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This paper provides a method of accurate time delay extraction for indoor pulse sound location. For short pulse signal, we use endpoint detection method and smoothed coherence transform weighted generalized cross correlation (SCOT-GCC) algorithm to estimate time difference of arrivals (TDOAs) between two microphones, and extract TDOAs of SCOT-GCC which is much closer to endpoint detection results...
Software defined infrastructure greatly reduces the deployment cost of distributed applications. Many distributed applications employ message oriented middleware (MOM) for the integration of heterogeneous components and to achieve scalability and fault tolerance. The structure of a distributed application can be very complex. In addition, the asynchronous message delivery model of MOM further complicates...
Given multiple classifiers, one prevalent approach in classifier ensemble is to diversely combine classifier components (diversity-based ensemble), and a lot of previous works show that this approach can improve accuracy in classification. However, how to measure diversity and perform diversity-based learning are still challenges in the literature. Moreover, the learning procedure highly depends upon...
A domain-decomposition-based preconditioner (DDP) is presented for the hybrid finite element-boundary integral-multilevel fast multipole algorithm (FE-BI-MLFMA). The formulation of FE-BI is first approximated by the finite element method (FEM) with absorbing boundary condition (ABC). Then this approximate FEM-ABC formulation is solved by using the finite element tearing and interconnecting method...
In ensemble learning, a higher accuracy can be achieved by integrating some classifiers instead of all the classifiers. But, it is very difficult to select the best classifier combination which can be seen as an optimization problem, from a pool of classifiers. To deal with this problem, we propose a new classifier selection method, Sorting-based Dynamic Classifier Ensemble Selection (SDES), which...
The robustness and reusability of Intellectual Properties (IPs) is the key to the success of the modern System on chip (SoC) designs. Therefore, it is very important to implement a rigid IP qualification platform to ensure the quality of IPs in the SoC design flow. In this paper, we propose an automated IP qualification platform, which uses XML schema technique to describe the quality model and has...
Transmission property of one-dimensional photonic crystal containing left-handed materials is simulated by using precise integration algorithm. Simulation results are also analyzed. Photonic crystal is divided into different sections. The export stiffness matrix of each section is first obtained by using precise integration algorithm, and then each stiffness matrix is assembled. Electric field can...
Document images captured by a mobile phone camera often have perspective distortions. In this paper, fast and robust vanishing point detection methods for such perspective documents are presented. Most of previous methods are either slow or unstable. Based on robust detection of text baselines and character tilt orientations, our proposed technology is fast and robust with the following features:...
Airborne Light Detection And Ranging (LIDAR) provides accurate height information for objects on the earth, which makes LIDAR become more and more popular in terrain and land surveying. In particular, LIDAR data offer vital and significant features for land-cover classification which is an important task in many application domains. In this paper, an unsupervised approach based on an improved fuzzy...
Reduced Support Vector Machine (RSVM) was proposed as an alternate of the standard SVM. Motivated by resolving the difficulty on handling large data sets using SVM, it pre-extracts a subset of data as `support vectors' and solves a smaller optimization problem. But it selects `support vectors' randomly from the training set, and this will affect the result. A new method called reduced support vector...
Random forest is an excellent ensemble learning method, which is composed of multiple decision trees grown on random input samples and splitting nodes on a random subset of features. Due to its good classification and generalization ability, random forest has achieved success in various domains. However, random forest will generate many noisy trees when it learns from the data set that has high dimension...
The reduced support vector machine (RSVM) was proposed to overcome the computational difficulties as well as to reduce the model complexity in generating a nonlinear separating surface for a massive data set. However, it selects `support vectors' randomly from the training set, this will effect the result. To overcome this shortcoming of RSVM, an improved RSVM algorithm is presented in this paper...
AdaBoost is an efficient method for producing a highly accurate learning algorithm by assembling multiple classifiers, but it is also widely known for its long duration of off-line learning. Especially, when it is applied for feature selection for object detection, its learning process is to exhaustively evaluate every feature in a large set. With the increasing of image resolution and complexity...
In this paper, a review of man-made object detection algorithms is presented based on various fractal features which are derived from the blanket covering method. These fractal features include fractal dimension (D), fractal model fitting error (FE), D-dimension area (K), multi-scale fractal feature related with D (MFFD), and multi-scale fractal feature related with K (MFFK). To choose the optimal...
The steam turbine generator faults not only damage the generator itself, but also cause outages and loss of profits, for this reason, many researchers work on the fault diagnosis. But misdiagnosing may also lead to serious losses. In order to improve the diagnosis reliability and reduce the loss caused by misdiagnosis, in this paper, cost integrated multiclass SVM with reject option (CIMC-SVM) is...
China has already become world's largest coal producer and consumer. China's production in 2006 roughly equaled the combined production of the next four top producers (the United States, India, Australia and Russia). The dynamic GM(1,1) model of grey theory is used to forecast the coal production and consumption in China. In order to improve the forecast accuracy, the original GM(1, 1) models are...
In this paper, a fuzzy Markov random field (FMRF) model is used to segment land-objects into tree, grass, building, and road regions by fusing remotely sensed LIDAR data and co-registered color bands, i.e. scanned aerial color (RGB) photo and near infra-red (NIR) photo. An FMRF model is defined as a Markov random field (MRF) model in a fuzzy domain. Three optimization algorithms in the FMRF model,...
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