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Eddy current testing is a kind of non-destructive testing (NDT) method based on the principle of electromagnetic induction. The probe is the key of eddy current non-destructive inspection and its design or combination of form will influence detectability. A complete set of eddy current testing system is designed for standard testing copper and defect copper. Under the same lift-off distance and the same high frequency excitation signal, designed three types of probe, which are single probe single coil, single probe double coil and double probe double coil, are used to carry out NDT experiment. Experimental results show that sensitivity and resolution of detection system are obvious difference among the different form of eddy current sensor probe. Probe shape and coil winding are improved according to the experimental results. Corresponding improved probe is adopted to carry out NDT experiment at the same condition. Experimental results show that detectability is enhanced significantly. [ABSTRACT FROM AUTHOR]

Enhancing competitiveness, shortening the response time to environmental changes, increasing profits and so forth are all goals that refer to the same concept: `improvement΄. Yet, these elements are bounded to the same necessity: `measurement΄. On such bases, this work intends to provide an operative framework which, using many heterogeneous typologies of tools and technologies, would enable enterprises to define, formalize and model key performance indicators (KPIs) according to Model Driven Architecture (MDA) vision. The tools required for achieving this goal belong to different categories, according to the particular step of the framework: the theories for identification of KPIs are the balanced scorecard (BSc) and the goal question metric (GQM); process modeling is realized trough BPMN (Business Process Modeling Notation); KPIs were modeled using semantics of business vocabulary and business rules (SBVR), so as to enable automatic parsing, according to MDA vision. Finally, the mathematical formulas were represented in machine readable format through MathML. [ABSTRACT FROM AUTHOR]

The discipline of hematopathology traditionally relies upon morphologic evaluation, cytochemical stains, immunohistochemistry, flow cytometry, and karyotypic analysis to classify hematolymphoid neoplasms. Although these time-honored methods still comprise the primary diagnostic arsenal of the pathologist, the last few decades have borne witness to the widespread acceptance of molecular techniques to classify these neoplasms. No longer considered ancillary, molecular analyses have led to a greater understanding of the biological and clinical heterogeneity of hematolymphoid neoplasms, and now form the primary diagnostic criteria for many diagnoses as set forth by the World Health Organization [1]. They also provide extremely sensitive and specific methods for prognostic marker detection and minimal residual disease monitoring. These techniques have evolved rapidly over the last decade from Southern blot and hybridization assays to polymerase chain reaction and its variants to gene expression profiling and single-nucleotide polymorphism analysis, and more recently to microarray technology and whole-genome analysis. Despite technological advancements, molecular techniques are critically dependent upon the nature of nucleic acids retrieved from the specimen. Results cannot be correctly interpreted if the quantity and/or the integrity of nucleic acids are not optimal for the desired molecular application. As such, the purpose of this chapter is twofold. First, issues pertaining to specimen collection, handling and processing, and nucleic acid extraction, stability, and storage are reviewed. Second, molecular techniques commonly utilized in hematopathology are reviewed. Cytogenetics, fluorescent in situ hybridization (FISH), and microarray techniques are discussed in Chapter 2. [ABSTRACT FROM AUTHOR]

For fault Diagnosis in internet service, the detection and localization of high-level failure is very important and a real big challenge. The diagnose methods that passively collect information have two drawbacks: 1) requiring the target system to report its inner message; 2) it΄s impossible to detect and locate faults before user senses them. This paper proposes an active diagnose method which test internet service with probes and make fault inferences based on the probe results. Probing method is proactive and adaptive with low cost. We evaluate it through applying it to a J2EE application ˵Pet Store″, compare it with a current passive method Pinpoint, and show that our method outperforms Pinpoint. [ABSTRACT FROM AUTHOR]