21 papers · ranked by Valyu relevance
Wing-kin Tam, Matthew F. Nolan
Accurate decoding of neural signals often requires assigning extracellular waveforms acquired on the same electrode to their originating neurons, a process known as spike sorting. While many offline sorters are available, accurate online sorting of spikes with many channels is still a challenging problem. Existing…
Masaya Misaki, Jerzy Bodurka, Martin P Paulus
Real-time fMRI (rtfMRI)has enormous potential for both mechanistic brain imaging studies or treatment-oriented neuromodulation. However, the adaption of rtfMRI has been limited due to technical difficulties implement an efficient computational framework. Here, we introduce a python library for real-time fMRI (rtfMRI)…
Giovanni Diraco, Gabriele Rescio, Pietro Siciliano, Alessandro Leone + 1 more
'Anthony Fleury'] Smart living, a concept that has gained increasing attention in recent years, revolves around integrating advanced technologies in homes and cities to enhance the quality of life for citizens. Sensing and human action recognition are crucial aspects of this concept. Smart living applications span…
Lei Wang, Yinlin Chen, Emma Scaletti Hutchinson, Pål Stenmark + 3 more
Three-dimensional electron diffraction (3D ED), also known as microcrystal electron diffraction (MicroED), is an emerging method for determining structures of submicron-sized crystals. With the development of rapid and convenient data collection protocols, acquiring dozens of datasets in a single MicroED session has…
Mengxi Tan, Xingyuan Xu, Andreas Boes, Bill Corcoran + 7 more
'Thach G. Nguyen' 'Sai T. Chu' 'Brent E. Little' 'Roberto Morandotti' 'Jiayang Wu' 'Arnan Mitchell' 'David J. Moss'] Signal processing has become central to many fields, from coherent optical telecommunications, where it is used to compensate signal impairments, to video image processing. Image processing is…
V. V. Gligorov, V. Reković
We review the status of, and prospects for, real-time data processing for collider experiments in experimental High Energy Physics. We discuss the historical evolution of data rates and volumes in the field and place them in the context of data in other scientific domains and commercial applications. We review the…
Ouiam Khattach, Omar Moussaoui, Mohammed Hassine, Manuel José Cabral dos Santos Reis + 1 more
'Manuel José Cabral dos Santos Reis' 'Nishu Gupta'] The rapid proliferation of Internet of Things (IoT) devices across industries has created a need for robust, scalable, and real-time data processing architectures capable of supporting intelligent analytics and predictive maintenance. This paper presents a novel…
Soundes Oumaima Boufaida, Abdemadjid Benmachiche, Majda Maâtallah
Embedded vision systems need efficient and robust image processing algorithms to perform real-time, with resource-constrained hardware. This research investigates image processing algorithms, specifically edge detection, corner detection, and blob detection, that are implemented on embedded processors, including DSPs…
Luís Miguel Pinho
Real-time systems applications usually consist of a set of concurrent activities with timing-related properties. Developing these applications requires programming paradigms that can effectively handle the specification of concurrent activities and timing constraints, as well as controlling their execution on a…
Liu, Wenyi, Rahul Sharma, Guo + 3 more
Digital twin (DT) enables smart manufacturing by leveraging real-time data, AI models, and intelligent control systems. This paper presents a state-of-the-art analysis on the emerging field of DTs in the context of milling. The critical aspects of DT are explored through the lens of virtual models of physical milling…
Suneth Samarasinghe, Ira Deveson, Hasindu Gamaarachchi
Nanopore sequencers allow sequencing data to be accessed in real-time. This allows live analysis to be performed, while the sequencing is running, reducing the turnaround time of the results. We introduce realfreq, a framework for obtaining real-time base modification frequencies while a nanopore sequencer is in…
Casado, Constantino Álvarez, Sharifipour, Sasan + 8 more
The growing integration of smart environments and low-power computing devices, coupled with mass-market sensor technologies, is driving advancements in remote and non-contact physiological monitoring. However, deploying these systems in real-time on resource-constrained platforms introduces significant challenges…
Michael Lührs, Benedikt A Poser, Tibor Auer, Rainer Goebel
One of the significant challenges in real-time fMRI environments is to ensure that the functional images are exported in real-time. The prerequired ability to reconstruct these images immediately after the acquisition has already been resolved in 2004. Nowadays, more sophisticated sequences allow for higher resolution…
Ana Almeida, Susana Brás, Susana Sargento, Filipe Cabral Pinto
Big data has a substantial role nowadays, and its importance has significantly increased over the last decade. Big data’s biggest advantages are providing knowledge, supporting the decision-making process, and improving the use of resources, services, and infrastructures. The potential of big data increases when we…
Luca Longo, Richard B. Reilly, Jerritta Selvaraj
Electroencephalographic signals are obtained by amplifying and recording the brain’s spontaneous biological potential using electrodes positioned on the scalp. While proven to help find changes in brain activity with a high temporal resolution, such signals are contaminated by non-stationary and frequent artefacts. A…
Sarah J. A. Carr, Weicong Chen, Jeremy Fondran, Harry Friel + 3 more
Introduction: Functional magnetic resonance imaging (fMRI) often involves long scanning durations to ensure the associated brain activity can be detected. However, excessive experimentation can lead to many undesirable effects, such as from learning and/or fatigue effects, discomfort for the subject, excessive motion…
Pablo Quijano Velasco, Kedar Hippalgaonkar, Balamurugan Ramalingam
The discovery of optimal conditions of chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and Design of Experiments where one…
Rama El-khawaldeh, Mason Guy, Finn Bork, Nina Taherimakhsousi + 6 more
This work presents a generalizable computer vision (CV) and machine learning model that is used for automated real-time monitoring and control of a diverse array of workup processes. Our system simultaneously monitors multiple physical parameters (e.g., liquid level, homogeneity, turbidity, solid, residue, and color)…
Peter Sagmeister, Lukas Melnizky, Jason Williams, C. Oliver Kappe
In modern pharmaceutical research, the demand for expeditious development of synthetic routes to active pharmaceutical ingredients (APIs) has led to a paradigm shift towards data-rich process development. Conventional methodologies en-compass prolonged timelines for reaction and analytical model developments. Both…
Marios Fragkoulis, Paris Carbone, Vasiliki Kalavri, Asterios Katsifodimos
'Asterios Katsifodimos'] Abstract Stream processing has been an active research field for more than 20 years, but it is now witnessing its prime time due to recent successful efforts by the research community and numerous worldwide open-source communities. This survey provides a comprehensive overview of fundamental…
Yu Shen
Alzheimer's disease (AD) is a neurodegenerative disorder that affects millions of people worldwide. Early screening is crucial to prevent potential damages, and researchers are exploring alternative approaches such as multiplexed assays and emerging technologies such as microfluidics, nanotechnology, and biosensors.…