To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multiple RS datasets to overcome limitations and produce comparatively detailed outcomes. However, there are still knowledge gaps in examining the effectiveness of these RS approaches in enhancing the detection of archaeological remains/areas. Thus, this review paper is likely to deliver valuable comprehension for archaeological studies to fill knowledge gaps and further advance exploration of archaeological areas/features using RS along with DL approaches.
Maximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.
The interest of this paper is that
... Show Morethe pursue of social systems history present to us solid evidence that the collapse of that systems be caused by either the stagnancy aftermath maturity or unreal intellectual foundation which lead to sudden collapse, while the capitalism can avoided that intellectual damages due to its dynamic system with appropriate auto adaptation mechanism and use it excellently in the right time.
The globalization had excrete (as one of the capitalism adaptation mechanism) its own targets and its methods in framework of multinationals corporations which consist with capitalism states that employed the international organizations to reconstruction the global economy to serve such targets. So the glob
... Show Moreالنظام السياسي اليمني : دراسة في المتغيرات الداخلية
This research was aimed to study the osmotic efficiency of the draw solutions and the factors affecting the performance of forward osmosis process : The draw solutions used were magnesium sulfate hydrate (MgSO4.7H2O) pojtassium chloride (KCL), calcium chloride (CaCl2) and ammonium bicarbonate (NH4HCO3). It was found that water flux increases with increasing draw solution concentration, and feed solution flow rate and decreases with increasing draw solution flow rate and feed solution concentration. And also found that the efficiency of the draw solutions is in the following order:
CaCl2> KCI > NH4HCO3> MgSO4.7H
In this article, a new deterministic primality test for Mersenne primes is presented. It also includes a comparative study between well-known primality tests in order to identify the best test. Moreover, new modifications are suggested in order to eliminate pseudoprimes. The study covers random primes such as Mersenne primes and Proth primes. Finally, these tests are arranged from the best to the worst according to strength, speed, and effectiveness based on the results obtained through programs prepared and operated by Mathematica, and the results are presented through tables and graphs.
Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.
We compare two methods Bayesian and . Then the results were compared using MSe criteria.
A simulation had been used to study the empirical behavior for the Logistic model , with different sample sizes and variances. The results using represent that the Bayesian method is better than the at small samples sizes.
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