Dr. Jany Shabu | Artificial Intelligence Awards | Best Researcher Award

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Dr. Jany Shabu | Artificial Intelligence Awards | Best Researcher Award 

Dr. Jany Shabu, Sathyabama Institute of Science & Technology, India

Dr. S.L. Jany Shabu is an accomplished Associate Professor in the Department of Computer Science Engineering at Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India. With a Ph.D. in Image Fusion, her research focuses on multimodal image fusion using intelligent optimization techniques, particularly in the context of brain tumor detection. Dr. Shabu has a strong academic background, holding both M.Tech and MS degrees in Information Technology, and has published extensively, with 58 papers indexed in Scopus and four in WoS. She has received multiple accolades for her contributions to research and education, including cash awards for publishing in high-impact journals and the prestigious NPTEL Discipline Star Certificate. As an active member of the National Institute for Technical Training and Skill Development, Dr. Shabu is dedicated to advancing the field of computer science through her research, teaching, and professional engagement. Her innovative projects, including a Safety Stick for Elders, and her patents in smart traffic control and gesture-based systems, exemplify her commitment to leveraging technology for societal benefit. She has also authored several books on machine learning, cloud computing, and data analytics, further solidifying her reputation as a thought leader in her field. With a robust online presence, including profiles on ORCID and Scopus, Dr. Shabu continues to contribute to academic excellence and innovation in computer science.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award:

Dr. S.L. Jany Shabu is a commendable candidate for the Best Researcher Award, recognized for her significant contributions to computer science engineering and her innovative research in image fusion and optimization techniques.

Education 🎓

  • Ph.D. in Image Fusion
    Sathyabama Institute of Science and Technology
    Thesis Title: Multimodal Image Fusion using Intelligent Optimization Techniques with Brain Tumor Detection
  • M.Tech (IT) in Information Technology
    Sathyabama Institute of Science and Technology
    Graduated with First Class
  • M.S. (IT) in Information Technology
    Manonmaniam Sundaranar University
    Graduated with First Class

Work Experience 💼

  • Current Position: Associate Professor, Computer Science Engineering
    Sathyabama Institute of Science and Technology

Achievements 🌟

  • Seed Funding:
    Project Title: Safety Stick for Elders
    Amount: ₹300,000
    Period: Oct 2021 – June 2022
    Role: Co Principal Investigator
  • Patent Holder:
    1. SMART TRAFFIC CONTROL SYSTEM USING IOT BASED MONITORING SYSTEM
      Application No: 201741038384 – Published
    2. GARMENT STEAMER MANAGEMENT SYSTEM
      Application No: 367890-001 – Published
    3. GESTURE BASED ELECTRONIC GADGET OPERATING SYSTEM
      Application No: 202341088351 A – Published
  • Reviewer:
    • Journal of Scientific Research and Reports
    • Journal of Pharmaceutical Research International
    • International Conference on Computational Intelligence, Networks & Security
    • Book Chapter for CRC PRESS Taylor & Francis Group

Awards and Honors 🏆

  • Cash Award for Publishing Paper in High Impact WOS Journal
    Sathyabama Institute of Science and Technology (Teachers Day 2022 & 2024)
  • NPTEL Discipline Star Certificate
  • Disciplinarian Award
    Sathyabama Institute of Science & Technology, Chennai

Publication Top Notes:

DeepExuDetectNet: Diabetic retinopathy diagnosis: Blood vessel segmentation and exudates disease detection in fundus images

A swarm intelligence optimization for lung cancer detection from RNA-seq gene expression data using convolutional neural networks

A novel framework for entertainment robots in personalized elderly care using adaptive emotional resonance technologies

An Improved Adaptive Neuro-fuzzy Inference Framework for Lung Cancer Detection and Prediction on Internet of Medical Things Platform

Rainfall prediction using machine learning techniques

Online product review using sentiment analysis

Dr. Minh-Khang Le | Artificial Intelligence Awards | Best Researcher Award

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Dr. Minh-Khang Le | Artificial Intelligence Awards | Best Researcher Award 

Dr. Minh-Khang Le, Cedars-Sinai Medical Center, United States

Minh-Khang Le, M.D., Ph.D., is a Postdoctoral Research Scientist in the Department of Pathology and Computational Biomedicine at Cedars-Sinai Medical Center in Los Angeles, California. He obtained his Doctor of Medicine degree from the University of Medicine and Pharmacy at Ho Chi Minh City, graduating in the top 10% of his class, and completed his Ph.D. in Pathology at the University of Yamanashi in Japan. His research focuses on integrating histopathology, molecular profiles, and clinicopathological features to characterize human cancers, particularly lymphoid and hematopoietic neoplasms. Dr. Le has contributed to several projects involving histopathology, molecular analyses, and the development of clinicopathological machine-learning models. As a strong advocate for the transformative potential of artificial intelligence in pathology, he aims to enhance the understanding and treatment of cancer. In addition to his postdoctoral position, he has held research roles at various institutions, including the University of Iowa Hospitals and Clinics and the University of Oklahoma Health Sciences Center. Dr. Le’s work has led to impactful advancements in digital pathology and cancer research.

Professional Profile:

SCOPUS

Researcher Suitability Summary for Best Researcher Award: 

Minh-Khang Le is an exemplary candidate for the Best Researcher Award, showcasing a profound commitment to advancing the field of digital pathology and computational biomedicine. His research is particularly focused on integrating histopathological and molecular profiles to enhance the understanding and characterization of human cancers, especially lymphoid and hematopoietic neoplasms. This multidisciplinary approach not only reflects his extensive knowledge but also his dedication to translating complex data into meaningful clinical insights.

Education 🎓

  • Postdoctoral Research Scientist
    Cedars-Sinai Medical Center, Department of Computational Biomedicine and Pathology
    July 2024 – Present
    8700 Beverly Blvd, Los Angeles, CA, USA
  • Ph.D. Student
    University of Yamanashi, Department of Pathology
    April 2020 – March 2024
    GPA: 3.5/4.0
    1110 Shimokato, Chuo, Yamanashi, Japan
  • Doctor of Medicine
    University of Medicine and Pharmacy at Ho Chi Minh City
    October 2013 – September 2019
    Degree Classification: Good (Top 10% of the Course)
    Ho Chi Minh City, Vietnam

Work Experience 💼

  • Postdoctoral Research Scientist
    Cedars-Sinai Medical Center, Department of Computational Biomedicine and Pathology
    July 2024 – Present
  • Part-time Researcher
    New Energy and Industrial Technology Development Organization (NEDO)
    April 2022 – Present
  • Part-time Researcher
    Department of Pathology, The University of Iowa Hospitals and Clinics, Iowa, USA
    April 2022 – Present
  • Research Assistant
    Department of Pathology, University of Yamanashi
    April 2020 – Present
  • Teaching Assistant
    Department of Pathology, University of Yamanashi
    April 2020 – Present
  • Part-time Researcher
    Department of Neurosurgery, The University of Oklahoma Health Sciences Center, Oklahoma, USA
    April 2021 – March 2022

Achievements, Awards, and Honors 🏆

  • Top 10% of the Course in Doctor of Medicine program at the University of Medicine and Pharmacy at Ho Chi Minh City
  • GPA of 3.5/4.0 in Ph.D. studies at the University of Yamanashi

Publication Top Notes:

Clinical implication of PRAME immunohistochemistry in differentiating melanoma in situ and dysplastic nevus in non-acral nevus-associated melanoma in situ: An institutional experience and meta-analysis

A Novel Artificial Intelligence-Based Parameterization Approach of the Stromal Landscape in Merkel Cell Carcinoma: A Multi-Institutional Study

Comprehensive analysis of distinct circadian clock subtypes of adult diffuse glioma and their associations with clinicopathological, genetic, and epigenetic profiles

CXCL5 expression is associated with active signals of macrophages in the microenvironment of papillary thyroid carcinoma

Severe asthmatic airways have distinct circadian clock gene expression pattern associated with WNT signaling

Assoc. Prof. Dr. Mahmoud Bayat | Artificial intelligence Award | Best Researcher Award

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Assoc. Prof. Dr. Mahmoud Bayat | Artificial intelligence Award | Best Researcher Award

Assoc. Prof. Dr. Mahmoud Bayat, Research Institute of Forests and Rangelands, Iran

Mahmoud Bayat is an Assistant Professor at the Research Institute of Forests and Rangelands, part of the Agricultural Research, Education, and Extension Organization (AREEO) in Tehran, Iran. He earned his B.A., M.Sc., and Ph.D. degrees from the University of Tehran, specializing in forestry science. Mahmoud has collaborated with renowned researchers, including Dr. Charles P.-A. Bourque, Dr. Pete Bettinger, Dr. Eric Zenner, Dr. Aaron Weiskittel, Dr. Harold Burkhart, and Dr. Timo Pukkala. His research focuses on forest modeling and inventory, with particular interest in applying artificial intelligence and machine learning techniques in forestry. Currently, he is working on projects related to growth and yield models for uneven-aged and mixed broadleaf forests using neural networks and the monitoring and mapping of tree species richness in northern Iran’s forests through symbolic regression and artificial neural networks. Mahmoud is proficient in statistical tools such as SPSS and MATLAB, and he is eager to share his expertise and discuss potential collaborations. For more information, his profiles can be found on ResearchGate, Google Scholar, and Scopus.

Professional Profile:

SCOPUS

 

Mahmoud Bayat’s Suitability for the Research for Best Researcher Award

Based on the provided details, Mahmoud Bayat demonstrates a strong candidacy for the Research for Best Researcher Award due to his extensive academic and professional contributions. Below is a summary supporting his suitability

Education 🎓

  • Ph.D. in Forestry Science
    University of Tehran, Iran
  • M.Sc. in Forestry Science
    University of Tehran, Iran
  • B.A. in Forestry Science
    University of Tehran, Iran

Work Experience 🏢

  • Assistant Professor
    Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO)
    Tehran, Iran
    Year: [Specify Year] – Present
  • Research Collaborator
    Worked with:

    • Dr. Charles P.-A. Bourque
    • Dr. Pete Bettinger
    • Dr. Eric Zenner
    • Dr. Aaron Weiskittel
    • Dr. Harold Burkhart
    • Dr. Timo Pukkala

Research Interests 🔍

  • Forest modeling and inventory
  • Application of artificial intelligence and machine learning in forestry

Current Projects 📊

  1. Growth and Yield Models for Uneven-Aged and Mixed Broadleaf Forest
    • Method: Neural Network
  2. Monitoring, Mapping, and Modeling Variation in Tree Species Richness
    • Method: Symbolic Regression and Artificial Neural Networks
    • Location: Northern Iran Forests

Publication Top Notes:

Comparison of Random Forest Models, Support Vector Machine and Multivariate Linear Regression for Biodiversity Assessment in the Hyrcanian Forests

Projected biodiversity in the Hyrcanian Mountain Forest of Iran: an investigation based on two climate scenarios

Recreation Potential Assessment at Tamarix Forest Reserves: A Method Based on Multicriteria Evaluation Approach and Landscape Metrics

Comparison between graph theory connectivity indices and landscape connectivity metrics for modeling river water quality in the southern Caspian sea basin

Development of multiclass alternating decision trees based models for landslide susceptibility mapping

Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests

 

Dr. Tara P Banjade | Artificial Intelligence Awards | Best Researcher Award

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Dr. Tara P Banjade | Artificial Intelligence Awards | Best Researcher Award 

Dr. Tara P Banjade, East China University of Technology, Nanchang, China

Dr. Tara P. Banjade is an Associate Professor at the East China University of Technology, Nanchang, China, specializing in applied mathematics, seismic signal processing, and artificial intelligence applications for seismic data processing. He completed his Ph.D. in Applied Mathematics at Harbin Institute of Technology in China in 2020, following a Master’s and Bachelor’s in Mathematics from Tribhuvan University, Nepal. Dr. Banjade’s research focuses on developing mathematical algorithms for denoising seismic data, including 1D earthquake signals and 2D geophysical data like oil, gas, and ground-penetrating radar (GPR) data. His innovative approaches employ techniques such as variational mode decomposition, wavelet transforms, and artificial intelligence, including DARE U-Net for seismic noise attenuation and self-guided singular value decomposition for data edge detection.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Dr. Tara P. Banjade demonstrates an impressive academic and research profile, particularly within Applied Mathematics and Seismic Signal Processing, fields which align closely with the scope of the Best Researcher Award. His doctoral education from Harbin Institute of Technology and ongoing research position at East China University of Technology position him as a strong candidate.

Education

  1. Harbin Institute of Technology, Harbin, China
    • Ph.D. in Applied Mathematics
    • Duration: September 2015 – January 2020
  2. Tribhuvan University, Kathmandu, Nepal
    • Master’s in Mathematics
    • Duration: 2012 – 2014
  3. Tribhuvan University, Kathmandu, Nepal
    • Bachelor’s in Mathematics
    • Duration: 2006 – 2010

Work Experience

  1. Associate Professor
    • Institution: East China University of Technology, School of Geophysics and Measurement-Control Technology, Nanchang, Jiangxi, China
    • Duration: March 2023 – Present
  2. Founder/Chairperson
    • Organization: Intellisia Institute for Research and Development, Nepal
  3. Research Director
    • Organization: Girija Prasad Koirala Foundation
    • Duration: 2020 – Present
  4. Visiting Scientist
    • Institution: Research Centre for Applied Science and Technology (RECAST), Tribhuvan University, Nepal
  5. Founding Member and Mathematics Lecturer
    • Institution: Arunima College, Tribhuvan University, Nepal
    • Duration: 2020 – 2023
  6. Executive Member
    • Organization: Nepal Mathematical Society
    • Duration: 2021 – 2024
  7. Visiting Faculty
    • Institution: School of Mathematical Science, Tribhuvan University, Nepa.

Publication top Notes:

Seismic Random Noise Attenuation Using DARE U-Net

Enhancing seismic data by edge-preserving geometrical mode decomposition

Prof. Dr. Tamara Gajic | Artificial Intelligence Awards | Top Researcher Award

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Prof. Dr. Tamara Gajic | Artificial Intelligence Awards | Top Researcher Award 

Prof. Dr. Tamara Gajic, Geographical Institute “Jovan Cvijic” Serbian Academy of Sciences and Arts, Belgrade, Serbia

Tamara Gajić is a distinguished Senior Research Associate at the Geographical Institute “Jovan Cvijić” of the Serbian Academy of Sciences and Arts (SASA), specializing in social geography. She holds a Ph.D. in Geosciences from the University of Novi Sad and has extensive experience in research and education across various institutions. Her academic career spans several positions, including Senior Researcher at the Institute of Environmental Engineering, People’s Friendship University of Russia (RUDN University), and Associate Professor at Singidunum University in Belgrade. She has also served as a professor and assistant professor at various universities in Serbia, Bosnia, and Herzegovina. Gajić’s research focuses on rural development, tourism management, and sustainable practices in agritourism, gastrotourism, and sport tourism. She has contributed to numerous projects, including the modernization of tourism study programs in Serbia and feasibility studies for spa tourism. Gajić is an active member of various professional organizations, including the Serbian Geographical Society and the Tourist Organization of Serbia, and has mentored numerous graduate and doctoral students. Her expertise in integrating economics, service quality, and human resources in tourism management has earned her recognition as one of the top 10% of distinguished scientists in Serbia in 2024.

Professional Profile:

SCOPUS

ORCID

GOOGLE SCHOLAR

Suitability of Tamara Gajić for the Top Researcher Award

Tamara Gajić is highly qualified for the Top Researcher Award due to her extensive academic and professional achievements in the fields of Geography, Rural Studies, and Tourism Management. Below are the key reasons why she is a suitable candidate for this prestigious award:

Academic Degrees:

🎓 Ph.D. in Geosciences
📅 2010
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia 🇷🇸

🎓 M.Sc. in Tourism Management
📅 2007
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia 🇷🇸

🎓 B.Sc. in Tourism Management
📅 2001
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia 🇷🇸

Research & Teaching Interests:

🌍 Research Areas:

  • Geography 🌍
  • Rural Studies 🌾
  • Tourism Management 🌐
    Focus on Agrotourism, Gastrotourism, and Sport Tourism 🏞️🍴🏃‍♀️
    Intersection of Economics in Tourism, Service Quality, and Human Resources 💼
    Sustainability in Environment and Tourism 🌱

Previous Employment:

  • Associate Professor
    📅 February 2021 – September 2021
    Faculty of Tourism and Hotel Management, Singidunum University, Belgrade, Serbia 🇷🇸
  • Assistant Professor
    📅 October 2018 – February 2022
    University for Business Studies, Banja Luka, Bosnia and Herzegovina 🇧🇦
  • Professor of Vocational Studies
    📅 October 2008 – February 2021
    Novi Sad Business School, Novi Sad, Serbia 🇷🇸

Publication top Notes:

Innovative Approaches in Hotel Management: Integrating Artificial Intelligence (AI) and the Internet of Things (IoT) to Enhance Operational Efficiency and Sustainability

The Contribution of the Farm to Table Concept to the Sustainable Development of Agritourism Homesteads

Fostering Sustainable Urban Tourism in Predominantly Industrial Small-Sized Cities (SSCs)—Focusing on Two Selected Locations

Leveraging digital platforms for responsible sports tourism: Budapest’s role in the 2020 European football championship

Tourists’ Willingness to Adopt AI in Hospitality—Assumption of Sustainability in Developing Countries

The Adoption of Artificial Intelligence in Serbian Hospitality: A Potential Path to Sustainable Practice

Mr. Omer Tariq | Artificial Intelligence Award | Best Researcher Award

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Mr. Omer Tariq | Artificial Intelligence Award | Best Researcher Award 

Mr. Omer Tariq, Korea Advanced Institute of Science and Technology, KAIST, South Korea

Omer Tariq is a Ph.D. candidate at the Korea Advanced Institute of Science and Technology (KAIST), specializing in efficient and privacy-preserving deep learning for AIoT and autonomous systems. With a strong foundation in digital ASIC design, embedded systems, and hardware design, Omer has over seven years of experience in developing and deploying innovative machine learning solutions using TensorFlow, TensorRT, and PyTorch. His research includes advanced robotics software systems, autonomous navigation, and state-of-the-art motion planning algorithms. He has led teams in high-performance SoC/RTL design and verification at the National Electronics Complex, Pakistan, and contributed to satellite imaging systems at SUPARCO. Omer holds a BSc in Electrical Engineering from the University of Engineering and Technology, Taxila, and has published several papers in prominent journals. His technical skills are complemented by a range of certifications in machine learning, data science, and digital signal processing.

Professional Profile:

Summary of Suitability for Best Researcher Award

Omer Tariq is a Ph.D. candidate specializing in efficient and privacy-preserving deep learning for AIoT and Autonomous Systems. His work is highly relevant to current technological advancements and addresses significant challenges in machine learning, robotics, and autonomous systems. His research includes:

Education

Korea Advanced Institute of Science and Technology (KAIST)
Doctor of Philosophy (Ph.D.) in Computer Science
May 2021 – July 2025

  • Majors: Machine Learning & AI
  • CGPA: 3.74/4.3
  • Coursework: Programming for AI, Introduction to Artificial Intelligence, Design and Analysis of Algorithms, Intelligent Robotics, Human-Computer Interaction, Artificial Intelligence and Machine Learning, Technical Writing for Computer Science, Advanced Machine Learning, IoT Datascience

University of Engineering and Technology (UET), Taxila
Bachelor of Science in Electrical Engineering
Nov 2010 – July 2014

  • CGPA: 3.25/4.0
  • Thesis: Computer Vision-Assisted Object Detection and Control Framework for 3-DoF Robotic Arm
  • Area: Microelectronics, Control Systems, and Advanced Computer Architecture

Work Experience

Department of Industrial & Systems Engineering (ISysE), KAIST
Research Assistant
Nov. 2023 – March 2024

  • Designed and developed the electronics and power management module for the DAIM-Autonomous Mobile Robot, enhancing operational efficiency and reliability.
  • Engineered advanced robotics software systems for autonomous navigation and task execution.
  • Implemented state-of-the-art robot motion planning, mapping, and localization (SLAM) algorithms to improve real-time navigation accuracy.

National Electronics Complex, Pakistan (NECOP)
Engineering Manager & Team Lead
Apr. 2019 – Sep. 2022

  • Led verification and validation of high-performance SoC/RTL designs, ensuring system performance and reliability.
  • Spearheaded RTL development and optimization for high-performance IC designs, including logic synthesis, DFT, scan chain insertion, formal verification, and static timing analysis.
  • Managed the use of Synopsys and Cadence EDA tools for front-end and back-end digital IC design processes.

National Space Agency, Pakistan (SUPARCO)
Assistant Manager
Oct. 2014 – Apr. 2019

  • Designed and developed satellite imaging payload systems for national satellite missions.
  • Engineered high-speed, multi-layer PCB designs and conducted signal/power integrity simulations for satellite systems.
  • Developed embedded systems for the Satellite Ku-Band Positioning Unit, enhancing communication and positioning capabilities.

Publication top Notes:

2D Particle Filter Accelerator for Mobile Robot Indoor Localization and Pose Estimation

TabCLR: Contrastive Learning Representation of Tabular Data Classification for Indoor-Outdoor Detection

Compact Walsh–Hadamard Transform-Driven S-Box Design for ASIC Implementations

DeepIOD: Towards A Context-Aware Indoor–Outdoor Detection Framework Using Smartphone Sensors

 

 

Ms. Hind MEZIANE | Artificial Intelligence | Best Scholar Award

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Ms. Hind MEZIANE | Artificial Intelligence | Best Scholar Award 

Ms. Hind MEZIANE, ACSA Lab, Faculty of Sciences, University Mohammed First, Oujda, Morocco

Hind Meziane is a dedicated researcher and Ph.D. candidate in Computer Science at the ACSA Laboratory, Department of Mathematics, Faculty of Sciences, Mohammed Premier University, Oujda, Morocco. Her academic journey began with a Baccalaureate in Science (Science Mathematics Option B) from Mehdi Ben Berka High School in Oujda in 2012. She then pursued higher education at Mohammed Premier University, obtaining a DEUG in Mathematics and Computer Science (2012-2014), a LICENSE in Mathematics and Computer Science (2014-2016), and a Specialized Master’s in Computer Engineering with Honors (2017-2019).

Professional Profile:

Summary of Suitability for Best Scholar Award

Hind Meziane is a highly accomplished researcher whose work primarily focuses on the security of Internet of Things (IoT) systems. She is currently pursuing a Ph.D. in Computer Science at Mohammed Premier University and has an impressive academic background, including a specialized master’s degree in Computer Engineering and a bachelor’s degree in Mathematics and Computer Science. Her research contributions are well-documented through various publications in reputable international journals and conference proceedings.

🎓 Education:

  • 2019-Present: Doctorate (PhD) in Computer Science at Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2017-2019: Specialized Master in Computer Engineering, with Honors, at Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2014-2016: LICENSE in Mathematics and Computer Science from Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2012-2014: DEUG in Mathematics and Computer Science from Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2011-2012: Baccalaureate in Science, Mathematics Option B from Mehdi Ben Berka High School, Oujda.

Publication top Notes:

A survey on performance evaluation of artificial intelligence algorithms for improving IoT security systems

A Comparative Study for Modeling IoT Security Systems

Modeling IoT based Forest Fire Detection System with IoTsec

A Study of Modelling IoT Security Systems with Unified Modelling Language (UML)

Classifying security attacks in iot using ctm method

Internet of Things: Classification of attacks using CTM method