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学者姓名：吴小竹
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Abstract ：
In recent years, the protection and management of water environments have garnered heightened attention due to their critical importance. Detection of small objects in unmanned aerial vehicle (UAV) images remains a persistent challenge due to the limited pixel values and interference from background noise. To address this challenge, this paper proposes an integrated object detection approach that utilizes an improved YOLOv5 model for real-time detection of small water surface floaters. The proposed improved YOLOv5 model effectively detects small objects by better integrating shallow and deep features and addressing the issue of missed detections and, therefore, aligns with the characteristics of the water surface floater dataset. Our proposed model has demonstrated significant improvements in detecting small water surface floaters when compared to previous studies. Specifically, the average precision (AP), recall (R), and frames per second (FPS) of our model achieved 86.3%, 79.4%, and 92%, respectively. Furthermore, when compared to the original YOLOv5 model, our model exhibits a notable increase in both AP and R, with improvements of 5% and 6.1%, respectively. As such, the proposed improved YOLOv5 model is well-suited for the real-time detection of small objects on the water's surface. Therefore, this method will be essential for large-scale, high-precision, and intelligent water surface floater monitoring.
Keyword ：
improved YOLOv5 improved YOLOv5 object detection object detection small objects small objects UAV UAV water surface floaters water surface floaters
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| GB/T 7714 | Chen, Fuxun , Zhang, Lanxin , Kang, Siyu et al. Soft-NMS-Enabled YOLOv5 with SIOU for Small Water Surface Floater Detection in UAV-Captured Images [J]. | SUSTAINABILITY , 2023 , 15 (14) . |
| MLA | Chen, Fuxun et al. "Soft-NMS-Enabled YOLOv5 with SIOU for Small Water Surface Floater Detection in UAV-Captured Images" . | SUSTAINABILITY 15 . 14 (2023) . |
| APA | Chen, Fuxun , Zhang, Lanxin , Kang, Siyu , Chen, Lutong , Dong, Honghong , Li, Dan et al. Soft-NMS-Enabled YOLOv5 with SIOU for Small Water Surface Floater Detection in UAV-Captured Images . | SUSTAINABILITY , 2023 , 15 (14) . |
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化学事故具有突发性强、环境污染破坏严重、救援难度大等特点,对突发化学事故的影响范围、破坏程度进行快速评估,为事故抢险救援提供决策支持,是应对重特大突发化学事故、降低事故损失的重要手段.本文基于三维地理信息系统(Three-dimensional Geographic Information System,3D GIS),在充分考虑下垫面影响的前提下,研究了大气污染扩散模型,提出了扩散场快速构建技术及兼顾污染分区的救援力量调度方法,并以此为核心建立了系统总体框架,形成了集扩散模拟、危害分析、救援调度等功能于一体的突发化学事故危害评估与救援辅助决策支持系统,可为突发化学事故危害后果评估与辅助救援决策提供有效的技术支撑.
Keyword ：
3D GIS 3D GIS 动态规划 动态规划 污染扩散模拟 污染扩散模拟 突发化学事故 突发化学事故
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| GB/T 7714 | 朱勇兵 , 林定 , 杨浩锋 et al. 基于3D GIS的突发化学事故危害评估与救援辅助决策支持系统 [J]. | 防化研究 , 2023 , 2 (2) : 58-65 . |
| MLA | 朱勇兵 et al. "基于3D GIS的突发化学事故危害评估与救援辅助决策支持系统" . | 防化研究 2 . 2 (2023) : 58-65 . |
| APA | 朱勇兵 , 林定 , 杨浩锋 , 赵三平 , 吴小竹 , 韩梦薇 et al. 基于3D GIS的突发化学事故危害评估与救援辅助决策支持系统 . | 防化研究 , 2023 , 2 (2) , 58-65 . |
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跟驰行为研究旨在探究单行道上前车运动状态的变化对后车行驶状态的影响,通过建立相应的跟驰模型进行仿真研究,可以揭示交通拥堵、交通流震荡等交通现象的内在机理,有助于研究交通流的稳定性、道路通行能力和运行效率.由于驾驶经验、性格等特征的差异,驾驶员会表现出不同的跟车特征.然而,传统的跟驰模型往往假设驾驶员的驾驶行为是同质的,较少考虑通行车辆驾驶风格的差异,这与实际情况不符.为此,本文首先提取了路面通行车辆的4种驾驶行为特征(变道、起步、制动、平稳行驶),开发了基于权重的自适应数据流引力聚类(Weight-based Adaptive Data Stream Gravity Clustering,WAStream)算法,分别对不同驾驶行为特征时序数据进行聚类分析,进而根据驾驶风格评分模型量化了驾驶员不同驾驶行为的激进程度,实现了通行车辆驾驶风格的有效分类;接着通过分析不同风格驾驶员的跟驰数据,构建不同风格车辆的速度期望函数,并充分考虑主车与驾驶视野中多辆前车的速度差、加速度差等影响,提出了一种考虑驾驶员驾驶风格的车辆跟驰模型;最后基于NGSIM车辆轨迹数据,利用遗传算法标定考虑驾驶员驾驶风格的车辆跟驰模型的关键参数,实现模型的验证和数值仿真分析.实验结果表明:与经典的FVD模型相比,所提出的跟驰模型能够更好地拟合车辆跟驰数据,其MAE、MAPE、RMSE分别减小了1.511 m/s2、6.122%、1.064 m/s2;同时,该模型能够有效降低车辆在跟驰行为中的延迟性,构建更逼近真实情况的交通流场景,提高了交通流的稳定性.本研究提出的跟驰模型能够为交通运输规划和管理部门提供有效的决策信息,为微观交通仿真研究提供模型参考.
Keyword ：
参数标定 参数标定 微观交通仿真 微观交通仿真 数据挖掘 数据挖掘 数据流聚类 数据流聚类 车辆跟驰模型 车辆跟驰模型 轨迹提取 轨迹提取 驾驶行为 驾驶行为 驾驶风格 驾驶风格
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| GB/T 7714 | 林志坤 , 吴小竹 . 考虑驾驶员驾驶风格的车辆跟驰模型 [J]. | 地球信息科学学报 , 2023 , 25 (9) : 1798-1812 . |
| MLA | 林志坤 et al. "考虑驾驶员驾驶风格的车辆跟驰模型" . | 地球信息科学学报 25 . 9 (2023) : 1798-1812 . |
| APA | 林志坤 , 吴小竹 . 考虑驾驶员驾驶风格的车辆跟驰模型 . | 地球信息科学学报 , 2023 , 25 (9) , 1798-1812 . |
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The research on car-following behavior aims to explore the impact of the leading vehicle's movement on the following vehicle's driving state on a one-way road. By establishing corresponding car-following models for simulation studies, it can reveal the underlying mechanism of traffic congestion, traffic flow oscillation, and other traffic phenomena, which is helpful for evaluating the stability, road capacity, and operational efficiency of traffic flow. Due to differences in driving experience, personality, and other characteristics, drivers may exhibit different car- following characteristics. Moreover, under the same conditions, the car- following behavior of different drivers may differ, and the car-following behavior of the same driver may also vary at different times. However, traditional car- following models often assume that drivers' driving behavior is homogeneous and rarely consider differences in driving styles among passing vehicles, which is inconsistent with actual situations. Therefore, this paper first extracts four driving behaviors of passing vehicles on the road (lane changing, starting, braking, and smooth driving), develops a Weight-based Adaptive Data Stream Gravity Clustering (WAStream) algorithm based on weights, and conducts clustering analysis on the time-series data of different driving behavior characteristics. Then, according to the driving style scoring model, the aggressiveness of different driving behaviors of drivers is quantified, the effective classification of driving styles of passing vehicles is achieved, and the overall driving behavior characteristics of different style driver groups are obtained. Next, by analyzing the car-following data of drivers with different styles, a speed expectation function for different style vehicles is constructed. Furthermore, the proposed car- following model considers the impact of speed and acceleration differences between the leading vehicle and multiple front vehicles in the driver's field of vision, which considers the driver's driving style. Finally, based on the NGSIM vehicle trajectory data, the key parameters of the car-following model considering the driver's driving style are calibrated using genetic algorithms, and the model's validation and numerical simulation analysis are achieved. The experimental results show that compared with the classical FVD model, the proposed car- following model can better fit the car- following data, and the MAE, MAPE, and RMSE are reduced by 1.511 m/s2, 6.122%, and 1.064 m/s2, respectively. At the same time, the model can effectively reduce the delay of vehicles in car- following behavior, construct traffic flow scenarios closer to reality, and improve the stability of traffic flow. The car- following model proposed in this study can provide effective decision- making information for transportation planning and management departments and provide model references for micro-traffic simulation studies. © 2023 Journal of Geo-Information Science. All rights reserved.
Keyword ：
car-following model car-following model data mining data mining data stream clustering data stream clustering driving behavior driving behavior driving style driving style microscopic traffic simulation microscopic traffic simulation parameter calibration parameter calibration trajectory extraction trajectory extraction
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| GB/T 7714 | Lin, Z. , Wu, X. . Car-Following Model Considering Driver's Driving Style; [考虑驾驶员驾驶风格的车辆跟驰模型] [J]. | Journal of Geo-Information Science , 2023 , 25 (9) : 1798-1812 . |
| MLA | Lin, Z. et al. "Car-Following Model Considering Driver's Driving Style; [考虑驾驶员驾驶风格的车辆跟驰模型]" . | Journal of Geo-Information Science 25 . 9 (2023) : 1798-1812 . |
| APA | Lin, Z. , Wu, X. . Car-Following Model Considering Driver's Driving Style; [考虑驾驶员驾驶风格的车辆跟驰模型] . | Journal of Geo-Information Science , 2023 , 25 (9) , 1798-1812 . |
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Task allocation is a critical issue of spatial crowdsourcing. Although the batching strategy performs better than the real-time matching mode, it still has the following two drawbacks: (1) Because the granularity of the batch size set obtained by batching is too coarse, it will result in poor matching accuracy. However, roughly designing the batch size for all possible delays will result in a large computational overhead. (2) Ignoring non-stationary factors will lead to a change in optimal batch size that cannot be found as soon as possible. Therefore, this paper proposes a fine-grained, batching-based task allocation algorithm (FGBTA), considering non-stationary setting. In the batch method, the algorithm first uses variable step size to allow for fine-grained exploration within the predicted value given by the multi-armed bandit (MAB) algorithm and uses the results of pseudo-matching to calculate the batch utility. Then, the batch size with higher utility is selected, and the exact maximum weight matching algorithm is used to obtain the allocation result within the batch. In order to cope with the non-stationary changes, we use the sliding window (SW) method to retain the latest batch utility and discard the historical information that is too far away, so as to finally achieve refined batching and adapt to temporal changes. In addition, we also take into account the benefits of requesters, workers, and the platform. Experiments on real data and synthetic data show that this method can accomplish the task assignment of spatial crowdsourcing effectively and can adapt to the non-stationary setting as soon as possible. This paper mainly focuses on the spatial crowdsourcing task of ride-hailing.
Keyword ：
fine-grained batching algorithm fine-grained batching algorithm multi-armed bandit algorithm multi-armed bandit algorithm online task assignment online task assignment spatial crowdsourcing spatial crowdsourcing
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| GB/T 7714 | Jiao, Yuxin , Lin, Zhikun , Yu, Long et al. A Fine-Grain Batching-Based Task Allocation Algorithm for Spatial Crowdsourcing [J]. | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION , 2022 , 11 (3) . |
| MLA | Jiao, Yuxin et al. "A Fine-Grain Batching-Based Task Allocation Algorithm for Spatial Crowdsourcing" . | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 11 . 3 (2022) . |
| APA | Jiao, Yuxin , Lin, Zhikun , Yu, Long , Wu, Xiaozhu . A Fine-Grain Batching-Based Task Allocation Algorithm for Spatial Crowdsourcing . | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION , 2022 , 11 (3) . |
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提出一种基于激励机制的负载均衡和服务质量感知服务组合(LBQSC)方法.首先,构建一个全局约束分解模型,并采用文化遗传算法求解;其次,考虑服务质量(QoS)和负载构造激励合同,提出一种基于激励机制的服务选择算法,通过不断激励QoS的动态调整获取最优服务;最后,在QWS 2.0综合数据集上进行对比实验.实验结果表明:基于激励机制的负载均衡和QoS感知服务组合方法能在保证负载均衡的情况下有效地获取高质量的组合服务.
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| GB/T 7714 | 刘英 , 焦竽鑫 , 吴小竹 . 激励机制下负载均衡和QoS感知服务组合方法 [J]. | 华侨大学学报（自然科学版） , 2021 , 42 (5) : 684-692 . |
| MLA | 刘英 et al. "激励机制下负载均衡和QoS感知服务组合方法" . | 华侨大学学报（自然科学版） 42 . 5 (2021) : 684-692 . |
| APA | 刘英 , 焦竽鑫 , 吴小竹 . 激励机制下负载均衡和QoS感知服务组合方法 . | 华侨大学学报（自然科学版） , 2021 , 42 (5) , 684-692 . |
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Previous QoS-aware service composition methods mainly focus on how to generate composite service with the optimal QoS efficiently for a single request. However, in the real application scenarios, there are multiple service requests and multiple service providers. It is more important to compose services with suboptimal QoS and maintain the load balance between services. To solve this problem, in this paper, we propose a service composition method, named as dynamically change and balancing composition method (DCBC). It assumes that the QoS of service is not static, and the services can adjust the value of QoS to gain more opportunities to be selected for composition. The method mainly includes two steps, which are the preprocessing step and the service selection step. In the preprocessing step, a backward global best QoS calculation is performed which regarding the static and dynamic QoS respectively; then guided by the global QoS, the feasible services can be selected efficiently in the service selection step. The experiments show that the DCBC method can not only improve the overall quality of composite services but also guarantee the fulfill ratio of requests and the load balance of services.
Keyword ：
Dynamic QoS Dynamic QoS Load Balance Load Balance QoS Adjustment QoS Adjustment Service Composition Service Composition
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| GB/T 7714 | Wu, Xiaozhu . A Dynamic QoS Adjustment Enabled and Load-balancing-aware Service Composition Method for Multiple Requests [J]. | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS , 2021 , 15 (3) : 891-910 . |
| MLA | Wu, Xiaozhu . "A Dynamic QoS Adjustment Enabled and Load-balancing-aware Service Composition Method for Multiple Requests" . | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 15 . 3 (2021) : 891-910 . |
| APA | Wu, Xiaozhu . A Dynamic QoS Adjustment Enabled and Load-balancing-aware Service Composition Method for Multiple Requests . | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS , 2021 , 15 (3) , 891-910 . |
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We present a framework for the event semantic retrieval of cultural tourism. Nowadays, information and communication technologies are ubiquitous and pervasive and have greatly promoted the development of cultural tourism. Cultural tourism should utilize these technologies to improve a sense of participation and experience for cultural tourists by sorting out domain-specific cultural knowledge from tourism attractions systematically, building bridges between tourism resources and cultural connotation naturally and presenting the cultural changes behind tourism resources vividly. To the end, we present a complete framework that is suitable to event retrieval of cultural tourism, helping cultural tourists learn culture in all directions and in depth quickly and easily before their cultural tours, and local government create tourism cards through the dissemination of culture connotation as well. Our main inspiration is that story-telling would be an effective form of acceptance by cultural tourists to spread the culture behind tourism resources. Concretely, our framework includes data acquisition and preprocessing, data organization and processing, and data visualization components. The data acquisition and preprocessing component is responsible for collecting historical event texts and fusing text knowledge. The data organization and processing component enables an intuitive view on properties and relations of the event elements in terms of defined event ontology for cultural tourism and supports event semantic retrieval. The data visualization component provides a knowledge navigation through dynamic display and an interactive interface with modification function. We have conducted event semantic retrieval of Minnan culture and verified the feasibility and effectiveness of the framework.
Keyword ：
Cultural tourism Cultural tourism event ontology event ontology interactive visualization interactive visualization knowledge fusion knowledge fusion knowledge retrieval knowledge retrieval
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| GB/T 7714 | Fang, Hui , Chen, Chongcheng , Wu, Xiaozu et al. FESRCT: A Framework for the Event Semantic Retrieval of Cultural Tourism [J]. | ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE , 2021 , 14 (3) . |
| MLA | Fang, Hui et al. "FESRCT: A Framework for the Event Semantic Retrieval of Cultural Tourism" . | ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE 14 . 3 (2021) . |
| APA | Fang, Hui , Chen, Chongcheng , Wu, Xiaozu , Ye, Xiaoyan . FESRCT: A Framework for the Event Semantic Retrieval of Cultural Tourism . | ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE , 2021 , 14 (3) . |
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The accumulation of serial remote sensing images provides plentiful data for discovering sequential spatial patterns in various fields such as agricultural monitoring, urban development, and vegetation cover. Otherwise, traditional sequential pattern-mining algorithms cannot be directly or efficiently applied to remote sensing images. In this study, we propose a pixel clustering-based method to improve the efficiency of mining spatial sequential patterns from raster serial remote sensing images (SRSI). Firstly, the images are compressed by using the Run-Length coding schema. Then, pixels with identical sequences are clustered by means of the Run-length code-based spatial overlay operation. Finally, a pruning strategy is proposed, to extend the prefixSpan algorithm to skip unnecessary database scanning when mining from pixel groups. The experimental results indicate that the method presented in this paper could extract spatial sequential patterns from SRSI efficiently. Although accurate support rates for the patterns may not be obtained, our method could ensure that all patterns are extracted with a lower time cost.
Keyword ：
Pixels cluster Pixels cluster Sequence mining Sequence mining Serial remote sensing images Serial remote sensing images Spatial sequential pattern Spatial sequential pattern
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| GB/T 7714 | Wu, Xiaozhu , Zhang, Ximei . An efficient pixel clustering-based method for mining spatial sequential patterns from serial remote sensing images [J]. | COMPUTERS & GEOSCIENCES , 2019 , 124 : 128-139 . |
| MLA | Wu, Xiaozhu et al. "An efficient pixel clustering-based method for mining spatial sequential patterns from serial remote sensing images" . | COMPUTERS & GEOSCIENCES 124 (2019) : 128-139 . |
| APA | Wu, Xiaozhu , Zhang, Ximei . An efficient pixel clustering-based method for mining spatial sequential patterns from serial remote sensing images . | COMPUTERS & GEOSCIENCES , 2019 , 124 , 128-139 . |
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Massive data transmission between distributed data centers is the major efficiency bottleneck of geospatial workflow. Although many data placement methods have been proposed to overcome this problem, few researches have considered the impact of the structure of the workflow. In this paper, we define the problem of data placement for data-intensive geospatial workflow aiming to minimize the data transfer time. An algorithm called ant colony optimization based data placement of data-intensive geospatial workflow (ACO-DPDGW) is proposed to handle this problem. By taking advantage of the node vector to represent the traditional workflow model, the ants could place datasets and tasks in appropriate data centers according to the combination of pheromone information and heuristic information, when they visit the nodes randomly. To prevent premature convergence, a variable neighborhood search operation is embedded into ACO-DPDGW. The experiments show that our algorithm can reduce data transfer volume and data transfer time even as the numbers of datasets, tasks, and data centers increase.
Keyword ：
Ant colony optimization Ant colony optimization Data placement Data placement Geospatial workflow Geospatial workflow
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| GB/T 7714 | Wu, Xiaozhu , Liu, Ying , Chen, Chongcheng . ACO-DPDGW: an ant colony optimization algorithm for data placement of data-intensive geospatial workflow [J]. | EARTH SCIENCE INFORMATICS , 2019 , 12 (4) : 641-658 . |
| MLA | Wu, Xiaozhu et al. "ACO-DPDGW: an ant colony optimization algorithm for data placement of data-intensive geospatial workflow" . | EARTH SCIENCE INFORMATICS 12 . 4 (2019) : 641-658 . |
| APA | Wu, Xiaozhu , Liu, Ying , Chen, Chongcheng . ACO-DPDGW: an ant colony optimization algorithm for data placement of data-intensive geospatial workflow . | EARTH SCIENCE INFORMATICS , 2019 , 12 (4) , 641-658 . |
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