Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show the success of this system where the accuracy of the system is more than 95% on social media data.
Women's rights in social studies and national textbooks in the secondary stage in the light of the international charters of women's rights and the cultural specificity of the Saudi society Abstract The current study focuses on exploring women rights that required to be involved in social studies and national textbooks in the secondary stage in the light of international conventions on women's rights and cultural specificity of the Saudi society, as well as to reveal the teachers and educational supervisors' estimation about the degree of importance of those components included in the books, and then build a matrix of the range and sequence of women's rights in the books of social studies and national in the secondary stage. The study us
... Show MoreInspite of the renovation and development that occurred on the
mathematics curricula and its teaching styles (methods), the teaching methods and the evaluation styles that the teachers of the country
follow are still traditionaL It depends on the normal distribution approach and the principle of individual differences among students in
addition the traditional tests that are used to evaluate student achievement are built on standard-referenced system. These types of tests focus on comparing the student's performance with his peers'
performance. The limitary of this type of evaluation in diagnosing the
students' acquisition of the stu
... Show MoreThis research is mostly concerned of exploration analysis of a random sample of data from Al-sadder hospital. We examine duration of hospital stay (DHS) and investigate any significant difference in duration between sex, age groups, occupation, patients’ condition at admission, and patients’ condition at discharge
Research Summary
Praise be to God, and may blessings and peace be upon the Messenger of God. As for:
The Noble Qur’an is the constitution of life, and a comprehensive educational approach that deals with individuals comprehensively, as it organizes worldly and eschatological life, and it is a curriculum concerned with organizing life starting with individuals and the family until the establishment of states, and from its comprehensiveness is reform, guidance and establishing boundaries. They have a disease in their hearts. They are exposed to this and are trying, by falsehood, to subjugate the Islamic world with man-made laws set by the West. Their aim is to distance people from
... Show MoreCumhuriyet Üniversitesi Fen-Edebiyat Fakültesi Sosyal Bilimler Dergisi | Volume: 48 Issue: 2
Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
... Show MoreDeep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
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