Tesfay Gidey | Artificial Intelligence | Best Researcher Award

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Dr. Tesfay Gidey | Artificial Intelligence | Best Researcher Award

Lecturer, Addis Ababa Science and Technology University, Ethiopia

Tesfay Gidey Hailu is a highly skilled Information and Communication Engineer and data scientist with a passion for leveraging data to drive innovation and business insights. With expertise in computer science, software engineering, machine learning, and data analytics, he excels in problem-solving, leadership, and technology project management. Tesfay’s work focuses on indoor localization, signal processing, and health data applications, making him a forward-thinking leader in his field. His dedication to continuous learning and delivering actionable results underscores his impressive career in academia and industry. 💼🔧📊

Publication Profile

ORCID

Strengths for the Award:

  1. Diverse Expertise: Tesfay’s expertise spans across critical areas such as signal processing, indoor localization, machine learning, data fusion, and health informatics, aligning well with cutting-edge research areas.
  2. Impressive Academic Qualifications: Holding a Ph.D. in Information and Communication Engineering, along with two MSc degrees, he possesses deep knowledge in interdisciplinary fields.
  3. Research Contributions: He has authored numerous peer-reviewed publications in high-impact journals such as Sensors, Intelligent Information Management, and Journal of Biostatistics. His work in Wi-Fi indoor positioning, predictive modeling, and health informatics shows a broad application of research across industries.
  4. Leadership in Academia: His roles as Associate Dean and Head of Department demonstrate his leadership in driving research, improving curriculum quality, and promoting technology transfer.
  5. Innovative Research Focus: His Ph.D. dissertation on transfer learning for fingerprint-based indoor positioning and various data fusion methods reflect his innovative contributions to solving real-world problems with advanced technologies.

Areas for Improvement:

  1. Broader Industry Impact: While his research is highly academic, incorporating more industry-driven collaborations or commercial applications could strengthen the practical impact of his work.
  2. Public Engagement: Increasing public outreach and collaboration with non-academic sectors or public talks could elevate his visibility and expand the impact of his research findings.
  3. Global Collaboration: Expanding his research collaborations beyond local and regional levels, particularly with international industries, could further showcase the global relevance of his work.

Education 🎓

Tesfay holds a Ph.D. in Information and Communication Engineering from the University of Electronic Science and Technology of China (2023), where his research centered on signal and information processing applied to indoor positioning using machine learning algorithms. He also earned an MSc in Software Engineering from HILCOE School of Computer Science and Information Technology (2018) and an MSc in Health Informatics and Biostatistics from Mekelle University (2013). Additionally, he completed his BSc in Statistics with a minor in Computer Science at Addis Ababa University (2006). 📚💻📈

Experience 💼

Tesfay has held several leadership positions, including Associate Dean at Addis Ababa Science and Technology University (AASTU), where he led research, technology transfer, student recruitment, and faculty training initiatives. He was also the Head of Department and Coordinator at Jimma University, contributing to curriculum enhancement and student retention programs. His experience spans research in manufacturing industries, project management, and academic administration. 🏫📊👨‍🏫

Research Focus 🔬

Tesfay’s research focuses on signal processing, indoor localization, machine learning, data mining, and information fusion. He specializes in developing advanced models for indoor positioning systems, predictive modeling, and statistical quality control, aiming to solve complex problems in health informatics, manufacturing industries, and public health. His work integrates cutting-edge technologies to advance both theoretical and applied fields. 📡📉🤖

Awards and Honors 🏆

Tesfay has been recognized for his contributions to the fields of information and communication engineering and data science. He has received multiple awards and honors for his research and leadership roles in academia, particularly in driving innovative projects that bridge the gap between technology and industry. 🌍🎖️

Publications Highlights 📚

Tesfay has published extensively in top-tier journals, with a focus on indoor positioning systems, data fusion, and health informatics. His research includes the development of novel machine learning models and statistical analysis tools. His works have been widely cited, showcasing his impact in the academic community. 📊✍️

MultiDMet: Designing a Hybrid Multidimensional Metrics Framework to Predictive Modeling for Performance Evaluation and Feature Selection (2023). Intelligent Information Management, 15, 391-425. Cited by 2 articles. Link

Data Fusion Methods for Indoor Positioning Systems Based on Channel State Information Fingerprinting (2022). Sensors, 22, 8720. Cited by 15 articles. Link

Heterogeneous Transfer Learning for Wi-Fi Indoor Positioning Based Hybrid Feature Selection (2022). Sensors, 22, 5840. Cited by 10 articles. Link

OHetTLAL: An Online Transfer Learning Method for Fingerprint-Based Indoor Positioning (2022). Sensors, 22, 9044. Cited by 5 articles. Link

A Multilevel Modeling Analysis of the Determinants and Cross-Regional Variations of HIV Testing in Ethiopia (2016). J Biom Biostat, 7, 277. Cited by 8 articles. Link

Conclusion:

Tesfay Gidey Hailu’s robust academic background, extensive research portfolio, and leadership roles make him a strong candidate for the Best Research Award. His work in signal processing, machine learning, and data-driven innovation in health informatics and communication systems demonstrates a clear commitment to advancing technology and solving societal problems. While his impact could be enhanced by deeper industry collaborations and global outreach, his current achievements already reflect substantial contributions to the field, making him deserving of recognition.

 

Christopher Ekeocha | Machine learning | Best Researcher Award

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Mr. Christopher Ekeocha | Machine learning | Best Researcher Award

Graduate Research Assistant, Africa Centre of Excellence in Future Energies and Electrochemical Systems (ACE-FUELS), Nigeria

Christopher Ikechukwu Ekeocha is a dedicated Assistant Research Fellow at the National Mathematical Centre in Abuja, Nigeria, with a keen interest in corrosion mitigation and environmental pollution. His extensive research focuses on developing innovative eco-friendly materials and computational simulation techniques to address corrosion and pollution challenges. He has represented Nigeria internationally at the International Chemistry Olympiad, guiding students to success in countries like Vietnam, Azerbaijan, Georgia, France, and China. 🌍🔬

Publication Profile

ORCID

Strengths for the Award:

  1. Academic Excellence: Christopher Ikechukwu Ekeocha has consistently performed at a high academic level throughout his education. His Ph.D. in Corrosion Technology (CGPA: 4.60/5.0) and Master’s in Environmental Chemistry (CGPA: 3.92/5.0) demonstrate his dedication to research and academic rigor.
  2. Innovative Research: His focus on developing eco-friendly, biomass-based anti-corrosion materials and using machine learning models for corrosion prediction is cutting-edge. His work combines experimental and computational techniques, pushing the boundaries of corrosion technology.
  3. Strong Publication Record: Ekeocha has published extensively in reputable, high-impact journals, with topics ranging from corrosion inhibitors to environmental chemistry. This demonstrates the relevance and quality of his work. Key publications include machine learning models and computational simulations for anti-corrosion research, which have been well-received in the scientific community.
  4. Interdisciplinary Collaboration: He has collaborated on multidisciplinary projects promoting circular economy and eco-friendly techniques for corrosion mitigation. His ability to work across various fields shows adaptability and leadership in research.
  5. Community Contribution: In addition to his academic work, Ekeocha has made significant contributions to the Chemistry Olympiad, leading Nigerian teams and authoring textbooks. His role in this capacity speaks to his leadership and commitment to education and knowledge dissemination.

Areas for Improvement:

  1. Research Diversification: While Ekeocha has made strong contributions in corrosion technology, expanding his research to other areas of environmental chemistry or further enhancing the practical applications of his work could strengthen his overall profile. Engaging in more diverse projects could showcase his versatility.
  2. Industry Engagement: Although his research is well-grounded in academia, there could be a stronger connection with industry to ensure his innovations, especially in corrosion mitigation, are applied in real-world settings. Collaborations with companies focusing on corrosion prevention or environmental impact assessments could enhance the practical impact of his research.
  3. International Recognition: While his publications are gaining recognition, presenting his research at more international conferences or collaborating with foreign institutions could boost his global visibility and increase the influence of his work.

Education

Christopher Ekeocha is affiliated with the Africa Centre of Excellence in Future Energies and Electrochemical Systems (ACE-FUELS) at the Federal University of Technology, Owerri (FUTO). His research emphasizes the permeation of ions across semi-permeable membranes, focusing on membrane thickness, permeation time, and electrolyte concentration. 🎓⚛️

Experience

With over a decade of experience, Christopher Ekeocha has served as an Assistant Research Fellow at the National Mathematical Centre, Abuja, since 2011. He leads Nigeria’s participation in the International Chemistry Olympiad, having represented the country in multiple international events. His expertise lies in corrosion studies, computational modeling, and eco-friendly corrosion inhibitors. 🌱🔧

Research Focus

Christopher’s research centers on the development of mathematical and predictive models for novel corrosion inhibitors. He specializes in using computational simulations and eco-friendly materials to mitigate metallic corrosion and conducting ecological risk assessments of environmental pollution. His work also covers adsorption kinetics, water and solvent treatment using nanoparticles, and pollutant removal with agricultural waste. 📊🔍

Awards and Honours

Ekeocha has gained recognition for his contributions to corrosion research and environmental protection. His participation in the International Chemistry Olympiad as a Nigerian team leader is notable, alongside his extensive academic publications and active role in global scientific conferences. 🏆🌟

Publication Top Notes

Christopher Ikechukwu Ekeocha has authored several influential articles in prestigious journals, including Materials Today Communications, Structural Chemistry, and African Scientific Reports. His works primarily focus on corrosion inhibition, eco-friendly materials, and environmental pollution. 📚✨

Ekeocha, C. I., et al. (2024). Data-Driven Machine Learning Models and Computational Simulation Techniques for Prediction of Anti-Corrosion Properties of Novel Benzimidazole Derivatives. Materials Today Communications https://doi.org/10.1016/j.mtcomm.2024.110156

Ekeocha, C. I., et al. (2024). Theoretical Study of Novel Antipyrine Derivatives as Promising Corrosion Inhibitors for Mild Steel in an Acidic Environment. Structural Chemistry https://doi.org/10.1007/s11224-024-02368-4

Ekeocha, C. I., et al. (2023). Review of Forms of Corrosion and Mitigation Techniques: A Visual Guide. African Scientific Reports, 2(3): 117. https://doi.org/10.46481/asr.2023.2.3.117

Conclusion:

Christopher Ikechukwu Ekeocha is an excellent candidate for the Research for Best Research Award. His innovative contributions in the field of corrosion technology, combined with his interdisciplinary approach and strong academic background, position him well for recognition. His research aligns with global trends toward eco-friendly solutions and computational advancements, making him a strong contender. However, increased industry engagement and further research diversification would further elevate his impact in both academic and practical domains.

 

Avirup Roy | Machine Learning |Machine Learning Research Award

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Mr. Avirup Roy | Machine Learning |Machine Learning Research Award

PhD Student, Michigan State University, United States

Dr. Avirup Roy is a dedicated researcher and engineer specializing in networked embedded and wireless systems. Currently pursuing his PhD at Michigan State University, his work focuses on developing self-learning mechanisms for embedded hardware systems with limited computational resources. With a solid foundation in electronics and communication engineering, Avirup has gained extensive experience in both academia and industry, contributing to projects ranging from smart malaria detection to automated power management systems. His technical skills span machine learning, embedded systems, cloud computing, and web development. Beyond his professional life, Avirup is passionate about Indian classical music, photography, and swimming. 🌟📚🎵📷🏊‍♂️

Profile

ORCID

 

Education🎓

Michigan State University, East Lansing, MI, US PhD in Electrical and Computer Engineering (2020-Present). Dissertation: Self-learning mechanisms for Embedded hardware systems with limited computational resources. GPA: 3.75/4Maulana Abul Kalam Azad University of Technology, Kolkata, WB, India Bachelor of Technology (BTech) in Electronics and Communication Engineering (2013-2017)

Experience💼

Graduate Research Assistant, Michigan State University (Sep 2020 – Jul 2023),Developed an android and website application for smart malaria detection involving cloud database integration. Graduate Teaching Assistant, Michigan State University (Aug 2023 – Present), Instructed and graded labs for Embedded Cyber-physical Systems, VLSI Systems, and Digital Control courses. ICER Cloud Computing Fellow, Michigan State University (Sep 2023 – Present), Implemented Azure cloud resources in semi-supervised federated learning for embedded devices. Programmer Analyst, Cognizant Technology Solutions (Dec 2017 – Jul 2020), Developer and support analyst for ASP.NET based applications of MetLife Inc. Intern, Calcutta Electric Supply Corporation (CESC) Limited (Jul 2016 – Aug 2016), Worked on automated power management systems using SCADA communication. Intern, Bharat Sanchar Nigam Limited (BSNL) (Jun 2015 – Aug 2015), Explored general trends in wireless communication. Undergraduate Researcher, Maulana Abul Kalam Azad University of Technology (2015-2016), Presented research at various international conferences and served as the vice-president of SPIE Student Chapter.

Research Interests🔍

Embedded Machine Learning: Focused on developing efficient learning algorithms for resource-constrained devices.
Networked Embedded Systems: Exploring self-learning mechanisms and their applications in real-world scenarios.
Cloud Computing: Leveraging cloud resources for semi-supervised federated learning.
VLSI Systems: In-depth study and teaching of Very-Large-Scale Integration systems.
Cyber-Physical Systems: Research on embedded systems interacting with physical processes.

Awards🏆

National Social Entrepreneurship Programme (2014): Secured 2nd position for the ‘Hand-Made Paper Industry’ project.
SPIE Smart Structures and Non-destructive Evaluation Conference (2016): Presented research in Las Vegas, Nevada.
EAPE Conference (2015): Presented research on emerging areas of photonics and electronics.
Graduate Fellowships: Awarded multiple fellowships during PhD for research and teaching excellence.

Publications

Semi-Supervised Learning Using Sparsely Labelled Sip Events for Online Hydration Tracking Systems
A. Roy, H. Dutta, A. K. Bhuyan, and S. K. Biswas, 2023, International Conference on Machine Learning and Applications (ICMLA).
Cited by: 3 articles.

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation
Roy, A., Dutta, H., Griffith, H., & Biswas, S., 2022, Sensors.
Cited by: 5 articles.

GAN XU | Computer Science | Best Researcher Award

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Mr. GAN XU | Computer Science | Best Researcher Award

PhD. candidate, capital university of economics and business, China

Xu Gan is a Doctoral student at Capital University of Economics and Business, Beijing, specializing in Rural Finance, Financial Theory and Policy, and Supply Chain Finance. With a solid academic background and practical experience, Xu has contributed significantly to research in financial services and blockchain technology. 🏛️📚

Profile

Scopus

 

Education

Xu Gan completed a Master of Finance from Capital University of Economics and Business in Beijing (2018-2021) and a Bachelor of Biotechnology from Beijing Union University (2006-2010). Xu also has an extensive academic background in these fields, providing a strong foundation for research and analysis. 🎓📈

Experience

Xu has actively participated in several high-profile research projects, including the National Social Science Foundation of China’s research on rural financial services and the China Mobile Communication Federation’s blockchain technology applications in finance. Xu was responsible for designing research sub-topics and writing research reports. 📊🔬

Research Interests

Xu Gan’s research interests include Rural Finance, Financial Theory and Policy, and Supply Chain Finance. Xu is focused on improving rural financial services and exploring innovative financial technologies such as blockchain. 🌾💡

Awards

Xu has been recognized for academic excellence with several honors: Beijing Outstanding Graduates (2020), Outstanding Graduate of Beijing Union University (2020), and several awards for excellent papers at various financial and rural finance forums. 🏅📜

Publications

Yang, GZ., Xu, G., Zhang, Y., et al. Financial density of village banks and income growth of rural residents. Economic Issues, 2021, 504(08): 89-94.

Zhang, F., Xu, G., Zhang, XY, Cheng, X. Knowledge mapping analysis of seven decades of rural finance research in China. Rural Finance Research, 2020(01): 10-20.

Zhang, F., Xu, G., Cheng, X. A review of blockchain applications in the financial sector. Technology for Development, 2019, 15(08): 865-871.

Hafiza Sadia Nawaz | Computer Science | Women Researcher Award

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Dr. Hafiza Sadia Nawaz | Computer Science | Women Researcher Award

Shenzhen University, China

🎓 Dr. H. Sadia Nawaz is a distinguished researcher and academic in Computer Vision, with a Ph.D. from Ocean University of China. Her work focuses on Temporal Activity Detection using Natural Language. With a background in both teaching and research, she has contributed significantly to the field of computer vision and continues to pursue a career as a postdoctoral researcher. Her extensive knowledge and dedication to the subject make her a valuable asset to any research group.

Profile

Scopus

 

Education

📚 Dr. H. Sadia Nawaz holds a Ph.D. in Computer Science from Ocean University of China, specializing in Temporal Moment Localization using Natural Language. She also completed her Master’s in Information Science and Technology at the University of Sargodha and an MS in Computer Science and Technology with a focus on Cyber Security at the University of Lahore. Her academic background provides a strong foundation for her research and teaching roles.

Experience

💼 Dr. Nawaz has a robust teaching background, having served as a Programming Teaching Assistant at Heriot-Watt University and Ocean University of China, and as a Computer Science Lecturer at Superior University of Lahore and the University of Sargodha. Her roles in academia have honed her skills in teaching, mentoring, and research, contributing to her expertise in computer vision and machine learning.

Research Interests

🔍 Dr. Nawaz’s research interests include Activity Localization in Videos via Language, Temporal Moment Detection, and Natural Language Processing. She is particularly focused on moment detection in complex scenarios and the integration of machine learning methods with computer vision techniques to enhance video understanding and activity localization.

Awards

🏅 Dr. H. Sadia Nawaz has been recognized for her research contributions in the field of computer vision, particularly for her work on Temporal Moment Localization using Natural Language. Her research has been published in high-impact journals, reflecting her expertise and commitment to advancing the field.

Publications

Temporal Moment Localization via Natural Language by Utilizing Video Question Answers as a Special Variant and Bypassing NLP for Corpora

IVTEN – Integration of Visual-Textual Entities for Temporal Activity Localization via Language in Video

Revelation of Novel Paradigm in Temporal Moment Localization by Using Natural Language in Video

Multi-level Edges and Context Arranger Architecture Using Referencing Expressions for Temporal Moment Localization via Natural Language

A Frame-Based Feature Model for Violence Detection from Surveillance Cameras Using ConvLSTM Network

Omar Soufi | Artificial Intelligence | Best Researcher Award

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Dr. Omar Soufi | Artificial Intelligence | Best Researcher Award

Doctorate, Mohammed V University of Rabat Mohammadia School of Engineering, Morocco

👨‍💼 Dr. Omar Soufi is a distinguished Computer Science Engineer specializing in Artificial Intelligence, Data Science, Remote Sensing, and Geographic Information Systems (GIS). With a robust background in data analysis and decision-support systems, Dr. Soufi excels in promoting organizational advancements and enhancing strategic performance through well-planned recommendations. His proactive and industrious approach ensures the achievement of objectives by leveraging data-driven insights.

Profile

ORCID

Education

🎓 Dr. Omar Soufi earned his Ph.D. in Computer Science Engineering with a focus on Artificial Intelligence from EMI Rabat in 2023, completing his doctoral research with the AMIPS/E3S team. He also holds a degree in Engineering from Polytechnique Grenoble, ENSIMAG, and EMI Rabat, specializing in Information Systems Engineering and Software Quality Engineering, respectively. His foundational studies include a Diploma and a Bachelor’s degree in Mechanical Engineering from ARM Merkèns.

Experience

💼 Dr. Soufi’s professional journey includes notable roles such as Project Manager in the IT Department, Team Leader at the Decision Support Center, Head of the BI & Decision Tools Department, Head of the Geomatics & Decision Tools Division, and AI Mission Manager. His expertise spans numerous projects in artificial intelligence and data science, including the development of national geospatial platforms, disaster risk management systems, and SaaS solutions for real estate asset management and financial risk analysis.

Research Interests

🔍 Dr. Soufi’s research focuses on applying deep learning techniques to satellite image super-resolution and spacecraft attitude control. His interests extend to big data architecture, distributed systems, and geospatial data analysis, aiming to enhance the accessibility and quality of high-resolution satellite imagery.

Awards

🏆 Dr. Soufi has been recognized for his contributions to artificial intelligence and remote sensing. He has received certifications in various professional and personal development areas, including PMO, coaching, and personal development, further solidifying his expertise and commitment to excellence in his field.

Publications

📄 Study of deep learning-based models for single image super-resolution. Soufi, O., Belouadha, F.Z. (2022). Revue d’Intelligence Artificielle, Vol. 36, No. 6, pp. 939-952. https://doi.org/10.18280/ria.360616

📄 FSRSI: New deep learning-based approach for super-resolution of multispectral satellite images. Soufi, O., Belouadha, F.Z. (2023). Ingénierie des Systèmes d’Information, Vol. 28, No. 1, pp. 113-132. https://doi.org/10.18280/isi.280112

📄 Deep learning technique for image satellite processing. O. Soufi and F.Z- Belouadha. Intell Methods Eng Sci, vol. 2, no. 1, pp. 27–34, Mar. 2023.

📄 Enhancing Accessibility to High-Resolution Satellite Imagery: A Novel Deep Learning-Based Super-Resolution Approach. O. Soufi and F.Z- Belouadha. Journal of Environmental Treatment Techniques, 11(2), 44-49, 2023.

📄 An intelligent deep learning approach to spacecraft attitude control: the case of satellites. O. Soufi and FZ.- Belouadha. (2023). (Under Review)

Nabi Mehri Khansari | Machine Learning | Best Researcher Award

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Dr. Nabi Mehri Khansari | Machine Learning | Best Researcher Award

University Professor, Sahand University of Technology, Iran

Dr. Nabi Mehri-Khansari is an esteemed Assistant Professor at the Sahand University of Technology. With a rich academic background in Mechanical and Aerospace engineering from prestigious institutions like Iran University of Science and Technology and the University of Tehran, he has made significant contributions to the field. His research spans failure analysis, damage and fracture mechanics in lightweight composite structures, leveraging machine learning and deep learning. Dr. Mehri-Khansari has collaborated with various international research centers and industries, enhancing his expertise and impact in the field.

Profile

Scopus

Education

🎓 Dr. Nabi Mehri-Khansari obtained his B.Sc. degree in Mechanical Engineering from the Iran University of Science and Technology in 2011. He pursued his M.Sc. and Ph.D. degrees in Aerospace Engineering from the University of Tehran, completing them in 2014 and 2018, respectively. His academic excellence is marked by being ranked 2nd in M.Sc. and 1st in Ph.D., earning acceptance with quotas for talented students. He also served as a research fellow at NTNU University, Trondheim, Norway, further broadening his academic horizons.

Experience

🔧 Dr. Mehri-Khansari has an extensive professional background. He has been a faculty member at the Sahand University of Technology since January 2019. Prior to this, he was a lecturer at the University of Tehran – North Branch, a research assistant at NTNU University in Norway, and a technical expert at the Iranian Space Institute. His diverse roles reflect his versatile expertise and commitment to advancing engineering education and research.

Research Interests

🔬 Dr. Mehri-Khansari’s research interests are vast and interdisciplinary. They include wind turbine technology, multi-scale fracture mechanics of composites and inhomogeneous media, multi-scale damage mechanics, aeroelasticity, and defect detection methods. His innovative work often incorporates machine learning and deep learning techniques, pushing the boundaries of traditional engineering research.

Awards

🏅 Dr. Mehri-Khansari has received numerous accolades throughout his career. These include the prestigious Ph.D. acceptance with quotas for talented students, being ranked 1st in his Ph.D. program at the University of Tehran, and the Best Teacher Award from the Sahand University of Technology in June 2024. His membership in professional organizations such as the American Society of Mechanical Engineering and the Iranian Composites Scientific Association further underscores his professional excellence.

Publications

Orthotropic failure criteria based on machine learning and micro-mechanical matrix adapting coefficient
Mixed-modes (I/III) fracture of aluminum foam based on micromechanics of damage
Micro-mechanical damage diagnosis methodologies based on machine learning and deep learning models
Numerical & experimental assessment of mixed-modes (I/II) fracture of PMMA/hydroxyapatite nanocomposite