Keratoconus Severity Detection From Elevation, Topography and Pachymetry Raw Data Using a Machine Learning Approach
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The present study aimed to try to find natural substances stimulate the production of bacteriocin, as well as "for detection of bacteriocin producing isolates. Two hundred and eighty ( 280) bacterial isolates, gram negative only, were collected from 760 different pathogenic samples, consist: (Urinary tract infection, septicemia, Vaginal inflammation and diarrhea). The isolated bacteria are: Escherichia coli, Klebsiella pneumonia Pseudomonas aeruginosa,, Salmonella typhi, Enterobacter cloacae, Acinetobacter baumannii, Serratia liquefaciens, Citrobacter freundii, Proteus mirabilis and Serrattia odorifera. Cup assay method was used to detect bacteriocin production. Loc
... Show MoreThis paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi
... Show MoreThe antiviral activity of leaf extracts from Datura stramonium and tomato plants inoculated with TMV, combined with 20% skimmed milk, was investigated. A TMV isolate was confirmed using bioassay, serological, and molecular approaches and subsequently used to inoculate plants. Tomato plants, both pre- and post-inoculated with TMV, were sprayed with leaf extracts from either TMV-free or infected plants, alone or mixed with 20% skimmed milk. Enzyme-linked immunosorbent assay (ELISA) using tobamovirus-specific antibodies and local lesion tests were conducted to assess antiviral activity based on virus concentration and infectivity in treated plants. The experiment followed a completely randomized design (CRD), and the Least Significant
... Show MoreA three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
... Show MorePectin is available in many plants and in this study, the peels of tomatoes and beet were used to be an economical source of pectin production instead of dumping it with waste or using it as animal feed. The pectin extracted from the peels using different solutions, namely citric acid (2 M), oxalic acid (2%) and hydrochloric acid (0.5 M) the outcome of the extraction methods, 7. 1%, 6% and 11% respectively for tomatoes peels, while the pectin of beet peels were 8%, 6.5%, and 8.3%, and the highest percentage obtained in the manner of hydrochloric acid adopted in the manufacture of yogurt.Yogurt was manufactured with four treatments, in the first treatment standard pectin was added and the second treatment in addition to the pectin extracted
... Show MoreBuilding numerical reservoir simulation model with a view to model actual case requires enormous amount of data and information. Such modeling and simulation processes normally require lengthy time and different sets of field data and experimental tests that are usually very expensive. In addition, the availability, quality and accessibility of all necessary data are very limited, especially for the green field. The degree of complexities of such modelling increases significantly especially in the case of heterogeneous nature typically inherited in unconventional reservoirs. In this perspective, this study focuses on exploring the possibility of simplifying the numerical simulation pr
The resort to the eloquence of the poetic image as a style reveals the poet's creativity and creativity in dealing with external influences, and reflect them with emotional images express a sense of intense emotional imagination, and this imagination stems from the experience of a poetic sense of truth, tasted by the recipient before the creator of the poetic text.
Research Objectives: The research aims to highlight the approach of Imam Al-Qaradawi in contemporary jurisprudence in the recent issues of the jurisprudence of minorities, and mentioning the foundations of jurisprudence of minorities, along with some of the practical applications of Imam Al-Qaradawi.
Study Methodology: The researcher applied the inductive, analytical and comparative approach by tracking the scientific material related to the subject of the study from the books of Al-Qaradawi in the first place, then by comparing the legal provisions with what had been stated in the four schools of jurisprudence.
Findings: The interest and need of Muslim minorities in non-
... Show MoreWithin the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo
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