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Deep learning (DL) in remote sensing has nowadays become an effective operative tool: it is largely used in applications, such as change detection, image restoration, segmentation, detection, and classification. With reference to the synthetic aperture radar (SAR) domain, the application of DL techniques is not straightforward due to the nontrivial interpretation of SAR images, especially caused by the presence of speckle. Several DL solutions for SAR despeckling have been proposed in the last few years. Most of these solutions focus on the definition of different network architectures with similar cost functions, not involving SAR image properties. In this article, a convolutional neural network (CNN) with a multi-objective cost function taking care of spatial and statistical properties of the SAR image is proposed. This is achieved by the definition of a peculiar loss function obtained by the weighted combination of three different terms. Each of these terms is dedicated mainly to one of the following SAR image characteristics: spatial details, speckle statistical properties, and strong scatterers identification. Their combination allows balancing these effects. Moreover, a specifically designed architecture is proposed to effectively extract distinctive features within the considered framework. Experiments on simulated and real SAR images show the accuracy of the proposed method compared with the state-of-art despeckling algorithms, both from a quantitative and qualitative point of view. The importance of considering such SAR properties in the cost function is crucial for correct noise rejection and details preservation in different underlined scenarios, such as homogeneous, heterogeneous, and extremely heterogeneous. [ABSTRACT FROM AUTHOR]

Research into statistical distributions of φ, λ and two-dimensional (2D) position errors of the global positioning system (GPS) enables the evaluation of its accuracy. Based on this, the navigation applications in which the positioning system can be used are determined. However, studies of GPS accuracy indicate that the empirical φ and λ errors deviate from the typical normal distribution, significantly affecting the statistical distribution of 2D position errors. Therefore, determining the actual statistical distributions of position errors (1D and 2D) is decisive for the precision of calculating the actual accuracy of the GPS system. In this paper, based on two measurement sessions (900,000 and 237,000 fixes), the distributions of GPS position error statistics in both 1D and 2D space are analysed. Statistical distribution measures are determined using statistical tests, the hypothesis on the normal distribution of φ and λ errors is verified, and the consistency of GPS position errors with commonly used statistical distributions is assessed together with finding the best fit. Research has shown that φ and λ errors for the GPS system are normally distributed. It is proven that φ and λ errors are more concentrated around the central value than in a typical normal distribution (positive kurtosis) with a low value of asymmetry. Moreover, φ errors are clearly more concentrated than λ errors. This results in larger standard deviation values for φ errors than λ errors. The differences in both values were 25–39%. Regarding the 2D position error, it should be noted that the value of twice the distance root mean square (2DRMS) is about 10–14% greater than the value of R95. In addition, studies show that statistical distributions such as beta, gamma, lognormal and Weibull are the best fit for 2D position errors in the GPS system. [ABSTRACT FROM AUTHOR]

Image filters has taken attention last few years due to its importance in terms of image processing and applications. Applying image filters on images elements can be affected by the values of image parameters, which resulted from any processing tasks. By applying image filters, we can extent the image processing methods to present higher productivity. In this paper, we compare the effect of applying five image filters on the statistical distribution, which are (Laplacian, Differentiation, LOG, Sharpening, and Gaussian). Our method has been applied for a number of textural images (water texture, wool texture, and wood texture), the images has been divided for three groups according to the texture type. The result of our method proved that some of image filter affects the statistical distribution of image elements which are: (Differentiation, LOG, Sharpening) while other do not affect the parameter distribution (Laplacian, Gaussian). We evaluate our method by calculating the value of (MSE). The method opens the door in front of extending such technique with other image processing aspects. [ABSTRACT FROM AUTHOR]

Sampling plans are essential components to establish decision-making systems for integrated pest management (IPM) programs. Thus, this study was aimed to develop a conventional sampling plan of Tetranychus mexicanus (McGregor) (Tetranychidae) on the yellow passion fruit Passiflora edulis. The work was conducted in nine passion fruit fields with plants at the reproductive stage. Our results indicated that the sample, ideal area, and the technique for the evaluation of the mites in passion fruit were the second and third most apical leaves on the branches, the leaf blade on the abaxial surface near the petiole, and the directly counting the mites using a hand lens with 10× magnification, respectively. The density of T. mexicanus was adjusted to a negative binomial frequency distribution, and they present a common aggregation parameter (Kcommon = 0.5176), which made it possible to generate a sampling plan. The sampling plan consisted of 52 samples per field that took 39 minutes, and the cost of US $6.73 per sampling, respectively. Thus, the sampling plan developed in this study can be used by farmers in management programs for T. mexicanus in passion fruit crops by facilitating the accurate, representative and feasible sampling of this pest at the plant. [ABSTRACT FROM AUTHOR]

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Pathological articulation exploration, especially the study of the kinematic characteristics of motor organ, is helpful to further reveal the essence of motor dysarthria. Due to the scarcity of the available pathological pronunciation database, there has little research working on the statistic distribution analysis for patients and normal controlled people. This paper applied the distribution method on TORGO database to discover the cognitive and motor rules of dysarthria patients. Single phoneme analysis is effective for locating the specific tongue muscle but ignoring cognitive ability assessment, particularly for the content understanding and the fluency degree of expression by patients. The paper focused on the word/sentence level rather than single phoneme analysis. The reaction time was designed to reveal the relationship between the brain cognition and motor neuron activation. The statistic distribution tells that the cerebral palsy or amyotrophic lateral sclerosis does affect people's reflection and make the patients hard to control the tongue muscles effectively, resulting in unstable reaction time. The articulation velocity of patients appears 5mm/s faster than normal people, at 85mm/s, perhaps due to the factors of the word/sentence data and the big proportion of extra large displacement. It illustrates that the tongue moves relatively coherently and fluently once patients active the muscles, but hard to slow down as the muscle control ability decreases. The spatial occupancy was represented by the maximum articulation movement range (MAMR). We adapted the logarithmic normal distribution to find out the significant threshold for the diagnosis of dysarthria with the MAMR exceeding 7mm along left and right direction and the number of abnormal ranges surpassing 10% of total number. Primary test of MAMR, as an articulatory feature, for speech classification was carried out and it achieves 81% accuracy. These explorations convinced us to apply them to the pathological speech recognition task for improvement in future.

Brushes are critical components in power generation equipment. The interruptions in brush operation because they have failed in their service can cause financial losses avoidable by proper maintenance planning. Therefore, this article aims to offer a methodology for estimating the reliability parameter of brushes used in hydroelectric generators through machine learning concepts and through a statistical distribution compatible with complex phenomena. The method uses six selection patterns by graphical plotting of lifetimes and brush lengths to recognize problems of recording wear information. Then, the information is separated into three data sets according to the failure mode. The brushes reliability prediction uses an artificial neural network with assisted learning to predict a cumulative distribution function based on the operating time extracted from the equipment's hour meter. The method compares the statistical models q-Weibull, Weibull, q-exponential, and exponential with the prediction function. Three measures of goodness of fit were calculated, the logarithm of likelihood, coefficient of determination, and mean squared error. Most of the values found point to an advantage in the use of artificial neural networks over the use of the q-Weibull distribution. The method compares density and failure rate functions. The application of artificial neural networks in reliability analysis can have a significant impact on reducing maintenance costs, as it leads to results closer to reality. This article presents artificial neural networks for the first time compared to a distribution based on non-extensive statistical mechanics in the context of hydroelectric brushes.

Complex load and haul cycles in mining are composed of individual steps, whose times could be better described by a statistical distribution than by the average value. In order to evaluate how loading times and dumping times behave, this paper tested a large dataset of loading and dumping times measured at an open pit limestone mine in Brazil against the distributions most commonly used to model these variables, Log-normal and Normal; as well as Gamma, Logistic, Weibull and Exponential distributions. None of the tested distributions provided statistically significant adherence to the data, but it was possible to identify that for most equipment, Logistic and Normal distributions would produce less error on stochastic modelling then the other tested distributions. [ABSTRACT FROM AUTHOR]

In this letter, the weighted fractional Fourier transform (WFRFT) is performed on the chaotic sequence to enhance the security of the chaotic direct sequence spread spectrum (CD3S) communication, and a WFRFT-CD3S system that spreads the information bits through the WFRFT-chaotic sequence is proposed. In the proposed system, the transmitter scrambles the phase space trajectory of the chaotic sequence through WFRFT and make the distribution of the transmitted signal be Gaussian-like. The receiver synchronizes the WFRFT-chaotic sequence through bidirectional correlation search and demodulates the information through the synchronized local WFRFT-chaotic sequence. Simulations are implemented to evaluate the security performance, synchronization performance, and demodulation performance of the proposed system. [ABSTRACT FROM AUTHOR]

We perform a statistical analysis of magnetosonic (MS) waves in the slot region based on Van Allen Probes observations from September 2012 to February 2018. Our results demonstrate that the wave occurrence rate increases with enhanced geomagnetic activity and decreasing magnetic latitude, with the presence of strongest slot region MS waves near the geomagnetic equator within the 08–20 magnetic local time sector. Power spectral densities of slot region MS waves also intensify during geomagnetically active times, with the occurrence of the major wave power (>∼10−5 nT2/Hz) below ∼25fcp (where fcp is the proton gyrofrequency) and the peak wave intensity (∼10−3 nT2/Hz) below ∼5fcp at L > ∼2.6. A remarkable gap in the MS wave frequency spectrum is also revealed at <∼15fcp during weak substorm activities (AE ≤ 300 nT). Plain Language Summary: Various plasma waves have been involved in the slot region electron dynamics, among them, magnetosonic (MS) waves have acquired intensive attention due to their underlying effects on energetic electrons. Using high‐quality wave measurements from Van Allen Probes during the period from September 2012 to February 2018, we statistically investigate the global distribution and spectral characteristics of MS waves in the slot region (1.8 ≤ L ≤ 3.0). We found that MS waves preferentially occur at low magnetic latitudes from the dawnside to the duskside under strongly disturbed geomagnetic conditions. Strongest MS waves exist near the geomagnetic equator within 08–20 magnetic local time sector. With the enhancement of geomagnetic activity, the increasing magnetic field power spectral densities of MS waves show the presence of the major wave power spectra (>∼10−5 nT2/Hz) below ∼25fcp (where fcp is the proton gyrofrequency) and the largest wave intensity (∼10−3nT2/Hz) below ∼5fcp at L > ∼2.6. We also found a remarkable gap in the slot region MS wave frequency spectrum at frequencies below ∼15fcp. Our results provide important clues for understanding the excitation and propagation mechanism of slot region MS waves and their potential contributions to the slot region electron dynamics under various geomagnetic conditions. Key Points: The spatial and spectral distributions of magnetosonic (MS) waves in the slot region are statistically investigatedStrong MS waves in the slot region mainly occur within ∼6° of the geomagnetic equator over the 08–20 magnetic local time sectorA remarkable gap in the MS wave frequency spectrum is found at low proton gyrofrequency harmonics during weak substorm activities [ABSTRACT FROM AUTHOR]

Advanced loss characterizations of power semiconductor devices are becoming crucial for the reliability evaluation and improvement of power electronics systems. In this letter, a method based on an H-bridge testing circuit is proposed to reveal the statistical distribution of switching energy and on-state voltage of power semiconductor devices. This method includes a specially designed testing sequence for multiple devices under test, as well as the statistical representation of loss-related characteristics. By the proposed method, the loss-related characteristics of multiple transistors and freewheeling diodes can be evaluated in multiple times, and the testing conditions are closer to the working conditions of devices in practical use compared to the conventional double-pulse test. Based on the experimental results, the probability density function for the switching energy and on-state voltage can be further generated, which enables more correct prediction for the thermal and reliability performances of power semiconductor devices. [ABSTRACT FROM AUTHOR]

The estimation of precipitation data is very important while designing buildings in cities. Because of fast response of rainfall-runoff in urban areas, the stormwater infrastructure systems are developed. Especially in flood prone areas which have flash flood risks, the total precipitation, its return period and its duration should be known. For this aim, statistical distributions of long-term observed precipitation data can be determined. In this study, Antalya district which is near the Mediterranean Sea is selected as study area. The city is very crowded touristic place with more than 2.5 million local people. Antalya is one of the warmest regions in Turkey with an average daily high temperature of 25 degrees centigrade. In 6 months, the average temperatures are over 25 degrees. In the study, the best statistical distributions of precipitation data from the gauging stations near Antalya are investigated. KolmogorovSmirnov test is applied to select the best statistical distribution.

Offshore wind energy has seen dynamic growth in Europe in recent years and this is mirrored in the ambitious strategic plans for the Polish market. This article deals with selected regulatory and market aspects related to the construction of offshore wind farms in the Polish area of the Baltic Sea. Using wind speed measurements, statistical power distributions were obtained for an exemplary wind farm located in the southern Baltic. Analysis was carried out for data collected at an altitude of 102 m over a ten year period. Using Balancing Market data, the Value at Risk was estimated. The offshore results were compared with the calculations for an onshore wind farm for the selected year. The analysis shows the potential of the Polish area of the Baltic Sea for generating renewable energy. • Polish strategic documents indicate ambitious plans for offshore wind energy. • Offshore wind farm produces more electricity in winter months and evening/night hours. • Significant differences in offshore wind farm generation between years are observed. • Correlation between generation in onshore and offshore wind farms can be noted. • The analysis shows the wind power potential in the Polish area of the Baltic Sea. [ABSTRACT FROM AUTHOR]

Since the Paris Agreement in 2015, the greenhouse gas (GHG) inventory has been considered as an indicator in the evaluation of national GHG reduction. Despite the importance of achieving and evaluating the national GHG reduction targets by the local government, GHG information availed to local governments is very limited, thus necessitating the use of additional resources to create a GHG inventory for each region. This study established and introduced procedures for the selection and distribution of activity data using a national inventory to allow for the estimation of emission values according to region and used them to calculate emissions in Korea. Statistics that were not based on regional data or those based on different data collection systems were identified, and in such cases, data required improvement to achieve consistency. Emission estimation showed that the applied activity data was consistent with the sum of the regional and national values for 12% of GHG emissions. We expect the improvement of certain statistical data to improve data consistency to 82% within a ± 5% variance. With this method, the consistency between the emission data at the national and local or regional levels can be ensured, and ultimately used to establish or evaluate the implementation of a GHG reduction plan. The proposed method can be particularly useful when capacity enhancement of local governments in developing countries is required for GHG inventory management. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Utilizing inner‐crystal piezoelectric polarization charges to control carrier transport across a metal‐semiconductor or semiconductor–semiconductor interface, piezotronic effect has great potential applications in smart micro/nano‐electromechanical system (MEMS/NEMS), human‐machine interfacing, and nanorobotics. However, current research on piezotronics has mainly focused on systems with only one or rather limited interfaces. Here, the statistical piezotronic effect is reported in ZnO bulk composited of nanoplatelets, of which the strain/stress‐induced piezo‐potential at the crystals' interfaces can effectively gate the electrical transport of ZnO bulk. It is a statistical phenomenon of piezotronic modification of large numbers of interfaces, and the crystal orientation of inner ZnO nanoplatelets strongly influence the transport property of ZnO bulk. With optimum preferred orientation of ZnO nanoplatelets, the bulk exhibits an increased conductivity with decreasing stress at a high pressure range of 200–400 MPa, which has not been observed previously in bulk. A maximum sensitivity of 1.149 µS m−1 MPa−1 and a corresponding gauge factor of 467–589 have been achieved. As a statistical phenomenon of many piezotronic interfaces modulation, the proposed statistical piezotronic effect extends the connotation of piezotronics and promotes its practical applications in intelligent sensing. [ABSTRACT FROM AUTHOR]

Though numerous studies have investigated optimal locations for biorefineries given the availability of feedstock supplies, few have considered that these supplies could vary over time, thereby potentially failing to meet feedstock requirements. In this paper, we develop a process for identifying a shortlist of five potentially viable biorefinery sites in Alberta, and then consider the stochastic nature of these supplies, and what that variation could mean for supplying a biorefinery. A shortlist of sites was selected based on agricultural residues within a distance of 80 km of the site. Across all sites, a total amount of 16.7 million t [oven dried] y−1 is found to be economically accessible in the province. However, this shortlist is based only on a summation of one-year crop yields surrounding the sites. When crop yield variability (estimated from data over 40 years between 1978 and 2017) is also considered, substantially different results were found. For example, if supply was required to exceed 1.59 million t [oven dried] y−1, 95% of the time, then two selected sites, which were chosen based on one-year crop yields, must be excluded. Under these circumstances the total amount available across sites falls to 12.4 million t [oven dried] y−1. Overall, when variability in supply is included as a criterion, site selection and rankings change, suggesting that site selection using only an average or point estimate is not sufficient. Instead, more sophisticated techniques to investigate feedstock supply variability would be useful. • Economic accessibility of agricultural residues can vary substantially over time. • Selecting biorefinery locations based on one year of data is misleading. • Modelling stochastic feedstock supplies can improve biorefinery siting decisions. [ABSTRACT FROM AUTHOR]

For prognostics in industrial applications, the degree of anomaly of a test point from a baseline cluster is estimated using a statistical distance metric. Among different statistical distance metrics, energy distance is an interesting concept based on Newton’s Law of Gravitation, promising simpler computation than classical distance metrics. In this paper, we review the state of the art formulations of energy distance and point out several reasons why they are not directly applicable to the anomaly-detection problem. Thereby, we propose a new energy-based metric called the P-statistic which addresses these issues, is applicable to anomaly detection and retains the computational simplicity of the energy distance. We also demonstrate its effectiveness on a real-life data-set.

Abstract Knowledge of particulate system properties is very important in various industrial instances and the possibility of fast predicting the behavior of such systems is an important control tool. The specific surface area of simulated particulate systems was studied as a function of the sharpness parameter of the size distribution of the Gates–Gaudin-Schumann, Gaudin–Meloy and Rosin–Rammler equations. The results showed good statistical adherence, especially the Rosin–Rammler equation, in situations where it is the best descriptor of particle size distribution.

Wire and arc additively manufactured (WAAM) parts and structures often present internal defects, such as gas pores, and cause irregularities in the manufacturing process. In order to describe and assess the effect of internal defects in fatigue design, this research study investigates the fatigue strength of wire arc additive manufactured structures covering the influence of imperfections, particularly gas pores. Single pass WAAM structures are manufactured using titanium alloy Ti-6Al-4V and round fatigue, tensile specimen are extracted. Tensile tests and uniaxial fatigue tests with a load stress ratio of R = 0.1 were carried out, whereby fatigue test results are used for further assessments. An extensive fractographic and metallographic fracture surface analysis is utilized to characterize and measure crack-initiating defects. As surface pores as well as bulk pores are detected, a stress intensity equivalent ∆Keqv transformation approach is presented in this study. Thereby, the defect size of the surface pore is transformed to an increased defect size, which is equivalent to a bulk pore. Subsequently, the fatigue strength assessment method by Tiryakioğlu, commonly used for casting processes, is applied. For this method, a cumulative Gumbel extreme value distribution is utilized to statistically describe the defect size. The fitted distribution with modified data reveals a better agreement with the experimental data than unmodified. Additionally, the validation of the model shows that the usage of the ∆K modified data demonstrates better results, with a slight underestimation of up to about −7%, compared to unmodified data, with an overestimation of up to about 14%, comparing the number of load cycles until failure. Hence, the presented approach applying a stress intensity equivalent transformation of surface to bulk pores facilitates a sound fatigue strength assessment of WAAM Ti-6Al-4V structures.

Introduction: Air pollution in the metropolis of Tehran is a serious environmental issue. Assigning an optimal budget to deal with air pollution problems in the East (no.4) and West (no.22) regions of Tehran, determining the optimal proportion of green spaces and determining the ratio of applying optimal traffic constraints in these two regions, and addressing similar problems, are all necessary and require a statistical optimization scale for resolving them. Unfortunately, so far, no study has been done in this regard, and research on this issue is needed. The main purpose of this research is to investigate the difference between the air pollution in East and West of Tehran and provide a benchmark for responding to the above issues. Materials and methods: A new statistical approach has been proposed in this study for comparing air pollution in the East and West of Tehran, which eliminates the problems associated with conventional methods such as the t-test and nonparametric tests. In this method, the air pollution index values of the two regions have been modelled using a suitable statistical distribution and, then, the probability that air pollution in the East of Tehran would be more than in the western part of it would be reached through a Bayesian method. The value of this probability, called R, has been used as an optimal scale for allocating air pollution-related assets between the two regions. Results and discussion: Air pollution data was collected in the east and west of Tehran in the winter of 2016 in terms of air quality index (AQI) and was modelled using distributions with a power hazard function. The mean and standard deviations for air pollution data in the East of Tehran have been obtained as 76.70 and 37.074, respectively, and the corresponding statistics for the West of Tehran were 72.14 and 34.166, respectively. Although, the sample mean of AQI in the East of Tehran is a little greater than in the West, the nonparametric Mann-Whitney test shows that there is no significant difference between air quality of these two regions. The 95% Bayesian confidence interval of R has been obtained (0.594 and 0.436) and a Bayes estimate of R has been obtained at 0.519. According to the results, although there is no significant difference (at a confidence level of 95%) between the air pollution in the eastern and the western parts of the city, with a probability 0.519, the air in the East of Tehran was more polluted than the West. Also, this probability value is an optimal scale which can be applied to the appropriate allocation of facilities related to air pollution between the two regions. That is, 51.9% of facilities related to air pollution should be allocated to the East of Tehran and 48.1% should be allocated to its western part. Conclusion: It seems that the proper allocation of funds from different regions of Tehran to control Tehran's air pollution can be a step towards solving this problem. The statistical method presented in this study provides an optimal amount for allocating funds to the East and West of Tehran. Officials can use the optimal amount based on this method to create appropriate policies for the proper distribution of funds and facilities in East and West Tehran. For example, to maximize the effectiveness of tree-planting in air purification, with this proportion it is better to plant trees in the eastern part of the city more than in the western part. Also, it is suggested that traffic constraints in eastern Tehran should be greater than in the western part of it.

Herein, micromechanical material deformation behavior of medium carbon steel—with varying cementite particle size and distribution—under monotonic tensile load is modeled. The statistical phase morphology data are collected from the microscopy images of 83% spheroidized C45EC steel. Virtual microstructures for nine different cases are constructed using Dream.3D by varying the concentrations of small, large, and bimodal cementite particles on the ferrite grain boundaries. A crystal plasticity‐based numerical simulation model, i.e., DAMASK, is used to simulate the local material deformation behavior. The material model parameters for elastic–plastic ferrite and elastic cementite phases are adopted from the literature and calibrated by modifying the fitting parameters to match the experimentally observed material flow curve. It is observed that the cementite particle size and distribution in the primary phase affect the local mechanical behavior of the material. An analysis of deformation at 20% of global strain has helped in the qualitative understanding of factors affecting the stress and strain concentration points. The evolution of stresses and strains in the least and the most stressed representative volume elements (RVEs) has provided interesting information regarding the path followed by the dislocation movement during deformation. The study has provided insight into the factors affecting the material's global and local deformation behavior. [ABSTRACT FROM AUTHOR]

In this paper, we performed a series of measurement campaigns on the wireless electromagnetic noise for two typical industrial welding scenarios. On this basis, we investigate the characterization of the impulsive noise mainly from two aspects, that is, frequency and time domains. To start with, a novel denoising method based on the dynamic threshold is proposed to identify the desirable impulse noise from the background noise. Then, in the frequency domain, we focus on the power distribution of impulsive noise at different frequency bands. Results exhibit a shadow effect with regard to different frequency bands and we characterize it by using a linear function with a Gaussian distribution. Besides, analyses on the power spectrum correlation for different polarization modes and scenarios are also provided. In the time domain, we performed a series of statistical analyses from aspects of pulse amplitude, duration, and elapse interval to characterize the impulsive noise. Furthermore, three empirical distributions are employed to depict the parameters' variation tendency, that is, Cauchy distribution for amplitude, Gamma distribution for pulse duration, and exponential distribution for pulse interval. Finally, a first‐order two‐states Markov method is proposed to model the industrial noise. Simulation results are proved to be consistent with the actual measured results in terms of the amplitude distribution. [ABSTRACT FROM AUTHOR]

We present a survey of the bifurcation of the Earth's energetic electron belt (tens of keV) using 6‐year measurements from Van Allen Probes. The inner energetic electron belt usually presents one‐peak radial structure with high flux intensity at L < ∼2.5, which however can be bifurcated to exhibit a double‐peak radial structure. By automatically identifying the events of bifurcation based on Radiation Belt Storm Probes Ion Composition Experiment data, we find that the bifurcation is mostly observed at ∼30–100 keV with a local flux minimum at L = ∼2.0 to ∼2.3 under relatively quiet geomagnetic conditions, typically after a significant flux enhancement due to radial diffusion or injections to L < ∼2.5. The bifurcation typically lasts for a few days during quiet periods until interrupted by injections or radial diffusion. The L‐shell, energy, and seasonal dependences of the occurrence of bifurcated inner electron belt support the important role of electron scattering by very low‐frequency transmitter waves in the bifurcation formation. Plain Language Summary: The Earth's inner energetic electron belt typically exhibits one‐peak radial structure with high flux intensities at radial distances < ∼2.5 Earth radii. Recent studies suggested that human‐made very low‐frequency (VLF) transmitters leaked into the inner magnetosphere can efficiently scatter energetic electrons, bifurcating the inner electron belt. In this letter, we use 6‐year electron flux data from Van Allen Probes to comprehensively analyze the statistical distributions of the bifurcated inner electron belt and their dependence on electron energy, season, and geomagnetic activity, which is crucial to understand when and where VLF transmitters can efficiently scatter electrons in addition to other naturally occurring waves. We reveal that bifurcation can be frequently observed for tens of keV electrons under relatively quiet geomagnetic conditions, typically after significant flux enhancements that elevate fluxes at L = 2.0 to ∼2.5 providing the prerequisite for the bifurcation. The bifurcation typically lasts for a few days until interrupted by substorm injections or inward radial diffusion. The L‐shells of bifurcation dip decrease with increasing electron energy, and the occurrence of bifurcation is higher during Northern Hemisphere winter than summer, supporting the important role of VLF transmitter waves in energetic electron loss in near‐Earth space. Key Points: Statistics of bifurcated inner energetic electron belt is investigated using 6‐year Van Allen Probes measurementsThe bifurcated inner belt is mostly observed at ∼ 30–100 keV with the bifurcation dip at L ∼ 2.0–2.3 under quiet geomagnetic conditionsEnergy and seasonal dependences of the inner belt bifurcation support the important role of VLF transmitter signals in its formation [ABSTRACT FROM AUTHOR]

Investigating travel time distribution and associated variability is important for a variety of transport planning, traffic management, and control projects. Studies that investigated travel time distribution tend to be limited to explore changes in characteristics of distribution with respect to space and time of day. Given the availability of big dataset that contains seven different types of vehicle trajectories in the city of Athens for around 56,000 trips which are traversing on more than 1.8 million road links, this study presents the detailed investigation of travel time distribution in different spatiotemporal settings. The study considered four different types of urban roads and six time intervals along with consideration of weekdays and weekends. The empirical investigation employed Kruskal-Wallis, Chi-square, and Kolmogorov-Smirnov tests to fit travel time data into seven unimodal statistical distributions that are found in the literature to describe travel time distribution. It is found that lognormal distribution outperformed other distribution, and all of the considered categories of travel time data are well-fitted to this distribution. Additionally, parameters of lognormal distribution for different categories of travel time data are not significantly different from each other, which led to the conclusion that travel time distribution is roughly independent of space and time, which is in agreement with a few earlier studies that are limited in their scope especially in relation with availability of data. With this important finding, this study estimate values of travel time variability for different classes of individuals employing a standard approach that requires time of day independent standardized distribution of travel time. It is estimated that for Athens population value of travel time variability is approximately half of the value of travel time. This is useful to carry out cost-benefit analyses for mobility-related projects in Athens, Greece. [ABSTRACT FROM AUTHOR]

This paper proposes, a novel hybrid color component (HCC) issued from amounts number of color space with iterative manner, in fact traditional images obtained by RGB sensor weren't the effective way in image processing applications, for this purpose we have propose a supervised algorithm to substitute RGB level by hybrid and suitable color space at the aim to make well representation of the handled amounts of data, this step is extremely important because the obtained results it will be injected in many future studies like tracking, classification, steganography and cryptography. The second part of this paper consists to segment image coded in hybrid color space already selected, the used algorithm is inspired from kernel function where statistical distribution was used to model background and Bayes rule to make decision of the membership of each pixel, in this research topics we have extended this algorithm in the aim to improve compactness of these distribution. Cauchy background modeling and subtraction is used, and shows the high accuracy of automatic player detection. [ABSTRACT FROM AUTHOR]

The crack widths in reinforced concrete structures are affected by various influencing parameters, such as the tensile strength of the concrete, which is a highly variable parameter. While safe predictions of crack widths are possible with the existing models supplied in the code provisions accompanied by suitable safety factors, there are large discrepancies between the experimentally measured crack widths and the calculated values. Even within a uniaxial tensile test on reinforced concrete components, several crack parameters (spacings and widths) are usually measured. To further investigate the effects of scattering input parameters on the distribution of crack parameters, a crack propagation model (CPM) is developed, which is a powerful tool that can be used to observe sequential cracking of uniaxially loaded reinforced concrete components. In the present paper, the background of the scattering of the concrete tensile strength will be explained and the procedure for the simulation in the CPM, including the investigation of different bond–slip relationships, will be introduced. Finally, the CPM will be used to calculate experimental crack parameters and the distribution of the calculated crack parameters will be discussed. [ABSTRACT FROM AUTHOR]

This paper presents a statistical study on the AC Breakdown Voltage (BDV) of Refined, Bleached and Deodorized Palm Oil (RBDPO) olein under the influence of moisture. Different moisture contents of the RBPDPO were prepared by drying the RBDPO in the oven at different time intervals. The AC BDV test of RBDPO was performed whereby the distance between 2 electrodes was set to 1 mm. The statistical analyses of AC BDV data for RBDPO were carried out based on normal, lognormal and Weibull distributions. It was shown that as the moisture content increased, the AC BDV of RDBPO decreased exponentially. Statistical analyses revealed that the AC BDV data with different moisture contents had platykurtic distributions. Moisture could influence the skewness of the distribution whereby the tail shifted from right to left as the content increased. At different moisture contents of RBDPO, most of the AC BDV data of RBDPO could be represented by Weibull distribution. [ABSTRACT FROM AUTHOR]

Recently, various forms of extended beta function have been proposed and presented by many researchers. The principal goal of this paper is to present another expansion of beta function using Appell series and Lauricella function and examine various properties like integral representation and summation formula. Statistical distribution for the above extension of beta function has been defined, and the mean, variance, moment generating function and cumulative distribution function have been obtained. Using the newly defined extension of beta function, we build up the extension of hypergeometric and confluent hypergeometric functions and discuss their integral representations and differentiation formulas. Further, we define a new extension of Riemann–Liouville fractional operator using Appell series and Lauricella function and derive its various properties using the new extension of beta function. [ABSTRACT FROM AUTHOR]

The application of proved statistical and geostatistical techniques is a useful tool to create introductory overviews of the distribution of geogene or planetogene features defined by their topographic position (punctual occurrences). The methodological approach can be transferred to analyse the distribution of any punctual structures such as craters on planetary surfaces, terrestrial volcanoes, calderas, sinkholes, cenotes, glacial kettle holes, springs and lakes regardless of their shape, size, age, genetic aspects and regardless of the size of the studied area or of the scale of the used map as well. The meteoritic craters on the Mercury were applied for a case study. The terrestrial planet Mercury is well explored by NASA missions. Its surface shows a large number of meteoritic impacts and a few Planitia as extended basins. The Caloris Basin is one of the Planitia which covers the Hermean surface on the northern hemisphere. More than 10,000 recognisable meteoritic impact structures can be observed at the Caloris Basin. The frequency of occurrence has been registered at 225 equal quadratic cells without distinction of their age, size or shape. Gamma, negative-binomial and Weibull distributions are suitable to fit the empirical statistical crater density at a 0.05 significance level. The varying density of meteoritic impacts at the Caloris Basin (Mercury) is apparently determined as random with lower and medium densities dominant. A representation of the spatial pattern of impacts by a raster grey scale map is too rough as to result in detailed information. The spatial distribution of craters per cell is visualised by Ordinary Kriging and shows a high irregularity and remarkably changes between nearby low and high crater densities. Trend surface analysis indicates a slight increase in impact density towards the south and shows a general SW-NE striking zone of a lower crater density beside two maximums in the SE and NW area but these tendencies are statistically not significant. The predominant variation between all cells seems to be caused by long-term random impact processes. [ABSTRACT FROM AUTHOR]

This Letter reports the multilevel resistive switching characteristics of bipolar bi‐layer nanodevice made of Ag/Al2O3(10 nm)/ZnO (5 nm)/fluorine‐doped tin oxide for the first time, exhibiting five distinguishable resistive states including both high resistance state (HRS) and low resistance state (LRS). Among five distinct memory states, three resistive states are attained with RESET voltages and two are attained with SET voltages. The distinguishable resistive levels obtained with RESET voltages 2.3, 3.0 and 3.8 V are 1300, 2700 and 4320 Ω, respectively, whereas two stable resistive levels attained with SET voltages 0.8 and 1.70 V are 3000 and 100 Ω, respectively. Moreover, the proposed device excels in its Roff/Ron ratio of 354 obtained with HRS/LRS at −1.4 V as well as the ratio of intermediate states IRS1, IRS2, IRS3 to HRS becomes 15, 04 and 27, respectively. Further, the conduction mechanism as well as the switching mechanism are demonstrated. Finally, the cycle‐to‐cycle as well as device‐to‐device variability in device characteristics and statistical distribution of their resistance levels are also analysed and report that devices in the sample are also exhibiting stable multilevel capability. [ABSTRACT FROM AUTHOR]

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ITS-2 is one of the latest synthetic unit hydrograph-based flood estimation models in Indonesia. Developed at the Institut Teknologi Sepuluh Nopember (ITS) Surabaya in 2017, the basic parameters of the model were formulated using fractal and morphometric charac- teristics of eight observed river basin in Central Sulawesi, Indonesia. The fundamental concern with developing this model is how to derive a curve equation which illustrates the shape of the hydrograph. This paper aims to formulate this equation using the 2-parameter Gamma distribution, one of the statistical distribution model that is widely used for hydrological modeling especially hydrographs. The derivation of the equation was carried out by simplifying the parameters of the Gamma function which corresponds to the shape of the hydrograph such as the rising limb, peak and, recession limb. This research has succeeded in formulating an equation of dimensionless synthetic unit hydrograph curve expressed by the ratio of time (T) and peak time (Tp) of the hydrograph. A coefficient of C3 states that the hydrograph shape parameters can be optimized to improve model performance, when a series of observation discharge is available for calibration. The performance of the synthetic unit hydrograph equation was assessed using Mean Absolute Percentage Error (MAPE) and the Coefficient of correlation (r ). The analysis results based on a series of verification indicated that the performance of the hydrograph equation was very high with MAPE below 20% and a r above 0.8. [ABSTRACT FROM AUTHOR]

The optimization of the aeronautical structure manufacturing is a challenging task in the development of a new aircraft. To date, aeronautical industries are funding research about new assembly approaches based on cost reduction and increased efficiency of the assembly processes. The work here presented focused on an innovative assembly method based on the integration between statistical methods of tolerance prediction and the determinant assembly approach. The coupling tolerances between airframe components are predicted through statistical approach in order to reduce the features manufactured in assembly. This aspect contributes to a reduction of the costs due non-recurring costs. The method proposed has been tested on a dedicated case study developed in the frame of the "integrated main landing gear box" project on the CleanSky2 Research program. Tests have been conducted to check the consistency of the method and its feasibility in the industrial contexts in the case of flat-shaped component. The performed experiments confirmed the analytical study. [ABSTRACT FROM AUTHOR]

Price fluctuation is a random walk and the resulting statistical distribution is Gaussian. This is the starting point of financial engineering to derive, for example, the Black-Sholes Formula for derivative prices. On the other hand, it is widely known that the real price time series are not Gaussian, and the resulting statistical distribution has 'fat' tails at the both tails of the distribution. In order to solve this problem, new knowledge and deep insight are called for. In this article, we report our new discovery in the ultra-high speed transactions of a stock index named TOPIX at every second in the period of 2010-2019. [ABSTRACT FROM AUTHOR]

Species sensitivity distributions (SSDs) estimated by fitting a statistical distribution to ecotoxicity data are indispensable tools used to derive the hazardous concentration for 5 % of species (HC5) and thereby a predicted no-effect concentration in environmental risk assessment. Whereas various statistical distributions are available for SSD estimation, the fundamental question of which statistical distribution should be used has received limited systematic analysis. We aimed to address this knowledge gap by applying four frequently used statistical distributions (log-normal, log-logistic, Burr type III, and Weibull distributions) to acute and chronic SSD estimation using aquatic toxicity data for 191 and 31 chemicals, respectively. Based on the differences in the corrected Akaike's information criterion (AICc) as well as visual inspection of the fitting of the lower tails of SSD curves, the log-normal SSD was generally better or equally good for the majority of chemicals examined. Together with the fact that the ratios of HC5 values of other alternative SSDs to those of log-normal SSDs generally fell within the range 0.1–10, our findings indicate that the log-normal distribution can be a reasonable first candidate for SSD derivation, which does not contest the existing widespread use of log-normal SSDs. [Display omitted] • Acute and chronic species sensitivity distributions (SSDs) were estimated. • Four statistical distributions frequently used were compared for ∼200 chemicals. • Log-normal SSD performed generally better or equally well in terms of prediction. • Ratios of HC5 of other SSDs to log-normal SSDs generally fell within 0.1–10 range. • Log-normal distribution is suggested as a reasonable first choice for deriving SSDs. [ABSTRACT FROM AUTHOR]

This work presents an experimental—analytical study of the possibility of applying the method of the greatest probability to evaluate the sensitive thresholds of the bottom (N0) and top (Nk) of the statistical distribution of the mechanical structural characteristics. For the structural materials alloyed steel 15Cr2MoVA, steel C45 and aluminium alloy D16T1, the statistical distribution of proportional limit, yield strength, ultimate tensile strength, reduction in area, cyclic stress was estimated, as well as the following statistical parameters: mathematical mean, average square deviation, dispersion, asymmetry, variation coefficient, and excess. Purpose: to determine whether the limits of the sensitivity of the statistical distribution of the mechanical characteristics have been computed using the maximum likelihood method. Value: there is a certain upward and downward flattening of the probability curves in the statistical distribution curves of the fatigue test results. This implies that the chosen law of the distribution of random variables has an effect on the appearance of errors. These errors are unacceptable given the importance of accurately determining the reliability and durability of transport means, shipbuilding, machinery, and other important structures. Our results could potentially explain why sensitive limits cannot be applied to the statistical distribution of the mechanical characteristics of structural materials.

The ability to predict material removal rates in chemical mechanical planarization (CMP) is an essential ingredient for low cost, high quality IC chips. Recently, models that address the slurry particles have been proposed. We address three such models. The first two differ only in how the number of active particles is computed. Both assume that pad asperities are identical and nonrandom. The third is dynamic in accommodating changing pad properties. For larger mean particle size (diameter), the role of the standard deviation of particle size distribution is uncertain. The dynamic behavior of the third model is compared with experimental observations.

This paper presents a statistical modeling approach of the real-life user-induced randomness due to mobile phone orientations for different phone usage types. As well-known, the radiated performance of a wireless device depends on its orientation and position relative to the user. Therefore, realistic handset usage models will lead to more accurate over-the-air characterization measurements for antennas and wireless devices in general. We introduce a phone usage classification based on the network access modes, e.g., voice (circuit switched) or non-voice (packet switched) services, and the use of accessories, such as wired or Bluetooth handsets, or a speaker-phone during the network access session. The random phone orientation is then modeled by the spherical von Mises-Fisher distribution for each of the identified phone usage types. A finite mixture model based on the individual probability distribution functions and heuristic weights is also presented. The models are based on data collected from built-in accelerometer measurements. Our approach offers a straightforward modeling of the user-induced random orientation for different phone usage types. The models can be used in the design of better handsets and antenna systems as well as for the design and optimization of wireless networks.

Analysis of the patterns formed during the drying of biological fluids is employed for research and diagnosis in medicine and agriculture. Saline solutions of native proteins and DNA are characterized by zigzag patterns, which could be quantitatively described using the specific length of zigzags Lspecific. The aim of this study was to analyze a wide number of characteristics in order to identify those most sensitive to the effects of various physical and chemical factors on the protein structure. We examined the films prepared from salt solutions of bovine serum albumin (BSA) under varying conditions, viz.: a proportional change in the concentration of the components, substitution of NaCl with NaF and NaBr, temperature treatment, gamma irradiation, and addition of trivalent iron and biologically active flavin mononucleotide. The results revealed that the distribution of zigzag segment lengths was approximately lognormal, and the distribution of angles between the segments was approximately logistic. Two parameters appeared to be the most informative, viz. the average length of the segments, mainly depending on Cl– concentration, and the number of segments, depending on: Cl– concentration, concentration of the non-aggregated (but not necessarily unfragmented) protein, and the excess concentration of ions and low molecular weight compounds.

In this study, a new concept of statistical distribution of payback period is calculated for AC–DC transmission and distribution asset expansion projects. For calculation of the payback period, uncertainty is considered with cost and benefit. The Gaussian distribution is considered for correlated input cost and benefit variates. For more examination point of view, the distribution of the payback period is calculated with different correlation coefficients between cost and benefit. The main advantage of this study is to draw the probability distribution function of the payback period in terms of cost and benefit because most of the industrialist are often interested in cost and benefit analysis of AC–DC transmission and distribution asset expansion projects. An example is considered for evaluation of the proposed model.