The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and the most recent attack patterns in network traffic, ensuring data quality for analysis, (2) CSNN‐based Detection, where outlier identification is conducted by comparing two dataset groups (the normal set and the attack set) within the same time period to enhance anomaly detection and (3) In the evaluation level, the detection performance of the proposed model is assessed by comparing it with two benchmark models: ZD‐Deep Learning (ZD‐DL) and ZD‐ Convolutional Neural Network (ZD‐CNN). The implementation results demonstrate that ZD‐ CSNN achieves superior accuracy in detecting zero‐day attacks compared to both ZD‐DL and ZD‐CNN.
Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c
... Show MoreBackground: Day case surgery has become widely accepted as a safe alternative to the inpatient care in up to 70% of the cases at a children’s hospital. It has the advantage of minimizing the psychological trauma of hospitalization, decreasing nosocomial infection, less costly and frees up hospital beds.Objectives: To assess the advantages and disadvantages of this type of surgery.Methods: this is a prospective study, in which two hundred thirty childhood tonsillectomies were performed as a day-case in the department of otolaryngology at Al Shaheed Gazi hospital, Medical City Complex during the period from October 2009 to September 2010. The patients age range from 3-12 years (Mean 7.2 years).Results: 46.08% males and 53.91% females wer
... Show MoreDetermining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
... Show MoreThe marketing of banking service is considered to be one of the impotent fields which showed a universal inebriates . He research showed the comparison between the application of marketing in ideas and application for loot government and private Iraqi bank. The research comets of four parts; Mythology / the concept and the importance of Banking Marketing / Research applichlion/ Conelnion and recommendation.
The study aimed to find out the relationship between the dimensions of internal control systems and the availability of an effective governance framework in the Sudanese banks. The study used descriptive and analytical method for collecting and analyzing the study data using SPSS program. The questionnaire was used as an analysis tool. The target sample of Sudanese bank employees, the study found several results, including that the bank avoids methods that lead to the rational use of available resources, and identifies and separation of tasks among employees, in addition to rapid response to reports The study found several recommendations, including the need for a list of banks that are sufficiently flexible and comp
... Show MoreBackground: A minimally invasive antral membrane balloon elevation (MIAMBE) has been introduced to overcome the invasiveness of modified Caldwell-Luc (lateral approach) and the drawbacks of the osteotome (summers' technique) in maxillary sinus floor elevation surgery. Materials and methods: A total of 13 adult Iraqi patients aged 28-55 years, 4 males and 9 females underwent sinus floor elevation surgery via crestal approach by using sinus balloon technique. A panoramic radiograph and (Cone beam computed tomography (CBCT)/or medical CT scan) were obtained before and after surgery. Postoperative gained bone was assessed and the patient reactions including pain, nasal bleeding, and ecchymosis were recorded. The whole follow up period was 1yea
... Show MoreThe development of information systems in recent years has contributed to various methods of gathering information to evaluate IS performance. The most common approach used to collect information is called the survey system. This method, however, suffers one major drawback. The decision makers consume considerable time to transform data from survey sheets to analytical programs. As such, this paper proposes a method called ‘survey algorithm based on R programming language’ or SABR, for data transformation from the survey sheets inside R environments by treating the arrangement of data as a relational format. R and Relational data format provide excellent opportunity to manage and analyse the accumulated data. Moreover, a survey syste
... Show MoreThe rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
... Show More