Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that represents the relationship between the compared texts and extracts the degree of similarity between them. Representing a text as a semantic network is the best knowledge representation that comes close to the human mind's understanding of the texts, where the semantic network reflects the sentence's semantic, syntactical, and structural knowledge. The network representation is a visual representation of knowledge objects, their qualities, and their relationships. WordNet lexical database has been used as a knowledge-based source while the GloVe pre-trained word embedding vectors have been used as a corpus-based source. The proposed method was tested using three different datasets, DSCS, SICK, and MOHLER datasets. A good result has been obtained in terms of RMSE and MAE.
The present study deals with the strategies used in the Arabic translations of the most popular genres of children’s literature; namely fairy tales and fables as an attempt to identify the best methods and strategies to be adopted in translating these genres to fulfill the ultimate purpose of enriching the children’s knowledge in addition to attracting their interest and arousing the joy sought for in every piece of literature.
The study sets off from three dominating trends: the first calls for the adoption of domestication strategy of translation as the most appropriate and effective strategy in translation for children. In the same line, the second opposes using the foreignization strategy, w
... Show MoreIn 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
... Show MoreThe construction industry in Iraq suffers from many problems, perhaps the most important of which is the delay in time and the increase in costs. Therefore, it was necessary to try to adopt a new methodology that would help in overcoming these problems. It was suggested to combine building information modeling with the agile management approach because this technique and methodology is modern and helps in reducing time and cost and improving quality. This paper aims to know the status of using Building Information Modeling (BIM) and Agile Project management (APM) in Iraq and to shed light on the merging of this integration, explaining the benefits, difficulties, and workflow practices, finding the most influencing factors on the tim
... Show MoreTo obtain the approximate solution to Riccati matrix differential equations, a new variational iteration approach was proposed, which is suggested to improve the accuracy and increase the convergence rate of the approximate solutons to the exact solution. This technique was found to give very accurate results in a few number of iterations. In this paper, the modified approaches were derived to give modified solutions of proposed and used and the convergence analysis to the exact solution of the derived sequence of approximate solutions is also stated and proved. Two examples were also solved, which shows the reliability and applicability of the proposed approach.
Every so often, a confluence of novel technologies emerges that radically transforms every aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of human ingenuity are known as industrial revolutions, and we are currently in the midst of the fourth such revolution, coined Industry 4.0 by the World Economic Forum. Building on their guideline set of technologies that encompass Industry 4.0, we present a full set of pillar technologies on which Industry 4.0 project portfolio management rests as well as the foundation technologies that support these pillars. A complete model of an Industry 4.0 factory which relies on these pillar technologies is presented. The full set of pillars encompasses cyberph
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreIn this article we propose a general Bayesian estimation framework for the Birnbaum-Saunders Quantile Regression (BSQ) model which is used to analyze asymmetric and heterogeneous economic data. In this work, the novel aspect is the joint incorporation of several existing surrogate structures (with different degrees of approximation) and decision-theoretic loss functions (with direct impact on estimation performance trade-offs) under a common BSQ framework conducive to systematic testing of their effect on quantile estimation performance. We consider two previous prior specifications which are Jeffreys prior and weakly informative priors together with three loss functions quadratic, LINEX and the proposed quadratic-logarithmic loss function.
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreThis 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