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Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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1

Gong, Jian, and Christopher J. Rutland. "PDF-Based Heterogeneous Multiscale Filtration Model." Environmental Science & Technology 49, no. 8 (April 9, 2015): 4963–70. http://dx.doi.org/10.1021/acs.est.5b00329.

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2

Kang, Ah, Young-Seob Jeong, Se Kim, and Jiyoung Woo. "Malicious PDF Detection Model against Adversarial Attack Built from Benign PDF Containing JavaScript." Applied Sciences 9, no. 22 (November 8, 2019): 4764. http://dx.doi.org/10.3390/app9224764.

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Intelligent attacks using document-based malware that exploit vulnerabilities in document viewing software programs or document file structure are increasing rapidly. There are many cases of using PDF (portable document format) in proportion to its usage. We provide in-depth analysis on PDF structure and JavaScript content embedded in PDFs. Then, we develop the diverse feature set encompassing the structure and metadata such as file size, version, encoding method and keywords, and the content features such as object names, keywords, and readable strings in JavaScript. When features are diverse, it is hard to develop adversarial examples because small changes are robust for machine-learning algorithms. We develop a detection model using black-box type models with the structure and content features to minimize the risk of adversarial attacks. To validate the proposed model, we design the adversarial attack. We collect benign documents containing multiple JavaScript codes for the base of adversarial samples. We build the adversarial samples by injecting the malware codes into base samples. The proposed model is evaluated against a large collection of malicious and benign PDFs. We found that random forest, an ensemble algorithm of a decision tree, exhibits a good performance on malware detection and is robust for adversarial samples.
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3

Vettoretti, Martina, Andrea Facchinetti, Giovanni Sparacino, and Claudio Cobelli. "A Model of Self-Monitoring Blood Glucose Measurement Error." Journal of Diabetes Science and Technology 11, no. 4 (March 16, 2017): 724–35. http://dx.doi.org/10.1177/1932296817698498.

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Background: A reliable model of the probability density function (PDF) of self-monitoring of blood glucose (SMBG) measurement error would be important for several applications in diabetes, like testing in silico insulin therapies. In the literature, the PDF of SMBG error is usually described by a Gaussian function, whose symmetry and simplicity are unable to properly describe the variability of experimental data. Here, we propose a new methodology to derive more realistic models of SMBG error PDF. Methods: The blood glucose range is divided into zones where error (absolute or relative) presents a constant standard deviation (SD). In each zone, a suitable PDF model is fitted by maximum-likelihood to experimental data. Model validation is performed by goodness-of-fit tests. The method is tested on two databases collected by the One Touch Ultra 2 (OTU2; Lifescan Inc, Milpitas, CA) and the Bayer Contour Next USB (BCN; Bayer HealthCare LLC, Diabetes Care, Whippany, NJ). In both cases, skew-normal and exponential models are used to describe the distribution of errors and outliers, respectively. Results: Two zones were identified: zone 1 with constant SD absolute error; zone 2 with constant SD relative error. Goodness-of-fit tests confirmed that identified PDF models are valid and superior to Gaussian models used so far in the literature. Conclusions: The proposed methodology allows to derive realistic models of SMBG error PDF. These models can be used in several investigations of present interest in the scientific community, for example, to perform in silico clinical trials to compare SMBG-based with nonadjunctive CGM-based insulin treatments.
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4

Haran, Duaa Yaseen, and Ahmed Abed AL-Kadhem Majhool. "Application of LES/PDF and RANS/PDF approaches for simulation of spray combustion." Al-Qadisiyah Journal for Engineering Sciences 14, no. 2 (July 13, 2021): 109–16. http://dx.doi.org/10.30772/qjes.v14i2.752.

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This paper is addressing of a coupling Large-eddy simulation (LES) and RANS turbulence models with mixture fraction/probability density function as a combustion model. The two models have been implemented to simulate ethanol-air spray combustion. The gas phase is described with the Eulerian approach while the liquid phase is designed using a Lagrangian framework. The LES/PDF approach is obtained statistically. The sub-grid scale energy equation is used with the LES/PDF approach. The numerical results are validated with experimental data. Both LES/PDF and RANS/PDF approaches are compared with the experimental data. The LES/PDF approach shows a good agreement in predicting the average gas temperature compared with RANS/PDF approach. The LES/PDF shows a better prediction of both turbulence intensity profiles and the vortices which are generated in the turbulent flow in comparison with the RANS/PDF approach.
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5

Enouy, Robert W., Andre J. A. Unger, and Rashid Rehan. "An advective-dispersive transport model for residential water consumption." Journal of Hydroinformatics 21, no. 4 (May 23, 2019): 607–23. http://dx.doi.org/10.2166/hydro.2019.130.

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Abstract This work applies an advective-dispersive framework to simulate utility-wide residential water consumption using the analogy of a continuum transport process. In this context, the advective-dispersive process describes how changes in real water price and seasonal weather variability influence water consumption distribution, which ultimately governs mean and total water consumption values. Water consumption response is measured using histogram data optimally fit using parametric probability density functions (PDF) that have consistent parametrization over the entire observation period. Median statistic denotes advection and prescribes location of the measurement-space PDF, while standard deviation combined with standard-score PDF denotes dispersion which provides the measurement-space PDF with scale and shape. Combining location, scale, and shape components produces a measurement-space PDF that represents the solution to advective-dispersive transport phenomena. We use a Taylor series expansion of the statistics that define the PDF along with curvilinear regression to develop constitutive relationships that define how location, scale, and shape of the PDF respond to price and weather information. This results in a fully parametrizing advective-dispersive process represented by a partial differential equation that provides a tool for anticipating the probability that households will experience water poverty or use excess amounts as price, weather, and policy considerations change through time. This approach is conducive to automation when combined with smart water metering.
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6

Zhou, Xiaodong, Tinghua Ai, Nina Meng, and Peng Xie. "A PDF Tile Model for Geographic Map Data." ISPRS International Journal of Geo-Information 8, no. 9 (August 27, 2019): 373. http://dx.doi.org/10.3390/ijgi8090373.

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Vector tile mapping is an important issue in web map research. At present, vector tile mapping requires the symbolization of geographic information, as supported by cartographic software, and the development of a corresponding symbolic database when web map services are provided for users. The development of PDF (portable document format) mapping makes it possible to use symbolized map data directly for web map services. This paper presents a PDF tile map model suitable for web map services, in order to provide a new solution for vector tile mapping. This paper details the construction and establishment method of the PDF tile map model and verifies that the model has the characteristics of a vector tile map and that this approach can provide web map services. In addition, this model has some other noticeable characteristics. First, the map service supported by this model does not require the support of cartographic software, and thus has low system software and hardware requirements. Second, the maps displayed in the service system can be directly used for high-quality map publishing. Third, the high popularity of the PDF format can promote the sharing of PDF tile maps and reduce the use threshold of ordinary users.
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7

Hong, Zuu-Chang, and Ming-Hua Chen. "Statistical Model of a Self-Similar Turbulent Plane Shear Layer." Journal of Fluids Engineering 120, no. 2 (June 1, 1998): 263–73. http://dx.doi.org/10.1115/1.2820643.

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A turbulence probability density function (pdf) equation model is employed to solve a self-similar turbulent plane shear layer. The proper similarity variable was introduced into the problem of interest to reduce the pdf equation into a spatially one-dimensional equation, which is still three dimensional in velocity space. Then the approximate moment method is employed to solve this simplified pdf equation. By the solutions of this equation, the various one-point mean quantities are immediatelly available. Agreement of the calculated mean velocity, turbulent energy and Reynolds stress with the available experimental data is generally satisfactory indicating that the pdf equation model and the moment method can quantitatively describe the statistics of free turbulence. Additionally, the balance of turbulence energy was calculated and discussed subsequently. It shows that the pdf methods are of more potential in revealing turbulence structure than conventional turbulence models.
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8

Bartlett, M. S., E. Daly, J. J. McDonnell, A. J. Parolari, and A. Porporato. "Stochastic rainfall-runoff model with explicit soil moisture dynamics." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 471, no. 2183 (November 2015): 20150389. http://dx.doi.org/10.1098/rspa.2015.0389.

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Stream runoff is perhaps the most poorly represented process in ecohydrological stochastic soil moisture models. Here we present a rainfall-runoff model with a new stochastic description of runoff linked to soil moisture dynamics. We describe the rainfall-runoff system as the joint probability density function (PDF) of rainfall, soil moisture and runoff forced by random, instantaneous jumps of rainfall. We develop a master equation for the soil moisture PDF that accounts explicitly for a general state-dependent rainfall-runoff transformation. This framework is then used to derive the joint rainfall-runoff and soil moisture-runoff PDFs. Runoff is initiated by a soil moisture threshold and a linear progressive partitioning of rainfall based on the soil moisture status. We explore the dependence of the PDFs on the rainfall occurrence PDF (homogeneous or state-dependent Poisson process) and the rainfall magnitude PDF (exponential or mixed-exponential distribution). We calibrate the model to 63 years of rainfall and runoff data from the Upper Little Tennessee watershed (USA) and show how the new model can reproduce the measured runoff PDF.
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9

Aljuneidi, Wassim Yassin, Yasser M. Jaamour, and Khaldoun Khorzom. "Approximating Shadowed Rician Model to Other Simpler Models." International Journal of Embedded and Real-Time Communication Systems 7, no. 1 (January 2016): 1–29. http://dx.doi.org/10.4018/ijertcs.2016010101.

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Shadowed Rician model is considered to be the most appropriate that is used to characterize the impairments seen in wireless channels, which suffer Line-Of-Sight (LOS) shadowing and small-scale fading. In this model, the Probability Density Function (PDF) of the Signal to Noise Ratio (SNR) per symbol needs numerical solutions to be evaluated. More than that, for some values of the fading parameters, the numerical solution converging too slowly, and so needs too much time to be evaluated. This is considered as a problem in real time applications where delay is a critical issue. In this paper, the authors present and prove approximations for Shadowed Rician model according to the values of the fading parameters, which are the Rice factor and the Shadowing standard deviation. With the proposed approximation, the required PDF could be written in intervals which make it easier to calculate at parameters values that causes slow converging.
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10

Zhou, Xiaodong, Chuncheng Yang, Nina Meng, and Peng Peng. "A Electronic Map Data Model Based on PDF." Proceedings of the ICA 1 (May 16, 2018): 1–5. http://dx.doi.org/10.5194/ica-proc-1-129-2018.

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In this paper, we proposed the PDFEMAP (PDF electronic map) that is a kind of new electronic map products aiming at the current situation and demand of the use of electronic map products. Firstly gives the definition and characteristics of PDFEMAP, followed by a detailed description of the data model and method for generating PDFEMAP, and finally expounds application modes of the PDFEMAP which feasibility and effectiveness are verified.
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11

Goldin, Graham M. "A priori investigation of the constructed PDF model." Proceedings of the Combustion Institute 30, no. 1 (January 2005): 785–92. http://dx.doi.org/10.1016/j.proci.2004.08.012.

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12

Zoller, Benjamin T., Mathias L. Hack, and Patrick Jenny. "A PDF combustion model for turbulent premixed flames." Proceedings of the Combustion Institute 34, no. 1 (January 2013): 1421–28. http://dx.doi.org/10.1016/j.proci.2012.05.053.

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13

Arbanas, Goran, Jinghua Feng, Zia J. Clifton, Andrew M. Holcomb, Marco T. Pigni, Dorothea Wiarda, Christopher W. Chapman, Vladimir Sobes, Li Emily Liu, and Yaron Danon. "Bayesian optimization of generalized data." EPJ Nuclear Sciences & Technologies 4 (2018): 30. http://dx.doi.org/10.1051/epjn/2018038.

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Direct application of Bayes' theorem to generalized data yields a posterior probability distribution function (PDF) that is a product of a prior PDF of generalized data and a likelihood function, where generalized data consists of model parameters, measured data, and model defect data. The prior PDF of generalized data is defined by prior expectation values and a prior covariance matrix of generalized data that naturally includes covariance between any two components of generalized data. A set of constraints imposed on the posterior expectation values and covariances of generalized data via a given model is formally solved by the method of Lagrange multipliers. Posterior expectation values of the constraints and their covariance matrix are conventionally set to zero, leading to a likelihood function that is a Dirac delta function of the constraining equation. It is shown that setting constraints to values other than zero is analogous to introducing a model defect. Since posterior expectation values of any function of generalized data are integrals of that function over all generalized data weighted by the posterior PDF, all elements of generalized data may be viewed as nuisance parameters marginalized by this integration. One simple form of posterior PDF is obtained when the prior PDF and the likelihood function are normal PDFs. For linear models without a defect this PDF becomes equivalent to constrained least squares (CLS) method, that is, the χ2 minimization method.
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14

Vidybida, Alexander. "Relation Between Firing Statistics of Spiking Neuron with Instantaneous Feedback and Without Feedback." Fluctuation and Noise Letters 14, no. 04 (November 9, 2015): 1550034. http://dx.doi.org/10.1142/s0219477515500340.

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We consider a class of spiking neuron models, defined by a set of conditions which are typical for basic threshold-type models like leaky integrate-and-fire, or binding neuron model and also for some artificial neurons. A neuron is fed with a point renewal process. A relation between the three probability density functions (PDF): (i) PDF of input interspike intervals ISIs, (ii) PDF of output interspike intervals of a neuron with a feedback and (iii) PDF for that same neuron without feedback is derived. This allows to calculate any one of the three PDFs provided the remaining two are given. Similar relation between corresponding means and variances is derived. The relations are checked exactly for the binding neuron model stimulated with Poisson stream.
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15

Abou-Ellail, M. M. M., and H. Salem. "A Skewed PDF Combustion Model for Jet Diffusion Flames." Journal of Heat Transfer 112, no. 4 (November 1, 1990): 1002–7. http://dx.doi.org/10.1115/1.2910471.

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A combustion model based on restricted chemical equilibrium is described. A transport equation for the skewness of the mixture fraction is derived. It contains two adjustable constants. The computed values of the mean mixture fraction (f) and its variance and skewness (g and s) for a jet diffusion methane flame are used to obtain the shape of a skewed pdf. The skewed pdf is split into a turbulent part (beta function) and a nonturbulent part (delta function) at f = 0. The contribution of each part is directly related to the values of f, g, and s. The inclusion of intermittency in the skewed pdf appreciably improves the numerical predictions obtained for a turbulent jet diffusion methane flame for which experimental data are available.
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16

Mortarini, L., and E. Ferrero. "A Lagrangian Stochastic Model for the concentration fluctuations." Atmospheric Chemistry and Physics Discussions 5, no. 3 (June 2, 2005): 3621–39. http://dx.doi.org/10.5194/acpd-5-3621-2005.

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Abstract. A Lagrangian Stochastic Model for the two-particles dispersion, aiming at simulating the pollutant concentration fluctuations, is presented. Three model versions (1-D, 2-D and 3-D) are tested. Firstly the ability of the model to reproduce the two-particle statistics in a homogeneous isotropic turbulence is discussed, comparing the model results with theoretical predictions in terms of the probability density function (PDF) of the particles separation and its statistics. Then, the mean concentration and its fluctuations are considered and the results presented. The influence of the PDF of the particle separation on the concentration fluctuations is shown and discussed. We found that the separation PDF in the inertial subrange is not gaussian and this fact influences the predicted concentration fluctuations.
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17

Mortarini, L., and E. Ferrero. "A Lagrangian Stochastic Model for the concentration fluctuations." Atmospheric Chemistry and Physics 5, no. 9 (September 23, 2005): 2539–45. http://dx.doi.org/10.5194/acp-5-2539-2005.

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Abstract. A Lagrangian Stochastic Model for the two-particles dispersion, aiming at simulating the pollutant concentration fluctuations, is presented. Three model versions (1-D, 2-D and 3-D) are tested. Firstly the ability of the model to reproduce the two-particle statistics in a homogeneous isotropic turbulence is discussed, comparing the model results with theoretical predictions in terms of the probability density function (PDF) of the particles separation and its statistics. Then, the mean concentration and its fluctuations are considered and the results presented. The influence of the PDF of the particle separation on the concentration fluctuations is shown and discussed. We found that the separation PDF in the inertial subrange is not gaussian and this fact influences the predicted concentration fluctuations.
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18

Rivlin, Yonatan, and Monika Pinchas. "Edgeworth Expansion Based Model for the Convolutional Noise pdf." Mathematical Problems in Engineering 2014 (2014): 1–19. http://dx.doi.org/10.1155/2014/951927.

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Recently, the Edgeworth expansion up to order 4 was used to represent the convolutional noise probability density function (pdf) in the conditional expectation calculations where the source pdf was modeled with the maximum entropy density approximation technique. However, the applied Lagrange multipliers were not the appropriate ones for the chosen model for the convolutional noise pdf. In this paper we use the Edgeworth expansion up to order 4 and up to order 6 to model the convolutional noise pdf. We derive the appropriate Lagrange multipliers, thus obtaining new closed-form approximated expressions for the conditional expectation and mean square error (MSE) as a byproduct. Simulation results indicate hardly any equalization improvement with Edgeworth expansion up to order 4 when using optimal Lagrange multipliers over a nonoptimal set. In addition, there is no justification for using the Edgeworth expansion up to order 6 over the Edgeworth expansion up to order 4 for the 16QAM and easy channel case. However, Edgeworth expansion up to order 6 leads to improved equalization performance compared to the Edgeworth expansion up to order 4 for the 16QAM and hard channel case as well as for the case where the 64QAM is sent via an easy channel.
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19

Tsai, Kuochen, Paul A. Gillis, Subrata Sen, and Rodney O. Fox. "A Finite-Mode PDF Model for Turbulent Reacting Flows." Journal of Fluids Engineering 124, no. 1 (April 25, 2001): 102–7. http://dx.doi.org/10.1115/1.1431546.

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The recently proposed multi-environment model, R. O. Fox, 1998, “On the Relationship between Lagrangian Micromixing Models and Computational Fluid Dynamics,” Chem. Eng. Proc., Vol. 37, pp. 521–535. J. Villermaux and J. C. Devillon, 1994, “A Generalized Mixing Model for Initial Contacting of Reactive Fluids,” Chem. Eng. Sci., Vol. 49, p. 5127, provides a new category of modeling techniques that can be employed to resolve the turbulence-chemistry interactions found in reactive flows. By solving the Eulerian transport equations for volume fractions and chemical species simultaneously, the local concentrations of chemical species in each environment can be obtained. Assuming micromixing occurs only in phase space, the well-known IEM (interaction by exchange with the mean) model can be applied to close the micromixing term. This simplification allows the model to use micromixing timescales obtained from more sophisticated models and can be applied to any number of environments. Although the PDF shape doesn’t change under this assumption, the interaction between turbulence and chemistry can be resolved up to the second moments without any ad-hoc assumptions for the mean reaction rates. Furthermore, the PDF shape is found to have minimal effect on mean reaction rates for incompressible turbulent reacting flows. In this formulation, a spurious dissipation term arises in the transport equation of the scalar variances due to the use of Eulerian transport equations. A procedure is proposed to eliminate this spurious term. The model is applied to simulate the experiment of S. Komori, et al., 1993, “Measurements of Mass Flux in a Turbulent Liquid Flow With a Chemical Reaction,” AIChE J., Vol. 39, pp. 1611–1620, for a reactive mixing layer and the experiment of K. Li and H. Toor, 1986, “Turbulent Reactive Mixing With a Series Parallel reaction: Effect of Mixing on Yield,” AIChE J., Vol. 32, pp. 1312–1320, with a two-step parallel/consecutive reaction. The results are found to be in good agreement with the experimental data of Komori et al. and the PDF simulation of K. Tsai and R. Fox, 1994, “PDF Simulation of a Turbulent Series-Parallel Reaction in an Axisymmetric Reactor,” Chem. Eng. Sci., Vol. 49, pp. 5141–5158, for the experiment of Li and Toor. The resulting model is implemented in the commercial CFD code, FLUENT,1 and can be applied with any number of species and reactions.
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20

Cuesta-Lazaro, Carolina, Baojiu Li, Alexander Eggemeier, Pauline Zarrouk, Carlton M. Baugh, Takahiro Nishimichi, and Masahiro Takada. "Towards a non-Gaussian model of redshift space distortions." Monthly Notices of the Royal Astronomical Society 498, no. 1 (August 6, 2020): 1175–93. http://dx.doi.org/10.1093/mnras/staa2249.

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ABSTRACT To understand the nature of the accelerated expansion of the Universe, we need to combine constraints on the expansion rate and growth of structure. The growth rate is usually extracted from 3D galaxy maps by exploiting the effects of peculiar motions on galaxy clustering. However, theoretical models of the probability distribution function (PDF) of galaxy pairwise peculiar velocities are not accurate enough on small scales to reduce the error on theoretical predictions to the level required to match the precision expected for measurements from future surveys. Here, we improve the modelling of the pairwise velocity distribution by using the Skew-T PDF, which has non-zero skewness and kurtosis. Our model accurately reproduces the redshift space multipoles (monopole, quadrupole, and hexadecapole) predicted by N-body simulations, above scales of about $10\, h^{-1}{\rm Mpc}$. We illustrate how a Taylor expansion of the streaming model can reveal the contributions of the different moments to the clustering multipoles, which are independent of the shape of the velocity PDF. The Taylor expansion explains why the Gaussian streaming model works well in predicting the first two redshift space multipoles, although the velocity PDF is non-Gaussian even on large scales. Indeed, any PDF with the correct first two moments would produce precise results for the monopole down to scales of about $10\, h^{-1}{\rm Mpc}$, and for the quadrupole down to about $30\, h^{-1}{\rm Mpc}$. An accurate model for the hexadecapole needs to include higher order moments.
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21

Golaz, Jean-Christophe, Vincent E. Larson, and William R. Cotton. "A PDF-Based Model for Boundary Layer Clouds. Part II: Model Results." Journal of the Atmospheric Sciences 59, no. 24 (December 2002): 3552–71. http://dx.doi.org/10.1175/1520-0469(2002)059<3552:apbmfb>2.0.co;2.

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22

Li, X. T., J. Sun, L. W. Jin, and M. Liu. "Bi-parameter CGM model for approximation of -stable PDF." Electronics Letters 44, no. 18 (2008): 1096. http://dx.doi.org/10.1049/el:20080955.

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23

KAWANABE, Hiroshi, Akihiro KATSUURA, and Takuji ISHIYAMA. "C113 CFD Simulation of Diesel Combustion Using PDF Model." Proceedings of thermal engineering conference 2001 (2001): 125–26. http://dx.doi.org/10.1299/jsmeptec.2001.0_125.

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KAWANABE, Hiroshi, Takuji ISHIYAMA, and Masahiro SHIOJI. "420 CFD Simulation of Diesel Combustion Using PDF Model." Proceedings of The Computational Mechanics Conference 2001.14 (2001): 443–44. http://dx.doi.org/10.1299/jsmecmd.2001.14.443.

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Mura, Arnaud, Fabienne Galzin, and Roland Borghi. "A unified pdf-flamelet model for turbulent premixed combustion." Combustion Science and Technology 175, no. 9 (September 2003): 1573–609. http://dx.doi.org/10.1080/00102200302368.

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Liu, Zhaohui, Chuguang Zheng, and Lixing Zhou. "A joint PDF model for turbulent spray evaporation/combustion." Proceedings of the Combustion Institute 29, no. 1 (January 2002): 561–68. http://dx.doi.org/10.1016/s1540-7489(02)80072-4.

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27

Wang, Y., X. Liu, C. Hoose, and B. Wang. "Impact of heterogeneous ice nucleation by natural dust and soot based on a probability density function of contact angle model with the Community Atmospheric Model version 5." Atmospheric Chemistry and Physics Discussions 14, no. 6 (March 18, 2014): 7141–86. http://dx.doi.org/10.5194/acpd-14-7141-2014.

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Abstract. In order to investigate the impact of different treatments for the contact angle (α) in heterogeneous ice nucleating properties of natural dust and black carbon (BC) particles, we implement the classical-nucleation-theory-based parameterization of heterogeneous ice nucleation (Hoose et al., 2010) in the Community Atmospheric Model version 5 (CAM5), and then improve it by replacing the original single contact angle model with the probability density function of α (α-PDF) model to better represent the ice nucleation behavior of natural dust found in observations. We re-fit the classical nucleation theory (CNT) to constrain the uncertain parameters (i.e., onset α and activation energy in the single α model; mean contact angle and standard deviation in the α-PDF model) using recent observation datasets for Saharan natural dust and BC (soot). We investigate the impact of time-dependence of droplet freezing on mixed-phase clouds and climate in CAM5, and the roles of natural dust and soot by different nucleation mechanisms. Our results show that when comparing with observations, the potential ice nuclei (IN) calculated by the α-PDF model has a better agreement than that calculated by the single-α model at warm temperatures (T > −20 °C). Ice crystals can form at lower altitudes (with warmer temperatures) simulated by the α-PDF model compared with the single-α model in CAM5. All of these can be attributed to different ice nucleation efficiencies among aerosol particles with some particles having smaller contact angles (higher efficiencies) in the α-PDF model. In the sensitivity tests with the α-PDF model, we find that the change of mean contact angle has larger impact on the active fraction than that of standard deviation, even though the change of standard deviation can lead to the transition of freezing behavior. Both the single α and the α-PDF model indicates that the immersion freezing of natural dust plays a more important role in the heterogeneous nucleation than that of soot in mixed-phase clouds.
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Ong, Duu Sheng, Ai Hui Tan, Kan Yeep Choo, Keat Hoe Yeoh, and John P. R. David. "Weibull-Fréchet random path length model for avalanche gain and noise in photodiodes." Journal of Physics D: Applied Physics 55, no. 6 (November 2, 2021): 065105. http://dx.doi.org/10.1088/1361-6463/ac31f0.

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Abstract A four-parameter Weibull-Fréchet (WF) distribution function has been introduced in the random path length (RPL) model for nonlocal modelling of soft-threshold ionisation in semiconductors. The WF function has been demonstrated to be capable of reproducing the realistic probability distribution function (PDF) of electron and hole ionisation path lengths extracted from full band Monte Carlo (FBMC) transport simulations of bulk GaAs. The electron-initiated multiplication in GaAs avalanche photodiodes (APDs) calculated by the WF-RPL model is in excellent agreement with the results from FBMC. The predicted excess noise factor is closer to that of FBMC as compared to the hard threshold RPL model. The advantage of this improved RPL model as a tool for predicting the PDF of electron and hole ionisation path lengths in AlAs0.56Sb0.44 from the experimentally measured avalanche gain and noise has been analysed. The electron ionisation path length PDF of AlAs0.56Sb0.44 has a unique feature of two decay rates with a narrow full width at half maximum and a long tail. The extremely low hole ionisation coefficient in AlAs0.56Sb0.44 is found with a PDF of ionisation path length spanning over 50 µm at an electric field of 600 kVcm−1, supporting the very low hole feedback ionisation in AlAs0.56Sb0.44 APDs. The combination of the detailed and peaked electron’s ionisation path length PDF and of the broad hole’s ionisation path length PDF is responsible for the extremely low avalanche noise in the 1.55 µm thick AlAs0.56Sb0.44 APDs.
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29

Gandhimathi, Mrs K., and Dr N. Umadevi. "Predictive Model for Type II Diabetes: Deep Learning with Probability Density Function." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 1674–77. http://dx.doi.org/10.22214/ijraset.2022.42578.

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Abstract: Diabetes mellitus is a scientific ailment defined by hyperglycemia caused by a lack of absolute or relative insulin efficiency in the human body. Diabetes prediction is one of the newest and fastest-growing technologies in medical data analysis. The clustering method for grouping diabetes data based on cluster head properties is the focus of this study. This study proposes a new BG prediction method called RNN, which is based on recurrent neural networks (RNN). The probability of values of the variable is calculated using the probability density function (PDF). For pre-processing and missing value analysis, we used an enhanced Decision Tree and a weighted K-means method. The proposed method uses the weighted Binary Bat Optimization algorithm for feature selection. In terms of diabetic categorization, numerical findings reveal that when compared to other existing methods, the DP-RNN approach with PDF produces the way PDF-DPRNN produces the more accurate classification result. Keywords: PDF, RNN, Decision Tree, Bat Optimization, Diabetes mellitus
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Mullen, Katharine, and Igor Levin. "Mitigation of errors in pair distribution function analysis of nanoparticles." Journal of Applied Crystallography 44, no. 4 (June 8, 2011): 788–97. http://dx.doi.org/10.1107/s0021889811014749.

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Information on the size and structure of nanoparticles can be obtainedviaanalysis of the atomic pair distribution function (PDF), which is calculated as the Fourier transform of X-ray/neutron total scattering. The structural parameters are commonly extracted by fitting a model PDF calculated from atomic coordinates to the experimental data. This paper discusses procedures for minimizing systematic errors in PDF calculations for nanoparticles and also considers the effects of noise due to counting statistics in total scattering data used to obtain the PDF. The results presented here demonstrate that smoothing of statistical noise in reciprocal-space data can improve the precision of parameter estimates obtained from PDF analysis, facilitating identification of the correct model (from multiple plausible choices) from real-space PDF fits.
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Kang, Jianxiong, Yanjun Lu, Bin Zhao, Hongbo Luo, Jiacheng Meng, and Yongfang Zhang. "Remaining useful life prediction of cylinder liner based on nonlinear degradation model." Eksploatacja i Niezawodnosc - Maintenance and Reliability 24, no. 1 (December 13, 2021): 62–69. http://dx.doi.org/10.17531/ein.2022.1.8.

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In order to effectively monitor the wear and predict the life of cylinder liner, a nonlinear degradation model with multi-source uncertainty based on Wiener process is established to evaluate the remaining useful life (RUL) of cylinder liner wear. Due to complex service performance of cylinder liner, the uncertainty of operational environment and working conditions of cylinder liner wear are considered into the model by a random function. The probability density function (PDF) formula of RUL is derived, and the maximum likelihood estimation method is adopted to estimate the unknown parameters of PDF. Considering the evaluated parameters as the initial values, the model parameters are updated adaptively, and an adaptive PDF is obtained. Furthermore, the proposed model is compared with two classical degradation models. The results show that the proposed model has a good performance for predicting the life, and the error is within 5%. The method can provide a reference for condition monitoring of cylinder liner wear.
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Muller, Ann. "A model for research supervision." Health SA Gesondheid 3, no. 2 (December 1, 1998): 31–35. http://dx.doi.org/10.4102/hsag.v3i2.355.

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This article presents a model for research supervision.OpsommingHierdie artikel stel 'n model vir navorsingsbegeleiding voor. *Please note: This is a reduced version of the abstract. Please refer to PDF for full text.
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Abu Al-Haija, Qasem, Ammar Odeh, and Hazem Qattous. "PDF Malware Detection Based on Optimizable Decision Trees." Electronics 11, no. 19 (September 30, 2022): 3142. http://dx.doi.org/10.3390/electronics11193142.

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Portable document format (PDF) files are one of the most universally used file types. This has incentivized hackers to develop methods to use these normally innocent PDF files to create security threats via infection vector PDF files. This is usually realized by hiding embedded malicious code in the victims’ PDF documents to infect their machines. This, of course, results in PDF malware and requires techniques to identify benign files from malicious files. Research studies indicated that machine learning methods provide efficient detection techniques against such malware. In this paper, we present a new detection system that can analyze PDF documents in order to identify benign PDF files from malware PDF files. The proposed system makes use of the AdaBoost decision tree with optimal hyperparameters, which is trained and evaluated on a modern inclusive dataset, viz. Evasive-PDFMal2022. The investigational assessment demonstrates a lightweight and accurate PDF detection system, achieving a 98.84% prediction accuracy with a short prediction interval of 2.174 μSec. To this end, the proposed model outperforms other state-of-the-art models in the same study area. Hence, the proposed system can be effectively utilized to uncover PDF malware at a high detection performance and low detection overhead.
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Li, Xin, and Albert C. Reynolds. "A Gaussian Mixture Model as a Proposal Distribution for Efficient Markov-Chain Monte Carlo Characterization of Uncertainty in Reservoir Description and Forecasting." SPE Journal 25, no. 01 (September 23, 2019): 001–36. http://dx.doi.org/10.2118/182684-pa.

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Summary Generating an estimate of uncertainty in production forecasts has become nearly standard in the oil industry, but is often performed with procedures that yield at best a highly approximate uncertainty quantification. Formally, the uncertainty quantification of a production forecast can be achieved by generating a correct characterization of the posterior probability-density function (PDF) of reservoir-model parameters conditional to dynamic data and then sampling this PDF correctly. Although Markov-chain Monte Carlo (MCMC) provides a theoretically rigorous method for sampling any target PDF that is known up to a normalizing constant, in reservoir-engineering applications, researchers have found that it might require extraordinarily long chains containing millions to hundreds of millions of states to obtain a correct characterization of the target PDF. When the target PDF has a single mode or has multiple modes concentrated in a small region, it might be possible to implement a proposal distribution dependent on a random walk so that the resulting MCMC algorithm derived from the Metropolis-Hastings acceptance probability can yield a good characterization of the posterior PDF with a computationally feasible chain length. However, for a high-dimensional multimodal PDF with modes separated by large regions of low or zero probability, characterizing the PDF with MCMC using a random walk is not computationally feasible. Although methods such as population MCMC exist for characterizing a multimodal PDF, their computational cost generally makes the application of these algorithms far too costly for field application. In this paper, we design a new proposal distribution using a Gaussian mixture PDF for use in MCMC where the posterior PDF can be multimodal with the modes spread far apart. Simply put, the method generates modes using a gradient-based optimization method and constructs a Gaussian mixture model (GMM) to use as the basic proposal distribution. Tests on three simple problems are presented to establish the validity of the method. The performance of the new MCMC algorithm is compared with that of random-walk MCMC and is also compared with that of population MCMC for a target PDF that is multimodal.
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Cosenza, Diogo Nepomuceno, Paula Soares, Juan Guerra-Hernández, Luísa Pereira, Eduardo González-Ferreiro, Fernando Castedo-Dorado, and Margarida Tomé. "Comparing Johnson’s SB and Weibull Functions to Model the Diameter Distribution of Forest Plantations through ALS Data." Remote Sensing 11, no. 23 (November 26, 2019): 2792. http://dx.doi.org/10.3390/rs11232792.

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The analysis of the diameter distribution is important for forest management since the knowledge of tree density and growing stock by diameter classes is essential to define management plans and to support operational decisions. The modeling of diameter distributions from airborne laser scanning (ALS) data has been performed through the two-parameter Weibull probability density function (PDF), but the more flexible PDF Johnson’s SB has never been tested for this purpose until now. This study evaluated the performance of the Johnson’s SB to predict the diameter distributions based on ALS data from two of the most common forest plantations in the northwest of the Iberian Peninsula (Eucalyptus globulus Labill. and Pinus radiata D. Don). The Weibull PDF was taken as a benchmark for the diameter distributions prediction and both PDFs were fitted with ALS data. The results show that the SB presented a comparable performance to the Weibull for both forest types. The SB presented a slightly better performance for the E. globulus, while the Weibull PDF had a small advantage when applied to the P. radiata data. The Johnson’s SB PDF is more flexible but also more sensitive to possible errors arising from the higher number of stand variables needed for the estimation of the PDF parameters.
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LI, Huiling, Xuan SU, and Shuaipeng ZHANG. "https://ijsea.com/archive/volume10/issue9/IJSEA10091005.pdf." International Journal of Science and Engineering Applications 10, no. 9 (September 2021): 144–47. http://dx.doi.org/10.7753/ijsea1009.1006.

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Massive amounts of business process event logs are collected and stored by modern information systems. Model discovery aims to discover a process model from such event logs, however, most of the existing approaches still suffer from low efficiency when facing large-scale event logs. Event log sampling techniques provide an effective scheme to improve the efficiency of process discovery, but the existing techniques still cannot guarantee the quality of model mining. Therefore, a sampling approach based on set coverage algorithm named set coverage sampling approach is proposed. The proposed sampling approach has been implemented in the open-source process mining toolkit ProM. Furthermore, experiments using a real event log data set from conformance checking and time performance analysis show that the proposed event log sampling approach can greatly improve the efficiency of log sampling on the premise of ensuring the quality of model mining.
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Zhou, Fang Bin, and Yun Kai Guo. "Analysis on Difference of Contaminated Normal Distribution PDF." Applied Mechanics and Materials 409-410 (September 2013): 1661–66. http://dx.doi.org/10.4028/www.scientific.net/amm.409-410.1661.

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As a very important distribution, contaminated normal distribution play a great role in data processing. The probability density function (PDF) feature of the contaminated normal distribution was investigated. The Kullback-Leibler distance is suggested for measuring PDF difference between mean shift model and variance inflation model. Numerical calculations show that the PDF difference of two kinds of model is related to mean shift parameter λ and the variance inflation factor α closely when the main distribution is the standard normal distribution and the relationship is nonlinear proportional.
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FULCO, UMBERTO L., MARCELO L. LYRA, FILIPPO PETRONI, MAURIZIO SERVA, and GANDHI M. VISWANATHAN. "A STOCHASTIC MODEL FOR MULTIFRACTAL BEHAVIOR OF STOCK PRICES." International Journal of Modern Physics B 18, no. 04n05 (February 20, 2004): 681–89. http://dx.doi.org/10.1142/s0217979204024306.

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We investigate the general problem of how to model the kinematics of stock prices without considering the dynamical causes of motion. We propose a Markovian stochastic process which is able to reproduce the experimentally observed volatility clustering and fat tails in the probability density functions (PDF) of financial time series. More importantly, the process also reproduces the PDF time scaling, the power law memory of volatility and the apparent multifractality of the time series up to the time scale which is experimentally observable.
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Hermsen, Elizabeth D., Laurie B. Hovde, John R. Hotchkiss, and John C. Rotschafer. "Increased Killing of Staphylococci and Streptococci by Daptomycin Compared with Cefazolin and Vancomycin in an In Vitro Peritoneal Dialysate Model." Antimicrobial Agents and Chemotherapy 47, no. 12 (December 2003): 3764–67. http://dx.doi.org/10.1128/aac.47.12.3764-3767.2003.

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ABSTRACT Peritoneal dialysate fluid (PDF) is a bacteriostatic medium that compromises the antibacterial activity of cell wall-active agents. By use of an in vitro static model, methicillin-resistant Staphylococcus aureus (MRSA), methicillin-susceptible S. aureus (MSSA), methicillin-susceptible Staphylococcus epidermidis (MSSE), and Streptococcus sanguis were exposed to daptomycin at concentrations of 10, 30, and 100 mg/liter, cefazolin at 125 mg/liter, and vancomycin at 25 mg/liter in cation-adjusted Mueller-Hinton Broth or Todd Hewitt Broth (for S. sanguis) and PDF at pHs of 5.5 and 7.4. The pH had no effect on antibacterial activity. Neither cefazolin nor vancomycin produced a bactericidal or a bacteriostatic effect versus MRSA, MSSA, MSSE, or S. sanguis in PDF, while all concentrations of daptomycin were bactericidal against all organisms in PDF. Daptomycin did not exhibit concentration-dependent activity in PDF. Daptomycin appears to be a promising agent for use in peritoneal dialysis-associated peritonitis, producing bacterial kill to a greater extent and at a higher rate than cefazolin or vancomycin in PDF.
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MASOUDI, A. A., and P. AZIMI ANARAKI. "AN ANALYTICAL SOLUTION FOR THE STOCHASTIC MODEL OF A TURBULENT CASCADE." Modern Physics Letters B 20, no. 20 (August 30, 2006): 1247–51. http://dx.doi.org/10.1142/s0217984906011323.

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In this paper we are going to derive the Fokker–Planck equation (FPE) which is based on the Langevin equation for the stochastic model of a turbulent cascade and then we exactly solve the FPE for a certain case and find an explicit form of the probability distribution function (PDF) by the operator method. Finally, by using this PDF, we calculate the velocity moments for this system.
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Wang, Zhi Qiang, Yayin Du, and Feng Liu. "Catastrophe Model of Elastic Compression Pole Buckling." Applied Mechanics and Materials 166-169 (May 2012): 3369–73. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.3369.

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This screen is for uploading/submitting a new manuscript. This screen is NOT for updating revised versions of a previously submitted manuscript (click on 'My Papers' above to revise previous submissions). To upload/submit a new manuscript, first enter the title of the manuscript into the 'Paper Title' box. Then use the Browse buttons below to select BOTH a Word file and a PDF file on your computer of the manuscript that you are submitting. After you have selected both Word and PDF files from your local computer and entered your title, press the 'Update' button and the files will be transferred to our online system.
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42

Bhagavan, Druv, William M. Padovano, and Sándor J. Kovács. "Alternative diastolic function models of ventricular longitudinal filling velocity are mathematically identical." American Journal of Physiology-Heart and Circulatory Physiology 318, no. 5 (May 1, 2020): H1059—H1067. http://dx.doi.org/10.1152/ajpheart.00681.2019.

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The spatiotemporal features of normal in vivo cardiac motion are well established. Longitudinal velocity has become a focus of diastolic function (DF) characterization, particularly the tissue Doppler e′-wave, manifesting in early diastole when the left ventricle (LV) is a mechanical suction pump (dP/dV < 0). To characterize DF and elucidate mechanistic features, several models have been proposed and have been previously compared algebraically, numerically, and in their ability to fit physiological velocity data. We analyze two previously noncompared models of early rapid-filling lengthening velocity (Doppler e′-wave): parametrized diastolic filling (PDF) and force balance model (FBM). Our initial numerical experiments sampled FBM-generated e′( t) contours as input to determine PDF model predicted fit. The resulting exact numerical agreement [standard error of regression (SER) = 9.06 × 10−16] was not anticipated. Therefore, we analyzed all published FBM-generated e′( t) contours and observed identical agreement. We re-expressed FBM’s algebraic expressions for e′( t) and observed for the first time that model-based predictions for lengthening velocity by the FBM and the PDF model are mathematically identical: e′( t) = γe−α tsinh(β t), thereby providing exact algebraic relations between the three PDF parameters and the six FBM parameters. Previous pioneering experiments have independently established the unique determinants of e′( t) to be LV relaxation, restoring forces (stiffness), and load. In light of the exact intermodel agreement, we conclude that the three PDF parameters, relaxation, stiffness (restoring forces), and load, are unique determinants of DF and e′( t). Thus, we show that only the PDF formalism can compute the three unique, independent, physiological determinants of long-axis LV myocardial velocity from e′( t). NEW & NOTEWORTHY We show that two separate, independently derived physiological (kinematic) models predict mathematically identical expressions for LV-lengthening velocity (Doppler e′-wave), indicating that damped harmonic oscillatory motion is a physiologically accurate model of diastolic function. Although both models predict the same “overdamped” velocity contour, only one model solves the “inverse problem” and generates unique, lumped parameters of relaxation, stiffness (restoring force), and load from the e′-wave.
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43

Aroeira, Luiz S., Jesús Loureiro, Guadalupe T. González-Mateo, Vanessa Fernandez-Millara, Gloria del Peso, José Antonio Sánchez-Tomero, Marta Ruiz-Ortega, M. Auxiliadora Bajo, Manuel López-Cabrera, and Rafael Selgas. "Characterization of Epithelial-to-Mesenchymal Transition of Mesothelial Cells in a Mouse Model of Chronic Peritoneal Exposure to High Glucose Dialysate." Peritoneal Dialysis International: Journal of the International Society for Peritoneal Dialysis 28, no. 5_suppl (September 2008): 29–33. http://dx.doi.org/10.1177/089686080802805s06.

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Animal models of peritoneal dialysis fluid (PDF) exposure are key tools in the study of mechanisms involved in alterations of the peritoneal membrane and in the design of therapies. We recently developed a mouse model of chronic peritoneal exposure to high glucose dialysate. Herein, we make a sequential analysis of the effects of glucose-based PDF on mouse peritoneal membrane and on mesothelium. We demonstrate that chronic exposure to PDF induces thickness and fibrosis of the peritoneal membrane in a time-dependent manner. We also show that mesothelial cells progressively detach and lose cytokeratin expression. In addition, we demonstrate that some mesothelial cells invade the submesothelial space, where they appear as cytokeratin- and alpha-smooth muscle actin-positive cells. These findings demonstrate that epithelial-to-mesenchymal transition (EMT) of mesothelial cells takes place in mouse peritoneum exposed to PDF, validating this model for the study of effects of drugs on the EMT process as a therapy for peritoneal deterioration.
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44

Boisvert, J., F. Ashkar, S. El Adlouni, N. El-Jabi, and F. Aucoin. "Modeling St. John River (N.B., Canada) incomplete hydrometric data using bivariate distributions." Canadian Journal of Civil Engineering 42, no. 7 (July 2015): 427–36. http://dx.doi.org/10.1139/cjce-2014-0433.

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This study deals with incomplete bivariate data in hydrology, where information contained in a hydrological series of relatively long length (X, the auxiliary variable) is utilized to enhance the quality of the quantile estimates for a series of shorter length (Y, the variable of main interest), when there is an association between X and Y. It is suggested that bivariate models for representing (X, Y) be constructed by means of copulas, which allows for flexibility in choosing both the marginals and the bivariate distributions. Parameter estimation is done by maximum likelihood (ML), where all the unknown parameters of the bivariate model are estimated simultaneously. A case study using flow records at three gauging stations on the St. John River (New Brunswick, Canada) is used to demonstrate the interest of using bivariate distributions for modeling incomplete data. By using (X, Y) bivariate data observed on the St. John River, the probability density function (pdf) obtained from a univariate frequency analysis of Y (Model A), is compared to the pdf constructed using a bivariate model relating X to Y (Model B). It is shown that Model B reduces the variability in the Y pdf as compared to the pdf obtained from Model A, and also corrects the quantile estimates for Y through a location shift.
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45

Kulkarni, G., J. Fan, J. M. Comstock, X. Liu, and M. Ovchinnikov. "Laboratory measurements and model sensitivity studies of dust deposition ice nucleation." Atmospheric Chemistry and Physics Discussions 12, no. 1 (January 25, 2012): 2483–516. http://dx.doi.org/10.5194/acpd-12-2483-2012.

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Abstract. We investigated the ice nucleating properties of mineral dust particles to understand the sensitivity of modeled cloud properties to different representations of contact angle in the Classical Nucleation Theory (CNT): onset single angle and probability density function (PDF) distribution approaches. These contact angle representations are based on two sets of laboratory deposition ice nucleation measurements: Arizona Test Dust (ATD) particles of 100, 300, and 500 nm sizes were tested at three different temperatures (−25, −30 and −35 °C), and 400 nm ATD and Kaolinite dust species were tested at two different temperatures (−30 and −35 °C). These measurements were used to derive the onset relative humidity with respect to ice (RHice) required to activate 1% of dust particles as ice nuclei, from which the onset single contact angles were then calculated based on the CNT. For the PDF representation, parameters of the log-normal contact angle distribution (mean and standard deviation) were determined by fitting the CNT-predicted activated fraction to the measurements at different RHice. Results show that onset single contact angles are not much different between experiments, while the PDF parameters are sensitive to those environmental conditions (i.e., temperature and dust size). The cloud resolving model simulations show that cloud properties (i.e. ice number concentration, ice water content, and cloud initiation times) are sensitive to onset single contact angles and PDF distribution parameters, particularly to the mean value. The comparison of our experimental results with other studies shows that under similar measurement conditions the onset single contact angles are consistent within &amp;pm;2.0°, while our derived PDF parameters have discrepancies.
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46

Kulkarni, G., J. Fan, J. M. Comstock, X. Liu, and M. Ovchinnikov. "Laboratory measurements and model sensitivity studies of dust deposition ice nucleation." Atmospheric Chemistry and Physics 12, no. 16 (August 16, 2012): 7295–308. http://dx.doi.org/10.5194/acp-12-7295-2012.

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Abstract. We investigated the ice nucleating properties of mineral dust particles to understand the sensitivity of simulated cloud properties to two different representations of contact angle in the Classical Nucleation Theory (CNT). These contact angle representations are based on two sets of laboratory deposition ice nucleation measurements: Arizona Test Dust (ATD) particles of 100, 300 and 500 nm sizes were tested at three different temperatures (−25, −30 and −35 °C), and 400 nm ATD and kaolinite dust species were tested at two different temperatures (−30 and −35 °C). These measurements were used to derive the onset relative humidity with respect to ice (RHice) required to activate 1% of dust particles as ice nuclei, from which the onset single contact angles were then calculated based on CNT. For the probability density function (PDF) representation, parameters of the log-normal contact angle distribution were determined by fitting CNT-predicted activated fraction to the measurements at different RHice. Results show that onset single contact angles vary from ~18 to 24 degrees, while the PDF parameters are sensitive to the measurement conditions (i.e. temperature and dust size). Cloud modeling simulations were performed to understand the sensitivity of cloud properties (i.e. ice number concentration, ice water content, and cloud initiation times) to the representation of contact angle and PDF distribution parameters. The model simulations show that cloud properties are sensitive to onset single contact angles and PDF distribution parameters. The comparison of our experimental results with other studies shows that under similar measurement conditions the onset single contact angles are consistent within ±2.0 degrees, while our derived PDF parameters have larger discrepancies.
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47

Manceau, A. "PDF analysis of ferrihydrite and the violation of Pauling's Principia." Clay Minerals 45, no. 2 (June 2010): 225–28. http://dx.doi.org/10.1180/claymin.2010.045.2.225.

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AbstractThe risk of overfitting pair distribution function (PDF) data for highly defective material (Farrow et al., 2007) is illuminated with the example of the nanocrystalline hydrous ferric oxyhydroxide, ferrihydrite. Two structural models have been published by Michel et al. (2007, 2010) using this method, both of which contradict the standard ‘ferrihydrits’ model established by X-ray diffraction (Drits et al., 1993), and confirmed by single-crystal electron nanodiffraction (Janney et al., 2001) and neutron diffraction (Jansen et al., 2002). Although PDF data are reproduced equally well with the two regression models, neither model is realistic: the first (fhyd6) violates Pauling's 2nd rule, and the second (ferrifh), Pauling's 3rd rule.
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48

Yoon, Chae-Eun, Hye-hyeon Jeoung, and Chang-Jin Seo. "Detection for Document-Type Malware Code using Deep Learning Model and PDF Object Analysis." TRANSACTION OF THE KOREAN INSTITUTE OF ELECTRICAL ENGINEERS P 70P, no. 1 (March 31, 2021): 44–49. http://dx.doi.org/10.5370/kieep.2021.70.1.044.

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49

Singh, Shailendra. "Model for Converting PDF to Audio Format (Listen Your Book)." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 31, 2021): 3203–6. http://dx.doi.org/10.22214/ijraset.2021.36522.

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The present paper has introduced an innovative and efficient technique that enables user to hear the contents of text images instead of reading through them. In the current world, there is a great increase in the utilization of digital technology and multiple methods are available for the people to capture images. such images may contain important textual content that the user may need to edit or store digitally. It merges the concept of Optical Character Recognition (OCR) and Text to Speech Synthesizer (TTS). This can be done using Optical Character Recognition with the use of Tesseract OCR Engine. OCR is a branch of AI that is used in applications to recognize text from scanned documents or images. The analyzed text can also be converted to audio format to help visually impaired people hear the content that they wish to know. Text-to-Speech conversion is a method that scans and reads alphabets and numbers that are in the image using OCR technique and convert it into voices. The aim is to study and compare the multiple methods used for STT conversions and to figure out the most efficient technique that can be adapted for the conversion processes. As a result, based on review study it is found that HMM is a statistical model which is most suitable for TTS conversions.
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Rachman, Abdur, and Iksan Kamil Sahri. "Model Pembelajaran di PDF ULYA Al Fithrah di Masa Pandemi." Jurnal Kependidikan Islam 11, no. 2 (August 15, 2021): 208–12. http://dx.doi.org/10.15642/jkpi.2021.11.2.208-212.

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Pandemi Covid-19 di dunia termasuk di Indonesia menyangkut kebijakan pemerintah, termasuk di bidang pendidikan. Dalam hal ini Kementerian Pendidikan dan Kebudayaan memutuskan siswa untuk belajar di rumah dengan bimbingan orang tua. Dengan kebijakan ini, guru dituntut kreatif dan inovatif dalam mengerjakan kurikulum sesuai dengan situasi dan kebutuhan yang ada. Tujuan penelitian adalah untuk mempelajari kurikulum dan pembelajaran selama pandemi covid-19. Penelitian ini menggunakan metode kualitatif deskriptif yang menganalisis dan kemudian menggambarkan secara jelas masalah yang bersumber dari tinjauan pustaka. Hasil dari penelitian ini adalah: Komponen kurikulum adalah tujuan, pengaruh pembelajaran, dan proses pembelajaran
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