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Category: information science – Page 35

Widely utilized across various industries such as chemistry, agriculture, and military, this technology relies on strategies like dispersive optics and narrow-band light filters.

However, limitations exist in these approaches. Additionally, the fabrication of large-scale InGaAs detector arrays poses challenges, necessitating the development of new experimental methods and algorithms to advance infrared hyperspectral imaging technology in terms of miniaturization and cost-effectiveness.

In a paper published in Light Science & Applications, a team led by Professor Baoqing Sun and Yuan Gao from Shandong University introduce a novel method for encoding near-infrared spectral and spatial data.

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The study

The researchers monitored the brainwaves of 100 students as they performed a series of cognitive tasks. They then conducted a group comparison analysis between the performance of students with higher test scores (as recorded prior to the study) against those with lower test scores.

The brainwave analysis was then analyzed using algorithms running on a D-Wave quantum annealing computer. According to the researchers, the study resulted in new insights concerning how cognitive ability relates to testing outcomes.

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The three final algorithms, which have now been released, are ML-KEM, previously known as kyber; ML-DSA (formerly Dilithium); and SLH-DSA (SPHINCS+). NIST says it will release a draft standard for FALCON later this year. “These finalized standards include instructions for incorporating them into products and encryption systems,” says NIST mathematician Dustin Moody, who heads the PQC standardization project. “We encourage system administrators to start integrating them into their systems immediately.”

Duncan Jones, head of cybersecurity at the firm Quantinuum welcomes the development. “[It] represents a crucial first step towards protecting all our data against the threat of a future quantum computer that could decrypt traditionally secure communications,” he says. “On all fronts – from technology to global policy – advancements are causing experts to predict a faster timeline to reaching fault-tolerant quantum computers. The standardization of NIST’s algorithms is a critical milestone in that timeline.”

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In recent years, there have been many reviews investigating neuromorphic computing from the perspectives of device electrical properties,[ 9, 10 ] resistive switching materials,[ 11, 12 ] memristive synapses and neurons,[ 13 ] algorithm optimization,[ 14 ] and circuit design.[ 15 ] Different from the existing literature, we discuss the possibility of achieving brain-like computing from the perspective of memristor technology and review the establishment of spiking neural network neuromorphic computing systems. In this article, we first review the resistive switching mechanisms of different types of memristors and focus on factors, which affect device stability and the corresponding optimization measures that have been applied. Furthermore, we study the stochasticity, power consumption, switching speed, retention, endurance, and other properties of memristors, which are the basis for neuromorphic computing implementations. We then review various memristor-based neural networks and the building of spike neural network neuromorphic computing systems. Finally, we shed light upon the major challenges and offer our perspectives and opinions for memristor-based brain-like computing systems.

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From the article:

When Saha and Sinha took a closer look at the resulting equations, they realized that they could express the number pi in this way, as well as the zeta function, which is the heart of the Riemann conjecture, one of the greatest unsolved mysteries in mathematics.

Two physicists have come across infinitely many novel equations for pi while trying to develop a unifying theory of the fundamental forces.

By Manon Bischoff

The number pi (π) appears in the most unlikely places. It can be found in circles, of course—as well as in pendulums, springs and river bends. This everyday number is linked to transcendental mysteries. It has inspired Shakespearean thought puzzles, baking challenges and even an original song. And pi keeps the surprises coming—most recently in January 2024, when physicists Arnab Priya Saha and Aninda Sinha of the Indian Institute of Science presented a completely new formula for calculating it, which they later published in Physical Review Letters.

Continue reading “String Theorists Accidentally Find a New Formula for Pi” | >

In a paper published recently in the Journal of Applied Physics, an international team of scientists from Lawrence Livermore National Laboratory (LLNL), Argonne National Laboratory and Deutsches Elektronen-Synchrotron have developed a new sample configuration that improves the reliability of equation of state measurements in a pressure regime not previously achievable in the diamond anvil cell.

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Advancements in the field of robotics are fueled by research, which in turn heavily relies on effective platforms to test algorithms for robot control and navigation. While numerous robotics platforms have been developed over the past decades, most of them have shortcomings that limit their use in research settings.

Researchers at the University of California (UC) Berkeley recently developed Berkeley Humanoid, a new robotic platform that could be used to train and test algorithms for the control of humanoid robots. This new humanoid , introduced in a paper posted to the preprint server arXiv, addresses and overcomes some of the limitations of previously introduced robotics research platforms.

“Having conducted several experiments with commercially available robots, we have become aware of some of their weaknesses,” Qiayuan Liao, co-author of the paper, told Tech Xplore. “For instance, some robot hardware is very expensive, while other hardware is not designed especially for learning-based control or for research, which often means that it is ‘fragile,’ easy to break, and hard to maintain and repair.”

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The study, published by a multi-institutional team of researchers…

Researchers used D-Wave’s quantum computing technology to explore the relationship between prefrontal brain activity and academic achievement, particularly focusing on the College Scholastic Ability Test (CSAT) scores in South Korea.

The study, published by a multi-institutional team of researchers across Korea in Scientific Reports, relied on functional near-infrared spectroscopy (fNIRS) to measure brain signals during various cognitive tasks and then applied a quantum annealing algorithm to identify patterns correlating with higher academic performance.

The team identified several cognitive tasks that might boost CSAT score — and that could have significant implications for educational strategies and cognitive neuroscience. The use of a quantum computer as a partner in the research process could also be a step towards practical applications of quantum computing in neuroimaging and cognitive assessment.

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Organoid intelligence (OI) is an emerging scientific field aiming to create biocomputers where lab-grown brain organoids serve as ‘biological hardware’

In their article, published in Frontiers in Science, Smirnova et al., outline the multidisciplinary strategy needed to pursue this vision: from next-generation organoid and brain-computer interface technologies, to new machine-learning algorithms and big data infrastructures.

https://www.frontiersin.org/journals/.…

Citation:
Smirnova L, Caffo BS, Gracias DH, Huang Q, Morales Pantoja IE, Tang B, et al. (2023) Organoid intelligence(OI): the new frontier in biocomputing and intelligence-in-a-dish. Front. Sci. 1:1017235. doi: 10.3389/fsci.2023.

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