Konstantinos Blazakis | Machine Learning | Research Excellence Award

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Dr. Konstantinos Blazakis | Machine Learning | Research Excellence Award

Adjunct Professor | Hellenic Mediterranean University | Greece

Dr. Konstantinos Blazakis is an accomplished researcher specializing in advanced artificial intelligence applications for energy systems, with strong expertise in smart grids, renewable energy integration, and intelligent power system analytics. His research bridges theoretical modeling and real-world deployment, contributing to sustainable and intelligent energy infrastructures. He holds advanced training in electrical and computer engineering, with strong foundations in applied mathematics, physics, and intelligent systems. His work spans quantum machine learning, deep learning for renewable forecasting, electricity theft detection, and AI-driven energy optimization. His scholarly impact includes 345 citations from 336 documents, 11 publications, and an h-index of 6, reflecting consistent academic influence and research excellence.

Citation Metrics (Scopus)

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Citations
345

Documents
11

h-index
6

        🟦 Citations    🟥 Documents    🟩 h-index

Featured Publications

SASANK VVS |machine learning| Best Researcher Award

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Dr. SASANK VVS |machine learning| Best Researcher Award

ASSISTANT PROFESSOR,K L UNIVERSITY,India

Dr. VVS Sasank is an Assistant Professor at K L University, India. With a strong background in his field of expertise, Dr. Sasank is dedicated to advancing research and education. He has made significant contributions to academic literature and is recognized for his commitment to fostering innovative learning methodologies. At K L University, he focuses on mentoring students, conducting impactful research, and contributing to the institution’s mission of excellence in higher education. His areas of interest include [add specific areas of research or specialization if known].

Summary:

Dr. Sasank VVS has exhibited a robust academic and research profile, combining strong academic qualifications, a distinguished teaching career, and significant contributions to research. His efforts in publishing SCI-indexed papers, receiving patents, and securing prestigious certifications reflect his dedication to advancing knowledge in his field. His work is not only academic but also highly relevant in the practical application of IoT and machine learning technologies.

 

Professional Profiles:

Scopus

🎓 Education :

Dr. Sasank has consistently demonstrated academic brilliance, earning a Ph.D. in Computer Science from K.L. University (2019–2023), focusing on cutting-edge research. He completed his M.Tech in Computer Science and Technology at GITAM University (2016), securing a CGPA of 9.11 and achieving the top rank in his department. His B.Tech in Information Technology at GITAM University (2013) was marked by distinction with a CGPA of 8.15. Earlier, he excelled in his intermediate education at Mega Junior College (2009) and 10th-grade studies at Jassver English Medium School (2007), graduating with first-class distinctions.

 

🏢 Experience:

With extensive teaching and administrative experience, Dr. Sasank currently serves as an Assistant Professor and ERP Registration In-charge at K.L. University (December 2021–Present), where he manages course registrations and teaches advanced computer science topics. Previously, he held roles as an Assistant Professor and Placement Officer at Anil Neerukonda Institute of Technology & Sciences (2017–2019) and as an Assistant Professor at Lendi Institute of Engineering & Technology (2016–2017). His teaching journey began as a Teaching Assistant at GITAM University (2015–2016).

🛠️Skills:

Dr. Sasank is proficient in programming languages such as C, C++, Java, and DevOps, and database systems like Oracle-10G, MySQL, and PostgreSQL. His teaching repertoire includes specialized subjects like DBMS, Software Engineering, Computer Architecture, UI/UX Design, and DevOps. Certified as a Google Associate Cloud Engineer (2023) and AWS Cloud Practitioner, he combines technical and academic expertise to advance his professional goals

 

Research Focus :

A committed researcher, Dr. Sasank has published 5 SCI-indexed papers, with 1 under review, alongside 3 Scopus-indexed papers, 1 book chapter, and 3 IEEE conference papers. His research interests span IoT, machine learning, software modeling, and data management systems. Additionally, he has guided 12 B.Tech batches, 2 M.Tech project batches, and 1 ongoing Ph.D. scholar, showcasing his mentorship abilities.

 

🔬Awards:

He was recognized for his academic excellence by securing 1st rank in M.Tech (CSE) at GITAM University (2016) and is celebrated for his innovative project guidance and research accomplishments.

Conclusion:

Dr. Sasank VVS is an excellent candidate for the Best Researcher Award due to his substantial contributions to both the academic and research domains. His accomplishments in research, teaching, and innovation underscore his potential for long-term impact in the field of computer science. With a few strategic improvements, such as broadening his research areas and fostering more international collaborations, Dr. Sasank can continue to make significant contributions to the global scientific community.

 Publications:

  • Prostate cancer classification using adaptive swarm intelligence-based deep attention neural network
    • Authors: Sowmya, D., Bhavani, S.A., Sasank, V.V.S., Rao, T.S.
    • Year: 2024
    • Citations: 0

 

  • Real-time face detection and recognition
    • Authors: Lekhaz, A., Sasank, V.V.S., Rao, Y.K.
    • Year: 2024
    • Citations: 0

 

  • Effective Segmentation and Brain Tumor Classification Using Sparse Bayesian ELM in MRI Images
    • Authors: Sasank, V.V.S., Venkateswarlu, S.
    • Year: 2023
    • Citations: 1

 

  • Monitor and Control Electricity for Home Appliance
    • Authors: Sharma, P.K., Lakshmi, B., Prakash, A., Sasank, V.V.S., Ashokkumar, N.
    • Year: 2023
    • Citations: 0

 

  • An Analysis and Study of Brain Cancer with RNN Algorithm based AI Technique
    • Authors: Vallathan, G., Rao Yanamadni, V., Vidhya, R.G., Ambhika, C., Sasank, V.V.S.
    • Year: 2023
    • Citations: 7

 

  • Machine Learning Model to Reduce the Various Defects on Die Casting Process
    • Authors: Jagadeesan, S., Janardhan, M., Singh, B., Sasank, V.V.S., Kapila, D.
    • Year: 2023
    • Citations: 0

 

  • Smart Home Messenger Notifications System using IoT
    • Authors: Sai, M.R., Teja, K.K., Sasank, V.P., Kavitha, M., Aravinth, S.S.
    • Year: 2023
    • Citations: 10

 

  • Hybrid deep neural network with adaptive rain optimizer algorithm for multi-grade brain tumor classification of MRI images
    • Authors: Sasank, V.V.S., Venkateswarlu, S.
    • Year: 2022
    • Citations: 15

 

  • HATE SPEECH & OFFENSIVE LANGUAGE DETECTION USING ML & NLP
    • Authors: Panchala, G.H., Sasank, V.V.S., Adidela, D.R.H., Ashesh, K., Prasad, C.
    • Year: 2022
    • Citations: 6

 

  • Security and Privacy in Associated Self-Controlled Cars
    • Authors: Sasank, V.V.S., Lokesh, B., Mahesh, J., Kumar, T.S., Prasad, C.
    • Year: 2022
    • Citations: 0

 

Zubair Akhtar Mohd | Computer Aided Design In Mechanical Engineering | Best Researcher Award

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Mr. Zubair Akhtar Mohd | Computer Aided Design In Mechanical Engineering | Best Researcher Award

 Mr. Zubair Akhtar Mohd, Technische Hochschule Ingolstadt, Germany

Mr. Zubair Akhtar Mohd is a Research Associate at Technische Hochschule Ingolstadt, Germany, specializing in automotive engineering and artificial intelligence applications in predictive modeling and manufacturing optimization. He holds a Master’s degree in Automotive Engineering from THI and a Bachelor’s in Mechanical Engineering from Aligarh Muslim University, India. His research focuses on integrating Finite Element Analysis (FEA) with AI, using advanced machine learning algorithms like CNNs and RNNs to forecast the lifespan of electronic components. Mr. Mohd is also involved in scientific projects, data generation for materials testing, and academic teaching in CAD and simulation.

 

Professional Profiles:

 

🎓 Education :

Holds a Master’s degree in Automotive Engineering from Technische Hochschule Ingolstadt, Germany, with a GPA of 1.9, focusing on production optimization and AI in automotive systems. Bachelor’s degree in Mechanical Engineering from Aligarh Muslim University, India, with a GPA of 1.6, specializing in vehicle technology and CAD/CAE programming.

 

🏢 Experience:

Currently working as a Research Associate at the Institute of Innovative Mobility, Technische Hochschule Ingolstadt, focusing on method development for predicting electronics component lifespan using deep learning. Previously employed as a working student at CADS Engineering GmbH, contributing to vehicle design and occupant protection research, and as an Industrial Engineer in India, implementing safety and efficiency improvements in manufacturing processes.

🛠️Skills:

Proficient in Python, TensorFlow, PyTorch, and Linux, with additional expertise in tools such as Git, JavaScript, and MS Office applications. Experience with HTML, CSS, and Carla, and extensive knowledge in engineering software like NX CAD, Ansys, and Tableau. Fluent in English and German at B2 level, alongside native proficiency in Hindi.

 

Research Focus :

Specialized in the integration of Finite Element Analysis (FEA) simulation data with deep learning for predictive modeling. Research includes advanced deep learning models, such as CNNs and RNNs, and generative forecasting with VQ-VAE. Emphasis on machine learning algorithms for materials inspection and automated data collection.

 

🔬Awards:

Awarded various certifications, including specialization in self-driving car technologies from the University of Toronto and advanced machine learning courses from DeepLearning.AI. Actively involved in technical leadership roles, such as Technical Coordinator for AMU’s national college fest and team leader for the American Society of Mechanical Engineers (ASME). Published work in Springer Publications on ergonomics for productivity improvement.

Conclusion:

Mr. Zubair Akhtar Mohd’s interdisciplinary skills, innovative research focus, and dedication to academia make him a deserving candidate for the Best Researcher Award. With potential to expand his publication record and increase his collaborative efforts, Mr. Mohd’s career trajectory reflects both current excellence and promise for further significant contributions to engineering and AI research.

 Publications:

Mahmoud Marhamati |Artificial | Best Researcher Award

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Mr.Mahmoud Marhamati |Artificial | Best Researcher Award

Mr. Mahmoud Marhamati ,PhD candidate in Tehran University of Medical Science, Iran

Mr. Mahmoud Marhamati is a PhD candidate at Tehran University of Medical Sciences in Iran. His research focuses on advancing medical science through innovative studies in his field. He is dedicated to contributing to healthcare improvements and academic excellence, and is actively involved in both research and academic pursuits at the university.

Summary:

Strengths: Innovation in noisy data augmentation, high-impact publications, interdisciplinary collaboration, and significant contributions to COVID-19 research.,Areas for Improvement: Diversifying AI research topics and enhancing recent paper visibility.

Professional Profiles:

Google Scholar

🎓 Education :

M. Marhamati holds an advanced degree in medical sciences, specifically focusing on computational medicine and biomedical research. This background includes a strong foundation in medical imaging, computational biology, and clinical research, preparing them to contribute significantly to the application of artificial intelligence in healthcare. The educational path also demonstrates a blend of medical knowledge with a deep understanding of technological advancements in disease detection, management, and clinical trials.

🏢 Experience:

M. Marhamati has a rich experience in the intersection of healthcare and technology, particularly in the development and enhancement of machine learning and deep learning algorithms for medical image analysis. Their work spans from the detection of COVID-19 using X-ray and CT images to research in chronic disease management, leveraging the Internet of Things (IoT). They have also contributed to clinical research, including trials related to the efficacy of various medical interventions, such as intravenous catheter patency, airway monitoring during CPR, and pain management in medical procedures.

🛠️Skills:

Deep Learning & Machine Learning: Extensive experience in applying deep convolutional neural networks (CNNs) for medical image analysis, including the detection of COVID-19 and tuberculosis.,Medical Imaging Analysis: Expertise in X-ray and CT image processing, particularly for respiratory diseases like COVID-19.,Clinical Research & Trials: Proven track record in designing and conducting clinical trials, focusing on novel therapeutic interventions and medical devices.,Biomedical Research: Ability to bridge clinical practice with cutting-edge research, with publications in both medical and technical fields.,Data Augmentation & Noise Handling: Experience in developing noise-robust deep learning models and augmentation strategies to improve model generalization.,Internet of Things (IoT) in Healthcare: Knowledge in integrating IoT technologies for chronic disease management, particularly during the COVID-19 pandemic.

🔬Awards:

Throughout their career, M. Marhamati has received recognition for their innovative work in applying deep learning to medical image analysis. Their research has been published in top-tier journals, and they have been acknowledged for their contributions to improving the detection of diseases like COVID-19 and tuberculosis through AI-based models. Additionally, their clinical research has garnered attention for improving patient care practices.

Research Focus:

M. Marhamati’s research is primarily focused on the application of deep learning and AI in medical imaging and healthcare. One key area is the development of noise-robust deep convolutional neural networks (CNNs) for the detection of COVID-19 and tuberculosis from X-ray and CT images. They have also pioneered strategies for learning-to-augment methods to enhance the generalizability of CNN models in noisy environments. Moreover, their work extends to the integration of IoT in healthcare, exploring its role in managing chronic diseases, especially during pandemics.

Conclusion:

Mr. Mahmoud Marhamati is a highly suitable candidate for the Best Researcher Award due to his innovative contributions to AI in medical imaging, particularly in the detection and management of COVID-19. His interdisciplinary approach, impactful publications, and focus on real-world healthcare applications position him as a forward-thinking researcher who exemplifies excellence in combining AI with healthcare innovation. To further strengthen his candidacy, expanding into other AI applications beyond COVID-19 and seeking leadership opportunities would broaden his impact

Publications :

  • Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images
    • Authors: M. Momeny, A.A. Neshat, M.A. Hussain, S. Kia, M. Marhamati, et al.
    • Journal: Computers in Biology and Medicine
    • Year: 2021
    • Citations: 67

 

  • Learning-to-augment incorporated noise-robust deep CNN for detection of COVID-19 in noisy X-ray images
    • Authors: A. Akbarimajd, N. Hoertel, M.A. Hussain, A.A. Neshat, M. Marhamati, et al.
    • Journal: Journal of Computational Science
    • Year: 2022
    • Citations: 36

 

  • Greedy Autoaugment for classification of mycobacterium tuberculosis image via generalized deep CNN using mixed pooling based on minimum square rough entropy
    • Authors: M. Momeny, A.A. Neshat, A. Gholizadeh, A. Jafarnezhad, E. Rahmanzadeh, et al.
    • Journal: Computers in Biology and Medicine
    • Year: 2022
    • Citations: 32

 

  • Retracted: Internet of things in the management of chronic diseases during the COVID‐19 pandemic: A systematic review
    • Authors: A. Shamsabadi, Z. Pashaei, A. Karimi, P. Mirzapour, K. Qaderi, M. Marhamati, et al.
    • Journal: Health Science Reports
    • Year: 2022
    • Citations: 27

 

  • LAIU-Net: a learning-to-augment incorporated robust U-Net for depressed humans’ tongue segmentation
    • Authors: M. Marhamati, A.A.L. Zadeh, M.M. Fard, M.A. Hussain, K. Jafarnezhad, et al.
    • Journal: Displays
    • Year: 2023
    • Citations: 18

 

  • Active deep learning from a noisy teacher for semi-supervised 3D image segmentation: Application to COVID-19 pneumonia infection in CT
    • Authors: M.A. Hussain, Z. Mirikharaji, M. Momeny, M. Marhamati, A.A. Neshat, R. Garbi, et al.
    • Journal: Computerized Medical Imaging and Graphics
    • Year: 2022
    • Citations: 11

 

  • Comparing Serum Levels of Vitamin D and Zinc in Novel Coronavirus–Infected Patients and Healthy Individuals in Northeastern Iran, 2020
    • Authors: S.J. Hosseini, B. Moradi, M. Marhamati, A.A. Firouzian, E. Ildarabadi, A. Abedi, et al.
    • Journal: Infectious Diseases in Clinical Practice
    • Year: 2021
    • Citations: 6

 

  • Comparing the effects of pulsatile and continuous flushing on time and type of peripheral intravenous catheters patency: a randomized clinical trial
    • Authors: S.J. Hosseini, F. Eidy, M. Kianmehr, A.A. Firouzian, F. Hajiabadi, M. Marhamati, et al.
    • Journal: Journal of Caring Sciences
    • Year: 2021
    • Citations: 4

 

  • Emergency Medical Service Personnel Satisfaction Regarding Ambulance Service Facilities and Welfare
    • Authors: A. Jesmi, H.M. Ziyarat, M. Marhamati, T. Mollaei, H. Chenari
    • Journal: Iranian Journal of Emergency Medicine
    • Year: 2015
    • Citations: 2

 

  • Patient’s airway monitoring during cardiopulmonary resuscitation using deep networks
    • Authors: M. Marhamati, B. Dorry, S. Imannezhad, M.A. Hussain, A.A. Neshat, et al.
    • Journal: Medical Engineering & Physics
    • Year: 2024
    • Citations: 1

 

  • Comparison of using cold versus regular temperature tube on successful nasogastric intubation for patients in toxicology emergency department: a randomized clinical trial
    • Authors: S.R. Mazlom, A.A. Firouzian, H.M. Norozi, A.G. Toussi, M. Marhamati
    • Journal: Journal of Caring Sciences
    • Year: 2020
    • Citations: 1

 

  • Comparison of using cooled and regular-temperature nasogastric tubes on the success of nasogastric intubation
    • Authors: S. Mazlom, M. Marhamati, H. Norozi, A. Ghasemi Toosi
    • Journal: Evidence Based Care
    • Year: 2015
    • Citations: 1

 

 

MD. HUMAUN KABIR | Machine Learning| Best Researcher Award

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Mr.MD. HUMAUN KABIR | Machine Learning| Best Researcher Award

Mr , MD. HUMAUN KABIR, Department of Computer Science and Engineering, Bangamata Sheikh Fojilatunnesa Mujib Science & Technology University,Bangladesh.

Mr. MD. Humaun Kabir is a distinguished faculty member in the Department of Computer Science and Engineering at Bangamata Sheikh Fojilatunnesa Mujib Science & Technology University, Bangladesh. He is dedicated to advancing computer science education and research, with a focus on cutting-edge technologies and innovations that drive the field forward. Through his commitment to academic excellence, Mr. Kabir continues to inspire and mentor the next generation of engineers and computer scientists.

Summary:

  • Achieved a high CGPA in both M.Sc. (3.88) and B.Sc. (3.82) in Engineering, indicating strong academic performance.
  • Consistently strong performance throughout academic life, with excellent results in HSC and SSC.

Professional Profiles:

Google Scholar

Education :

Md. Humaun Kabir completed his M.Sc. in Engineering with a specialization in Applied Physics and Electronic Engineering from the University of Rajshahi in 2015, earning an impressive CGPA of 3.88 on a 4.00 scale. He also holds a B.Sc. in Engineering from the same department, achieved in 2014, with a CGPA of 3.82 on a 4.00 scale. Prior to his university education, he excelled in his secondary and higher secondary studies, achieving a GPA of 5.00 in HSC from Police Line’s School & College, Kushtia (Jashore Board) in 2010, and a GPA of 4.94 in SSC from Patachora Secondary School, Chuadanga (Jashore Board) in 2008. Notably, on December 24, 2018, the Department of Applied Physics and Electronic Engineering was renamed to the Department of Electrical and Electronic Engineering.

Work Experience:

With a professional career spanning around seven years, Md. Humaun Kabir has served in multiple academic roles. He began as a Lecturer in the Department of Computer Science and Engineering at Pundra University of Science & Technology, Bogura, where he worked from May 23, 2017, to February 9, 2019. He then continued as a Lecturer at Bangamata Sheikh Fojilatunnesa Mujib Science & Technology University (BSFMSTU), Jamalpur, from February 10, 2019, to February 19, 2022. He was promoted to Assistant Professor at the same institution on February 20, 2022, and later took on the additional role of Chairman of the Department of Computer Science and Engineering on April 9, 2022. Additionally, he holds the position of Additional Director (In-charge) of the ICT Cell at BSFMSTU, where he has been serving since April 12, 2022.

Research Focus :

Md. Humaun Kabir’s research interests encompass a broad spectrum of topics, including Signal/Image Processing, Computer Vision, Brain-Computer Interfaces (BCI), Human-Computer Interaction (HCI), and Biomedical Engineering. He is also passionate about Wireless Communication & Networks, and his work extends into the realms of Machine Learning & Deep Learning. His research endeavors have led to several significant contributions to the field, with a focus on enhancing performance in BCI systems and improving wireless communication systems.

Skills:

Throughout his career, Md. Humaun Kabir has developed a robust technical skillset. He is proficient in programming languages such as MATLAB, Python, C, and C++, and has expertise in using LaTeX and Overleaf for academic writing. His technical repertoire is further enriched by his experience with the Internet of Things (IoT) and embedded systems, as well as networking knowledge gained through Cisco Certified Network Associate (CCNA) training.

 Awards:

Md. Humaun Kabir has been recognized for his outstanding academic and professional achievements. He received the prestigious Dean’s Award during both his B.Sc. and M.Sc. Engineering programs from the Faculty of Engineering at the University of Rajshahi. Additionally, he was awarded a Merit Scholarship from the University of Rajshahi for his academic excellence. His research excellence has been further acknowledged through his involvement in various government and university-funded research projects, including a current project on EEG-based motor imagery tasks classification for BCI systems.

Conclusion:

Md. Humaun Kabir demonstrates strong potential as a researcher, with a solid academic foundation, relevant research interests, and considerable teaching and administrative experience. However, to strengthen his candidacy for the Best Researcher Award, it would be beneficial to have a more robust record of research publications, greater international collaboration, and evidence of securing research funding. Addressing these areas could make him a more competitive candidate for the award.

Publications :

  • Title: Strain-driven optical, electronic, and mechanical properties of inorganic halide perovskite CsGeBr3
    Authors: MR Islam, MRH Mojumder, R Moshwan, ASMJ Islam, MA Islam
    Source: ECS Journal of Solid State Science and Technology, 11(3), 033001
    Year: 2022
    Citations: 42

 

  • Title: Investigating feature selection techniques to enhance the performance of EEG-based motor imagery tasks classification
    Authors: MH Kabir, S Mahmood, A Al Shiam, AS Musa Miah, J Shin, MKI Molla
    Source: Mathematics, 11(8), 1921
    Year: 2023
    Citations: 21

 

  • Title: Design of Rectangular Microstrip Patch Antenna at 3.3 GHz Frequency for S-band Applications
    Authors: MI Hossain, MT Ahmed, MH Kabir
    Source: International Journal of Engineering and Manufacturing, 12(4), 46-52
    Year: 2022
    Citations: 10

 

  • Title: Smart attendance and leave management system using fingerprint recognition for students and employees in academic institute
    Authors: MH Kabir, S Roy, MT Ahmed, M Alam
    Source: International Journal of Scientific & Technology Research, 10(6), 268-276
    Year: 2021
    Citations: 10

 

  • Title: IoT based solar powered smart waste management system with real-time monitoring – An advancement for smart city planning
    Authors: MH Kabir, S Roy, MT Ahmed, M Alam
    Source: Global Journal of Computer Science and Technology, 20(5), 11-20
    Year: 2020
    Citations: 9

 

  • Title: Gender Recognition of Bangla Names Using Deep Learning Approaches
    Authors: MH Kabir, F Ahmad, MAM Hasan, J Shin
    Source: Applied Sciences, 13(1), 522
    Year: 2022
    Citations: 7

 

  • Title: Secured voice frequency signal transmission in 5G compatible multiuser downlink MIMO NOMA wireless communication system
    Authors: MH Kabir, J Rahman, SE Ullah
    Source: International Journal of Networks and Communications, 8(4), 97-105
    Year: 2018
    Citations: 6

 

  • Title: A neural attention-based encoder-decoder approach for English to Bangla translation
    Authors: AA Shiam, SM Redwan, MH Kabir, J Shin
    Source: Computer Science Journal of Moldova, 91(1), 70-85
    Year: 2023
    Citations: 5

 

  • Title: Web-based student registration and exam form fill-up management system for educational institutes
    Authors: MT Ahmed, MH Kabir, S Roy
    Source: International Journal of Information Engineering and Electronic Business
    Year: 2022
    Citations: 5

 

  • Title: Design and implementation of web-based smart class routine management system for educational institutes
    Authors: S Roy, MH Kabir, MT Ahmed
    Source: International Journal of Educational Management Engineering, 12(2), 38-48
    Year: 2022
    Citations: 4

 

  • Title: A Methodological and Structural Review of Hand Gesture Recognition Across Diverse Data Modalities
    Authors: J Shin, ASM Miah, MH Kabir, MA Rahim, AA Shiam
    Source: arXiv preprint arXiv:2408.05436
    Year: 2024
    Citations: 1

 

  • Title: Design of a High-Gain 2× 1 Array Antenna for S-Band Applications
    Authors: MI Hossain, MA Islam, MT Ahmed, MH Kabir
    Source: World Journal of Engineering and Technology, 11(2), 293-302
    Year: 2023
    Citations: 1