2 resultados para detection probability

em Instituto Politécnico do Porto, Portugal


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In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

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Prostate Specific Antigen (PSA) is the biomarker of choice for screening prostate cancer throughout the population, with PSA values above 10 ng/mL pointing out a high probability of associated cancer1. According to the most recent World Health Organization (WHO) data, prostate cancer is the commonest form of cancer in men in Europe2. Early detection of prostate cancer is thus very important and is currently made by screening PSA in men over 45 years old, combined with other alterations in serum and urine parameters. PSA is a glycoprotein with a molecular mass of approximately 32 kDa consisting of one polypeptide chain, which is produced by the secretory epithelium of human prostate. Currently, the standard methods available for PSA screening are immunoassays like Enzyme-Linked Immunoabsorbent Assay (ELISA). These methods are highly sensitive and specific for the detection of PSA, but they require expensive laboratory facilities and high qualify personal resources. Other highly sensitive and specific methods for the detection of PSA have also become available and are in its majority immunobiosensors1,3-5, relying on antibodies. Less expensive methods producing quicker responses are thus needed, which may be achieved by synthesizing artificial antibodies by means of molecular imprinting techniques. These should also be coupled to simple and low cost devices, such as those of the potentiometric kind, one approach that has been proven successful6. Potentiometric sensors offer the advantage of selectivity and portability for use in point-of-care and have been widely recognized as potential analytical tools in this field. The inherent method is simple, precise, accurate and inexpensive regarding reagent consumption and equipment involved. Thus, this work proposes a new plastic antibody for PSA, designed over the surface of graphene layers extracted from graphite. Charged monomers were used to enable an oriented tailoring of the PSA rebinding sites. Uncharged monomers were used as control. These materials were used as ionophores in conventional solid-contact graphite electrodes. The obtained results showed that the imprinted materials displayed a selective response to PSA. The electrodes with charged monomers showed a more stable and sensitive response, with an average slope of -44.2 mV/decade and a detection limit of 5.8X10-11 mol/L (2 ng/mL). The corresponding non-imprinted sensors showed smaller sensitivity, with average slopes of -24.8 mV/decade. The best sensors were successfully applied to the analysis of serum samples, with percentage recoveries of 106.5% and relatives errors of 6.5%.