The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The study aimed to identify the awareness level of hidden curriculum among field education students, College of Education, Hail University. To identify the different awareness level of hidden curriculum among field education students depending on specialization variable, and grade variable in curriculum and instruction course, a descriptive survey method was used. The study sample consisted of (182) students: 78 students in Islamic Culture major, 46 primary major and 58 in physical education. To achieve the study objectives, a hidden curriculum awareness scale was designed included (36) items. The study results showed: the awareness level of hidden curriculum among students of field education, Education College, Hail University, achieved

The current research aimed to identify the level of moral identity and social affiliation among students exposed to shock pressures, as well as to reveal the relationship between these variables. To achieve these objectives, the researcher adopted the diagnostic tool for the measure of post-traumatic stress disorder (PDS-5) scale (Foa, 2013) translated to Arabic language by (Imran, 2017). The researcher also adopted the moral identity scale built by (Al-Bayati, 2015) and the measure of social affiliation built by (Al-Jashami, 2013), which were applied to a random sample of (200) male and female students chose from al Anbar University. They were exposed to shock pressures. The results of the research showed that the sample has an average

Personality regard as one of the human soul pillars that has been built throughout the life of people, starting from the fertilizing process to different stages of people ages. Over time, numerous scientific studies have shown that fetus has the ability to hear and feel and he is being stereotyped since the first stages of formation. Accordingly, the process of forming human personality set up since that date. Besides, the socialization means that take different resources to enhance human personality such as holy Quran, school, social media, and social environment. The emergence of social media made the world as a small village which gives the chance for all people, over the world, to obtain the knowledge easily and limitless. Thus, the

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

This paper assesses the impact of changes and fluctuations in bank deposits on the money supply in Iraq. Employing  the research constructs an Error Correction Model (ECM) using  monthly time series data from 2010 to 2015. The analysis begins with  the Phillips-Perron unit root test to ascertain the stationarity of the  time series and the Engle and Granger cointegration test to examine  the existence of a long-term relationship. Nonparametric regression functions are estimated using two methods: Smoothing Spline and M-smoothing. The results indicate that the  M-smoothing approach is the most effective, achieving the shortest adjustment period and the highest adjustment ratio for short-term disturbances, thereby facilitating a return

The study aims to examine the problem of forced displacement and its social and economic problems in light of the Syrian crisis. Such an aim helps to know the difficulties and challenges facing the children of displaced families in learning, and the reasons for their lack of enrolment. It also clarifies whether there are significant statistical differences at  among the attitudes of the children of the displaced families towards education regarding the following variables: (the work of the head of the family, the economic level of the family, and the work of the children). The study has adopted the descriptive-analytical approach;  a questionnaire was adopted as a tool to collect information. The study was applied to a sample o