Application of artificial neural networks for the prediction of the compressive strength of cement-based mortars

Panagiotis G. Asteris,Maria Apostolopoulou,Athanasia D. Skentou,Antonia Moropoulou 사단법인 한국계산역학회 2019 Computers and Concrete, An International Journal Vol.24 No.4

Despite the extensive use of mortar materials in constructions over the last decades, there is not yet a robust quantitative method, available in the literature, which can reliably predict mortar strength based on its mix components. This limitation is due to the highly nonlinear relation between the mortar’s compressive strength and the mixed components. In this paper, the application of artificial neural networks for predicting the compressive strength of mortars has been investigated. Specifically, surrogate models (such as artificial neural network models) have been used for the prediction of the compressive strength of mortars (based on experimental data available in the literature). Furthermore, compressive strength maps are presented for the first time, aiming to facilitate mortar mix design. The comparison of the derived results with the experimental findings demonstrates the ability of artificial neural networks to approximate the compressive strength of mortars in a reliable and robust manner.

Adverse Effects of Aggressive Blood Pressure Control in Patients with Intracerebral Hemorrhage

Panagiotis Mastorakos,Kenneth C. Liu,Andrew Schomer 대한신경집중치료학회 2017 대한신경집중치료학회지 Vol.10 No.1

Background: Medical management of patients presenting with spontaneous intracerebral hemorrhage (ICH) is focused on blood pressure (BP) management. However, the BP goal to prevent ICH expansion remains controversial. Recent clinical trials have suggested that aggressive BP control is safe but may not have the previously thought benefits. Case Report: We present an example of aggressive BP control in the setting of hypertensive ICH, in accordance to previously established protocols. This resulted in adverse effects in the form of acute kidney injury and watershed infarcts, which impeded the patients’ recovery and prolonged his hospitalization. Conclusions: Hypertensive individuals have altered cerebral autoregulation curves shifted to the right and require higher arterial pressures to maintain adequate cerebral blood flow. Hence, aggressive BP reduction may result in cerebral hypoperfusion as well as other forms of end-organ damage."

Impact of Job Satisfaction on Greek Nurses' Health-Related Quality of Life

Panagiotis Ioannou,Vassiliki Katsikavali,Petros Galanis,Emmanuel Velonakis,Danai Papadatou,Panayota Sourtzi 한국산업안전보건공단 산업안전보건연구원 2015 Safety and health at work Vol.6 No.4

Background: Employee job satisfaction and its relationship with health and quality of life has been an issue of major concern over the past decades. Nurses experience difficult working conditions that affect their job satisfaction, health, and quality of life. Methods: A cross-sectional study was undertaken in three general hospitals and their respective health centers. Stratified random sampling by level of education was used, and 508 nurses and nursing assistants were included. A self-administered anonymous questionnaire, which included the Measure of Job Satisfaction, the 36-item Short Form Health Survey, as well as demographic details, education, and work conditions data, was used. Results: Greek nurses were found to be dissatisfied with their job according to the total score of the job satisfaction scale, although personal satisfaction and satisfaction with support had had higher scores. Their general health was reported as average, because of physical and mental health problems, low vitality, low energy, and increased physical pain. Multivariate linear regression analysis revealed that males and those wishing to stay in the job had higher physical and mental health. Increased job satisfaction was related to increased physical and mental health. Conclusion: Although Greek nurses are not satisfied with their work, those with high levels of job satisfaction had better health-related quality of life. The findings suggest that improvement of the work environment would contribute to a healthier and more satisfied nursing workforce.

COVID-19 transmission: a rapid systematic review of current knowledge

Panagiotis Mourmouris,Lazaros Tzelves,Christiana Roidi,Anastasia Fotsali 질병관리본부 2021 Osong Public Health and Research Persptectives Vol.12 No.2

Objectives: The objective of this study was to identify the potential and definite sources of transmission of coronavirus disease 2019 (COVID-19). Methods: Due to time constraints and the acute nature of the pandemic, we searched only PubMed/MEDLINE from inception until January 28, 2021. We analyzed the level of evidence and risk of bias in each category and made suggestions accordingly. Results: The virus was traced from its potential origin via possible ways of transmission to the last host. Symptomatic human-to-human transmission remains the driver of the epidemic, but asymptomatic transmission can potentially contribute in a substantial manner. Feces and fomites have both been found to contain viable virus; even though transmission through these routes has not been documented, their contribution cannot be ruled out. Finally, transmission from pregnant women to their children has been found to be low (up to 3%). Conclusion: Even though robust outcomes cannot be easily assessed, medical personnel must maintain awareness of the main routes of transmission (via droplets and aerosols from even asymptomatic patients). This is the first attempt to systematically review the existing knowledge to produce a paper with a potentially significant clinical impact.

On the fundamental period of infilled RC frame buildings

Panagiotis G. Asteris,Constantinos C. Repapis,Liborio Cavaleri,Vasilis Sarhosis,Adamantia Athanasopoulou 국제구조공학회 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.54 No.6

This paper investigates the fundamental period of vibration of RC buildings by means of finite element macro-modelling and modal eigenvalue analysis. As a base study, a number of 14-storey RC buildings have been considered “according to code designed” and “according to code non-designed”. Several parameters have been studied including the number of spans; the span length in the direction of motion; the stiffness of the infills; the percentage openings of the infills and; the location of the soft storeys. The computed values of the fundamental period are compared against those obtained from seismic code and equations proposed by various researchers in the literature. From the analysis of the results it has been found that the span length, the stiffness of the infill wall panels and the location of the soft storeys are crucial parameters influencing the fundamental period of RC buildings.

Soft computing-based estimation of ultimate axial load of rectangular concrete-filled steel tubes

Panagiotis G. Asteris,Minas E. Lemonis,Thuy-Anh Nguyen,Hiep Van Le,Binh Thai Pham 국제구조공학회 2021 Steel and Composite Structures, An International J Vol.39 No.4

In this study, we estimate the ultimate load of rectangular concrete-filled steel tubes (CFST) by developing a novel hybrid predictive model (ANN-BCMO) which is a combination of balancing composite motion optimization (BCMO) - a very new optimization technique and artificial neural network (ANN). For this aim, an experimental database consisting of 422 datasets is used for the development and validation of the ANN-BCMO model. Variables in the database are related with the geometrical characteristics of the structural members, and the mechanical properties of the constituent materials (steel and concrete). Validation of the hybrid ANN-BCMO model is carried out by applying standard statistical criteria such as root mean square error (RMSE), coefficient of determination (R2), and mean absolute error (MAE). In addition, the selection of appropriate values for parameters of the hybrid ANN-BCMO is conducted and its robustness is evaluated and compared with the conventional ANN techniques. The results reveal that the new hybrid ANN-BCMO model is a promising tool for prediction of the ultimate load of rectangular CFST, and prove the effective role of BCMO as a powerful algorithm in optimizing and improving the capability of the ANN predictor.

Does Higher Education Affect Economic Growth? The Case of Greece

Panagiotis Pegkas,Constantinos Tsamadias 한국국제경제학회 2014 International Economic Journal Vol.28 No.3

The purpose of the study is twofold: first, it presents an extensive review of empirical studies that have examined the relationship between higher education and economic growth. Second, it estimates the effect of higher education on economic growth in Greece over the period 1960–2009. It applies the model introduced by Mankiw, Romer, and Weil (1992) by using the higher enrolment rates as a proxy of human capital. The paper employs cointegration and an error-correction model to test the causal relationship between higher education, physical capital investments and economic growth. The empirical analysis reveals that there is a long-run cointegrating relationship between higher education, physical capital investments and economic growth. The elasticity of economic growth with respect to higher education is 0.52%. The results also suggest that there is evidence of unidirectional long-run and short-run Granger causality running fromhigher education and physical capital investments to economic growth.

HEVA: Cooperative Localization using a Combined Non-Parametric Belief Propagation and Variational Message Passing Approach

Panagiotis-Agis Oikonomou-Filandras,Kai-Kit Wong 한국통신학회 2016 Journal of communications and networks Vol.18 No.3

This paper proposes a novel cooperative localizationmethod for distributed wireless networks in 3-dimensional (3D)global positioning system (GPS) denied environments. The proposedmethod, which is referred to as hybrid ellipsoidal variationalalgorithm (HEVA), combines the use of non-parametric beliefpropagation (NBP) and variational Bayes (VB) to benefit fromboth the use of the rich information in NBP and compact communicationsize of a parametric form. InHEVA, two novel filters are alsoemployed. The first one mitigates non-line-of-sight (NLoS) timeof-arrival (ToA) messages, permitting it to work well in high noiseenvironments with NLoS bias while the second one decreases thenumber of calculations. Simulation results illustrate that HEVAsignificantly outperforms traditional NBP methods in localizationwhile requires only 50%of their complexity. The superiority of VBover other clustering techniques is also shown.

Decreased Basal Ganglia Volume in Cerebral Amyloid Angiopathy

Panagiotis Fotiadis,Marco Pasi,Andreas Charidimou,Andrew D. Warren,Kristin M. Schwab,Alzheimer’s Disease Neuroimaging Initiative,Jonathan Rosand,Jeroen van der Grond,Mark A. van Buchem,Anand Viswanath 대한뇌졸중학회 2021 Journal of stroke Vol.23 No.2

Background and Purpose Cerebral amyloid angiopathy (CAA) is a common pathology of the leptomeningeal and cortical small vessels associated with hemorrhagic and non-hemorrhagic brain injury. Given previous evidence for CAA-related loss of cortical thickness and white matter volume, we hypothesized that CAA might also cause tissue loss in the basal ganglia. Methods We compared basal ganglia volumes expressed as a percentage of total intracranial volume (pBGV) of non-demented patients with sporadic and hereditary CAA to age-matched healthy control (HC) and Alzheimer’s disease (AD) cohorts. Results Patients with sporadic CAA had lower pBGV (n=80, 1.16%±0.14%) compared to HC (n=80, 1.30%±0.13%, P<0.0001) and AD patients (n=80, 1.23%±0.11%, P=0.001). Similarly, patients with hereditary CAA demonstrated lower pBGV (n=25, 1.26%±0.17%) compared to their matched HC (n=25, 1.36%±0.15%, P=0.036). Using a measurement of normalized basal ganglia width developed for analysis of clinical-grade magnetic resonance images, we found smaller basal ganglia width in patients with CAA-related lobar intracerebral hemorrhage (ICH; n=93, 12.35±1.47) compared to age-matched patients with hypertension-related deep ICH (n=93, 13.46±1.51, P<0.0001) or HC (n=93, 15.45±1.22, P<0.0001). Within the sporadic CAA research cohort, decreased basal ganglia volume was independently correlated with greater cortical gray matter atrophy (r=0.45, P<0.0001), increased basal ganglia fractional anisotropy (r=–0.36, P=0.001), and worse performance on language processing (r=0.35, P=0.003), but not with cognitive tests of executive function or processing speed. Conclusions These findings suggest an independent effect of CAA on basal ganglia tissue loss, indicating a novel mechanism for CAA-related brain injury and neurologic dysfunction

Predicting the shear strength of reinforced concrete beams using Artificial Neural Networks

Panagiotis G. Asteris,Danial J. Armaghani,George D. Hatzigeorgiou,Chris G. Karayannis,Kypros Pilakoutas 사단법인 한국계산역학회 2019 Computers and Concrete, An International Journal Vol.24 No.5

In this research study, the artificial neural networks approach is used to estimate the ultimate shear capacity of reinforced concrete beams with transverse reinforcement. More specifically, surrogate approaches, such as artificial neural network models, have been examined for predicting the shear capacity of concrete beams, based on experimental test results available in the pertinent literature. The comparison of the predicted values with the corresponding experimental ones, as well as with available formulas from previous research studies or code provisions highlight the ability of artificial neural networks to evaluate the shear capacity of reinforced concrete beams in a trustworthy and effective manner. Furthermore, for the first time, the (quantitative) values of weights for the proposed neural network model, are provided, so that the proposed model can be readily implemented in a spreadsheet and accessible to everyone interested in the procedure of simulation.