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Risk assessment of oil and gas investment environment in countries along the Belt and Road Initiative 被引量:1
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作者 Bao-Jun Tang Chang-Jing Ji +3 位作者 Yu-Xian Zheng Kang-Ning Liu Yi-Fei Ma Jun-Yu Chen 《Petroleum Science》 SCIE EI CAS CSCD 2024年第2期1429-1443,共15页
With the implementation of the Belt and Road Initiative, China is deepening its cooperation in oil and gas resources with countries along the Initiative. In order to better mitigate risks and enhance the safety of inv... With the implementation of the Belt and Road Initiative, China is deepening its cooperation in oil and gas resources with countries along the Initiative. In order to better mitigate risks and enhance the safety of investments, it is of significant importance to research the oil and gas investment environment in these countries for China's overseas investment macro-layout. This paper proposes an indicator system including 27 indicators from 6 dimensions. On this basis, game theory models combined with global entropy method and analytic hierarchy process are applied to determine the combined weights, and the TOPSIS-GRA model is utilized to assess the risks of oil and gas investment in 76 countries along the Initiative from 2014 to 2021. Finally, the GM(1,1) model is employed to predict risk values for 2022-2025. In conclusion, oil and gas resources and political factors have the greatest impact on investment environment risk, and 12 countries with greater investment potential are selected through cluster analysis in conjunction with the predicted results. The research findings may provide scientific decisionmaking recommendations for the Chinese government and oil enterprises to strengthen oil and gas investment cooperation with countries along the Belt and Road Initiative. 展开更多
关键词 Belt and road Initiative Oil and Gas Investment Risk assessment
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A Brief Discussion on the Development of the Silk-Weaving Industry Along the “Southern Silk Road” in Yunnan 被引量:1
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作者 Lin Kaiqiang 《Contemporary Social Sciences》 2024年第1期18-33,共16页
Ancient Yunnan was one of the most significant regions along China’s ancient“Southern Silk Road.”During the Nanzhao period(738–902)of the late Tang Dynasty,Yunnan’s silk-weaving industry underwent a qualitative l... Ancient Yunnan was one of the most significant regions along China’s ancient“Southern Silk Road.”During the Nanzhao period(738–902)of the late Tang Dynasty,Yunnan’s silk-weaving industry underwent a qualitative leap as skilled silk craftsmen from the Bashu area migrated to Yunnan and introduced mulberry planting,silkworm breeding,and advanced silk-weaving techniques from Sichuan to the region.Consequently,people in Yunnan gradually acquired expertise in brocade weaving and embroidery.Many even mastered complex silk-weaving techniques.The development and progress of the silk-weaving industry in the ancient Yunnan region were intricately linked to the economic function and value of silk as both a commodity and currency along the“Southern Silk Road.”The local government in ancient Yunnan was greatly motivated by the economic interests brought by the development of silk-related industries and recognized the significance of developing the local silk industry.They even initiated a campaign to capture skilled silk craftsmen from Sichuan,aiming to foster the growth of the silk-weaving industry in Yunnan.After years of dedicated efforts from the local government in ancient Yunnan,the region emerged as a significant hub for silk production along China’s ancient“Southern Silk Road.”Despite the devastation caused by the wars in other parts of the country,Yunnan’s silk industry continued to thrive and provide ample silk products to sustain trade along this renowned route.In the contemporary era,amidst the decline of the silk-weaving industry in eastern China,Yunnan has proposed an industrial development strategy known as“relocating the silk-weaving industry from east to west.”This involves introducing advanced silk production techniques from the eastern regions into Yunnan to enhance and enrich its local silk industry,thereby establishing it as a traditional national sector and securing a competitive position within the global silk market.The historical experience of Yunnan’s silk industry demonstrated that economic development opportunities can only be seized through proactive endeavors rather than passive anticipation.The modern Yunnan silk industry,which upholds its historical traditions,continues to actively engage in international high-end technical cooperation,thus ensuring the enduring vitality of the ancient“Southern Silk Road.” 展开更多
关键词 Southern Silk road Bashu area YUNNAN silk-weaving technique
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基于ROAD的租车订购系统业务流程建模
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作者 严志超 倪枫 +3 位作者 刘姜 李业勋 陈年年 周兴郡 《智能计算机与应用》 2024年第5期227-234,共8页
基于业务架构为中心的企业架构开发思路,采用开放组架构框架(TOGAF)业务架构ACF元模型的划分,提出了一种ROAD架构迭代建模方法。针对目前ROAD元架构中业务活动模型采用IDEF0的活动模型导致的面向场景业务能力的不足,文中通过使用BPMN模... 基于业务架构为中心的企业架构开发思路,采用开放组架构框架(TOGAF)业务架构ACF元模型的划分,提出了一种ROAD架构迭代建模方法。针对目前ROAD元架构中业务活动模型采用IDEF0的活动模型导致的面向场景业务能力的不足,文中通过使用BPMN模型来覆盖IDEF0的活动建模,避免在描述复杂的业务过程时可能存在的局限性,并且更好地捕捉和表示所有的细节和关系,不会使得模型过于抽象。从而实现面向场景的系统建模和管理,提高业务架构设计的效率和精度。最后,文章中以旅游出行租车订购系统为例的方法,采用ROAD元架构方法建立场景化业务架构模型组,并对其进行讨论和改进,为现有架构体系提供一种面向场景的扩展思路。 展开更多
关键词 业务架构建模 road元架构 BPMN IDEF0
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3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles
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作者 Dun Cao Jia Ru +3 位作者 Jian Qin Amr Tolba Jin Wang Min Zhu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1365-1384,共20页
Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transp... Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety. 展开更多
关键词 Internet of vehicles road networks 3D road model structure recognition GIS
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Automation in road distress detection,diagnosis and treatment
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作者 Xu Yang Jianqi Zhang +3 位作者 Wenbo Liu Jiayu Jing Hao Zheng Wei Xu 《Journal of Road Engineering》 2024年第1期1-26,共26页
Road transportation plays a crucial role in society and daily life,as the functioning and durability of roads can significantly impact a nation's economic development.In the whole life cycle of the road,the emerge... Road transportation plays a crucial role in society and daily life,as the functioning and durability of roads can significantly impact a nation's economic development.In the whole life cycle of the road,the emergence of disease is unavoidable,so it is necessary to adopt relevant technical means to deal with the disease.This study comprehensively reviews the advancements in computer vision,artificial intelligence,and mobile robotics in the road domain and examines their progress and applications in road detection,diagnosis,and treatment,especially asphalt roads.Specifically,it analyzes the research progress in detecting and diagnosing surface and internal road distress and related techniques and algorithms are compared.In addition,also introduces various road gover-nance technologies,including automated repairs,intelligent construction,and path planning for crack sealing.Despite their proven effectiveness in detecting road distress,analyzing diagnoses,and planning maintenance,these technologies still confront challenges in data collection,parameter optimization,model portability,system accuracy,robustness,and real-time performance.Consequently,the integration of multidisciplinary technologies is imperative to enable the development of an integrated approach that includes road detection,diagnosis,and treatment.This paper addresses the challenges of precise defect detection,condition assessment,and unmanned construction.At the same time,the efficiency of labor liberation and road maintenance is achieved,and the automation level of the road engineering industry is improved. 展开更多
关键词 road detection road diagnosis road treatment Deep learning Intelligent maintenance
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Local failure mechanism of sand-blocking fence in latticed dune along desert roads
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作者 LI Liangying LV Lele +3 位作者 LI Qi WANG Zhenqiang YANG Youhai YIN Wenhua 《Journal of Mountain Science》 SCIE CSCD 2024年第2期526-537,共12页
The latticed dunes in the Tengger Desert are widely distributed,and the sand-blocking fence placed here are highly susceptible to local failure due to complex wind-sand activities,posing a serious threat to the safe o... The latticed dunes in the Tengger Desert are widely distributed,and the sand-blocking fence placed here are highly susceptible to local failure due to complex wind-sand activities,posing a serious threat to the safe operation of the highway.To explore the local failure mechanism of sand-blocking fence in the latticed dune area,the local failure of sand-blocking fence in the latticed dune areas along the Wuhai-Maqin Highway in China was observed.Taking the first main ridge of the latticed dune as the placement location,the structure of the wind-sand flow field of sand-blocking fence placed at top,the bottom and the middle of windward slope was analyzed by Computational Fluid Dynamics(CFD).The results show that when placed at top of the first main ridge,the wind speed near the sand-blocking fence is the highest,up to 15.23 m/s.Therefore,the wind load strength on the sand barrier is correspondingly larger,up to 232.61 N∙m-2.As the strength of material continues to decrease,the nylon net is prone to breakage.The roots of the angle steel posts are susceptible to hollowing by vortex action,which can cause sand-blocking fence to fall over in strong wind conditions.When placed at the bottom of windward slope,wind speed drop near sand-blocking fence is greatest,with the decrease of 12.48-14.32 m/s compared to the original wind speed.This is highly likely to lead to large-scale deposition of sand particles and burial of the sand-blocking fence.When placed in the middle of windward slope,sand-blocking fence is subjected to less wind load strength(168.61N∙m-2)and sand particles are mostly deposited at the bottom of windward slope,with only a small amount of sand accumulating at the root of sand-blocking fence.Based on field observations and numerical modelling results,when the sand-blocking fence is placed in latticed dune area,it should be placed in the middle of the windward slope of the first main ridge as a matter of priority.Besides the sand-blocking fence should be placed at the top of the first main ridge,and sand fixing measures should be added. 展开更多
关键词 Latticed dune Sand-blocking fence Local failure Numerical simulation Desert roads
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ConvNeXt-UperNet-Based Deep Learning Model for Road Extraction from High-Resolution Remote Sensing Images
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作者 Jing Wang Chen Zhang Tianwen Lin 《Computers, Materials & Continua》 SCIE EI 2024年第8期1907-1925,共19页
When existing deep learning models are used for road extraction tasks from high-resolution images,they are easily affected by noise factors such as tree and building occlusion and complex backgrounds,resulting in inco... When existing deep learning models are used for road extraction tasks from high-resolution images,they are easily affected by noise factors such as tree and building occlusion and complex backgrounds,resulting in incomplete road extraction and low accuracy.We propose the introduction of spatial and channel attention modules to the convolutional neural network ConvNeXt.Then,ConvNeXt is used as the backbone network,which cooperates with the perceptual analysis network UPerNet,retains the detection head of the semantic segmentation,and builds a new model ConvNeXt-UPerNet to suppress noise interference.Training on the open-source DeepGlobe and CHN6-CUG datasets and introducing the DiceLoss on the basis of CrossEntropyLoss solves the problem of positive and negative sample imbalance.Experimental results show that the new network model can achieve the following performance on the DeepGlobe dataset:79.40%for precision(Pre),97.93% for accuracy(Acc),69.28% for intersection over union(IoU),and 83.56% for mean intersection over union(MIoU).On the CHN6-CUG dataset,the model achieves the respective values of 78.17%for Pre,97.63%for Acc,65.4% for IoU,and 81.46% for MIoU.Compared with other network models,the fused ConvNeXt-UPerNet model can extract road information better when faced with the influence of noise contained in high-resolution remote sensing images.It also achieves multiscale image feature information with unified perception,ultimately improving the generalization ability of deep learning technology in extracting complex roads from high-resolution remote sensing images. 展开更多
关键词 Deep learning semantic segmentation remote sensing imagery road extraction
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Toxicity Evaluation of Different Exposure Scenarios of Road Dust Using Daphnia magna and Artemia salina as Aquatic Organisms, and Prosopis cineraria and Vachellia tortilis as Native Plant Species
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作者 Hilal K. Al-Shidi Hameed Sulaiman 《Open Journal of Air Pollution》 2024年第3期73-86,共14页
Particulate matter (PM10) deposited as road dust is considered an important source of contamination from atmosphere. However, there are limited studies on the toxicity of road dust as such on different organisms. This... Particulate matter (PM10) deposited as road dust is considered an important source of contamination from atmosphere. However, there are limited studies on the toxicity of road dust as such on different organisms. This study evaluates the toxicity of road dust using different extraction scenarios on Daphnia magna and Artemia salina as aquatic organisms and also on Prosopis cineraria and Vachellia tortilis as local plant species. Chemical analysis of different extracts shows considerable amount of trace metals, however the trace metals in the dust extract associated with suspended sediment were not absorbed by the receptors. On the other hand, the concentration of trace metals in the artificial mixture was found bioavailable and absorbed causing a high percentage of mortality. In the plant assay, significant difference was obtained in the germination percentage between the control and three different extraction exposures in both plant species. The mean root length of P. cineraria and V. tortilis were higher in 20% and 50% extracts than the control probably due to the availability of nutrients from the dust extract. Interestingly however, the seedling vigor index was the opposite with higher index in the control and lower in dust extracts that contain heavy metals. 展开更多
关键词 road Dust Heavy Metals TOXICITY BIOAVAILABILITY Holding Time
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Unstructured Road Extraction in UAV Images based on Lightweight Model
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作者 Di Zhang Qichao An +3 位作者 Xiaoxue Feng Ronghua Liu Jun Han Feng Pan 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第2期372-384,共13页
There is no unified planning standard for unstructured roads,and the morphological structures of these roads are complex and varied.It is important to maintain a balance between accuracy and speed for unstructured roa... There is no unified planning standard for unstructured roads,and the morphological structures of these roads are complex and varied.It is important to maintain a balance between accuracy and speed for unstructured road extraction models.Unstructured road extraction algorithms based on deep learning have problems such as high model complexity,high computational cost,and the inability to adapt to current edge computing devices.Therefore,it is best to use lightweight network models.Considering the need for lightweight models and the characteristics of unstructured roads with different pattern shapes,such as blocks and strips,a TMB(Triple Multi-Block)feature extraction module is proposed,and the overall structure of the TMBNet network is described.The TMB module was compared with SS-nbt,Non-bottleneck-1D,and other modules via experiments.The feasibility and effectiveness of the TMB module design were proven through experiments and visualizations.The comparison experiment,using multiple convolution kernel categories,proved that the TMB module can improve the segmentation accuracy of the network.The comparison with different semantic segmentation networks demonstrates that the TMBNet network has advantages in terms of unstructured road extraction. 展开更多
关键词 Unstructured road Lightweight model Triple Multi-Block(TMB) Semantic segmentation net
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Numerical Prediction of Ride Comfort of Tracked Vehicle Equipped with Novel Flexible Road Wheels
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作者 Yaoji Deng Zhiyue Wang +3 位作者 Youqun Zhao Junjie Gong Hui Shen Fen Lin 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第4期277-289,共13页
Enhancing ride comfort has always constituted a crucial focus in the design and research of modern tracked vehicles,heavily reliant on the driving system's performance.While the road wheel is a key component of th... Enhancing ride comfort has always constituted a crucial focus in the design and research of modern tracked vehicles,heavily reliant on the driving system's performance.While the road wheel is a key component of the driving system,traditional road wheels predominantly adopt a solid structure,exhibiting subpar adhesion performance and damping effects,thereby falling short of meeting the demands for high-speed,stable,and long-distance driving in tracked vehicles.Addressing this issue,this paper proposes a novel type of flexible road wheel(FRW)characterized by a catenary construction.The study investigates the ride comfort of tracked vehicles equipped with flexible road wheels by integrating finite element and vehicle dynamic.First,three-dimensional(3D)finite element(FE)models of both flexible and rigid road wheels are established,considering material and contact nonlinearities.These models are validated through a wheel radial loading test.Based on the validated FE model,the paper uncovers the relationship between load and radial deformation of the road wheel,forming the basis for a nonlinear mathematical model.Subsequently,a half-car model of a tracked vehicle with seven degrees of freedom is established using Newton's second law.A random road model,considering the track effect and employing white noise,is constructed.The study concludes by examining the ride comfort of tracked vehicles equipped with flexible and rigid road wheels under various speeds and road grades.The results demonstrate that,in comparison to the rigid road wheel(RRW),the flexible road wheel enhances the ride comfort of tracked vehicles on randomly uneven roads.This research provides a theoretical foundation for the implementation of flexible road wheels in tracked vehicles. 展开更多
关键词 Ride comfort Flexible road wheel Finite element model Dynamic model Tracked vehicle
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Exploring the Factors Associated with 12-Month Non-Return to Work among Motorcyclists Involved in Road Accidents
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作者 Yolaine Glèlè-Ahanhanzo Donatien Daddah +2 位作者 Alphonse Kpozehouen Bella Hounkpè Dos Santos Moussiliou N. Paraiso 《Open Journal of Preventive Medicine》 2024年第1期1-16,共16页
Introduction: Motorcyclists bear a disproportionate burden of morbidity and mortality from road accidents. In addition, the consequences of these accidents affect the ability of victims to return to work. This study a... Introduction: Motorcyclists bear a disproportionate burden of morbidity and mortality from road accidents. In addition, the consequences of these accidents affect the ability of victims to return to work. This study aimed to determine the prevalence and factors associated with non-return to work among surviving motorcyclists involved in road accidents 12 months after the event. Materials and Methods: It was a cross-sectional study conducted using data from a cohort of motorcyclists involved in accidents and recruited in five hospitals in Benin from July 2019 to January 2020. The dependent variable was non-return to work 12 months after the accident (yes vs no). The independent variables were categorized into two groups: baseline and 12-month follow-up variables. Logistic regression was used to determine the factors associated with non-return to work at 12 months among the participants. Results: Among the 362 participants, 55 (15.19%, 95% CI = 11.84 - 19.29) had not returned to work 12 months after the accident. Risk factors for non-return to work identified were: smoking (aOR = 4.41, 95% CI = 1.44 - 13.56, p = 0.010), hospitalization (aOR = 2.87, 95% CI = 1.14 - 7.24, p Conclusion: The prevalence of non-return to work at 12 months was high among surviving motorcyclists involved in road accidents in Benin. Integrated support for patients based on identified risk factors should effectively improve their return to work. 展开更多
关键词 road Accident Return to Work MOTORCYCLISTS HOSPITAL Mental Health COHORT BENIN
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The First Overseas Cooperation Station of Silk Road People-to-People Connectivity Unveiled in Budapest,Hungary
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《International Understanding》 2024年第2期44-45,共2页
On May 2nd,the Thematic Forum on China-Hungary Belt and Road Pragmatic Cooperation was held in Budapest,the capital of Hungary,during which,the China-Hungary Cooperation Station of Silk Road People-to-People Connectiv... On May 2nd,the Thematic Forum on China-Hungary Belt and Road Pragmatic Cooperation was held in Budapest,the capital of Hungary,during which,the China-Hungary Cooperation Station of Silk Road People-to-People Connectivity was officially launched.This is the first overseas station under the Action on Silk Road People-to-People Connectivity.It will surely provide important support to the achievement of more fruitful results in people-to-people exchanges and cooperation between the two countries. 展开更多
关键词 CONNECTIVITY road Budapest
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"Silk Road People-to-People Connectivity"Care for the Future Donation Ceremony Held in Nay Pyi Taw,Myanmar
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《International Understanding》 2024年第2期46-47,共2页
On April 1Oth,“Silk Road People-to-People Connectivity”Care for the Future Activity and a donation ceremony of school sports goods were held at China-Myanmar Friendship School,Basic Education High School(BEHS)No.14,... On April 1Oth,“Silk Road People-to-People Connectivity”Care for the Future Activity and a donation ceremony of school sports goods were held at China-Myanmar Friendship School,Basic Education High School(BEHS)No.14,in Nay Pyi Taw,Myanmar. 展开更多
关键词 road Basic CONNECTIVITY
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The 9th China-Mongolia-Russia Tea Road City Cooperation Conference Held in Hanchuan,Xiaogan City,Hubei Province
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《International Understanding》 2024年第2期52-54,共3页
The 9th China-Mongolia-Russia Tea Road City Cooperation Conference(the Conference for short)was held from April 17 to 19 at Huanglong Lake International Conference Centre in Hanchuan,Xiaogan City,which is an important... The 9th China-Mongolia-Russia Tea Road City Cooperation Conference(the Conference for short)was held from April 17 to 19 at Huanglong Lake International Conference Centre in Hanchuan,Xiaogan City,which is an important stop along the waterway of the tea road in Hubei Province.Themed Civilisation Exchanges and Mutual Learning for Win-Win City Cooperation,the Conference is on the list of the Multilateral Cooperation Deliverables of the Third Belt and Road Forum for International Cooperation.It is an important practice to implement the guiding principles of the keynote speech delivered by President Xi Jinping at the opening ceremony of the third BRF,as well as to carry forward the Deliverables of the BRF in a quality way. 展开更多
关键词 Province. road TEA
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The Thematic Forum on China-Hungary Belt and Road Pragmatic Cooperation Held in Budapest
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《International Understanding》 2024年第2期50-51,共2页
The Thematic Forum on China-Hungary Belt and Road Pragmatic Cooperation was held on May 2nd in Budapest,capital of Hungary.Liu Hongcai,Vice-President of the Chinese Association for International Understanding(CAFIU)sa... The Thematic Forum on China-Hungary Belt and Road Pragmatic Cooperation was held on May 2nd in Budapest,capital of Hungary.Liu Hongcai,Vice-President of the Chinese Association for International Understanding(CAFIU)said in his speech that all walks of life in China and Hungary should make great efforts to implement the important consensus between the state leaders,promote people-to-people exchanges and mutual learning among civilisation in an in-depth way,create more driving forces aiming at the future and fully leverage the advantage of multi-level cooperation platforms between the two countries,thus playing a constructive role in tackling global challenges together. 展开更多
关键词 FORUM road mutual
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"Silk Road People-to-People Connectivity"China-Cambodia Donation Activity Held in Phnom Penh
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《International Understanding》 2024年第2期48-49,共2页
On March 26th,the"Silk Road People-to-People Connectivity"China-Cambodia Donation Activity was held at Indradevi High School in Phnom Penh,Cambodia.Lv Xuejun,President and Chief Editor of the Contemporary Wo... On March 26th,the"Silk Road People-to-People Connectivity"China-Cambodia Donation Activity was held at Indradevi High School in Phnom Penh,Cambodia.Lv Xuejun,President and Chief Editor of the Contemporary World,Pay Sambo,Secretary General of Cambodia Civil Society Association Forum,Wu Chuanbing,Councilor of Chinese Embassy in Cambodia,Hu Jianguang,Deputy Director of the Education Committee of Haidian District of Beijing,Liu Zhanguo,Director of China Foundation for Peace and Development(CFPD)Cambodia Office,Soung Houth,President of National Union Alliance Chamber of Cambodia(NACC),Neak Sothea,President of Indradevi High School and other participants attended the event. 展开更多
关键词 CONNECTIVITY DIRECTOR road
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Resilience assessment and optimization method of city road network in the post-earthquake emergency period
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作者 Wang Haoran Xiao Jia +1 位作者 Li Shuang Zhai Changhai 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2024年第3期765-779,共15页
The post-earthquake emergency period,which is a sensitive time segment just after an event,mainly focuses on saving life and restoring social order.To improve the seismic resilience of city road networks,a resilience ... The post-earthquake emergency period,which is a sensitive time segment just after an event,mainly focuses on saving life and restoring social order.To improve the seismic resilience of city road networks,a resilience evaluation method used in the post-earthquake emergency period is proposed.The road seismic damage index of a city road network can consider the influence of roads,bridges and buildings along the roads,etc.on road capacity after an earthquake.A function index for a city road network is developed,which reflects the connectivity,redundancy,traffic demand and traffic function of the network.An optimization model for improving the road repair order in the post-earthquake emergency period is also developed according to the resilience evaluation,to enable decision support for city emergency management and achieve the best seismic resilience of the city road network.The optimization model is applied to a city road network and the results illustrate the feasibility of the resilience evaluation and optimization method for a city road network in the post-earthquake emergency period. 展开更多
关键词 city road network post-earthquake emergency period traffic demand resilience evaluation optimization model
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Weakly Supervised Network with Scribble-Supervised and Edge-Mask for Road Extraction from High-Resolution Remote Sensing Images
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作者 Supeng Yu Fen Huang Chengcheng Fan 《Computers, Materials & Continua》 SCIE EI 2024年第4期549-562,共14页
Significant advancements have been achieved in road surface extraction based on high-resolution remote sensingimage processing. Most current methods rely on fully supervised learning, which necessitates enormous human... Significant advancements have been achieved in road surface extraction based on high-resolution remote sensingimage processing. Most current methods rely on fully supervised learning, which necessitates enormous humaneffort to label the image. Within this field, other research endeavors utilize weakly supervised methods. Theseapproaches aim to reduce the expenses associated with annotation by leveraging sparsely annotated data, such asscribbles. This paper presents a novel technique called a weakly supervised network using scribble-supervised andedge-mask (WSSE-net). This network is a three-branch network architecture, whereby each branch is equippedwith a distinct decoder module dedicated to road extraction tasks. One of the branches is dedicated to generatingedge masks using edge detection algorithms and optimizing road edge details. The other two branches supervise themodel’s training by employing scribble labels and spreading scribble information throughout the image. To addressthe historical flaw that created pseudo-labels that are not updated with network training, we use mixup to blendprediction results dynamically and continually update new pseudo-labels to steer network training. Our solutiondemonstrates efficient operation by simultaneously considering both edge-mask aid and dynamic pseudo-labelsupport. The studies are conducted on three separate road datasets, which consist primarily of high-resolutionremote-sensing satellite photos and drone images. The experimental findings suggest that our methodologyperforms better than advanced scribble-supervised approaches and specific traditional fully supervised methods. 展开更多
关键词 Semantic segmentation road extraction weakly supervised learning scribble supervision remote sensing image
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Autonomous Vehicle Platoons In Urban Road Networks:A Joint Distributed Reinforcement Learning and Model Predictive Control Approach
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作者 Luigi D’Alfonso Francesco Giannini +3 位作者 Giuseppe Franzè Giuseppe Fedele Francesco Pupo Giancarlo Fortino 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第1期141-156,共16页
In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory... In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the proposed approach. Moreover, it is important to underline that in different operating scenarios the proposed reinforcement learning scheme is capable of significantly reducing traffic congestion phenomena when compared with well-reputed competitors. 展开更多
关键词 Distributed model predictive control distributed reinforcement learning routing decisions urban road networks
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Optimized Binary Neural Networks for Road Anomaly Detection:A TinyML Approach on Edge Devices
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作者 Amna Khatoon Weixing Wang +2 位作者 Asad Ullah Limin Li Mengfei Wang 《Computers, Materials & Continua》 SCIE EI 2024年第7期527-546,共20页
Integrating Tiny Machine Learning(TinyML)with edge computing in remotely sensed images enhances the capabilities of road anomaly detection on a broader level.Constrained devices efficiently implement a Binary Neural N... Integrating Tiny Machine Learning(TinyML)with edge computing in remotely sensed images enhances the capabilities of road anomaly detection on a broader level.Constrained devices efficiently implement a Binary Neural Network(BNN)for road feature extraction,utilizing quantization and compression through a pruning strategy.The modifications resulted in a 28-fold decrease in memory usage and a 25%enhancement in inference speed while only experiencing a 2.5%decrease in accuracy.It showcases its superiority over conventional detection algorithms in different road image scenarios.Although constrained by computer resources and training datasets,our results indicate opportunities for future research,demonstrating that quantization and focused optimization can significantly improve machine learning models’accuracy and operational efficiency.ARM Cortex-M0 gives practical feasibility and substantial benefits while deploying our optimized BNN model on this low-power device:Advanced machine learning in edge computing.The analysis work delves into the educational significance of TinyML and its essential function in analyzing road networks using remote sensing,suggesting ways to improve smart city frameworks in road network assessment,traffic management,and autonomous vehicle navigation systems by emphasizing the importance of new technologies for maintaining and safeguarding road networks. 展开更多
关键词 Edge computing remote sensing TinyML optimization BNNs road anomaly detection QUANTIZATION model compression
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