The majority of systems dealing with natural language processing (NLP) and artificial intelligence (AI) can assist in making automated and automatically-supported decisions. However, these systems may face challenges and difficulties or find it confusing to identify the required information (characterization) for eliciting a decision by extracting or summarizing relevant information from large text documents or colossal content. When obtaining these documents online, for instance from social networking or social media, these sites undergo a remarkable increase in the textual content. The main objective of the present study is to conduct a survey and show the latest developments about the implementation of text-mining techniques in humanities when summarizing and eliciting automated decisions. This process relies on technological advancement and considers (1) the automated-decision support-techniques commonly used in humanities, (2) the performance evolution and the use of the stylometric approach in text-mining, and (3) the comparisons of the results of chunking text by using different attributes in Burrows' Delta method. This study also provides an overview of the efficiency of applying some selected data-mining (DM) methods with various text-mining techniques to support the critics' decision in artistry ‒ one field of humanities. The automatic choice of criticism in this field was supported by a hybrid approach to these procedures.
Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
... Show MorePhishing is an internet crime achieved by imitating a legitimate website of a host in order to steal confidential information. Many researchers have developed phishing classification models that are limited in real-time and computational efficiency. This paper presents an ensemble learning model composed of DTree and NBayes, by STACKING method, with DTree as base learner. The aim is to combine the advantages of simplicity and effectiveness of DTree with the lower complexity time of NBayes. The models were integrated and appraised independently for data training and the probabilities of each class were averaged by their accuracy on the trained data through testing process. The present results of the empirical study on phishing websi
... Show MoreMonaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi
... Show MoreImages are important medium for conveying information; this makes improvement of image processing techniques also important. Interpretation of image content is one of the objectives of image processing techniques. Image interpretation that segments the image to number of objects called image segmentation. Image segmentation is an important field to deal with the contents of images and get non overlapping regions coherent in texture and color, it is important to deal only with objects with significant information. This paper presents survey of the most commonly used approaches of image segmentation and the results of those approaches have been compared and according to the measurement of quality presented in this paper the Otsu's threshol
... Show MoreProduced ancient Iraqi civilization among the ingredients of civilization as a result of
human interaction with the environment in which they live , and began this ingredient in a
simple and took vary and evolve with the evolution of human life itself.
And passing epoch long time occupied by this civilization in the land of Mesopotamia,
which reflected the legibility Althelol archaeological scattered in most parts of this land
emerged features of this civilization has been able shovels prospectors that secreted into the
essence of knowledge to the archaeological researcher and specialist process of analysis and
extrapolation of all information contained and provided by the missions excavation which
began in archae
ABSTRACT
Ticagrelor is an orally administered antiplatelet medicine, direct-acting P2Y12-receptor antagonist. Ticagrelor binds reversibly and noncompetitively to the P2Y12 receptor at a site distinct from that of the endogenous agonist adenosine diphosphate (ADP). Inhibition of platelet aggregation stimulated by ADP is a commonly used pharmacodynamic parameter for P2Y12-receptor antagonists.
Ticagrelor is a crystalline powder with an aqueous solubility of approximately 10?g/mL at room temperature.
... Show MoreCyberbullying is one of the biggest electronic problems that takes multiple forms of harassment using various social media. Currently, this phenomenon has become very common and is increasing, especially for young people and adolescents. Negative comments have a significant and dangerous impact on society in general and on adolescents in particular. Therefore, one of the most successful prevention methods is to detect and block harmful messages and comments. In this research, negative Arabic comments that refer to cyberbullying will be detected using a support vector machine algorithm. The term frequency-inverse document frequency vectorizer and the count vectorizer methods were used for feature extraction, and the results wer
... Show MoreEconomists agree upon the importance of exports and their positive impacts on the economic variables. Therefore، they studied policies encouraging exports and set out the instrumentalities supporting them. These instrumentalities included a combination of fiscal، monetary، commercial، production policies like the tax policy that is encouraging to the exports، exchange rates reduction، establishing commercial free zones، better production quality، fostering investment climate، and preparation of the necessary financing before the exporting process and afterwards.
This research is interested in the finding aspect amongst the instrumentalities encouraging exports which is parallel t
... Show MoreThere is a mutual relationship between the form of a text and its meaning so as separating these two or devaluating the role of one of them leads to the absence of the value therein. Thus, a translation is important as to how it relates the details of a text. That is, the text has special features which go beyond form, and these set out its distinctiveness. Here, we tackle Saleh al-Jafari's Arabic translation of "Rubbayat al-Khayyam" of Naysapour descriptively and analytically by depending on extracts from the original text. This translation is evaluated on the basis of Spanish critic Maria Carmen Valero Garces. Herein, we discuss the effectiveness of this theory in the criticism of literary texts. It has been concluded that al-Jaf
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