Coral reef area in northwest of the Arabian Gulf was investigated for mineralogy and geochemistry to throw lights on such unique Iraqi Marine Environment; six specimens of two main species of coral reefs, Platygyra pini Chevalier, 1975 and Octocoral Menella were collected at two sites. While eight samples of the surrounding sediments are chosen from other two sites. The mineralogy is determined by XRD, and reveals that calcite, low magnesium-calcite, and aragonite are the main minerals that comprise the Octocoral Menella in site 1, whilst aragonite and calcite are dominate in the P. pini coral reef at site 4.

    The non–carbonate fractions indicate that thes

The tourism activity is one of the pillars on which the economy of any country is based , the importance of the tourism sector is reflected in its potential to become an effective development alternative in many countries, especially Iraq ,this has a direct impact on the national economy as an important source in attracting hard currency and eliminating unemployment. Adding the Iraqi Marshlands to the list of effects makes it contribute to diversification of sources of income and stimulating rest of the economic sectors, the potentials and qualifications possessed by Iraq in the field of tourism and monuments have a significant impact on the state budget if they were exploited optimally. The research aims at identifying the contr

Abstract

      The changes that happened in the environment of  business have great effects upon organizations with different activities specially the banks  which requires the existence of an able opinion  resources can adapt with the changes . Accordingly importance put upon  intellectual  capital which become one of the basic resources for organizations and one of success and growth elements with the availability of expertise , skills and capability of making  essential changes in different process due to the presentation of innovations and creations of the to support banks activities .Therefore the intellectual  capital represents the more r

Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

      In this work, a test room was built in Baghdad city, with (2*1.5*1.5) m³  in dimensions, while the solar chimneys (SC) were designed with aspect ratio (ar) bigger than 12. Test room was supplied by many solar collectors; vertical single side of air pass with ar equals 25, and tilted 45^o double side of air passes with ar equals 50 for each pass, both collectors consist of flat thermal energy storage box collector (TESB) that covered by transparent clear acrylic sheet, third type of collector is array of evacuated tubular collectors with thermosyphon in 45^o instelled  in the bottom of TESB of vertical SC. The TESB was