2,520 research outputs found
Finding Academic Experts on a MultiSensor Approach using Shannon's Entropy
Expert finding is an information retrieval task concerned with the search for
the most knowledgeable people, in some topic, with basis on documents
describing peoples activities. The task involves taking a user query as input
and returning a list of people sorted by their level of expertise regarding the
user query. This paper introduces a novel approach for combining multiple
estimators of expertise based on a multisensor data fusion framework together
with the Dempster-Shafer theory of evidence and Shannon's entropy. More
specifically, we defined three sensors which detect heterogeneous information
derived from the textual contents, from the graph structure of the citation
patterns for the community of experts, and from profile information about the
academic experts. Given the evidences collected, each sensor may define
different candidates as experts and consequently do not agree in a final
ranking decision. To deal with these conflicts, we applied the Dempster-Shafer
theory of evidence combined with Shannon's Entropy formula to fuse this
information and come up with a more accurate and reliable final ranking list.
Experiments made over two datasets of academic publications from the Computer
Science domain attest for the adequacy of the proposed approach over the
traditional state of the art approaches. We also made experiments against
representative supervised state of the art algorithms. Results revealed that
the proposed method achieved a similar performance when compared to these
supervised techniques, confirming the capabilities of the proposed framework
Paradox Elimination in DempsterâShafer Combination Rule with Novel Entropy Function: Application in Decision-Level Multi-Sensor Fusion
Multi-sensor data fusion technology in an important tool in building decision-making applications. Modified DempsterâShafer (DS) evidence theory can handle conflicting sensor inputs and can be applied without any prior information. As a result, DS-based information fusion is very popular in decision-making applications, but original DS theory produces counterintuitive results when combining highly conflicting evidences from multiple sensors. An effective algorithm offering fusion of highly conflicting information in spatial domain is not widely reported in the literature. In this paper, a successful fusion algorithm is proposed which addresses these limitations of the original DempsterâShafer (DS) framework. A novel entropy function is proposed based on Shannon entropy, which is better at capturing uncertainties compared to Shannon and Deng entropy. An 8-step algorithm has been developed which can eliminate the inherent paradoxes of classical DS theory. Multiple examples are presented to show that the proposed method is effective in handling conflicting information in spatial domain. Simulation results showed that the proposed algorithm has competitive convergence rate and accuracy compared to other methods presented in the literature
A Survey on Multisensor Fusion and Consensus Filtering for Sensor Networks
Multisensor fusion and consensus filtering are two fascinating subjects in the research of sensor networks. In this survey, we will cover both classic results and recent advances developed in these two topics. First, we recall some important results in the development ofmultisensor fusion technology. Particularly, we pay great attention to the fusion with unknown correlations, which ubiquitously exist in most of distributed filtering problems. Next, we give a systematic review on several widely used consensus filtering approaches. Furthermore, some latest progress on multisensor fusion and consensus filtering is also presented. Finally,
conclusions are drawn and several potential future research directions are outlined.the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61374039, 61304010, 11301118, and 61573246, the Hujiang Foundation of China under Grants C14002
and D15009, the Alexander von Humboldt Foundation of Germany, and the Innovation Fund Project for Graduate Student of Shanghai under Grant JWCXSL140
Discrimination of milks with a multisensor system based on layer-by-layer films
ProducciĂłn CientĂficaA nanostructured electrochemical bi-sensor system for the analysis of milks has been developed using the layer-by-layer technique. The non-enzymatic sensor [CHI+IL/CuPcS]2, is a layered material containing a negative film of the anionic sulfonated copper phthalocyanine (CuPcS) acting as electrocatalytic material, and a cationic layer containing a mixture of an ionic liquid (IL) (1-butyl-3-methylimidazolium tetrafluoroborate) that enhances the conductivity, and chitosan (CHI), that facilitates the enzyme immobilization. The biosensor ([CHI+IL/CuPcS]2-GAO) results from the immobilization of galactose oxidase on the top of the LbL layers. FTIR, UVâvis, and AFM have confirmed the proposed structure and cyclic voltammetry has demonstrated the amplification caused by the combination of materials in the film. Sensors have been combined to form an electronic tongue for milk analysis. Principal component analysis has revealed the ability of the sensor system to discriminate between milk samples with different lactose content. Using a PLS-1 calibration models, correlations have been found between the voltammetric signals and chemical parameters measured by classical methods. PLS-1 models provide excellent correlations with lactose content. Additional information about other components, such as fats, proteins, and acidity, can also be obtained. The method developed is simple, and the short response time permits its use in assaying milk samples online.Ministerio de EconomĂa, Industria y Competitividad - Fondo Europeo de Desarrollo Regional (project AGL2015-67482-R)Junta de Castilla y Leon - Fondo Europeo de Desarrollo Regional (project VA-011U16)Junta de Castilla y LeĂłn (grant BOCYL-D-4112015-9
High-resolution optical and SAR image fusion for building database updating
This paper addresses the issue of cartographic database (DB) creation or updating using high-resolution synthetic aperture radar and optical images. In cartographic applications, objects of interest are mainly buildings and roads. This paper proposes a processing chain to create or update building DBs. The approach is composed of two steps. First, if a DB is available, the presence of each DB object is checked in the images. Then, we verify if objects coming from an image segmentation should be included in the DB. To do those two steps, relevant features are extracted from images in the neighborhood of the considered object. The object removal/inclusion in the DB is based on a score obtained by the fusion of features in the framework of DempsterâShafer evidence theory
Monitoring the phenolic ripening of red grapes using a multisensor system based on metal-oxide nanoparticles
ProducciĂłn CientĂficaThe maturity of grapes is usually monitored by means of the sugar concentration.
However, the assessment of other parameters such as the phenolic content is also
important because the phenolic maturity has an important impact on the organoleptic
characteristics of wines. In this work, voltammetric sensors able to detect phenols
in red grapes have been developed. They are based on metal oxide nanoparticles
(CeO2, NiO, and TiO2,) whose excellent electrocatalytic properties toward phenols
allows obtaining sensors with detection limits in the range of 10â8 M and coefficients
of variation lower than 7%. An electronic tongue constructed using a combination of the
nanoparticle-based sensors is capable to monitor the phenolic maturity of red grapes
from véraison to maturity. Principal Component Analysis (PCA) can be successfully used
to discriminate samples according to the ripeness. Regression models performed using
Partial Least Squares (PLS-1) have established good correlations between voltammetric
data obtained with the electrochemical sensors and the Total Polyphenolic Index, the
Brix degree and the Total Acidity, with correlation coefficients close to 1 and low number
of latent variables. An advantage of this system is that the electronic tongue can be used
for the simultaneous assessment of these three parameters which are the main factors
used to monitor the maturity of grapes. Thus the electronic tongue based on metal oxide
nanoparticles can be a valuable tool to monitor ripeness. These results demonstrate
the exciting possible applications of metal oxide nanoparticles in the field of electronic
tongues.Ministerio de EconomĂa, Industria y Competitividad - Fondo Europeo de Desarrollo Regional (project AGL2015-67482- R)Junta de Castilla y Leon - Fondo Europeo de Desarrollo Regional (project VA011U16)Junta de Castilla y LeĂłn (grant BOCYL-D-24112015-9
Application of probabilistic PCR5 Fusion Rule for Multisensor Target Tracking
This paper defines and implements a non-Bayesian fusion rule for combining
densities of probabilities estimated by local (non-linear) filters for tracking
a moving target by passive sensors. This rule is the restriction to a strict
probabilistic paradigm of the recent and efficient Proportional Conflict
Redistribution rule no 5 (PCR5) developed in the DSmT framework for fusing
basic belief assignments. A sampling method for probabilistic PCR5 (p-PCR5) is
defined. It is shown that p-PCR5 is more robust to an erroneous modeling and
allows to keep the modes of local densities and preserve as much as possible
the whole information inherent to each densities to combine. In particular,
p-PCR5 is able of maintaining multiple hypotheses/modes after fusion, when the
hypotheses are too distant in regards to their deviations. This new p-PCR5 rule
has been tested on a simple example of distributed non-linear filtering
application to show the interest of such approach for future developments. The
non-linear distributed filter is implemented through a basic particles
filtering technique. The results obtained in our simulations show the ability
of this p-PCR5-based filter to track the target even when the models are not
well consistent in regards to the initialization and real cinematic
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