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ijs-2746
Improvement of Chacha20 Algorithm based on Tent and Chebyshev Chaotic Maps
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Chacha 20 is a stream cypher that is used as lightweight on many CPUs that ‎do not have dedicated AES instructions. As stated by Google, that is the reason why they use it on many ‎devices, such as mobile devices, for authentication in TLS protocol. This paper ‎proposes an improvement of chaha20 stream cypher algorithm based on tent and ‎Chebyshev functions (IChacha20). The main objectives of the proposed IChacha20 ‎algorithm are increasing security layer, designing a robust structure of the IChacha20 ‎to be enabled to resist various types of attacks, implementing the proposed ‎algorithm for encryption of colour images, and transiting it in a secure manner. The ‎ test results proved that the MSE, PSNR, UQI and NCC metrics of ‎IChacha20 are better than those of the original Chacha20. Also, the proposed method has ‎a faster execution time (01:26:4 sec) compared with the original algorithm (02:07:1 sec).

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Determination of the lot size using the Wagner-Whitin algorithm under the Constraint Theory / Case Study of Diyala Public Company
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         International companies are striving to reduce their costs and increase their profits, and these trends have produced many methods and techniques to achieve these goals. these methods is heuristic and the other Optimization.. The research includes an attempt to adapt some of these techniques in the Iraqi companies, and these techniques are to determine the optimal lot size using the algorithms Wagner-Whitin under the theory of constraints. The research adopted the case study methodology to objectively identify the problem of research, namely determining lot size optimal for each of the products of electronic measurement laboratory in Diyala and in light of the bottlenecks in w

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Publication Date
Tue Jan 25 2022
Journal Name
Iraqi Journal Of Science
PIM-SM based Multicast Comparison for IPv4 verses IPv6 using GNS3 and JPERF
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The multicast technology implements a very high-efficiency point-to-multipoint data transmission over IP networks (IPv4 and IPv6). Multicast reduces network load, eliminates traffic redundancy, and saves network bandwidth. Therefore, multicast used widely in LAN/WAN applications such as online games, video conferencing and IPTV. The multicast technology implements varied protocols such as DVMRP(Distance Vector Multicast Routing Protocol), MOSPF(Multicast Open Shortest Path First), or PIM-DM (Protocol Independent Multicast- Dense Mode) which considered source tree type, while PIM-SM (Protocol Independent Multicast- Sparse Mode) and CBT (Core Based Tree) uses shared tree. Current paper focuses on the performance evaluation of the two multi

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Mobile-based Telemedicine Application using SVD and F-XoR Watermarking for Medical Images
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A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

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Publication Date
Mon Oct 28 2019
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
Heuristic Initialization And Similarity Integration Based Model for Improving Extractive Multi-Document Summarization
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Composites Science
Sawdust-Based Concrete Composite-Filled Steel Tube Beams: An Experimental and Analytical Investigation
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Incorporating waste byproducts into concrete is an innovative and promising way to minimize the environmental impact of waste material while maintaining and/or improving concrete’s mechanical characteristics and strength. The proper application of sawdust as a pozzolan in the building industry remains a significant challenge. Consequently, this study conducted an experimental evaluation of sawdust as a fill material. In particular, sawdust as a fine aggregate in concrete offers a realistic structural and economical possibility for the construction of lightweight structural systems. Failure under four-point loads was investigated for six concrete-filled steel tube (CFST) specimens. The results indicated that recycled lightweight co

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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
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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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Transfer Learning Based Traffic Light Detection and Recognition Using CNN Inception-V3 Model
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Due to the lack of vehicle-to-infrastructure (V2I) communication in the existing transportation systems, traffic light detection and recognition is essential for advanced driver assistant systems (ADAS) and road infrastructure surveys. Additionally, autonomous vehicles have the potential to change urban transportation by making it safe, economical, sustainable, congestion-free, and transportable in other ways. Because of their limitations, traditional traffic light detection and recognition algorithms are not able to recognize traffic lights as effectively as deep learning-based techniques, which take a lot of time and effort to develop. The main aim of this research is to propose a traffic light detection and recognition model based on

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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
Mon Apr 01 2019
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Teaching Strategy Based on the Cognitive Model of Daniel in the Development of Achievement and the Motivation of learning the School Mathematics among the Third Intermediate Grade Students
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This research aims to examine the effectiveness of a teaching strategy based on the cognitive model of Daniel in the development of achievement and the motivation of learning the school mathematics among the third intermediate grade students in the light of their study of "Systems of Linear Equations”. The research was conducted in the first semester (1439/1440AH), at Saeed Ibn Almosaieb Intermediate School, in Arar, Saudi Arabia. A quasi-experimental design has been used. In addition, a (pre & post) achievement test (20 Questions) and a (pre & post) scale of learning motivation to the school mathematics (25 Items) have been applied on two groups: a control group (31Students), and an experimental group (29 Students). The resear

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