A. F. M. Shahen Shah | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr A. F. M. Shahen Shah | Artificial Intelligence | Best Researcher Award

Associate Professor at Yildiz Technical University, Turkey

Assoc. Prof. Dr. A. F. M. Shahen Shah is a distinguished academic and researcher in the Department of Electronics and Communication Engineering at Yildiz Technical University, Turkey. He is recognized as one of the World’s Top 2% Scientists by Stanford University and Elsevier (2023-2024), reflecting his exceptional contributions to research and academia. With extensive experience in teaching, project management, and interdisciplinary research, Dr. Shah’s work primarily focuses on next-generation communication systems, artificial intelligence, and disaster-resilient technologies. His leadership in multiple funded projects and innovative research underscores his commitment to advancing the field of electronics and communication engineering.

Professional Profile

Education

Dr. Shah completed his Ph.D. in Electronics and Communication Engineering at Yildiz Technical University in 2020, earning a CGPA of 3.75 and receiving a prestigious Gold Medal at ITEX. He holds a Master’s degree in Information Technology from the University of Dhaka, Bangladesh, where he ranked third in his batch with a CGPA of 3.85. His academic journey began with a Bachelor’s in Electronics and Telecommunication Engineering from Daffodil International University, Bangladesh, graduating at the top of his class with a CGPA of 3.96. His academic achievements highlight his unwavering commitment to excellence in learning and research.

Professional Experience

Dr. Shah’s professional career encompasses both academia and industry. He is currently an Associate Professor at Yildiz Technical University, where he has been teaching advanced undergraduate and graduate courses since 2021. He previously served as an Assistant Professor at Istanbul Gelisim University, specializing in wireless communication and artificial neural networks. Before transitioning to academia, Dr. Shah gained valuable industry experience as an IT professional in leading banks in Bangladesh, managing critical operations and support systems. His diverse career trajectory combines academic rigor with practical expertise, enabling him to bridge theory and real-world applications effectively.

Research Interests

Dr. Shah’s research interests lie in the realms of next-generation wireless communication systems, artificial intelligence, vehicular ad hoc networks (VANETs), and UAV-based disaster communication systems. He is particularly passionate about exploring the integration of intelligent reflecting surfaces and fluid antenna systems for 6G communication. His work also includes developing deep learning models for real-time sign language recognition and designing mobility-aware cooperative MAC protocols for VANETs. Dr. Shah’s innovative approach to addressing real-world challenges through advanced communication technologies reflects his dedication to impactful and forward-thinking research.

Research Skills

Dr. Shah possesses a diverse set of research skills, including expertise in designing and analyzing wireless communication systems, MIMO antenna systems, and deep learning-based applications. He is proficient in project management, having led multiple high-impact projects funded by TÜBİTAK and YTÜ-BAP. His technical expertise extends to developing and simulating advanced communication protocols, integrating artificial intelligence into communication systems, and optimizing network performance. With a strong foundation in programming, data analysis, and mathematical modeling, Dr. Shah excels in delivering innovative solutions to complex engineering problems.

Awards and Honors

Dr. Shah’s illustrious career has earned him several accolades, including recognition among the World’s Top 2% Scientists by Stanford University and Elsevier. He was awarded a Gold Medal in the 32nd ITEX for his outstanding Ph.D. research. Additionally, his academic excellence during his undergraduate and master’s studies earned him top rankings in his class. Dr. Shah’s consistent record of achievements in both research and academics highlights his profound impact on the field of electronics and communication engineering.

Conclusion 🤝

Assoc. Prof. Dr. A. F. M. Shahen Shah is a strong contender for the Best Researcher Award due to his remarkable academic credentials, global recognition, and leadership in innovative projects. With increased emphasis on publishing in high-impact journals, pursuing patents, and engaging broader audiences, he has the potential to further solidify his reputation as a leading researcher. His interdisciplinary expertise and proven project management skills make him an outstanding candidate for this prestigious recognition.

Publication Top Notes

  1. Survey and performance evaluation of multiple access schemes for next-generation wireless communication systems
    Authors: AFMS Shah, AN Qasim, MA Karabulut, H Ilhan, MB Islam
    Year: 2021
    Citations: 91
    Published in: IEEE Access 9, 113428-113442
  2. A survey from 1G to 5G including the advent of 6G: Architectures, multiple access techniques, and emerging technologies
    Authors: AFMS Shah
    Year: 2022
    Citations: 65
    Published in: 2022 IEEE 12th Annual Computing and Communication Workshop and Conference
  3. Internet of things and wireless sensor networks for smart agriculture applications-a survey
    Authors: MN Mowla, N Mowla, AFMS Shah, K Rabie, T Shongwe
    Year: 2023
    Citations: 62
    Published in: IEEE Access
  4. A survey on cooperative communication in wireless networks
    Authors: AFMS Shah, MS Islam
    Year: 2014
    Citations: 60
    Published in: International Journal of Intelligent Systems and Applications 6 (7), 66-78
  5. A secured privacy-preserving multi-level blockchain framework for cluster-based VANET
    Authors: AFMS Akhter, M Ahmed, AFMS Shah, A Anwar, A Zengin
    Year: 2021
    Citations: 55
    Published in: Sustainability 13 (1), 400
  6. CB-MAC: A novel cluster-based MAC protocol for VANETs
    Authors: AFM Shahen Shah, H Ilhan, U Tureli
    Year: 2019
    Citations: 53
    Published in: IET Intelligent Transport Systems 13 (4), 587-595
  7. RECV-MAC: A novel reliable and efficient cooperative MAC protocol for VANETs
    Authors: AFM Shahen Shah, H Ilhan, U Tureli
    Year: 2019
    Citations: 43
    Published in: IET Communications 13 (16), 2541-2549
  8. Inspecting VANET with various critical aspects–a systematic review
    Authors: MA Karabulut, AFMS Shah, H Ilhan, ASK Pathan, M Atiquzzaman
    Year: 2023
    Citations: 41
    Published in: Ad Hoc Networks, 103281
  9. A blockchain-based emergency message transmission protocol for cooperative VANET
    Authors: M Ahmed, N Moustafa, AFMS Akhter, I Razzak, E Surid, A Anwar, …
    Year: 2021
    Citations: 38
    Published in: IEEE Transactions on Intelligent Transportation Systems 23 (10), 19624-19633
  10. A blockchain-based authentication protocol for cooperative vehicular ad hoc network
    Authors: AFMS Akhter, M Ahmed, AFMS Shah, A Anwar, ASM Kayes, A Zengin
    Year: 2021
    Citations: 37
    Published in: Sensors 21 (4), 1273

 

Amal Shaheen | Machine Learning AI | Excellence in Research

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Amal Shaheen | Machine Learning AI | Excellence in Research

Doctrate at UOB, Bahrain.

Amal Shaheen is a distinguished AI Transformation Strategy Leader and Big Data Analytics Expert with over 25 years of experience in government, business, and IT sectors. Renowned for her innovative thinking and strategic vision, she combines practical experience with academic expertise in AI, Machine Learning, and Project Management. Amal excels in driving AI transformation strategies, enhancing organizational efficiency, and overseeing complex projects to achieve impactful outcomes. Her leadership style emphasizes empowerment, collaboration, and resilience, allowing her to navigate dynamic environments effectively. As a current lecturer at the University of Bahrain, she is passionate about guiding students in Project Management and Big Data Analytics, preparing them for successful careers in technology. With a commitment to sustainable growth and continuous improvement, Amal is dedicated to advancing her field and contributing to impactful research and education.

Profile👤

Orcid

Education📝

Amal Shaheen holds a Ph.D. in Computing and Information Technology with a focus on AI and Machine Learning from the University of Bahrain, where she is expected to graduate in December 2024. Her thesis explores novel models in Graph Deep Learning based on Autoencoders, showcasing her commitment to advancing knowledge in the field. She also possesses an MBA in Management Information Systems from the New York Institute of Technology, Bahrain, which complements her technical expertise with essential management skills. Furthermore, her educational background includes a Bachelor’s degree in Computer Science from the University of Qatar. To further enhance her qualifications, Amal has obtained various certifications, including AI Transformation Leader from the United States AI Institute and Professional Co-Active Coach Certified in Leadership. Her diverse education equips her with a strong foundation to excel in both academic and professional environments.

Experience👨‍🏫

Amal Shaheen has amassed extensive experience across various leadership roles, demonstrating her capabilities in both academic and governmental sectors. Currently, she serves as a lecturer at the University of Bahrain, guiding students in Project Management and Big Data Analytics, where she blends practical insights with academic rigor. Previously, she held significant positions at the Civil Service Bureau, including Director of the Management Information Directorate and Acting Director of the Organizational Performance Directorate. In these roles, she managed IT processes, developed strategic business initiatives, and led the transformation of manual services to electronic workflows. Additionally, she spearheaded multiple civil service projects, ensuring their successful implementation and alignment with organizational goals. Her rich background reflects her ability to oversee complex plans, drive innovative solutions, and enhance operational efficiency, establishing her as a prominent leader in her field.

Research Interest🔬 

Amal Shaheen’s research interests lie at the intersection of AI, Big Data Analytics, and Machine Learning, with a focus on developing innovative solutions to real-world challenges. Her current research delves into Graph Deep Learning, exploring novel models that leverage Autoencoders to enhance predictive capabilities and data analysis. Amal is particularly passionate about the application of AI in government and public services, aiming to streamline processes and improve decision-making through data-driven insights. She is also interested in sustainable technology and its role in fostering organizational growth and efficiency. By bridging theoretical knowledge and practical application, Amal aims to contribute significantly to advancing research in AI and data analytics. Her commitment to mentorship and student engagement further enhances her research endeavors, as she encourages the next generation of researchers to explore innovative approaches in their studies and projects.

Awards and Honors🏆

Throughout her illustrious career, Amal Shaheen has received numerous awards and honors in recognition of her contributions to AI, Big Data Analytics, and public service transformation. Among her notable achievements is her designation as an AI Transformation Leader from the United States AI Institute, highlighting her expertise in driving technological advancements. Additionally, she has completed various training programs in leadership, project management, and strategic planning, earning accolades for her commitment to excellence and innovation. Amal’s leadership in spearheading successful civil service initiatives has garnered recognition from government authorities, underscoring her impact on organizational efficiency and effectiveness. Her contributions to education have also been acknowledged, as she continues to inspire students and foster a culture of learning and growth. These accolades reflect her dedication to advancing knowledge and driving positive change within her field.

Skills🛠️

Amal Shaheen possesses a diverse skill set that positions her as a leader in the fields of AI, Big Data Analytics, and Project Management. Her technical skills include proficiency in advanced AI frameworks, Machine Learning models, and data analysis tools such as Spark, Hadoop, Python, and R. Additionally, Amal has strong project management skills, enabling her to guide complex initiatives from conception to execution while ensuring quality and adherence to deadlines. Her leadership abilities are complemented by exceptional interpersonal skills, fostering collaboration and teamwork among colleagues and students. Detail-oriented and adaptable, she thrives in dynamic environments, embracing change and finding innovative solutions to challenges. Furthermore, Amal’s analytical thinking, strategic planning, and problem-solving skills equip her to identify and capitalize on opportunities for improvement and growth within organizations. This well-rounded skill set enables her to drive impactful projects and contribute to advancements in her field.

Conclusion 🔍 

In conclusion, Amal Shaheen exemplifies excellence in her roles as an AI Transformation Strategy Leader, educator, and researcher. With over 25 years of experience, she brings a wealth of knowledge and expertise to the fields of AI, Big Data Analytics, and Project Management. Her innovative mindset, strong leadership skills, and commitment to mentorship position her as a role model for aspiring professionals. Amal’s ongoing research endeavors and dedication to advancing technology for organizational efficiency reflect her passion for creating meaningful impacts in both academic and governmental sectors. As she continues her journey, her contributions to the field of AI and her commitment to nurturing the next generation of leaders are sure to leave a lasting legacy. Amal Shaheen stands poised to drive further innovations and advancements in her field, making her a deserving candidate for recognition in excellence in research.

Publication Top Notes

Title: “Innovative Approaches to Big Data Analytics in Public Sector Applications”
Author: Amal Shaheen
Year: 2023
Citation: Shaheen, A. (2023). Innovative Approaches to Big Data Analytics in Public Sector Applications. Journal of Government Information, 45(2), 101-115.

Title: “Graph Deep Learning: Novel Models Based on Autoencoder Framework”
Author: Amal Shaheen
Year: 2024
Citation: Shaheen, A. (2024). Graph Deep Learning: Novel Models Based on Autoencoder Framework. International Journal of Artificial Intelligence Research, 12(1), 45-59.

Title: “Transforming HR Processes: The Role of AI in Government Agencies”
Author: Amal Shaheen
Year: 2022
Citation: Shaheen, A. (2022). Transforming HR Processes: The Role of AI in Government Agencies. Journal of Public Administration Research and Theory, 34(3), 375-392.

Title: “AI and Machine Learning in Data-Driven Decision Making”
Author: Amal Shaheen
Year: 2021
Citation: Shaheen, A. (2021). AI and Machine Learning in Data-Driven Decision Making. Computing and Informatics, 40(4), 777-794.

Title: “Project Management Best Practices in AI Implementation”
Author: Amal Shaheen
Year: 2023
Citation: Shaheen, A. (2023). Project Management Best Practices in AI Implementation. Project Management Journal, 54(1), 28-39.

Mona Jamjoom | AI | Best Researcher Award

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Assoc Prof Dr. Mona Jamjoom | AI | Best Researcher Award

Assoc Prof Dr. Mona Jamjoom, Princess Nourah bint Abdulrahman University, Saudi Arabia

Assoc Prof Dr. Mona Jamjoom is an accomplished researcher in the field of artificial intelligence, recognized for her innovative contributions and impactful studies. With a strong focus on machine learning and data analytics, she has published numerous papers in leading journals and has been awarded the Best Researcher Award for her groundbreaking work. Mona is passionate about harnessing AI to solve complex problems and improve decision-making processes across various industries. Her commitment to advancing technology while addressing ethical considerations makes her a prominent figure in the AI community.

Profile:

Scholar

Academics:

Assoc Prof Dr. Mona Jamjoom holds a PhD in Artificial Intelligence from King Saud University, awarded in May 2016. She also earned her Master’s degree in Computer Science from the same institution in 2004, following her Bachelor’s degree in Computer Science, which she completed in 1992. Her academic background provides a strong foundation for her research and contributions to the field of AI.

Professional Experiences:

Assoc Prof Dr. Mona Jamjoom has extensive professional experience in academia. Since 2021, she has served as an Associate Professor at Princess Nourah bint Abdulrahman University in Riyadh, Saudi Arabia. Prior to this, she was an Assistant Professor at the same institution from 2017 to 2021. Mona began her academic career as a Lecturer at Princess Nourah bint Abdulrahman University from 2007 to 2016, and before that, she worked as a Teaching Assistant from 1998 to 2007. Her career in the field began in 1993, when she provided technical support at the university, further solidifying her commitment to education and technology.

Activities:

Assoc Prof Dr. Mona Jamjoom is actively engaged in various professional activities that enhance her contributions to the field of artificial intelligence. In 2024, she joined the work team at the Center for Advanced Studies in Artificial Intelligence at King Saud University, collaborating on the KSU AI Satellite Lab project with SDAIA. She served as an external examiner for a doctoral thesis on deep learning applications for visual pollution detection in Riyadh. Additionally, she reviewed applications for the Apple Developer Academy’s second challenge for female students and participated in consulting sessions during the Gulf Hackathon Program focused on AI in public education. Mona also acted as a consultant for the UNESCO project “AI Capacity Building in Arabic-speaking Countries,” supported by Huawei Technologies. She has reviewed numerous papers for ISI journals and attended the research day at Princess Nourah bint Abdulrahman University. Furthermore, she co-supervised a PhD student specializing in Cognitive Computing at Universiti Kuala Lumpur, Malaysia.

Publication Top Notes:

M. Adil, Z. Yinjun, M. M. Jamjoom, and Z. Ullah. “OptDevNet: An Optimized Deep Event-Based Network Framework for Credit Card Fraud Detection.” IEEE Access, vol. 12, pp. 132421-132433, 2024. doi: 10.1109/ACCESS.2024.3458944.

Rabbani, H., Shahid, M. F., Khanzada, T. J. S., Siddiqui, S., Jamjoom, M. M., Ashari, R. B., Ullah, Z., Mukati, M. U., and Nooruddin, M. “Enhancing Security in Financial Transactions: A Novel Blockchain-Based Federated Learning Framework for Detecting Counterfeit Data in Fintech.” PeerJ Computer Science, vol. 10, e2280, 2024.

Malik, M. S. I., Nawaz, A., and Jamjoom, M. M. “Hate Speech and Target Community Detection in Nastaliq Urdu Using Transfer Learning Techniques.” IEEE Access, 2024.

Kurtoğlu, A., Eken, Ö., Çiftçi, R., Çar, B., Dönmez, E., Kılıçarslan, S., Jamjoom, M. M., Abdel Samee, N., Hassan, D. S. M., and Mahmoud, N. F. “The Role of Morphometric Characteristics in Predicting 20-Meter Sprint Performance Through Machine Learning.” Scientific Reports, vol. 14, no. 1, 16593, 2024.

Shah, S. M. A. H., Khan, M. Q., Rizwan, A., Jan, S. U., Samee, N. A., and Jamjoom, M. M. “Computer-Aided Diagnosis of Alzheimer’s Disease and Neurocognitive Disorders with Multimodal Bi-Vision Transformer (BiViT).” Pattern Analysis and Applications, vol. 27, no. 3, 76, 2024.

Ishtiaq, A., Munir, K., Raza, A., Samee, N. A., Jamjoom, M. M., and Ullah, Z. “Product Helpfulness Detection with Novel Transformer Based BERT Embedding and Class Probability Features.” IEEE Access, 2024.

Abbas, M. A., Munir, K., Raza, A., Samee, N. A., Jamjoom, M. M., and Ullah, Z. “Novel Transformer Based Contextualized Embedding and Probabilistic Features for Depression Detection from Social Media.” IEEE Access, 2024.

Elhadad, A., Jamjoom, M., and Abulkasim, H. “Reduction of NIFTI Files Storage and Compression to Facilitate Telemedicine Services Based on Quantization Hiding of Downsampling Approach.” Scientific Reports, vol. 14, no. 1, 5168, 2024.

Malik, M. S. I., Younas, M. Z., Jamjoom, M. M., and Ignatov, D. I. “Categorization of Tweets for Damages: Infrastructure and Human Damage Assessment Using Fine-Tuned BERT Model.” PeerJ Computer Science, vol. 10, e1859, 2024.

Malik, M. S. I., Nawaz, A., Jamjoom, M. M., and Ignatov, D. I. “Effectiveness of ELMo Embeddings and Semantic Models in Predicting Review Helpfulness.” Intelligent Data Analysis, (Preprint), 1-21, 2023.

Karimeh Ata | Artificial Intelligence | Best Researcher Award

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Dr. Karimeh Ata | Artificial Intelligence | Best Researcher Award

Researcher at UPM, Jordan

Dr. Karimeh Ata is a Computer and Artificial Intelligence Engineering Ph.D. candidate at Universiti Putra Malaysia (UPM), specializing in deep learning and big data analytics for urban mobility and vehicle flow optimization. With a strong academic foundation, she holds a Master’s degree in Computer Engineering and Embedded Systems from UPM and a Bachelor’s degree in Computer Engineering from Fahad Bin Sultan University, Saudi Arabia, where she graduated with first-class honors. Dr. Ata’s research focuses on solving complex problems using advanced algorithms like Dijkstra’s and Ant Colony Optimization, contributing to various high-impact projects. In addition to her academic achievements, she has experience as an AI trainer and lecturer, and her work is highlighted by numerous publications in top-tier journals and conferences. Proficient in technologies like Microsoft Azure, GIS, Python, and Raspberry Pi, Dr. Ata is committed to driving innovation in the fields of artificial intelligence and computer engineering.

Profile

Education

Dr. Karimeh Ata is currently pursuing her Ph.D. in Computer Engineering and Artificial Intelligence at Universiti Putra Malaysia (UPM), with an expected completion in June 2024. Her doctoral research focuses on traffic flow prediction using deep learning and big data analysis, and she has maintained an outstanding GPA of 4.00 throughout her studies. Prior to this, she earned a Master of Computer Engineering and Embedded Systems from UPM in 2019, where she addressed challenges in vehicle navigation and parking optimization using algorithms like Dijkstra’s and Ant Colony Optimization, achieving a GPA of 3.57. Dr. Ata holds a Bachelor of Computer Engineering from Fahad Bin Sultan University (FBSU) in Saudi Arabia, where she graduated with first-class honors and a GPA of 4.91, also receiving the Prince Fahad Bin Sultan Scholarship for academic excellence.

Professional Experience

Dr. Karimeh Ata has a diverse range of professional experience in the fields of artificial intelligence and computer engineering. From December 2018 to January 2020, she served as an Artificial Intelligence Trainer at Hass Resources Corporation in Malaysia, where she supervised and trained teams on AI applications in education. In early 2019, she was a member of the Technical Committee for the Symposium on Control Systems and Signal Processing in Malaysia, bringing together experts to discuss advancements in AI, signal processing, and control systems. Dr. Ata has also contributed to academia as a Computer Engineering Lecturer at Universiti Putra Malaysia (UPM) from November 2022 to September 2023, where she designed and delivered courses on subjects such as Programming Fundamentals, Digital Logic Design, and Machine Learning, while also supervising laboratory sessions. Additionally, she worked as a Research Assistant at UPM from July 2021 to October 2022, where she ensured the quality, integrity, and security of research data and guided teams in preparing findings for top-tier journals and conferences. Dr. Ata’s professional experience highlights her leadership in project management, research ethics, and AI integration.

Research Interest

Dr. Karimeh Ata’s research interests focus on leveraging advanced technologies to address complex challenges in urban mobility, traffic flow optimization, and artificial intelligence. Her work primarily centers around deep learning and big data analytics, with a particular emphasis on traffic flow prediction and vehicle optimization. She has explored algorithms such as Dijkstra’s and Ant Colony Optimization to calculate the shortest paths and improve transportation efficiency in urban environments. Additionally, Dr. Ata is interested in applying AI-driven solutions to enhance brain stroke detection, lithium iron phosphate battery electrode performance, and spatial-temporal traffic flow prediction through multi-layer models. Her research aims to innovate in fields like smart transportation systems, deep learning, and AI for real-world problem-solving.

Research Skills

Dr. Karimeh Ata possesses extensive research skills in deep learning, big data analytics, and artificial intelligence, with a focus on solving complex problems in urban mobility and traffic flow optimization. She is proficient in designing and implementing deep learning models for traffic prediction and vehicle flow using large datasets to ensure accuracy. Dr. Ata has expertise in optimizing algorithms such as Dijkstra’s and Ant Colony Optimization to calculate efficient paths in transportation networks. Her research capabilities extend to developing innovative AI models for brain stroke detection and lithium battery performance evaluation, along with spatial-temporal data analysis using advanced machine learning techniques like CNN-GRU and dynamic KNN-Bi-LSTM. Dr. Ata’s skills reflect a deep understanding of integrating AI into real-world applications.

Award and Recognition

Dr. Karimeh Ata has been recognized for her academic excellence and contributions to research in the fields of computer engineering and artificial intelligence. She was awarded the prestigious Prince Fahad Bin Sultan Scholarship during her undergraduate studies for her outstanding academic performance, graduating with a first honor distinction. Additionally, her research work has been acknowledged through notable publications in top-tier journals, reflecting her deep expertise in areas such as traffic flow prediction and smart indoor parking systems. Dr. Ata’s achievements underscore her commitment to advancing the field of AI and computer engineering through innovative research and impactful projects.

Conclusion

Given Dr. Karimeh Ata’s strong academic background, innovative research contributions, and extensive skills in AI and big data, she is a suitable candidate for the Best Researcher Award. Her work not only demonstrates technical proficiency but also showcases her ability to solve complex, real-world problems, making a significant impact in the field of AI and computer engineering.

Publications Top Notes

  • Title: Smart Indoor Parking System Based on Dijkstra’s Algorithm
    Authors: K.M. Ata, A.C. Soh, A. Ishak, H. Jaafar, N. Khairuddin
    Cited By: 19
    Year: 2019
  • Title: Performance Evaluation of Two Mobile Ad-hoc Network Routing Protocols: Ad-hoc On-Demand Distance Vector Dynamic Source Routing
    Authors: J. Alamri, A.S. Al-Johani, K.I. Ata
    Cited By: 13
    Year: 2020
  • Title: Radio Frequency Identification (RFID) Indoor Parking Control System
    Authors: H.M.M. El-Hageen, K. Ibrahim, M. Ata, A. Chesoh, H. Jaafar
    Cited By: 3
    Year: 2017
  • Title: A Smart Guidance Indoor Parking System Based on Dijkstra’s Algorithm and Ant Colony Algorithm
    Authors: K.I. Ata, A.C. Soh, A.J. Ishak, H. Jaafar
    Cited By: 1
    Year: 2020
  • Title: Investigation of Loading Variation Effect on Lithium Iron Phosphate Battery Electrodes Using Long Short Term Memory
    Authors: K.A.A. Md Azizul Hoque, Mohd Khair Hassan, Muhesh Dhaarwind, Abdulrahman Hajjo
    Year: 2024
  • Title: Enhancing Brain Stroke Detection: A Novel Deep Neural Network with Weighted Binary Cross Entropy Training
    Authors: A.N. Qasim, S. Alani, S.N. Mahmood, S.S. Mohammed, D.A. Aziz, K.I.M. Ata
    Year: 2024
  • Title: Guidance System Based on Dijkstra-Ant Colony Algorithm with Binary Search Tree for Indoor Parking System
    Authors: H.J. K. Ibrahim Ata, A. Che Soh, A.J. Ishak
    Year: 2021