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Found 8 papers, 0 papers with code
Towards a Flexible Scale-out Framework for Efficient Visual Data Query Processing
In this paper, we develop VDMS-Async that adds the capability to run user-defined operations with VDMS and execute operations within a query on a remote server.
CDBB West Cambridge Digital Twin: Lessons Learned
The report describes the digital architecture developed for the West Cambridge Digital Twin, particularly focussed on real-time sensor data collection and analysis with a privacy framework allowing occupants of the buildings to be first-class participants in the system.
SmartSplit: Latency-Energy-Memory Optimisation for CNN Splitting on Smartphone Environment
In this paper, we analyse the feasibility of splitting CNNs between smartphones and cloud server by formulating a multi-objective optimisation problem that optimises the end-to-end latency, memory utilisation, and energy consumption.
FedFm: Towards a Robust Federated Learning Approach For Fault Mitigation at the Edge Nodes
In this paper, we first analyse the impact of the number of edge devices on an FL model and provide a strategy to select an optimal number of devices that would contribute to the model.
Latency-Memory Optimized Splitting of Convolution Neural Networks for Resource Constrained Edge Devices
Splitting the CNN architecture to perform part of the computation on edge and remaining on the cloud is an area of research that has seen increasing interest in the field.
Data Management for Building Information Modelling in a Real-Time Adaptive City Platform
Legacy Building Information Modelling (BIM) systems are not designed to process the high-volume, high-velocity data emitted by in-building Internet-of-Things (IoT) sensors.
Human-Computer Interaction
Feature Engineering Combined with 1 D Convolutional Neural Network for Improved Mortality Prediction
The intensive care units (ICUs) are responsible for generating a wealth of useful data in the form of Electronic Health Record (EHR).
Sentiment Analysis: It's Complicated!
In datasets constructed for the purpose of Twitter sentiment analysis (TSA), these controversial examples can compose over 30{\%} of the originally annotated data.
