Change detection using the generalized likelihood ratio method to improve the sensitivity of guided wave structural health monitoring systems

The transition from one-off ultrasound–based non-destructive testing systems to permanently installed monitoring techniques has the potential to significantly improve the defect detection sensitivity, since frequent measurements can be obtained and tracked with time. However, the measurements must be compensated for changing environmental and operational conditions, such as temperature, and careful analysis of measurements by highly skilled operators quickly becomes unfeasible as a large number of sensors acquiring signals frequently is installed on a plant. Recently, the authors have developed a location-specific temperature compensation method that uses a set of baseline measurements to remove temperature effects from the signals, thus producing “residual” signals on an unchanged structure that are essentially normally distributed with zero-mean and with standard deviation related to instrumentation noise. This enables the application of change detection techniques such as the generalized likelihood ratio method that can process sequences of residual signals searching for changes caused by damage. The defect detection performance offered by the generalized likelihood ratio when applied to guided wave signals adjusted either via the newly developed location-specific temperature compensation method or the widely used optimal baseline selection technique is investigated on a set of simulated measurements based on a set of experimental signals acquired by a permanently installed pipe monitoring system designed to monitor tens of meters of pipe from one location using the torsional, T(0,1), guided wave mode. The results presented here indicate that damage on the order of 0.1% cross section loss can reliably be detected with virtually zero false calls if the assumptions of the study are met, notably the absence of sensor drift with time. This represents a factor of 20–50 improvement over that typically achieved in one-off inspection and makes such monitoring systems very attractive. The method will also be applicable to bulk wave ultrasound signals.

Analysis of Voice Changes in Anti Forensic Activities Case Study: Voice Changer with Telephone Effect

Voice recordings can be changed in various ways, either intentionally or unintentionally, one of which is by using a voice changer. Reference voice recordings and suspect voice recordings will be more difficult to analyze if suspect voice recordings are changed using a voice changer application under certain effects such as telephone effect. Voice Changer can be one form of activity that can be carried out by anti-forensics, making it difficult for investigators to investigate if the voice recording is changed with telephone effect. This study has two types of recordings, namely the reference voice recording (unknown sample) and suspect voice recording (known sample) that has been changed using a voice changer application with telephone effect. Investigations were carried out based on data results extraction and analysis using pitch, formant, and spectrogram using the Analysis of variance (ANOVA) method and the likelihood ratio method. The results of this study indicate that the application of voice changer can be one form of activity that can be carried out by anti-forensics so that it can be difficult for investigators to conduct investigations on sound recording evidence. This research may help forensic communities, especially investigators to conduct investigations on sound recording.

The XXL Survey

We study the space density evolution of active galactic nuclei (AGN) using the 610 MHz radio survey of the XXL-North field, performed with the Giant Metrewave Radio Telescope. The survey covers an area of 30.4 deg2, with a beamsize of 6.5 arcsec. The survey is divided into two parts, one covering an area of 11.9 deg2 with 1σ rms noise of 200 μJy beam−1 and the other spanning 18.5 deg2 with rms noise of 45 μJy beam−1. We extracted the catalog of radio components above 7σ. The catalog was cross-matched with a multi-wavelength catalog of the XXL-North field (covering about 80% of the radio XXL-North field) using a likelihood ratio method, which determines the counterparts based on their positions and their optical properties. The multi-component sources were matched visually with the aid of a computer code: Multi-Catalog Visual Cross-Matching. A flux density cut above 1 mJy selects AGN hosts with a high purity in terms of star formation contamination based on the available source counts. After cross-matching and elimination of observational biases arising from survey incompletenesses, the number of remaining sources was 1150. We constructed the rest-frame 1.4 GHz radio luminosity functions of these sources using the maximum volume method. This survey allows us to probe luminosities of 23 ≲ log(L1.4 GHz[W Hz−1]) ≲ 28 up to redshifts of z ≈ 2.1. Our results are consistent with the results from the literature in which AGN are comprised of two differently evolving populations, where the high luminosity end of the luminosity functions evolves more strongly than the low-luminosity end.

On Double Value at Risk

Value at Risk (VaR) is used to illustrate the maximum potential loss under a given confidence level, and is just a single indicator to evaluate risk ignoring any information about income. The present paper will generalize one-dimensional VaR to two-dimensional VaR with income-risk double indicators. We first construct a double-VaR with ( μ , σ 2 ) (or ( μ , V a R 2 ) ) indicators, and deduce the joint confidence region of ( μ , σ 2 ) (or ( μ , V a R 2 ) ) by virtue of the two-dimensional likelihood ratio method. Finally, an example to cover the empirical analysis of two double-VaR models is stated.

The LOFAR Two-metre Sky Survey

The LOFAR Two-metre Sky Survey (LoTSS) is an ongoing sensitive, high-resolution 120–168 MHz survey of the northern sky with diverse and ambitious science goals. Many of the scientific objectives of LoTSS rely upon, or are enhanced by, the association or separation of the sometimes incorrectly catalogued radio components into distinct radio sources and the identification and characterisation of the optical counterparts to these sources. We present the source associations and optical and/or IR identifications for sources in the first data release, which are made using a combination of statistical techniques and visual association and identification. We document in detail the colour- and magnitude-dependent likelihood ratio method used for statistical identification as well as the Zooniverse project, called LOFAR Galaxy Zoo, used for visual classification. We describe the process used to select which of these two different methods is most appropriate for each LoTSS source. The final LoTSS-DR1-IDs value-added catalogue presented contains 318 520 radio sources, of which 231 716 (73%) have optical and/or IR identifications in Pan-STARRS and WISE.