The historical center's landscape suffers from neglect, despite their importance and broad capabilities in enhancing the cultural value of the historical center, as landscape includes many heterogeneous human and non-human components, material and immaterial, natural and manufactured, also different historical layers, ancient, modern and contemporary. Due to the difference in these components and layers, it has become difficult for the designer to deal with it. Therefore, the research was directed by following a methodology of actor-network theory as it deals with such a complex system and concerned with an advanced method to connect the various components of considering landscape as a ground that can include various elements and deal wi

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

<span lang="EN-US">Iraqi people have been without energy for nearly two decades, even though their geographic position provides a high intensity of radiation appropriate for the construction of solar plants capable of producing significant quantities of electricity. Also, the annual sunny hours in Iraq are between 3,600 to 4,300 hours which makes it perfect to use the photovoltaics arrays to generate electricity with very high efficiency compared to many countries, especially in Europe. This paper shows the amount of electric energy generated by the meter square of crystalline silicon in the photovoltaic (PV) array that already installed in 18 states in Iraq for each month of the year. The results of the meter-square of PV arr

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

Three hundred Iraqi people participated in demographic and attitudes study about red and white meat consumption. The mean age of the participants was 50 SD ± 11 years (mean 30-72); 51% were females and 49% males, mostly in forties who lived ≥ 5 years in Baghdad. The results showed that 80% of individuals prefer red meat. A 90% of people prefer fresh meat compared to frozen and processed meat. A 60% of people buy meat from popular markets. Nearly 87% of respondents believe the improving of livestock sector is essential and 80% of people confirmed there are obstacles to development this sector. An 80% of participates thought the reasons of the high prices of local fresh meat is the lack of plann

Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were

To avoid the negative effects due to inflexibility of the domestic production inresponse to the increase in government consumption expenditure leads to more  imports to meet the increase in domestic demand resulting from the increase in government consumption expenditure. Since the Iraqi economy economy yield unilateral depends on oil revenues to finance spending, and the fact government consumer spending is a progressive high flexibility the increase in overall revenues, while being a regressive flexibility is very low in the event of reduced public revenues, and therefore lead to a deficit in the current account position. And that caused the deficit for imbalance are the disruption of the

In recent years, data centre (DC) networks have improved their rapid exchanging abilities. Software-defined networking (SDN) is presented to alternate the impression of conventional networks by segregating the control plane from the SDN data plane. The SDN presented overcomes the limitations of traditional DC networks caused by the rapidly incrementing amounts of apps, websites, data storage needs, etc. Software-defined networking data centres (SDN-DC), based on the open-flow (OF) protocol, are used to achieve superior behaviour for executing traffic load-balancing (LB) jobs. The LB function divides the traffic-flow demands between the end devices to avoid links congestion. In short, SDN is proposed to manage more operative configur