Assoc Prof Dr. Ilyas Bolat | Challenges and Competitions | Best Researcher Award

Assoc Prof Dr. Ilyas Bolat | Challenges and Competitions | Best Researcher Award

Assoc Prof Doctorate at Bartin University, Forest Faculty, Turkey

Profiles

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Google Scholar

Summary:

Dr. Ilyas Bolat is an Associate Professor at Bartın University, specializing in forest ecology, soil science, and the impact of land-use changes on soil properties. With a focus on microbial biomass and forest nutrient dynamics, he has a strong research background in soil biology and forest ecological processes.

Education

  • Ph.D. in Forest Engineering (2008-2011), Bartın University, Turkey
    Thesis: Seasonal changes in microbial biomass and respiration in forest soils
  • Master of Arts in Forest Engineering (2005-2007), Zonguldak Karaelmas University, Turkey
    Thesis: The effect of different land uses on soil microbial biomass
  • Bachelor of Arts in Forest Engineering (1997-2001), Karadeniz Technical University, Turkey

💼 Professional Experience

  • Associate Professor (2016-present), Bartın University, Forestry Faculty
  • Assistant Professor (2011-2016), Bartın University, Forestry Faculty
  • Research Assistant (2008-2011), Bartın University, Forestry Faculty
  • Research Assistant (2005-2007), Zonguldak Karaelmas University, Forestry Faculty

🔬 Research Interests

  • Forest ecological processes and nutrient dynamics
  • Soil microbial biomass and basal respiration
  • Land-use change impacts on soil properties
  • Spatial and temporal vegetation dynamics

 

Publications

Changes in Soil Microbial Biomass and Activity under Different Land-Use Types in Bartın, Northwestern Türkiye

  • Authors: İsmail Bolat, Hasan Şensoy
  • Journal: Contemporary Problems of Ecology
  • Year: 2023
  • Authors: İsmail Bolat, Hasan Şensoy
  • Journal: Forestist
  • Year: 2023

Seasonal Changes of Microbial Biomass Carbon, Nitrogen, and Phosphorus in Soil under an Oriental Beech Stand

  • Authors: İsmail Bolat, Ömer Kara, Mustafa Tunay
  • Journal: Forestist
  • Year: 2022

Microbial biomass, basal respiration, and microbial indices of soil in diverse croplands in a region of northwestern Turkey (Bartın)

  • Authors: İsmail Bolat
  • Journal: Environmental Monitoring and Assessment
  • Year: 2019

Microbial Biomass Soil Content and Activity Under Black Alder and Sessile Oak in the Western Black Sea Region of Turkey

  • Authors: İsmail Bolat, Hasan Şensoy
  • Journal: International Journal of Environmental Research
  • Year: 2019

Dr. Mingxiu Tang | Challenges and Competitions | Best Researcher Award

Dr. Mingxiu Tang, Challenges and Competitions, Best Researcher Award

Doctorate at Beijing Normal University, China

Profile

Scopus

🌍 Academic Background:

Dr. Mingxiu Tang is a dedicated Ph.D. student at Beijing Normal University, focusing on cartography and geographic information systems. Her research addresses critical issues such as forest fires and deforestation through advanced satellite imagery, and she assesses future rainstorms to enhance predictive models and risk management.

🎓 Education:

Dr. Tang earned her B.E. in Remote Sensing Science and Technology from Shandong University of Science and Technology in 2021. She is currently pursuing a Ph.D. in Cartography and Geographic Information Systems at the Faculty of Geographical Science, Beijing Normal University.

👩‍🏫 Professional Experience:

Her work includes contributions to the global socioeconomic risk assessment of rainstorms, utilizing various CMIP6 scenarios to project future impacts. Additionally, she has developed the Temporal and Spatial Anomaly Index (TSAI) for improved fire detection, offering valuable insights into environmental and climatic challenges.

🔬 Research Interests:

Dr. Tang’s research interests are centered around the use of multimodal satellite images to study forest fires and deforestation, as well as assessing future rainstorm patterns. Her studies aim to advance understanding of environmental risks and inform better management strategies.

📖 Publications:

Multi-model ensemble bias-corrected precipitation dataset and its application in identification of drought-flood abrupt alternation in China
  • Authors: Liu, T., Zhu, X., Tang, M., Guo, C., Lu, D.
  • Journal: Atmospheric Research
  • Year: 2024
Assessment of drought risk changes in China under different temperature rise scenarios
  • Authors: Lu, D., Zhu, X., Tang, M., Guo, C., Liu, T.
  • Journal: Arid Land Geography
  • Year: 2024
Hazard analysis of rainstorms in different climatic regions of China
  • Authors: Tang, M., Sun, S., Zhu, X., Xu, K., Liu, T.
  • Journal: Journal of Natural Disasters
  • Year: 2023
Future global socioeconomic risk changes to rainstorms based on the different return periods of CMIP6
  • Authors: Tang, M., Zhu, X., Liu, T., Zhang, S., Xu, K.
  • Journal: Progress in Geography
  • Year: 2023
Hazard Changes Assessment of Future High Temperature in China based on CMIP6
  • Authors: Guo, C., Zhu, X., Zhang, S., Tang, M., Xu, K.
  • Journal: Journal of Geo-Information Science
  • Year: 2022

Challenges and Competitions

Introduction of Challenges and Competitions

Challenges and Competitions research plays a pivotal role in advancing the field of computer vision by providing platforms for researchers and practitioners to test and benchmark their algorithms and solutions. These competitions encourage innovation, foster collaboration, and push the boundaries of what is achievable in computer vision. They are instrumental in driving progress and identifying state-of-the-art solutions to complex problems.

Subtopics in Challenges and Competitions:

  1. Object Detection Challenges: Competitions in this subfield focus on evaluating object detection algorithms' performance in various scenarios, from general object detection to specific domains like autonomous driving.
  2. Image Segmentation Challenges: Researchers participate in challenges that assess the accuracy and efficiency of image segmentation techniques, facilitating advancements in this fundamental computer vision task.
  3. Visual Recognition Challenges: These competitions cover a wide range of tasks, from image classification and scene recognition to fine-grained recognition, pushing the boundaries of image understanding capabilities.
  4. Video Analysis Competitions: Challenges in video analysis assess algorithms for tasks such as action recognition, object tracking, and video captioning, addressing the unique complexities of temporal data.
  5. Medical Imaging Challenges: Competitions in medical imaging focus on improving diagnostic accuracy and image analysis in areas like radiology, pathology, and healthcare, contributing to advancements in medical research and practice.

Challenges and Competitions research enables the computer vision community to collaboratively tackle complex problems and push the field's boundaries. These subtopics represent key areas of competition and benchmarking within computer vision.

Introduction Object Detection and Recognition: Object Detection and Recognition is a vibrant and evolving field of computer vision and artificial intelligence, dedicated to the automated identification and localization of objects
Introduction Image Processing and Enhancement: Image Processing and Enhancement is a pivotal domain within the realm of computer vision and digital imaging. This field is dedicated to the development of
Introduction of Computer Vision for Robotics and Autonomous Introduction: Computer Vision for Robotics and Autonomous Systems is a multidisciplinary field at the intersection of computer vision, robotics, and artificial intelligence.
Introduction of 3D Computer Vision 3D Computer Vision is a dynamic and interdisciplinary field that aims to enable machines to perceive and understand the three-dimensional structure of the world from
Introduction of Medical Image Analysis Medical Image Analysis is a critical and rapidly evolving field that harnesses the power of computer vision and machine learning to extract valuable insights from
Introduction of Video Analysis Video Analysis and Understanding is a dynamic and interdisciplinary field that aims to develop algorithms and techniques for extracting meaningful information from video data. It plays
Introduction of Deep Learning for Computer Vision Deep Learning for Computer Vision is at the forefront of modern artificial intelligence, revolutionizing the way machines perceive and interpret visual information. It
Introduction of Applications of Computer Vision Applications of Computer Vision represent a diverse and ever-expanding landscape of practical uses for visual data analysis and interpretation. Computer vision technology has transitioned
Introduction of Human-Computer Interaction Introduction: Human-Computer Interaction (HCI) research is a multidisciplinary field that focuses on understanding and improving the interaction between humans and technology. It explores how users interact
Introduction of Biometrics and Security Biometrics and Security research is dedicated to the development of cutting-edge technologies that leverage unique physiological or behavioral characteristics of individuals for identity verification and