Chlorine evolution during the fusion of chlorofluoroindate glasses

Samples with a composition of 40InF 3-20ZnF 2-5MCl- xBaF 2-ySrF 2, where M=Na, Li and x+y=35 mol%, were prepared. The thermal properties related to the Ba/Sr ratio and to the remaining chlorine content in the glasses were studied. Thermal stability is improved with the addition of chlorine. However, chlorine concentration is regulated by the sublimation of indium fluorides which takes place at about 600°C. Indium fluorides arc formed during glass fusion. The mechanisms of chlorine sublimation were studied. © 2005 Akadémiai Kiadó, Budapest.

Inactivation of vesicular stomatitis virus through inhibition of membrane fusion by chemical modification of the viral glycoprotein

Membrane fusion is an essential step in the entry of enveloped viruses into their host cells triggered by conformational changes in viral glycoproteins. We have demonstrated previously that modification of vesicular stomatitis virus (VSV) with diethylpyrocarbonate (DEPC) abolished conformational changes on VSV glycoprotein and the fusion reaction catalyzed by the virus. In the present study, we evaluated whether treatment with DEPC was able to inactivate the virus. Infectivity and viral replication were abolished by viral treatment with 0.5 mM DEPC. Mortality profile and inflammatory response in the central nervous system indicated that G protein modification with DEPC eliminates the ability of the virus to cause disease. In addition, DEPC treatment did not alter the conformational integrity of surface proteins of inactivated VSV as demonstrated by transmission electron microscopy and competitive ELISA. Taken together, our results suggest a potential use of histidine (His) modification to the development of a new process of viral inactivation based on fusion inhibition. © 2006 Elsevier B.V. All rights reserved.

Fusion of fingerprint recognition methods for robust human identification

Biometrics is one of the biggest tendencies in human identification. The fingerprint is the most widely used biometric. However considering the automatic fingerprint recognition a completely solved problem is a common mistake. The most popular and extensively used methods, the minutiae-based, do not perform well on poor-quality images and when just a small area of overlap between the template and the query images exists. The use of multibiometrics is considered one of the keys to overcome the weakness and improve the accuracy of biometrics systems. This paper presents the fusion of a minutiae-based and a ridge-based fingerprint recognition method at rank, decision and score level. The fusion techniques implemented leaded to a reduction of the Equal Error Rate by 31.78% (from 4.09% to 2.79%) and a decreasing of 6 positions in the rank to reach a Correct Retrieval (from rank 8 to 2) when assessed in the FVC2002-DB1A database. © 2008 IEEE.

On data-centric misbehavior detection in VANETs

Detecting misbehavior (such as transmissions of false information) in vehicular ad hoc networks (VANETs) is a very important problem with wide range of implications, including safety related and congestion avoidance applications. We discuss several limitations of existing misbehavior detection schemes (MDS) designed for VANETs. Most MDS are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners, e.g. for gaining access to a particular lane. It is therefore more important to detect false information than to identify misbehaving nodes. We introduce the concept of data-centric misbehavior detection and propose algorithms which detect false alert messages and misbehaving nodes by observing their actions after sending out the alert messages. With the data-centric MDS, each node can decide whether an information received is correct or false. The decision is based on the consistency of recent messages and new alerts with reported and estimated vehicle positions. No voting or majority decisions is needed, making our MDS resilient to Sybil attacks. After misbehavior is detected, we do not revoke all the secret credentials of misbehaving nodes, as done in most schemes. Instead, we impose fines on misbehaving nodes (administered by the certification authority), discouraging them to act selfishly. This reduces the computation and communication costs involved in revoking all the secret credentials of misbehaving nodes. © 2011 IEEE.

An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

Local data fusion algorithm for fire detection through mobile robot

Multisensor data fusion is a technique that combines the readings of multiple sensors to detect some phenomenon. Data fusion applications are numerous and they can be used in smart buildings, environment monitoring, industry and defense applications. The main goal of multisensor data fusion is to minimize false alarms and maximize the probability of detection based on the detection of multiple sensors. In this paper a local data fusion algorithm based on luminosity, temperature and flame for fire detection is presented. The data fusion approach was embedded in a low cost mobile robot. The prototype test validation has indicated that our approach can detect fire occurrence. Moreover, the low cost project allow the development of robots that could be discarded in their fire detection missions. © 2013 IEEE.

Improving face recognition with multispectral fusion and support vector machines

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Search for invisible decays of Higgs bosons in the vector boson fusion and associated ZH production modes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)