Numerical simulations are carried out to assess the quality of the circular and square apodize apertures in observing extrasolar planets. The logarithmic scale of the normalized point spread function of these apertures showed sharp decline in the radial frequency components reaching to 10-36 and 10-34 respectively and demonstrating promising results. This decline is associated with an increase in the full width of the point spread function. A trade off must be done between this full width and the radial frequency components to overcome the problem of imaging extrasolar planets.
The main objective of this work was to adopt an environmentally friendly technology with enhanced results. The technology of magnetic water (MW) treatment system can be used in concrete mixture production instead of potable water (PW) to improve both workability and strength. Two types of concrete were adopted: normal concreter production with two grades 25 and 35 MPa and the self-compacted concrete (SCC) with 35 MPa grade. The concrete mixes containing MW instead of PW results showed that, for 25 MPa grade, an improvement in a compressive strength of 15.1, 14.8, and 10.2% was achieved for 7, 28, and 90 days, respectively. For 35 MPa grade, an improvement of 13.6, 11.5, and
Poly (3-hydroxybutyrate) (PHB) is a typical microbial bio-polyester reserve material; known as “green plastics”, which produced under controlled conditions as intracellular products of the secondary metabolism of diverse gram-negative/positive bacteria and various extremophiles archaea. Although PHB has properties allowing being very attractive, it is too expensive to compete with conventional and non-biodegradable plastics. Feasibility of this research to evaluate the suitability of using a watermelon-derived media as an alternative substrate for PHB synthesis under stress conditions was examined. Results, include the most nutrients extraction, indicated that the watermelon seeds contain a high content of nutrients makes them a promisi
... Show MoreFace recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.
This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J
... Show MoreA medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un
... Show MoreIn this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample
... Show MoreData Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need
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