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Power grid is often destroyed due to frequent typhoon disasters in coastal area of China, when making urgent repair on it, the guarantee of emergency supplies of power grid became vital. Currently, the sample data collected by the power grid company for typhoon events is relatively few, while typhoons events continue to occur, the data could be constantly obtained along with time series, but the traditional...
This paper proposes a CNN (Convolutional neural network) based blood vessel segmentation algorithm. Each pixel with its neighbors of the fundus image is checked by the CNN. The preliminary segmentation results of fundus images were refined by a two stages binarization and a morphological operation successively. The algorithm was tested on DRIVE dataset. While the specificity is 0.9603, sensitivity...
Distributed parameter estimation is more practical in wireless sensor networks, as it has less communication overhead and is robust in large scale sensor networks. To solve the state estimation problem of nonlinear and non-Gaussian system, we propose a distributed cubature Kalman particle filter, which use cubature Kalman filter to generate the importance proposal distribution of particle filter,...
As the modern radar system become increasingly multi-functional and sophisticated, the specific emitter identification (SEI), recognizing the different radar devices of the same type, seems to be one of the most important tasks in electronic warfare. The main operation of the SEI is utilizing a distance function to measure the distinction between the testing feature vector and each template vector...
In this paper, the best irradiation technology for improving the quality of liquor by 60Co-γ irradiation was studied. Different doses of rays on liquor quality Law model was built by Bayesian regularization BP neural network method. This model was used for prediction and verification, and then the particle swarm optimization algorithm was used to predict the process parameters of the irradiation process...
Just Noticeable Depth Difference (JNDD) describes the sensitivity of human for depth difference to Stereoscopic three Dimensional (S3D) viewing, which is an important cue in research on Human Visual System (HVS). Understanding the factors of human depth perception is helpful to the research on stereo image processing and optimization, which is heavily based on exploitation of HVS. The traditional...
Jilin ginseng as the research object in this article, from the government regulation, consumer, traceability chain enterprise three parties as a starting point, combining with the key data specification technology, radio frequency identification technology (RFID) and barcode logo design and based on the SAP Net Weaver's integrated development platform technology, design and implementation to cover...
In this paper, we present a parallel machine scheduling with shared and multi-mode resources (PMS-SMR) problem which is widely encountered in manufacturing engineering. The integer programming for this problem is given and a hybrid particle swarm optimization (HPSO) algorithm is put forward with a problem-based solution representation and a balancing optimization (BO)-based local search. The HPSO...
Turnout systems are one of the most critical components of railway infrastructure, and they are also an extremely vulnerable part of railway signaling systems. Failure prediction of signaling systems is an attractive area of research in the field of railway operation maintenance. In this work, we focus on the prediction of weather-related failure of turnouts since weather has significant impacts on...
To solve the problem that there is few invariant features, which can be extracted from both images, to be matched for large changes of view, an efficient invariant image matching approach is presented. The proposed approach consists of two main steps. In the first step, we use the multi-resolution strategy to detect maximally stable extremal regions (MSERs) and obtain the geometric transformation...
In open and distance education field, making use of data mining technologies to understand students' practical needs and usage habits about professional courses, which will greatly enhance students learning. China Open University system is Chinese largest scale organization engaging in open and distance education, and it has taken Chinese education ministry's a rural education project, called "one...
This paper presents a new contrast enhancement method using Histogram Equalization named Dualistc Sub-Image and Non-parametric Modified Histogram Equalization (DSINMHE). Our proposed method consists of three steps: (i) The original image is segmented into two sub-images by the median value of the image. (ii) Then we use the histogram modification technique to maximize entropy and control over enhancement...
As an effective dimensionality reduction method, feature selection can remove the irrelevant variables and increase the accuracy in machine learning. In this paper, a feature selection method based on grouped sorting is proposed to solve the problem of high-dimensional data processing. As in this work, feature grouping is firstly carried out with the redundancy between the features as the group criteria...
In this paper we present a novel framework based on multi-feature extraction for anomaly detection in video surveillance which global anomaly and local anomaly are detected separately. To detect global anomaly, we define kinetic energy Ek and compute the first derivative of Ek and then derive a global anomaly score of each test frame. As for local anomaly detection, three kinds of local anomaly are...
Traditional traffic lights control system works on a fixed-time basis, which can't optimize the time of traffic lights according to the change of traffic flow. To address this issue, this paper proposes an approach based on data-driven belief rule base for smart traffic lights. The main idea of this approach is using historical traffic data to predict traffic flow, and then determine traffic lights...
The abstract argumentation framework can only deal with the attack relations between single arguments and not allow the attack relations among the sets of arguments. However, there usually are various attack relations among groups in realistic applications of argumentation. In this paper, we propose a group-based argumentation framework, which allows us to cope with the attack relation among the sets...
Behavior models play an important role in analytical simulation system. However, weaknesses such as hard modeling, poor expansibility and little flexibility still exist in current models. In this paper, a behavior model is designed, which consists of Rule-based Expert system and Mission Components. The expert system has high efficient and flexible auto-decision capability. Mission Component provides...
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