Search results for: Poisson inverse Gaussian distribution

Authors: Wanessa G. Oliveira, Fernando C. Capovilla

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Capovilla and Raphael’s Libras Dictionary documents a corpus of 4,200 Brazilian Sign Language (Libras) signs. Duduchi and Capovilla’s software SignTracking permits users to retrieve signs even when ignoring the gloss corresponding to it and to discover the meaning of all 4,200 signs sign simply by clicking on graphic menus of the sign characteristics (phonemes). Duduchi and Capovilla have discovered that the ease with which any given sign can be retrieved is an inverse function of the average popularity of its component phonemes. Thus, signs composed of rare (distinct) phonemes are easier to retrieve than are those composed of common phonemes. SignTracking offers a means of computing the average popularity of the phonemes that make up each one of 4,200 signs. It provides a precise measure of the degree of ease with which signs can be retrieved, and sign meanings can be discovered. Duduchi and Capovilla’s logarithmic model proved valid: The degree with which any given sign can be retrieved is an inverse function of the arithmetic mean of the logarithm of the popularity of each component phoneme. Capovilla, Raphael and Mauricio’s New Libras Dictionary documents a corpus of 10,400 Libras signs. The present analysis revealed Libras DNA structure by mapping the incidence of 501 sign phonemes resulting from the layered distribution of five parameters: 163 handshape phonemes (CherEmes-ManusIculi); 34 finger shape phonemes (DactilEmes-DigitumIculi); 55 hand placement phonemes (ArtrotoToposEmes-ArticulatiLocusIculi); 173 movement dimension phonemes (CinesEmes-MotusIculi) pertaining to direction, frequency, and type; and 76 Facial Expression phonemes (MascarEmes-PersonalIculi).

Keywords: Brazilian sign language, lexical retrieval, libras sign, sign phonology

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Authors: Tsedeke Lambore Gemecho, Ayele Taye Goshu

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The main objective of this study is to identify the determinants of the number of international migrants in a household and to compare regression models for count response. This study is done by collecting data from total of 2288 household heads of 16 randomly sampled districts in Hadiya and Kembata-Tembaro zones of Southern Ethiopia. The Poisson mixed models, as special cases of the generalized linear mixed model, is explored to determine effects of the predictors: age of household head, farm land size, and household size. Two ethnicities Hadiya and Kembata are included in the final model as dummy variables. Stepwise variable selection has indentified four predictors: age of head, farm land size, family size and dummy variable ethnic2 (0=other, 1=Kembata). These predictors are significant at 5% significance level with count response number of migrant. The Poisson mixed model consisting of the four predictors with random effects districts. Area specific random effects are significant with the variance of about 0.5105 and standard deviation of 0.7145. The results show that the number of migrant increases with heads age, family size, and farm land size. In conclusion, there is a significantly high number of international migration per household in the area. Age of household head, family size, and farm land size are determinants that increase the number of international migrant in households. Community-based intervention is needed so as to monitor and regulate the international migration for the benefits of the society.

Keywords: Poisson regression, GLM, number of migrant, Hadiya and Kembata Tembaro zones

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Authors: Jinyoung Choi, Tae-Ho Yoon, Sunmook Lee

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Degradation of standard oxygen transfer efficiency (SOTE) with time was observed for the assessment of lifetime of metal-based air-diffuser, which displaced a polymer composite-based air-diffuser in order to attain a longer lifetime in the actual field. The degradation of air-diffuser occurred due to the failure of the formation of small and uniform air bubbles since the patterns formed on the disc of air-diffuser deteriorated and/or changed from their initial shapes while they were continuously exposed to the air blowing condition during the operation in the field. Therefore, the lifetime assessment of metal-based air-diffuser was carried out through an accelerated degradation test by accelerating the air-blowing conditions in 200 L/min, 300 L/min, and 400 L/min and the lifetime of normal operating condition at 120 L/min was predicted. It was found that Weibull distribution was the most proper one for describing the lifetime distribution of metal-based air-diffuser in the present study. The shape and scale parameters indicated that the accelerated blowing conditions were all within the acceleration domain. The lifetime was predicted by adopting inverse power model for a stress-life relationship and estimated to be B10=94,004 hrs with CL=95%. Acknowledgement: This work was financially supported by the Ministry of Trade, Industry and Energy (Grant number: N0001475).

Keywords: accelerated degradation test, air-diffuser, lifetime assessment, SOTE

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Authors: Samuel Ahamefula Mba

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Fluid turbulence is a complex and nonlinear phenomenon that occurs in various natural and industrial processes. Understanding turbulence remains a challenging task due to its intricate nature. One approach to gain insights into turbulence is through the study of entropy, which quantifies the disorder or randomness of a system. This research presents a numerical investigation of entropy signatures in fluid turbulence. The work is to develop a numerical framework to describe and analyse fluid turbulence in terms of entropy. This decomposes the turbulent flow field into different scales, ranging from large energy-containing eddies to small dissipative structures, thus establishing a correlation between entropy and other turbulence statistics. This entropy-based framework provides a powerful tool for understanding the underlying mechanisms driving turbulence and its impact on various phenomena. This work necessitates the derivation of the Poisson equation for pressure transformation of Navier-Stokes equation and using Chebyshev-Finite Difference techniques to effectively resolve it. To carry out the mathematical analysis, consider bounded domains with smooth solutions and non-periodic boundary conditions. To address this, a hybrid computational approach combining direct numerical simulation (DNS) and Large Eddy Simulation with Wall Models (LES-WM) is utilized to perform extensive simulations of turbulent flows. The potential impact ranges from industrial process optimization and improved prediction of weather patterns.

Keywords: turbulence, Navier-Stokes equation, Poisson pressure equation, numerical investigation, Chebyshev-finite difference, hybrid computational approach, large Eddy simulation with wall models, direct numerical simulation

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Authors: Muhammad Hassan Khalil, Xu Jiadong

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Early detection through screening is the best tool short of a perfect treatment against the malignant tumor inside the breast of a woman. By detecting cancer in its early stages, it can be recognized and treated before it has the opportunity to spread and change into potentially dangerous. Microwave tomography is a new imaging method based on contrast in dielectric properties of materials. The mathematical theory of microwave tomography involves solving an inverse problem for Maxwell’s equations. In this paper, we present designed antenna for breast cancer detection, which will use in microwave tomography configuration.

Keywords: microwave imaging, inverse scattering, breast cancer, malignant tumor detection

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Authors: Marjan Majdi, MohammadAli Moradi, Elham Samarikhalaj

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Income distribution is one of the most topics in macro economic theories. There are many categories in economy such as income distribution that have the most influenced by economic policies. Human capital has an impact on economic growth and it has significant effect on income distributions. The results of this study confirm that the effects of oil revenue and human capital on income distribution are negative and significant but the value of the estimated coefficient is too small in a real sample in period time (1969-2006).

Keywords: gini coefficient, human capital, income distribution, oil revenue

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Authors: Siavash Eftekharifar, Tohid Yousefi Rezaii, Mahdi Shamsi

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The purpose of this paper is to exploit compressed sensing (CS) method in order to model and compress the electrocardiogram (ECG) signals at a high compression ratio. In order to obtain a sparse representation of the ECG signals, first a suitable basis matrix with Gaussian kernels, which are shown to nicely fit the ECG signals, is constructed. Then the sparse model is extracted by applying some optimization technique. Finally, the CS theory is utilized to obtain a compressed version of the sparse signal. Reconstruction of the ECG signal from the compressed version is also done to prove the reliability of the algorithm. At this stage, a greedy optimization technique is used to reconstruct the ECG signal and the Mean Square Error (MSE) is calculated to evaluate the precision of the proposed compression method.

Keywords: compressed sensing, ECG compression, Gaussian kernel, sparse representation

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Authors: R. A. Deshpande, P. Chandhra Sekhar, V. Sankar

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In this paper, we discussed the basic reliability evaluation techniques needed to evaluate the reliability of distribution systems which are applied in distribution system planning and operation. Basically, the reliability study can also help to predict the reliability performance of the system after quantifying the impact of adding new components to the system. The number and locations of new components needed to improve the reliability indices to certain limits are identified and studied.

Keywords: distribution system, reliability indices, urban feeder, rural feeder

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Authors: Dmytro O. Plutenko, Alexei D. Kiselev, Mikhail V. Vasnetsov

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We present the results of our analytical and computational study of Laguerre-Gaussian (LG) beams scattering by spherical homogeneous isotropic particles located on the axis of the beam. We consider different types of scatterers (dielectric, metallic and double negative metamaterials) and different polarizations of the LG beams. A possibility to generate photonic nanojets using metallic and double negative metamaterial Mie scatterers is shown. We have studied the properties of such nonclassical nanojets and discovered new types of the nanojets characterized by zero on-axes magnetic (or electric) field with the electric (or magnetic) field polarized along the z-axis.

Keywords: double negative metamaterial, Laguerre-Gaussian beam, Mie scattering, optical vortices, photonic nanojets

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Authors: Ashis Mallick, Rajeev Ranjan

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The closed form solution for thermal stresses in an annular fin with hyperbolic profile is derived using Adomian decomposition method (ADM). The conductive-convective fin with variable thermal conductivity is considered in the analysis. The nonlinear heat transfer equation is efficiently solved by ADM considering insulated convective boundary conditions at the tip of fin. The constant of integration in the solution is to be estimated using minimum decomposition error method. The solution of temperature field is represented in a polynomial form for convenience to use in thermo-elasticity equation. The non-dimensional thermal stress fields are obtained using the ADM solution of temperature field coupled with the thermo-elasticity solution. The influence of the various thermal parameters in temperature field and stress fields are presented. In order to show the accuracy of the ADM solution, the present results are compared with the results available in literature. The stress fields in fin with hyperbolic profile are compared with those of uniform thickness profile. Result shows that hyperbolic fin profile is better choice for enhancing heat transfer. Moreover, less thermal stresses are developed in hyperbolic profile as compared to rectangular profile. Next, Nelder-Mead based simplex search method is employed for the inverse estimation of unknown non-dimensional thermal parameters in a given stress fields. Owing to the correlated nature of the unknowns, the best combinations of the model parameters which are satisfying the predefined stress field are to be estimated. The stress fields calculated using the inverse parameters give a very good agreement with the stress fields obtained from the forward solution. The estimated parameters are suitable to use for efficient and cost effective fin designing.

Keywords: Adomian decomposition, inverse analysis, hyperbolic fin, variable thermal conductivity

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Authors: Minho Kwon, Seonghyeok Lee, Wooyoung Jung

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In recent years, with increase of construction of skyscraper structures, the study of concrete materials to improve their weight and performance has been emerging as a key of research area. Typically, the concrete structures has disadvantage of increasing the weight due to its mass in comparison to the strength of the materials. Therefore, in order to improve such problems, the light-weight aggregate concrete and high strength concrete materials have been studied during the past decades. On the other hand, the study of light-weight aggregate concrete materials has lack of data in comparison to the concrete structure using high strength materials, relatively. Consequently, this study presents the performance characteristics of light-weight aggregate concrete materials due to the material properties and strength. Also, this study conducted the experimental tests with respect to normal and lightweight aggregate materials, in order to indentify the tensile crack failure of the concrete structures. As a result, the Crack Mouth Opening Displacement (CMOD) from the experimental tests was constructed and the fracture energy using inverse problem analysis was developed from the force-CMOD relationship in this study, respectively.

Keywords: lightweight aggregate concrete, crack mouth opening displacement, inverse analysis, fracture energy

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Authors: Alexandru George Vaduva, Adriana Vlad, Bogdan Badea

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In this research, we conduct a Monte Carlo analysis on a two-dimensional χ2 test, which is used to determine the minimum distance required for independent sampling in the context of chaotic signals. We investigate the impact of transforming initial data sets from any probability distribution to new signals with a uniform distribution using the Spearman rank correlation on the χ2 test. This transformation removes the randomness of the data pairs, and as a result, the observed distribution of χ2 test values differs from the expected distribution. We propose a solution to this problem and evaluate it using another chaotic signal.

Keywords: chaotic signals, logistic map, Pearson’s test, Chi Square test, bivariate distribution, statistical independence

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Authors: Zahira Belkacemi

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One of the most important tools in conservation biology is information on the geographic distribution of species and the variables determining those patterns. In this study, we used maximum-entropy niche modeling (Maxent) to predict the current and future distribution of Anthus pratensis using climatic variables. The results showed that the species would not be highly affected by the climate change in shifting its distribution; however, the results of this study should be improved by taking into account other predictors, and that the NATURA 2000 protected sites will be efficient at 42% in protecting the species.

Keywords: anthus pratensis, climate change, Europe, species distribution model

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa

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A generalized log-logistic distribution with variable shapes of the hazard rate was introduced and studied, extending the log-logistic distribution by adding an extra parameter to the classical distribution, leading to greater flexibility in analysing and modeling various data types. The proposed distribution has a large number of well-known lifetime special sub-models such as; Weibull, log-logistic, exponential, and Burr XII distributions. Its basic mathematical and statistical properties were derived. The method of maximum likelihood was adopted for estimating the unknown parameters of the proposed distribution, and a Monte Carlo simulation study is carried out to assess the behavior of the estimators. The importance of this distribution is that its tendency to model both monotone (increasing and decreasing) and non-monotone (unimodal and bathtub shape) or reversed “bathtub” shape hazard rate functions which are quite common in survival and reliability data analysis. Furthermore, the flexibility and usefulness of the proposed distribution are illustrated in a real-life data set and compared to its sub-models; Weibull, log-logistic, and BurrXII distributions and other parametric survival distributions with 3-parmaeters; like the exponentiated Weibull distribution, the 3-parameter lognormal distribution, the 3- parameter gamma distribution, the 3-parameter Weibull distribution, and the 3-parameter log-logistic (also known as shifted log-logistic) distribution. The proposed distribution provided a better fit than all of the competitive distributions based on the goodness-of-fit tests, the log-likelihood, and information criterion values. Finally, Bayesian analysis and performance of Gibbs sampling for the data set are also carried out.

Keywords: hazard rate function, log-logistic distribution, maximum likelihood estimation, generalized log-logistic distribution, survival data, Monte Carlo simulation

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Authors: Fatemeh Valizadeh Gamchi, Edward L. Boone

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This research focuses on Lyme disease, a widespread infectious condition in the United States caused by the bacterium Borrelia burgdorferi sensu stricto. It is critical to identify environmental and economic elements that are contributing to the spread of the disease. This study examined data from Virginia to identify a subset of explanatory variables significant for Lyme disease case numbers. To identify relevant variables and avoid overfitting, linear poisson, and regularization regression methods such as a ridge, lasso, and elastic net penalty were employed. Cross-validation was performed to acquire tuning parameters. The methods proposed can automatically identify relevant disease count covariates. The efficacy of the techniques was assessed using four criteria on three simulated datasets. Finally, using the Virginia Department of Health’s Lyme disease data set, the study successfully identified key factors, and the results were consistent with previous studies.

Keywords: lyme disease, Poisson generalized linear model, ridge regression, lasso regression, elastic net regression

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Authors: Ceren Vardar Acar, Mine Caglar

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In finance, the price of a volatile asset can be modeled using fractional Brownian motion (fBm) with Hurst parameter H>1/2. The Black-Scholes model for the values of returns of an asset using fBm is given as, 〖Y_t=Y_0 e^((r+μ)t+σB)〗_t^H, 0≤t≤T where Y_0 is the initial value, r is constant interest rate, μ is constant drift and σ is constant diffusion coefficient of fBm, which is denoted by B_t^H where t≥0. Black-Scholes model can be constructed with some Markov processes such as Brownian motion. The advantage of modeling with fBm to Markov processes is its capability of exposing the dependence between returns. The real life data for a volatile asset display long-range dependence property. For this reason, using fBm is a more realistic model compared to Markov processes. Investors would be interested in any kind of information on the risk in order to manage it or hedge it. The maximum possible loss is one way to measure highest possible risk. Therefore, it is an important variable for investors. In our study, we give some theoretical bounds on the distribution of maximum possible loss of fBm. We provide both asymptotical and strong estimates for the tail probability of maximum loss of standard fBm and fBm with drift and diffusion coefficients. In the investment point of view, these results explain, how large values of possible loss behave and its bounds.

Keywords: maximum drawdown, maximum loss, fractional brownian motion, large deviation, Gaussian process

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Authors: Abdelraheem M. Aly, Minh Tuan Nguyen, Sang-Wook Lee

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The incompressible smoothed particle hydrodynamics (ISPH) is used to simulate impact free surface flows. In the ISPH, pressure is evaluated by solving pressure Poisson equation using a semi-implicit algorithm based on the projection method. The current ISPH method is applied to simulate dam break flow over an inclined plane with different inclination angles. The effects of inclination angle in the velocity of wave front and pressure distribution is discussed. The impact of circular cylinder over water in tank has also been simulated using ISPH method. The computed pressures on the solid boundaries is studied and compared with the experimental results.

Keywords: incompressible smoothed particle hydrodynamics, free surface flow, inclined plane, water entry impact

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Authors: A. Amar

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A new model, namely the crystal model, has been modified to calculate the radius and density distribution of light nuclei up to ⁸Be. The crystal model has been modified according to solid-state physics, which uses the analogy between nucleon distribution and atoms distribution in the crystal. The model has analytical analysis to calculate the radius where the density distribution of light nuclei has obtained from analogy of crystal lattice. The distribution of nucleons over crystal has been discussed in a general form. The equation that has been used to calculate binding energy was taken from the solid-state model of repulsive and attractive force. The numbers of the protons were taken to control repulsive force, where the atomic number was responsible for the attractive force. The parameter has been calculated from the crystal model was found to be proportional to the radius of the nucleus. The density distribution of light nuclei was taken as a summation of two clusters distribution as in ⁶Li=alpha+deuteron configuration. A test has been done on the data obtained for radius and density distribution using double folding for d+⁶,⁷Li with M3Y nucleon-nucleon interaction. Good agreement has been obtained for both the radius and density distribution of light nuclei. The model failed to calculate the radius of ⁹Be, so modifications should be done to overcome discrepancy.

Keywords: nuclear physics, nuclear lattice, study nucleus as crystal, light nuclei till to ⁸Be

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Authors: Phutthiwat Waiyawuththanapoom, Wannapong Waiyawuththanapoom, Pimploi Tirastittam

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Nowadays, it is a globalization era which social media plays an important role to the lifestyle as an information source, tools to connect people together and etc. This research is object to find out about the significant level of the social media as a distribution channel to the agriculture product of Thailand. In this research, the agriculture product is the Rice Berry which is the cross-bred unmilled rice producing dark violet grain, is a combination of Hom Nin Rice and Thai Jasmine/ Fragrant Rice 105. Rice Berry has a very high nutrition and nice aroma so the product is in the growth stage of the product cycle. The problem for the Rice Berry product in Thailand is the production and the distribution channel. This study is to confirm that the social media is another option as the distribution channel for the product which is not a mass production product. This will be the role model for the other niche market product to select the distribution channel.

Keywords: distribution, social media, rice berry, distribution channel

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Authors: Mengjun Yang, Zhulin Zong, Jie Gao

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In this paper, a new and robust algorithm is proposed to achieve high resolution for inverse synthetic aperture radar (ISAR) imaging in the compressive sensing (CS) framework. Traditional CS based methods have to assume that unknown scatters exactly lie on the pre-divided grids; otherwise, their reconstruction performance dropped significantly. In this processing algorithm, several basis shifts are utilized to achieve the same effect as grid refinement does. The detailed implementation of the basis shift algorithm is presented in this paper. From the simulation we can see that using the basis shift algorithm, imaging precision can be improved. The effectiveness and feasibility of the proposed method are investigated by the simulation results.

Keywords: ISAR imaging, sparse reconstruction, off-grid, basis shift

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Authors: Yanli Qi, Ning Lv, Jing Li

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Sub-Nyquist sampling jamming method (SNSJ) is a well known deception jamming method for inverse synthetic aperture radar (ISAR). However, the anti-decoy of the SNSJ method performs easier since the amplitude of the false-target images are weaker than the real-target image; the false-target images always lag behind the real-target image, and all targets are located in the same cross-range. In order to overcome the drawbacks mentioned above, a simple modulation based on SNSJ (M-SNSJ) is presented in this paper. The method first uses amplitude modulation factor to make the amplitude of the false-target images consistent with the real-target image, then uses the down-range modulation factor and cross-range modulation factor to make the false-target images move freely in down-range and cross-range, respectively, thus the capacity of deception is improved. Finally, the simulation results on the six available combinations of three modulation factors are given to illustrate our conclusion.

Keywords: inverse synthetic aperture radar (ISAR), deceptive jamming, Sub-Nyquist sampling jamming method (SNSJ), modulation based on Sub-Nyquist sampling jamming method (M-SNSJ)

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Authors: Daoudi Abdelaziz, Mahmoudi Saïd, Chikh Mohamed Amine

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This paper presents a fully automatic segmentation method of the left ventricle at End Systolic (ES) and End Diastolic (ED) in the ultrasound images by means of an implicit deformable model (level set) based on Geodesic Active Contour model. A pre-processing Gaussian smoothing stage is applied to the image, which is essential for a good segmentation. Before the segmentation phase, we locate automatically the area of the left ventricle by using a detection approach based on the Hough Transform method. Consequently, the result obtained is used to automate the initialization of the level set model. This initial curve (zero level set) deforms to search the Endocardial border in the image. On the other hand, quantitative evaluation was performed on a data set composed of 15 subjects with a comparison to ground truth (manual segmentation).

Keywords: level set method, transform Hough, Gaussian smoothing, left ventricle, ultrasound images.

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Authors: Sheng-Bo Zhang, Huan-Hao Zhang, Zhi-Hua Chen, Chun Zheng

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In this paper, the Richtmyer-Meshkov instability has been studied numerically by using the high-resolution Roe scheme based on the two-dimensional unsteady Euler equation, which was caused by the interaction between shock wave and the helium circular light gas cylinder with different component distributions. The numerical results further discuss the deformation process of the gas cylinder, the wave structure of the flow field and quantitatively analyze the characteristic dimensions (length, height, and central axial width) of the gas cylinder, the volume compression ratio of the cylinder over time. In addition, the flow mechanism of shock-driven interface gas mixing is analyzed from multiple perspectives by combining it with the flow field pressure, velocity, circulation, and gas mixing rate. Then the effects of different initial component distribution conditions on interface instability are investigated. The results show when the diffusion interface transit to the sharp interface, the reflection coefficient gradually increases on both sides of the interface. When the incident shock wave interacts with the cylinder, the transmission of the shock wave will transit from conventional transmission to unconventional transmission. At the same time, the reflected shock wave is gradually strengthened, and the transmitted shock wave is gradually weakened, which leads to an increase in the Richtmyer-Meshkov instability. Moreover, the Atwood number on both sides of the interface also increases as the diffusion interface transit to the sharp interface, which leads to an increase in the Rayleigh-Taylor instability and the Kelvin-Helmholtz instability. Therefore, the increase in instability will lead to an increase the circulation, resulting in an increase in the growth rate of gas mixing rate.

Keywords: shock wave, He light cylinder, Richtmyer-Meshkov instability, Gaussian distribution

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Yosra Benchaabene, Noureddine Boujnah, Faouzi Zarai

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To meet the growing demand of users, the fifth generation (5G) will continue to provide services to higher data rates with higher carrier frequencies and wider bandwidths. As part of the 5G communication paradigm, Ultra Reliable Communication (URC) is envisaged as an important technology pillar for providing anywhere and anytime services to end users. Ultra Reliable Communication (URC) is considered an important technology that why it has become an active research topic. In this work, we analyze the availability of a service in the space domain. We characterize spatially available areas consisting of all locations that meet a performance requirement with confidence, and we define cell availability and system availability, individual user availability, and user-oriented system availability. Poisson point process (PPP) and Voronoi tessellation are adopted to model the spatial characteristics of a cell deployment in heterogeneous networks. Numerical results are presented, also highlighting the effect of different system parameters on the achievable link availability.

Keywords: URC, dependability and availability, space domain analysis, Poisson point process, Voronoi Tessellation

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Authors: N. Dahbi, R. B. Taleb

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This study concerns the ion implantation of oxygen in two semiconductors Si and GaAs realized by a simulation using the SRIM tool. The goal of this study is to compare the effect of implantation energy on the distribution of implant ions in the two targets and to examine the different processes resulting from the interaction between the ions of oxygen and the target atoms (Si, GaAs). SRIM simulation results indicate that the implanted ions have a profile as a function of Gaussian-type; oxygen produced more vacancies and implanted deeper in Si compared to GaAs. Also, most of the energy loss is due to ionization and phonon production, where vacancy production amounts to few percent of the total energy.

Keywords: defect profile, GaAs, ion implantation, SRIM, phonon production, vacancies

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Authors: Hiripurage Mallika Sandamali Dissanayaka

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Butterflies are found everywhere on Earth, helping flowering plants reproduce through pollination. Wetlands perform many valuable functions such as providing wildlife habitat. Diyasaru Wetland Park was chosen as the study site. It is located in a highly urbanized area of Sri Jayawardenepura Kotte, Sri Lanka. A distribution map was prepared to increase butterfly habitat in the urbanized area, and research was conducted to determine the most suitable sections for using it. As this wetland has footpaths for walking, line transect surveys were used to mark species within the sampling area, and directly observed species were recorded. All data collection was done from 0900 to 1200 hours and 1300 to 1600 hours and fieldwork was done from 11 February 2020 to 20 January 2021. ED binoculars (10.5x45), DSLR cameras (Canon EOS/EFS5 mm 3.5-5.6), and Garmin GPS (Etrex 10) were used to observe butterfly species, identify locations, and take photographs as evidence. Analyzing their habitats using GIS (ArcGIS Pro) to identify their distribution within the park premises, the distribution density of the known size of the population was calculated for each point by kernel density, and local similarity values were calculated for each pair of corresponding features through hotspot analysis, and cell values were determined by inverse distance weighting (IDW) using a linearly weighted combination of a set of sample points. According to the maps prepared to predict the distribution of butterflies in this park, the high level of distribution or favorable areas were near flower gardens and meadows, but some individual species prefer habitats that are more suitable for their life activities, so they live in other areas. Sixty-six (66) species belonging to six (6) families have been recorded in the premises. Sixty (60) species of least concern (LC), two (2) near threatened (NT), and four (4) vulnerable (VU) species have been recorded, and several new species, such as Plum Judy (Abisara echerius), were reported. The outcome of the study will form the basis for decision-making by the Sri Lanka Land Development (SLLD) Corporation for the future development and maintenance of the park.

Keywords: wetland, Lepidoptera, habitat, urban, west

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Authors: Dariusz Jacek Jakóbczak

Abstract:

Mathematics and computer science are interested in methods of 2D curve interpolation and extrapolation using the set of key points (knots). A proposed method of Hurwitz- Radon Matrices (MHR) is such a method. This novel method is based on the family of Hurwitz-Radon (HR) matrices which possess columns composed of orthogonal vectors. Two-dimensional curve is interpolated via different functions as probability distribution functions: polynomial, sinus, cosine, tangent, cotangent, logarithm, exponent, arcsin, arccos, arctan, arcctg or power function, also inverse functions. It is shown how to build the orthogonal matrix operator and how to use it in a process of curve reconstruction.

Keywords: 2D data interpolation, hurwitz-radon matrices, MHR method, probabilistic modeling, curve extrapolation

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Authors: Yehya Rasool, Mohit Agrawal

Abstract:

The site characterization and site response analysis are the crucial steps for reliable seismic microzonation of an area. So, the basic parameters involved in these fundamental steps are required to be chosen properly in order to efficiently characterize the vulnerable sites of the study region. In this study, efforts are made to delineate the variations in the physical parameter of the soil for the summer and monsoon seasons of the year (2021) by using Horizontal-to-Vertical Spectral Ratios (HVSRs) recorded at five sites of the Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand, India. The data recording at each site was done in such a way that less amount of anthropogenic noise was recorded at each site. The analysis has been done for five seismic parameters like predominant frequency, H/V ratio, the phase velocity of Rayleigh waves, shear wave velocity (Vs), compressional wave velocity (Vp), and Poisson’s ratio for both the seasons of the year. From the results, it is observed that these parameters majorly vary drastically for the upper layers of soil, which in turn may affect the amplification ratios and probability of exceedance obtained from seismic hazard studies. The HVSR peak comes out to be higher in monsoon, with a shift in predominant frequency as compared to the summer season of the year 2021. Also, the drastic reduction in shear wave velocity (up to ~10 m) of approximately 7%-15% is also perceived during the monsoon period with a slight decrease in compressional wave velocity. Generally, the increase in the Poisson ratios is found to have higher values during monsoon in comparison to the summer period. Our study may be very beneficial to various agricultural and geotechnical engineering projects.

Keywords: HVSR, shear wave velocity profile, Poisson ratio, microtremor data

Procedia PDF Downloads 57