Alireza sobbouhi | Predictive Modeling Innovations | Best Researcher Award

Dr. Alireza sobbouhi | Predictive Modeling Innovations | Best Researcher Award

shahid beheshti university | Iran

Author Profile

Early Academic Pursuits 📚

Dr. Alireza Sobbouhi’s academic journey began at Shahid Beheshti University in Iran, where he developed a strong foundation in mathematics, statistics, and computational sciences. His early fascination with complex systems and data-driven decision-making led him to specialize in predictive modeling. This interest propelled him into graduate studies, where he focused on developing and applying sophisticated techniques for forecasting and analyzing data.

Professional Endeavors 💼

Dr. Sobbouhi’s career blends academic achievements with professional success. As a professor at Shahid Beheshti University, he has been deeply involved in teaching, research, and industry collaboration. His role in academia extends beyond teaching as he works on impactful projects that link predictive modeling with real-world applications, from healthcare to finance. His expertise has also made him a sought-after consultant, furthering his reach and influence in both academia and industry.

Contributions and Research Focus On Predictive Modeling Innovations🔬

Dr. Sobbouhi’s research is rooted in the advancement of predictive modeling. His contributions have introduced new methodologies to improve the accuracy and efficiency of data analysis in various domains. Some key areas of focus include:

  • Development of Predictive Algorithms: Crafting algorithms that provide more precise predictions in economic, healthcare, and environmental sectors.
  • Machine Learning Integration: Exploring ways to integrate machine learning techniques into predictive models for better data interpretation and forecasting.
  • Big Data Analytics: Focusing on scalable approaches to handle and analyze massive datasets to uncover patterns that traditional models might miss.

Impact and Influence 🌍

Dr. Sobbouhi’s work has had a profound impact, not only in academia but also across various industries. His innovative contributions to predictive modeling and machine learning have influenced numerous researchers and professionals in fields ranging from economics to environmental science. His approach to enhancing model reliability and interpretability has set new standards and inspired further research in data science. The applications of his work continue to improve decision-making processes worldwide.

Academic Cites 📑

Dr. Sobbouhi’s research has been extensively cited in scholarly articles, journals, and conferences, indicating the high regard in which his work is held. His studies on predictive analytics and statistical modeling have been foundational, influencing a wide range of studies in machine learning and data science. The frequency of his citations reflects the relevance and significance of his contributions to the broader scientific community.

Technical Skills 🧑‍💻

Dr. Sobbouhi possesses a diverse and deep technical skill set that includes:

  • Programming: Expertise in Python, R, and MATLAB for data analysis and modeling.
  • Statistical Modeling: Advanced proficiency in developing and applying statistical techniques for prediction and forecasting.
  • Machine Learning: Expertise in applying machine learning algorithms to large datasets to uncover trends and make predictions.
  • Data Visualization: Strong skills in visualizing complex datasets to facilitate understanding and decision-making.

These technical competencies allow him to tackle complex datasets and develop state-of-the-art predictive models.

Teaching Experience 🏫

As an educator, Dr. Sobbouhi has taught a variety of courses on statistics, data science, and machine learning at Shahid Beheshti University. His teaching style blends theoretical knowledge with practical applications, ensuring students are well-prepared for the real-world challenges of the data science field. Dr. Sobbouhi has also supervised many graduate students, guiding them in their research and helping to shape the next generation of data scientists.

Legacy and Future Contributions 🔮

Dr. Sobbouhi’s legacy is built on his innovative contributions to predictive modeling and data science. His ability to bridge the gap between academic theory and industry application has had a lasting influence on both fields. Looking ahead, Dr. Sobbouhi is expected to continue making groundbreaking advancements in predictive analytics, particularly in the integration of AI and machine learning into real-world applications. His future research will likely shape the development of new predictive tools, influencing a wide range of industries for years to come.

Notable Publications  📑 

A novel predictor for areal blackout in power system under emergency state using measured data
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2025
A novel SVM ensemble classifier for predicting potential blackouts under emergency condition using on-line transient operating variables
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2025 (April issue)
Transient stability improvement based on out-of-step prediction
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2021
Transient stability prediction of power system; a review on methods, classification and considerations
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2021
Online synchronous generator out-of-step prediction by electrical power curve fitting
    • Authors: Alireza Sobbouhi (main author)
    • Journal: IET Generation, Transmission and Distribution
    • Year: 2020
Online synchronous generator out-of-step prediction by ellipse fitting on acceleration power – Speed deviation curve
    • Authors: Alireza Sobbouhi (main author)
    • Journal: International Journal of Electrical Power and Energy Systems
    • Year: 2020

Jiao Kai | Data Science | Best Researcher Award

Prof Dr. Jiao Kai | Data Science | Best Researcher Award

Department of Stomatology, Tangdu Hospital, China

Author Profile

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👨‍⚕️ Prof. Dr. Jiao Kai - A Leading Expert In Stomatology

Early Academic Pursuits 🎓

Prof. Dr. Jiao Kai’s academic journey in stomatology began with a deep commitment to the field. He pursued higher education, ultimately becoming a doctoral supervisor. His early research laid the groundwork for his future breakthroughs, with a focus on oral medicine and temporomandibular joint disorders. Through rigorous training, he became an expert in the intricacies of oral health, reconstructive techniques, and joint disorders, propelling his career to new heights.

Professional Endeavors 💼

Currently, Prof. Dr. Jiao serves as the Director of the Department of Stomatology at Tangdu Hospital, Air Force Medical University. His role encompasses both clinical practice and leading research initiatives. In addition, he is the Branch Secretary and Director of the Oral Medicine Teaching and Research Section. As a Doctoral Supervisor and member of various esteemed professional organizations, his influence spans across national and international levels.

Contributions and Research Focus 🔬

Prof. Dr. Jiao’s research primarily targets the prevention, treatment, and regenerative reconstruction of temporomandibular joint disorders. Leading numerous high-level research projects, his groundbreaking work in regenerative techniques has advanced the understanding and treatment of joint disorders, focusing on enhancing patient outcomes. His contributions have garnered numerous awards and recognition for scientific progress in stomatology.

Impact and Influence 🌍

Prof. Dr. Jiao has left a significant mark on the field, with his research being cited over 3,200 times globally. He has earned recognition as a scientist in the top 2% worldwide. His work has shaped clinical practices and continues to influence stomatology, earning him a reputation as a global leader in his field. He is also a sought-after reviewer and editor for numerous prestigious journals.

Academic Cites 📚

Over the last five years, Prof. Dr. Jiao’s research has been cited more than 3,200 times, with over 20 of his papers having an impact factor (IF) greater than 10. His extensive body of work has set new benchmarks in oral medicine, influencing clinical practices and advancing the understanding of temporomandibular joint disorders.

Legacy and Future Contributions 🌱

Prof. Dr. Jiao’s legacy is rooted in innovation, mentorship, and exceptional research. His groundbreaking studies and pioneering therapeutic techniques have solidified his position as a global leader in stomatology. Committed to advancing temporomandibular joint disorder research, he remains dedicated to the development of regenerative treatments and fostering international collaborations for future advancements.

Awards and Recognitions 🏆

Prof. Dr. Jiao has received multiple accolades, including the prestigious First Prize from the Chinese Stomatological Association and for Scientific Progress in Shaanxi Province. He has been recognized as a Young Top Talent of the National "Ten Thousand Talents Program" and a Distinguished Young Scholar in Shaanxi Province for his outstanding contributions to research and innovation.

Patents and Technology Transfer 🛠️

Prof. Dr. Jiao has contributed significantly to applied science, holding 29 invention patents, with 16 attributed to him as the primary inventor. His patents have led to the commercialization of advanced technologies, contributing to the academic and industrial sectors with a total transfer value exceeding 10 million yuan.

Collaborations and Professional Memberships 🤝

Prof. Dr. Jiao’s collaborations with global experts such as Professor Xu Cao (Johns Hopkins University) and Professor Jiang Chang (Chinese Academy of Sciences) have enhanced his international influence. He holds leadership positions in several national and regional scientific organizations, including the Shaanxi Provincial Stomatological Association and the Shaanxi Oral Physicians Association, contributing to the progress of the field.

Books Published and Editorial Appointments 📖

Prof. Dr. Jiao has actively contributed to academic literature, participating in the compilation and translation of 12 books, and serving as the chief editor for four of them. His editorial roles in national and international journals reflect his dedication to advancing knowledge in the field of stomatology.

Areas of Research 🔍

His ongoing research focuses on the prevention, treatment, and regenerative regeneration of temporomandibular joint disorders, striving to develop innovative therapies that improve patient care and outcomes globally. His work continues to shape the future of stomatology and has made a lasting impact on medical practices worldwide.

Top Noted Publications 📖

Pathological mechanism of chondrocytes and the surrounding environment during osteoarthritis of temporomandibular joint

Authors: Li B, Guan G, Mei L, Jiao K, Li H

Journal: Journal of Cellular and Molecular Medicine

Year: 2021

Crosstalk between Bone and Nerves within Bone

Authors: Wan QQ, Qin WP, Ma YX, Shen MJ, Li J, Zhang ZB, Chen JH, Tay FR, Niu LN, Jiao K

Journal: Advanced Science (Weinheim, Baden-Wurttemberg, Germany)

Year: 2021

Matrix stiffening by self-mineralizable guided bone regeneration

Authors: Li J, Yan JF, Wan QQ, Shen MJ, Ma YX, Gu JT, Gao P, Tang XY, Yu F, Chen JH et al.

Journal: Acta Biomaterialia

Year: 2021

miR-200-3p suppresses cell proliferation and reduces apoptosis in diabetic retinopathy via blocking the TGF-β2/Smad pathway

Authors: Xue L, Xiong C, Li J, Ren Y, Zhang L, Jiao K, Chen C, Ding P

Journal: Bioscience Reports

Year: 2020

The 14-3-3η/GSK-3β/β-catenin complex regulates EndMT induced by 27-hydroxycholesterol in HUVECs and promotes the migration of breast cancer cells.

Authors: Zhen J, Jiao K, Yang K, Wu M, Zhou Q, Yang B, Xiao W, Hu C, Zhou M, Li Z

Journal: Cell Biology and Toxicology

Year: 2020

Maame Yaa Yiadom | Data collection | Women Researcher Award

Dr. Maame Yaa Yiadom | Data collection | Women Researcher Award

Stanford University, United States

Author Profile

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Early Academic Pursuits 🎓

Dr. Maame Yaa Yiadom’s academic journey began at Princeton University, where she earned her undergraduate degree in Public Health Policy and International Affairs, with a certificate in African Studies. This laid a strong foundation for her later research and clinical work in global health. Her commitment to expanding her expertise led her to advanced studies at Johns Hopkins School of Public Health and Harvard School of Public Health, where she obtained her Master of Public Health degree and further honed her focus on health systems and population health. Dr. Yiadom’s academic progression continued with a Doctor of Medicine degree from Robert Wood Johnson Medical School, solidifying her clinical expertise in emergency medicine.

Professional Endeavors & Contributions 🔬

Dr. Yiadom’s career spans over two decades and has seen her contribute in both administrative and clinical roles across multiple health systems. As a physician-scientist, she has focused on translating research into clinical practice through program development, health system optimization, and change management. Her research efforts are centered on improving clinical care delivery, with a particular emphasis on emergency medicine and health equity. She has led pivotal projects involving digital health integration, clinical practice epidemiology, and healthcare innovation, with significant contributions to artificial intelligence and algorithmic equity in health systems.

Throughout her career, she has applied a mix of analytical strategies and leadership to tackle issues like healthcare efficiency, financial sustainability, and clinical effectiveness, particularly in emergency departments across the U.S. and internationally. Her leadership roles in organizations like the Emergency Department Benchmarking Alliance (EDBA) and the Health Equity Action Leadership (HEAL) Network highlight her commitment to advancing healthcare innovation and equity. Additionally, her involvement in research grants and mentorship has further fueled the development of the next generation of health leaders.

Research Focus & Impact 📊

Dr. Yiadom’s research efforts are particularly focused on healthcare delivery operations, clinical workflows, and health equity, with ongoing projects spanning North America, Europe, and Africa. She leads a highly impactful lab, the Emergency Care Health Service Research Data Coordinating Center (HSR-DCC), which aims to improve clinical practice and workflow integration through cutting-edge digital health technologies. Through collaborations with multiple international institutions, Dr. Yiadom has made substantial contributions to improving emergency care systems and advancing equitable healthcare access across diverse populations. Notably, her projects tackle key issues such as algorithmic fairness and clinical decision support using artificial intelligence, particularly in heart attack screening.

Academic Citations & Recognition 📚

As a physician-scientist, Dr. Yiadom has gained recognition in the field for her contributions to research, evidenced by her leadership roles in numerous initiatives and her consistent engagement with funding bodies. Her work has earned citations in major academic journals, cementing her as a key figure in emergency medicine and health system research. Through her collaborations, both national and international, Dr. Yiadom has been integral in publishing impactful work on topics such as clinical data analytics, health policy reform, and healthcare access for underserved populations.

Technical Skills & Teaching Experience 💻

Dr. Yiadom’s technical skills are vast and varied, including expertise in clinical informatics, data analytics, and the integration of digital health tools into clinical environments. Her work in developing data-driven solutions to healthcare challenges has placed her at the forefront of innovative healthcare technologies. In her teaching roles, she has mentored numerous advanced trainees and faculty, providing guidance in research, clinical practice, and leadership development. Her educational impact extends beyond the classroom, as she also actively engages in mentorship programs, ensuring that the next generation of physicians and researchers is equipped to handle the evolving landscape of healthcare.

Legacy & Future Contributions 🔮

Dr. Yiadom’s legacy is rooted in her unwavering commitment to improving healthcare delivery, with a particular focus on emergency care, health equity, and digital health innovation. As she continues to advance research in algorithmic equity and healthcare policy, her work has the potential to significantly influence how emergency departments and other healthcare settings operate globally. Looking forward, Dr. Yiadom is poised to leave an indelible mark on health system transformation, especially through her leadership roles at Stanford University and beyond. Her involvement in cutting-edge initiatives such as the Center for Digital Health and her guidance in the fogarty innovation program ensures that her contributions will continue to shape the future of healthcare.

Teaching & Mentorship 🌱

Dr. Yiadom has demonstrated a strong commitment to mentorship and teaching, shaping future leaders in healthcare. She has mentored faculty members, trainees, and researchers, contributing significantly to academic and clinical environments. Her leadership in various academic programs has helped guide young professionals in their careers, particularly in emergency medicine and healthcare research. The knowledge and skills she imparts will undoubtedly have a long-lasting influence on the medical community.

 

 Top Noted Publications 📖

Influence of time‐to‐diagnosis on time‐to‐percutaneous coronary intervention for emergency department ST‐elevation myocardial infarction patients: Time‐to‐electrocardiogram matters

Authors: Maame Yaa A.B. Yiadom, Wu Gong, Brian W. Patterson, Christopher W. Baugh, Angela M. Mills, Nicholas Gavin, Seth R. Podolsky, Bryn E. Mumma, Mary Tanski, Gilberto Salazar et al.

Journal: JACEP Open

Year: 2024

Stanford Emergency Medicine Partnership Program: a novel approach to streamlining the evaluation and implementation of emerging health technologies through academic-industry partnerships

Authors: John Dayton, Maame Yaa A. B. Yiadom, Sam Shen, Matthew C. Strehlow, Christian Rose, Gabrielle Bunney, Ryan Ribeira

Journal: BMJ Innovations

Year: 2024

2023 Society for Academic Emergency Medicine Consensus Conference on Precision Emergency Medicine: Development of a policy-relevant, patient-centered research agenda

Authors: Matthew Strehlow, Michael A Gisondi, Holly Caretta-Weyer, Felix Ankel, Alexandria Brackett, Pawan Brar, Teresa M Chan, Adrene Garabedian, Bridget Gunn, Eric Isaacs et al.

Journal: Academic Emergency Medicine: Official Journal of the Society for Academic Emergency Medicine

Year: 2024

 Shorter Door-to-ECG Time Is Associated with Improved Mortality in STEMI Patients

Authors: Maame Yaa A. B. Yiadom, Wu Gong, Sean M. Bloos, Gabrielle Bunney, Rana Kabeer, Melissa A. Pasao, Fatima Rodriguez, Christopher W. Baugh, Angela M. Mills, Nicholas Gavin et al.

Journal: Journal of Clinical Medicine

Year: 2024

 Changes in low-acuity patient volume in an emergency department after launching a walk-in clinic

Authors: Divya Kurian, Vandana Sundaram, Anna Graber Naidich, Shreya A Shah, Daniel Ramberger, Saud Khan, Shashank Ravi, Sunny Patel, Ryan Ribeira, Ian Brown et al.

Journal: Journal of the American College of Emergency Physicians Open

Year: 2023

yunhao zhao | Data Analysis Innovation | Best Researcher Award

Assoc Prof Dr. yunhao zhao | Data Analysis Innovation | Best Researcher Award

Qingdao Huanghai University, China

Author Profile

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🧑‍🎓 Early Academic Pursuits

Yunhao Zhao was Shandong, P.R. China. His academic journey began with a strong foundation in International Economics and Social Security studies, setting the stage for his future research. After completing his undergraduate education, he became an associate professor at Qingdao Huanghai University, where he also supervises undergraduate students. His quest for further knowledge continues as he pursues a Ph.D. at The Catholic University of Korea, focusing on the evolving fields of economics and social security.

👨‍🏫 Professional Endeavors

Dr. Zhao’s academic career has been marked by significant contributions in the realms of data analysis and economic research. As an All-Media Operator and Associate Professor, he actively engages in both teaching and research at Qingdao Huanghai University. His dedication to advancing knowledge in the academic sphere extends to overseeing the academic progress of undergraduate students, ensuring they are equipped with the necessary skills and insights to excel in their respective fields.

📊 Contributions and Research Focus

Dr. Zhao’s primary research areas are data analysis, internet of things (IoT), and auction theory. His most notable work focuses on congestion control in IoT systems, where he applied auction theory to improve performance and efficiency. His research contributions are significant in their potential to drive forward the development of smarter and more efficient IoT networks. Furthermore, his work on energy consumption reduction demonstrates the real-world impact of his methods, achieving a remarkable 24.13% reduction in energy usage in experimental scenarios.

🌍 Impact and Influence

Dr. Zhao’s work has already made notable contributions to the global research community, evidenced by his publication in Scientific Reports (SCI) and recognition in high-impact journals. His research on IoT and auction theory has contributed to solving critical issues in technology and energy efficiency, impacting industries reliant on smart technology. His scholarly output has the potential to influence policy and innovation in areas such as network management and resource optimization.

🔧 Technical Skills

Dr. Zhao possesses advanced technical skills in data analysis, machine learning, and network optimization, particularly within the context of IoT systems. His expertise in auction theory and its applications in real-world scenarios is a testament to his depth of understanding and innovation in these areas. He is also adept at utilizing advanced analytical tools and methods to derive actionable insights from complex datasets.

👩‍🏫 Teaching Experience

As an Associate Professor at Qingdao Huanghai University, Dr. Zhao has extensive experience in educating the next generation of scholars and professionals. His role as a supervisor for undergraduate students allows him to nurture young talent and help shape their academic journeys. His commitment to teaching is evident through his personalized mentorship approach, guiding students to succeed in both their academic and professional aspirations.

🌟 Legacy and Future Contributions

Looking ahead, Dr. Zhao aims to continue contributing to the field of International Economics and Social Security Studies, with a strong emphasis on data-driven solutions. His work has already proven impactful, and he intends to further refine his methodologies to solve pressing global issues such as economic inequality, social security systems, and technological advancements in IoT. His legacy will undoubtedly inspire future researchers and practitioners in these fields, and his work has the potential to pave the way for groundbreaking solutions in economic policy and technological development.

🏆 Recognition and Awards

Dr. Zhao’s academic achievements have garnered recognition within the research community. He is a strong candidate for the Best Researcher Award for his ongoing contributions to data analysis and IoT research. His ability to surpass existing methodologies, particularly in terms of energy efficiency, sets him apart as an innovator in his field. His commitment to advancing knowledge and solving real-world problems makes him a deserving nominee for such accolades.

 

📖 Top Noted Publications

Congestion control in internet of things (IoT) using auction theory
    • Authors: Zhenlong Li; Yunhao Zhao
    • Journal: Scientific Reports
    • Year: 2024
Enhancing China’s green GDP accounting through blockchain and artificial neural networks (ANNs) and machine learning (ML) modeling
    • Authors: Nasi Wang; Yunhao Zhao; Jun Li; Guanfeng Cai
    • Journal: Scientific Reports
    • Year: 2024
Speech emotion analysis using convolutional neural network (CNN) and gamma classifier-based error correcting output codes (ECOC)
    • Authors: Yunhao Zhao; Xiaoqing Shu
    • Journal: Scientific Reports
    • Year: 2023

Haixia Mao | Data Science | Best Researcher Award

Dr. Haixia Mao | Data Science | Best Researcher Award

Shenzhen Polytechnic University, China

👨‍🎓Professional Profile

Scopus Profile

👩‍🏫 Summary

Dr. Haixia Mao is an Associate Professor at the School of Automobile and Transportation at Shenzhen Polytechnic University, China. She holds a Ph.D. in Geographic Information System (GIS) and Remote Sensing from the Hong Kong Polytechnic University. Her research focuses on GIS-T, big data analytics, and analyzing urban mobility patterns, using spatial-temporal data from transportation systems to improve urban planning and human behavior modeling.

🎓 Education

Dr. Mao earned her Ph.D. in GIS and Remote Sensing from the Hong Kong Polytechnic University in 2010. She also completed her M.S. in GIS at Wuhan University in 2004 and her B.S. in Photogrammetry and Remote Sensing from Wuhan University.

💼 Professional Experience

Dr. Mao currently serves as an Associate Professor at Shenzhen Polytechnic University (since 2012), where she has contributed to the development of transportation-related GIS courses. Previously, she worked as a Postdoctoral Researcher at the Hong Kong Polytechnic University from 2014 to 2016, furthering her expertise in urban computing and GIS.

📚 Research Interests

Her research encompasses GIS-T (Geographic Information Systems for Transportation), big data analytics, remote sensing, deep learning, and urban planning. She investigates the mobility patterns of citizens through traffic data (including taxis, buses, and metro) and leverages spatial-temporal data to enhance urban infrastructure and predict human behavior.

🏅 Academic Contributions

Dr. Mao has authored over 20 peer-reviewed journal articles and conference papers. She has also been awarded a patent for a caching system with a new cache placement method. She has received research grants for spatial-temporal data analytics in transportation and has actively contributed to major projects in urban computing.

💻 Technical Skills

Dr. Mao’s technical expertise spans GIS, remote sensing, big data analytics, deep learning, and spatial-temporal data analysis. She integrates these advanced techniques to solve complex transportation and urban planning challenges.

📚 Teaching Experience

Dr. Mao has taught several courses since 2012 at Shenzhen Polytechnic University, including GIS for Transportation, Traffic Engineering Cartography, and Traffic Information Processing. She has a long-standing dedication to educating future professionals in the field of urban planning and transportation technology.

 

📖Top Noted Publications

Multiple sclerosis lesions segmentation based on 3D voxel enhancement and 3D alpha matting

Authors: Sun, Y., Zhang, Y., Wang, X., Zeng, Z., Mao, H.
Journal: Chinese Journal of Medical Physics
Year: 2022

Customer attractiveness evaluation and classification of urban commercial centers by crowd intelligence

Authors: Mao, H., Fan, X., Guan, J., Wang, Y., Xu, C.
Journal: Computers in Human Behavior
Year: 2019

 When Taxi Meets Bus: Night bus stop planning over large-scale traffic data

Authors: Xiao, L., Fan, X., Mao, H., Lu, P., Luo, S.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Characterizing On-Bus WiFi passenger behaviors by approximate search and cluster analysis

Authors: Jiang, M., Fan, X., Zhang, F., Mao, H., Liu, R.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Efficient visibility analysis for massive observers

Authors: Wang, W., Tang, B., Fan, X., Yang, H., Zhu, M.
Conference: Procedia Computer Science
Year: 2017

Web access patterns enhancing data access performance of cooperative caching in IMANETs

Authors: Fan, X., Cao, J., Mao, H., Zhao, Y., Xu, C.
Conference: Proceedings – IEEE International Conference on Mobile Data Management
Year: 2016