The Normalization Difference Vegetation Index (NDVI), for many years, was widely used in remote sensing for the detection of vegetation land cover. This index uses red channel radiances (i.e., 0.66 μm reflectance) and near-IR channel (i.e., 0.86 μm reflectance). In the heavy chlorophyll absorption area, the red channel is located, while in the high reflectance plateau of vegetation canopies, the Near-IR channel is situated. Senses of channels (Red & Near- IR) read variance depths over vegetation canopies. In the present study, a further index for vegetation identification is proposed. The normalized difference vegetation shortwave index (NDVSI) is defined as the difference between the cubic bands of Near- IR and Shortwave infrared radiation (SWIR) divided by their sums. The radiances or reflectances are included in this index from the Near-IR channel and WSIR2 channel (2.1 μm). The NDVSI is less sensitivite to atmospheric effects as compared to NDVI. By comparing the one NDVSI index with the two indexes (NDVI, SAVI) of vegetation cover, good correlations were found between NDVI and NDVSI (R2=0.917) and between SAVI and NDVSI (R2=0.809. Accordingly, the proposed index can be taken into consideration as an independent vegetation index
The aim of this article is to solve the Volterra-Fredholm integro-differential equations of fractional order numerically by using the shifted Jacobi polynomial collocation method. The Jacobi polynomial and collocation method properties are presented. This technique is used to convert the problem into the solution of linear algebraic equations. The fractional derivatives are considered in the Caputo sense. Numerical examples are given to show the accuracy and reliability of the proposed technique.
The dependence of the cross-section of the coherent and incoherent radiation peaks in the X-ray absorption experiment of different energies (20-800 Kev) was investigated. Cross-sectional dependence on the atomic number Z was included from the published data for (8) elements, ranging from carbon to silver (C-Ag). The proportional constant K was obtained between (σc/σi), with the atomic number Z from (6-47). The results show that the value of K exponentially changes with energy.
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The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen
... Show MoreResearchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat
... Show MoreSupport vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
... Show MoreThe proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
... Show MoreBackground:Varicoceles, present in 15% to 20% of men, are the most common abnormal finding among men presenting with infertility, yet controversy exists regarding their etiology. Anecdotal experience suggests that varicoceles are more prevalent in lean men, supporting the "nutcracker" effect of the superior mesenteric artery compressing the left renal vein over the aorta.
Materials and methods: A total of 206 males with varicocele attending the urological out patient clinic were evaluated from their physical screening examinations. All subjects underwent history taking and physical examinations to evaluate for the presence and severity of varicocele ht,weight and BMI, those compared with 206 men without v