Multimedia Data Delivery Based on IoT Clouds
A method for reducing delivery delays for multimedia data produced by the Internet of Things.
Research and Advances
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Scaling Up Chatbots for Corporate Service Delivery Systems
A future-state architectural strategy designed to support chatbot integration with service delivery systems.
Collaborations between two communities have unearthed a sweet spot for future programming efforts.
Optimal Auctions Through Deep Learning
We overview recent research results that show how tools from deep learning are shaping up to become a powerful tool for the automated design of near-optimal auctions.
eBP: An Ear-Worn Device for Frequent and Comfortable Blood Pressure Monitoring
We developed eBP to measure blood pressure from inside a user's ear aiming to minimize the measurement's impact on normal activities while maximizing its comfort level.
Technical Perspective: eBP Rides the Third Wave of Mobile Health
The automated blood pressure wearable system described in "eBP," by Nam Bui et al., is a sterling example of the third wave of mobile health tech to fill the preventative care gap.
Technical Perspective: The Quest for Optimal Multi-Item Auctions
"Optimal Auctions Through Deep Learning," by Paul Dütting et al., contributes a very interesting and forward-looking new take on the optimal multi-item mechanism computational challenge, initiating the use of deep learning for mechanism design.
How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding language?
The Harm in Conflating Aging With Accessibility
Including older adults as full stakeholders in digital society.
Flexible Work and Personal Digital Infrastructures
PDIs are emerging as alternative sociotechnical infrastructures to enhance flexible work arrangments.
Spatial Concepts in the Conversation With a Computer
Conversing about places with a computer poses a range of challenges to current AI.
A Year in Lockdown: How the Waves of COVID-19 Impact Internet Traffic
We review the impact of the first year of the COVID-19 pandemic on Internet traffic in order to analyze its performance.
Technical Perspective: Tracking Pandemic-Driven Internet Traffic
"A Year in Lockdown," by Anja Feldmann, et al., offers a detailed look at how Internet traffic changed during the COVID-19 pandemic.
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 that hold between physical quantities from data using dimensional analysis to drastically narrow down the space of hypotheses.
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 system.
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 domain with large compute and on-chip storage requirements.
CoCoPIE: Enabling Real-Time AI on Off-the-Shelf Mobile Devices via Compression-Compilation Co-Design
A new framework allows intelligence on mainstream end devices without special hardware.
Dynamics of Gender Bias in Computing
A new dataset significantly revises both scholarly assessment and popular understanding about gender bias in computing.
On the Requirements Engineer Role
The requirements engineer role is defined differently within most organizations.
Securing Internet Applications from Routing Attacks
Application-layer and network-layer defenses are critical for fortifying routing attacks.
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.
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 by rethinking the digital/analog boundary.
Shaping the Foundations of Programming Languages
ACM A.M. Turing Award recipients Alfred Aho and Jeffrey Ullman discuss their early work, the 'Dragon Book,' and the future of 'live' computer science education.
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 workload partitioning and non-uniform latency effects on deep neural network performance.
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