23 papers · ranked by Valyu relevance
Hutchatai Chanlekha, Ai Kawazoe, Nigel Collier
Background Current public concern over the spread of infectious diseases has underscored the importance of health surveillance systems for the speedy detection of disease outbreaks. Several international report-based monitoring systems have been developed, including GPHIN, Argus, HealthMap, and BioCaster. A vital…
Van Long Ho, Nguyen Ho, Torben Bach Pedersen
—Very large time series are increasingly available from an ever wider range of IoT-enabled sensors, from which significant insights can be obtained through mining temporal patterns from them. A useful type of patterns found in many real-world applications exhibits periodic occurrences, and is thus called seasonal…
Xiangjian Jiang, Yanyi Pu
Dynamic Graph Neural Networks (DGNNs) have emerged as the predominant approach for processing dynamic graph-structured data. However, the influence of temporal information on model performance and robustness remains insufficiently explored, particularly regarding how models address prediction tasks with different time…
Sayani Gupta, Rob Hyndman, Dianne Cook, Antony Unwin
Deconstructing a time index into time granularities can assist in exploration and automated analysis of large temporal data sets. This paper describes classes of time deconstructions using linear and cyclic time granularities. Linear granularities respect the linear progression of time such as hours, days, weeks and…
Jiani Huang, He Yan, Qixiu Chen, Yingan Liu + 1 more
Traffic flow forecasting is integral to transportation to avoid traffic accidents and congestion. Due to the heterogeneous and nonlinear nature of the data, traffic flow prediction is facing challenges. Existing models only utilize plain historical data for prediction. Inadequate use of temporal information has become…
Fan Zhou, Pan Chen, Lintao Ma, Yu Liu + 8 more
'Jun Zhou' 'Hongyuan Mei' 'Weitao Lin' 'Zi Zhuang' 'Wenxin Ning' 'Yunhua Hu'] Time series forecasts of different temporal granularity are widely used in real-world applications, e.g., sales prediction in days and weeks for making different inventory plans. However, these tasks are usually solved separately without…
Weigang Ma, Chaohui Zhang, Ling Chen, Zhoukai Wang + 3 more
'Yingan Cui' 'Jiawei Xiang'] The axle-box bearing is a critical load-bearing component in high-speed trains and is prone to failure under long-term heavy-duty operation, affecting both operational efficiency and safety. Current deep-learning-based fault diagnosis methods face two key challenges: difficulty in capturing…
Richard K. Darst, Clara Granell, Alex Arenas, Sergio Gómez + 2 more
'Jari Saramäki' 'Santo Fortunato'] Most complex systems are intrinsically dynamic in nature. The evolution of a dynamic complex system is typically represented as a sequence of snapshots, where each snapshot describes the configuration of the system at a particular instant of time. This is often done by using constant…
Tony Lindeberg
This article presents an overview of a theory for performing temporal smoothing on temporal signals in such a way that: (i) temporally smoothed signals at coarser temporal scales are guaranteed to constitute simplifications of corresponding temporally smoothed signals at any finer temporal scale (including the original…
Zahra M. Aghajan, Gabriel Kreiman, Itzhak Fried
The representation of time in the brain is a fundamental component of cognition. Here we investigated how the human brain represents time during a temporally continuous uninterrupted experience by presenting fifteen neurosurgical patients with an audiovisual video while recording neurons’ activity from multiple brain…
Rui Cao, John H. Bladon, Stephen J. Charczynski, Michael E. Hasselmo + 1 more
The Weber-Fechner law proposes that our perceived sensory input increases with physical input on a logarithmic scale. Hippocampal “time cells” carry a record of recent experience by firing sequentially during a circumscribed period of time after a triggering stimulus. Different cells have “time fields” at different…
Shanglin Zhou, Sotiris C. Masmanidis, Dean V. Buonomano
Converging evidence suggests the brain encodes time in time-varying patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Temporal tasks that require producing the same time-dependent output patterns may have distinct computational requirements in regard to the need to exhibit…
Qun Ye, Yi Hu, Yixuan Ku, Kofi Appiah + 1 more
The human brain parsimoniously situates past events by their order in relation to time. Here, we show the posteromedial cortex geometrically abstracts the time intervals separating pairs of event-moments in long-term, episodic memory. Transcranial magnetic stimulation targeted at the precuneus erases these locally…
Fernanda Dantas Bueno, Vanessa C. Morita, Raphael Y. de Camargo, Marcelo B. Reyes + 2 more
The ability to process time on the scale of milliseconds and seconds is essential for behaviour. A growing number of studies have started to focus on brain dynamics as a mechanism for temporal encoding. Although there is growing evidence in favour of this view from computational and in vitro studies, there is still a…
Matthew Bailey, Mark Wilson
One of the critical tools of persistent homology is the persistence diagram. We demonstrate the applicability of a persistence diagram showing the existence of topological features (here rings in a 2D network) generated over time instead of space as a tool to analyse trajectories of biological networks. We show how the…
Lynn J. Lohnas, M. Karl Healey, Lila Davachi
Although life unfolds continuously, experiences are generally perceived and remembered as discrete events. Accumulating evidence suggests that event boundaries disrupt temporal representations and weaken memory associations. However, less is known about the consequences of event boundaries on temporal representations…
Javier Valenzuela, Daniel Alcaraz Carrión
This study investigates how typological and metaphorical construal differences may affect the use and frequency of temporal expressions in English and Spanish. More precisely, we explore whether there are any differences between English, a satellite-framed language, and Spanish, a verb-framed language, in the use of…
Authors not listed
Aerial surveys, while effective in detecting emissions from upset conditions, face challenges in fully capturing CH4 emissions due to their temporal limitations, variability in measurements, and detection thresholds. Conversely, annual inventories submitted by operators likely don’t include emissions from failure…
Authors not listed
Accurate prediction of chemical reaction yields remains essential for accelerating synthesis optimization, yet current machine learning models face critical limitations in capturing temporal dynamics, providing calibrated uncertainty estimates, and explicitly modeling reactant-to-product transformations. Here we…
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Accurately modeling the dynamics of open quantum systems is critical for advancing quantum technologies, yet traditional methods often struggle with balancing accuracy and efficiency. Machine learning (ML) offers a promising alternative, particularly through recursive models that predict system evolution based on the…
Ja Y. Lee, Kristen A. Lindquist, Chang S. Nam
There is debate about whether emotional granularity, the tendency to label emotions in a nuanced and specific manner, is merely a product of labeling abilities, or a systematic difference in the experience of emotion during emotionally evocative events. According to the Conceptual Act Theory of Emotion (CAT) ([4])…
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A framework for catalysis based on categorical aperture selection rather than temporal acceleration is presented. Traditional catalysis theory describes catalysts as agents that accelerate reactions by lowering activation energies, implicitly treating time as the fundamental variable and reaction rate enhancement as…
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This work establishes theoretical foundations for hierarchical quantum-classical algorithm design, where complex problems are decomposed across multiple spatial, temporal, or organizational scales with quantum and classical computation assigned to appropriate levels. We develop a mathematical framework that…