21 papers · ranked by Valyu relevance
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…
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…
Tongya Zheng, Gang Chen, Xinyu Wang, Chun Chen + 2 more
'Sihui Luo'] Abstract Human beings keep exploring the physical space using information means. Only recently, with the rapid development of information technologies and the increasing accumulation of data, human beings can learn more about the unknown world with data-driven methods. Given data timeliness, there is a…
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)…
Stephan Heunis, Rolf Lamerichs, Svitlana Zinger, Cesar Caballero‐Gaudes + 3 more
Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non-invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy…
Maninder Singh, Mohammad A. Hoque, Sasu Tarkoma
The immense growth of data demands switching from traditional data processing solutions to systems, which can process a continuous stream of real time data. Various applications employ stream processing systems to provide solutions to emerging Big Data problems. Open-source solutions such as Storm, Spark Streaming, and…
Byounghoon Kim, Shobha Kenchappa, Adhira Sunkara, Ting-Yu Chang + 3 more
Modern neuroscience research often requires the coordination of multiple processes such as stimulus generation, real-time experimental control, as well as behavioral and neural measurements. The technical demands required to simultaneously manage these processes with high temporal fidelity limits the number of labs…
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…
Syed Ijaz Ahmad Bukhari
Real Time Data Warehouse (RTDW) is a simulation of working of human brain. Every human brain consists of approximately one billion neurons which pass data in the shape of signals to each other via synaptic connections (about thousand trillion). The brain continuously receives sensory information; refresh its data…
Pablo Garaizar, Miguel A. Vadillo, Diego López-de-Ipiña, Helena Matute + 1 more
'Helena Matute' 'Suliann Ben Hamed'] Because of the features provided by an abundance of specialized experimental software packages, personal computers have become prominent and powerful tools in cognitive research. Most of these programs have mechanisms to control the precision and accuracy with which visual stimuli…
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…
Giuseppe Conti, Marcos Quintana, Pedro Malagón, David Jiménez
This paper presents a study on the optimization of the tracking system designed for patients with Parkinson’s disease tested at a day hospital center. The work performed significantly improves the efficiency of the computer vision based system in terms of energy consumption and hardware requirements. More specifically…
Massimiliano Leone Itria, Alessandro Daidone, Andrea Ceccarelli
—In modern advanced emergency management systems many solutions for decision support have been provided as attempts to support humans to take important decisions for the critical situations recovery. The critical situation detection is a complex procedure that involves both human and machine activities and leads to…
David R. Jenkins, Alastair Basden, Richard M. Myers
We propose a solution to the increased computational demands of Extremely Large Telescope (ELT) scale adaptive optics (AO) real-time control with the Intel Xeon Phi Knights Landing (KNL) Many Integrated Core (MIC) Architecture. The computational demands of an AO real-time controller (RTC) scale with the fourth power of…
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…
Gabriel Weindel, Leendert van Maanen, Jelmer P. Borst
Measuring the time-course of neural events that make up cognitive processing is crucial to understand the relation between brain and behavior. To this aim, we formulated a method to discover a trial-wise sequence of events in multivariate neural signals such as electro- or magneto-encephalograpic (E/MEG) recordings.…
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.…