Abstract:

The models of time series often suffer from the problem of the existence of outliers ​​that accompany the data collection process for many reasons, their existence may have a significant impact on the estimation of the parameters of the studied model. Access to highly efficient estimators  is one of the most important stages of statistical analysis, And it is therefore important to choose the appropriate methods to obtain good  estimators. The aim of this research is to compare the ordinary estimators and the robust estimators of the estimation of the parameters of

Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

The aim of this research is to assess the validity of Detailed Micro-Modeling (DMM) as a numerical model for masonry analysis. To achieve this aim, a set of load-displacement curves obtained based on both numerical simulation and experimental results of clay masonry prisms loaded by a vertical load. The finite element method was implemented in DMM for analysis of the experimental clay masonry prism. The finite element software ABAQUS with implicit solver was used to model and analyze the clay masonry prism subjected to a vertical load. The load-displacement relationship of numerical model was found in good agreement with those drawn from experimental results. Evidence shows that load-displacement curvefound from the finite element m

In this study, the optimum conditions for COD removal from petroleum refinery wastewater by using a combined electrocoagulation- electro-oxidation system were attained by Taguchi method. An orthogonal array experimental design (L18) which is of four controllable parameters including NaCl concentration, C.D. (current density), PH, and time (time of electrolysis) was employed. Chemical oxygen demand (COD) removal percentage was considered as the quality characteristics to be enhanced. Also, the value of turbidity and TDS (total dissolved solid) were estimated. The optimum levels of the studied parameters were determined precisely by implementing S/N analysis and analysis of variance (ANOVA). The optimum conditions were found to be NaCl = 2.5

This paper describes a research effort that aims of developing solar models for housing suitable for the Arabian region since the Arabian Peninsula is excelled with very high levels of solar radiation.
The current paper is focused on achieving energy efficiency through utilizing solar energy and conserving energy. This task can be accomplished by implementation the major elements related to energy efficiency in housing design , such as embark on an optimum photovoltaic system orientation to maximize seize solar energy and produce solar electricity. All the precautions were taken to minimizing the consumption of solar energy for providing the suitable air-condition to the inhibitor of the solar house in addition to use of energy effici

Stone Matrix Asphalt (SMA) is a gap-graded asphalt concrete hot blend combining high-quality coarse aggregate with a rich asphalt cement content. This blend generates a stable paving combination with a powerful stone-on-stone skeleton that offers excellent durability and routing strength. The objectives of this work are: Studying the durability performance of stone matrix asphalt (SMA) mixture in terms of moisture damage and temperature susceptibility and Discovering the effect of stabilized additive (Fly Ash ) on the performance of stone matrix asphalt (SMA) mixture. In this investigation, the durability of stone matrix asphalt concrete was assessed in terms of temperature susceptibility, resistance to moisture damage, and sensitivity t

       The study aimed to determine the extent of market knowledge in the companies researched, as if market knowledge is qualified to lead the companies researched to achieve marketing performance , for this purpose, formulated hypotheses of the study in three hypotheses, the first major hypothesis "there is a correlation with significance of market knowledge to improve the marketing performance  , "while the second major hypothesis, "there is a significant moral influence of market knowledge to improve the marketing performance  " these hypotheses targeting to determine the role played by market knowledge in the leadership of companies researched to achieve improvement in marketing perfor