Browsing by Author "Alban, Ahmad Qadeib"
Now showing items 1-6 of 6
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A Goal-Oriented Fault Tolerance Software Enhanced by Critical Information Code Protection
( IEEE Computer Society , 2020 , Conference)Currently, during runtime, programs are mostly uncontrollable objects. They are very vulnerable to either transient or permanent, external, or internal contaminations of the program state. Here one finds a new method that ... -
Anomalies detection in software by conceptual learning from normal executions
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Could we detect anomalies during the run-time of a program by learning from the analysis of its previous traces for normally completed executions? In this paper we create a featured data set from program traces at run time, ... -
A Comprehensive Machine and Deep Learning Approach for Aerosol Optical Depth Forecasting: New Evidence from the Arabian Peninsula
( Springer Nature , 2024 , Article)Accurate forecasting of environmental pollution indicators holds significant importance in diverse fields, including climate modeling, environmental monitoring, and public health. In this study, we investigate a wide range ... -
Detection of challenging behaviours of children with autism using wearable sensors during interactions with social robots
( IEEE Explore , 2021 , Conference)Autism spectrum disorder is a neurodevelopmental disorder that is characterized by patterns of behaviours and difficulties with social communication and interaction. Children on the spectrum exhibit atypical, restricted, ... -
Heart Rate as a Predictor of Challenging Behaviours among Children with Autism from Wearable Sensors in Social Robot Interactions
( MDPI , 2023 , Article)Children with autism face challenges in various skills (e.g., communication and social) and they exhibit challenging behaviours. These challenging behaviours represent a challenge to their families, therapists, and caregivers, ... -
Modeling and forecasting electricity consumption amid the COVID-19 pandemic: Machine learning vs. nonlinear econometric time series models
( Elsevier , 2023 , Article)Accurately modeling and forecasting electricity consumption remains a challenging task due to the large number of the statistical properties that characterize this time series such as seasonality, trend, sudden changes, ...
