Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

Blogs have emerged as a powerful technology tool for English as a Foreign Language (EFL) classrooms. This literature review aims to provide an overview of the use of blogs as learning tools in EFL classrooms. The study examines the benefits and challenges of using blogs for language learning and the different types of blogs that can be used for language learning. It provides suggestions for teachers interested in using blogs as learning tools in their EFL classrooms. The findings suggest that blogs are a valuable and effective tool for language learning, particularly in promoting collaboration, communication, and motivation.

This research includes a study of the ability of Iraqi porcelanite rocks powder to remove the basic Safranine dye from its aqueous process by adsorption. The experiments were carried out at 298Kelvin in order to determine the effect of the starting concentration for Safranin dye, mixing time, pH, and the effect of ionic Strength. The good conditions were perfect for safranine dye adsorption was performed when0.0200g from that adsorbed particles and the removal max percentage  was found  be 96.86%  at 9 mg/L , 20 minutes adsorption time and at PH=8 and in 298 K. The isothermal equilibrum stoichiometric adsorption confirmed, the process data were examined by Langmuir, Freundlich and Temkin adsorption equations at different temperatures

The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie

The present study aims to identify the most and the least common teaching practices among faculty members in Northern Border University according to brain-based learning theory, as well as to identify the effect of sex, qualifications, faculty type, and years of experiences in teaching practices. The study sample consisted of (199) participants divided into 100 males and 99 females. The study results revealed that the most teaching practice among the study sample was ‘I am trying to create an Environment of encouragement and support within the classroom which found to be (4.4623). As for the least teaching practice was ‘I use a natural musical sounds to create student's mood to learn’ found to be (2.2965). The study results also in

Deep Learning Techniques For Skull Stripping of Brain MR Images