Most two-phase flow measurements depend on correct flow regime identification. Many methods have been proposed to identify the flow regime, but none of them can work well across different flow conditions. In this paper we apply a non-intrusive instrument of different types of sensor to extract the data under different flow conditions. In light of these different sensor information, evidence the...

As a new theory and technology, information fusion provides advanced and reliable theory and method for the information processing and decision making in the information age.This paper establishes a framework of multi-sensorand full source information fusion theory based on network environment, and establishes the information fusion model and implementation method based on multi-sensors and net...

Image understanding applications are often tainted with a high degree of complexity, uncertainty, and imprecision. The large amount of data makes it necessary to select the most useful information. The active fusion system proposed in this paper is able to eeectively select information sources, to control the acquisition process, to select processing strategies, to integrate results, and to dra...

The Dempster-Shafer (D-S) theory is an excellent method of information fusion. Because of the difference which is caused by the sensors, it is essential to deal with the evidence with a method of weighed D-S theory. The new method to deal with data fusion based on improved D-S theory has been proposed, and set up the concept of weight of sensor evidence itself and evidence distance based on a q...

Information fusion introduces special operators ◦ in probability theory and fuzzy theory. Some serious data certify in each cases these two quite distinct techniques. This communication will show that four postulates are the unique aim of these two theories. Evidence theory and fuzzy set theory replace often probabilities in medicine, economy and control. Fuzzy theory is used for example in Jap...

Strong adoption of Internet and Communication technologies across industries in the last two decades has led to large-scale digitization business processes. While this helped instant availability information, over period, source amount information have increased multi-fold giving rise Big Data. With increase volume, relevance data its raw format continues decrease time. According HACE Theorem, ...

ABSTRACT The consequences of the use of probability in modelling under uncertainty are explored, and it is shown how data and parameter independence and likelihood modularity emerge as desirable properties for statistical models. They lead directly to multi-object models which themselves create the association problem. The expectation-maximisation (EM) technique is introduced and then applied t...

The task of data fusion is to identify the true values of data items (e.g., the true date of birth for Tom Cruise) among multiple observed values drawn from different sources (e.g., Web sites) of varying (and unknown) reliability. A recent survey [20] has provided a detailed comparison of various fusion methods on Deep Web data. In this paper, we study the applicability and limitations of diffe...

Data fusion is concerned with combining information from knowledge sources such as sensors to provide a greater understanding of a given situation. Two major classes of fusion techniques in robotics and machine intelligence are (1) those based on probabilistic (such as Bayesian reasoning and the theory of evidence) models and (2) those based on least squares techniques (such as extended Kalman ...

Background and Aim: Degenerative lumbar scoliosis is a spinal deformity resulting from advanced disc degeneration and facet arthropathy. Given the inconclusive available literature and lack of high-quality data supporting the role of minimally invasive surgical management of degenerative lumbar scoliosis, this review intends to highlight and compare the various viable minimally invasive surgica...