The research studied and analyzed the hybrid parallel-series systems of asymmetrical components by applying different experiments of simulations used to estimate the reliability function of those systems through the use of the maximum likelihood method as well as the Bayes standard method via both symmetrical and asymmetrical loss functions following Rayleigh distribution and Informative Prior distribution. The simulation experiments included different sizes of samples and default parameters which were then compared with one another depending on Square Error averages. Following that was the application of Bayes standard method by the Entropy Loss function that proved successful throughout the experimental side in finding the reliability function for the soap manufacturing machines of the State Company for Vegetable Oils Industries whose behavior was based on the hybrid parallel-series system of a symmetrical component that followed both the exponential distribution and the Rayleigh distribution.
Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce
... Show MoreThe aim of this research was to estimate the production function to measure returns to scale and distribution efficiency of resources used in the production of wheat. Cross sectional data used of a random sample of 130 farmers in Dhi Qar Province. The results of the quantitative analysis of estimating production function showed that the double logarithmic form was the best estimated model based on economic and statistical indicators. However, that form suffered from heteroscedasticity and autocorrelation, so the robust regression technique was chosen. Value of returns to scale was 0.89 and this indicates decreasing returns to scale. This means that production function is in the second stage of the function. The results of the dist
... Show MoreLead-acid batteries have been used increasingly in recent years in solar power systems, especially in homes and small businesses, due to their cheapness and advanced development in manufacturing them. However, these batteries have low voltages and low capacities, to increase voltage and capacities, they need to be connected in series and parallel. Whether they are connected in series or parallel, their voltages and capacities must be equal otherwise the quality of service will be degraded. The fact that these different voltages are inherent in their manufacturing, but these unbalanced voltages can be controlled. Using a switched capacitor is a method that was used in many methods for balancing voltages, but their respons
... Show MoreABSTRACT Background: The main goal of chemomechanical endodontic treatment is the reduction or elimination of microorganisms from root canal system. The intracanal medicaments were used to enhance the disinfection process. This study was conducted to evaluate the antibacterial effect of thymus vulgaris, tea tree essential oils and cold pressed black seed oil (BSO) against E.faecalis. Materials and methods: E.faecalis was isolated from ten patients in need for endodontic treatment. The sensitivity of E.faecalis to the tested oils was evaluated in different concentrations in agar well diffusion method and compared with calcium hydroxide. The sensitivity of E.faecalis to vapor of the tested oils was also evaluated, in disk vaporization method
... Show MoreIn this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete
... Show MoreThis research aims to identify the role that forensic accounting plays on the transparency and quality of the financial statements in trade bank of Iraq and the Gulf Commercial Bank in Babylon. This research came to address the problem that most financial institutions suffer from, which is represented by the lack of transparency and the quality of the financial statements issued in a manner. Annual also the manipulation and fraud in the financial data, which causes a big gap between that institutions and organizational stakeholders. According to the implementation of the research hypothesis and the objectives of the research, a questionnaire was prepared consisting of three axes, the first axis dealing with the demographic distri
... Show More"The aim of the research is to identify the availability of the dimensions of the research variables represented by organizational symmetry and the quality of work-life at the University of Information and Communications Technology, which is one of the formations of the Ministry of Higher Education and Scientific Research in Baghdad, in addition to knowing the relationship and influence between them. The research relied on the descriptive analytical approach based on peer description. The research was analyzed and the research sample consisted of (148) individuals, the sample was chosen using the comprehensive inventory method, data was obtained by relying on the questionnaire which was prepared from ready-made m
... Show MoreThe operation and management of water resources projects have direct and significant effects on the optimum use of water. Artificial intelligence techniques are a new tool used to help in making optimized decisions, based on knowledge bases in the planning, implementation, operation and management of projects as well as controlling flowing water quantities to prevent flooding and storage of excess water and use it during drought.
In this research, an Expert System was designed for operating and managing the system of AthTharthar Lake (ESSTAR). It was applied for all expected conditions of flow, including the cases of drought, normal flow, and during floods. Moreover, the cases of hypothetical op
... Show MoreThe effect of the concentration of the colloidal nanomaterial on their optical limiting behavior is reported in this paper. The colloids of sliver nanoparticles in deionized water were chemically prepared for the two concentrations (31 ppm and 11ppm). Two cw lasers (473 nm Blue DPSS laser and 532 nm Nd:YAG laser) are used to compare the optical limiting performance for the samples. UV–visible spectrophotometer, transmission electron microscope (TEM) and Fourier Transformation Infrared Spectrometer (FTIR) were used to obtain the characteristics of the sample. The nonlinear refractive index was calculated to be in the order of 10-9 cm2/W. The results demonstrate that the observed limiting response is significant for 532nm. In addition, t
... Show MoreEmotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
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