A lotic ecosystem is considered a source of carbon dioxide (CO2) in the atmosphere where it becomes supersaturated with CO2, which contributes to the global carbon cycle. To enhance our comprehension of the roles of CO2 in rivers, an outdoor experiment was designed with controlled carbon source inputs to investigate the roles of the dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) in the phytoplankton community. Plastic enclosures were installed in the Tigris River within Baghdad for that goal. Samples were collected on the first day, as well as on the 5th and the 12th days from 14 enclosures. The enclosures were treated by artificial glucose (C6H12O6) (10, 20, 30mg/ l) as DOC sources, while sodium bicarbonate (NaHCO3) (10, 20, 30μM) was used as a DIC source. The results showed that the concentration of nitrate (NO3 -) and phosphate (PO4 3-) changed over time and weren’t affected by the treatments. On the other hand pH, DOC, and CO2 concentrations were affected by treatments. Moreover, our results indicated that DOC and DIC treatments had a direct impact on phytoplankton biomass growth via increasing chlorophyll (Chl) concentration. Overall, it was concluded that different carbon sources (DOC and CO2) could be essential factors that shape river ecosystems function through influencing the base of food webs.
This research was aimed to determine the petrophysical properties (porosity, permeability and fluid saturation) of a reservoir. Petrophysical properties of the Shuiaba Formation at Y field are determined from the interpretation of open hole log data of six wells. Depending on these properties, it is possible to divide the Shuiaba Formation which has thickness of a proximately 180-195m, into three lithological units: A is upper unit (thickness about 8 to 15 m) involving of moderately dolomitized limestones; B is a middle unit (thickness about 52 to 56 m) which is composed of dolomitic limestone, and C is lower unit ( >110 m thick) which consists of shale-rich and dolomitic limestones. The results showed that the average formation water
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There are many factors effect on the spread of infectious disease or control it,
some of these factors are (immigration and vaccination). The main objective of this
paper is to study the effect of those factors on the dynamical behavior of an SVIR
model. It is assumed that the disease is spread by contact between members of
populations individuals. While the recovered individuals gain permanent immunity
against the disease. The existence, uniqueness and boundedness of the solution of
this model are investigated. The local and global dynamical behaviors of the model
are studied. The local bifurcations and Hopf bifurcation of the model are
investigated. Finally, in order to confirm our obtained results and specify t
Abstract
Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance. This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H2/H∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS). Simulatio
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One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone
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An assembled pulsed Nd:YAG laser-robot system for spot welding similar and dissimilar metals is presented in this paper. The study evaluates the performance of this system through investigating the possibility and accuracy of executing laser spot welding of 0.2 mm in thickness stainless steel grade AISI302 to 0.5 mm in thickness low carbon steel grade AISI1008. The influence of laser beam parameters (peak power, pulse energy, pulse duration, repetition rate, and focal plane position on the final gained best results are evaluated. Enhancement of the experimental results was carried by a computational simulation using ANSYS FLUENT 6.3 package code.
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In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f
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With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t
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