This paper presents the thermophysical properties of zinc oxide nanofluid that have been measured for experimental investigation. The main contribution of this study is to define the heat transfer characteristics of nanofluids. The measuring of these properties was carried out within a range of temperatures from 25 °C to 45 °C, volume fraction from 1 to 2 %, and the average nanoparticle diameter size is 25 nm, and the base fluid is water. The thermophysical properties, including viscosity and thermal conductivity, were measured by using Brookfield rotational Viscometer and Thermal Properties Analyzer, respectively. The result indicates that the thermophysical properties of zinc oxide nanofluid increasing with nanoparticle volume f

Automation is one of the key systems in modern agriculture, providing potential solutions to the challenges related to the growing world population, demographic shifts, and economic situation. The present article aims to highlight the importance of precision agriculture (PA) and smart agriculture (SA) in increasing agricultural production and the importance of environmental protection in increasing production and reducing traditional production. For this purpose, different types of automation systems in the field of agricultural operations are discussed, as well as smart agriculture technologies including the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), big data analysis, in addition to agricultural robots,

Iraq is highly dependent on international markets to provide food for its residents. As imported food prices are highly dependent on crude oil prices in global markets, any shock in oil prices will have an impact on food consumption in the country. As a result, it is essential to study the demand for imported food at every time period. To the best of our knowledge as researchers, as not even a single study is available in the literature, this paper is considered the first to study the demand for imported food groups in Iraq. Therefore, the main objective of this research is to estimate demand elasticities for several imported food categories in Iraq. This study uses an Almost Ideal Demand System model to analyze the demand for imported f

A niger, a fungus which doesn't have high ability to production lipid, this fungus has been select to investigate the non oleaginicity. In this search, there are explorations about: i) growth profile ii) enzymes profile iii) isoforms. Growth profile shows that this fungus doesn't have ability to accumulate lipid more than 6% while bio mass are around 10g/l in spite of the presence of glucose in the media till the end of cultivation time and excision of nitrogen within 24 hrs. In enzyme study, we investigate all lipogenic enzymes Malic enzyme (ME), Fatty acid synthase (FAS), ATP: Citrate lays (ACL), NAD+ isocitrate dehydrogenase (NAD+ICDH), Glucose-6-phosphate (G6PD), and 6-phosphogluconate dehydrogenase (6PGD), all these enzymes show, ac

The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

Simulated annealing (SA) has been an effective means that can address difficulties related to optimization problems. is now a common discipline for research with several productive applications such as production planning. Due to the fact that aggregate production planning (APP) is one of the most considerable problems in production planning, in this paper, we present multi-objective linear programming model for APP and optimized by . During the course of optimizing for the APP problem, it uncovered that the capability of was inadequate and its performance was substandard, particularly for a sizable controlled problem with many decision variables and plenty of constraints. Since this algorithm works sequentially then the current state wi

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a