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The Choice of Evaluation Metrics in the Prediction of Epileptiform Activity
In this study, we investigate the problem of prediction of epileptiform activity from EEG data using a deep learning approach. We implement LSTM deep...
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CBGA: A deep learning method for power grid communication networks service activity prediction
The prediction of power equipment activity plays a vital role in optimizing power resource dispatch, ensuring supply and demand balance, and guiding...
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Partial Alignment of Time Series for Action and Activity Prediction
The temporal alignment of two complete action/activity sequences has been the focus of interest in many research works. However, the problem of...
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A semantic blocks model for human activity prediction in smart environments using time-windowed contextual data
Complex human activity prediction is a difficult problem for computer science. Simple behaviours can be mapped to sequence prediction algorithms with...
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Protein Structure Prediction
ProteinsProteins are essential components of living organisms. They are composed of a linear sequence of amino acids. However, proteins only exhibit...
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A Transformer-Based Framework for Geomagnetic Activity Prediction
Geomagnetic activities have a crucial impact on Earth, which can affect spacecraft and electrical power grids. Geospace scientists use a geomagnetic...
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Multi-perspective enriched instance graphs for next activity prediction through graph neural network
Today’s organizations store lots of data tracking the execution of their business processes. These data often contain valuable information that can...
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Graphing the Future: Activity and Next Active Object Prediction Using Graph-Based Activity Representations
We present a novel approach for the visual prediction of human-object interactions in videos. Rather than forecasting the human and object motion or...
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Exploiting Instance Graphs and Graph Neural Networks for Next Activity Prediction
Nowadays, a lot of data regarding business process executions are maintained in event logs. The next activity prediction task exploits such event...
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Molecular Activity Prediction Based on Graph Attention Network
Spatial convolutional models of Graph Neural Networks (GNNs) updates embeddings of nodes by the neighborhood aggregation, it has obvious advantages...
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Outcome Prediction
This chapter focuses on how we can best predict the future health of patients, known as prognosis. This encompasses areas such as risk prediction and...
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Prediction of schizophrenia from activity data using hidden Markov model parameters
In this paper, we address the problem of predicting schizophrenia based on a persons measured motor activity over time. A key challenge to achieve...
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On prediction-modelers and decision-makers: why fairness requires more than a fair prediction model
An implicit ambiguity in the field of prediction-based decision-making concerns the relation between the concepts of prediction and decision. Much of...
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MOOCs Dropout Prediction via Classmates Augmented Time-Flow Hybrid Network
Massive Open Online Courses (MOOCs) provide learners with a platform for free learning. However, MOOCs have been criticized for high dropout rates in...
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Enhancing early action prediction in videos through temporal composition of sub-actions
Early Action Prediction (EAP) in videos aims at forecasting the action labels from partially observed videos. It is crucial in various applications,...
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Stress Prediction Using Per-Activity Biometric Data to Improve QoL in the Elderly
To improve the QoL of the elderly, it is essential to predict their stress states. In general, the stress state varies from day to day or time to...
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Real-time prediction of smoking activity using machine learning based multi-class classification model
Smoking cessation efforts can be greatly influenced by providing just-in-time intervention to individuals who are trying to quit smoking. Detecting...
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Just-in-Time crash prediction for mobile apps
Just-In-Time (JIT) defect prediction aims to identify defects early, at commit time. Hence, developers can take precautions to avoid defects when...
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Human mobility prediction with causal and spatial-constrained multi-task network
Modeling human mobility helps to understand how people are accessing resources and physically contacting with each other in cities, and thus...
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Spatiotemporal Object Detection and Activity Recognition
Spatiotemporal object detection and activity recognition are essential components in the advancement of computer vision, with broad applications...