Manar Hamza | Computer Science Data mining | Best Researcher Award

Dr. Manar Hamza | Computer Science Data mining | Best Researcher Award

professor atΒ  Prince Sattam bin Abd El Aziz University, China

πŸ‘©β€πŸ« Experienced Computer Science Lecturer since 2005 with expertise in data mining, text mining, and information security. πŸ’» Holds a strong track record in research and academia, leveraging innovation and teamwork. Aims to thrive in challenging, dynamic, and team-oriented environments that foster growth. 🌍 Based in Sudan and Saudi Arabia, dedicated to academic excellence and community impact.

Professional Profiles:

scopus

Education πŸŽ“

Ph.D. in Computer Science from Omdurman Islamic University, Sudan (2018–2021). πŸŽ“ Master’s Degree in Computer Science from Sudan University of Science and Technology (2003–2005). πŸŽ“ B.Sc. in Computer Science from Omdurman Islamic University, Sudan (1995–1999). πŸ“š Comprehensive training in research skills, academic advising, and IT tools like Mendeley, Latex, and iThenticate.

Experience πŸ–₯️

Lecturer in Computer Science at Prince Sattam bin Abdul-Aziz University, Saudi Arabia (2013–present). πŸ‘©β€πŸ’Ό Supervisor and Coordinator roles in quality, academic advising, and measurement (2014–2020). πŸ‡ΈπŸ‡© Lecturer at Omdurman Islamic University, Sudan (2005–2012). πŸ‘©β€πŸ”¬ E-teaching and training specialist with Arab Board experience (2023).

Awards and Honors πŸ†

Certificates of Appreciation from PSAU for contributions to quality, development, and academic planning. πŸ™Œ Recognized for voluntary services, including extracurricular activities and technical support for students and staff. ⭐ Esteemed arbitrator in scientific and innovation conferences. πŸ“œ Active contributor to enhancing the learning environment with innovative solutions.

Research Focus πŸ”

Data mining, text mining, and information security are core research areas. πŸ“Š Interested in qualitative research, outcome-based education, and e-learning systems. 🌐 Advocates for advancing academic IT tools like Prezi, Mendeley, and iThenticate. πŸ›‘οΈ Exploring cybersecurity methods and their application in education and industry.

✍️Publications Top Note :

1. Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

Published in: SN Computer Science, 2024, 5(5), 549

Summary: This paper proposes a novel classification model for urban-related tweets using arithmetic optimization integrated with deep learning to support sustainable urban living solutions.

2. Enhancing Traffic Flow Prediction in Intelligent Cyber-Physical Systems

Published in: IEEE Transactions on Consumer Electronics, 2024, 70(1), pp. 1889–1902

Summary: Introduces a Bi-LSTM approach enhanced with a Kalman filter for accurate traffic flow prediction, addressing challenges in intelligent cyber-physical systems.

Citations: 5

3. Deer Hunting Optimization with Deep Learning-Driven Automated Fabric Defect Detection and Classification

Published in: Mobile Networks and Applications, 2024, 29(1), pp. 176–186

Summary: Utilizes the Deer Hunting Optimization algorithm with deep learning to achieve high accuracy in detecting and classifying fabric defects.

Citations: 1

4. Automatic Recognition of Cyberbullying in the Web of Things and Social Media Using Deep Learning Framework

Published in: IEEE Transactions on Big Data, 2024

Summary: Develops a deep learning-based framework to detect and prevent cyberbullying within social media and IoT environments.

5. Artificial Rabbit Optimizer with Deep Learning for Fall Detection in IoT Environment

Published in: AIMS Mathematics, 2024, 9(6), pp. 15486–15504

Summary: Introduces the Artificial Rabbit Optimizer combined with deep learning to enhance fall detection systems for disabled individuals in IoT environments.

Citations: 1

6. Computational Linguistics-Based Arabic Poem Classification and Dictarization Model

Published in: Computer Systems Science and Engineering, 2024, 48(1), pp. 98–114

Summary: Proposes a computational linguistics model to classify Arabic poems and enhance their dictarization process.

7. Abstractive Arabic Text Summarization Using Hyperparameter Tuned Denoising Deep Neural Network

Published in: Intelligent Automation and Soft Computing, 2024, 38(2), pp. 153–168

Summary: Develops a deep neural network with hyperparameter tuning for effective abstractive summarization of Arabic texts.

Citations: 1

8. Chaotic Equilibrium Optimizer-Based Green Communication With Deep Learning Enabled Load Prediction in IoT Environment

Published in: IEEE Access, 2024, 12, pp. 258–267

Summary: Presents a Chaotic Equilibrium Optimizer combined with deep learning to improve green communication and load prediction in IoT systems.

Citations: 2

9. Land Use and Land Cover Classification Using River Formation Dynamics Algorithm With Deep Learning on Remote Sensing Images

Published in: IEEE Access, 2024, 12, pp. 11147–11156

Summary: Leverages the River Formation Dynamics algorithm integrated with deep learning for efficient land use and land cover classification using remote sensing data.

Citations: 4

10. Prediction of Sleep Quality Using Wearable-Assisted Smart Health Monitoring Systems

Published in: Journal of King Saud University – Science, 2023, 35(9), 102927

Summary: Utilizes wearable technology and statistical data to predict sleep quality, providing insights into personalized smart health monitoring systems.

Citations: 1

Conclusion

The candidate’s extensive experience, academic qualifications, and contributions to computer science, particularly in data mining and information security, make them a strong contender for the Research for Best Researcher Award. With some strategic enhancements to highlight impactful research and global contributions, their profile could exemplify the qualities of an award-winning researcher in computer science.

Mr. Bingtao Wang | Energy consumption model | Best Researcher Award

Mr. Bingtao Wang | Energy consumption model | Best Researcher Award

Mr. Bingtao Wang, Shan Dong University, China

Bingtao Wang, currently a Master’s student in Communication Engineering at Shandong University (Weihai), holds a Bachelor’s degree in Electronic Engineering. His research focuses on energy consumption models and fault diagnosis in mobile robots. Bingtao has led multiple innovative projects, including the development of a quadcopter UAV and a visual perception crawler robot. His significant contribution lies in the creation of robust energy models and diagnostic methods that enhance the efficiency and reliability of Three-Wheeled Omnidirectional Mobile Robots (TOMRs), paving the way for future advancements in autonomous navigation and robotics.

Professional Profiles:

Orcid

πŸŽ“ Academic and Professional Background (100 words max):

Bingtao Wang, male, was born in Liaocheng City, Shandong Province in September 2001. In 2023, he graduated from Shandong University (Weihai) with a Bachelor’s degree in Electronic Engineering. He is currently pursuing a Master’s in Communication Engineering at Shandong University (Weihai), College of Electrical and Engineering. His research focuses on energy consumption model building and fault diagnosis.

πŸ“ Self-Declaration:

I authenticate that to the best of my knowledge the information given in this form is correct and complete. At any time, I am found to have concealed any material information, my application shall be liable to be summarily terminated without notice. I have read the terms and conditions and other policies of the Awards and agree to them.

✍️Publications Top Note :