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Text Steganography Based on Arabic Characters Linguistic Features and Word Shifting Method
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In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harnesses the unique attributes of this language, encompassing its complex character designs, diacritical marks, and ligatures, to effectively protect information. In this work, we propose a new text steganography method based on Arabic language characteristics concealment, where the proposed method has two levels of security which are: Arabic encoding and word shifting. In the first step, build a new Arabic encoding mapping table to convert an English plaintext to Arabic characters, then use a word shifting process to add an authentication phase for the sending message and add another level of security to the achieved ciphertext. The proposed method showed that Arabic language characteristics steganography achieved 0.15 ms for 1 k, 1.0033 ms for 3 k, 2.331 ms for 5 k, and 5.22 ms for 10 k file sizes respectively.

Publication Date
Fri Mar 24 2017
Journal Name
Journal Of Engineering
Composite Techniques Based Color Image Compression
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Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3 rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet transform (MMM) in M technique wh

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Publication Date
Sun Dec 30 2018
Journal Name
Journal Of Engineering
Knowledge-Based Urban Development The Impact of Knowledge- Based Urban Development in the Growth of Contemporary Cities
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Urban Development refers to many topics such as: increased population density, city size, and individual’s production, distribution of technology and the growth of commercial, industrial and service professions. Such development is linked to the coordination of social and cultural trends in order to achieve social progress and economical prosperity. Knowledge as a topic now is known as intellectual capital wich led to upgrae the concept of urban development to be extended into many fields of knowledge, for example, cultural, social and human development to move the level of community culture into a new better standard.

The research adopted the urban transformation based on knowledge as an important factor in gr

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Developed Unit in The Arabic Language Textbook for The Enhancement of 21st Century Skills
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Abstract

This research aims to develop a unit as part of a sixth-grade Arabic language textbook and measure its effectiveness in the development of twenty-first-century skills of female students. The author adopted the experimental approach with a quasi-experimental design of the pre-post single-group. A list of the major skills was derived from the framework for the 21st-century skills of the mother tongue that was developed by the Partnership for 21st-Century Skills and reviewed and adjusted by some specialists. According to their views, the unit was developed. The study targeted 15 sub-skills falling under three main skills. The results of the study showed the effectiveness of the developed unit in the develo

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Publication Date
Mon Feb 08 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
AWN-similarity: Towards developing free open-source frameworks for measuring Arabic semantic similarity under Windows / Linux operating systems
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Publication Date
Thu Nov 14 2024
Journal Name
Journal Of Emergency Medicine, Trauma And Acute Care
Novel isolation and optimization of anti-MRSA bacteriophages using plaque-based biokinetic methods
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Background: MRSA (methicillin-resistant Staphylococcus aureus) is a global health problem. Many people are looking for new ways to combat MRSA, for example by using bacteriophages (phages). It has been extremely challenging to isolate a sufficient quantity of lytic anti-MRSA phages. Therefore, new techniques for separating, refining, and reworking anti-MRSA phages were sought in this study.

Methods: Of 437 S. aureus isolates, nine clinical MRSA isolates were obtained from three hospitals in Baghdad, Iraq and two ATCC MRSA strains were used to separate wild anti-MRS

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Tue Dec 13 2022
Journal Name
Lecture Notes In Networks And Systems
Design and FPGA Implementation of Matrix Multiplier Using DEMUX-RCA-Based Vedic Multiplier
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Publication Date
Fri Dec 01 2017
Journal Name
2017 11th Asian Control Conference (ascc)
ESO-based repetitive control for rejecting periodic and aperiodic disturbances in piezoelectric actuators
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This paper presents the Extended State Observer (ESO) based repetitive control (RC) for piezoelectric actuator (PEA) based nano-positioning systems. The system stability is proved using Linear Matrix Inequalities (LMIs), which guarantees the asymptotic stability of the system. The ESObased RC used in this paper has the ability to eliminate periodic disturbances, aperiodic disturbances and model uncertainties. Moreover, ESO can be tuned using only two parameters and the model free approach of ESO-based RC, makes it an ideal solution to overcome the challenges of nano-positioning system control. Different types of periodic and aperiodic disturbances are used in simulation to demonstrate the effectiveness of the algorithm. The comparison studi

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Publication Date
Fri Dec 01 2023
Journal Name
Advances In Science And Technology Research Journal
Experimental Investigation and Fuzzy Based Prediction of Titanium Alloy Performance During Drilling Process
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Topology-Based Modularity and Modularity Density for Detecting Protein Complexes: A Comparative Study
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     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

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