Image-Based Concrete Crack Detection Method Using the Median Absolute Deviation.

This paper proposes an innovative approach for detecting and quantifying concrete cracks using an adaptive threshold method based on Median Absolute Deviation (MAD) in images. The technique applies limited pre-processing steps and then dynamically determines a threshold adapted for each sub-image depending on the greyscale distribution of the pixels, resulting in tailored crack segmentation. The edges of the crack are obtained using the Laplace edge detection method, and the width of the crack is obtained for each centreline point. The method's performance is measured using the Probability of Detection (POD) curves as a function of the actual crack size, revealing remarkable capabilities. It was found that the proposed method could detect cracks as narrow as 0.1 mm, with a probability of 94% and 100% for cracks with larger widths. It was also found that the method has higher accuracy, precision, and F2 score values than the Otsu and Niblack methods.

Performance Analysis of Centralized Cooperative Schemes for Compressed Sensing.

This paper presents a performance analysis of centralized spectrum sensing based on compressed measurements. We assume cooperative sensing, where unlicensed users individually perform compressed sensing and send their results to a fusion center, which makes the final decision about the presence or absence of a licensed user signal. Several cooperation schemes are considered, such as and-rule, or-rule, majority voting, soft equal-gain combining (EGC). The proposed analysis provides simplified closed-form expressions that calculate the required number of sensors, the required number of samples, the required compression ratio, and the required signal-to-noise ratio (SNR) as a function of the probability of detection and the probability of the false alarm of the fusion center and of the sensors. The resulting expressions are derived by exploiting some accurate approximations of the test statistics of the fusion center and of the sensors, equipped with energy detectors. The obtained results are useful, especially for a low number of sensors and low sample sizes, where conventional closed-form expressions based on the central limit theorem (CLT) fail to provide accurate approximations. The proposed analysis also allows the self-computation of the performance of each sensor and of the fusion center with reduced complexity.

Estimation of the performance of two real-time polymerase chain reaction assays for detection of Staphylococcus aureus, Streptococcus agalactiae, and Streptococcus dysgalactiae in pooled milk samples in a field study.

The early detection of major mastitis pathogens is crucial for the udder health management of dairy herds. Testing of pooled milk samples, either individual test-day cow samples (TDCS) or aseptically collected pre-milk quarter samples (PMQS) may provide an easy to use and cost-effective group level screening tool. Therefore, the aim of this study was (1) to evaluate the sensitivity (Se) and specificity (Sp) of 2 commercial multiplex real-time PCR test kits applied to pooled milk samples using a Bayesian latent class analysis and (2) to estimate the probability of detection in relation to the pool size and the number of cows positively tested by bacteriological culture (BC) within a pool. Pools of 10, 20 and 50 cows were assembled from 1,912 test-day samples and 7,336 PMQS collected from a total of 2,045 cows from 2 commercial dairy farms. Two commercial quantitative real-time PCR kits were applied to detect Staphylococcus aureus, Streptococcus agalactiae, and Streptococcus dysgalactiae in the pooled samples, and a BC was applied to PMQS yielding a cumulative pool result. A pool was considered BC-positive if it contained at least one BC-positive PMQS. Pathogens were more frequently detected in the PMQS pools than in the TDCS pools. Pools of 10 cows showed the highest probability of detection irrespective of sample type or type of PCR kit compared with larger pool sizes. Estimation with a Bayesian latent class analysis resulted in a median Se in PMQS pools of 10 cows for Staph. aureus of 63.3% for PCR kit I, 78.1% for PCR kit II, and 95.5% for BC; the Sp values were 97.0%, 97.6%, and 89.1%, respectively. The estimated median Se for Strep. species for PCR kits ranged between 77.5 and 85.6% and for BC between 73.7% and 79.2%; the median Sp values ranged between 93.6 and 99.2% for PCR kits, and between 96.9% and 97.4% for BC. In addition, the probability of detection increased with an increasing number of BC-positive cows per pool. To achieve a probability of detection of 90%, the estimated number of positive cows in PMQS pools of 10 cows for kit I was 4.1 for Staph. aureus, 1.5 for Strep. agalactiae, and 1.3 for Strep. dysgalactiae; for the equivalent TDCS pools and pathogens, 6.9, 1.9, and 2.0 positive cows were required, respectively. For Kit II and PMQS pools, the number of positive cows required was 2.8 for Staph. aureus, 1.4 for Strep. agalactiae, and 1.2 for Strep. dysgalactiae; for the equivalent TDCS pools and pathogens, 5.3, 1.8, and 2.0 positive cows were required, respectively. In conclusion, the type of samples used for pooling, the pool size and the number of infected cows per pool determine the probability of detecting an infection with major mastitis pathogens within a pool by PCR testing.

A Model-Assisted Probability of Detection Framework for Optical Fiber Sensors.

Optical fiber sensors (OFSs) represent an efficient sensing solution in various structural health monitoring (SHM) applications. However, a well-defined methodology is still missing to quantify their damage detection performance, preventing their certification and full deployment in SHM. In a recent study, the authors proposed an experimental methodology to qualify distributed OFSs using the concept of probability of detection (POD). Nevertheless, POD curves require considerable testing, which is often not feasible. This study takes a step forward, presenting a model-assisted POD (MAPOD) approach for the first time applied to distributed OFSs (DOFSs). The new MAPOD framework applied to DOFSs is validated through previous experimental results, considering the mode I delamination monitoring of a double-cantilever beam (DCB) specimen under quasi-static loading conditions. The results show how strain transfer, loading conditions, human factors, interrogator resolution, and noise can alter the damage detection capabilities of DOFSs. This MAPOD approach represents a tool to study the effects of varying environmental and operational conditions on SHM systems based on DOFSs and for the design optimization of the monitoring system.

Disguised Full-Duplex Covert Communications.

Covert communications have arisen as an effective communications security measure that overcomes some of the limitations of cryptography and physical layer security. The main objective is to completely conceal from external devices the very existence of the link for exchanging confidential messages. In this paper, we take a step further and consider a scenario in which a covert communications node disguises itself as another functional entity for even more covertness. To be specific, we study a system where a source node communicates with a seemingly receive-only destination node which, in fact, is full-duplex (FD) and covertly delivers critical messages to another hidden receiver while evading the surveillance. Our aim is to identify the achievable covert rate at the hidden receiver by optimizing the public data rate and the transmit power of the FD destination node subject to the worst-case detection error probability (DEP) of the warden. Closed-form solutions are provided, and we investigate the effects of various system parameters on the covert rate through numerical results, one of which reveals that applying more (less) destination transmit power achieves a higher covert rate when the source transmit power is low (high). Since our work provides a performance guideline from the information-theoretic point of view, we conclude this paper with a discussion on possible future research such as analyses with practical modulations and imperfect channel state information.

Gaussian-Distributed Spread-Spectrum for Covert Communications.

Covert communication techniques play a crucial role in military and commercial applications to maintain the privacy and security of wireless transmissions from prying eyes. These techniques ensure that adversaries cannot detect or exploit the existence of such transmissions. Covert communications, also known as low probability of detection (LPD) communication, are instrumental in preventing attacks such as eavesdropping, jamming, or interference that could compromise the confidentiality, integrity, and availability of wireless communication. Direct-sequence spread-spectrum (DSSS) is a widely used covert communication scheme that expands the bandwidth to mitigate interference and hostile detection effects, reducing the signal power spectral density (PSD) to a low level. However, DSSS signals possess cyclostationary random properties that an adversary can exploit using cyclic spectral analysis to extract useful features from the transmitted signal. These features can then be used to detect and analyse the signal, making it more susceptible to electronic attacks such as jamming. To overcome this problem, a method to randomise the transmitted signal and reduce its cyclic features is proposed in this paper. This method produces a signal with a probability density function (PDF) similar to thermal noise, which masks the signal constellation to appear as thermal white noise to unintended receivers. This proposed scheme, called Gaussian distributed spread-spectrum (GDSS), is designed such that the receiver does not need to know any information about the thermal white noise used to mask the transmit signal to recover the message. The paper presents the details of the proposed scheme and investigates its performance in comparison to the standard DSSS system. This study used three detectors, namely, a high-order moments based detector, a modulation stripping detector, and a spectral correlation detector, to evaluate the detectability of the proposed scheme. The detectors were applied to noisy signals, and the results revealed that the moment-based detector failed to detect the GDSS signal with a spreading factor, N = 256 at all signal-to-noise ratios (SNRs), whereas it could detect the DSSS signals up to an SNR of -12 dB. The results obtained using the modulation stripping detector showed no significant phase distribution convergence for the GDSS signals, similar to the noise-only case, whereas the DSSS signals generated a phase distribution with a distinct shape, indicating the presence of a valid signal. Additionally, the spectral correlation detector applied to the GDSS signal at an SNR of -12 dB showed no identifiable peaks on the spectrum, providing further evidence of the effectiveness of the GDSS scheme and making it a favourable choice for covert communication applications. A semi-analytical calculation of the bit error rate is also presented for the uncoded system. The investigation results show that the GDSS scheme can generate a noise-like signal with reduced identifiable features, making it a superior solution for covert communication. However, achieving this comes at a cost of approximately 2 dB on the signal-to-noise ratio.

Performance Comparison of Relay-Based Covert Communications: DF, CF and AF.

In this paper, we investigate the performance of covert communications in different types of a relay system: decode-and-forward (DF), compress-and-forward (CF) and amplify-and-forward (AF). We consider a source node that attempts to send both public and covert messages to a destination node through a relay on which a covert message detector is embedded. By taking the minimum detection error probability (DEP) at the relay into account, we optimize the power distribution between the public and covert messages to achieve the maximum covert rate. We further make a delay-aware comparison among DF, CF and AF relay systems with the obtained closed-form covert rates and conduct an extensive examination on the asymptotic behaviors in different limits. Our analyses reveal that CF or AF tend to outperform DF for high source transmit power or low relay transmit power, while various system parameters such as the processing delay, minimum required quality of service for public messages and DEP threshold lead to different performance relationships among DF, CF and AF for high relay transmit power. Numerical results verify our investigation into the performance comparison in various channel models.

A Novel Unified Framework for Energy-Based Spectrum Sensing Analysis in the Presence of Fading.

This paper studies the performance of the energy-based sensing procedure in the presence of multipath fading and shadowing effects in terms of its average probability of detection (APD), average receiver operating characteristic (AROC) and the area under the AROC curve (AUC). A new generalization for the class of the fading channel moment generating functions (MGFs) (i.e., factorized power type (FPT) MGF) was proposed and applied for the construction of the unified framework for the analytical treatment of the formulated problem. The contiguity of the proposed model with the existing classical ones (Rayleigh, Nakagami-m, Hoyt, η-µ, κ-µ shadowed and Mixture-Gamma) was demonstrated. Within the assumed MGF representation, the novel closed-form solutions and computationally efficient approximation for APD and AUC are derived. The obtained general expressions were then applied for derivation of the new results for the recent generalized fading channel models: Fluctuating Beckmann and Beaulieu-Xie shadowed. For each of the models, high-SNR asymptotic expressions were obtained. Lastly, numeric simulation was performed to verify the correctness of the derived results, to establish the dependencies of the sensing performance quality from the channel parameters and to identify the specific ranges of their asymptotic behavior.

Performance Assessment for a Guided Wave-Based SHM System Applied to a Stiffened Composite Structure.

To assess the ability of structural health monitoring (SHM) systems, a variety of prerequisites and contributing factors have to be taken into account. Within this publication, this variety is analyzed for actively introduced guided wave-based SHM systems. For these systems, it is not possible to analyze their performance without taking into account their structure and their applied system parameters. Therefore, interdependencies of performance assessment are displayed in an SHM pyramid based on the structure and its monitoring requirements. Factors influencing the quality, capability and reliability of the monitoring system are given and put into relation with state-of-the-art performance analysis in a non-destructive evaluation. While some aspects are similar and can be treated in similar ways, others, such as location, environmental condition and structural dependency, demand novel solutions. Using an open-access data set from the Open Guided Waves platform, a detailed method description and analysis of path-based performance assessment is presented.The adopted approach clearly begs the question about the decision framework, as the threshold affects the reliability of the system. In addition, the findings show the effect of the propagation path according to the damage position. Indeed, the distance of damage directly affects the system performance. Otherwise, the propagation direction does not alter the potentiality of the detection approach despite the anisotropy of composites. Nonetheless, the finite waveguide makes it necessary to look at the whole paths, as singular phenomena associated with the reflections may appear. Numerical investigation helps to clarify the centrality of wave mechanics and the necessity to take sensor position into account as an influencing factor. Starting from the findings achieved, all the issues are discussed, and potential future steps are outlined.

Efficient Model Assisted Probability of Detection Estimations in Eddy Current NDT with ACA-SVD Based Forward Solver.

Model assisted probability of detection (MAPoD) is crucial for quantifying the inspection capability of a nondestructive testing (NDT) system which uses the coil or probe to sense the size and location of the cracks. Unfortunately, it may be computationally intensive for the simulation models. To improve the efficiency of the MAPoD, in this article, an efficient 3D eddy current nondestructive evaluation (ECNDE) forward solver is proposed to make estimations for PoD study. It is the first time that singular value decomposition (SVD) is used as the recompression technique to improve the overall performance of the adaptive cross approximation (ACA) algorithm-based boundary element method (BEM) ECNDE forward solver for implementation of PoD. Both the robustness and efficiency of the proposed solver are demonstrated and testified by comparing the predicted impedance variations of the coil with analytical, semi-analytical and experimental benchmarks. Calculation of PoD curves assisted by the proposed simulation model is performed on a finite thickness plate with a rectangular surface flaw. The features, which are the maximum impedance variations of the coil for various flaw lengths, are obtained entirely by the proposed model with selection of the liftoff distance as the uncertain parameter in a Gaussian distribution. The results show that the proposed ACA-SVD based BEM fast ECNDE forward solver is an excellent simulation model to make estimations for MAPoD study.

An Improved POD Model for Fast Semi-Quantitative Analysis of Carbendazim in Fruit by Surface Enhanced Raman Spectroscopy.

The current detection method of carbendazim suffers from the disadvantages of complicated preprocessing and long cycle time. In order to solve the problem of rapid quantitative screening of finite contaminants, this article proposed a qualitative method based on characteristic peaks and a semi-quantitative method based on threshold to detect carbendazim in apple, and finally the method is evaluated by a validation system based on binary output. The results showed that the detection limit for carbendazim was 0.5 mg/kg, and the detection probability was 100% when the concentration was no less than 1 mg/kg. The semi-quantitative analysis method had a false positive rate of 0% and 5% at 0.5 mg/kg and 2.5 mg/kg, respectively. The results of method evaluation showed that when the added concentration was greater than 2.5 mg/kg, the qualitative detection method was consistent with the reference method. When the concentration was no less than 5 mg/kg, the semi-quantitative method is consistent between different labs. The semi-quantitative method proposed in this study can achieve the screening of finite contaminants in blind samples and simplify the test validation process through the detection probability model, which can meet the needs of rapid on-site detection and has a good application prospect.

Mycoplasma hyopneumoniae Surveillance in Pig Populations: Establishing Sampling Guidelines for Detection in Growing Pigs.

Antemortem detection of Mycoplasma hyopneumoniae infection in swine production systems has relied on antibody testing, but the availability of tests based on DNA detection and novel diagnostic specimens, e.g., tracheal swabs and oral fluids, has the potential to improve M. hyopneumoniae surveillance. A field study was performed over a 14-week period during which 10 pigs in one pen at the center of a room with 1,250 6-week-old pigs housed in 46 pens were intratracheally inoculated with M. hyopneumoniae Thereafter, one tracheal sample, four serum samples, and one oral fluid sample were collected from every pen at 2-week intervals. Tracheal and oral fluid samples were tested for M. hyopneumoniae DNA and serum samples for M. hyopneumoniae antibody. Test results were modeled using a hierarchical Bayesian model, based on a latent spatial piecewise exponential survival model, to estimate the probability of detection by within-pen prevalence, number of positive pens in the barn, sample allocation, sample size, and sample type over time. Analysis showed that tracheal samples provided the earliest detection, especially at large sample sizes. While serum samples are more commonly collected and are less expensive to test, high probability of detection estimates were only obtained 30 days postexposure at large sample sizes. In all scenarios, probability of detection estimates for oral fluids within 30 days were significantly lower than those for tracheal and serum samples. Ultimately, the choice of specimen type, sample number, and assay will depend on testing objectives and economics, but the estimates provided here will assist in the design of M. hyopneumoniae surveillance and monitoring programs for different situations.

Despite Excellent Test Characteristics of the cobas 4800 CT/NG Assay, Detection of Oropharyngeal Chlamydia trachomatis and Neisseria gonorrhoeae Remains Challenging.

Oropharyngeal Chlamydia trachomatis (CT) infections and, especially, Neisseria gonorrhoeae (NG) infections are common, but few commercial nucleic acid amplification tests (NAATs) specify extragenital samples for intended use. The test characteristics of the cobas 4800 CT/NG assay were evaluated for oropharyngeal swabs. The technical validation included analysis of the specificity, sensitivity, dynamic range, linearity, efficiency, and precision. The probability of detection curve combined with historical data enabled the estimation of potentially missed diagnoses. A clinical evaluation was performed on a subset of 2,798 clinical samples available from routine diagnostics. Results of the cobas 4800 were compared with those from in-house C. trachomatis/N. gonorrhoeae PCR assays. Discrepant samples were tested with resolver assays, and these results were considered decisive. No cross-reactivity was seen in the analytical specificity analysis. High linearity (R2 ≥ 0.983), efficiency (89% to 99%), and precision (cycle threshold [CT ] value of 0.1 to 0.9) were seen for both C. trachomatis and N. gonorrhoeae The limit of detection in oropharyngeal samples was 3.2 × 102 inclusion-forming units (IFU)/ml for C. trachomatis and 6.7 × 102 CFU/ml for N. gonorrhoeae Estimates on potentially missed diagnoses were up to 7.2% for C. trachomatis and up to 24.7% for N. gonorrhoeae Clinical sensitivity and specificity were evaluated with 25 C. trachomatis-positive, 86 N. gonorrhoeae-positive, and 264 negative samples, resulting in 100% and 99.6% for C. trachomatis and 100% and 96.7% for N. gonorrhoeae, respectively. The findings in this study demonstrate the utility of the cobas 4800 CT/NG assay for oropharyngeal samples. Despite its being a highly accurate test, the range of reported CT values, especially for N. gonorrhoeae, suggests relatively low oropharyngeal loads. Hence, consistent detection over the full range of oropharyngeal loads could be impaired.

Algorithm for Evaluating Energy Detection Spectrum Sensing Performance of Cognitive Radio MIMO-OFDM Systems.

Cognitive radio technology enables spectrum sensing (SS), which allows the secondary user (SU) to access vacant frequency bands in the periods when the primary user (PU) is not active. Due to its minute implementation complexity, the SS approach based on energy detection (ED) of the PU signal has been analyzed in this paper. Analyses were performed for detecting PU signals by the SU in communication systems exploiting multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) transmission technology. To perform the analyses, a new algorithm for simulating the ED process based on a square-law combining (SLC) technique was developed. The main contribution of the proposed algorithm is enabling comprehensive simulation analyses of ED performance based on the SLC method for versatile combinations of operating parameter characteristics for different working environments of MIMO-OFDM systems. The influence of a false alarm on the detection probability of PU signals impacted by operating parameters such as the signal-to-noise ratios, the number of samples, the PU transmit powers, the modulation types and the number of the PU transmit and SU receive branches of the MIMO-OFDM systems have been analyzed in the paper. Simulation analyses are performed by running the proposed algorithm, which enables precise selection of and variation in the operating parameters, the level of noise uncertainty and the detection threshold in different simulation scenarios. The presented analysis of the obtained simulation results indicates how the considered operating parameters impact the ED efficiency of symmetric and asymmetric MIMO-OFDM systems.

From Constellation Dithering to NOMA Multiple Access: Security in Wireless Systems.

In recent years, there has been a noticeable increase in interest in the possibilities of embedding additional data in the constellation of an already existing information signal in radio technology. This solution more precisely is based on adding a low power signal (or signals) to a stronger signal (cover). As will be described in the article, this technique is used in numerous radio communication areas, such as watermarking, covert channel creation, and multiple access techniques. Typically, those areas are considered as independent research topics. Our comparison suggests that these areas are closely related. In this article, a comprehensive survey of the implementation of signal superposition is conducted with an emphasis on the similarities and differences between individual solutions. Since the nature of the signal model entails certain problems in the security area, we provide the reader with a review of the state-of-the-art research on this topic, including the PLS (physical layer security) and LPD (low probability of detection) issues.

Device Free Detection in Impulse Radio Ultrawide Bandwidth Systems.

In this paper, an analytical framework is presented for device detection in an impulse radio (IR) ultra-wide bandwidth (UWB) system and its performance analysis is carried out. The Neyman-Pearson (NP) criteria is employed for this device-free detection. Different from the frequency-based approaches, the proposed detection method utilizes time domain concepts. The characteristic function (CF) is utilized to measure the moments of the presence and absence of the device. Furthermore, this method is easily extendable to existing device-free and device-based techniques. This method can also be applied to different pulse-based UWB systems which use different modulation schemes compared to IR-UWB. In addition, the proposed method does not require training to measure or calibrate the system operating parameters. From the simulation results, it is observed that an optimal threshold can be chosen to improve the ROC for UWB system. It is shown that the probability of false alarm, PFA, has an inverse relationship with the detection threshold and frame length. Particularly, to maintain PFA<10-5 for a frame length of 300 ns, it is required that the threshold should be greater than 2.2. It is also shown that for a fix PFA, the probability of detection PD increases with an increase in interference-to-noise ratio (INR). Furthermore, PD approaches 1 for INR >-2 dB even for a very low PFA i.e., PFA=1×10-7. It is also shown that a 2 times increase in the interference energy results in a 3 dB improvement in INR for a fixed PFA=0.1 and PD=0.5. Finally, the derived performance expressions are corroborated through simulation.

Critical Separation Versus Effective Sweep Width: Bridging the Old and New Search-and-Rescue Worlds.

INTRODUCTION: "Critical separation" is a simple method for spacing searchers intended to produce a predictable probability of detection (POD). A more precise method, based on effective sweep width (W), has been adopted only slowly. Accurate PODs are critical in planning priorities in future operational periods. Therefore, it would be useful to know what POD a critical separation determination actually produces. METHODS: Detection ranges (Rd) were measured on high- and low-visibility adult mannequins (stuffed Tyvek suits of varying colors) and a red helmet detected by 6 searcher volunteers. Conversion factors previously described in the literature were used to convert Rds into predicted Ws and the previously described logit model to convert Ws into PODs. RESULTS: The Rds were 26±6 m (mean±SD) for the high-visibility mannequin, 15±5 m for the low-visibility mannequin, and 24±6 m for the helmet used in the critical separation determination. The predicted Ws were 47±15 m, 16±8 m, and 42±14 m, respectively. Critical separation would therefore result in predicted PODs of 67±17% or 32±16% for nonresponsive adults in high- versus low-visibility clothing. CONCLUSIONS: Critical separation is a simple, quick way to array searchers in the field. The current study suggests that the value of critical separation in producing the 50% target POD will depend on the whether the search object used for the critical separation determination has a similar detectability/W to the actual target of the search effort. Still, the results from a critical separation determination may offer more predictability and reliability than the common practice of POD estimation by team leaders.

A Study of the Automated Eddy Current Detection of Cracks in Steel Plates.

Applying life estimation approaches to determine in-service life of structures and plan the inspection schedules accordingly are becoming acceptable safety design procedures in aerospace. However, these design systems shall be fed with reliable parameters related to material properties, loading conditions and defect characteristics. In this context, the role of non-destructive (NDT) testing reliability is of high importance in detecting and sizing defects. Eddy current test (ECT) is an electromagnetic NDT method frequently used to inspect tiny surface fatigue cracks in sensitive industries. Owing to the new advances in robotic technologies, there is a trend to integrate the ECT into automated systems to perform NDT inspections more efficiently. In fact, ECT can be effectively automated as to increase the coverage, repeatability and scanning speed. The reliability of ECT scanning, however, should be thoroughly investigated and compared to conventional modes of applications to obtain a better understanding of the advantages and shortcomings related to this technique. In this contribution, a series of manual and automated ECT tests are carried out on a set of samples using a split-D reflection differential surface probe. The study investigates the level of noise recorded in each technique and discuss its dependency on different parameters, such as surface roughness and frequency. Afterwards, a description of the effect of crack orientation on ECT signal amplitude is provided through experimental tests and finite element simulations. Finally, the reliability of each ECT technique is investigated by means of probability of detection (POD) curves. POD parameters are then extracted and compared to examine the effect of scanning index, frequency and automation on detection reliability.

The Influence of X-Ray Computed Tomography Acquisition Parameters on Image Quality and Probability of Detection of Additive Manufacturing Defects.

X-ray computed tomography (XCT) is a promising nondestructive evaluation technique for additive manufacturing (AM) parts with complex shapes. Industrial XCT scanning is a relatively new development, and XCT has several acquisition parameters that a user can change for a scan whose effects are not fully understood. An artifact incorporating simulated defects of different sizes was produced using laser powder bed fusion (LPBF) AM. The influence of six XCT acquisition parameters was investigated experimentally based on a fractional factorial designed experiment. Twenty experimental runs were performed. The noise level of the XCT images was affected by the acquisition parameters, and the importance of the acquisition parameters was ranked. The measurement results were further analyzed to understand the probability of detection (POD) of the simulated defects. The POD determination process is detailed, including estimation of the POD confidence limit curve using a bootstrap method. The results are interpreted in the context of the AM process and XCT acquisition parameters.

Relationships between vital rates and ecological traits in an avian community.

Comparative studies about the relationships between vital rates and ecological traits at the community level are conspicuously lacking for most taxa because estimating vital rates requires detailed demographic data. Identifying relationships between vital rates and ecological traits could help to better understand ecological and evolutionary demographic mechanisms that lead to interspecific differences in vital rates. We use novel dynamic N-mixture models for counts to achieve this for a whole avian community comprising 53 passerine species, while simultaneously accounting for density dependence and environmental stochasticity in recruitment and survival and, importantly, correcting our inferences for imperfect detection. Demographic stochasticity is taken into account in the form of the binomial and Poisson distributions describing survival events and number of recruits. We then explore relationships between estimated demographic parameters (i.e., vital rates) and ecological traits related to migration patterns, diet, habitat and nesting location of each species. The relative importance of recruitment and adult survival as contributors to population growth varied greatly among species, and interspecific differences in vital rates partly reflected differences in ecological traits. Migratory mode was associated with interspecific differences in population growth and density dependence. Resident species had higher population growth rates than long- and short-distance migrants. We found no relationships between diet and population growth rate. Habitat differences were associated with different growth rates: alpine, wetland and farmland species had lower population growth rates than forest species. Differences in population growth rates among nesting locations showed that breeding habitat is essential for population dynamics. Our study reveals relationships between ecological traits and contributions of vital rates to population growth and suggests ways in which patterns of population growth fluctuations in a community might be determined by life history.