The traditional methods of indoor positioning, such as fingerprinting and sensor-based techniques, have long been utilized but come with significant drawbacks. These drawbacks include the need for extensive training data, poor scalability, and reliance on additional sensor information. These limitations hinder the effectiveness and efficiency of indoor navigation solutions, leading to the demand for more
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The impact of climate change on soil carbon is a topic of increasing concern among scientists. Recent research conducted by Lawrence Livermore National Laboratory (LLNL) and collaborators has shed light on the vulnerability of soil organic carbon to microbial decomposition under warmer temperatures associated with climate change. While soil has the potential to sequester large
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Polymer systems have the unique ability to spontaneously induce emulsion or microdroplets through mechanical mixing, creating an intermediate state of macroscopic phase separation. However, the challenge lies in the nonuniform size and random spatial arrangement of these droplets, which tend to grow larger over time in a process known as coarsening. Researchers have attempted to
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The ability to recognize emotions is a fundamental aspect of human communication. Non-verbal cues play a significant role in conveying emotions, and researchers are now exploring whether machines can accurately predict emotional undertones in voice recordings. A recent study conducted in Germany delved into this topic by comparing the accuracy of machine learning models in
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In a recent perspective paper published in Nature Machine Intelligence, researchers from the Oxford Martin Programme on Ethical Web and Data Architectures (EWADA) at the University of Oxford have shed light on the importance of a more thoughtful approach in embedding ethical principles in the development and governance of AI specifically for children. While there
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