In order to overcome the problems of large calculation error and low evaluation accuracy of traditional online education reform effect evaluation methods, this paper proposes a new online education reform effect evalu...
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In order to overcome the problems of large calculation error and low evaluation accuracy of traditional online education reform effect evaluation methods, this paper proposes a new online education reform effect evaluation method based on fuzzy weight. First, the key influencing factors of online teaching reform effect evaluation are determined for different subjects. Then, the cluster algorithm is used to determine the cluster centre of the evaluation index data, and the construction and quantification of the online teaching reform effect evaluation index system are completed. Finally, the fuzzy weight is determined, and the online education reform effect evaluation algorithm is constructed by using the judgment matrix and the training evaluation index data set. The experimental results show that this method can reduce the calculation error of evaluation weight and improve the evaluation accuracy, and the evaluation accuracy is always kept above 90%.
Ultra-high frequency (UHF) monitoring technique for partial discharge (PD) is an important technical means to evaluate the insulation deterioration state of GIS equipment. However, huge interference and aliasing of a ...
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ISBN:
(纸本)9781538664612
Ultra-high frequency (UHF) monitoring technique for partial discharge (PD) is an important technical means to evaluate the insulation deterioration state of GIS equipment. However, huge interference and aliasing of a multiple PD signals in field test effect the sensitivity and reliability of UHF detection. To identify the interference and aliasing of a multiple PD signals more accurately, meanwhile to cover the shortage of amplitude ratio clustering technique which can not identify signals' characteristics in frequency domain, the accuracy and adaptability of clustering algorithm should be further improved. To solve these problems, the separation and measurement technique based on dynamic frequency-selection and frequency division applied to multi discharge sources are proposed. UHF conditioner with high sensitivity and wide dynamic range are designed, whose work modes include wide-band amplification detection and narrowband frequency selection. Accordingly, the interactive dynamic clustering algorithm is proposed. The PD tests in real GIS with five kinds of PD defect and interference models are designed, the real PD tests indicate that the interactive dynamic clustering algorithm is more adaptable in the complex environment of the multiple PD and interference signals.
A 3D feature space is proposed to represent visual complexity of images based on Structure, Noise, and Diversity (SND) features that are extracted from the images. By representing images using the proposed feature spa...
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A 3D feature space is proposed to represent visual complexity of images based on Structure, Noise, and Diversity (SND) features that are extracted from the images. By representing images using the proposed feature space, the human classification of visual complexity of images as being simple, medium, or complex can be implied from the structure of the space. The structure of the SND space as determined by a clustering algorithm and a fuzzy inference system are then used to assign visual complexity labels and values to the images respectively. Experiments on Corel 1000A dataset, Web-crawled, and Caltech 256 object category dataset with 1000, 9907, and 30607 images respectively using MATLAB demonstrate the capability of the 3D feature space to effectively represent the visual complexity. The proposal provides a richer understanding about the visual complexity of images which has applications in evaluations to determine the capacity and feasibility of the images to tolerate image processing tasks such as watermarking and compression.
GM_PHD (Gaussian mixture of probability hypothesis density) cannot completely track multiple targets, such as the flying birds in the complex low-altitude airspace near the airport, due to the lack of the steps of bir...
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GM_PHD (Gaussian mixture of probability hypothesis density) cannot completely track multiple targets, such as the flying birds in the complex low-altitude airspace near the airport, due to the lack of the steps of birth detection, track extraction and death detection. A new algorithm is proposed to solve this problem, which mainly contributes to the following three aspects. First, the k-nearest neighbour algorithm is used to detect the birth of bird targets from measurements which is necessary to construct the birth intensity function. Second, the clustering algorithm is introduced into the probability hypothesis density filter framework to extract the bird targets' tracks from the filtering results. Third, an algorithm is added to detect the death of bird targets for better tracking. The Gaussian mixture implementation of the algorithm denoted as BT_GM_PHD (Bird Tracking GM_PHD) is presented. The test results on simulation and ground-truth data show that the proposed BT_GM_PHD algorithm can effectively track the multiple flying bird targets in the complex low-altitude airspace near the airport, outperforming the GM_PHD filter.
In this article, we prove the relaxed triangle inequality for Southworth and Hawkins, Drummond and Jopek orbital similarity criteria on the set of non-rectilinear Keplerian orbits with the eccentricity bounded above. ...
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In this article, we prove the relaxed triangle inequality for Southworth and Hawkins, Drummond and Jopek orbital similarity criteria on the set of non-rectilinear Keplerian orbits with the eccentricity bounded above. We give estimates of the minimal coefficients in the inequality for each criterion and show that one of the calculated coefficients is exactly minimal. The obtained inequalities can be used for the acceleration of algorithms involving pairwise distances calculations between orbits. We present an algorithm for calculation of all distances not exceeding a fixed number in a quasi-metric space and demonstrate that the algorithm is faster than the complete calculation on the set of meteors orbits. Finally, we estimate the correlation dimensions of the set of main belt asteroids orbits and meteors orbits with respect to various orbital metrics and quasi-metrics.
Vehicular Ad Hoc Network (VANET) is an application of Mobile Ad Hoc (MANET) for road traffic. VANET has the characteristics of high moving speed, frequent changing topology, and different node densities. In this disse...
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Vehicular Ad Hoc Network (VANET) is an application of Mobile Ad Hoc (MANET) for road traffic. VANET has the characteristics of high moving speed, frequent changing topology, and different node densities. In this dissertation, according to the characteristics of VANET, it is aimed to improve the performance of MAC layer and provide reliable and real-time communications between vehicles. Modeling and analysis of periodic broadcast, modeling and analysis of broadcast in control channel, dynamic contention window scheme, MAC delay based clustering algorithm and cluster based time division multiple access are studied in *** main research contributions are as follows.(1) Modeling of periodic broadcast and dynamic contention window scheme in VANETA 1-D Markov model is proposed to analyze the performance of periodic broadcast in VANET. In this model, a new idle state is introduced under non-saturated condition when there is no message to send in the buffer of a node. The freezing of backoff time counter in backoff process is also considered in this model and a discrete time D/M/l queue is established to model the buffer of each node. Theoretical analysis show when vehicle density increases the performance of periodic broadcast decreases accordingly. Dynamic contention window scheme is proposed according to the changing of node density. Simulation results show the collision probability of DCW scheme is lower than that of fixed-contention window broadcast in IEEE 802.11 p. Simulation results also verify the accuracy of the Markov model.(2) Modeling of priority access to control channel in VANETAccording to the characteristics of messages with different priorities accessing to control channel, discrete time queue D/M/1 and M/M/1 are proposed to model periodic messages and emergent messages, respectively. Priority analysis is added to this model which is based on the previous 1-D Markov model. Packet collision probability, access delay of periodic message and emergent me
SAR (synthetic aperture radar) ATR (automatic target recognition) algorithm proposed by Lincoln Lab is widely used for its classic mode that is a three-stage framework. The clustering algorithm between prescreener and...
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SAR (synthetic aperture radar) ATR (automatic target recognition) algorithm proposed by Lincoln Lab is widely used for its classic mode that is a three-stage framework. The clustering algorithm between prescreener and discriminator of SAR ATR algorithm is important for the performance of detection algorithm. This paper introduces the common clustering algorithm used in SAR ATR algorithm and analyzes its disadvantages of clutter disturbance. A morphologic method is proposed to be used before clustering that can delete the isolated pixels and save the pixel blobs in an image. It avoids the disturbance of clutter for clustering. The clustering results of an actual SAR image testify that the morphologic method is effective for improving clustering results.
The development of the Internet of Things has prominently expanded the perception of human beings, but ensuing security issues have attracted people's attention. From the perspective of the relatively weak sensor ...
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The development of the Internet of Things has prominently expanded the perception of human beings, but ensuing security issues have attracted people's attention. From the perspective of the relatively weak sensor network in the Internet of Things. Proposed method Aiming at the characteristics of diversification and heterogeneity of collected data in sensor networks, the data set is clustered and analyzed from the aspects of network delay and data flow to extract data characteristics. Then, according to the characteristics of different types of network attacks, a hybrid detection method for network attacks is established. An efficient data intrusion detection algorithm based on K-means clustering is proposed. This paper proposes a network node control method based on traffic constraints to improve the security level of the network. Simulation experiments show that compared with traditional password-based intrusion detection methods;the proposed method has a higher detection level and is suitable for data security protection in the Internet of Things. This paper proposes an efficient intrusion detection method for applications with Internet of Things.
In this paper, we firstly analyze Lingras' algorithm with respect to its objective-function, numerical stability of the *** we point out its shortcoming in adjusting thethree coefficients W1, Wu and ε.To tackle t...
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In this paper, we firstly analyze Lingras' algorithm with respect to its objective-function, numerical stability of the *** we point out its shortcoming in adjusting thethree coefficients W1, Wu and ε.To tackle this problem, arough k-means clustering method is finally presented with adaptive *** algorithm is used in a testing sample and obtains a less error clustering rate.
A new fuzzy clustering approach is presented based on two steps:data reduction and core data aggregation in a reduced subset of original *** data reduction largely reduces number of data points in a dataset and improv...
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A new fuzzy clustering approach is presented based on two steps:data reduction and core data aggregation in a reduced subset of original *** data reduction largely reduces number of data points in a dataset and improves clustering quality based on a grid-based initialization for data space,where each grid is continuously bisected into two volumeequal smaller grids,so that a group of core points is *** clustering these core points,all cluster prototypes are *** new approach can work faster and more effective in a series of datasets compared with most of the existing fuzzy clustering approaches,effectively approximating the number of *** experiments were used to verify the usefulness of the new approach.
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