Results 51 to 60 of about 931,753 (278)
Convolutional Echo‐State Network with Random Memristors for Spatiotemporal Signal Classification
Advanced Intelligent Systems, 2022 The unprecedented development of Internet of Things results in the explosion of spatiotemporal signals generated by smart edge devices, leading to a surge of interest in real‐time learning of such data.
Shaocong Wang +19 more
doaj +1 more source
Dietary Protein Intake and Peritoneal Protein Losses in Peritoneal Dialysis Patients
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Introduction Peritoneal dialysis (PD) patients lose protein in their waste dialysate, potentially increasing their risk for malnutrition. We wished to determine whether there was any association between losses and dietary protein intake (DPI). Methods DPI was assessed from 24‐h dietary recall using Nutrics software.
Haalah Shaaker, Andrew Davenport
wiley +1 more source
Exploiting drain-erase scheme in ferroelectric FETs for logic-in-memory
Neuromorphic Computing and EngineeringThe conventional computing platforms based on von-Neumann architecture are highly space- and energy-intensive while handling the emerging applications such as AI, ML, and big data. To overcome the von Neumann bottleneck, compact and light-weight logic-in-
Musaib Rafiq +2 more
doaj +1 more source
A Comparative Study of Reservoir Computing for Temporal Signal Processing [PDF]
, 2014 Reservoir computing (RC) is a novel approach to time series prediction using recurrent neural networks. In RC, an input signal perturbs the intrinsic dynamics of a medium called a reservoir.
Banda, Peter +4 more
core +2 more sources
Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system
FEBS Letters, EarlyView.Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley +1 more source
MRAM-Based Analog Computing-In-Memory Macro With Reconfigurable In-Memory Reference ADC
IEEE AccessA compact $64\times 64$ magnetic RAM (MRAM)-based analog computing-in-memory (ACIM) macro is presented, co-optimizing in-memory techniques to overcome the inherently small read margin of MRAM-based ACIM.
Kyung Min Lee +7 more
doaj +1 more source
Flash Memory Array for Efficient Implementation of Deep Neural Networks
Advanced Intelligent Systems, 2021 The advancement of artificial intelligence applications is promoted by developing deep neural networks (DNNs) with increasing sizes and putting forward higher computing power requirements of the processing devices.
Runze Han +5 more
doaj +1 more source
CIDAN-XE: Computing in DRAM with Artificial Neurons
Frontiers in Electronics, 2022 This paper presents a DRAM-based processing-in-memory (PIM) architecture, called CIDAN-XE. It contains a novel computing unit called the neuron processing element (NPE).
Gian Singh +3 more
doaj +1 more source
Molecular Oncology, EarlyView.Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson +9 more
wiley +1 more source
A survey on processing-in-memory techniques: Advances and challenges
Memories - Materials, Devices, Circuits and Systems, 2023 Processing-in-memory (PIM) techniques have gained much attention from computer architecture researchers, and significant research effort has been invested in exploring and developing such techniques.
Kazi Asifuzzaman +4 more
doaj +1 more source