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A Novel DNA Sequence Approach for Network Intrusion Detection System Based on Cryptography Encoding Method
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A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results show that the proposed system has obtained good results and these results are equal to 86.36%, 49.69%, and 77.65% for detection rate, false alarm rate and accuracy respectively. These results are considered as a better result when it is compared with the other previous basic algorithms. It is possible to conclude that DNA sequence has potential for NIDS solution and it has potential improvement using a better encoding method.

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Publication Date
Tue Jun 18 2019
Journal Name
Journal Of College Of Education For Women
Antonia's Mannish Behavioral Transition in Willa Cather's Novel My
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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Pharmaceutical Sciences And Research
Synthesis of some Schiff base metal complexes involving trimethoprim and 2'-amino-4-chlorobenzophenone: Spectral, thermal, DNA Cleavage antimicrobial,antifungal and Cytotoxic activity studies
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In study of effective bioactive compounds, we have synthesized the Co((ІІ), Mn(ІІ), Fe(ІІ), Cu(ІІ), Ni(ІІ), and Zn(ІІ) complexes of the Schiff base derived from trimethoprim and2'-amino-4-chlorobenzophenone and characterized by spectroscopic (NMR, IR, Mass, UV–vis,), analytical, TGA studies and magnetic data .The solution electronic spectral study suggests the stoichiometry of the synthesized complexes and Elemental analysis detected the square planer and octahedral geometry of the compounds. The prepared metal complexes presented promoted efficiency versus the screened bacterial (Escherichia Coli and Staphylococcus aureus) antibacterial efficacy against (Staphylococcus aureus, Salmonella spp., E. coli, Vibrio spp., Pseudomona

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Publication Date
Tue Jul 21 2026
Journal Name
Journal Of Baghdad College Of Dentistry
A Micro Computed Tomography Assessment of New Carrier-Based Root Canal Fillings
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Background: The main aim of the present study is to qualify and quantify voids formation of root canals obturated with GuttaCore (GC) and experimental Hydroxyapatite polyethylene (HA/PE) as new carrier-based root canal fillings by using micro computed tomography scan. Materials and methods: In the present study, eight straight single-rooted human permanent premolar teeth are selected and disinfected, then stored in distilled water. The teeth decoronated leaving a root length of 12mm each. The root canals instrumented by using crown down technique and the apical diameter of the root canal prepared to a size # 30/0.04 for achieving standardized measurements. A 5mL of 17% EDTA used to remove the smear layer followed by 5mL of 2.5% NaOCl and r

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Publication Date
Tue Dec 19 2023
Journal Name
Journal Of Ethnic And Cultural Studies
Request Constructions in Classical Arabic versus Modern Arabic: A Corpus-based Study
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The present study aims to investigate the various request constructions used in Classical Arabic and Modern Arabic language by identifying the differences in their usage in these two different genres. Also, the study attempts to trace the cases of felicitous and infelicitous requests in the Arabic language. Methodologically, the current study employs a web-based corpus tool (Sketch Engine) to analyze different corpora: the first one is Classical Arabic, represented by King Saud University Corpus of Classical Arabic, while the second is The Arabic Web Corpus “arTenTen” representing Modern Arabic. To do so, the study relies on felicity conditions to qualitatively interpret the quantitative data, i.e., following a mixed mode method

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Publication Date
Tue May 31 2022
Journal Name
Journal Of Positive School Psychology
A GENRE-BASED ANALYSIS OF POLITICAL SPEECHES IN THE UN GENERAL ASSEMBLY
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Publication Date
Sun Oct 01 2023
Journal Name
Optical Fiber Technology
A taper-in-etch based hybrid fiber Mach-Zehnder interferometer hydrogen sensor
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Publication Date
Thu Feb 01 2018
Journal Name
Iet Signal Processing
Signal compression and enhancement using a new orthogonal‐polynomial‐based discrete transform
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Publication Date
Thu Mar 24 2022
Journal Name
Arab World English Journal
Collocation Networks of Selected Words in Academic Writing: A Corpus-Based Study
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This study aims at shedding light on the linguistic significance of collocation networks in the academic writing context. Following Firth’s principle “You shall know a word by the company it keeps.” The study intends to examine three selected nodes (i.e. research, study, and paper) shared collocations in an academic context. This is achieved by using the corpus linguistic tool; GraphColl in #LancsBox software version 5 which was announced in June 2020 in analyzing selected nodes. The study focuses on academic writing of two corpora which were designed and collected especially to serve the purpose of the study. The corpora consist of a collection of abstracts extracted from two different academic journals that publish for writ

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Publication Date
Sun Mar 06 2022
Journal Name
Cogent Arts &humanities
A corpus-based stylistic analysis of online suicide notes retrieved from Reddit
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Publication Date
Fri Sep 27 2024
Journal Name
Journal Of Applied Mathematics And Computational Mechanics
Fruit classification by assessing slice hardness based on RGB imaging. Case study: apple slices
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

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