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Encryption of Medical Image Based on Cascaded Design of AES Block Algorithm and Chaotic Map
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Security concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascaded-looking composition of F-functions in a quadrate architecture. The proposed F-function architecture is a three-input, three-output Type-3 AES-Feistel network with additional integer parameters representing the subkeys in use. The suggested system makes use of the AES block cipher as a function on a Type-3 AES-Feistel network. Blocks in the proposed system are 896 bits in length, whereas keys are 128 bits. The production of subkeys is encrypted using a chain of E8- algorithms. The necessary subkeys are then generated with a recursion. The results are reviewed to verify that the new layout improves the security of the AES block cipher when used to encrypt medical images in a computer system.

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Publication Date
Mon Dec 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Fingerprints Identification and Verification Based on Local Density Distribution with Rotation Compensation
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The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

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Publication Date
Fri Apr 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
SMS Spam Detection Based on Fuzzy Rules and Binary Particle Swarm Optimization
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Human Face Recognition Based on Local Ternary Pattern and Singular Value Decomposition
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There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

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Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Fast Shot Boundary Detection Based on Separable Moments and Support Vector Machine
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Scopus (27)
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Publication Date
Fri Mar 15 2024
Journal Name
Iraqi Statisticians Journal
Estimate a nonparametric copula density function based on probit and wavelet transforms
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This study employs wavelet transforms to address the issue of boundary effects. Additionally, it utilizes probit transform techniques, which are based on probit functions, to estimate the copula density function. This estimation is dependent on the empirical distribution function of the variables. The density is estimated within a transformed domain. Recent research indicates that the early implementations of this strategy may have been more efficient. Nevertheless, in this work, we implemented two novel methodologies utilizing probit transform and wavelet transform. We then proceeded to evaluate and contrast these methodologies using three specific criteria: root mean square error (RMSE), Akaike information criterion (AIC), and log

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Publication Date
Tue Jan 30 2024
Journal Name
International Journal Of Engineering Pedagogy (ijep)
The Impact of Two Proposed Strategies Based on Active Learning on Students' Achievement at the Computer and Their Social Intelligence
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Active learning is a teaching method that involves students actively participating in activities, exercises, and projects within a rich and diverse educational environment. The teacher plays a role in encouraging students to take responsibility for their own education under their scientific and pedagogical supervision and motivates them to achieve ambitious educational goals that focus on developing an integrated personality for today’s students and tomorrow’s leaders. It is important to understand the impact of two proposed strategies based on active learning on the academic performance of first-class intermediate students in computer subjects and their social intelligence. The research sample was intentionally selected, consis

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of Educational And Psychological Researches
Training Program based on Some Strategies of Self-Regulated Learning for the Teachers of Mathematics and its Effect on their Relational Mathematics
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This research aims at building a proposed training program according to the self-regulated strategies for the mathematics teachers and to identify the effect of this program on relational Mathematics of teachers. The sample of the research was (60) Math teachers; (30) teachers as experimental group and (30) teachers as control group. The results of the current research reacheded that the proposed training program according to some self-managed learning strategies, meets the needs of trainees with remarkable effectiveness to improve the level of their teaching performance to achieve the desired goals. Training teacher according to self-managed learning strategies is effective in bringing about the transition of training to their students

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Publication Date
Sun Jun 23 2024
Journal Name
Asee Annual Conference And Exposition
Undergraduate Research Impact on Students' Retention and Academic Development Based on Their Study Field and the Mentoring Approach
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The impact of undergraduate research experiences on students' academic development and retention in STEM fields is significant. Students' success in STEM fields is based on developing strong research and critical thinking skills that make it essential for students to engage in research activities throughout their academic programs. This work evaluates the effectiveness of undergraduate research experiences with respect to its influence on student retention and academic development. The cases presented are based on years of experience implementing undergraduate research programs in various STEM fields at Colorado State University Pueblo (CSU Pueblo) funded by HSI STEM Grants. The study seeks to establish a correlation between students' reten

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Scopus
Publication Date
Thu Nov 15 2018
Journal Name
Journal Of Mathematical Imaging And Vision
A New Hybrid form of Krawtchouk and Tchebichef Polynomials: Design and Application
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Scopus (33)
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