To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distributes network traffic to suitable paths, in addition to supervising link and path loads. A scenario with a minimum spanning tree (MST) routing algorithm and another with open shortest path first (OSPF) routing algorithms were employed to assess the SFSA. By comparison, to these two routing algorithms, the suggested SFSA strategy determined a reduction of 2% in packets dropped ratio (PDR), a reduction of 15-45% in end-to-end delay according to the traffic produced, as well as a reduction of 23% in round trip time (RTT). The Mininet emulator and POX controller were employed to conduct the simulation. Another advantage of the SFSA over the MST and OSPF is that its implementation and recovery time do not exhibit fluctuations. The smart flow steering agent will open a new horizon for deploying new smart agents in SDN that enhance network programmability and management.
Native speakers of English from different parts of the world have different accents,but the differences of accents are mainly the result of differences in the sound of vowels and consonants . The actual use of all these sounds in combination leads the speaker to produce a number of segments which only appear on the production level and realized on the perceptual one . RP pronunciation represents the teachable variety in all Iraqi universities because it is the most acceptable and understandable accent all over the world and not only in South East London ..The structure of the English syllable in RP pronunciation is influenced by the appearance of certain allophones especially aspiration and glottalization which ch
... Show MoreA new method for determination of allopurinol in microgram level depending on its ability to reduce the yellow absorption spectrum of (I-3) at maximum wavelength ( ?max 350nm) . The optimum conditions such as "concentration of reactant materials , time of sitting and order of addition were studied to get a high sensitivity ( ? = 27229 l.mole-1.cm-1) sandal sensitivity : 0.0053 µg cm-2 ,with wide range of calibration curve ( 1 – 9 µg.ml-1 ) good stability (more then24 hr.) and repeatability ( RSD % : 2.1 -2.6 % ) , the Recovery % : ( 98.17 – 100.5 % ) , the Erel % ( 0.50 -1.83 % ) and the interference's of Xanthine , Cystein , Creatinine , Urea and the Glucose in 20 , 40 , 60 fold of analyate were also studied .
In this paper, two meshless methods have been introduced to solve some nonlinear problems arising in engineering and applied sciences. These two methods include the operational matrix Bernstein polynomials and the operational matrix with Chebyshev polynomials. They provide an approximate solution by converting the nonlinear differential equation into a system of nonlinear algebraic equations, which is solved by using
This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
Objective: Assessment of health problems and identify demographical information to elderly. Methodology:
it is a descriptive study, data were collected by the researchers depended on the direct interview with the
elderly by using the study instrument (questionnaire) as well as review the records of the geriatric.
Results: The majority of study sample (66%) were males and (24.3%) were within age group (70-74) years,
(44.7%) were widows, and (41.7%) did not read and write. This study applied the international classification
of diseases(short-table) in (11) items, which stated that most of the elderly were complaining from
health problems: debility of hearing (80.65%), eczema or allergies (69.35%), debility of vision (66.9