97 citations · 447 across the 15 of their papers we have counts for
15 papers
Data-driven building energy efficiency prediction using physics-informed neural networks
Vasilis Michalakopoulos, Sotiris Pelekis, Giorgos Kormpakis +3
The analytical prediction of building energy performance in residential buildings based on the heat losses of its individual envelope components is a challenging task. It is worth…
Transfer learning for day-ahead load forecasting: a case study on European national electricity demand time series
Alexandros-Menelaos Tzortzis, Sotiris Pelekis, Evangelos Spiliotis +3
Short-term load forecasting (STLF) is crucial for the daily operation of power grids. However, the non-linearity, non-stationarity, and randomness characterizing electricity demand…
Multimodal Detection of Bots on X (Twitter) using Transformers
Loukas Ilias, Ioannis Michail Kazelidis, Dimitris Askounis
Although not all bots are malicious, the vast majority of them are responsible for spreading misinformation and manipulating the public opinion about several issues, i.e., election…
DeepTSF: Codeless machine learning operations for time series forecasting
Sotiris Pelekis, Evangelos Karakolis, Theodosios Pountridis +4
This paper presents DeepTSF, a comprehensive machine learning operations (MLOps) framework aiming to innovate time series forecasting through workflow automation and codeless model…
Multitask learning for recognizing stress and depression in social media
Loukas Ilias, Dimitris Askounis
Stress and depression are prevalent nowadays across people of all ages due to the quick paces of life. People use social media to express their feelings. Thus, social media constit…
Calibration of Transformer-based Models for Identifying Stress and Depression in Social Media
Loukas Ilias, Spiros Mouzakitis, Dimitris Askounis
In today's fast-paced world, the rates of stress and depression present a surge. Social media provide assistance for the early detection of mental health conditions. Existing metho…
Context-aware attention layers coupled with optimal transport domain adaptation and multimodal fusion methods for recognizing dementia from spontaneous speech
Loukas Ilias, Dimitris Askounis
Alzheimer's disease (AD) constitutes a complex neurocognitive disease and is the main cause of dementia. Although many studies have been proposed targeting at diagnosing dementia t…
Targeted demand response for flexible energy communities using clustering techniques
Sotiris Pelekis, Angelos Pipergias, Evangelos Karakolis +4
The present study proposes clustering techniques for designing demand response (DR) programs for commercial and residential prosumers. The goal is to alter the consumption behavior…
A comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers
Sotiris Pelekis, Ioannis-Konstantinos Seisopoulos, Evangelos Spiliotis +4
Short-term load forecasting (STLF) is vital for the effective and economic operation of power grids and energy markets. However, the non-linearity and non-stationarity of electrici…
Neural Architecture Search with Multimodal Fusion Methods for Diagnosing Dementia
Michail Chatzianastasis, Loukas Ilias, Dimitris Askounis +1
Alzheimer's dementia (AD) affects memory, thinking, and language, deteriorating person's life. An early diagnosis is very important as it enables the person to receive medical help…
A Multimodal Approach for Dementia Detection from Spontaneous Speech with Tensor Fusion Layer
Loukas Ilias, Dimitris Askounis, John Psarras
Alzheimer's disease (AD) is a progressive neurological disorder, meaning that the symptoms develop gradually throughout the years. It is also the main cause of dementia, which affe…
Comparison of Missing Data Imputation Methods using the Framingham Heart study dataset
Konstantinos Psychogyios, Loukas Ilias, Dimitris Askounis
Cardiovascular disease (CVD) is a class of diseases that involve the heart or blood vessels and according to World Health Organization is the leading cause of death worldwide. EHR…
Detecting Dementia from Speech and Transcripts using Transformers
Loukas Ilias, Dimitris Askounis, John Psarras
Alzheimer's disease (AD) constitutes a neurodegenerative disease with serious consequences to peoples' everyday lives, if it is not diagnosed early since there is no available cure…
Explainable Identification of Dementia from Transcripts using Transformer Networks
Loukas Ilias, Dimitris Askounis
Alzheimer's disease (AD) is the main cause of dementia which is accompanied by loss of memory and may lead to severe consequences in peoples' everyday life if not diagnosed on time…
Designing a Cyber-security Culture Assessment Survey Targeting Critical Infrastructures During Covid-19 Crisis
Anna Georgiadou, Spiros Mouzakitis, Dimitris Askounis
The paper at hand presents the design of a survey aiming at the cyber-security culture assessment of critical infrastructures during the COVID-19 crisis, when living reality was he…