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The viewing direction characterization of reflective displays is more demanding than for emissive displays because defined illumination-detection geometries must be maintained for each viewing direction. In addition, the geometry should mimic the behavior of viewers who tend to exclude the reflection of light sources from a handheld reflective display. Viewing direction data was extracted from measured Bidirectional Reflectance Distribution Functions, showing that a source inclination of 45° sufficiently excludes the specular and haze components of source reflection from the measurement. Applying this so-called 45/θ geometry to curved flexible displays is not straightforward since viewing direction, display curvature, and alignment each affect the measured reflectance. The viewing direction geometry proposed for convex cylindrical displays uses a ring light to deliver viewing-direction independent illuminance, and maps the range of viewing directions onto the pixels of an image sensor. The illumination can also be applied to flat displays, allowing direct comparisons of flat and cylindrical display states. First results on e-paper show good agreement with Bidirectional Reflectance Distribution Function data. [ABSTRACT FROM AUTHOR]

This paper describes the dielectric breakdown characteristics of oil and oil-impregnated paper for very fast transient (VFT) voltages. Blumlein circuits generate VFT voltages of 60 and 300 ns in a pulse width that simulates disconnecting switching surges in gas-insulated switch gears. We measured the breakdown voltages of needle-to-plane, plane-to-plane oil gaps and several pieces of paper between plane electrodes for VFT and lightning impulse voltages. The measured data were formulated in V-t characteristics and Weibull probability distributions. The inclination n of V-t characteristics of insulating paper is 150, which is less than n = 13.7 of the plane-to-plane oil gap in the VFT time range. The shape parameters of Weibull distribution obtained in this study show that the scattering of breakdown voltages of paper is much less than that of oil. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 141(4): 16–24, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.10043 [ABSTRACT FROM AUTHOR]

A sudden capacity increase in demand during the summer peak, or in contingencies such as malfunctioning transformers, may cause an overload in normal transform-ers. In this paper, on the basis of overloaded transformer operation in distribution substations, thermal aging testing in oil was carried out under various overload patterns, such as short-term overload and long-term overload, but with the winding insulation paper's lifespan loss kept constant. From the results, various characteristics, such as the mean degree of polymerization and production of furfural and (C02+C0), and their effects on the lifespan loss of the insulation paper, were obtained. ©2012 Wiley Periodicals, Inc. Electr Eng Jpn, 182(2): 1-8, 2013; Published online in Wiley Online Library (wileyonlinelibrary.com). [ABSTRACT FROM AUTHOR]

Background: To test and validate novel CT techniques, such as texture analysis in radiomics, repeat measurements are required. Current anthropomorphic phantoms lack fine texture and true anatomic representation. 3D‐printing of iodinated ink on paper is a promising phantom manufacturing technique. Previously acquired or artificially created CT data can be used to generate realistic phantoms. Purpose: To present the design process of an anthropomorphic 3D‐printed iodine ink phantom, highlighting the different advantages and pitfalls in its use. To analyze the phantom's X‐ray attenuation properties, and the influences of the printing process on the imaging characteristics, by comparing it to the original input dataset. Methods: Two patient CT scans and artificially generated test patterns were combined in a single dataset for phantom printing and cropped to a size of 26 × 19 × 30 cm3. This DICOM dataset was printed on paper using iodinated ink. The phantom was CT‐scanned and compared to the original image dataset used for printing the phantom. The water‐equivalent diameter of the phantom was compared to that of a patient cohort (N = 104). Iodine concentrations in the phantom were measured using dual‐energy CT. 86 radiomics features were extracted from 10 repeat phantom scans and the input dataset. Features were compared using a histogram analysis and a PCA individually and overall, respectively. The frequency content was compared using the normalized spectrum modulus. Results: Low density structures are depicted incorrectly, while soft tissue structures show excellent visual accordance with the input dataset. Maximum deviations of around 30 HU between the original dataset and phantom HU values were observed. The phantom has X‐ray attenuation properties comparable to a lightweight adult patient (∼54 kg, BMI 19 kg/m2). Iodine concentrations in the phantom varied between 0 and 50 mg/ml. PCA of radiomics features shows different tissue types separate in similar areas of PCA representation in the phantom scans as in the input dataset. Individual feature analysis revealed systematic shift of first order radiomics features compared to the original dataset, while some higher order radiomics features did not. The normalized frequency modulus |f(ω)| of the phantom data agrees well with the original data. However, all frequencies systematically occur more frequently in the phantom compared to the maximum of the spectrum modulus than in the original data set, especially for mid‐frequencies (e.g., for ω = 0.3942 mm−1, |f(ω)|original = 0.09 * |fmax|original and |f(ω)|phantom = 0.12 * |fmax|phantom). Conclusions: 3D‐iodine‐ink‐printing technology can be used to print anthropomorphic phantoms with a water‐equivalent diameter of a lightweight adult patient. Challenges include small residual air enclosures and the fidelity of HU values. For soft tissue, there is a good agreement between the HU values of the phantom and input data set. Radiomics texture features of the phantom scans are similar to the input data set, but systematic shifts of radiomics features in first order features, due to differences in HU values, need to be considered. The paper substrate influences the spatial frequency distribution of the phantom scans. This phantom type is of very limited use for dual‐energy CT analyses. [ABSTRACT FROM AUTHOR]

In conservation biology, uncertainty about the choice of a statistical model is rarely considered. Model-selection uncertainty occurs whenever one model is chosen over plausible alternative models to represent understanding about a process and to make predictions about future observations. The standard approach to representing prediction uncertainty involves the calculation of prediction (or confidence) intervals that incorporate uncertainty about parameter estimates contingent on the choice of a “best” model chosen to represent truth. However, this approach to prediction based on statistical models tends to ignore model-selection uncertainty, resulting in overconfident predictions. Bayesian model averaging (BMA) has been promoted in a range of disciplines as a simple means of incorporating model-selection uncertainty into statistical inference and prediction. Bayesian model averaging also provides a formal framework for incorporating prior knowledge about the process being modeled. We provide an example of the application of BMA in modeling and predicting the spatial distribution of an arboreal marsupial in the Eden region of southeastern Australia. Other approaches to estimating prediction uncertainty are discussed. [ABSTRACT FROM AUTHOR]

This paper proposes an alternative rule for placing empirical points on Weibull probability paper. Following the standard or old rule, one takes the mean or median value of the order statistics first, then performs the Weibull transformation. The new rule is to make the Weibull transformation first, then take the expected value of the transformed order statistics. Although the new rule for placing points requires much more complicated calculations, a simple Monte Carlo experiment shows that the new rule estimator of the shape parameter is unbiased, whereas the old rule estimator turns out to be heavily biased. Copyright © 1999 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Under high stress conditions the `freak' and `strong' subpopulations lie very close to each other on the time scale. It is easy to `read' such a time-to-failure distribution as unimodal. especially when probability paper is used. This paper puts forward Parzen's estimator of the probability density function as a very useful method of indicating the `freak' subpopulation. [ABSTRACT FROM AUTHOR]

Recently we proposed a model in which when a scientist writes a manuscript, he picks up several random papers, cites them, and also copies a fraction of their references. The model was stimulated by our finding that a majority of scientific citations are copied from the lists of references used in other papers. It accounted quantitatively for several properties of empirically observed distribution of citations; however, important features such as power-law distributions of citations to papers published during the same year and the fact that the average rate of citing decreases with aging of a paper were not accounted for by that model. Here, we propose a modified model: When a scientist writes a manuscript, he picks up several random recent papers, cites them, and also copies some of their references. The difference with the original model is the word recent. We solve the model using methods of the theory of branching processes, and find that it can explain the aforementioned features of citation distribution, which our original model could not account for. The model also can explain “sleeping beauties in science;” that is, papers that are little cited for a decade or so and later “awaken” and get many citations. Although much can be understood from purely random models, we find that to obtain a good quantitative agreement with empirical citation data, one must introduce Darwinian fitness parameter for the papers. [ABSTRACT FROM AUTHOR]

The BL17B beamline at the Shanghai Synchrotron Radiation Facility was first designed as a versatile high‐throughput protein crystallography beamline and one of five beamlines affiliated to the National Facility for Protein Science in Shanghai. It was officially opened to users in July 2015. As a bending magnet beamline, BL17B has the advantages of high photon flux, brightness, energy resolution and continuous adjustable energy between 5 and 23 keV. The experimental station excels in crystal screening and structure determination, providing cost‐effective routine experimental services to numerous users. Given the interdisciplinary and green energy research demands, BL17B beamline has undergone optimization, expanded its range of experimental methods and enhanced sample environments for a more user‐friendly testing mode. These methods include single‐crystal X‐ray diffraction, powder crystal X‐ray diffraction, wide‐angle X‐ray scattering, grazing‐incidence wide‐angle X‐ray scattering (GIWAXS), and fully scattered atom pair distribution function analysis, covering structure detection from crystalline to amorphous states. This paper primarily presents the performance of the BL17B beamline and the application of the GIWAXS methodology at the beamline in the field of perovskite materials. [ABSTRACT FROM AUTHOR]

As one of the dimensionality reduction techniques of hyperspectral image (HSI), band selection (BS) does not change the spectral characteristics and physical meaning of HSIs, which is beneficial to the identification and analysis of surface objects. Recently, many BS methods for target detection have achieved promising results by making full use of the priori spectral features of the target to be detected. Conversely, anomaly detection separates the anomaly based solely on the statistical distribution difference between anomaly and background without any prior information. Therefore, the development of BS for anomaly detection has lagged far behind that of BS for target detection. To this end, this paper proposes a novel BS algorithm dedicated to anomaly detection tasks, named anomaly‐background separation and particle swarm optimization (PSO)‐based BS. Specifically, an anomaly‐background separation framework (ABSF) is established to predetermine a priori knowledge of anomaly distribution. Then, three band prioritization criteria are constructed with the anomaly‐background constraints generated by ABSF. Finally, PSO is used to find the optimal subset of bands in the solution space. The experiments on two real datasets demonstrate that the proposed method yields better detection results and greater stability compared to other BS methods discussed in this paper. [ABSTRACT FROM AUTHOR]

Males and females often desynchronise their mating activity during the breeding season (intersexual phenological asynchrony). This suggests that the two sexes differentially use environmental cues to initiate seasonal reproduction, and climate change may cause phenological shifts in a sex‐specific manner, subsequently altering frequency distribution of mating attempts over time and influencing the emergence timing and recruitment success of juveniles. In this article, we tested these hypotheses through literature reviews and theoretical modelling. We found that the sex specificity of environmental cues and phenological shifts remain poorly understood in most sexually reproducing animal taxa because of sex‐specific publication bias and data limitations. Meanwhile, our theoretical model predicted that the ecological consequences of phenological shifts are sexually asymmetric, with earlier mating onset of males having generally greater negative effects on population growth than that of females. We therefore suggest that further research is necessary to collect and incorporate sex‐specific information on seasonal reproduction into the theory of phenological mismatch, for which previous work has mostly focused on interspecific trophic asynchrony. We also outline a future research agenda to better understand the consequences of sex‐specific phenological shifts on seasonal population dynamics and long‐term persistence of species. [ABSTRACT FROM AUTHOR]

This special issue of Applied Stochastic Models in Business and Industry contains 10 papers that were presented at the 36th ASA Quality and Productivity Research Conference QPRC-2019. The author builds upon this algorithm to create a second procedure which analyzes data from multiple periodic processes and then deinterleave the processes. DATA AVAILABILITY STATEMENT Data sharing is not applicable to this article as no new data were created or analyzed in this study. [Extracted from the article]

Video steganography has the potential to be used to convey illegal information, and video steganalysis is a vital tool to detect the presence of this illicit act. Currently, all the motion vector (MV)‐based video steganalysis algorithms extract feature sets directly from the MVs, but ignoring the embedding operation may perturb the statistical distribution of other video encoding elements, such as the skipped macroblocks (no direct MVs). This paper proposes a novel 11‐dimensional feature set to detect MV‐based video steganography based on the above observation. The proposed feature is extracted based on the skipped macroblocks by recompression calibration. Specifically, the feature consists of two components. The first is the probability distribution of motion vector prediction (MVP) difference, and the second is the probability distribution of partition state transfer. Extensive experiments on different conditions demonstrate that the proposed feature set achieves good detection accuracy, especially in lower embedding capacities. In addition, the loss of detection performance caused by recompression calibration using mismatched quantization parameters (QP) is within the acceptable range, so the proposed method can be used in practical scenarios. [ABSTRACT FROM AUTHOR]

Failure Mode and Effect Analysis (FMEA) is acknowledged as a beneficial instrument for identifying and mitigating system failures. However, the traditional FMEA method has its limitations. For instance, crisp numbers fail to adequately represent the intricate information and cognitive nuances of experts. Additionally, the conventional approach overlooks the significance of weights assigned to FMEA experts and risk factors (RFs). Furthermore, the simplistic ranking of failure modes in traditional FMEA does not accurately reflect priorities. In light of these drawbacks, this paper introduces an innovative, fully data‐driven FMEA method, leveraging a probabilistic uncertain linguistic term sets (PULTSs) environment and the Weighted Aggregates Sum Product Assessment (WASPAS) method. In the assessment process, PULTSs serve as linguistic tools that express probability distribution, allowing for a more reasonable and precise description of information. To address the issue of weights for RFs, the regret theory and Modified CRITIC method are employed. Subsequently, the WASPAS method is applied to determine the risk rankings of failure modes. To illustrate the feasibility and rationality of this novel FMEA model, the paper includes an example involving the production of Lithium‐ion batteries. To emphasize the excellence of the proposed FMEA model, sensitivity and comparative analyses are carried out. [ABSTRACT FROM AUTHOR]

This paper deals with the probabilistic analysis of a class of compartmental models formulated via a system of linear differential equations with time‐dependent non‐homogeneous terms. For the sake of generality, we assume that initial conditions and rates between compartments are random variables with arbitrary distributions while the source terms defining the flows entering the compartments are stochastic processes. We then take extensive advantage of the so‐called random variable transformation (RVT) technique to determine the first probability distribution of the solution of such a randomized model under very general hypotheses. In the simplest but relevant case of time‐independent source terms, we also obtain the probability distribution of the equilibrium, which is a random vector. Furthermore, we first particularize the aforementioned results for different types of integrable source terms that permit obtaining an explicit solution of the compartmental model: random constants, a train of Dirac delta impulses with random intensities, and a Wiener process. Secondly, we show an alternative approach based on the Liouville–Gibbs equation, which is useful when dealing with source terms that do not admit a closed‐form primitive. All the previous theoretical results are first illustrated through several numerical examples and simulations where a wide range of different probability distributions are assumed for the model parameters. The paper concludes by applying a compartmental model that describes the dynamics of oral drug administration through multiple chronologically spaced doses using synthetic data generated according to pharmacological references. [ABSTRACT FROM AUTHOR]

Reliability, Availability and Condition Monitoring (RACM) evaluation has become a critical area of interest for researchers as the output power quality of a Photo‐Voltaic (PV) system depend on the reliability of its components. In this paper, the RACM of grid‐connected PV systems is presented. For this, the Reliability Block Diagram (RBD) technique along with the exponential probability distribution function is used. The main objective of this work is to identify the weakest subsystem of a system in order to enhance system reliability. The condition monitoring system will be helpful in avoiding the sudden breakdown and unexpected maintenance of the system. An elaborate analysis is presented for PV system beginning from the sub‐assemblies to the subsystems and then to the overall system. In addition, the subsystems are ranked based on their impact on the overall availability of the system. This is decided based on the availability importance measures. It is observed that the inverter forms the weakest subsystem in the solar system. The novelty of the proposed RACM method is that one can monitor the health status or useful life of the system regularly which is not yet explored in the literature. Most of the papers have considered that the components of PV systems are non‐repairable but in this paper, the redundancy concept is explored which helps in increasing the reliability and availability of the system. When the proposed method and the results obtained are compared to existing methods, it is discovered that the proposed work outperforms them. [ABSTRACT FROM AUTHOR]

Summary: In this paper, 51 sets of directional spectrum measured data collected from the Bohai offshore site were applied to study the comparative characteristics of Wen's direction spectrum and Donelan direction function. Firstly, the optimal frequency value of direction spectrum is analyzed from two aspects: the direction cumulative distribution and the direction distribution function fitting quality. Secondly, combined with the experimental results, the distribution characteristics of different direction functions are compared from the maximum and standard deviation of the distribution function. The experiments prove that Donelan function contains all the states of the wind and wave growth stage, which can fully measure the influence of the wave age on wind frequency spectrum. Then, this paper analyzes the classical Monte Carlo method and the Las Vegas method from the perspective of the computational complexity and direction distribution difference of simulation step. Based on the classical Monte Carlo method, this paper proposes a two‐dimensional random rough sea surface numerical calculation model suitable for different water depths and different wind wave growth stages. Finally, by analyzing the characteristics of the nonlinear sea surface, this paper studies the effects of wind speed, wind direction, and fetch on sea surface wave height and growth state. [ABSTRACT FROM AUTHOR]

The logit and probit models have become critical parts of the management researcher's analytical arsenal, growing rapidly from almost no use in the 1980s to appearing in 15% of all articles published in Strategic Management Journal in 2005. However, a review of three top strategy journals revealed numerous areas in their use and interpretation where current practice fell short of ideal. Failure to understand how these models differ from ordinary least squares can lead researchers to misunderstand their statistical results and draw incorrect conclusions regarding the theory they are testing. Based on a review of the methodological literature and recent empirical papers in three leading strategy journals, this paper identifies four critical issues in their use: interpreting coefficients, modeling interactions between variables, comparing coefficients between groups (e.g., foreign and domestic firms), and measures of model fit. For each issue, the paper provides a background, a review of current practice, and recommendations for best practice. A concluding section presents overall implications for the conduct of research with logit and probit models, which should assist both authors and readers of strategic management research. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Population growth has always played a key role in human mobility, even before the age of farming and husbandry. This paper explores population dynamics among early Holocene (∼9500–1700 cal BCE) hunter‐fisher‐gatherers in Southern Norway, focusing in particular on the Mesolithic‐Neolithic transition (4000/3900 cal BCE). Radiocarbon dates are calibrated and turned into summed probability distributions (SPDs). A heuristic linear method is used to calculate annual growth rates from the SPDs. Observed fluctuations in the SPDs are tested for significance by applying a Monte Carlo‐based simulation method. The paper finds evidence of a steady growth rate from the Boreal period until a sudden population trough at ∼4330–4300 cal BCE. The trough coincides with indications from the archaeological record of a dispersal of hunter‐fisher‐gatherers from Southern Scandinavia to Norway. The dispersal was likely an effect of lowered habitat suitability and social stress caused by population pressure among Southern Scandinavian hunter‐fisher‐gatherers. In Southern Norway, the proxy data show that the trough enabled a subsequent 'boom' in population and the emergence of regional technological innovations that define the Mesolithic‐Neolithic transition. [ABSTRACT FROM AUTHOR]

In the weapon test range, the space projectile explosion position parameter at the terminal trajectory is an important index to evaluate the damage performance of the projectile fuze. Due to the random distribution of the falling dispersion of the projectile, it is difficult to test the projectile explosion position in the long‐range terminal trajectory falling area. To solve this problem, this paper proposes a method for measuring the projectile explosion position based on ultra‐wide imaging with a multi‐lens array. A curved multi‐lens array optical imaging system is designed and the parameter calculation method of the optical system is presented. The relationship between the space projectile explosion position and the center of the sub‐eye lens and the relationship between the center of the sub‐eye lens and the imaging point of the image sensor is established according to the imaging principle of the optical system. The object image relations of any seven adjacent sub‐eye lenses of the curved multi‐lens array optical imaging system are combined and the calculation model of the space projectile explosion position is deduced. The experimental results verify that the designed curved multi‐lens array optical imaging system and the calculation model of the projectile explosion position proposed in this paper are reasonable. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this paper is to analyze the adoption and outcomes of the ISO 14001 standard through a systematic review of the main studies on this issue published in peer‐reviewed journals between 1996 and 2015. The 94 papers analyzed make it possible to paint a comprehensive picture of the effectiveness of ISO 14001 in environmental management practices, performance in this area and social aspects such as employee awareness. The systematic review also sheds more light on the main pitfalls and success factors of the standard. Nevertheless, the similarities and even redundancies of the literature in terms of objectives, approaches and methods used tend to produce quite predictable and optimistic results, which do not reflect the complexity of the impact of ISO 14001. The paper highlights the importance of more diverse and critical approaches that might challenge the successful rhetoric of the dominant literature, which tends to focus on positive aspects and be limited to a few countries that are not representative of the wide international distribution of certification. The findings of this systematic review can also help managers in making decisions on the adoption and renewal of certification. [ABSTRACT FROM AUTHOR]

This article presents a comment on the papers by statisticians G.F. Cooper and D.A. Lane. The author says that these two excellent papers reflect the increasing interest in structured probabilistic analysis, in which the complex relationships between variables are developed for a particular problem, instead of using standard statistical models for analysis. Cooper's paper discusses the increasing interest in probabilistic analysis in expert systems. Lane's analysis emphasizes coherence in using evidence on a particular case, and provides admirable detail concerning the source of the subjective probability assessments.

In many research studies, multiple objectives need to be considered simultaneously to ensure an effective and efficient investigation. A compound optimal design provides a viable solution to this problem, allowing for the maximization of overall benefits through the integration of several factors. The paper addresses the application of compound optimal designs in the context of progressive first‐failure censoring, with a particular focus on the Generalized Exponential distribution with two parameters. The paper provides an illustrative example of compound designs by considering the cost function along with trace, variance, and determinant of inverse Fisher information. The best design is determined using a graphical solution technique that is both comprehensible and precise. Using a simple example, we demonstrate the advantage of compound optimal designs over constraint optimal designs. Furthermore, the paper examines real‐world data collection to demonstrate the practical utility of compound optimal designs. [ABSTRACT FROM AUTHOR]

Highlights This paper presents a comprehensive study on anisotropic heat transmission behaviors in quartz fiber fabrics. Considering the random distribution characteristic of fibers within the yarn, an innovative two‐scale finite element method (tFEM) is introduced, incorporating multiple micro‐scale fiber models (MMFM) based on scanning electron microscope (SEM) observations. MMFM are divided into 8 distinct models to capture intricate fiber arrangements. The macro‐scale fabric model is constructed based on the geometric structure analysis by Micro‐CT technology. Both micro‐ and macro‐scale models are assembled with the air matrix to form the two‐phase composite model. The Hot‐Disk thermal analysis instrument is applied to measure the anisotropic thermal conductivity (ATC). Numerical results from MMFM shows more excellent agreements with the experimental ones at 3D orthogonal directions of fabrics, i.e., the error rates of the thermal conductivity in the warp, weft and thickness directions between numerical and experimental methods are all less than 3%, which indicates the tFEM including MMFM in this paper is more accurate than the tFEM including OSMFM. In addition, the temperature distribution and heat transmission differences due to fiber arrangements are simulated and illustrated through the MMFM. Afterwards, temperature drop and isothermal characteristics are demonstrated in this study. Effects of fiber arrangements on steady heat transfer behaviors at micro‐scale are illustrated. Isothermal and temperature‐drop characteristics at micro‐ and macro‐scale are simulated and studied. The transverse isotropy of thermal conductivity at micro‐scale and the anisotropy of that at macro‐scale are revealed. [ABSTRACT FROM AUTHOR]

Riverbed elevations play a crucial role in sediment transport and flow resistance, making it essential to understand and quantify their effects. This knowledge is vital for various fields, including river engineering and stream ecology. Previous observations have revealed that fluctuations in the bed surface can exhibit both multifractal and monofractal behaviors. Specifically, the probability distribution function (PDF) of elevation increments may transition from Laplace (two‐sided exponential) to Gaussian with increasing scales or consistently remain Gaussian, respectively. These differences at the finest timescale lead to distinct patterns of bedload particle exchange with the bed surface, thereby influencing particle resting times and streamwise transport. In this paper, we utilize the fractional Laplace motion (FLM) model to analyze riverbed elevation series, demonstrating its capability to capture both mono‐ and multi‐fractal behaviors. Our focus is on studying the resting time distribution of bedload particles during downstream transport, with the FLM model primarily parameterized based on the Laplace distribution of increments PDF at the finest timescale. Resting times are extracted from the bed elevation series by identifying pairs of adjacent deposition and entrainment events at the same elevation. We demonstrate that in cases of insufficient data series length, the FLM model robustly estimates the tail exponent of the resting time distribution. Notably, the tail of the exceedance probability distribution of resting times is much heavier for experimental measurements displaying Laplace increments PDF at the finest scale, compared to previous studies observing Gaussian PDF for bed elevation. Plain Language Summary: The evolution of riverbed elevations is difficult to describe due to its highly variable and strongly non‐linear nature. Understanding and quantifying the dynamics of riverbed elevations are important for river engineering and stream ecology, and serve as the basis for numerical models of predicting sediment transport as well as interpreting stratigraphy from the past records. Through laboratory experiments, we have observed that the form of elevation increment PDF can change from Laplace to Gaussian as the timescale increases. This phenomenon is successfully modeled in this paper for the first time by the fractional Laplace motion, which essentially generates bed elevation series for the evolution of bed surface height at a certain spatial location of the bed. This series contains information on how long a bedload particle can rest (resting time) in the riverbed before it can be re‐entrained to move downstream, the determination of which by other means (e.g., particle‐tracking measurements) is challenging. By extracting resting times embedded in this bed elevation series, we obtain statistics (i.e., the tail behavior of the resting time distribution) that are key for correctly modeling the transport of bedload particles, and more specifically, that can help us to understand the anomalous bedload diffusion process. Key Points: The Fractional Laplace motion (FLM) can be used to describe the evolution of the distribution of bed elevation increments over different timescalesCorrectly predicting bed elevation fluctuations at the finest timescale is critical for estimating resting times for bedload tracer transportFLM model provides a means of robustly estimating the tail exponent of the resting time distribution in case of insufficient data series length [ABSTRACT FROM AUTHOR]

The incorporation of randomness into stochastic computing can provide ample opportunities for applications such as simulated annealing, non‐polynomial hard problem solving, and Bayesian neuron networks. In these cases, a considerable number of random numbers with an accurate and configurable probability distribution function (PDF) are indispensable. Preferably, these random numbers are provided at the hardware level to improve speed, efficiency, and parallelism. In this paper, how spin‐orbit torque magnetic tunnel junctions (SOT‐MTJs) with high barriers are suitable candidates for the desired true random number generators is demonstrated. Not only do these SOT‐MTJs perform excellently in speed and endurance, but their randomness can also be conveniently and precisely controlled by a writing voltage, which makes them a well‐performed Bernoulli bit. By utilizing these SOT‐MTJ‐based Bernoulli bits, any PDF, including Gaussian, uniform, exponential, Chi‐square, and even arbitrarily defined distributions can be realized. These PDF‐configurable true random number generators can then promise to advance the development of stochastic computing and broaden the applications of the SOT‐MTJs. [ABSTRACT FROM AUTHOR]

This paper introduces a new 2D representation of the orientation distribution function for an arbitrary material texture. The approach is based on the isometric square torus mapping of the Clifford torus, which allows for points on the unit quaternion hypersphere (each corresponding to a 3D orientation) to be represented in a periodic 2D square map. The combination of three such orthogonal mappings into a single RGB (red–green–blue) image provides a compact periodic representation of any set of orientations. Square torus representations of five different orientation sampling methods are compared and analyzed in terms of the Riesz s energies that quantify the uniformity of the samplings. The effect of crystallographic symmetry on the square torus map is analyzed in terms of the Rodrigues fundamental zones for the rotational symmetry groups. The paper concludes with example representations of important texture components in cubic and hexagonal materials. The new RGB representation provides a convenient and compact way of generating training data for the automated analysis of material textures by means of neural networks. [ABSTRACT FROM AUTHOR]

Econometric duration analysis has become an important part of methodology in econometrics, bringing forth a plenty of applications. The probability distribution of the duration of a time span is modelled through its conditional hazard rate given the covariates. When some of the covariates are unobservable, the duration, given the observable covariates, has a mixture distribution. The paper surveys and discusses recent developments in the specification, estimation, diagnosis and economic application of proportional hazard models with unobservables. Copyright © 2003 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the authors discusses various reports within the issue on topics including the methods for managing problems from the distribution process in transportation, the integer linear model for production and management, and optimal solutions for energy applications.

A silo structure is usually constructed in the form of a cylindrical steel shell. It has the advantages of being lightweight, having a short construction period, and possessing a large storage space. It has been widely used in many fields of industry. Thin‐walled cylindrical shells often exhibit buckling failure and the experimental buckling load is usually lower than calculation results from classical theory and simulation without geometrical imperfection. Besides, test results with carefully conducted similar specimens still have substantial scatter due to imperfection sensitivity. The nonlinear analysis with FEM can obtain a high‐precision result comparing the experiment if the geometric parameters of the shell are fully known. However, this is almost impossible in practical engineering. The initial geometric imperfections and shell thickness of cylindrical shells are complex and random properties. Theoretically, these geometric imperfections can be described using a random field. This paper presents the experimental investigation of buckling analysis of cylindrical shells under axial compression considering the randomness of geometric imperfections and thickness. A total of 12 cylindrical shell specimens were fabricated and tested. Based on the test results, the optimal statistical distribution is obtained by the maximum entropy fitting method and the obtained results were compared with geometric imperfections based on laser scan measurements. [ABSTRACT FROM AUTHOR]

Ensemble climatological forecasts play a critical part in benchmarking the predictive performance of hydroclimatic forecasts. Accounting for the skewness and censoring characteristics of hydroclimatic variables, ensemble climatological forecasts can be generated by the log, Box‐Cox and log‐sinh transformations, by the combinations of the Bernoulli distribution with the Gaussian, Gamma, log‐normal, generalized extreme value, generalized logistic and Pearson type III distributions and by the non‐parametric resampling, empirical cumulative distribution function and kernel density estimation methods. This paper is concentrated on the reliability of the 12 types of ensemble climatological forecasts. Specifically, mathematical formulations are presented and large‐sample tests are devised to verify the forecast reliability for the Multi‐Source Weighted‐Ensemble Precipitation version 2 across the globe. Climatological forecasts of monthly precipitation over 18,425 grid cells are generated for 30 years under leave‐one‐year‐out cross validation, leading to 6,633,000 (12 × 18425 × 30) sets of ensemble climatological forecasts. The results point out that the reliability of climatological forecasts considerably varies across the 12 methods, particularly in regions with high hydroclimatic variability. One observation is that climatological forecasts tend to deviate from the distributions of observations when there is inadequate flexibility to fit precipitation data. Another observation is that ensemble spreads can be overly wide when there exist overfits of sample‐specific noises in cross validation. Through the tests of global precipitation, the robustness of the log‐sinh transformation and the Bernoulli‐Gamma distribution is highlighted. Overall, the investigations can serve as a guidance on the uses of transformations, distributions and non‐parametric methods in generating climatological forecasts. Plain Language Summary: Ensemble climatological forecasts have been extensively used as the benchmark to evaluate forecast skill. That is, forecasts generated by a certain forecasting model are skillful when they outperform climatological forecasts and otherwise they are not. In practice, ensemble climatological forecasts are generated by different methods, including the log, Box‐Cox and log‐sinh transformations, the combinations of the Bernoulli distribution with the Gaussian, Gamma, log‐normal, generalized extreme value, generalized logistic and Pearson type III distributions and the non‐parametric resampling, empirical cumulative distribution function and kernel density estimation methods. It is important to investigate pros and cons of different types of climatological forecasts. Focusing on the reliability, that is, statistical consistency between forecasts and observations, this paper has devised large‐sample tests of global monthly precipitation. The results show that owing to hydroclimatic variability, different types of climatological forecasts exhibit varying characteristics of reliability. On the one hand, climatological forecasts can deviate from observations when there is inadequate flexibility to fit precipitation data, especially for the Bernoulli‐Gaussian distribution. On the other hand, ensemble spreads can be too wide when there exist overfits of sample‐specific noises in cross validation. Among the 12 methods, the robustness of the log‐sinh transformation and the Bernoulli‐Gamma distribution is highlighted. Key Points: Climatological forecasts can be generated by using data transformations, statistical distributions and non‐parametric methodsThe reliability of climatological forecasts generated by different methods is shown to vary considerably in large‐sample testsThe robustness of log‐sinh transformation and Bernoulli‐Gamma distribution is illustrated through the tests of global precipitation [ABSTRACT FROM AUTHOR]

Adaptation decision‐scientists increasingly use real‐option analysis to consider the value of learning about future climate variable development in adaptation decisions. Toward this end learning scenarios are needed, which are scenarios that provide information on future variable values seen not only from today (as static scenarios), but also seen from future moments in time. Decision‐scientists generally develop learning scenarios themselves, mostly through time‐independent (stationary) or highly simplified methods. The climate learning scenarios thus attained generally only poorly represent the uncertainties of state‐of‐the‐art climate science and thus may lead to biased decisions. This paper first motivates the need for learning scenarios by providing a simple example to illustrate characteristics and benefits of learning scenarios. Next, we analyze how well learning scenarios represent climate uncertainties in the context of sea level rise and present a novel method called direct fit to generate climate learning scenarios that outperforms existing methods. This is illustrated by quantifying the difference of the sea level rise learning scenarios created with both methods to the original underlying scenario. The direct fit method is based on pointwise probability distributions, for example, boxplots, and hence can be applied to static scenarios as well as ensemble trajectories. Furthermore, the direct fit method offers a much simpler process for generating learning scenarios from static or "ordinary" climate scenarios. Plain Language Summary: Many climate change adaptation decisions require large investments in infrastructure (e.g., dikes), while at the same time future projections about critical variables (e.g., sea level rise) are highly uncertain. Decision‐scientists address these challenges with methods based on flexibility and staged decision‐making. For example, a coastal decision‐maker could implement a dike with a wider foundation, and, if necessary, upgrade the dike height in the future. The decision‐maker will learn by observing future sea level rise if higher dike protection levels are actually necessary in the future. In order to assess whether it is economically beneficial to wait for future learning through observations, and thus to justify additional expenses for flexible infrastructure investments, learning scenarios are required. Learning scenarios provide projections of critical variables seen from today and from future moments in time. For example, learning scenarios of sea level rise contain sea level rise projections seen from 2050 onward, depending on a certain amount of sea level rise observed until 2050. In this paper, we provide a simple example to illustrate coastal decision‐making with a learning scenario, propose a new method to generate learning scenarios, and apply this method to generate sea level rise learning scenarios. Key Points: We show how climate learning scenarios can be applied for improving and justifying investments in flexible long‐lasting infrastructureWe develop sea level rise learning scenarios based on Intergovernmental Panel on Climate Change sixth Assessment Report using a novel method termed direct fitOur new method reduces the average deviation of learning scenarios from the original data by 83% compared to standard methods [ABSTRACT FROM AUTHOR]

In the postmarket drug and vaccine safety surveillance, when the number of adverse events follows a Poisson distribution, the ratio between the exposed and the unexposed person‐time information is the random variable that governs the decision rule about the safety of the drug or vaccine. The probability distribution function of such a ratio is derived in this paper. Exact point and interval estimators for the relative risk are discussed as well as statistical hypothesis testing. To the best of our knowledge, this is the first paper that provides an unbiased estimator for the relative risk based on the person‐time ratio. The applicability of this new distribution is illustrated through a real data analysis aimed to detect increased risk of occurrence of Myocarditis/Pericarditis following mRNA COVID‐19 vaccination in Manitoba, Canada. [ABSTRACT FROM AUTHOR]

Agile practices have received attention from industry as an alternative to plan-driven software development approaches. Agile encourages, for example, small self-organized collocated teams, whereas global software engineering (GSE) implies distribution across cultural, temporal, and geographical boundaries. Hence, combining them is a challenge. A systematic review was conducted to capture the status of combining agility with GSE. The results were limited to peer-reviewed conference papers or journal articles, published between 1999 and 2009. The synthesis was made through classifying the papers into different categories (e.g. publication year, contribution type, research method). At the end, 81 papers were judged as primary for further analysis. The distribution of papers over the years indicated that GSE and Agile in combination has received more attention in the last 5 years. However, the majority of the existing research is industrial experience reports in which Agile practices were modified with respect to the context and situational requirements. The emergent need in this research area is suggested to be developing a framework that considers various factors from different perspectives when incorporating Agile in GSE. Practitioners may use it as a decision-making basis in early phases of software development. [ABSTRACT FROM AUTHOR]

An attractive feature of using a Bayesian analysis for a clinical trial is that knowledge and uncertainty about the treatment effect is summarized in a posterior probability distribution. Researchers often find probability statements about treatment effects highly intuitive and the fact that this is not accommodated in frequentist inference is a disadvantage. At the same time, the requirement to specify a prior distribution in order to obtain a posterior distribution is sometimes an artificial process that may introduce subjectivity or complexity into the analysis. This paper considers a compromise involving confidence distributions, which are probability distributions that summarize uncertainty about the treatment effect without the need for a prior distribution and in a way that is fully compatible with frequentist inference. The concept of a confidence distribution provides a posterior–like probability distribution that is distinct from, but exists in tandem with, the relative frequency interpretation of probability used in frequentist inference. Although they have been discussed for decades, confidence distributions are not well known among clinical trial statisticians and the goal of this paper is to discuss their use in analyzing treatment effects from randomized trials. As well as providing an introduction to confidence distributions, some illustrative examples relevant to clinical trials are presented, along with various case studies based on real clinical trials. It is recommended that trial statisticians consider presenting confidence distributions for treatment effects when reporting analyses of clinical trials. [ABSTRACT FROM AUTHOR]

This paper presents the fire load data in educational, office and library buildings, obtained through an extensive inventory survey. This data collection effort is prompted by a growing need to simulate compartment fires, wherein estimating realistic fire scenarios is essential to assess the level of fire severity in a structure, and consequently the strength of the various structural members at elevated temperatures. The attributes of compartment fires primarily depend upon the fuel load and its composition, compartment dimensions, ventilation characteristics, and construction materials. Despite an acute need, fire load data across the world is scarce and outdated, and does not reflect the change in the type of materials in‐use today. The survey data presented in this paper is collected from 108 rooms in 10 educational buildings, 51 rooms in three office buildings, and 13 rooms in a library building. This paper also presents the composition of fire loads and the levels of ventilation in these buildings. The studies show that fire loads can vary significantly depending on the room‐use; thereby basing fire load values solely on the overall category of a building may result in either conservative or unsafe design. This study also finds that certain room types (e.g., computer labs) have significant plastic‐based fuels, indicating that typical modelling recommendations based on cellulosic fuels for heat release rate, combustion heat, etc. may not always be appropriate. The paper finally examines the statistical distribution that best describes the measured values of the fire load densities. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) diagnostics test is a reliable solution for estimating insulation health conditions in power system components. During laboratory PD diagnostics, the effect of harmonic components in the voltage waveform generated by variable frequency drives (VFD) fed electric motors (EMs) is often overlooked. As VFD‐fed EMs operate at low speeds, the harmonic concentration in the voltage increases. It has been found that PD activity in VFD‐fed EM is significantly affected by the addition of harmonic components in the voltage, thus making it necessary to consider their impact when performing true PD diagnostics. This paper investigates the influence of voltage harmonic distortion produced in VFD‐fed EM on PD severity and the subsequent insulation degradation. Eight VFD‐fed EM are used to study the PD behaviour under different levels of harmonic pollution. The PD characteristics, such as inception voltage, pulse repetition rate, accumulated apparent charge, average discharge current, discharge power, and quadratic rate, are determined. Using probability distribution functions, PD activity and severity at various voltage harmonic levels are estimated. The proposed technique can be used to plan the maintenance activities that ensure the reliability for industrial applications dealing with the voltage harmonic distortion. [ABSTRACT FROM AUTHOR]

Develops a model of fractional frequency distributions derived from two dual Lotka's laws. Comparison between the theoretically obtained fractional frequency distribution and the experimental one; Construction of fractional data sets.

The extreme value theory has been object of engineering studies for more than a century. The analysis of extreme winds plays a key role for complex civil structures and a driving role in different stages of wind turbines lifetime. Most of extremes probability models depend on the annual rate of independent events (ARIE) which has been traditionally considered a constant value. The authors have embraced a recent belief considering the ARIE as a function of the wind velocity. Even though a certain agreement has been achieved across the researches, some issues are still pending. In this regard, the paper shows that the annual, seasonal and daily fluctuations embedded in time series of the mean wind speeds, constrain its probability distribution and time correlation to be physically consistent. Besides, a new physical interpretation of the ARIE is presented, expressing how the independence across wind observations increases with the wind speed, up to the point that all yearly observations are independent if larger than a suitable speed value. Such a tendency is not revealed if the annual, seasonal and daily fluctuations are excluded by the analysis, leading to a deceitful shape of the ARIE. Finally, the paper shows how the velocity‐dependent ARIE model is consistent with the conventional asymptotic extreme value theory, if a sufficiently large left‐censorship applies to the dataset. The study of the ARIE presented in this paper is based on long‐term Monte Carlo simulation of the mean wind speed. [ABSTRACT FROM AUTHOR]

Summary: Fractional‐order circuits, which contain fractance devices (Lβ and Cα) described by fractional‐order differential equations, are widely used in interdisciplinary engineering research. The application of time‐domain response (TDR) measurement increases rapidly in analyzing the characteristics of fractance devices and fractional‐order circuits. However, the previous methods are mainly focused on deducing TDR expressions of a single fractance device or series fractional‐order circuits in some specific input signals, while overlook the TDR analysis of series‐parallel fractional‐order circuits (SPFOC) that are commonly applied in modeling electrochemical impedance or electrical bioimpedance. This paper proposes a novel method to derive TDR expressions of SPFOC in an arbitrary periodic signal. First, a discretization method to represent the SPFOC as the sum of first‐order circuits is proposed in Cole distribution function, which could approximate the transfer function of fractional‐order impedance/admittance. Second, the TDR expression of SPFOC in sinusoidal input signals is deduced in inverse Laplace transform, which can be applied as the components of a general TDR expression of SPFOC in an arbitrary periodic signal based on the Fourier series theory. Finally, both TDR simulations and experiments on Cole impedance model (a basic SPFOC) are conducted to verify the proposed method, which shows excellent agreement compared to theorical analysis. This paper presents a TDR solution to SPFOC that consist of a RCα or RLβ element. In future, the theoretical and application extension of the proposed TDR analysis method is still necessary on analysis of more general fractional‐order circuits. [ABSTRACT FROM AUTHOR]

In the paper, the statistical distribution of the total strain and the fatigue life in the low cycle fatigue (LCF)–high cycle fatigue (HCF) life range is analytically derived starting from the Coffin–Manson and Morrow model. The maximum likelihood principle is exploited for parameter estimation, thus allowing to consider both failures and runout specimens. A straightforward procedure for the estimation of the design curves based on the likelihood ratio confidence lower bound has been also developed. The proposed model has been validated with literature datasets obtained by testing steel and aluminum alloys, proving its effectiveness and representing a reliable alternative to the currently adopted literature models. Highlights: A method for the strain–life design curves is proposed.Likelihood ratio lower confidence bound is exploited for the design curves.The analytical formulation of the statistical distribution of total strain is derived.A procedure for parameter estimation based on maximum likelihood principle is proposed [ABSTRACT FROM AUTHOR]

The earthquake‐induced displacement of sloping soil mass is an important indicator of co‐seismic landslide initiation. In this paper, an improved Newmark displacement model that considers the accumulation of dynamic pore water pressure (DPWP) in the soil caused by both vertical and horizontal ground motions is proposed. The model can quantitatively describe the dynamic changes of the seismic yield acceleration of near‐saturated infinite soil slopes. Three different types of ground motion time histories are selected to compare the performance of the proposed Newmark displacement model, and the influence of DPWP accumulation on the slope yield acceleration and on the seismic displacement is obtained. The seismic slope displacement analyses indicate that the weakening effect of slope yield acceleration caused by bidirectional earthquake excitation‐induced DPWP is more obvious than when only considering the horizontal ground motion, when the slip surface soils are in near‐saturated state. The effect of initial saturation (Sr0) on the DPWP accumulation caused by vertical ground motion is also investigated. Furthermore, the accumulated seismic displacement can be reasonably explained by the frequency distribution characteristics of the ground motions. Finally, the numerical results of this paper show that the seismic displacement model seldomly considering the effect of DPWP, or only considering the DPWP induced by horizontal ground motion, can significantly underestimate the displacement value when the slip surface soils are in a near‐saturated state. [ABSTRACT FROM AUTHOR]

In a restructured electricity market, a large consumer could supply its electricity consumption through its own available resources or purchasing from the electricity markets. Moreover, it could participate in demand response programs (DRPs) and also supply some portion of its demand from bilateral contracts. In this regard, the large consumer's objective is to minimize its own operation cost while facing several uncertainties that could affect its optimal decisions. The decision‐making problem becomes more difficult especially when the historical data is incomplete, or when the data is not available. This paper proposes an optimal decision‐making framework for a large consumer in the face of a comprehensive set of uncertain resources including electricity market price, internal electricity consumption, renewable power generation, and DR participation. To this end, a probabilistic‐possibilistic methodology is proposed to model the uncertainty of the electricity market prices in a more accurate way in comparison with existing approaches through the concept of Z‐number method. The uncertainty of internal electricity consumption is modelled by means of the seasonal ARIMA model, while the stochastic generation of its existing renewable resources are modelled through appropriate probability distribution functions. Moreover, the uncertainty of DRPs is considered by Markov chain. The large consumer also could sign bilateral contracts with generation companies to provide a portion of its required electricity demand. The simulation results confirm the effectiveness of the Z‐number methodology in comparison with other techniques for handling the uncertainties. [ABSTRACT FROM AUTHOR]

The Monte‐Carlo (MC) method for generating stochastic scenarios to model uncertainty has a special role in research related to energy systems, but most studies have not provided a specific criterion for choosing an appropriate probability distribution function for using MC. This paper develops a new process for applying MC to improve uncertainty modelling based on Anderson‐Darling (AD), Kolmogorov‐Smirnov (KS), and Chi‐Square (CS) tests statistical. Moreover, three clustering algorithms of K‐means, Fuzzy c‐means, and Kantorovich distance matrix have been applied to reduce the generated scenarios. To evaluate the performance of the proposed process, a renewable energy hub involving electricity, heat, cooling, natural gas, and biomass fuel carriers, is used employing valid data. The results of numerical studies show that the quality of the scenarios in the proposed process based on statistical tests is much higher than the conventional method. Also, MC‐CS has been superior to the other two proposed methods in various seasons, so that, for example, in summer, its operating cost has decreased by 3% and 4% compared to MC‐KS and MC‐AD, respectively. [ABSTRACT FROM AUTHOR]

Many systems in the real world are periodic due to periodic phenomena in nature. Periodic hybrid stochastic differential equations are often used to model them. In many situations, it is inappropriate to study whether the solutions of periodic hybrid stochastic differential equations will converge to an equilibrium state (say, 0 or the trivial solution) but more appropriate to discuss whether the probability distributions of the solutions will converge to a stationary distribution, known as stability in distribution. This paper aims to determine whether or not a periodic stochastic state feedback control can make a given nonlinear periodic hybrid differential equation, which is not stable in distribution, to become stable in distribution. This problem will be referred to as stabilisation in distribution by periodic noise. There is little known on this problem so far. This paper initiates the study in this direction. [ABSTRACT FROM AUTHOR]

The paper develops an information‐theoretic model of induced technical change where payoff‐maximizing agents are exposed to a positive degree of uncertainty when adopting new technology due to unobserved cost factors. The derived equilibrium of the model comes in the form of a non‐degenerate probability distribution that defines the distance of productivity growth from the potential maximum growth on the innovation possibilities frontier, often called the technical inefficiency function (TIF) in the frontier estimation literature. Many forms of the TIF are shown to be derived by specifying a particular functional form of the payoff function in our model. The paper estimates the innovation possibilities frontier and the TIF using the KLEMS data for 1995–2015 and documents the time evolution and sectoral heterogeneity of the innovation possibilities frontier. [ABSTRACT FROM AUTHOR]