Background: Animal bite is one of the public health problems all over the world, especially in poor countries. Animal bites have an impact on human health due to rabies disease, which is a viral transmitted disease from animal to human with a high mortality rate.
Objective: To determine the epidemiological characteristics of animal bite cases by person, time, and place.
Method: Descriptive cross sectional study was done by reviewing cases caused by animal bites., Data including the demographic characteristics of age, gender, occupation, site of bite, and attending health institutions searching treatment were all included.
Results: There were 11600 animal bite cases. Most of bites caused by stray dogs 11577(99.8%), and the males

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

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

Each school of Islamic jurisprudence has principles and rules upon which the diligent work in these schools is based. This is due to the view of sanctification of these rulings, as they are divine rulings. Therefore, the goal is to reach a ruling that represents the intent of the legislator as much as possible.
Hence, these schools of thought established rules for issuing fatwas with the intention of restricting the performance of a fatwa to the hands of those who are qualified for it and have met its conditions, so they gave priority to the most knowledgeable person over others to perform the fatwa. In the Hanafi school of thought, for example, the saying of Imam Abu Hanifa (may God have mercy on him) is given precedence over others,

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

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

Contracaecum rudolphii Hartwich, 1964 is a nematode which causes major concerns to human and wildlife animal’s health. However, the population genetics of C. rudolphii has been poorly studied in Iraq. In order to gain a deeper understanding in the outline of the genetic diversity of the nematode C. rudolphii that were isolated from its host cormorant Phalacrocorax carbo (Linnaeus, 1758), in the middle areas of Iraq, twenty specimens of C. rudolphii adults were isolated from nine individuals of P. carbo. The first (ITS-1) internal transcribed spacers (ITS) of ribosomal DNA (rDNA) of C. rudolphii were amplified using conventional polymerase chain reaction (PCR); then, the amplicons were subjected to sequencing. Concatenation of ITS-1 (rD

Contracaecum rudolphii Hartwich, 1964 is a nematode which causes major concerns to human and wildlife animal’s health. However, the population genetics of C. rudolphii has been poorly studied in Iraq. In order to gain a deeper understanding in the outline of the genetic diversity of the nematode C. rudolphii that were isolated from its host cormorant Phalacrocorax carbo (Linnaeus, 1758), in the middle areas of Iraq, twenty specimens of C. rudolphii adults were isolated from nine individuals of P. carbo. The first (ITS-1) internal transcribed spacers (ITS) of ribosomal DNA (rDNA) of C. rudolphii were amplified using conventional polymerase chain reaction (PCR); then, the amplicons were subjected to sequencing. Concatenation of ITS