This paper reports a fiber Bragg grating (FBG) as a biosensor. The FBGs were etched using a chemical agent,namely,hydrofluoric acid (HF). This implies the removal of some part of the cladding layer. Consequently, the evanescent field propagating out of the core will be closer to the environment and become more sensitive to the change in the surrounding. The proposed FBG sensor was utilized to detect toxic heavy metal ions aqueous medium namely, copper ions (Cu2+). Two FBG sensors were etched with 20 and 40 μm diameters and fabricated. The sensors were studied towards Cu2+ with different concentrations using wavelength shift as a result of the interaction between the evanescent field and copper ions. The FBG sensors showed

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

This study was done at Al-Balad City Hospital on 60 diabetic patients (25 male and 35 female). The study included Fasting Blood Sugar and fungal diagnosis (systemic and superficial fungus). The results showed that the high concentration of blood sugar belonged to the group > 70 years among the diabetic patients with high significant differences in comparison with other groups P<0.001 . The result showed that percentage of female systemic fungus infection was higher than male systemic fungus infection ( female 63% and male 24%) and vice versa about superficial fungus infection (female 37% and male 76%) . Data showed that the percentage of nail fungus infection among female diabetic patients was higher than the percentage of male diabetic p

This research paper attempts to explore problems facing the teaching of written expression among first-year female university students. The focal point behind conducting this research is to show the importance that writing is taking as a skill in learning the language. To achieve this goal, the researcher prepared a questionnaire consisting of 20 items. The sample, whose size is 60 participants, was selected randomly from the department of Arabic, College of Education for Women, University of Baghdad. Through the use of a set of statistical means including weighting means and percentage, the findings revealed that the students face many difficulties in learning writing. The researcher suggested some recommendations, mainly improving the

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

Abstract: The term extremism refers to the distance from moderation, excess and hyperbole, and it is a relative term that varies from one society to another, according to the prevailing traditions, values and culture, as the problem of extremism is one of the main issues that contemporary societies are concerned with is a phenomenon that has its roots in the intellectual formation of societies. By knowing the concept of extremism, we can identify the reasons that contributed to the existence of extremism as a phenomenon, on the one hand; on the other hand, to clarify the role of women in combating extremism and developing effective solutions to reduce this phenomenon. As women play a major role in society, starting from the family to educa

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