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2023

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Navigating The Metaverse Of Big Data: A Bibliometric Journey, O. S. Albahri, A. H. Alamoodi Jan 2023

Navigating The Metaverse Of Big Data: A Bibliometric Journey, O. S. Albahri, A. H. Alamoodi

Mesopotamian Journal of Big Data

The advent of the metaverse, an immersive digital universe, has caused a sea change in how people experience and share knowledge, fun, and community. This bibliometric study examines the vast realm of big data research into metaverses. We analyse the development, trends, and major players in this cross-disciplinary subject using bibliometric methods applied to a large database of academic publications, conference proceedings, and journals. Our study covers the years 2021–2023 and incorporates the most recent discoveries in the metaverse. In doing so, it sheds light on the intellectual landscape of metaverse-related studies by identifying the most relevant authors, publications, and …

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Chatgpt In Waste Management: Is It A Profitable, Thaeer Mueen Sahib, Hussain A. Younis, Osamah Mohammed Alyasiri, Ahmed Hussein Ali, Sani Salisu, Ameen A. Noore, Israa M. Hayder, Misbah Shahid Jan 2023

Chatgpt In Waste Management: Is It A Profitable, Thaeer Mueen Sahib, Hussain A. Younis, Osamah Mohammed Alyasiri, Ahmed Hussein Ali, Sani Salisu, Ameen A. Noore, Israa M. Hayder, Misbah Shahid

Mesopotamian Journal of Big Data

No abstract provided.

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A Novel Approach Of Reducing Energy Consumption By Utilizing Big Data Analysis In Mobile Cloud Computing, Mostafa Abdulghafoor Mohammed, Nicolae Țăpuș Jan 2023

A Novel Approach Of Reducing Energy Consumption By Utilizing Big Data Analysis In Mobile Cloud Computing, Mostafa Abdulghafoor Mohammed, Nicolae Țăpuș

Mesopotamian Journal of Big Data

With the rapid proliferation of smart mobile devices and increasing adoption of cloud computing services, energy efficiency has become an important issue in mobile cloud environments. High energy consumption not only results in higher operational costs but also creates sustainability concerns related to cloud infrastructure and services. This paper proposes leveraging big data techniques such as machine learning and predictive analytics to optimize resource allocation and reduce energy consumption in mobile cloud computing. The massive amount of data on factors like user behavior, mobility patterns, network availability, and resource utilization can provide key insights to improve energy efficiency. We present …

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Optimizing Big Data Analytics For Reliability And Resilience: A Survey Of Techniques And Applications, El-Houcine El Baqqaly, Alaa Hussein Khaleel Jan 2023

Optimizing Big Data Analytics For Reliability And Resilience: A Survey Of Techniques And Applications, El-Houcine El Baqqaly, Alaa Hussein Khaleel

Mesopotamian Journal of Big Data

The advent of big data has revolutionized various industries, enabling organizations to make data- driven decisions and gain valuable insights. However, the sheer volume, velocity, and variety of big data pose significant challenges in ensuring the reliability and resilience of big data analytics pipelines. In this context, optimization techniques play a crucial role in enhancing the reliability and resilience of big data analytics. This paper provides a comprehensive survey of optimization techniques for reliable and resilient big data analytics. The paper first discusses the motivation for optimizing big data analytics for reliability and resilience. Then, it presents a detailed overview …

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Climate Changes Through Data Science: Understanding And Mitigating Environmental Crisis, Ahmed Hussein Ali, Rahul Thakkar Jan 2023

Climate Changes Through Data Science: Understanding And Mitigating Environmental Crisis, Ahmed Hussein Ali, Rahul Thakkar

Mesopotamian Journal of Big Data

Climate change represents an urgent environmental crisis with far-reaching risks to ecosystems and human communities worldwide. Rapid development of mitigation strategies and solutions is imperative but relies profoundly on advancements in detection, attribution, and prediction derived from climate data analytics. This paper examines the growing role of data science in not only quantifying anthropogenic climate change but also informing impact assessment and targeted intervention across climate-sensitive sectors. First, we survey established and emerging techniques for climate characterization, including machine learning applications on Earth systems data. Next, we discuss how sophisticated climate models alongside statistical analysis of multi-domain datasets—from migration patterns …

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