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LiDAR technology is playing a more and more important role in power line patrol, and the working model is the key segment in this patrol. This paper objectively investigate the influence of point cloud density for power patrol by man-machine carrying laser radar equipment, and then recognize and extract the power line information. Firstly, this paper obtains the original data of power line by three...
With a large number of wind farms integrated into power systems, the load characteristics of the power systems will vary, resulting in the inapplicability of the traditional load model. Thus, it is of great importance to describe the load characteristics of power systems by taking the impact of the integration of the wind power into consideration. This paper first discusses the influence of wind power...
How the hotspot or congestion area evolves in a large scale complex networks is still not clear. The prediction of such behavior is more difficult. In this paper, the classical Fast-Newman algorithms for community detection is improved by considering node weight and edge weight in the network model. The evolution of the communities are reconstructed from the network trace. The relation between the...
Rainfall prediction is an important part of weather prediction. Compared to conventional methods predicting rainfall rate, the approach applying historical records and data mining technology shows obviously advantage in computing cost. Many excellent works have been done attempting to build predicting model with data mining methods, however, most of them just test the predicting accuracy on data set...
Natural disasters can lead to severe losses in human life and property. Because many factors combine in a disaster, such events are difficult to forecast accurately. A cooperative multi-classifier method is proposed in this paper to mine local area meteorological data. The proposed method is verified by the implementation of both base and integration classifiers. Experimental results indicate that...
Data from affordable body-sensor devices that monitor personal metrics like heart-rate, weight, and movements are changing how athletes train and perform. Existing sport-analytic tools are, however, mostly monolithic proprietary systems where athletes have little control over how their data is used and managed over time. This paper describes Girji, security centered body-sensor data acquisition and...
Secure and efficient data storage and computation for an outsourced database is a primary concern for users, especially with the push for cloud computing that affords both compute and resource scalability. Among the diverse secure building blocks for secure analytical computations on outsourced databases, the encrypted set intersection operation extracts common sensitive information from datasets...
The proliferation of malware has presented a serious threat to internet security, and made traditional signature-based methods unable to analyze and process the massive data timely and effectively. The development trend of malware motivates many research efforts in intelligent malware analysis, where machine learning is used for malware detection. Currently, most of machine learning methods on malware...
The shared emerging patterns (SEPs) is a special form of emerging patterns(EPs). In the field of data mining, EPs represents the knowledge of strong characters in one dataset and it is very important for building classifier. However, SEPs represents the shared knowledge of strong characters in two or more datasets and it has great potential for applying in analogy and transfer learning. When the training...
Multiple Criterion Group Decision Making (MCGDM) which is based on the procedure has the virtue of drawing on the wisdom of masses with the defect of time and resource wasting. Then the experience of the historical MCGDM processes as the collective knowledge for future tasks is possible to be made use of to overcome the shortcoming of MCGDM without losing its advantage. But the existing techniques...
The concept lattice is an effective tool for data analysis and knowledge extraction. In this paper, the method of extracting classification rules based on concept lattice is studied. According to the characteristics of classification rules, only the nodes with class attribute are generated in the process of constructing concept lattices; thereby the number of lattice nodes has been reduced and the...
The large-sized coal-fired power units characterizes as wide thermodynamic scale, huge equipment, large flow and mass, which results in distinct nonlinear feature in energy transmission, conversion and dissipation for specific equipment, system and process. There's highly coupling and nonlinear correlation between the energy consumption in power generation and the external environment, resources and...
The Research of detection malware using machine learning method attracts much attention recent years. However, most of research focused on code analysis which is signature-based or analysis of system call sequence in Linux environment. Obviously, all methods have their strengths and weaknesses. In this paper, we concentrate on detection Trojan horse by operation system information in Windows environment...
Compare with SOAP-based service that based on interfaces access pattern, RESTful web service is HTTP-based and use resource as the operation object. On the purpose of supporting RESTful in the enterprise information application, a Resource-oriented Information Supported Framework is constructed based on ontology construction and evolution. First, the initial ontology with relational pattern is extracted...
Spatial heterogeneity of physiogeographical components leads to spatial and temporal changes of hydrological processing in watershed. Watershed digital elevation model used to build digital drainage network model and extraction of drainage characteristics is an important prerequisite of distributed hydrological processing simulation. This paper presents a digital drainage network model of distributed...
From the reality, this article presents anti-money laundering real-time system architecture on the base of analyzing custom transaction. At the same time, data process, custom transaction and bank node are discussed.
The task of finding authoritative people within an organization has received increased interest over the past few years. To identify an expert in a specific field, expertise evidence of candidates should be collected in the enterprise corpora to represent one's knowledge and skills. Though there have been various methods proposed for evidence collecting and expertise modeling, little work has been...
Conditional Random Fields (CRFs) are widely used in machine learning and natural language processing fields. A number of methods have been developed for CRF training. However, even with state-of-the-art algorithms, the training of CRF is still very time and space consuming. This make it infeasible to use CRFs in large-scale data analysis tasks. This paper proposes an efficient algorithm, HOCT, for...
This paper presents a visual cortex inspired method for corner and vertex detection. Endstopped cells in cortical area VI, which combine outputs of complex cells tuned to different orientations, serve to detect line and edge crossings (junctions) and points with a large curvature. This property is used for corner and vertex detection in this paper. We utilize the endstopped neurons model of Dobbins,...
In software engineering, formal software specification has long been touted as a way to increase the quality and reliability of software. At the same time, component-based development (CBD) is an important emerging topic, which aims to compose systems from prebuilt software units or components. How to formally represent the software components supporting the development of real-time application systems...
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