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A general method to filter out defective spatial observations from yield mapping datasets

PRECISION AGRICULTURE 2018年第5期19卷 789-808页

作者： Leroux, Corentin Jones, Hazael Clenet, Anthony Dreux, Benoit Becu, Maxime Tisseyre, Bruno SMAG Montpellier France Montpellier SupAgro Irstea UMR ITAP Montpellier France DEFISOL Evreux France

Yield maps are recognized as a valuable tool with regard to managing upcoming crop production but can contain a large amount of defective data that might result in misleading decisions. These anomalies must be removed before further processing to ensure the quality of future decisions. This paper proposes a new holistic methodology to filter out defective observations likely to be present in yield datasets. The notion of spatial neighbourhood has been refined to embrace the specific characteristics of such on-the-go vehicle based datasets. Observations are compared with their newly-defined spatial neighbourhood and the most abnormal ones are classified as defective observations based on a density-based clustering algorithm. The approach was conceived to be as non-parametric and automated as far as possible to pre-process a growing number of datasets without supervision. The proposed approach showed promising results on real yield datasets with the detection of well-known sources of errors such as filling and emptying times, speed changes and non-fully used cutting bar.

关键词： dbscan algorithm Filtering Local outliers On-board sensors Spatial neighbourhood Yield

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Exploring Traffic Patterns of Bicycle Sharing System 18

Exploring Traffic Patterns of Bicycle Sharing System

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2nd International Conference on Computer Science and Application Engineering (CSAE)

作者： Xue, Caoyi Li, Yanxi Univ Elect Sci & Technol China Sch Resources & Environm Chengdu Sichuan Peoples R China

ISBN: (纸本)9781450365123

The bicycle(1) sharing system provides a convenient transportation mode for urban traffic travel. Analyzing the operation mode of the bicycle sharing system through the bicycle station clustering can help the bicycle sharing system operate more efficiently. In this paper, New York City bicycle sharing system data were used. Combined with station location and traffic interaction information, a two-tier clustering method that combines dbscan and K-means clustering algorithms was proposed to achieve bicycle station clustering, to analyze the traffic patterns of bicycle sharing system in different geographical areas. This is used to reflect the user's social and economic activities at different times and locations and it provides technical support for the effective operation of the bicycle sharing system.

关键词： Bike-sharing system clustering analysis K-means algorithm dbscan algorithm

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Mining Taxi Pick-Up Hotspots Based On Spatial Clustering 4

Mining Taxi Pick-Up Hotspots Based On Spatial Clustering

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IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)

作者： Qi, Hong Liu, Panpan Jilin Univ Coll Comp Sci & Technol Changchun Jilin Peoples R China

ISBN: (纸本)9781538693803

Mining useful information from taxi operation data in order to optimize the dynamic scheduling of taxi is a hot research problem. In this paper, the spatial clustering method is applied to excavate the taxi pick-up hotspots which are analyzed and visualized further. An improved spatial clustering algorithm R-Fdbscan is proposed, which has an additional parameter R for controlling the range of clusters, to fine-grained cluster the GPS data of taxis. The experimental results show that the R-Fdbscan algorithm has advantages in time performance and clustering results. In addition, two concepts, "center of mass" and "heat", are defined respectively as the location and the demand degree to reduce the representation about the taxi pick-up hotspots. R-Fdbscan algorithm is used on the GPS data of 12,000 taxis in 4 days from Beijing. The reduction results visualized on ArcGIS platform show that the pick-up hotspots are highly coincident with the residents' daily regularity.

关键词： Spatial Clustering Pick-Up Hotspots Dynamic Scheduling of Taxis dbscan algorithm ArcGIS

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Anomaly Detection of Target Dynamics Based on Clustering 15

Anomaly Detection of Target Dynamics Based on Clustering

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15th International Symposium on Pervasive Systems, algorithms and Networks (I-SPAN)

作者： Jian, Zhang Qing, Ye Ti, Zhou Wuhan Digital Engn Inst Wuhan Hubei Peoples R China

ISBN: (纸本)9781538685341

Battlefield data analysis plays an important role in warfare. In this paper, the anomaly detection problem of group target dynamics on the battlefield is taken as the research object,and an anomaly detection process based on dbscan clustering algorithm is designed. The simulation proves that the anomaly detection process has preferably applicability.

关键词： anomaly detection dbscan algorithm

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Data Fusion Based Power Benchmarking for the Cement Manufacturing Process

Data Fusion Based Power Benchmarking for the Cement Manufact...

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Chinese Automation Congress (CAC)

作者： Liu, Zhao Wang, Xiaohong Zhang, Qiang Yuan, Zhugang Univ Jinan Sch Automat & Elect Engn Jinan Shandong Peoples R China

ISBN: (纸本)9781728113128

In order to get the actual power consumption of the cement manufacturing process, the clustering algorithm and linear minimum variance fusion algorithm are proposed to establish the actual power benchmark of the cement manufacturing process. To manipulate the change of clustering number that is due to the variation of operation conditions and noise data, the dbscan algorithm is applied to cluster the power consumption data of each process unit in the cement manufacturing process. Classifications, clustering centers and their variances of power consumption data are obtained. The actual power consumption benchmark of each process unit in the cement manufacturing process is obtained by using the clustering centers and their variances with the linear minimum variance fusion algorithm. The actual power consumption benchmarking obtained by data fusion can reasonably reflect the actual level of power consumption, and reveal power saving potentialities.

关键词： Data Fusion dbscan algorithm Power Consumption Cement Manufacturing Process

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A Lightning Location algorithm Based on Clustering Analysis 1

A Lightning Location Algorithm Based on Clustering Analysis

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1st International Cognitive Cities Conference (IC3)

作者： Li, Tao Zhang, Shuaichi Ren, Yongjun Li, Xiang Ren, Yongzhen Zhang, Can Nanjing Univ Informat Sci & Technol Coll Elect & Informat Engn Nanjing Jiangsu Peoples R China Nanjing Univ Informat Sci & Technol Coll Comp & Software Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538650592

Location accuracy is an important measurement for evaluation of lightning locating networks, and the location algorithm directly affect the accuracy of the lightning detection results. According to the existed weakness of arrival time difference in traditional location method such as poor ability of resisting error interference and low location accuracy, and iterative algorithms are easy to diverge, an improved dbscan algorithm is introduced in location calculation. The performance of the proposed location algorithm was confirmed by regional simulation The results showed that Adbscan does not require manual intervention, and has better clustering effect for lightning location results. The lightning location algorithm based on Adbscan overcomes the shortcomings that iterative algorithms are easy to diverge and fall into local optimum, and can solve the lightning points steadily and accurately.

关键词： lightning location clustering analysis time difference of arrival dbscan algorithm

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Adaptive Block Online Learning Target Tracking Based on Super Pixel Segmentation 9

Adaptive Block Online Learning Target Tracking Based on Supe...

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9th International Conference on Graphic and Image Processing (ICGIP)

作者： Cheng, Yue Li, Jianzeng Mech Engn Coll Dept UAV Shijiazhuang 050000 Hebei Peoples R China

ISBN: (数字)9781510617421

ISBN: (纸本)9781510617421

Video target tracking technology under the unremitting exploration of predecessors has made big progress, but there are still lots of problems not solved. This paper proposed a new algorithm of target tracking based on image segmentation technology. Firstly we divide the selected region using simple linear iterative clustering (SLIC) algorithm, after that, we block the area with the improved density-based spatial clustering of applications with noise (dbscan) clustering algorithm. Each sub-block independently trained classifier and tracked, then the algorithm ignore the failed tracking sub-block while reintegrate the rest of the sub-blocks into tracking box to complete the target tracking. The experimental results show that our algorithm can work effectively under occlusion interference, rotation change, scale change and many other problems in target tracking compared with the current mainstream algorithms.

关键词： Target tracking super pixel division dbscan algorithm online learning

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A Research on Dynamic Identification of Main Route of River Estuary Segment Based on AIS

A Research on Dynamic Identification of Main Route of River ...

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3rd IEEE International Conference on Intelligent Transportation Engineering (ICITE)

作者： Pei YiLou Chen DeJun Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Hubei Peoples R China

ISBN: (纸本)9781538678312

The dynamic uncertainty caused by tidal current in river estuary is affected, A method for dynamic identification of main route of river estuary segment based on AIS (Automatic Identification System) is proposed by using the AIS navigation trajectory of the most recent typical ship and the time point of large Ocean currents. Firstly, clustering algorithm is used to analyze the navigation trajectory of typical ships in the estuary recently, and the track of the estuary channel is identified, then, cubic spline interpolation algorithm is used to fit the center trajectory points obtained by dbscan (Density-Based Spatial Clustering of Applications with Noise), and get the main route, combined with the current characteristics of large ocean current, the main route is modified appropriately, therefore, the effect of frequent changes on the channel of river estuary is solved, and the validity of this method is verified through the analysis of the measured data.

关键词： AIS dbscan algorithm Main course of the estuary

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Accurate Sybil Attack Detection Based on Fine-Grained Physical Channel Information

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SENSORS 2018年第3期18卷 878-878页

作者： Wang, Chundong Zhu, Likun Gong, Liangyi Zhao, Zhentang Yang, Lei Liu, Zheli Cheng, Xiaochun Tianjin Univ Technol Key Lab Comp Vis & Syst Minist Educ Tianjin 300384 Peoples R China Tianjin Univ Technol Tianjin Key Lab Intelligence Comp & Novel Softwar Minist Educ Tianjin 300384 Peoples R China Nankai Univ Coll Comp & Control Engn Tianjin 300350 Peoples R China Middlesex Univ Dept Comp Sci London NW4 4BT England

With the development of the Internet-of-Things (IoT), wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI). This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI). Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless networks.

关键词： channel state information Sybil attack indoor AoA technology dbscan algorithm

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Visualisation and analysis of hepatitis C virus non-structural proteins using super-resolution microscopy

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SCIENTIFIC REPORTS 2018年第1期8卷 13604-13604页

作者： Bartlett, Christopher Curd, Alistair Peckham, Michelle Harris, Mark Univ Leeds Fac Biol Sci Sch Mol & Cellular Biol Leeds LS2 9JT W Yorkshire England Univ Leeds Astbury Ctr Struct Mol Biol Leeds LS2 9JT W Yorkshire England

Hepatitis C virus (HCV) RNA replication occurs in the cytosol of infected cells within a specialised membranous compartment. How the viral non-structural (NS) proteins are associated and organised within these structures remains poorly defined. We employed a super-resolution microscopy approach to visualise NS3 and NS5A in HCV infected cells. Using single molecule localisation microscopy, both NS proteins were resolved as clusters of localisations smaller than the diffraction-limited volume observed by wide-field. Analysis of the protein clusters identified a significant difference in size between the NS proteins. We also observed a reduction in NS5A cluster size following inhibition of RNA replication using daclatasvir, a phenotype which was maintained in the presence of the Y93H resistance associated substitution and not observed for NS3 clusters. These results provide insight into the NS protein organisation within hepatitis C virus RNA replication complexes and the mode of action of NS5A inhibitors.

关键词： Single-molecule Localization Microscopy (SMLM) Daclatasvir (DCV) Protein Clusters Density-based Spatial Clustering Of Applications With Noise (dbscan) dbscan algorithm

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