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MARL: Multimodal Attentional Representation Learning for Disease Prediction
(
Springer Science and Business Media Deutschland GmbH
, 2021 , Conference Paper)
Existing learning models often utilise CT-scan images to predict lung diseases. These models are posed by high uncertainties that affect lung segmentation and visual feature learning. We introduce MARL, a novel Multimodal ...
Machine Learning-based Regression and Classification Models for Oil Assessment of Power Transformers
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Expensive and widely used power and distribution transformers need to be monitored to ensure the reliability of the power grid. Evaluating the transformer oil different parameters is vital to determine the transformer ...
Securing Smart Grid Communication using Ethereum Smart Contracts
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Smart grids are being continually adopted as a replacement of the traditional power grid systems to ensure safe, efficient, and cost-effective power distribution. The smart grid is a heterogeneous communication network ...
Finding Behavioural and Imaging Biomarkers of Major Depressive Disorder (MDD) using Artificial Intelligence: A Review
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Major Depressive Disorder (MDD) is a serious ailment in mental health and is a medical illness that has a debilitating impact on a person's ability to think effectively. According to the World Health Organization (WHO), ...
Empathy and Persona of English vs. Arabic Chatbots: A Survey and Future Directions
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Conference Paper)
There is a high demand for chatbots across a wide range of sectors. Human-like chatbots engage meaningfully in dialogues while interpreting and expressing emotions and being consistent through understanding the user's ...
Degradation of 4-chlorophenol through cooperative reductive and oxidative processes in an electrochemical system
(
Elsevier B.V.
, 2023 , Conference Paper)
Electrochemical treatment can be an effective approach for degrading recalcitrant organic contaminants because its anode/cathode produces powerful oxidizing/reducing conditions. Herein, through the cooperation of the ...
Detection of Appliance-Level Abnormal Energy Consumption in Buildings Using Autoencoders and Micro-moments
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Conference Paper)
The detection of anomalous energy usage could help significantly in signaling energy wastage and identifying faulty appliances, especially if the individual power traces are analyzed. To that end, this paper proposes a ...
The Emergence of Hybrid Edge-Cloud Computing for Energy Efficiency in Buildings
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Conference Paper)
Edge computing is attracting an increasing attention presently even though most of the building energy efficiency solutions are still using cloud computing for gathering, pre-processing and analyzing energy data. However, ...
Cloud energy micro-moment data classification: A platform study
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Energy efficiency is a crucial factor in the wellbeing of our planet. In parallel, Machine Learning (ML) plays an instrumental role in automating our lives and creating convenient workflows for enhancing behavior. So, ...
On the applicability of 2D local binary patterns for identifying electrical appliances in non-intrusive load monitoring
(
Springer
, 2021 , Conference Paper)
In recent years, the automatic identification of electrical devices through their power consumption signals finds a variety of applications in smart home monitoring and non-intrusive load monitoring (NILM). This work ...