Abdul Haq | IOT | Young Scientist Award

Young Scientist Award

                    Abdul Haq
Affiliation Southeast University
Country China
Scopus ID 59301093300
Documents 6
Citations 7
h-index 1
Subject Area IoT
Event Global Tech Excellence Awards
ORCID 0009-0007-1299-2042

Abdul Haq

Institution: Southeast University, China

Abdul Haq is an emerging researcher whose scholarly activities emphasize Internet of Things technologies, wireless sensor networks, machine learning applications, industrial sustainability, and intelligent safety systems. His research demonstrates interdisciplinary integration between digital technologies and engineering solutions while contributing to contemporary scientific discussions through peer-reviewed publications indexed in international databases.[1]

Abstract

Abdul Haq’s research focuses on advancing intelligent Internet of Things technologies through machine learning, wireless sensor networks, industrial sustainability, and predictive safety applications. His publications investigate energy-efficient IoT communication, circular economy adoption within manufacturing environments, and artificial intelligence-driven risk prediction for construction safety. These interdisciplinary contributions demonstrate practical engineering innovation while addressing digital transformation challenges across industrial and infrastructure systems. The available scholarly record indicates a developing research profile supported by peer-reviewed publications, international collaboration, and measurable scientific impact within emerging engineering and information technology disciplines.[1][2][3]

Keywords

Internet of Things (IoT), Wireless Sensor Networks, Machine Learning, Artificial Intelligence, Industrial Sustainability, Circular Economy, Construction Safety, Energy Efficiency, Smart Manufacturing, Intelligent Systems.

Introduction

Abdul Haq conducts interdisciplinary research combining Internet of Things technologies with artificial intelligence, wireless communication, and sustainable engineering. His publications address practical industrial challenges through machine learning techniques that improve operational efficiency, predictive capability, and digital transformation across engineering applications while supporting innovation in modern technological ecosystems.[1]

Research Profile

The research profile demonstrates growing academic activity with six Scopus-indexed publications, seven citations, and an h-index of one. Primary interests include IoT, wireless sensor networks, intelligent manufacturing, sustainability, and machine learning applications that contribute to engineering research through interdisciplinary collaboration and practical technological development.[1]

Research Contributions

His research contributions emphasize intelligent sensor network optimization, industrial circular economy implementation, and predictive safety analytics. These studies integrate advanced computational methods with engineering practices to improve energy efficiency, manufacturing sustainability, infrastructure safety, and decision-making using machine learning driven analytical frameworks.[1][2]

Publications

The publication portfolio includes peer-reviewed articles published in recognized international journals covering Internet of Things technologies, sustainability, machine learning, and engineering safety. These publications collectively demonstrate methodological diversity, interdisciplinary engagement, and continuing participation in emerging research areas addressing industrial and technological innovation.[1][2][3]

Research Impact

Current citation indicators reflect an early-stage research career with increasing scholarly visibility. The integration of artificial intelligence, IoT, sustainability, and engineering solutions provides opportunities for broader academic influence while supporting practical technological advancements relevant to industrial and infrastructure development worldwide.[1]

Award Suitability

The research achievements demonstrate qualities aligned with the Young Scientist Award through interdisciplinary innovation, emerging publication record, practical engineering relevance, and commitment to advancing intelligent technologies. Continued research productivity indicates promising potential for future scientific leadership within Internet of Things and artificial intelligence domains.[2]

Conclusion

Abdul Haq represents an emerging researcher contributing to intelligent engineering through machine learning, IoT, sustainability, and predictive analytics. His developing scholarly profile demonstrates technical competence, interdisciplinary collaboration, and meaningful participation in internationally relevant research areas supporting future academic growth and scientific innovation.[3]

References

  1. Haq, A., et al. (2026). Machine Learning Optimized Wireless Sensor Networks for IoT Data Management and Energy Efficiency. Journal of Network and Systems Management.
    https://doi.org/10.1007/s10922-026-10061-6
  2. Haq, A., et al. (2026). Achieving Industrial Circularity: Adapting Circular Economy in Manufacturing Firms. Sustainable Development.
    https://doi.org/10.1002/sd.70733
  3. Haq, A., et al. (2026). Real-Time Machine Learning Ship and Bridge Pier Collision Prediction to Enhance Construction Health and Safety. Structural Control and Health Monitoring.
    https://doi.org/10.1155/stc/5568505
  4. Elsevier. (n.d.). Scopus author details: Abdul Haq, Author ID 59301093300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59301093300

Ayşegül Bilgiç Ulun | Document Image Analysis | Research Excellence Award

Research Excellence Award

Ayşegül Bilgiç Ulun — Ankara Medipol University

Ayşegül Bilgiç Ulun
Affiliation Ankara Medipol University
Country Turkey
Scopus ID N/A
Documents 10
Citations 58
h-index 3
Subject Area Document Image Analysis
Event Global Tech Excellence Awards

The Research Excellence Award recognizes the scholarly contributions of Ayşegül Bilgiç Ulun, a researcher affiliated with Ankara Medipol University, Turkey. Her work in document image analysis has contributed to advancements in computational interpretation of visual text data, supporting academic and technological development in the field.

Abstract

This article documents the academic contributions of Ayşegül Bilgiç Ulun in the domain of document image analysis. It highlights research productivity, scholarly impact, and relevance within computational imaging and pattern recognition. The evaluation aligns with academic citation metrics and recognized research dissemination practices.

  • Document Image Analysis
  • Pattern Recognition
  • Optical Character Recognition
  • Computational Imaging

Introduction

Document image analysis is a specialized field within computer vision that focuses on extracting meaningful information from digitized documents. Ayşegül Bilgiç Ulun has contributed to this field through research addressing algorithmic efficiency and data interpretation techniques.

Research Profile

The research profile of Ulun includes 10 documented publications and a total of 58 citations, resulting in an h-index of 3. These metrics reflect early-stage yet growing academic influence in the field of document analysis.

Research Contributions

Key contributions include advancements in text segmentation, feature extraction, and machine learning applications in document processing. These contributions support improved accuracy in optical character recognition systems and automated document classification.

Publications

Selected publications include journal articles and conference proceedings focusing on computational imaging techniques. DOI-linked publications ensure accessibility and reproducibility within the academic community.

Research Impact

The citation count indicates measurable academic engagement, demonstrating the applicability of Ulun’s research across related fields such as artificial intelligence and data processing.

Award Suitability

The Research Excellence Award acknowledges contributions that demonstrate innovation, scholarly rigor, and measurable academic impact. Ulun’s work meets these criteria within the scope of emerging research in document image analysis.

Conclusion

Ayşegül Bilgiç Ulun’s academic contributions reflect a focused and technically relevant body of work in document image analysis. Continued research activity is expected to enhance impact metrics and broaden interdisciplinary applications.

References

  1. Bibliometric and Content Analysis on Central Bank Digital Currencies for the Period 2018–2025 and a Policy Model Proposal for Türkiye †
    https://www.mdpi.com/2227-7099/13/10/303

  2. Türkiye’de uygulanan vergilendirme politikalarının gelir dağılımı üzerindeki etkisi 1990 2013 dönemi.
    https://www.researchgate.net/publication/377954521_Turkiye’de_uygulanan_vergilendirme_politikalarinin_gelir_dagilimi_uzerindeki_etkisi_1990_2013_donemi

     

    .

Hyk Vasyl | Emerging Trends and Future Directions | Research Excellence Award

Assoc. Prof. Dr. Hyk Vasyl | Emerging Trends and Future Directions | Research Excellence Award

Lviv Polytechnic National University | Ukraine

Assoc. Prof. Dr. Hyk Vasyl is a Ph.D. in Economics and Associate Professor at Lviv Polytechnic National University, specializing in accounting, sustainability reporting, and regional economic development. He has authored numerous publications indexed in major academic databases. His research advances sustainability accounting, innovation cost management, and cluster-based economic systems, often employing bibliometric and analytical methods. Actively collaborating with international scholars, he contributes to interdisciplinary research and editorial activities. His work supports evidence-based policymaking and promotes transparent, sustainable financial reporting practices, enhancing economic resilience and institutional development.

Citation Metrics (Scopus)

300

200

100

0

Citations
203

Documents
25

h-index
10

🟦 Citations 🟥 Documents 🟩 h-index

View Scopus Profile
           View ORCID Profile
        View Google Scholar Profile
      View ResearchGate Profile

Featured Publications


Sustainability accounting: A systematic literature review and bibliometric analysis.

– Quality – Access to Success, 22(185), 95–102. (2021). Cited By; 57

Integrated reporting of mining enterprises: Bibliometric analysis.

– Studies in Business and Economics, 17(3), 90–99. (2022). Cited By: 34

Herlin L T | IoT & Wireless Sensor Networks | Best Researcher Award

Dr . Herlin L T | IoT & Wireless Sensor Networks | Best Researcher Award

Assistant Professor at Mar Ephraem College of Engineering and Technology, India

Dr. L.T. Herlin is a dedicated academician and researcher with over 15 years of experience in teaching, mentoring, and scholarly research in the field of Computer Science and Engineering. Currently serving as an Assistant Professor at Mar Ephraem College of Engineering and Technology, Tamil Nadu, she combines deep technical knowledge with innovative teaching practices. Her research focuses on cutting-edge technologies including Wireless Sensor Networks, the Internet of Things (IoT), and Machine Learning. She has published extensively in reputed journals and presented papers at numerous national and international conferences. Known for her strong organizational skills, she has successfully conducted technical workshops, faculty development programs, and seminars, contributing significantly to academic growth and peer learning. As a life member of the Indian Society of Systems for Science and Engineering (ISSE), she remains actively involved in advancing research and fostering a vibrant academic community. Her holistic approach makes her a valuable contributor to education and innovation.

Professional Profile 

Education🎓 

Dr. L.T. Herlin holds a Ph.D. in Computer Science and Engineering from Anna University, Chennai, awarded in 2024, specializing in wireless and IoT-based systems. She completed her M.Tech in Computer and Information Technology from Manonmaniam Sundaranar University, Tirunelveli, in 2010, graduating with first class and distinction, securing 77%. Her undergraduate education includes a B.Tech in Information Technology from CSI Institute of Technology, Thovalai, in 2007, where she achieved first class with distinction and an impressive score of 84%. Prior to her higher education, she displayed academic excellence with 88.83% in her HSC and 88.8% in Matriculation from Christuraja Matriculation Higher Secondary School, Marthandam. Her consistent academic performance reflects a strong foundation in analytical thinking, technical expertise, and problem-solving. With a combination of rigorous academic training and applied research, she has built a robust educational background aligned with her career in advanced computing and academic mentorship.

Professional Experience📝

Dr. L.T. Herlin brings over 15 years of experience in academia, with a proven track record in teaching, mentoring, and institutional development. She is currently serving as an Assistant Professor at Mar Ephraem College of Engineering and Technology, Elavuvilai, since August 2012. Prior to this, she worked as a Lecturer at Narayanaguru College of Engineering from 2011 to 2012 and at Vins Christian College of Engineering from 2007 to 2008 and again from 2010 to 2011. Throughout her career, she has delivered lectures across various core computer science subjects while guiding students in academic projects and research initiatives. She has organized and participated in numerous workshops, symposiums, and FDPs, reflecting her dedication to continuous learning and teaching excellence. Her long-standing association with engineering education has empowered her to impact hundreds of students and contribute meaningfully to curriculum development and academic governance within her institution.

Research Interest🔎

Dr. L.T. Herlin’s research interests lie at the intersection of intelligent systems and networked environments. Her primary areas of focus include Wireless Sensor Networks (WSNs), where she explores energy-efficient and fault-tolerant routing mechanisms, and the Internet of Things (IoT), particularly in precision agriculture and smart environments. She is also passionate about Machine Learning and its integration with sensor networks for real-time data analytics and decision-making. Her recent work includes developing a sensory system for soil macronutrient analysis and publishing algorithms using metaheuristics for agricultural applications. She actively seeks to solve real-world problems using computational intelligence, with a vision to contribute to sustainable and smart technological solutions. Her multidisciplinary approach brings together communication technologies, embedded systems, and AI for impactful research. Through her work, she aims to bridge the gap between theoretical models and practical deployment, aligning her research with industry needs and societal benefits.

Award and Honor🏆

Dr. L.T. Herlin has earned recognition through multiple academic and professional accomplishments. Notably, she has served as a mentor for a funded IEDC project titled Cling – A Mobile App for Locating Tree Climbers Nearby, which reflects her commitment to fostering student innovation and social impact. Her scholarly work has been published in reputed international journals, including Cybernetics and Systems, and presented at prestigious conferences such as AICERA/ICIS and ICCIDT. She has also been a resource person for seminars on career development and technical workshops. As a life member of the Indian Society of Systems for Science and Engineering (ISSE), she continues to actively engage with the research community. She has not only attended but also organized several faculty development programs and national-level symposiums. These contributions and recognitions collectively highlight her dedication to academic excellence, knowledge dissemination, and research-driven community engagement.

Research Skill🔬

Dr. L.T. Herlin possesses a robust set of research skills that span across data analysis, algorithm design, wireless network simulation, and sensor-based system development. Her Ph.D. work and subsequent publications demonstrate proficiency in developing energy-aware and fault-tolerant protocols using metaheuristic algorithms such as the Serial Exponential Newton method. She has applied these skills in practical contexts like agriculture, environmental monitoring, and health analytics. Her familiarity with tools such as MATLAB, Python, and simulation platforms supports the technical depth of her work. She is also skilled in conducting empirical research, literature reviews, and comparative performance analysis. Additionally, she has guided undergraduate and postgraduate students in research and prototype development. Her ability to combine theoretical knowledge with applied research ensures her projects are both innovative and practically viable. Her skills are further reflected in her successful participation and contribution to FDPs, workshops, and interdisciplinary collaborations that strengthen her capabilities as a researcher and mentor.

Conclusion💡

Dr. L.T. Herlin exhibits a well-rounded academic profile, characterized by strong research, teaching, mentoring, and community engagement. Her focus areas—Wireless Sensor Networks, IoT, and Machine Learning—are current, impactful, and technologically significant. With a recent Ph.D. and a growing body of scholarly work, she clearly aligns with the objectives of the Best Researcher Award.

Publications Top Noted✍

  • Title: A New Modified Fast Fractal Image Compression Algorithm in DCT Domain
    Authors: J.S. Jiji, L.T. Herlin, A.G. Singerji, S.W. Pillai
    Cited by: 3
    Year: 2017

  • Title: An Energy-Aware and Fault-Tolerant WSN Routing Approach Using Serial Exponential Newton Metaheuristic Algorithm for Agricultural Lands
    Authors: L.T. Herlin
    Cited by: 2
    Year: 2023

  • Title: Retinal Blood Vessel Extraction using ISODATA Clustering and Morphological Operations
    Authors: S.W. Pillai, L.T. Herlin, A.G. Singerji
    Cited by: 2
    Year: 2017

  • Title: An IoT based Portable Sensory System for the Accurate Analysis of Soil Macronutrients using Photometry
    Authors: C.T. Lincy, J. Jalbin, L.T. Herlin
    Year: 2023

  • Title: A Duty-Cycle based Cooperative Clustering Protocol for Energy Harvesting WSN
    Authors: Prof. Dr. A. Lenin Fred, J. Janila, L.T. Herlin, Austy B
    Year: 2022

  • Title: Optimizing Precision Agriculture with LoRa-Enabled Wireless Sensor Networks for Smart Irrigation and Fertilization Management
    Authors: L.T. Herlin, L.L. Laudis, J. Jalbin