Daehee Jang | Engineering | Best Researcher Award

Posted on by Phenomenological Research

Best Researcher Award

Daehee Jang —Department of Architectural Engineering, Chungnam National University, South Korea

Daehee Jang
Affiliation Chungnam National University
Country South Korea
Scopus ID 59008285100
Documents 11
Citations 6
h-index 1
Subject Area Architecture Engineering
Event International Phenomenological Research Awards
ORCID 0009-0001-8515-8987

Daehee Jang is a Ph.D. candidate in Architectural Engineering with a specialization in Structural Engineering at Chungnam National University, South Korea. His research focuses on steel structures, modular building systems, steel plate shear walls, seismic engineering, nonlinear finite element analysis, and performance-based seismic design. His academic and professional activities combine structural engineering research, university-level teaching, and practical structural engineering experience.

His doctoral research addresses the structural performance of inserted steel plate shear wall core systems for steel modular structures, reflecting an interest in improving the seismic response and structural efficiency of modular construction. His publication record includes research on embedded steel plate-concrete shear wall systems, modular steel beam-column connections, timber beam-to-column connections, and finite element analysis of modular structural connections.[1][2]

Abstract

Daehee Jang is an emerging structural engineering researcher whose work is centered on the development and evaluation of steel and modular structural systems. As a Ph.D. candidate in Architectural Engineering at Chungnam National University, his doctoral research investigates the structural performance of inserted steel plate shear wall core systems for steel modular structures. His broader research interests include steel plate shear walls, seismic engineering, structural connections, nonlinear finite element analysis using ABAQUS, tension strip modeling, and performance-based seismic design. His academic profile is complemented by teaching appointments at several Korean universities and approximately three years of professional experience as a structural engineer.

Daehee Jang’s publication portfolio covers analytical, numerical, and experimental aspects of structural systems, including embedded steel plate-concrete shear walls and modular steel beam-column connections. His Scopus profile records 11 documents, 6 citations, and an h-index of 1, providing an identifiable bibliometric record for evaluation. [1][2]

Keywords

Structural engineering; architectural engineering; steel structures; modular building systems; steel plate shear walls; SPSWs; seismic engineering; nonlinear finite element analysis; ABAQUS; performance-based seismic design; structural connections; modular steel structures; seismic performance; steel beam-column connections.

Introduction

Modern modular construction requires structural systems capable of combining manufacturing efficiency with adequate strength, stiffness, ductility, and seismic resilience. Steel modular systems and steel plate shear wall technologies therefore represent important areas of structural engineering research. Jang’s academic work is situated within this context, with particular attention to structural behavior, connection performance, and analytical evaluation of innovative steel systems.

His doctoral studies at Chungnam National University focus on the structural performance of inserted steel plate shear wall core systems for steel modular structures. This research direction connects modular construction with established seismic-resisting structural technologies and emphasizes the assessment of structural response under demanding loading conditions.

Research Profile

Jang’s research profile encompasses several interconnected areas of structural engineering. His principal interests include:

  • Steel structures and structural steel design.
  • Modular building systems and modular steel structures.
  • Steel plate shear walls and seismic-resisting systems.
  • Seismic engineering and performance-based seismic design.
  • Nonlinear finite element analysis using ABAQUS.
  • Tension strip modeling and numerical evaluation of shear wall behavior.
  • Beam-column and modular structural connections.

His educational background includes a Bachelor of Science and Master of Science in Architectural Engineering from Chungnam National University, followed by doctoral study in Architectural Engineering with a Structural Engineering specialization. His Ph.D. research is expected to be completed in February 2027.

In addition to research, Jang has served as a lecturer at Hannam University, Chungnam National University, Daejeon University, and Kyung Hee Cyber University. His teaching responsibilities have included steel structures, steel structure design, engineering mathematics, structural mechanics, and reinforced concrete and steel structures.[1][2]

Research Contributions

Daehee Jang’s research contributions are primarily associated with the analysis and evaluation of structural systems intended to improve the performance of steel and modular buildings. His work on embedded steel plate-concrete shear wall systems examines analytical characteristics relevant to the behavior of hybrid structural wall systems. [3]

His research on modular steel beam-column connections addresses seismic behavior and connection configurations incorporating H-shaped brackets. Such research is relevant to the structural continuity and seismic performance of modular steel construction, where connection behavior is a significant component of overall structural response. [4]

Additional research examines failure modes and stiffness evaluation of timber beam-to-column connections through case studies, broadening the scope of his structural connection research beyond steel-only systems. [5]

His research experience also includes nonlinear finite element modeling using ABAQUS, tension strip modeling, seismic performance evaluation, innovative modular core systems, and beam-column connection behavior. These methods provide a computational and analytical foundation for evaluating structural response under nonlinear loading conditions.

Publications

Daehee Jang’s publications examine embedded steel plate-concrete shear walls, modular steel beam-column connections, and structural connection behavior, combining finite element analysis with seismic performance evaluation. His 2025 ESPC study identifies key effects of plate thickness, stud spacing, and aspect ratio. [3] [4][5]

The supplied publication record indicates four SCI journal papers, two Scopus-indexed papers, and one KCI journal paper. The following selected publications illustrate the principal themes of Jang’s research:

  1. Jang, D., & Lee, K. (2025). Analytical study of embedded steel plate-concrete (ESPC) shear wall system. Steel and Composite Structures, 56(3), 247–?. [3]
  2. Jang, D., Kim, Y., Kim, E., & Lee, K. (2025). Seismic behavior of modular steel beam-column connection with H-shaped bracket. Journal of Constructional Steel Research, 109774. [4]
  3. Jang, D., Kim, Y., Oh, K., Shin, D.-H., Park, K.-S., & Lee, K. (2025). Failure modes and stiffness evaluation of timber beam-to-column connections using case studies. Journal of the Architectural Institute of Korea, 41(5), 251–?. [5]
  4. Jang, D., & Lee, K. (2024). Finite element analysis of beam-to-column connection in modular system considering panel zone strength and bracket shape.

Research Impact

Daehee Jang’s research addresses structural challenges associated with modular construction and seismic-resistant structural systems. The combination of modular steel construction, steel plate shear walls, structural connections, and nonlinear numerical analysis provides a coherent research direction focused on understanding and improving structural performance.

His Scopus record currently contains 11 documents, 6 citations, and an h-index of 1. [1] These metrics represent an early-stage research profile and should be interpreted in the context of his ongoing doctoral education and developing publication record. His publication activity in SCI, Scopus-indexed, and KCI journals demonstrates continuing engagement with scholarly structural engineering research.

The relevance of his work is further supported by research addressing modular connection seismic behavior and analytical evaluation of steel plate-concrete shear wall systems. [3] [4]

Award Suitability

For consideration for the Best Researcher Award, Daehee Jang presents a developing academic profile characterized by a focused specialization in structural and architectural engineering. His doctoral research addresses a technically relevant problem in modular steel construction, while his publication record demonstrates engagement with structural wall systems, modular connections, and numerical structural analysis.

Key factors supporting his suitability include:

  • A clearly defined research specialization in steel and modular structural systems.
  • Doctoral research focused on inserted steel plate shear wall core systems for steel modular structures.
  • Research experience involving nonlinear finite element analysis and seismic performance evaluation.
  • Peer-reviewed publication activity across SCI, Scopus-indexed, and KCI outlets.
  • Academic teaching experience across structural engineering and related engineering subjects.
  • Professional structural engineering experience complementing his academic research.

Taken together, these elements indicate an emerging researcher with a specialized research agenda and a combination of academic, computational, teaching, and professional structural engineering experience. The award assessment should consider the full body of submitted evidence, including publications, research originality, methodological contributions, and demonstrated influence within the field.[1][2]

Conclusion

Daehee Jang is an emerging structural engineering researcher affiliated with Chungnam National University whose work concentrates on steel structures, modular construction, steel plate shear walls, structural connections, and seismic performance. His doctoral research on inserted steel plate shear wall core systems for steel modular structures represents a focused contribution to the study of resilient modular structural systems.

His combination of research publications, finite element analysis expertise, academic teaching, and professional structural engineering experience provides a multidisciplinary foundation for continued development as a structural engineering researcher. His current Scopus record and publication portfolio indicate an early but active research trajectory, with potential for further contributions as his doctoral research and subsequent scholarly work progress.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Daehee Jang, Author ID 59008285100. Scopus. https://www.scopus.com/authid/detail.uri?authorId=59008285100
  2. ORCID. (n.d.). Daehee Jang, ORCID 0009-0001-8515-8987. ORCID. https://orcid.org/0009-0001-8515-8987
  3. Jang, D., & Lee, K. (2025). Analytical study of embedded steel plate-concrete (ESPC) shear wall system. Steel and Composite Structures, 56(3), 247–?. DOI: https://doi.org/10.12989/SCS.2025.56.3.247
  4. Jang, D., Kim, Y., Kim, E., & Lee, K. (2025). Seismic behavior of modular steel beam-column connection with H-shaped bracket. Journal of Constructional Steel Research, 109774. DOI: https://doi.org/10.1016/j.jcsr.2025.109774
  5. Jang, D., Kim, Y., Oh, K., Shin, D.-H., Park, K.-S., & Lee, K. (2025). Failure modes and stiffness evaluation of timber beam-to-column connections using case studies. Journal of the Architectural Institute of Korea, 41(5), 251–?. DOI: https://doi.org/10.5659/JAIK.2025.41.5.251
  6. Related publication: Jang, D., & Lee, K. (2024). Finite element analysis of beam-to-column connection in modular system considering panel zone strength and bracket shape.

Shailendra Sinha | Engineering | Editorial Board Member

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Dr. Shailendra Sinha | Engineering | Editorial Board Member 

Professor at Institute of Engineering and Technology  | India

Dr. Shailendra Sinha is a distinguished academic and researcher at the Institute of Engineering and Technology (IET), Lucknow, India, recognized for his strong contributions to engineering education, applied research, and the advancement of computer science. Known for his dedication to academic excellence, he combines deep theoretical understanding with practical technological innovation, consistently striving to enhance learning outcomes and foster technical leadership. Dr. Sinha has built a solid educational foundation in computer science and engineering, complemented by progressive teaching and research experience that reflects his commitment to intellectual growth and innovation. His academic journey includes advanced studies and extensive engagement with evolving computational paradigms, enabling him to contribute meaningfully to curriculum development, student mentorship, and interdisciplinary collaboration. Over the course of his career, Dr. Sinha has produced impactful research, evidenced by 1,405 citations across 1,271 documents, 53 published works, and an h-index of 15, highlighting the relevance and influence of his scholarly contributions. His research interests span emerging technologies, data-driven systems, computational intelligence, and innovative engineering methodologies aimed at addressing contemporary challenges in the digital landscape. He consistently integrates modern research insights into classroom instruction, bridging the gap between theory and application, and preparing students for the demands of rapidly advancing technological environments. Dr. Sinha has participated in numerous academic initiatives and collaborative projects, demonstrating his commitment to expanding the boundaries of knowledge and promoting technical excellence. He remains actively engaged in guiding students, contributing to academic committees, and supporting the development of engineering education through research-driven strategies. As a respected member of the engineering community, Dr. Shailendra Sinha continues to uphold high standards of scholarship, innovation, and professional integrity, striving to create meaningful impact through his research, teaching, and collaborative endeavors while nurturing the next generation of engineers and fostering a culture of inquiry and advancement within the academic ecosystem.

Profile: Scopus | Orcid 

Featured Publications:

  • Yadav, A. K., & Sinha, S. (2024). Techno-economic and environmental analysis of a hybrid power system formed from solid oxide fuel cell, gas turbine, and organic Rankine cycle. Journal of Energy Resources Technology, Transactions of the ASME, 146(7), 1–11.

  • Yadav, A. K., & Sinha, S. (2024). Advancements in composite cathodes for intermediate-temperature solid oxide fuel cells: A comprehensive review. International Journal of Hydrogen Energy, 59, 1080–1093.

  • Yadav, A. K., Kumar, A., & Sinha, S. (2023). Comprehensive review on performance assessment of solid oxide fuel cell-based hybrid power generation systems. Thermal Science and Engineering Progress, 46, 102226.

  • Verma, S. K., Dubey, V., & Sinha, S. (2021). A review on additive mixed electrical discharge machining processes. Materials Today: Proceedings, 709–715.

  • Singh, A., & Sinha, S. (2021). Optimization of operating parameters of diesel engine powered with Jatropha oil diesel blend by employing response surface methodology. International Journal of Renewable Energy Research, 504–513.

  • Nigam, A. P., & Sinha, S. (2020). Techniques to control IC engine exhaust emissions through modification in fuel and intake air – A review. Journal of Ambient Energy.

  • Singh, A., & Sinha, S. (2020). Optimization of performance and emission characteristics of CI engine fueled with Jatropha biodiesel produced using a heterogeneous catalyst (CaO). Fuel.

  • Agrawal, B. N., & Sinha, S. (2019). Effect of vegetable oil share on combustion characteristics and thermal efficiency of diesel engine fueled with different blends. Thermal Science and Engineering Progress, 14, 100404.

  • Sinha, S., & Agarwal, A. K. (2007). Experimental investigation of the performance and emission characteristics of direct injection medium duty transport diesel engine using Rice-bran oil biodiesel. In ASME Internal Combustion Engine Division Fall Technical Conference.

  • Sinha, S., & Agarwal, A. K. (2006). Combustion characteristics of Rice bran oil derived biodiesel in a transportation diesel engine. In Proceedings of ICES 2006, ASME I.C. Engine Division Spring Technical Conference

Yuezhao Pang | Engineering | Best Researcher Award

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Dr. Yuezhao Pang | Engineering | Best Researcher Award 

Engineer at Marine Design and Research Institute of China | China

Dr. Yuezhao Pang is a highly accomplished structural engineer at the Marine Design and Research Institute of China with a Ph.D. in Mechanics, whose expertise centers on impact dynamics, composite materials, and the development of advanced metal and non-metallic sandwich structures. His academic foundation and research journey reflect a commitment to understanding mechanical responses, energy absorption, and failure mechanisms under impact loading, combining both multi-scale experimentation and numerical simulations to address complex engineering problems. Professionally, he has completed five major research projects, engaged in three consultancy and industry-linked initiatives, and contributed significantly to the field through innovative solutions aimed at structural protection and crashworthiness, with applications in aerospace, transportation, and industrial safety. His research interests extend to dynamic and static compression of closed-cell PVC foams, exploring material properties under varying strain rates to design lightweight protective structures with improved resilience. Dr. Yuezhao Pang has produced a notable body of work with 17 publications indexed in reputed databases, amassing 139 citations by 136 documents with an h-index of 7, reflecting the quality and relevance of his research contributions. In addition, he has secured five patents that bridge the gap between theoretical advancements and practical applications, underscoring his strength in innovation-driven engineering. His research skills encompass advanced materials testing, computational modeling, mechanical characterization, and cross-disciplinary collaborations, making him a versatile and impactful researcher. While he has not yet accumulated extensive professional memberships, his strong collaborations and project outputs demonstrate leadership potential and dedication to advancing the field. Recognized for his significant contributions, Dr. Yuezhao Pang stands as a deserving recipient of research honors, and his future trajectory indicates immense promise in expanding global collaborations, enhancing high-impact publications, and shaping protective engineering solutions that benefit both academia and industry.

Profile: Scopus

Fuetured Publications:

  • Pang, Y., Wang, C., Zhao, Y., & Wang, X. (2025). Strain‐Rate Effects on the Mechanical Behavior of Basalt-Fiber-Reinforced Polymer Composites: Experimental Investigation and Numerical Validation. Materials, 18(15).

  • Pang, Y. (2022). Experimental study of basalt fiber/steel hybrid laminates: Low‐velocity impact characteristics with different lay-up structures. International Journal of Impact Engineering.

Jamal Raiyn | Engineering | Best Researcher Award

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Prof. Dr. Jamal Raiyn | Engineering | Best Researcher Award

Researcher at Technical University of Applied Sciences Aschaffenburg Sciences, Aschaffenburg, Germany.

Dr. Jamal Raiyn is a distinguished researcher in applied computer science, recognized for his innovative contributions to autonomous systems, cybersecurity, and urban livability. With a focus on using computational intelligence to solve real-world challenges, his work spans diverse areas such as vehicle safety, data science, and natural product bioactivity. Dr. Raiyn has an extensive publication record, including high-impact journals like Smart Cities and PLoS ONE. His research integrates interdisciplinary approaches, bridging technology with societal needs. Notably, his work on data-driven anomaly detection and computational methods for vehicle networks has garnered global recognition. Dr. Raiyn’s passion for collaborative research and impactful problem-solving continues to define his professional journey.

Professional Profile:

Education

Dr. Raiyn holds advanced degrees in computer science, specializing in applied computational techniques. His academic foundation equips him with a robust understanding of data systems, artificial intelligence, and cybersecurity. Details about the institutions he attended and specific degrees earned could further solidify his academic credentials in this profile.

Professional Experience

Dr. Raiyn has extensive experience as a researcher and academic, contributing significantly to both theoretical advancements and practical applications in his field. Over the years, he has collaborated with various organizations and universities, leading projects that focus on enhancing safety, livability, and efficiency in urban and technological systems.

Research Interests

Dr. Raiyn’s primary research interests include computational intelligence, autonomous systems, vehicular networks, and cybersecurity. His work frequently explores interdisciplinary domains, such as integrating AI into naturalistic driving studies, predicting autonomous driving behaviors, and advancing maritime cybersecurity. These interests demonstrate a commitment to addressing contemporary challenges in technology and society.

Research Skills

Dr. Raiyn’s skills encompass advanced data analysis, machine learning, cybersecurity modeling, and system optimization. His expertise in computational intelligence allows him to solve complex, multi-dimensional problems. Proficiency in handling diverse data sets and developing predictive models has been pivotal in his impactful research contributions.

Awards and Honors

Dr. Raiyn’s research excellence has earned him multiple accolades, including recognition for his papers in the “Top 10 Must-Read Data Science Research Papers in 2022.” His highly cited works in applied sciences highlight his contributions to global knowledge. Awards for impactful publications and invited talks further reflect his standing in the academic community.

Conclusion

Dr. Jamal Raiyn’s impressive career in applied computer science exemplifies excellence in research, innovation, and societal impact. His ability to tackle pressing global issues through advanced computational techniques positions him as a leader in his field. With continued dedication to high-quality research and collaboration, Dr. Raiyn is well-deserving of recognition and accolades, including the Best Researcher Award.

Publication Top Notes

  1. Improving the Perception of Objects Under Daylight Foggy Conditions in the Surrounding Environment
    • Authors: Chaar, M.M., Raiyn, J., Weidl, G.
    • Year: 2024
  2. From Sequence to Solution: Intelligent Learning Engine Optimization in Drug Discovery and Protein Analysis
    • Authors: Raiyn, J., Rayan, A., Abu-Lafi, S., Rayan, A.
    • Year: 2024
  3. Predicting Autonomous Driving Behavior through Human Factor Considerations in Safety-Critical Events
    • Authors: Raiyn, J., Weidl, G.
    • Year: 2024
    • Citations: 1
  4. Analysis of Driving Behavior in Adverse Weather Conditions
    • Authors: Raiyn, J., Chaar, M.M., Weidl, G.
    • Year: 2024
  5. Improve Bounding Box in Carla Simulator
    • Authors: Chaar, M.M., Raiyn, J., Weidl, G.
    • Year: 2024
    • Citations: 1
  6. Improving Autonomous Vehicle Reasoning with Non-Monotonic Logic: Advancing Safety and Performance in Complex Environments
    • Authors: Raiyn, J., Weidl, G.
    • Year: 2023
    • Citations: 1
  7. Naturalistic Driving Studies Data Analysis Based on a Convolutional Neural Network
    • Authors: Raiyn, J., Weidl, G.
    • Year: 2023
    • Citations: 4
  8. Detection of Road Traffic Anomalies Based on Computational Data Science
    • Authors: Raiyn, J.
    • Year: 2022
    • Citations: 4
  9. Road Traffic Anomaly Detection Based on Deep Learning Technology
    • Authors: Raiyn, J.
    • Year: 2021
    • Citations: 1
  10. Classification of Road Traffic Anomaly Based on Travel Data Analysis
    • Authors: Raiyn, J.
    • Year: 2021
    • Citations: 6

Rajeevan Arunthavanathan | Engineering | Best Researcher Award

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Dr. Rajeevan Arunthavanathan | Engineering | Best Researcher Award

Postdoctoral Researcher at Texas A&M University, United States.

🌍Dr. Rajeevan Arunthavanathan is a distinguished researcher and educator specializing in AI safety, process safety, and ICS cybersecurity. With a Ph.D. in Process Engineering and over a decade of academic and industrial experience, he has developed groundbreaking methods for risk evaluation and safety in critical infrastructures. His prolific publication record includes high-impact journals and book chapters on AI-human conflict, machine learning applications, and process fault diagnosis. Dr. Arunthavanathan has contributed significantly to curriculum development, student mentorship, and project management in academia and industry, positioning himself as a leader in the intersection of AI and process safety.

Profile👤

Education 🎓

🎓Dr. Arunthavanathan completed his Ph.D. in Process Engineering at Memorial University, Canada, in 2022, focusing on AI-driven fault diagnosis in process systems. He earned his MSc in Microelectronics and Communication from Northumbria University, UK, in 2010, graduating with distinction, and a B.Eng. in Electrical and Electronics Engineering from the same institution in 2007. His academic mentors included renowned professors, under whom he honed expertise in AI, control systems, and microelectronics. Throughout his education, he demonstrated excellence through research on AI-human interaction and advanced microelectronics, laying the foundation for his impactful career.🧬🎓

Experience💼

🩺Dr. Arunthavanathan has extensive experience in academia and industry. At Texas A&M University, he researches AI safety and mentors graduate students. Previously, at C-CORE, Canada, he developed ML models for data noise cleaning and smart ice management. He served as a senior lecturer at SLIIT, Sri Lanka, revising engineering curricula to meet international accreditation standards. His industrial experience includes work as a trainee engineer at Perry Slingsby Systems, UK, where he contributed to advanced underwater surveillance systems. His teaching spans multiple institutions, offering courses in process safety, microelectronics, and programming, blending theory with practical applications.👨‍🔬🌍

Research Interests 🔬

🔬Dr. Arunthavanathan’s research lies at the nexus of AI safety, process safety, and industrial control systems (ICS) cybersecurity. He develops innovative models to evaluate AI efficiency and mitigate risks in human-AI collaboration. His work on fault diagnosis, risk assessment, and operational technology cybersecurity addresses pressing challenges in critical infrastructure. His focus extends to integrating machine learning for noise cleaning in data systems and applying AI in Industry 4.0 technologies. With a commitment to enhancing process safety and addressing cyber threats, his research bridges theoretical advancements with practical applications for safer industrial operations. 🌿🧪

Awards and Honors 🏆

🏆Dr. Arunthavanathan has received numerous accolades, including being named a Fellow of the School of Graduate Studies at Memorial University (2022). His MSc degree was conferred with distinction by Northumbria University (2010). He serves as an editor for leading journals like Sensors and AI and reviews manuscripts for high-impact publications, including IEEE Access. His professional memberships with IEEE and AIChE reflect his standing in the academic community. These achievements underscore his dedication to advancing AI, process safety, and engineering education through impactful research and professional service. 🏆🎉

Conclusion 🔚 

Dr. Rajeevan Arunthavanathan is a strong contender for the Best Researcher Award, given his impactful contributions to AI safety, process fault diagnosis, and industrial control systems. His expertise, combined with a commitment to education and industry applications, exemplifies the qualities of an outstanding researcher. Recognizing his achievements will inspire further advancements in safety and AI-driven solutions for critical infrastructure.

Publications Top Notes 📚

An analysis of process fault diagnosis methods from safety perspectives

Authors: R. Arunthavanathan, F. Khan, S. Ahmed, S. Imtiaz

Citations: 126

Year: 2021

A deep learning model for process fault prognosis

Authors: R. Arunthavanathan, F. Khan, S. Ahmed, S. Imtiaz

Citations: 120

Year: 2021

Fault detection and diagnosis in process system using artificial intelligence-based cognitive technique

Authors: R. Arunthavanathan, F. Khan, S. Ahmed, S. Imtiaz, R. Rusli

Citations: 76

Year: 2020

Autonomous fault diagnosis and root cause analysis for the processing system using one-class SVM and NN permutation algorithm

Authors: R. Arunthavanathan, F. Khan, S. Ahmed, S. Imtiaz

Citations: 52

Year: 2022

Industry 4.0-based process data analytics platform

Authors: T.R. Wanasinghe, M.G. Don, R. Arunthavanathan, R.G. Gosine

Citations: 10

Year: 2022

Machine Learning for Process Fault Detection and Diagnosis

Authors: R. Arunthavanathan, S. Ahmed, F. Khan, S. Imtiaz

Citations: 9

Year: 2022

Vehicle monitoring controlling and tracking system by using Android application

Authors: A. Rajeevan, N.K. Payagala

Citations: 8

Year: 2016

Artificial intelligence–Human intelligence conflict and its impact on process system safety

Authors: R. Arunthavanathan, Z. Sajid, F. Khan, E. Pistikopoulos

Citations: 7

Year: 2024

Process safety 4.0: Artificial intelligence or intelligence augmentation for safer process operation?

Authors: R. Arunthavanathan, Z. Sajid, M.T. Amin, Y. Tian, F. Khan, E. Pistikopoulos

Citations: 7

Year: 2024

Statistical approaches and artificial neural networks for process monitoring

Authors: M. Alauddin, R. Arunthavanathan, M.T. Amin, F. Khan

Citations: 6

Year: 2022