Biography
تدريسية في قسم تقنيات الاجهزة الطبية بلقب علمي مدرس مساعد حاصلة على شهادة الماجستير في علم البرمجيات من جامعة بابل / كلية تكنولوجيا المعلومات 2023. بكالوريوس في علوم الحاسبات / جامعة بابل 2025. من مواليد 1983 بغداد.Rsearch Interests
- الاهتمامات البحثية في مجالات الذكاء الاصطناعي, التليم العميق, الرؤيا الحاسوبية, معالجة الصور الرقمية والطبية,
Qualifications
- بكالوريوس علوم الحاسبات / جامعة بابل 2025
ماجستير برمجيات / جامعة بابل 2023
طالبة دكتوراه 2026
Scientific Research
- Abstract
The mobility and open access of wireless communication channels expose sensitive electronic health information to
unauthorized access. In Wireless Body Sensor Networks (WBSNs), securing this data is critical. To address these security
concerns, the proposed system introduces a Modified-Enhanced Lattice-Based Cryptography with Message Authentication Code (MAC-MELBC) as a hybrid authentication solution. This system integrates both symmetric and asymmetric
cryptographic techniques, creating a robust ciphering mechanism. The Message Authentication Code (MAC) ensures message integrity and authentication, while symmetric key cryptography supports efficient key management and validation
of communication parties. The MAC-MELBC method employs symmetric cryptography for the authentication process
and asymmetric lattice-based cryptography for secure key generation and data verification. The asymmetric component,
MELBC, utilizes advanced lattice-based algorithms to generate encryption keys and perform cryptographic operations for
verifying physiological data collected from the human body. The system splits plaintext and applies dual encryption for
enhanced security and authentication. Its encryption and decryption mechanisms offer strong protection against various
security threats within WBSNs. Performance is evaluated using key generation time, encryption/decryption time, memory
usage, total execution time, energy consumption, and resilience against attacks. Compared to conventional algorithms like
RSA and Elliptic Curve Cryptography (ECC), the proposed MAC-MELBC demonstrates superior performance, achieving
a 96% accuracy rate and offering enhanced security and efficiency for WBSN implementations.
- Abstract
Power systems have become more efficient, reliable, and sustainable as smart grids are
increasingly integrated into them. Developing innovative security solutions is often required
to counter evolving cyber threats because traditional security mechanisms lack real-time
protection. The purpose of this paper is to propose a blockchain-based hybrid optimization
approach for enhancing smart grid security and resilience. To improve decision-making,
resource allocation, and attack mitigation, the framework incorporates artificial intelligence
(AI) to detect anomalies in real-time, blockchain technology to store unrestricted data,
and a hybrid optimization algorithm to make decisions in real-time. Adaptive Vulture
Optimization Algorithm (AVOA) and Convolutional Neural Networks (CNN) combine to
reduce computational overhead and maintain detection accuracy effectively. According to
the proposed approach, which is compared to existing models, including ML-ID, HHT,
and THD, it achieves superior performance, with a detection rate of 99.17%, a reduction in
computation time, and enhanced scalability. These results demonstrate that AI-Blockchain
hybrid frameworks are effective in protecting smart grids against emerging cyber threats,
making them a reliable and scalable security solution.
- Abstract— Human-machine coexistence is a mutually
beneficial state between humans and technology in the
application of smart technology in classroom teaching.
Research in the field of human-machine coexistence not only
covers the relationship between humans and smart technology
but also includes the internal mechanism of how the two work
together in teaching. It can be said that human-machine
coexistence is key to the deep integration of intelligence and
machine. This study is conducted in the light of the concept of
the Human Computer Interaction as discussed in Elspeth
McKay’s Enhancing Learning Through Human Computer
Interaction (2007). The question which is raised in this paper
is how to improve the ability to learn English for school
students in classroom teaching based on human-machine
coexistence? For answering this question, first the value of
smart technology in teaching English should be analyzed since
from the characteristics of smart technology in educational
and teaching applications, and the model of smart technology
application in English teaching to the mechanism of
enhancing smart technology in English learning. Secondly, the
coexistence between humans and computers and its
characteristics in English teaching are analyzed, and then the
forms of coexistence between humans and computers to get
the advantages of this integration
