The technology was vulnerable to online hackers and assaults on the open and dispersed nature of the cloud. To recognize and stop both internal and external attacks in a cloud ecosystem with high identification accura...
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In the environment with objects moving randomly,the positions of moving objects can be modeled as a range of possible values,associated with a probability density *** mining of such positions of uncertain moving objec...
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In the environment with objects moving randomly,the positions of moving objects can be modeled as a range of possible values,associated with a probability density *** mining of such positions of uncertain moving objects attracts more and more research interest *** definitions of probabilistic core object and probabilistic density-reachability are presented and a density-based probabilistic clustering algorithm for uncertain moving objects is proposed,based on DBSCAN algorithm and probabilistic index on uncertain moving *** results show that the proposed algorithm outperforms other density-based clustering algorithm for uncertain moving objects in accuracy and update rate needed for clustering.
We presented in this paper a usage scenario in which cultural resources in a public context, items on display in a historical museum for instance, should be recommended to groups of visitors in response to their inter...
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ISBN:
(纸本)9783319486741;9783319486734
We presented in this paper a usage scenario in which cultural resources in a public context, items on display in a historical museum for instance, should be recommended to groups of visitors in response to their interest (or preferences), thus conserving computational resources and reducing network traffic. Motivated by the scenario, we set out to design and implement a group recommender system, Museum Guides for Groups (MGG), that provides visitors to a museum with a sequence of items of interest by efficiently clustering visitors of similar user profiles into groups and computing recommendations for each group. Our work in progress was reported, focusing on the system design and the selection of an appropriate clustering algorithm for dividing visitors. We evaluated the efficiency of three candidate clustering techniques, including the bisecting K-Means, DBSCAN, and improved CURE, using the MovieLens dataset with 1M ratings.
Mobile edge computing can expand the limited computing power of on-board equipment, which is an effective means to assist vehicles to realize complex applications. However, the task offloading process brings a certain...
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There is an increase in the energy consumption and cost of base station deployment due to increase in the number of devices which require a dense deployment of base stations to handle the resultant data traffic. C-RAN...
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ISBN:
(数字)9781728131269
ISBN:
(纸本)9781728131276
There is an increase in the energy consumption and cost of base station deployment due to increase in the number of devices which require a dense deployment of base stations to handle the resultant data traffic. C-RAN (Cloud Radio Access Network) was proposed to remedy the problem of increasing data traffic volume and reduce the capital expenditure and operating expenditure of Mobile Network operators. Cloud Radio Access Network (C-RAN) allows for network resources to be shared amongst several base stations thereby reducing cost. By using different clustering algorithms such as K-means, Hierarchical and Gaussian Mixture Models to cluster these base stations there is a reduction in the needed network resources and this reduces cost. Capacity Utility and cost of deployment are the metrics used in making a comparative analysis of the different clustering algorithms used in this work. From evaluation of the methodology, it showed that the Hierarchical clustering algorithm had a Capacity Utility of 0.0012, Gaussian Mixture Models had 0.0035 and K-means with 0.0044 and when you compare this with the Capacity Utility before clustering of 0.63 it can be seen that the Hierarchical clustering algorithm had reduced the needed network resources better than Gaussian Mixture Models and K-means. The 3 clustering algorithms were also able to reduce the number of needed base stations from 182 to 80, thereby reducing Cost of deployment.
Gather the information of the environment by the monocular vision. Using the H and S weight of the HSV color model, separate the target from the environment with a certain color, by a fast clustering algorithm for two...
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ISBN:
(纸本)9787811240559
Gather the information of the environment by the monocular vision. Using the H and S weight of the HSV color model, separate the target from the environment with a certain color, by a fast clustering algorithm for two-value image segmentation. Calculating the distance between the camera and target by the 3D reconstruction algorithm and sub-control strategy, and raise its veracity by laser information fusion. Furthermore, a vision servo system has been designed and utilized to achieve the robot's dynamic track. At last, some experiments were used to certification its availability.
Power large users are the key users of power supply enterprises, and their potential value and development trend in power market environment are closely related to the profit of power supply enterprises. In order to i...
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ISBN:
(纸本)9781538614273
Power large users are the key users of power supply enterprises, and their potential value and development trend in power market environment are closely related to the profit of power supply enterprises. In order to identify valuable user behavior and value characteristics, a large user segmentation method based on Affinity Propagation(AP) and K-means algorithm is proposed. First of all, from the existing indicators to extract the key sub-indicators, and consider the recent and long-term power consumption rate of electricity, put forward to assess the development potential of large users of the breakdown of indicators;Secondly, the AP and K-means are combined to solve the problem and finding the initial clustering center and the number of clusters, at the same time, it avoids the problem that the K-means clustering is easy to fall into the local optimum;finally, the user data of a region in Zhejiang Province is analyzed and verified, and the proposed method is feasible.
The deviation of motor speed directly affects the accuracy of the project control system, for the current questions about the accuracy of motor speed measurement, combined with traditional optical enc
ISBN:
(纸本)9781467389808
The deviation of motor speed directly affects the accuracy of the project control system, for the current questions about the accuracy of motor speed measurement, combined with traditional optical enc
The problem of reliable automatic target recognition (ATR) from incoherent radar returns is discussed. In the problems under consideration, feature extraction methods are divided into two basic types: (1) Feature extr...
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ISBN:
(纸本)0780326679
The problem of reliable automatic target recognition (ATR) from incoherent radar returns is discussed. In the problems under consideration, feature extraction methods are divided into two basic types: (1) Feature extraction directly based on time-domain description; (2) Feature extraction based on multiple transformation technique. In this paper, we shall demonstrate the problem of feature extraction by considering two examples of ship target recognition. The main algorithms and the recognition processing are discussed in detail. The experimental results show that a high reliability of recognition can be achieved.
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