Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T

Writing plays an effective role in developing one's thinking and
enhancing Learning. It is, in fact, a means of widening one's own views about
the world for the numerous uses that it can serve (Samuel, 1988:28).
In regard to the unquestionable significance of writing in the teaching –
Learning process, the traditional approach seems to be far from being able to
put such significance into practice. Traditionalists give priority to formulating
students' ideas before using prescribed rhetorical framework and then
submitting the written product for grading. Emphasis is, therefore, limited to the
prewriting stage where a certain topic is explored, and the role of the teacher is
confined to assigning the topic and

Tafsir, ‘interpretation’ is one of the most important sciences the Muslims need. Because Allah, Almighty, revealed the Qur’an to be a way of life for the Muslims in which the healing of what is in the chest, including their goodness and their peasant. Allah says:
“O people, an admonition has indeed come to you from your Lord and a healing for what is in the hearts; and a guidance and a mercy for the believers.”
In order to achieve the goal for which God revealed the Quran must be understood and managed verses:” This is a Book that We have revealed to you abounding in good, that they may ponder over its verses, and that those who have understanding may be mindful.”
The Prophet (PBUH) and his companions understood t

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

Arcology is a new vision of urban design for densely populated settlements. It is referred to as the urban formation aimed at achieving the highest level of utilization in the least area of land to reduce human impact on the environment. Moreover, the integration of this formation with the environment will work to reduce energy consumption, and achieve an economy that is characterized by adaptation and self-sufficiency, leading towards sustainable urbanism. The current study deals with this new concept in sustainable urban design, in an attempt to investigate its impact on traditional urban formation and to make a comparison between them. The lack of a clear conception of the term ‘arcology’ and comparing it with the organic compact urb

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide low bit error rates (BER) along with information security. The aim of such activity is to steal or distort the information being conveyed. Optical Wireless Systems (basically Free Space Optic Systems, FSO) are no exception to this trend. Thus, there is an urgent necessity to design techniques that can secure privileged information against unauthorized eavesdroppers while simultaneously protecting information against channel-induced perturbations and errors. Conventional cryptographic techniques are not designed