The present work aimed to study effect of (N749 & N3) dyes on TiO2 optical and electrical properties for optoelectronic application. The TiO2 paste prepared by using a doctor blade method. The samples were UV-VIS specterophometricall analyzes of TiO2 before and after immersed in dyes (N749 & N3). The results showed absorption spectra shift toward the visible region due to the adsorption of dye molecules on the surface of oxide nanoparticles. It is seen that the Eg determined to give a value of 3.3eV for TiO2 before immersing in dyes, and immersing in dyes (N749 & N3) are (1.4 &1.6 eV) respectively. The structural properties (XRD), (FTIR) and (SEM) for the sample prepared were investigated and (J-V) characteristics was stu

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

This research aims to analyze the impact of effective manufacturing strategy on total productive maintenance. Effective manufacturing focuses on improving product quality, increasing productivity, and reducing costs, while total productive maintenance focuses on maintaining machines and equipment in good operational condition and high efficiency. The research seeks to understand how to achieve integration between these two dimensions to achieve excellent performance in manufacturing operations. The study was conducted using the General Company for Battery Manufacturing as a research community, with a sample size of 60 individuals. The research found significant results, including the fact that using an effective manufacturing strategy leads

Moisture induced damage can cause a progressive deterioration in the performance of asphalt pavement by the loss of adhesion between asphalt binder and aggregate surface and/or loss of cohesion within the binder in the presence of water. The objective of this paper is to improve the asphalt mixtures resistance to moisture by using hydrated lime as an anti-stripping additive. For this purpose, two types of asphalt binder were utilized; asphalt grades (40-50) and (60-70) with one type of aggregate of 19.0 mm aggregate nominal maximum size, and limestone dust as a mineral filler. Marshall method was adopted to find the optimum asphalt content. Essentially, two parameters were determined to evaluate the moisture susceptibili

Abstract
This study was conducted by using soil map of LD7 project to interpret the
distribution and shapes of map units by using the index of compaction as an
index of map unit shape explanation. Where there were wide and varied
ranges of compaction index of map units, where the maximum value was
0.892 for MF9 map unit and the lower value was 0.010 for same map unit.
MF9 has wide range appearance of index of compaction after those indices
were statistically analyzed by using cluster analysis to group the similar
ranges together to ease using their values, so the unit MF9 was considered as
key map unit that appears in the soils of LD7 project which may be used to
expect another map units existence in area of

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien