effects of Adaptive Random Deceleration on Traffic Flow

学校读者我要写书评

暂无评论

Journal of Applied Mathematics and Physics 2023年第3期11卷 618-628页

作者： Qi Wang Shu Zhu Liuhua Zhu School of computer Jiangsu University of Science and Technology Zhenjiang China School of Physics and Telecommunication Engineering Yulin Normal University Yulin China Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin China Optoelectronic Information Research Center Yulin Normal University Yulin China

Based on the Nagel-Schreckenberg model, an improved cellular automaton traffic flow model is proposed, in which the random deceleration probability of each vehicle is no longer fixed, but is adaptively adjusted according to the local traffic density in its vision and its current velocity. The numerical simulation results show that the maximum traffic capacity of the improved model under the same parameters is greater than that of the Nagel-Schreckenberg model, and is closer to the measured data. In addition, the traffic flow and vehicle velocity under different meteorological conditions are simulated by using the improved model, and the synchronized flow phenomenon consistent with the actual traffic is reproduced. Meanwhile, the results show that under the same parameters, when the traffic density is equal to 0.3, the traffic flow of the improved model increases by about 11% compared with the original model, and when the traffic density increases to 0.6, the traffic flow increases by about 27%. .

关键词： Traffic Flow Cellular Automaton Adaptive Random Deceleration Synchronized Flow

Medium recoil mode of ∆ production in single isobaric charge-exchange reactions

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Lei, Xin Xiao, Erxi Huang, Yingge Feng, Yujie Wang, Hui Huang, Jiali Gu, Fuchang Zhu, Long Su, Jun Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen University Zhuhai519082 China China Nuclear Data Center China Institute of Atomic Energy Beijing102413 China Guangxi Key Laboratory of Nuclear Physics and Nuclear Technology Guangxi Normal University Guilin541001 China

The dynamic mechanisms underlying single charge-exchange reactions have been investigated using a theoretical framework that combines the Isospin-dependent Quantum Molecular Dynamics (IQMD) model with the statistical decay model GEMINI++. Two distinct channels contribute to the single isobaric charge-exchange reaction: quasi-elastic channel, where neutron-proton scattering drives the charge-exchange, and inelastic channel, where the ∆ particle is produced during the process. In a referenced study [*** 106.014618(2022)], experimental data have revealed that the inelastic channel accounts for approximately 50 percent of the single isobaric charge-exchange reaction. However, our current model fails in reproducing the significant contribution of inelastic channel unless the novel medium recoil mode associated with ∆ production is considered in the calculations. Notably, this in-medium effect arising from inelastic nucleon-nucleon collisions is not yet incorporated into mainstream microscopic transport models. The dynamical properties of protons and pions emitting in the single isobaric charge-exchange reactions are predicted. This exploration of in-medium effects adds a valuable dimension to our understanding of the intricate dynamics involved in single charge-exchange reactions. Copyright © 2024, The Authors. All rights reserved.

关键词： Inelastic neutron scattering

Building a Private Cloud Based on Microservices for Computer Science laboratory in Universities 7

学校读者我要写书评

暂无评论

Building a Private Cloud Based on Microservices for Computer...

7th International Conference on Information Science and Control engineering, ICISCE 2020

作者： Liu, Hao Wang, Zhe Huang, Lan Wang, Kangping Jilin University School of Computer Science and Technology Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun China

ISBN: (纸本)9781728164069

Computer science labs in universities have different demands in cloud computing compared with typical IT companies. They differ greatly in software requirements and resource utilization. As an instance, we propose building a private cloud based on microservices with Docker and Kubernetes in our laboratory to match our labs' typical *** private cloud proposed in this paper is composed of multiple components such as authentication, service gateway, distributed storage, knowledge management, code management, etc. Furthermore, some typical research software systems are deployed as microservices in the private cloud. To satisfy complex software environment requirements, a multi version microservice is implemented. In our microservices platform, users can submit their own microservices and manage these microservices' life cycle through a web interface. In addition, the platform will automatically start and stop low frequency services to improve resource utilization rate. We use laboratory resources to conduct experiments and build a platform. With deploying the platform in our laboratory, it shows that the platform meets most of typical demands in research work and improves research efficiency. © 2020 IEEE.

关键词： Laboratories

The dynamics of tea plantation encroachment into forests and effect on forest landscape pattern during 1991–2021 through time series Landsat images

学校读者我要写书评

暂无评论

Ecological Indicators 2022年第0期141卷

作者： Xiong, Yuan Kang, Qianwen Xu, Weiheng Huang, Shaodong Dai, Fei Wang, Leiguang Lu, Ning Kou, Weili College of Big Data and Intelligent Engineering Southwest Forestry University Kunming650233 China Institute of Big Data and Artificial Intelligence Southwest Forestry University Yunnan Kunming650233 China Key Laboratory of National Forestry and Grassland Administration on Forestry and Ecological Big Data Southwest Forestry University Yunnan Kunming650233 China

Tea plantations encroachment into forests has occurred in the major tea planting area of Yunnan province, China in the past decades. However, the dynamics of tea plantation encroachment into forests and the effect on forest landscape pattern is not clear. In this study, we proposed a method to evaluate the dynamic effects of tea plantation encroachment on forest landscape pattern change by using time series Landsat 5/7/8 data from 1991 to 2021 on the Google Earth Engine (GEE) platform. First, a pixel- and phenology-based algorithm was applied to generate tea plantations encroachment into forests maps for seven historical periods. Second, three indices including the tea plantations encroachment index (TPEI), the growth area of tea plantations encroachment into forests (GATEF), and the growth index of tea plantations encroachment into forests (GITEF) were used to quantify the tea plantations encroachment into forests of seven historical periods. Third, the effects of forests landscape pattern resulting from tea plantations encroachment were evaluated in class metrics and landscape metrics respectively. Our results show a total of 13,721 ha of GATEF from the early 1990s to the early 2020s. The GITEF increased from the early 1990s to the early 2010s and decreased from the early 2010s to the early 2020s in our study area. And the TPEI indicates that the edge encroachment mode dominated in our study period. Correlation analysis indicates that tea plantations encroachment level had significant correlation coefficients with landscape pattern indices (such as CONTAG (r = −0.91), ED (r = 0.95), DIVISION (r = 0.85), and SHEI (r = 0.86)), which indicates that the level of tea plantations encroachment affects significantly the forest landscape pattern. This study provides a promising approach to quantifying the effect of forest landscape pattern results from tea plantations encroachment. © 2022 The Authors

关键词： Deforestation

CG-SSD: Corner Guided Single Stage 3D Object Detection from LiDAR Point Cloud

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Ma, Ruiqi Chen, Chi Yang, Bisheng Li, Deren Wang, Haiping Cong, Yangzi Hu, Zongtian State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430079 China Engineering Research Center of Space-Time Data Capturing and Smart Application The Ministry of Education of P.R.C. China

At present, the anchor-based or anchor-free models that use LiDAR point clouds for 3D object detection use the center assigner strategy to infer the 3D bounding boxes. However, in a real world scene, the LiDAR can only acquire a limited object surface point clouds, but the center point of the object does not exist. Obtaining the object by aggregating the incomplete surface point clouds will bring a loss of accuracy in direction and dimension estimation. To address this problem, we propose a corner-guided anchor-free single-stage 3D object detection model (CG-SSD1).Firstly, 3D sparse convolution backbone network composed of residual layers and sub-manifold sparse convolutional layers are used to construct bird's eye view (BEV) features for further deeper feature mining by a lite U-shaped network;Secondly, a novel corner-guided auxiliary module (CGAM) is proposed to incorporate corner supervision signals into the neural network. CGAM is explicitly designed and trained to detect partially visible and invisible corners to obtains a more accurate object feature representation, especially for small or partial occluded objects;Finally, the deep features from both the backbone networks and CGAM module are concatenated and fed into the head module to predict the classification and 3D bounding boxes of the objects in the scene. The experiments demonstrate CG-SSD achieves the state-of-art performance on the ONCE benchmark for supervised 3D object detection using single frame point cloud data, with 62.77%mAP. Additionally, the experiments on ONCE and Waymo Open dataset show that CGAM can be extended to most anchor-based models which use the BEV feature to detect objects, as a plug-in and bring +1.17%∼+14.27%AP *** Codes 00-02 Copyright © 2022, The Authors. All rights reserved.

关键词： Object recognition

Masked Thought: Simply Masking Partial Reasoning Steps Can Improve Mathematical Reasoning Learning of Language Models

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Chen, Changyu Wang, Xiting Lin, Ting-En Lv, Ang Wu, Yuchuan Gao, Xin Wen, Ji-Rong Yan, Rui Li, Yongbin Beijing Key Laboratory of Big Data Management and Analysis Methods Gaoling School of Artificial Intelligence Renmin University of China China Alibaba Group China Engineering Research Center of Next-Generation Intelligent Search and Recommendation Ministry of Education China Computational Bioscience Research Center KAUST Saudi Arabia

In reasoning tasks, even a minor error can cascade into inaccurate results, leading to suboptimal performance of large language models in such domains. Earlier fine-tuning approaches sought to mitigate this by leveraging more precise supervisory signals from human labeling, larger models, or self-sampling, although at a high cost. Conversely, we develop a method that avoids external resources, relying instead on introducing perturbations to the input. Our training approach randomly masks certain tokens within the chain of thought, a technique we found to be particularly effective for reasoning tasks. When applied to fine-tuning with GSM8K on Llama-2-7B, this method achieved a 5% improvement in GSM8K accuracy and a 10% improvement in GSM-IC accuracy over standard supervised fine-tuning with a few codes modified. Furthermore, it is complementary to existing methods. When integrated with related explicit data augmentation methods, it leads to improvements across five datasets of various augmentation methods, as well as two different base models. We further investigate the mechanisms behind this improvement through case studies and quantitative analysis, suggesting that our approach may provide superior support for the model in capturing long-distance dependencies, especially those related to questions. This enhancement could deepen understanding of the premises in questions and prior steps. Our code is available at Github. © 2024, CC BY.

关键词： Signal sampling

TJCCT: A Two-timescale Approach for UAV-assisted Mobile Edge Computing

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Sun, Zemin Sun, Geng Wu, Qingqing He, Long Liang, Shuang Pan, Hongyang Niyato, Dusit Yuen, Chau Leung, Victor C.M. The College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China The School of Information Science and Technology Northeast Normal University Changchun130024 China The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The School of Electrical and Electronics Engineering Nanyang Technological University Singapore639798 Singapore The College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) is emerging as a promising paradigm to provide aerial-terrestrial computing services in close proximity to mobile devices (MDs). However, meeting the demands of computation-intensive and delay-sensitive tasks for MDs poses several challenges, including the demand-supply contradiction between MDs and MEC servers, the demand-supply heterogeneity between MDs and MEC servers, the trajectory control requirements on energy efficiency and timeliness, and the different time-scale dynamics of the network. To address these issues, we first present a hierarchical architecture by incorporating terrestrial-aerial computing capabilities and leveraging UAV flexibility. Furthermore, we formulate a joint computing resource allocation, computation offloading, and trajectory control problem to maximize the system utility. Since the problem is a non-convex and NP-hard mixed integer nonlinear programming (MINLP), we propose a two-timescale joint computing resource allocation, computation offloading, and trajectory control (TJCCT) approach for solving the problem. In the short timescale, we propose a price-incentive model for on-demand computing resource allocation and a matching mechanism-based method for computation offloading. In the long timescale, we propose a convex optimization-based method for UAV trajectory control. Besides, we theoretically prove the stability, optimality, and polynomial complexity of TJCCT. Extended simulation results demonstrate that the proposed TJCCT outperforms the comparative algorithms in terms of the system utility, average processing rate, average completion delay, and average completion ratio. Copyright © 2024, The Authors. All rights reserved.

关键词： Computation offloading

Disentangled Representation Learning with Transmitted Information Bottleneck

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Dang, Zhuohang Luo, Minnan Jia, Chengyou Dai, Guang Wang, Jihong Chang, Xiaojun Wang, Jingdong The School of Computer Science and Technology The Ministry of Education Key Laboratory of Intelligent Networks and Network Security The Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi'an Jiaotong University Shaanxi Xi’an710049 China The SGIT AI Laboratory Xi’an710048 China The State Grid Shaanxi Electric Power Company Ltd. State Grid Corporation of China Xi’an710048 China The School of Information Science and Technology University of Science and Technology of China Hefei230026 China Abu Dhabi United Arab Emirates Baidu Inc Beijing100085 China

Encoding only the task-related information from the raw data, i.e., disentangled representation learning, can greatly contribute to the robustness and generalizability of models. Although significant advances have been made by regularizing the information in representations with information theory, two major challenges remain: 1) the representation compression inevitably leads to performance drop;2) the disentanglement constraints on representations are in complicated optimization. To these issues, we introduce Bayesian networks with transmitted information to formulate the interaction among input and representations during disentanglement. Building upon this framework, we propose DisTIB (Transmitted Information Bottleneck for Disentangled representation learning), a novel objective that navigates the balance between information compression and preservation. We employ variational inference to derive a tractable estimation for DisTIB. This estimation can be simply optimized via standard gradient descent with a reparameterization trick. Moreover, we theoretically prove that DisTIB can achieve optimal disentanglement, underscoring its superior efficacy. To solidify our claims, we conduct extensive experiments on various downstream tasks to demonstrate the appealing efficacy of DisTIB and validate our theoretical analyses. Copyright © 2023, The Authors. All rights reserved.

关键词： Information theory

Special issue: Innovative applications of big data and artificial intelligence

学校读者我要写书评

暂无评论

Frontiers of engineering Management 2022年第4期9卷 517-519页

作者： W.Art CHAOVALITWONGSE Ye YUAN Qingpeng ZHANG Jianguo LIU Department of Industrial Engineering University of ArkansasFayettevilleAR 72701USA School of Artificial Intelligence and Automation State Key Laboratory of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and TechnologyWuhan 430074China School of Data Science City University of Hong KongHong KongChina Institute of Accounting and Finance Shanghai University of Finance and EconomicsShanghai 200433China

Big data refers to complex data sets that cannot be processed using traditional data processing *** could also be defined as a large amount of unstructured or structured data from various *** intelligence(AI)refers to the science of expressing and acquiring knowledge using data,algorithms,and computing *** far,the big data industry chain is gradually mature,leading to a combination of big data and AI techniques developed in comprehensive *** cutting-edge technologies of big data and AI have played an increasingly important role in the innovative development of various industries such as epidemic prevention and control,emergency management,social governance,manufacturing,medical services,intelligent transportation,Internet of Things/supply chain,Internet industry,new media,and so *** addition,there are many typical innovative projects,which are being produced.

关键词： artificial services prevention