Strategy to detect ground control in digital images

The identification of ground control on photographs or images is usually carried out by a human operator, who uses his natural skills to make interpretations. In Digital Photogrammetry, which uses techniques of digital image processing extraction of ground control can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features of object space and its homologous in the image space. A build-in self-diagnosis is also used in this method. It is based on implementation of data snooping statistic test in the process of spatial resection using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.

Validation of an immunohistochemistry assay to detect turkey coronavirus: A rapid and simple screening tool for limited resource settings

The objective of the present study was to develop and apply the direct immunohistochemistry (D-IHC) assay to search for turkey coronavirus (TCoV) antigens in formalin-fixed embedded-paraffin tissues by the use of biotin-labeled polyclonal antibody. Twenty-eight-day-old embryonated turkey eggs (n = 50) were inoculated with TCoV-purified virus, and 3 d after inoculation, sections from ileum, ileum-cecal junction, and ceca were harvested, fixed in neutral formalin, and embedded in paraffin blocks and used as positive control. In addition, a total of 100 field samples from ileum, ileum-cecal junction, and ceca, collected from 30 to 45-d-old turkeys poults experiencing an outbreak of acute enteritis, were used to search for TCoV by the same D-IHC. All results were compared with those obtained by conventional RT-PCR and indirect fluorescent antibody assay (IFA) for all tested samples. Turkey coronavirus was detected in experimentally infected embryo tissues and also in field samples in 100% of ileum-cecal junction and ceca by the 3 detection procedures. With IFA as a reference assay, sensitivity and specificity of D-IHC were 98 and 58%, whereas sensitivity and specificity of reverse transcription-PCR were 96 and 66%, calculated from the total of tested samples from experimental infection. Each of the examined procedures was highly specific (D-IHC, 93%; RT-PCR, 90%), sensitive (D-IHC, 85%; RT-PCR, 86%), and agreement of both D-IHC and RT-PCR was 99 and 100%, respectively, compared with IFA results obtained from all the field samples. These findings demonstrated the utility of D-IHC for direct detection of TCoV from field samples and considering the sensitivity and specificity found here, can be used as an alternative technique.

Using the Euclidean Distance as a Mechanism Distance between Signatures to the Detect Spam and Phishing Scams

Spams and Phishing Scams are some of the abuse forms on the Internet that have grown up now. These abuses influence in user's routine of electronic mail and in the infrastructure of Internet communication. So, this paper proposes a new model messages filter based in Euclidian distance, beyond show the containment's methodologies currently more used. A new model messages filter, based in frequency's distribution of character present in your content and in signature generation is described. An architecture to combat Phishing Scam and spam is proposed in order to contribute to the containment of attempted fraud by mail.

Near-infrared Raman spectroscopy to detect anti-Toxoplasma gondii antibody in blood sera of domestic cats: quantitative analysis based on partial least-squares multivariate statistics

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

Determination and statistical treatment of short-circuit currents for faults on the lines of networks of 440 kV CESP system

The distribution of short-circuit current is investigated by means of two methods, one direct and the other analytic; both methods consider uniform probability distribution of line faults. In the direct method, the procedure consists of calculating fault currents at equidistant points along the line, starting from one of the end points and considering the other end open. The magnitude of the current is classified according to Brazilian standards (regulation NBR-7118). The analytic method assumes that the distribution of short-circuit currents through the busbar and the distribution of the line length connected to it are known, as well as the independence of values. The method is designed to determine the probability that fault currents through a line will surpass the pre-established magnitude, thus generating frequency distribution curves of short-circuit currents along the lines.

Investigating effects of neutral wire and grounding in distribution systems with faults

In some applications like fault analysis, fault location, power quality studies, safety analysis, loss analysis, etc., knowing the neutral wire and ground currents and voltages could be of particular interest. In order to investigate effects of neutrals and system grounding on the operation of the distribution feeders with faults, in this research a hybrid short circuit algorithm is generalized. In this novel use of the technique, the neutral wire and assumed ground conductor are explicitly represented. Results obtained from several case studies using IEEE 34-node test network are presented and discussed.

Location of single line-to-ground faults on distribution feeders using voltage measurements

This paper proposes a dedicated algorithm for lation of single line-to-ground faults in distribution systems. The proposed algorithm uses voltage and current phasors measured at the substation level, voltage magnitudes measured at some buses of the feeder, a database containing electrical, operational and topological parameters of the distribution networks, and fault simulation. Voltage measurements can be obtained using power quality devices already installed on the feeders or using voltage measurement devices dedicated for fault location. Using the proposed algorithm, likely faulted points that are located on feeder laterals geographically far from the actual faulted point are excluded from the results. Assessment of the algorithm efficiency was carried out using a 238 buses real-life distribution feeder. The results show that the proposed algorithm is robust for performing fast and efficient fault location for sustained single line-to-ground faults requiring less than 5% of the feeder buses to be covered by voltage measurement devices. © 2006 IEEE.

Immunohistochemistry assay to detect Turkey coronavirus (TCoV) from experimentally infected poults

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

An effective wavelet method to detect and mitigate low-frequency multipath effects

To ensure high accuracy results from GPS relative positioning, the multipath effects have to be mitigated. Although the careful selection of antenna site and the use of especial antennas and receivers can minimize multipath, it cannot always be eliminated and frequently the residual multipath disturbance remains as the major error in GPS results. The high-frequency multipath from large delays can be attenuated by double difference (DD) denoising methods. But the low-frequency multipath from short delays is very difficult to be reduced or modeled. In this paper, it is proposed a method based on wavelet regression (WR), which can effectively detect and reduce the low-frequency multipath. The wavelet technique is firstly applied to decompose the DD residuals into the low-frequency bias and high-frequency noise components. The extracted bias components by WR are then directly applied to the DD observations to correct them from the trend. The remaining terms, largely characterized by the high-frequency measurement noise, are expected to give the best linear unbiased solutions from a least-squares (LS) adjustment. An experiment was carried out using objects placed close to the receiver antenna to cause, mainly, low-frequency multipath. The data were collected for two days to verify the multipath repeatability. The ground truth coordinates were computed with data collected in the absence of the reflector objects. The coordinates and ambiguity solution were compared with and without the multipath mitigation using WR. After mitigating the multipath, ambiguity resolution became more reliable and the coordinates were more accurate.

Stacking faults in SiCf/SiC composite obtained by chemical vapor reaction process

SiC fiber-reinforced SiC matrix composite (SiCf/SiC) is one of the leading candidates in ceramic materials for engineering applications due to its unique combination of properties such as high thermal conductivity, high resistance to corrosion and working conditions. Fiber-reinforced composites are materials which exhibit a significant improvement in properties like ductility in comparison to the monolithic SiC ceramic. The SiCf/SiC composite was obtained from a C/C composite precursor using convertion reaction under high temperature and controlled atmosphere. In this work, SiC phase presented the stacking faults in the structure, being not possible to calculate the unit cell size, symmetry and bond lengths but it seem equal card number 29-1129 of JCPDS.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

Effect of drying on the reproducibility of DIAGNOdent to detect caries-like lesions

The aim of this study was to verify the drying effect on the reproducibility of DIAGNOdent (Dd) devices to detect caries-like lesions. Three areas were created in each of the 34 bovine incisors: sound (S), demineralized (DE) and remineralized (RE). One examiner measured each area with two Dd devices (denominated X and Y), twice under humid, and twice under dry condition. Intra-rater agreement according each device and inter-device agreement were estimated by kappa statistics (κ). Intra-rater agreement for device Y was substantial under humid (κ DE=0.68 and κ RE+S=0.68) and dry condition (κ DE=0.64 and κ RE+S=0.67). For device X, it was substantial under humid condition (κ DE=0.57 and κ RE+S=0.49), and it was almost perfect after air drying (κ DE=1.0 and κRE+S=1.0). Inter-device agreement was slight (κ =0.17) under humid condition, and it was substantial under dry condition (κ =0.62). As reproducibility increased under dry condition, drying is advised to detect caries-like lesions on free smooth surfaces when different devices are used.