In distributed energy hybrid power system of intelligent building, Multi-input DC/DC converter has many advantages, simplifying the dynamic interface to the system for distributed power and playing voltage Boost or Bu...
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ISBN:
(纸本)9781467371070
In distributed energy hybrid power system of intelligent building, Multi-input DC/DC converter has many advantages, simplifying the dynamic interface to the system for distributed power and playing voltage Boost or Buck more effectively in the system. Based on OpenADR communication protocol and according to electricity prices, the system load can be adjusted by the intelligent controller for the economic optimal goal Besides, an intelligent building DC Micro-grid simulation in which the Wind-PV-diesel battery hybrid power system also realized will be presented so as to increase accesses of distributed energy.
With the rapid development of network technology, network security problems are gradually increasing, and the network attack situation is very severe. In a complex attack scenario, timely detection of potential attack...
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ISBN:
(纸本)9781450376624
With the rapid development of network technology, network security problems are gradually increasing, and the network attack situation is very severe. In a complex attack scenario, timely detection of potential attack behaviors and timely identification and pre-judgment of attack intentions are important components of security risks. However, the attack behavior in the network presents complexity, multi-step and uncertainty, which brings new technical challenges to attack intent analysis. Aiming at the problem that the attack intention of multi-step complex attack is difficult to identify, this paper proposes an attack intention analysis method based on attack path graph. Firstly, aiming at the multi-step complex attack behavior analysis problem, the key asset assessment technology is used to find out the key assets in the network system, and the hypothetical attack intention is generated according to the security protection requirements of the network system. Then, it is difficult to manually construct the attack path map in the large-scale network, and the automatic generation of the attack path map is realized. Finally, a method of network attack intent identification is proposed and a calculation method of attack intent probability is designed, which improves the efficiency and accuracy of attack intent recognition.
The digital system of Archaeological includes multi-scale non-destructive detection of archaeological methods,data mining technologies and the GIS of archaeological *** preservation is not just for the protection of c...
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The digital system of Archaeological includes multi-scale non-destructive detection of archaeological methods,data mining technologies and the GIS of archaeological *** preservation is not just for the protection of cultural relics has been *** non-destructive detection method to detect archaeological artifacts and clarify the situation of cultural relics buried *** detection data through the using of data mining algorithm make out the archaeological ***,use GIS technology to achieve the detection of data management and integration of data mining methods.A whole system of digital archaeological built on the GIS platform,based on the using of data mining technology to achieve a detection method and archaeological information mapping,the system for the digital archaeology has provided a complete technical support.
In this paper, we propose a vehicle detection method based on AdaBoost. We focus on the detection of front-view car and bus with occlusions on highway. Samples with different occlusion situations are selected into the...
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ISBN:
(纸本)9781424449934
In this paper, we propose a vehicle detection method based on AdaBoost. We focus on the detection of front-view car and bus with occlusions on highway. Samples with different occlusion situations are selected into the training set. By using basic and rotated Haar-like features extracted from the samples in the set, we train an AdaBoost-based cascade vehicle detector. The performance tests on static images and short time videos show that (1) our approach detects cars more effectively than buses (2) the real-time detection of our method on video proceeds at 30 frames per second.
The contributions of scientific researchers include personal influence and talent training achievements. In this paper, using 9964 high-quality co-author scientific papers in English teaching research from China citat...
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In polynomial and linear control systems, the Lienard-Chipart stability criterion plays an important role in the judgment of the zeros of a real polynomial based on the inertia of a Bezout matrix. In this paper we con...
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In polynomial and linear control systems, the Lienard-Chipart stability criterion plays an important role in the judgment of the zeros of a real polynomial based on the inertia of a Bezout matrix. In this paper we consider the case in the Bernstein polynomials basis. First, the Bernstein Bezout matrix and some important properties are introduced, and then a generalized perturbations of a real polynomial under the Bernstein polynomials basis is considered. Finally, a generalized Lienard-Chipart stability criterion in terms of the Bernstein Bezout matrix is established.
This paper proposes a dual-band wearable monopole antenna adopting an electromagnetic band-gap (EBG) structure, which operates at 2.45 and 5.8 GHz ISM bands and is suitable for wearable applications. Both the monopole...
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Spherical image object detection emerges in many applications from virtual reality to robotics and automatic driving, while many existing detectors use $l_{n}$ -norms loss for regression of spherical bounding boxes....
Spherical image object detection emerges in many applications from virtual reality to robotics and automatic driving, while many existing detectors use $l_{n}$ -norms loss for regression of spherical bounding boxes. There are two intrinsic flaws for $l_{n}$ -norms loss, i.e., independent optimization of parameters and inconsistency between metric (dominated by IoU) and loss. These problems are common in planar image detection but more significant in spherical image detection. Solution for these problems has been extensively discussed in planar image detection by using IoU loss and related variants. However, these solutions cannot be migrated to spherical image object detection due to the undifferentiable of the Spherical IoU (SphIoU). In this paper, we design a simple but effective regression loss based on Gaussian Label Distribution Learning (GLDL) for spherical image object detection. Besides, we observe that the scale of the object in a spherical image varies greatly. The huge differences among objects from different categories make the sample selection strategy based on SphIoU challenging. Therefore, we propose GLDL-ATSS as a better training sample selection strategy for objects of the spherical image, which can alleviate the drawback of IoU threshold-based strategy of scale-sample imbalance. Extensive results on various two datasets with different baseline detectors show the effectiveness of our approach.
In this paper, we introduced an intelligent call center platform (ICCP) for communication enterprises. The platform is based on two broad suites of technologies: Knowledge management and natural language processing. F...
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ISBN:
(纸本)9781424463275
In this paper, we introduced an intelligent call center platform (ICCP) for communication enterprises. The platform is based on two broad suites of technologies: Knowledge management and natural language processing. First, we designed an enterprise knowledge modeling technology, and provided a knowledge management system for managing customer service knowledge. Then mobile customers are allowed to send Chinese queries, through either Internet tools (e.g. MSN, QQ, BBS and Fetion) or Wireless SM devices (e.g. mobile phones), to a multi-tier natural language understanding engine, and the engine retrieves the knowledge bases to find correct answers after understanding the queries. The ICCP has been successfully used in a domestic communication group since March 2009, and achieved a satisfactory performance.
Deep neural networks have greatly promoted the performance of single image super-resolution (SISR). Conventional methods still resort to restoring the single high-resolution (HR) solution only based on the input of im...
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