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.
The total and individual multipole moments of magnetic electron scattering form factors in 41Ca have been investigated using a widely successful model which is the nuclear shell model configurations keeping in mind of 1f7/2 subshell as an L-S shell and Millinar, Baymann, Zamick as L-S shell (F7MBZ) to give the model space wave vector. Also, harmonic oscillator wave functions have been used as wave function of a single particle in 1f7/2 shell. Nucleus 40Ca as core closed and Core polarization effects have been used as a corrective with first order correction concept to basic computation of L-S shell and the excitement energy has been implemented with 2ћω. The
... Show MoreThe Purpose of this study is mainly to improve the competitive position of products economic units using technique target cost and method reverse engineering and through the application of technique and style on one of the public sector companies (general company for vegetable oils) which are important in the detection of prices accepted in the market for items similar products and processing the problem of high cost which attract managerial and technical leadership to the weakness that need to be improved through the introduction of new innovative solutions which make appropriate change to satisfy the needs of consumers in a cheaper way to affect the decisions of private customer to buy , especially of purchase private economic units to
... Show MoreAn analytical and clinical study has been applied for measure the bioavailability of Zinc in serum of twenty adults healthy volunteers, using flame atomic absorption spectrophotometer (FAAS) at 213.9 nm. The calibration graph is linear in the ranges of 0.25-1.5 μg.mL-1 with correlation coefficient (R) 0.09996)μg.mL1-and molar absorpitivites 22957.76(L.mol1-cm-1.The concentration of Zinc determined in serum of all volunteers before and after administered orally a tablet of 50 mg zinc sulphate, produced by Samara drugs company (SDI). All data were subjected to statistical analysis by calculating accuracy, precision in addition to other parameters. The results indicate that the average maximum concentration (C-max ± SD) of blood zinc was 0.
... Show Moreتتمثل مشكلة الدراسة في الصعوبات التي يواجهها طلاب اللغة الإنجليزية كلغة أجنبية في تعلم وإتقان المتلازمات اللفظية. تهدف هذا الدراسة تهدف إلى تحديد أثر استخدام تقنية المسرد الاملائي على معرفة المتلازمات اللفظية لدى الطلاب. ولتحقيق أهداف هذا البحث والتحقق من فرضياته تم اختيار عينة عشوائية مكونة من (60) طالبة من كلية اللغة الإنجليزية للسنة الثانية باستخدام كتاب الفهم القرائي المقرر للمستوى الثاني في قسم الل
... Show MoreMost of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
... Show MoreThis study aimed to reveal the degree possession of secondary teachers for effective teaching skills from the perspective of the teachers themselves in the Mafraq governorate .To achieve the objective of the study(45) teachers were chosen randomly, also a questionnaire composed of 17 was prepared spread over three skill areas (planning, implementation, evaluation).
After application of the tool on the sample results of the study showed that the degree of ownership ranged between medium and high.
The results showed no differences in the degree of ownership due to the variables of sex in favor of females and variable qualification for the benefit of people with qualified Master higher, while differences are attributed to the experien
The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).