The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

This paper describes a new finishing process using magnetic abrasives were newly made to finish effectively brass plate that is very difficult to be polished by the conventional machining processes. Taguchi experimental design method was adopted for evaluating the effect of the process parameters on the improvement of the surface roughness and hardness by the magnetic abrasive polishing. The process parameters are: the applied current to the inductor, the working gap between the workpiece and the inductor, the rotational speed and the volume of powder. The analysis of variance(ANOVA) was analyzed using statistical software to identify the optimal conditions for better surface roughness and hardness. Regressions models based on statistical m

In this paper, we present a comparison of double informative priors which are assumed for the parameter of inverted exponential distribution.To estimate the parameter of inverted exponential distribution by using Bayes estimation ,will be  used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of inverted exponential distribution. Also assumed Chi-squared - Gamma distribution, Chi-squared - Erlang distribution, and- Gamma- Erlang distribution as double priors. The results are the derivations of these estimators under the squared error loss function with three different double priors.

Additionally Maximum likelihood estimation method

The ionospheric characteristics exhibit significant variations with the solar cycle, geomagnetic conditions, seasons, latitudes and even local time. Representation of this research focused on global distribution of electron (Te) and ion temperatures (Ti) during great and severe geomagnetic storms (GMS), their daily and seasonally variation for years (2001-2013), variations of electron and ion temperature during GMS with plasma velocity and geographic latitudes. Finally comparison between observed and predicted Te and Ti get from IRI model during the two kinds of storm selected. Data from satellite Defense Meteorological Satellite Program (DMSP) 850 km altitude are taken for Te, Ti and plasma velocity for different latitudes during great

In this paper, the dynamic of quark and anti-quark interaction has been used to study the production of photons in the annihilation process based on the theory of chromodynamic. The rate of the photon is to be calculated for charm and anti-strange interaction c→γg system with critical temperature 113 and 130 MeV and photon energy GeV/c. Here the critical temperature, strength coupling and photons energy are assumed to be affected dramatically on the rate of photons emission of state interaction c, which can form gluon possible structures and photon emission state. The decreased photons emission yields with increased strength couple of quarks reaction due to increase critical temperature from 113 MeV to 130 MeV were predicted. We

Asphalt binder is a thermoplastic material that conducts as an elastic solid at lower service temperatures or throughout fast loading rate. At a high temperature or slow rate of loading, asphalt binder conducts as a different liquid. The classical duplication generates a required to assess the mechanical properties of asphalt concrete at the anticipated service temperature to reduce the stress cracking, which happens at lower temperatures, fatigue, and the plastic deformation at higher temperatures (rutting). In this study, an achievement was made to assess the effect of temperature on the mechanical characteristics of asphalt concrete mixes. A total of 132 asphalt concrete samples were attended utilizing two asphalt cement grades (40-50) a

Asphalt pavement properties in Iraq are highly affected by elevated summer air temperatures. One of these properties is stiffness (resilient modulus). To explain the effect of air temperatures on stiffness of asphalt concrete, it is necessary to determine the distribution of temperatures through the pavement asphalt concrete layers. In this study, the distribution of pavement temperatures at three depths (2cm,7cm, 10cm) below the pavement surface is determined by using the temperature data logger instrument. A relationship for determining pavement temperature as related to depth and air temperature has been suggested. To achieve the objective of this thesis, the prepared specimens have been tested for indirect tension in accordance with

Measurements of Hall effect properties at different of annealing temperature have been made on polycrystalline Pb0.55S0.45 films were prepared at room temperature by thermal evaporation technique under high vacuum 4*10-5 torr . The thickness of the film was 2?m .The carrier concentration (n) was observed to decrease with increasing the annealing temperature. The Hall measurements showed that the charge carriers are electrons (i.e n-type conduction). From the observed dependence on the temperature, it is found that the Hall mobility (µH), drift velocity ( d) carrier life time ( ), mean free path (?) were increased with increasing annealing temperature

Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.