George Stamoulis's research while affiliated with University of Thessaly and other places

Publications (44)

Article
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The banking sector is on the eve of a serious transformation and the thrust behind it is artificial intelligence (AI). Novel AI applications have been already proposed to deal with challenges in the areas of credit scoring, risk assessment, client experience and portfolio management. One of the most critical challenges in the aforementioned sector...
Conference Paper
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With process technology scaling, accurate gate-level timing analysis becomes even more challenging. Highly resistive on-chip interconnects have an ever-increasing impact on timing, signals no longer resemble smooth saturated ramps, while gate-interconnect interdependencies are stronger. Moreover, efficiency is a serious concern since repeatedly inv...
Article
Full-text available
The aim of our study was to determine COVID-19 syndromic phenotypes in a data-driven manner using the survey results based on survey results from Carnegie Mellon University’s Delphi Group. Monthly survey results (>1 million responders per month; 320,326 responders with a certain COVID-19 test status and disease duration <30 days were included in th...
Preprint
Full-text available
The rapid growth of circuit complexity has rendered Model Order Reduction (MOR) a key enabler for the efficient simulation of large circuit models. MOR techniques based on moment-matching are well established due to their simplicity and computational performance in the reduction process. However, moment-matching methods based on the ordinary Krylov...
Article
Full-text available
Current advances in the Internet of Things (IoT) and Cloud involve the presence of an additional layer between them acting as mediator for data transfer and processing in close distance to end users. This mediator is the edge computing (EC) infrastructure. In EC, we can identify an ecosystem of heterogeneous nodes capable of interacting with IoT de...
Article
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Due to continuous CMOS technology downscaling, Integrated Circuits (ICs) have become more susceptible to radiation-induced hazards such as soft errors. Thus, to design radiation-hardened and reliable ICs, the Soft Error Rate (SER) estimation constitutes an essential procedure. An accurate SER evaluation is provided based on a SPICE-oriented electri...
Article
The preference of preschool children for interactive traditional paper books has long been proved. More novel than traditional interactive books are the Augmented Reality (AR) books, which took a place in the book market for more than a decade now. For this study, we have used the Mosaic approach as a form of participatory research. The main method...
Preprint
Fraud detection and prevention has received a lot of attention from the research community due to its high impact on financial institutions' revenues and reputation. The increased use of the Web and the provision of online services open up the pathway for exposing these systems to numerous threats and jeopardise their effective functioning. Natural...
Article
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Most public libraries, small, medium, or large, offer a variety of services, facilities and amenities to their audience, depending on the assigned functions. The ideal size of space for children in public libraries cannot be calculated according to the population that it will serve, as is often the case with school libraries, but based on the activ...
Article
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Introduction The purpose of our study is to detect and compare common, significantly enriched pathways in peripheral blood mononuclears (PBMC) and CNS tissue donated by idiopathic Parkinson's Disease (iPD) patients and compare their transcriptomic profiles with those donated by tuberculosis (TB) patients. Methods We performed comparative transcrip...
Chapter
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Forecasting fraud detection has never been more essential for the finance industry than today. The detection of fraud has been a major concern for the banking industry due to the high impact on banks’ revenues and reputation. Fraud can be related with an augmented financial risk, which is often underestimated until it is too late. Recently, deep le...
Preprint
Introduction COVID-19 has pathological pulmonary as well as several extrapulmonary manifestations and thus many different symptoms may arise in patients. The aim of our study was to determine COVID-19 syndromic phenotypes in a data driven manner using survey results extracted from Carnegie Mellon University's Delphi Group. Methods Monthly survey re...
Article
Full-text available
As process geometries shrink below 45 nm, accurate and efficient gate-level timing analysis becomes even more challenging. Modern VLSI interconnects are more resistive, signals no longer resemble saturated ramps, and gate input pins exhibit a significant Miller effect. Over recent years, the semiconductor industry has adopted current source models...
Article
Full-text available
Background IFITM3 is a viral restriction protein that enables sequestration of viral particles and subsequent trafficking to lysosomes. Recently, IFITM3 upregulation was found to induce gamma – secretase activity and the production of amyloid beta. The purpose of this study was to determine whether dysregulation of IFITM3-dependent pathways was pre...
Conference Paper
Full-text available
During the past decade, Model Order Reduction (MOR) has become key enabler for the efficient simulation of large circuit models. MOR techniques based on moment-matching are well established due to their simplicity and computational performance in the reduction process. However, moment-matching methods based on the ordinary Krylov subspace are usual...
Article
The aim of this study was to determine the interaction of peripheral immunity vs. the CNS in the setting of AD pathogenesis at the transcriptomic level in a data driven manner. For this purpose, publicly available gene expression data from the GEO Datasets repository. We performed differential gene expression and functional enrichment analyses were...
Article
Full-text available
Several studies related to treatment of Parkinson's disease, have been performed, using mechanical support methods. Most of these studies use accelerometer technology to track the patient's movement with Parkinson's disease, as it enables the recording of full motion range and acceleration in all directions, with great accuracy. With our proposed s...
Conference Paper
Full-text available
Plant diseases are major threat to green product quality and agricultural productivity. Agronomists and farmers often encounter great difficulties in early detection of plant diseases and controlling their potential production damages. Thus, it is of great importance for stakeholders to diagnose plant diseases at very early stages of plant growing...
Conference Paper
Intrusion Detection Systems (IDS) are the systems that detect and block any potential threats (e.g. DDoS attacks) in the network. In this project, we explore the performance of several machine learning techniques when used as parts of an IDS. We experiment with the CICIDS2017 dataset, one of the biggest and most complete IDS datasets in terms of ha...
Conference Paper
Full-text available
Plant diseases are major threat to green product quality and agricultural productivity. Agronomists and farmers often encounter great difficulties in early detection of plant diseases and controlling their potential production damages. Thus, it is of great importance for stakeholders to diagnose plant diseases at very early stages of plant growing...
Preprint
During the past decade, Model Order Reduction (MOR) has become key enabler for the efficient simulation of large circuit models. MOR techniques based on moment-matching are well established due to their simplicity and computational performance in the reduction process. However, moment-matching methods based on the ordinary Krylov subspace are usual...
Article
Full-text available
(1) Background: Forecasting of energy consumption demand is a crucial task linked directly with the economy of every country all over the world. Accurate natural gas consumption forecasting allows policy makers to formulate natural gas supply planning and apply the right strategic policies in this direction. In order to develop a real accurate natu...
Article
Aims The aims of our study were to determine for the first time differentially expressed genes (DEGs) and enriched molecular pathways involving the PARK7 interactome in PBMCs donated from tuberculosis patients. Methods Data on a previously reconstructed PARK7 interactome (Vavougios et al., 2017) from datasets GDS4966 (Case-Control) and GDS4781 (Tr...
Article
Full-text available
Photovoltaic Solar Energy (PSE) sector has sparked great interest from governments over the last decade towards diminution of world’s dependency to fossil fuels, greenhouse gas emissions reduction and global warming mitigation. Photovoltaic solar energy also holds a significant role in the transition to sustainable energy systems. These systems and...
Article
Full-text available
Participatory modelling is an emerging approach in the decision-making process through which stakeholders contribute to the representation of the perceived causal linkages of a complex system. The use of fuzzy cognitive maps (FCMs) for participatory modelling helps policy-makers develop dynamic quantitative models for strategising development inter...
Article
Full-text available
Every development and production process needs to operate within a circular economy to keep the human being within a safe limit of the planetary boundary. Policymakers are in the quest of a powerful and easy-to-use tool for representing the perceived causal structure of a complex system that could help them choose and develop the right strategies....
Chapter
The new era of the Internet of Things (IoT) provides the space where novel applications will play a significant role in people’s daily lives through the adoption of multiple services that facilitate everyday activities. The huge volumes of data produced by numerous IoT devices make the adoption of analytics imperative to produce knowledge and suppo...
Article
Full-text available
This paper introduced a new ensemble learning approach, based on evolutionary fuzzy cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM-ANN), for time series prediction. The main aim of time series forecasting is to obtain reasonably accurate forecasts of future data from analyzing records of data. In the paper...
Conference Paper
Fuzzy cognitive maps are graph-based models mostly constructed in a participatory setting either by experts to given domains or by a large number of stakeholders in various scientific areas (that need to be investigated) of interest. Usually each expert or stakeholder designs individually a FCM based on his/her knowledge or opinion for the specific...
Article
Efficient full-chip thermal simulation is among the most challenging problems facing the EDA industry today, due to the need for solution of very large systems of equations that require unreasonably long computational times. However, in most cases, temperature is not required to be computed at every point of the IC but only at certain hotspots, in...
Article
Full-text available
Efficient full-chip thermal simulation is among the most challenging problems facing the EDA industry today, especially for modern 3D integrated circuits, due to the huge linear systems resulting from thermal modeling approaches that require unreasonably long computational times. While the formulation problem, by applying a thermal equivalent circu...
Conference Paper
Full-text available
Developmental dyslexia is defined as an unexpected specific and persistent failure to acquire efficient reading skills despite conventional instruction, adequate intelligence and sociocultural opportunity. The main aim of the present research protocol was to construct a web screening battery of tests in order to screen children’s reading, orthograp...
Conference Paper
Full-text available
Extending network lifetime is a primary design objective for a wireless sensor network (WSN). Efficient clustering among sensor nodes seems a promising solution to evenly balance energy consumption and thus extend node and network lifetime. One of the most dominant clustering algorithms for energy efficient cluster formation is LEACH, because it ba...
Conference Paper
Learning disabilities is a generic term that refers to a heterogeneous group of disorders. The aim of the present pilot study was to examine the efficacy of a new web neurocognitive screening tool, the " askisi " that was developed to provide a brief screening measure for learning difficulties. Participants were twenty children who had been initial...

Citations

... Paper [7] deals with the effect of time and amplitude variations on the soft error rate (SER) in VLSI circuits. An accurate SER evaluation is provided based on a SPICE-oriented electrical masking analysis combined with a TCAD characterization process. ...
Reference: MOCAST 2021
... Such technology can transform normal images into 3D images, whereby students can see shapes from all angles [5,61]. A 3D view can provide students with a compelling learning expe-Mathematics 2022, 10, 1808 4 of 18 rience, e.g., in geometry lessons [62]. Sometimes teachers find it difficult to use dynamic mathematics software to explain geometric shapes [63]. ...
... is the threshold for considering as overloaded and start offloading the upcoming tasks to peer nodes. For instance, offloading can be performed through the adoption of various techniques like [17,23,14,15,16]. With the proposed model, we are able to support to maintain a free room for high priority tasks, based on a proactive approach. ...
... IFITM3 facilitates lysosome acidification [34,35] and limits immune-response cytokine production [36,37]. Notably, IFITM3 gene networks are enriched in brains and peripheral blood mononuclear cells of AD patients [38], suggesting that IFITM3 plays a role in microglial inflammatory responses to AD pathology. Collectively, these findings provide important insights into BIN1 expression and function in microglia, demonstrating the significance of microglial BIN1 expression in brain inflammatory response. ...
... Traditional eff estimation techniques [5,6] focus on computing a single capacitance value for accurate gate delay estimation, thus being inadequate to approximate slew. To accurately estimate the nonlinear driver output waveform using CSMs, eff must be computed in multiple voltage regions [7]. ...
... More specifically, we develop two procedures for applying EKS-MM and AEKS-MM to large-scale regular and singular models, by implementing computationally efficient transformations in order to preserve the original form of the sparse input matrices. A preliminary version of this work appeared in [7]. Finally, we evaluate our methodology on industrial IBM power grids. ...
... Current state of the art transcriptomic evidence suggest that FYN interacts with SARS-CoV-2 during the course of infection 6 , and was found to be upregulated in a recent meta-analysis of SARS-CoV-2 expression datasets 7 . Expanding on our previous research on IFITM3 networks in AD 8 and their overlap with COVID-19 9 , we propose a comprehensive model of AD pathogenesis where viral induction of the IFITM3/FYN endocytosis signal could account for increased Aβ oligomerization via γ-secretase activation 2 . ...
... The directed links that define the relationships between concepts can be positive or negative taking values between [−1,1]. Figure 1 presents an example of an FCM for exploring the development of the photovoltaic solar energy sector in Brazil [30], in economic and political terms. Due to the causal nature of the relationships between the concepts, FCMs are an effective tool for modeling decision support systems and time series prediction. ...
... Although, this model was achieved better accuracy, but the difficulty was enlarged during attributes and hidden layers got augmented to attain a preferred outcome. Xenakis, A. et al. [39] developed the CNN for the leaf disease identification. It was reliable for providing the client with real-world response through a rich dataset. ...
... Other active research direction is IoT application in the food industry. For example, Nasir et al. (2020) and Xenakis et al. (2020) proposed CNN solutions for IoT to detect plant diseases. ...