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A new modulated hopping Discrete Fourier Transform (mHDFT) algorithm which is characterized by its merits of high accuracy and constant stability is presented. The proposed algorithm, which is based on the circular frequency shift property of DFT, directly moves the -th DFT bin to the position of , and computes the DFT by incorporating the successive DFT outputs with arbitrary time hop . Compared...
The amount of students data in the educational databases is growing day by day, so the knowledge taken out from these data need to be updated continuously. In the circumstances, where there is a need of handling continuous flow of student's data, there is a challenge of how to handle this massive amount of data into the information and how to accommodate new knowledge introduces with the new data...
Missing data imputation is an important task in cases where it is crucial to use all available data and no discard records with missing values. However, most of the existing algorithms are focused on missing at random (MAR) or missing completely at random (MCAR). In this paper, an information decomposition imputation (IDIM) algorithm using fuzzy membership function is proposed for addressing the missing...
A novel eye detection method based on template matching is proposed for glasses-free 3D device. Before matching, get the average eye template through a great quantity of eye images, splice several average templates into a chessboard template. Then locate the position of eyes by calculating the correlation coefficient between template and the candidate image. It has been testified that these algorithm...
Effective machine-learning handles large datasets efficiently. One key feature of handling large data is the use of databases such as MySQL. The freeware fuzzy decision tree induction tool, FDT, is a scalable supervised-classification software tool implementing fuzzy decision trees. It is based on an optimized fuzzy ID3 (FID3) algorithm. FDT 2.0 improves upon FDT 1.0 by bridging the gap between data...
Incomplete data clustering plays an important role in the big data analysis and processing. Existing algorithms for clustering incomplete high-dimensional big data have low performances in both efficiency and effectiveness. The paper proposes an incomplete high-dimensional big data clustering algorithm based on feature selection and partial distance strategy. First, a hierarchical clustering-based...
Existing personalized recommendation systems are facing many problems such as cold start, data sparseness and high complexity. Users' interests exist more widely and are more personalized compared with purchasing history in traditional recommendation systems. Thus, applying the interest graph in the recommendation process can make up certain shortages. This paper builds the mechanism of a user-interest-goods...
For hyperspectral data classification, feature reduction techniques have become an apparent need to extract information from original data. In this paper, we introduce Locality Sensitive Discriminant Analysis (LSDA) to perform feature reduction for classification of hyperspectral imagery. By preserving both the discriminant and local geometrical structure in the data, the proposed method can obtain...
Higher requirements of the placement of numerous instruments are necessary in Industry, Medical and Metering System. The device now available is of low efficiency and accuracy. In view of the problem, a new device was designed based on STM32, According to the feedback of the angle sensor, the PID closed-loop control algorithm was adopted. The stepper motor and reduction gearbox we reconnected by gears,...
Wireless Sensor Network as an important technology of Internet of things' development, is more and more widely used in various research fields. This paper mainly researches the part of localization application based on wireless sensor network, focuses on DV-Hop localization algorithm, and gives its algorithm simulation and analysis of the simulation results. Also this paper improves the algorithm...
In this paper the authors evaluate in context of numerical calculations accuracy classical integer order and direct non-integer based order numerical algorithms of non-integer orders derivatives and integrals computations. Classical integer order based algorithm involves integer and fractional order differentiation and integration operators concatenation to obtain non-integer order. Riemann-Liouville...
The invited papers in this session will first discuss compressive sensing as a novel approach to achieve energy scaling in highly complex sensing systems, and will then review the design tradeoffs in low-power biosignal recording interfaces.
Opportunistic networks (OppNets) are an interesting topic that are seen to have a promising future. Many protocols have been developed to accommodate the features of OppNets such as frequent partitions, long delays, and no end-to-end path between the source and destination nodes. Embedding security into these protocols is challenging and has taken a lot of attention in research. One of the attacks...
In the application of the Rough Set theory to preprocess the data, continuous attribute discretization is the necessary and key step. Here, a discretization method based on the k-means algorithm was introduced. Using this method, the wholly attributes could be classified into 2 categories. Four sets of data on UCI database were chosen to verify the performance of the presented method. In this experiment,...
Opinion leaders are core users in online communities, who can guide the direction of the public opinion. With the rapid development of microblog, identification of the microblog opinion leaders has become a significant task. In this paper, we propose a hybrid data mining approach based on user feature and interaction network, which includes three parts: a way to analyze users' authority, activity...
The traditional DV-HOP algorithm for three-dimensional localization precision is not good enough to use. Its positioning deviation is too large to find out the unknown nodes, and the scope of coverage is too small to find out all the nodes. Because of these shortcomings, a novel three-dimensional localization DV-Hop algorithm (NTLDV-HOP) is proposed. The proposed algorithm revises per jump distance...
Data aggregation is an efficient way to prolong the lifetime of wireless sensor networks (WSNs) by reducing communication traffic. However, sensor nodes are usually deployed in harsh or hostile environments. They are easy to be malfunctioning or become compromised nodes, which makes the sensor data unreliable and affects the accuracy of data aggregation. This paper proposes a secure data aggregation...
Wheat diseases are harmful to wheat production, but there are few segmentation algorithms that can effectively identify common diseases of wheat leaves. This paper proposes an automatic and efficient solution with K-means clustering. Firstly, the colour image is transformed to Lab colour space from RGB. Clustering is then done by taking the absolute difference between each pixel and the clustering...
Existing algorithms of mining preferred browsing paths just consider the influence of user visiting times, but ignore the accuracy influenced by other factors. In order to solve the problem, an improved algorithm which imports page similarity and support-preference concepts is proposed. Firstly a Web-log-based user access matrix is set up. Then by calculating the angel cosine similarity and support-preference,...
Due to the effects of noise, quantization error and regional texture details, traditional watershed algorithm tended to lead to over-segmentation. Especially, when the ridges of image are of discontinuity and the edges are of fuzziness, the over-segmentation is significantly worse and the blob of image is easy to lose vital boundary. In this paper, in order to solve these drawbacks, a watershed segmentation...
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