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.
Electrical Discharge Machining (EDM) is a widespread Nontraditional Machining (NTM) processes for manufacturing of a complicated geometry or very hard metals parts that are difficult to machine by traditional machining operations. Electrical discharge machining is a material removal (MR) process characterized by using electrical discharge erosion. This paper discusses the optimal parameters of EDM on high-speed steel (HSS) AISI M2 as a workpiece using copper and brass as an electrode. The input parameters used for experimental work are current (10, 24 and 42 A), pulse on time (100, 150 and 200 µs), and pulse off time (4, 12 and 25 µs) that have effect on the material removal rate (MRR), electrode wear rate (EWR) and wear ratio (WR). A
... Show MoreGlobal Navigation Satellite System (GNSS) is considered to be one of the most crucial tools for different applications, i.e. transportation, geographic information systems, mobile satellite communications, and others. Without a doubt, the GNSS has been widely employed for different scientific applications, such as land surveying, mapping, and precise monitoring for huge structures, etc. Thus, an intense competitive has appeared between companies which produce geodetic GNSS hardware devices to meet all the requirements of GNSS communities. This study aims to assess the performance of different GNSS receivers to provide reliable positions. In this study, three different receivers, which are produced by different manufactur
... Show MoreGlobal Navigation Satellite System (GNSS) is considered to be one of the most crucial tools for different applications, i.e. transportation, geographic information systems, mobile satellite communications, and others. Without a doubt, the GNSS has been widely employed for different scientific applications, such as land surveying, mapping, and precise monitoring for huge structures, etc. Thus, an intense competitive has appeared between companies which produce geodetic GNSS hardware devices to meet all the requirements of GNSS communities. This study aims to assess the performance of different GNSS receivers to provide reliable positions. In this study, three different receivers, which are produced by different manufacturers, were fi
... Show MoreThe study aims to explore the effect of cognitive behavioral therapy on internet addiction among university students. The experimental method was used. The study population consisted of (100) university students (50 males, 50 females). The Research sample included (13) University students at Baghdad University addicted to the Internet (9 males, 4 females), divided into two groups: a control group consisting of (6) individuals (4 males, 2 females) and an experimental sample consisting of (6) individuals (4 males, 2 females). The Scale of Internet Addiction by Young (1996), which was translated and modified into the Arabic language by (Moegel and Prism, 2016), was administered to the study sample. The sample was subjected to two sess
... Show MoreThe study aimed to reveal the level of knowledge and tendencies of high- study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with brain-based learning (BBL). And Then, putting a proposed concept to develop knowledge and tendencies of high-study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with Brain-based learning (BBL). For achieving this goal, a cognitive test and a scale of tendency were prepared to apply harmonious strategies with brain-based learning. The descriptive approach was used because it suits the goals of the study. The study sample consisted of (70) male and female students of postgraduate
... Show MoreCassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
... Show MoreWith the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
... Show MoreBackground: White spot lesion is the first visible sign of dental caries that is characterized by demineralized lesion underneath an intact surface. Several studies demonstrated that they could be treated using noninvasive techniques like the use of fluoride or casein phospho-peptide and amorphous calcium phosphate. Improvement in aesthetic outcomes by covering the demineralized enamel is one of the advantages of the use of resin infiltration and opal-ustre microabrasion, which are two new techniques that had been used for treatment of white spot lesion. The purpose of this study was to evaluate the impact of resin infiltration and microabrasion in the microhardness of the artificial white spot lesions at various depths. Material and method
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