Communications of the ACM
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From Communications of the ACM
Technical Perspective: Sensing Interaction with Everyday Objects Using Near-Field Communication in Textiles
"Locating Everyday Objects Using NFC Textiles," by Jingxian Wang et al., describes the potential of Near-Field Communication for advanced home automation.
From Communications of the ACM
Locating Everyday Objects Using NFC Textiles
This paper builds a Near-Field Communication-based localization system that allows ordinary surfaces to locate surrounding objects with high accuracy in the near...
From Communications of the ACM
Technical Perspective: On Abstractions and Embedded Networks
"Symbol-Synchronous Buses," by Jonathan Oostvogels et al., conceives a notion of a symbol-synchronous bus, which effectively makes a multi-hop wireless network...
From Communications of the ACM
Symbol-Synchronous Buses: Deterministic, Low-Latency Wireless Mesh Networking with LEDs
We describe a novel networking paradigm that aims to enable a new class of latency-sensitive applications by systematically breaking networking abstractions.
From Communications of the ACM
Technical Perspective: The Power of Low-Power GPS Receivers for Nanosats
The work explored in "Hummingbird," by Sujay Narayana et al., focuses on the energy consumption of a typical GPS receiver and its operational challenges in a nanosat...
From Communications of the ACM
Hummingbird: An Energy-Efficient GPS Receiver for Small Satellites
In this work, we elucidate the design of a low-cost, low-power GPS receiver for small satellites.
From Communications of the ACM
Technical Perspective: Physical Layer Resilience through Deep Learning in Software Radios
"Polymorphic Wireless Receivers," by Francesco Restuccia and Tommaso Melodia, tackles the problem of physical layer resilience in wireless systems from a completely...
From Communications of the ACM
Polymorphic Wireless Receivers
We introduce PolymoRF, a deep learning-based polymorphic receiver able to reconfigure itself in real time based on the inferred waveform parameters.
From Communications of the ACM
Technical Perspective: hXDP: Light and Efficient Packet Processing Offload
In "hXDP: Efficient Software Packet Processing on FPGA NICs," the authors offer an interesting solution to bridging the performance gap between the CPU and the...
From Communications of the ACM
hXDP: Efficient Software Packet Processing on FPGA NICs
We present hXDP, a solution to run on FPGAs software packet processing tasks described with the eBPF technology and targeting the Linux's eXpress Data Path.
From Communications of the ACM
Technical Perspective: Leveraging Social Context for Fake News Detection
In "FANG," the authors focus on a strategy of automatically detecting disinformation campaigns on online media with a new graph-based, contextual technique for...
From Communications of the ACM
FANG: Leveraging Social Context for Fake News Detection Using Graph Representation
We propose Factual News Graph (FANG), a novel graphical social context representation and learning framework for fake news detection.
From Communications of the ACM
Technical Perspective: An Elegant Model for Deriving Equations
"Deriving Equations from Sensor Data Using Dimensional Function Synthesis," by Vasileios Tsoutsouras, et al., addresses the key problem of discovering relationships...
From Communications of the ACM
Deriving Equations from Sensor Data Using Dimensional Function Synthesis
We present a new method, which we call dimensional function synthesis, for deriving functions that model the relationship between multiple signals in a physical...
From Communications of the ACM
Technical Perspective: Race Logic Presents a Novel Form of Encoding
"In-Sensor Classification With Boosted Race Trees," by Georgios Tzimpragos, et al., proposes a surprising, novel, and creative approach to post-Moore's Law computing...
From Communications of the ACM
In-Sensor Classification With Boosted Race Trees
We demonstrate the potential of a novel form of encoding, race logic, in which information is represented as the delay in the arrival of a signal.
From Communications of the ACM
Technical Perspective: A Chiplet Prototype System for Deep Learning Inference
"Simba," by Yakun Sophia Shao, et al., presents a scalable deep learning accelerator architecture that tackles issues ranging from chip integration technology to...
From Communications of the ACM
Simba: Scaling Deep-Learning Inference with Chiplet-Based Architecture
This work investigates and quantifies the costs and benefits of using multi-chip-modules with fine-grained chiplets for deep learning inference, an application...
From Communications of the ACM
Technical Perspective: Solving the Signal Reconstruction Problem at Scale
"Scalable Signal Reconstruction for a Broad Range of Applications," by Abolfazl Asudeh, et al. shows that algorithmic insights about SRP, combined with database...
From Communications of the ACM