Unmanned aerial vehicles (UAVs) network are a very vibrant research area nowadays. They have many military and civil applications. Limited bandwidth, the high mobility and secure communication of micro UAVs represent ...
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Unmanned aerial vehicles (UAVs) network are a very vibrant research area nowadays. They have many military and civil applications. Limited bandwidth, the high mobility and secure communication of micro UAVs represent their three main problems. In this paper, we try to address these problems by means of secure clustering, and a security clustering algorithm based on integrated trust value for UAVs network is proposed. First, an improved the k-means++ algorithm is presented to determine the optimal number of clusters by the network bandwidth parameter, which ensures the optimal use of network bandwidth. Second, we considered variables representing the link expiration time to improve node clustering, and used the integrated trust value to rapidly detect malicious nodes and establish a head list. Node clustering reduce impact of high mobility and head list enhance the security of clustering algorithm. Finally, combined the remaining energy ratio, relative mobility, and the relative degrees of the nodes to select the best cluster head. The results of a simulation showed that the proposed clustering algorithm incurred a smaller computational load and higher network security.
In Cellular Manufacturing literature, early work focused on the use of routers as a way of forming product families and manufacturing cells. Later, several measures of similarity among machines and parts have been pro...
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In Cellular Manufacturing literature, early work focused on the use of routers as a way of forming product families and manufacturing cells. Later, several measures of similarity among machines and parts have been proposed by different authors. In this paper, a new clustering algorithm is proposed that considers the number of machines of each type and the most recent configuration of cells in revising the values of similarity coefficient. The potential benefits of the procedure is demonstrated with a simple example.
clustering algorithm has been widely used in refined oil marketing strategy system, but there are certain shortcomings in sales productivity and diversity means. Thereby, it is necessary to further improve refined oil...
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clustering algorithm has been widely used in refined oil marketing strategy system, but there are certain shortcomings in sales productivity and diversity means. Thereby, it is necessary to further improve refined oil marketing strategy system based on clustering algorithm. A unified strategic framework was proposed in the paper, which could make marketing strategy options gain financial returns on the basis of trading, and combine the change of company client assets with customer life cycle. The life cycle and purchase frequency data of all the customers in the industry were summarized, and a set of fast and effective refined product marketing strategy system was designed, which improved the efficiency of sales.
The Unmanned Aerial Vehicles (UAVs), organized as a Flying Ad-hoc NETwork (FANET), are used to make effective remote monitoring in diverse applications. Due to their high mobility, their energy consumption is increasi...
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The Unmanned Aerial Vehicles (UAVs), organized as a Flying Ad-hoc NETwork (FANET), are used to make effective remote monitoring in diverse applications. Due to their high mobility, their energy consumption is increasingly affected leading to reduced network stability and communication efficiency. The design of node clustering of a FANET needs to consider the number of UAVs in the vicinity (transmission range) in order to ensure an adaptive reliable routing. Novel clustering schemes have been employed to deal with the highly dynamic flying behavior of UAVs and to maintain network stability. In this context, a new clustering algorithm is proposed to address the fast mobility of UAVs and provide safe inter-UAV distance, stable communication and extended network lifetime. The main contributions of this paper are first to extend and improve important metrics used in two well-known algorithms in the literature namely: The Bio-Inspired clustering Scheme for FANETs (BICSF) and the Energy Aware Link-based clustering (EALC). Then, exploiting the improved metrics, an Energy and Mobility-aware Stable and Safe clustering (EMASS) algorithm, built upon new schemes useful for ensuring stability and safety in FANETs, is proposed. The simulation results showed that the EMASS algorithm outperformed the BICSF and the EALC algorithms in terms of better cluster stability, guaranteed safety, higher packet deliverability, improved energy saving and lower delays.
In recent years, cryogenic microcalorimeters using their superconductirig transition edge have been under development for possible application to the research for astronomical X-ray observations. To improve the energy...
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In recent years, cryogenic microcalorimeters using their superconductirig transition edge have been under development for possible application to the research for astronomical X-ray observations. To improve the energy resolution of superconducting transition edge sensors (TES), several correction methods have been developed. Among them, a clustering method based on digital signal processing has recently been proposed. In this paper, we applied the clustering method to Ir/Au bilayer TES. This method resulted in almost a 10% improvement in the energy resolution. Conversely, from the point of view of imaging X-ray spectroscopy, we applied the clustering method to pixellated Ir/Au-TES devices. We will thus show how a clustering method which sorts signals by their shapes is also useful for position identification.
Unmanned Aerial Vehicles (UAVs) can play a significant role as flying base station (FBSs) in assisting terrestrial base stations (BSs) to increase overall network capacity by providing localized transmission to a set ...
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Unmanned Aerial Vehicles (UAVs) can play a significant role as flying base station (FBSs) in assisting terrestrial base stations (BSs) to increase overall network capacity by providing localized transmission to a set of users. In that respect, FBSs can be deployed from a terrestrial macro BS which can act as the depot. In this letter, we propose two flavors of a Geographical Division (GD) clustering algorithm to assign FBSs located at the same terrestrial BS to a set of end users. Numerical investigations demonstrate that the proposed algorithm outperforms the two most widely used and best known clustering algorithms for this specific problem, namelyK-means and Hierarchical clustering algorithms.
Adaptive cluster sampling (ACS) is a sampling method relies on the neighbourhood search on a grid structure. It has an adaptive selection process of units and recursively added units reveal the batched individuals eas...
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Adaptive cluster sampling (ACS) is a sampling method relies on the neighbourhood search on a grid structure. It has an adaptive selection process of units and recursively added units reveal the batched individuals easily and quickly. In this paper, we propose a new clustering method called spatial adaptive clustering (SAC) based on the idea of ACS design. The SAC algorithm forms clusters based on neighbourhood search using grid structures and is able to detect noise points. The performance of the proposed algorithm is evaluated through comparison with the results from well-known density-based clustering approaches in the literature using real and artificial data sets. Computational results indicate that the proposed algorithm is effective in terms of external validation measures for clustering of arbitrary shaped data with noise. Additionally, the SAC algorithm is tested on artificial data sets of varying sizes for the runtime criterion. The results reveal that it also performs superbly for the objective of reducing the runtime.
In visible light communication (VLC) systems, the nonlinear effects induced by many devices, such as the electrical amplifiers and optoelectronic devices, can significantly degrade the overall system performance. In t...
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In visible light communication (VLC) systems, the nonlinear effects induced by many devices, such as the electrical amplifiers and optoelectronic devices, can significantly degrade the overall system performance. In this letter, to mitigate the nonlinear distortion effects, a clustering algorithm based on k-means is proposed and experimentally demonstrated in the VLC systems. The experimental results show that with the help of clustering algorithm to compensate the nonlinear effects, the bit error rate (BER) can be reduced from 2.4x10(-1) to 3.6x10(-3). Moreover, the 400-Mbit/s Nyquist PAM-4 signal over 80-cm free space transmission can be successfully achieved.
Tourism is the pillar industry of many cities, and it is also an important key point to promote urban development and maintain urban vitality. At present, the analysis of urban tourism activity in China can better ass...
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Tourism is the pillar industry of many cities, and it is also an important key point to promote urban development and maintain urban vitality. At present, the analysis of urban tourism activity in China can better assist the research of regional economic development and promote the orderly development of regional economy. Many scholars have carried out the analysis in this respect. As a new and growing field, artificial intelligence also plays an important role in urban tourism. With the continuous development of science and technology, and the human intelligence field of human research is also developing. New artificial intelligence products continue to emerge. The workload of most artificial intelligence may exceed the manual workload. In order to continuously update artificial intelligence, individuals effectively combine data mining and artificial intelligence, and combine many knowledge disseminated by the network with artificial intelligence technology to create an advanced knowledge network model. This paper uses the OPTICS-based clustering algorithm to analyze the clustering of photographs on the Flickr website and obtain information about tourism activities in Chinese cities. With the help of visualization software to visualize the experimental data and verify the experimental results introduced in this article, city tourism activities can be recommended to the destination. At present, many scholars have studied the application of improved density clustering algorithm in the field of biology and image analysis, but there are still some gaps in the development of tourism. This paper can make some contributions to the related fields.
作者：
Li YujianBeijing Univ Technol
Coll Comp Sci & Technol Beijing Municipal Key Lab Multimedia & Intelligen Beijing 100022 Peoples R China
This paper presents a clustering algorithm based on maximal theta-distant subtrees, the basic idea of which is to find a set of maximal theta-distant subtrees by threshold cutting from a minimal spanning tree and merg...
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This paper presents a clustering algorithm based on maximal theta-distant subtrees, the basic idea of which is to find a set of maximal theta-distant subtrees by threshold cutting from a minimal spanning tree and merge each of their vertex sets into a cluster, coupled with a post-processing step for merging small clusters. The proposed algorithm can detect any number of well-separated clusters with any shapes and indicate the inherent hierarchical nature of the Clusters present in a data set. Moreover, it is able to detect elements of small clusters as outliers in a data set and group them into a new cluster if the number of outliers is relatively large. Some computer simulations demonstrate the effectiveness of the clustering scheme. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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