This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc

Future generations of wireless networks are expected to heavily rely on unmanned aerial vehicles (UAVs). UAV networks have extraordinary features like high mobility, frequent topology change, tolerance to link failure, and extending the coverage area by adding external UAVs. UAV network provides several advantages for civilian, commercial, search and rescue applications. A realistic mobility model must be used to assess the dependability and effectiveness of UAV protocols and algorithms.  In this research paper, the performance of the Gauss Markov (GM) and Random Waypoint (RWP) mobility models in multi-UAV networks for a search and rescue scenario is analyzed and evaluated. Additionally, the two mobility models GM and RWP are descr

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

The research is trying to identify the investment portfolio risks of the insurance company and their impact, on the Profitability ratios of the company, and whether the company's scientific methods followed in the measurement of these risks, and conducted research in the National Insurance Company. by relying on its annual budget as well as the annual reports, The search dealing with these data in theoretical and practical major premise to statistically significant between to investment portfolio risk and financial performance correlation and reach a set of conclusions and recommendations which are the following.                

investments include many ri

Notwithstanding the importance of international cooperation as the other facet of international interactions, a strategy of conflict resolution, a maintainer of international peace and security, its provision in the United Nations conventions, as an objective of the United Nations after the international peace and security, however, the recognition of international cooperation has not been underlined by global, intellectual think tanks. While realism emphasized on the state's role in achieving international cooperation to ensure mutual and multilateral interests, liberalism focused on the role of international organizations in building such cooperation. Additionally, constructivist approaches developed other sub-variables to contribute to t

KE Sharquie, AA Noaimi, SD Hameed, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 15

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we