Revendo os códigos hamming e CRC para tratar com erros na transmissão de dados

This article has the purpose to review the main codes used to detect and correct errors in data communication specifically in the computer's network. The Hamming's code and the Ciclic Redundancy Code (CRC) are presented as the focus of this article as well as CRC hardware implementation. Each code is reviewed in details in order to fill the gaps in the literature and to make it accessible to the computer science and engineering students as well as to anyone who may be interested in learning the technique to treat error in data communication.

Search for the flavor-changing neutral current decay Bs 0 → μ+ μ- pp̄ Collisions at √s = 1.96 TeV with the DO Detector

We present the results of a search for the flavor-changing neutral current decay Bs 0 → μ+ μ-. using a data set with integrated luminosity of 240 pb-1 of pp̄ collisions at √s = 1.96 TeV collected with the D0 detector in run II of the Fermilab Tevatron collider. We find the upper limit on the branching fraction to be B(Bs 0 → μ+ π-) ≤ 5.0 × 10-7 at the 95% C.L. assuming no contributions from the decay Bd 0 → μ+ μ- in the signal region. This limit is the most stringent upper bound on the branching fraction Bs 0 → μ+ μ- to date. © 2005 The American Physical Society.

Safety illusion and error trap in a collectively-operated machine accident

Workplace accidents involving machines are relevant for their magnitude and their impacts on worker health. Despite consolidated critical statements, explanation centered on errors of operators remains predominant with industry professionals, hampering preventive measures and the improvement of production-system reliability. Several initiatives were adopted by enforcement agencies in partnership with universities to stimulate production and diffusion of analysis methodologies with a systemic approach. Starting from one accident case that occurred with a worker who operated a brake-clutch type mechanical press, the article explores cognitive aspects and the existence of traps in the operation of this machine. It deals with a large-sized press that, despite being endowed with a light curtain in areas of access to the pressing zone, did not meet legal requirements. The safety devices gave rise to an illusion of safety, permitting activation of the machine when a worker was still found within the operational zone. Preventive interventions must stimulate the tailoring of systems to the characteristics of workers, minimizing the creation of traps and encouraging safety policies and practices that replace judgments of behaviors that participate in accidents by analyses of reasons that lead workers to act in that manner.

High sensitivity fiber optic angular displacement sensor and its application for detection of ultrasound

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

PCR detection of staphylococcal enterotoxin genes in Staphylococcus aureus strains isolated from raw and pasteurized milk

Milk is considered a nutritious food because it contains several important nutrients including proteins and vitamins. Conversely, it can be a vehicle for several pathogenic bacteria such as Staphylococcus aureus. This study aimed to analyze the frequency of genes encoding the staphylococcal enterotoxins (SEs) SEA, SEB, SEC, SED, SEE, SEG, SEH, SEI and SEJ in S. aureus strains isolated from raw or pasteurized bovine milk. S. aureus was found in 38 (70.4%) out of 54 raw milk samples at concentrations of up to 8.9 X 10(5) CFU/ml. This microorganism was present in eight samples of pasteurized milk before the expiration date and in 11 samples analyzed on the expiration date. of the 57 strains studied, 68.4% were positive for one or more genes encoding the enterotoxins, and 12 different genotypes were identified. The gene coding for enterotoxin A, sea, was the most frequent ( 16 strains, 41%), followed by sec (8 strains, 20.5%), sed (5 strains, 12.8%). seb (3 strains. 7.7%) and see (2 strains, 5.1%). Among the genes encoding the other enterotoxins, seg was the most frequently observed (11 strains. 28.2%), followed by sei (10 strains) and seh and sej (3 strains each). With the recent identification of new SEs, the perceived frequency of enterotoxigenic strains has increased. suggesting that the pathogenic potential of staphylococci may be higher than previously thoughts however, further studies are required to assess the expression of these new SEs by S. aureus. and their impact in foodborne disease. The quality of Brazilian milk is still low. and efforts from the government and the entire productive chain are required to attain consumer safety. (C) 2008 Elsevier B.V. All rights reserved.

Double-Tagging Polymerase Chain Reaction with a Thiolated Primer and Electrochemical Genosensing based on Gold Nanocomposite Sensor for Food Safety

A novel material for electrochemical biosensing based on rigid conducting gold nanocomposite (nano-AuGEC) is presented. Islands of chemisorbing material (gold nanoparticles) surrounded by nonreactive, rigid, and conducting graphite epoxy composite are thus achieved to avoid the stringent control of surface coverage parameters required during immobilization of thiolated oligos in continuous gold surfaces. The spatial resolution of the immobilized thiolated DNA was easily controlled by merely varying the percentage of gold nanoparticles in the composition of the composite. As low as 9 fmol (60 pM) of synthetic DNA were detected in hybridization experiments when using a thiolated probe. Moreover, for the first time a double tagging PCR strategy was performed with a thiolated primer for the detection of Salmonella sp., one of the most important foodborne pathogens affecting food safety. Ibis assay was performed by double-labeling the amplicon during the PCR with a -DIG and -SH set of labeled primers. The thiolated end allows the immobilization of the amplicon on the nano-AuGEC electrode, while digoxigenin allows the electrochemical detection with the antiDIG-HRP reporter in the femtomole range. Rigid conducting gold nanocomposite represents a good material for the improved and oriented immobilization of biomolecules with excellent transducing properties for the construction of a wide range of electrochemical biosensors such as immunosensors, genosensors, and enzymosensors.

Screening and confirmation of PAHs in vegetable oil samples by use of supercritical fluid extraction in conjunction with liquid chromatography and fluorimetric detection

A fast, simple, non-destructive method for the direct screening of polycyclic aromatic hydrocarbons (PAHs) in vegetable oil samples is proposed. The method uses a supercritical fluid extraction (SFE) system coupled on-line with a fluorimetric detector to determine PAHs. This special assembly avoids the main problems encountered in the determination of PAHs in complex matrices such as vegetable oils. PAHs are selectively extracted by using silica gel in the thimble and cleaned up by passage through a C18 column. Interferences are preferentially retained by the silica gel during the SFE process while PAHs are adsorbed in the C18 column and the remainder of the matrix is sent to waste. Finally, the C18 column is purged to remove residual CO2 gas and adsorbed PAHs are recovered by desorption with a solvent. The extracts from positive samples are subsequently analyzed by liquid chromatography (LC) with fluorescence detection. The proposed method allows the confirmation of vegetable oil safety and hence provides a new tool for consumer protection. (C) 2004 Elsevier B.V. All rights reserved.

Use of the Normalized Absorbance Ratio as an Internal Standardization Approach To Minimize Measurement Error in Enzyme-Linked Immunosorbent Assays for Diagnosis of Human Papillomavirus Infection

The serological detection of antibodies against human papillomavirus (HPV) antigens is a useful tool to determine exposure to genital HPV infection and in predicting the risk of infection persistence and associated lesions. Enzyme-linked immunosorbent assays (ELISAs) are commonly used for seroepidemiological studies of HPV infection but are not standardized. Intra-and interassay performance variation is difficult to control, especially in cohort studies that require the testing of specimens over extended periods. We propose the use of normalized absorbance ratios (NARs) as a standardization procedure to control for such variations and minimize measurement error. We compared NAR and ELISA optical density (OD) values for the strength of the correlation between serological results for paired visits 4 months apart and HPV-16 DNA positivity in cervical specimens from a cohort investigation of 2,048 women tested with an ELISA using HPV-16 virus-like particles. NARs were calculated by dividing the mean blank-subtracted (net) ODs by the equivalent values of a control serum pool included in the same plate in triplicate, using different dilutions. Stronger correlations were observed with NAR values than with net ODs at every dilution, with an overall reduction in nonexplained regression variability of 39%. Using logistic regression, the ranges of odds ratios of HPV-16 DNA positivity contrasting upper and lower quintiles at different dilutions and their averages were 4.73 to 5.47 for NARs and 2.78 to 3.28 for net ODs, with corresponding significant improvements in seroreactivity-risk trends across quintiles when NARs were used. The NAR standardization is a simple procedure to reduce measurement error in seroepidemiological studies of HPV infection.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

Bio-safety technology in production of bovine herpesvirus type 5 (BoHV-5) using an alternative serum-free medium

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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.

Fuzzy community structure detection by particle competition and cooperation

Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

Damage detection in nonlinear structures using discrete-time volterra series

Structural damage identification is basically a nonlinear phenomenon; however, nonlinear procedures are not used currently in practical applications due to the complexity and difficulty for implementation of such techniques. Therefore, the development of techniques that consider the nonlinear behavior of structures for damage detection is a research of major importance since nonlinear dynamical effects can be erroneously treated as damage in the structure by classical metrics. This paper proposes the discrete-time Volterra series for modeling the nonlinear convolution between the input and output signals in a benchmark nonlinear system. The prediction error of the model in an unknown structural condition is compared with the values of the reference structure in healthy condition for evaluating the method of damage detection. Since the Volterra series separate the response of the system in linear and nonlinear contributions, these indexes are used to show the importance of considering the nonlinear behavior of the structure. The paper concludes pointing out the main advantages and drawbacks of this damage detection methodology. © (2013) Trans Tech Publications.

Convergence Property of the Measurement Gross Error Correction in Power System State Estimation, Using Geometrical Background

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Flavonoid Detection in Hydroethanolic Extract of Pouteria torta (Sapotaceae) Leaves by HPLC-DAD and the Determination of Its Mutagenic Activity

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)