Towards Space Sensor Network and Internet of Things: Merging CubeSats with IoT
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The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe
The aim of this research is to show the level of banking leadership trends in the importance of organizational confidence and its reflection in the dimensions of the strategic position the research was applied in a bank (Al- Mansour Investment, Business Bay), and the Questionnaire Was adopted as a tool to collect data and information from the number of the sample (15) who are in allocation (Department Manager, Department Manager Department Manager, Division Officer, Unit Officer) and he used the statistical program (spss) to calculate (standard deviation, arithmetic mean, percentages, regression, analysis,F-test coefficient of determination R2, Coefficieent, square Kay and the research reached a number of conclusions, the mos
... Show MoreAerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A
... Show MoreThe operative system of theatrical performance depends on the construction of the scenographic space, as it constitutes the most aesthetic effect of the recipient, and the body of the theatrical discourse that contains the signs of the show, and it comes as an embodiment of the directing vision of the show director, so most of the world directors resorted to attention to the output treatment to establish the scenographic space, and thus it possesses a contrast in The embodiment of the directing vision according to the stylistic and hermeneutical dimension of the director, so the two researchers found the importance of studying the topic, and the study came under the title (Directing Treatments of the Scenographic Space in the Iraqi Theat
... Show MoreThe research aims to identify the future teachers' attitudes toward cloud computing in the Kingdom of Saudi Arabia from their point of view. The research adopted the descriptive approach, and a questionnaire was applied to a random sample of (370) male and female teachers in governmental and private general education schools in the Al-Jouf region, Saudi Arabia. The results of the research concluded that the reality of future teachers' attitudes towards cloud computing in the Kingdom of Saudi Arabia from their point of view is very high and that most areas of using computing are in the field of assessment, then teaching, and activities. The challenges of future teachers' attitudes toward cloud computing are recorded at a high level, parti
... Show MoreCredit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering res
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