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.

Prof. Shao Hsien Chen | Smart machine | Best Researcher Award

Prof. Shao Hsien Chen | Smart machine | Best Researcher Award

Prof. Shao Hsien Chen,Β  National Chin-Yi University of Technology, Taiwan

Prof. Shao Hsien Chen is academic and researcher in the field of renewable energy, holds a PhD in Bio systems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

 

Professional Profiles:

Scopus

πŸŽ“ Academic Background:

B.S. degree from National Chin-Yi University of Technology, Taiwan, in 1992.M.S. and Ph.D. degrees from National Chung Cheng University, Taiwan, in 2001 and 2006, respectively.

πŸ‘¨β€πŸ« Professional Experience:

R&D manager at Ching Hung Machinery & Electric Industrial Co. LTD and AWEA Machinery & Electric Industrial Co. LTD, Taiwan, from 2005 to 2009.Professor at National Chin-Yi University of Technology since 2009.

πŸ” Research Focus:

Smart machines, machine tool design, and superalloy machining.

πŸ“Š Selected Research Highlights:

πŸ” Utilized Neural Networks for cutting temperature prediction.πŸ”„ Developed a Hybrid Optimization Algorithm for thermal displacement compensation.πŸ› οΈ Explored the application of Response Surface Methodology in rigid tapping.πŸ“ˆ Investigated the use of CNN-BP for Inconel-718 chip feature analysis.πŸ”„ Applied Backpropagation Neural Model in automatic lubrication installation.🌐 Explored the integration of CNC Machine Tool with Plasma for online surface heat treatment.This comprehensive research portfolio showcases Dr. Shao-Hsien Chen’s expertise in advanced manufacturing technologies, optimization methodologies, and innovative applications in machine tool design. πŸš€πŸ”§

πŸ“ŠΒ Citation Metrics (Google Scholar):

Citations by: All – 215, Since 2018 – 158

h-index: All – 7, Since 2018 – 7

i10 index: All – 6, Since 2018 –6