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The growth of digital storage capacities and diversity devices has had a significant time impact on digital forensic laboratories in law enforcement. Backlogs have become commonplace and increasingly more time is spent in the acquisition and preparation steps of an investigation as opposed to detailed evidence analysis and reporting. There is generally little room for increasing digital investigation...
Laser scanning (also known as Light Detection And Ranging) has been widely applied in various application. As part of that, aerial laser scanning (ALS) has been used to collect topographic data points for a large area, which triggers to million points to be acquired. Furthermore, today, with integrating full wareform (FWF) technology during ALS data acquisition, all return information of laser pulse...
Today, mobile phones are very popular, fast growing technology. Mobile phones of the present day are more and more like small computers. The so-called “smartphones” contain a wealth of information each. This information has been proven to be very useful in crime investigations, because relevant evidence can be found in data retrieved from mobile phones used by criminals. In traditional methods, the...
Nowadays, massive amounts of data which are often geographically distributed and owned by different organisations, are being mined. As consequence, large volumes of knowledge is being generated. This causes the problem of efficient knowledge management in distributed data mining (DDM). The main aim of is to exploit fully the benefit of distributed data analysis while minimising the communication overhead...
The huge data requirements of large nowadays applications, in science, engineering, and commerce, make efficient data placement an essential need. For this purpose, we propose a framework which can be considered as a grid workflow system with advanced data placement capabilities. Computational jobs and data placement are handled concurrently. This framework also includes a specialised scheduling for...
Today, a deluge of data is collected from different fields. These massive amounts of data which are often geographically distributed and owned by different organisations are being mined. As consequence, a large mount of knowledge is being produced. This causes the problem of efficient knowledge management in distributed data mining (DDM). The main aim of DDM is to exploit fully the benefit of distributed...
Distributed data mining (DDM) deals with the problem of finding patterns or models, called knowledge, in an environment with distributed data and computations. Today, a massive amounts of data which are often geographically distributed and owned by different organisation are being mined. As consequence, a large mount of knowledge are being produced. This causes problems of not only knowledge management...
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