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关键词： Computer science   Electrical and electronic engineering   Mechanical engineering  

摘要： Imagine being in a crowded room with a cacophony of speakers and having the ability to focus on or remove speech from a specific 2D region. This would require understanding and manipulating an acoustic scene, isolating each speaker, and associating a 2D spatial context with each constituent speech. However, separating speech from a large number of concurrent speakers in a room into individual streams and identifying their precise 2D locations is challenging, even for the human brain. Here, we present the first acoustic swarm that demonstrates cooperative navigation with centimeter-resolution using sound, eliminating the need for cameras or external infrastructure. Our acoustic swarm forms a self-distributing wireless microphone array, which, along with our attention-based neural network framework, lets us separate and localize concurrent human speakers in the 2D space, enabling speech zones. Our evaluations showed that the acoustic swarm could localize and separate 3-5 concurrent speech sources in real-world unseen reverberant environments with median and 90-percentile 2D errors of 15 cm and 50 cm, respectively. Our system enables applications like mute zones (parts of the room where sounds are muted), active zones (regions where sounds are captured), multi-conversation separation and location-aware interaction. Want to mute or focus on speech from a specific region in a crowded room? Here, the authors built an acoustic swarm that, along with neural networks, separates and localizes concurrent speakers in the 2D space with high precision.

关键词： Computer science   Computational methods   Characterization and analytical techniques  

摘要： Understanding the nature and origin of collective excitations in materials is of fundamental importance for unraveling the underlying physics of a many-body system. Excitation spectra are usually obtained by measuring the dynamical structure factor, S(Q, omega), using inelastic neutron or x-ray scattering techniques and are analyzed by comparing the experimental results against calculated predictions. We introduce a data-driven analysis tool which leverages 'neural implicit representations' that are specifically tailored for handling spectrographic measurements and are able to efficiently obtain unknown parameters from experimental data via automatic differentiation. In this work, we employ linear spin wave theory simulations to train a machine learning platform, enabling precise exchange parameter extraction from inelastic neutron scattering data on the square-lattice spin-1 antiferromagnet La2NiO4, showcasing a viable pathway towards automatic refinement of advanced models for ordered magnetic systems. Analysis of experimental data in condensed matter is often challenging due to system complexity and slow character of physical simulations. The authors propose a framework that combines machine learning with theoretical calculations to enable real-time analysis for electron, neutron, and x-ray spectroscopies.

摘要： In 1972, ten members of the machine intelligence research community travelled to Lake Como, Italy, for a conference on the ‘social implications of machine intelligence research’. This paper explores their varied and contradictory approaches to this topic. Researchers, including John McCarthy, Donald Michie and Richard Gregory, raised ‘ethical’ questions surrounding their research and actively predicted risks of machine intelligence. At the same time, they delayed any action to mitigate these risks to an uncertain future where technical capabilities were greater. I argue that conference participants’ claims that 1972 was ‘too early’ to speculate on societal impacts of their research were disingenuous, motivated both by threats to funding and by researchers’ own politically informed speculation on the future.

摘要： Interdisciplinarity has over the recent years have gained tremendous importance and has become one of the key ways of doing cutting edge research‡. In this paper we attempt to model the citation flow across three different fields - Physics (PHY), Mathematics (MA) and Computer Science (CS). For instance, is there a specific pattern in which these fields cite one another? We carry out experiments on a dataset comprising more than 1.2 million articles taken from these three fields. We quantify the citation interactions among these three fields through temporal bucket signatures. We present numerical models based on variants of the recently proposed relay-linking framework to explain the citation dynamics across the three disciplines. These models make a modest attempt to unfold the underlying principles of how citation links could have been formed across the three fields over time. Copyright © 2023, The Authors. All rights reserved.

关键词： Computer science   Artificial intelligence   Artificial intelligence applications  

摘要： Severe weather conditions pose a significant challenge for computer vision algorithms in autonomous driving applications, particularly regarding robust-ness. Image rain-removal algorithms have emerged as a potential solution by leveraging the power of neural networks to restore rain-free backgrounds in images. However, existing research overlooks the vulnerability concerns in neural networks, which exposes a potential threat to the intelligent perception of autonomous vehicles in rainy conditions. This paper proposes a universal rain-removal attack (URA) that exploits the vulnerability of image rain-removal algorithms. By generating a non-additive spatial perturbation, URA significantly diminishes scene restoration similarity and image quality. The imperceptible and generic perturbation employed by URA makes it a crucial tool for vulnera-bility detection in image rain-removal algorithms and a potential real-world AI attack method. Experimental results demonstrate that URA can reduce scene repair capability by 39.5% and image generation quality by 26.4%, effectively targeting state-of-the-art rain-removal algorithms.

关键词： Contracts   Servers   Internet of Things   Computer science   Resource management   Streaming media   Device-to-device communication   Augmented reality (AR)   computational caching   contract theory   virtual reality (VR)  

摘要： The proliferation of novel infotainment services, such as virtual reality (VR)-based services, has fundamentally changed the existing mobile networks. These bandwidth-hungry services expanded at a tremendously rapid pace, thus, generating a burden of data traffic in the mobile networks. To cope with this issue, one can use multiaccess edge computing (MEC) to bring the resource to the edge. By doing so, we can release the burden of the core network by taking the communication, computation, and caching resources nearby the end users (UEs). Nevertheless, due to the vast adoption of VR-enabled devices, MEC resources might be insufficient in peak times or dense settings. To overcome these challenges, we propose a system model where the service provider (SP) might rent unmanned area vehicles (UAVs) from UAV SPs (USPs) to serve as micro-base stations (UBSs) that expand the service area and improve the spectrum efficiency. In which, UAV can precached certain sets of VR-based contents and serve UEs via air-to-ground (A2G) communication. Furthermore, future intelligent devices are capable of 5G and B5G communication interfaces, and thus, they can communicate with UAVs via A2G links. By doing so, we can significantly reduce a considerable amount of data traffic in mobile networks. In order to successfully enable such kinds of services, an attractive incentive mechanism is required. Therefore, we propose a contract theory-based incentive mechanism for UAV-assisted MEC in VR-based infotainment services, in which the MEC offers an amount reward to a UAV for serving as a UBS in a specific location for certain time slots. We then derive an optimal contract-based scheme with individual rationality and incentive compatibility conditions. The numerical findings show that our proposed approach outperforms the linear pricing (LP) technique and is close to the optimal solution in terms of social welfare. Additionally, our proposed scheme significantly enhanced the fairness of utility for

关键词： Computational biology and bioinformatics   Computer science   RNA vaccines  

摘要： Messenger RNA (mRNA) vaccines are being used to combat the spread of COVID-19 (refs. (1-3)), but they still exhibit critical limitations caused by mRNA instability and degradation, which are major obstacles for the storage, distribution and efficacy of the vaccine products(4). Increasing secondary structure lengthens mRNA half-life, which, together with optimal codons, improves protein expression(5). Therefore, a principled mRNA design algorithm must optimize both structural stability and codon usage. However, owing to synonymous codons, the mRNA design space is prohibitively large-for example, there are around 2.4 x 10(632) candidate mRNA sequences for the SARS-CoV-2 spike protein. This poses insurmountable computational challenges. Here we provide a simple and unexpected solution using the classical concept of lattice parsing in computational linguistics, where finding the optimal mRNA sequence is analogous to identifying the most likely sentence among similar-sounding alternatives(6). Our algorithm LinearDesign finds an optimal mRNA design for the spike protein in just 11 minutes, and can concurrently optimize stability and codon usage. LinearDesign substantially improves mRNA half-life and protein expression, and profoundly increases antibody titre by up to 128 times in mice compared to the codon-optimization benchmark on mRNA vaccines for COVID-19 and varicella-zoster virus. This result reveals the great potential of principled mRNA design and enables the exploration of previously unreachable but highly stable and efficient designs. Our work is a timely tool for vaccines and other mRNA-based medicines encoding therapeutic proteins such as monoclonal antibodies and anti-cancer drugs(7,8).

摘要： Forest degradation is a serious environmental issue that has significant implications for ecological stability, biodiversity, and human well-being. Identifying the extent and severity of forest degradation is crucial for effective management and conservation of forest ecosystems. The objective of this study was to assess the ecological vulnerability of the forest in the Dadabad region using spatial analysis and landscape metrics. The land cover map of the area was divided into 13 sub-basins to quantify landscape metrics, and the severity of human activities, degradation level, and ecological vulnerability were calculated for each sub-basin. Each sub-basin was evaluated as a single landscape to determine the extent of degradation, and landscape zoning was performed based on the degradation coefficients. The study found that sub-basins 2 and 4 had the highest levels of degradation, while sub-basins 3, 7, 8, 11, and 12 were the least degraded. Over half of the Dadabad region, 37.8% for protection and 32.25% for rehabilitation, was recommended for conservation planning. The research highlights the importance of using spatial analysis of landscape metrics to assist managers and planners in protecting and conserving natural areas.

摘要： From smart sensors that infringe on our privacy to neural nets that portrayrealistic imposter deepfakes, our society increasingly bears the burden ofnegative, if unintended, consequences of computing innovations. As the expertsin the technology we create, Computer Science (CS) researchers must do betterat anticipating and addressing these undesirable consequences proactively. Ourprior work showed that many of us recognize the value of thinking preemptivelyabout the perils our research can pose, yet we tend to address them only inhindsight. How can we change the culture in which considering undesirableconsequences of digital technology is deemed as important, but is not commonlydone? © 2023, CC BY.

关键词： Computer science   Peer review   Publishing  

摘要： Manuscripts that don’t disclose AI assistance are slipping past peer reviewers.