The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In order to estimate the amount of energy that will be generated by a wind farm and provide efficient power distribution planning, it is necessary to deliver information of wind speed at all wind turbines. This paper proposes a scheme for compressing wind speed measurements exploiting both temporal and spatial correlation between the turbine readings via distributed source coding. The proposed scheme...
Accurately estimating correlation between sources has significant impact on the performance of Slepian-Wolf (SW) coding. In this paper, we propose a low complexity estimator based on Laplace propagation for exploiting the source correlation at the decoder side, by modeling the correlation estimation as a Bayesian inference problem. Through simulations, we show that the proposed algorithm can simultaneously...
In order to transform the vibration energy into electric energy, piezoelectric materials are often used due to their properties. This paper proposes an energy analysis model of cylindrical panels laminated with piezoelectric patch. With simply supported boundary condition at four sides, panels are excited by harmonic line loadings in transverse direction. Love & Kirchhoff thin shell theory and...
Boundary points detection of clusters is important in image processing, machine learning and so on. We propose a boundary detecting algorithm called BDDTS (Boundary Detection algorithm of clusters based on Dual Threshold Segmentation), which is based on the characteristics of the distribution of boundary points. The algorithm, which firstly accrues to the different cost function values of data points,...
Belief propagation (BP) is a powerful algorithm to decode low- density parity check (LDPC) codes over additive white Gaussian noise (AWGN) channels. However, the traditional BP algorithm cannot adapt efficiently to the statistical change of SNR in an AWGN channel. This paper proposes an adaptive scheme that incorporates expectation propagation (EP) into the BP based LDPC decoding process. The proposed...
The article based on the Apriori improved model, combined with the related theory of natural disasters derivative events, analyzes the information data of the natural disaster in the last three years in China, and finally confirms 10 representative derivative events of natural disasters. Through analyzing and sorting, this paper checks the results based on minimum support and minimum confidence, and...
Testing statistical association of individual rare variants is underpowered due to low frequency. A common approach is to test the aggregated effects of individual variants in a locus such as genes. Current methods have distinct power profiles that are determined by underlying assumptions about the genetic model and effect size. Here we describe a parametric Bayesian approach to detect the association...
Acquiring and processing astronomical images is becoming increasingly important for accurate space weather prediction and expanding our understanding about the Sun and the Universe. These images are often rich in content, large in size and dynamic range. Efficient, low-complexity compression solutions are essential to reduce onboard storage, processing, and communication resources. Distributed compression...
Based on the analysis of the distribution and characteristics of up-layer sediment in Lake Wuliangsuhai, its health status in terms of deposition rates were assessed. The results showed that: the distribution of deposition thickness significantly varied with sampling sites. These may be mainly controlled by the effects of landforms of the lake bottom, source of the sediment, hydrodynamic conditions,...
In this paper, a new classification scheme for polarimetric SAR data sets is presented. The proposed method mainly involves two concepts: Freeman-Durden decomposition and co-polarization ratio. The core concept of Freeman-Durden decomposition is to decompose the covariance matrix into three scattering mechanisms: surface scattering, double-bounce scattering and volume scattering; the co-polarization...
The research focuses on how to improve the employment rate of the computer science and technology major graduates. The paper first described why the employment of this major was low by carried on the thorough investigation and analysis. Then it described the feasibility construction scheme of computer science and technology characteristic major of Xuchang University which is an applied college. The...
In this paper, a novel method for water/land segmentation is proposed based on the framework of geodesic distance. The proposed method models the water/land according to the statistics of both the speckle and land covers, which leads to a fast point-wised coarse segmentation. Based on the water/land models, the boundary area between water and land can be localized with automatically generated class...
The article tries to apply the hierarchical location theory to traditional Location-allocation model to form a dynamic hierarchical location model. This model considers the rating of bank outlet and the influence of population redistribution caused by land use alteration after the urban extension. The case research of the downtown in Kunming indicates that it has certain advantage in simulating the...
In this work, an optimization model of load balancing in P2P network is proposed to make full use of each node resource, and to consider the coordination of network resource allocation between the other network area and this area, making the whole network resource can be used as fully as possible. based on the load information of the different nodes, we layer the nodes and use an undirected graph...
This paper investigates the control algorithm of an exoskeleton for hand rehabilitation, which can realize the active, passive, and assisted rehabilitation motion. The active mode is accomplished with the force control algorithm during which the resistance is compensated in free space and the virtual interactive force is rendered to the finger in constraint space. The passive mode is realized by the...
Quantum secret sharing is a important problem in the quantum cryptography. We analyzed two kinds of practical quantum secret sharing protocols without entanglement. And their combination could be a basic unit in the quantum secret sharing network, which is potential in practical applications.
In this paper, we propose an adaptive Distributed Video Coding (DVC) scheme that dynamically estimates correlation statistics of the scene in a video sequence to enhance belief-propagation (BP) Slepian-Wolf (SW) decoding. In order to exploit the robustness of distributed source coding (DSC) designs, we integrate particle filtering with standard BP decoding in one factor graph to estimate online correlation...
This paper describes ongoing work in analyzing sensor data logged in the homes of seniors. An estimation of relative energy expenditure is computed using motion density from passive infrared motion sensors mounted in the environment. We introduce a new algorithm for detecting visitors in the home using motion sensor data and a set of fuzzy rules. The visitor algorithm, as well as a previous algorithm...
Frequent items detection is one of the valuable techniques in many applications, such as network monitor, network intrusion detection, worm virus detection, and so on. This technique has been well studied on deterministic databases. However, it is a new task on emerging uncertain database. In this paper, a new definition of frequent items detection on uncertain data is defined. Based on it, two efficient...
Considering training time of traditional BP neural network is too long and it can not solve the problem that input vector is multiple-valued, a new method based on rough BP neural network for fault diagnosis is presented. The approach is realized by applying PSO (particle swarm optimization) to discretize continuous attributes, using property of dependency of rough set to carry through attribute reduction...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.