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Ph.D. researcher in the Department of Mechanical, Energy, and Management Engineering of the University of Calabria. My main research interests are sustainability of water and energy, water and wastewater treatment, sustainability of renewable energy, novel methods in using solar energy with high efficiency, NZEBs, PEDs, and AI application in different areas, such as COVID-19 pandemic analysis. Currently I am involved in several research project activities, Editor and referee of several academic journals.
The purpose of heating, ventilation, and air conditioning (HVAC) systems are to create optimum thermal comfort and appropriate indoor air quality (IAQ) for occupants. Air ventilation systems can significantly affect the health risk in indoor environments, especially those by contaminated aerosols. Therefore, the main goal of the study is to analyze the indoor airflow patterns in the heating, ventilation, and air conditioning (HVAC) systems and the impact of outlets/windows. The other goal of this study is to simulate the trajectory of the aerosols from a human sneeze, investigate the impact of opening windows on the number of air changes per hour (ACH) and exhibit the role of dead zones with poor ventilation. The final goal is to show the application of computational fluid dynamics (CFD) simulation in improving the HVAC design, such as outlet locations or airflow rate, in addition to the placement of occupants. In this regard, an extensive literature review has been combined with the CFD method to analyze the indoor airflow patterns, ACH, and the role of windows. The airflow pattern analysis shows the critical impact of inflow/outflow and windows. The results show that the CFD model simulation could exhibit optimal placement and safer locations for the occupants to decrease the health risk. The results of the discrete phase simulation determined that the actual ACH could be different from the theoretical ACH as the short circuit and dead zones affect the ACH.
Behrouz Pirouz; Stefania Palermo; Seyed Naghib; Domenico Mazzeo; Michele Turco; Patrizia Piro. The Role of HVAC Design and Windows on the Indoor Airflow Pattern and ACH. Sustainability 2021, 13, 7931 .
AMA StyleBehrouz Pirouz, Stefania Palermo, Seyed Naghib, Domenico Mazzeo, Michele Turco, Patrizia Piro. The Role of HVAC Design and Windows on the Indoor Airflow Pattern and ACH. Sustainability. 2021; 13 (14):7931.
Chicago/Turabian StyleBehrouz Pirouz; Stefania Palermo; Seyed Naghib; Domenico Mazzeo; Michele Turco; Patrizia Piro. 2021. "The Role of HVAC Design and Windows on the Indoor Airflow Pattern and ACH." Sustainability 13, no. 14: 7931.
Many complex problems require a multi-criteria decision, such as the COVID-19 pandemic that affected nearly all activities in the world. In this regard, this study aims to develop a multi-criteria decision support system considering the sustainability, feasibility, and success rate of possible approaches. Therefore, two models have been developed: Geo-AHP (applying geo-based data) and BN-Geo-AHP using probabilistic techniques (Bayesian network). The ranking method of Geo-APH is generalized, and the equations are provided in a way that adding new elements and variables would be possible by experts. Then, to improve the ranking, the application of the probabilistic technique of a Bayesian network and the role of machine learning for database and weight of each parameter are explained, and the model of BN-Geo-APH has been developed. In the next step, to show the application of the developed Geo-AHP and BN-Geo-AHP models, we selected the new pandemic of COVID-19 that affected nearly all activities, and we used both models for analysis. For this purpose, we first analyzed the available data about COVID-19 and previous studies about similar virus infections, and then we ranked the main approaches and alternatives in confronting the pandemic of COVID-19. The analysis of approaches with the selected alternatives shows the first ranked approach is massive vaccination and the second ranked is massive swabs or other tests. The third is the use of medical masks and gloves, and the last ranked is the lockdown, mostly due to its major negative impact on the economy and individuals.
Behrouz Pirouz; Aldo Ferrante; Behzad Pirouz; Patrizia Piro. Machine Learning and Geo-Based Multi-Criteria Decision Support Systems in Analysis of Complex Problems. ISPRS International Journal of Geo-Information 2021, 10, 424 .
AMA StyleBehrouz Pirouz, Aldo Ferrante, Behzad Pirouz, Patrizia Piro. Machine Learning and Geo-Based Multi-Criteria Decision Support Systems in Analysis of Complex Problems. ISPRS International Journal of Geo-Information. 2021; 10 (6):424.
Chicago/Turabian StyleBehrouz Pirouz; Aldo Ferrante; Behzad Pirouz; Patrizia Piro. 2021. "Machine Learning and Geo-Based Multi-Criteria Decision Support Systems in Analysis of Complex Problems." ISPRS International Journal of Geo-Information 10, no. 6: 424.
The simulation of the ventilation and the heating, ventilation, and air conditioning (HVAC) systems of vehicles could be used in the energy demand management of vehicles besides improving the air quality inside their cabins. Moreover, traveling by public transport during a pandemic is a concerning factor, and analysis of the vehicle’s cabin environments could demonstrate how to decrease the risk and create a safer journey for passengers. Therefore, this article presents airflow analysis, air changes per hour (ACH), and respiration aerosols’ trajectory inside three vehicles, including a typical car, bus, and airplane. In this regard, three vehicles’ cabin environment boundary conditions and the HVAC systems of the selected vehicles were determined, and three-dimensional numerical simulations were performed using computational fluid dynamic (CFD) modeling. The analysis of the airflow patterns and aerosol trajectories in the selected vehicles demonstrate the critical impact of inflow, outflow, and passenger’s locations in the cabins. The CFD model results exhibited that the lowest risk could be in the airplane and the highest in the bus because of the location of airflows and outflows. The discrete CFD model analysis determined the ACH for a typical car of about 4.3, a typical bus of about 7.5, and in a typical airplane of about 8.5, which were all less than the standard protocol of infection prevention, 12 ACH. According to the results, opening windows in the cars could decrease the aerosol loads and improve the low ACH by the HVAC systems. However, for the buses, a new design for the outflow location or an increase in the number of outflows appeared necessary. In the case of airplanes, the airflow paths were suitable, and by increasing the airflow speed, the required ACH might be achieved. Finally, in the closed (recirculating) systems, the role of filters in decreasing the risk appeared critical.
Behrouz Pirouz; Domenico Mazzeo; Stefania Palermo; Seyed Naghib; Michele Turco; Patrizia Piro. CFD Investigation of Vehicle’s Ventilation Systems and Analysis of ACH in Typical Airplanes, Cars, and Buses. Sustainability 2021, 13, 6799 .
AMA StyleBehrouz Pirouz, Domenico Mazzeo, Stefania Palermo, Seyed Naghib, Michele Turco, Patrizia Piro. CFD Investigation of Vehicle’s Ventilation Systems and Analysis of ACH in Typical Airplanes, Cars, and Buses. Sustainability. 2021; 13 (12):6799.
Chicago/Turabian StyleBehrouz Pirouz; Domenico Mazzeo; Stefania Palermo; Seyed Naghib; Michele Turco; Patrizia Piro. 2021. "CFD Investigation of Vehicle’s Ventilation Systems and Analysis of ACH in Typical Airplanes, Cars, and Buses." Sustainability 13, no. 12: 6799.
Conventional green roofs, although having numerous advantages, could place water resources under pressure in dry periods due to irrigation requirements. Moreover, the thermal efficiency of green roofs could decrease without irrigation, and the plants could get damaged. Therefore, this study aims to improve the efficiency of conventional green roofs by proposing a new multipurpose green roof combined with fog and dew harvesting systems. The analysis determined that the average water use of green roofs in the summer (in humid regions) is about 3.7 L/m2/day, in the Mediterranean regions about 4.5 L/m2/day, and in arid regions about 2.7 L/m2/day. During the dry season, the average fog potential in humid regions is 1.2 to 15.6 L/m2/day, Mediterranean regions between 1.6 and 4.6 L/m2/day, and arid regions between 1.8 and 11.8 L/m2/day. The average dew potential during the dry season in humid regions is 0.1 to 0.3 L/m2/day, in the Mediterranean regions is 0.2 to 0.3 L/m2/day, and in the arid regions is 0.5 to 0.7 L/m2/day. The analysis of the suggested multipurpose green roof combined with fog/dew harvesting systems, in the summer, in three different climates, show that fog harvesting could provide the total water requirement of the green roofs, and that dew harvesting by PV (photo-voltaic) panels could provide 15 to 26% of the water requirements. Moreover, it could show a higher thermal impact on the building, higher efficiency in stormwater management, less dependence on the urban water network, and greater efficiency in decreasing urban air, water, and noise pollution. Finally, the novel green roof system could consume less water due to the shaded area by mesh and solar PVs and maximize the utilization of the roof area, as solar panels could be applied on the same green roof.
Behrouz Pirouz; Stefania Palermo; Michele Turco. Improving the Efficiency of Green Roofs Using Atmospheric Water Harvesting Systems (An Innovative Design). Water 2021, 13, 546 .
AMA StyleBehrouz Pirouz, Stefania Palermo, Michele Turco. Improving the Efficiency of Green Roofs Using Atmospheric Water Harvesting Systems (An Innovative Design). Water. 2021; 13 (4):546.
Chicago/Turabian StyleBehrouz Pirouz; Stefania Palermo; Michele Turco. 2021. "Improving the Efficiency of Green Roofs Using Atmospheric Water Harvesting Systems (An Innovative Design)." Water 13, no. 4: 546.
The advantages of low-impact development approaches, such as green walls in an urban environment, are numerous. These systems can be applied for managing stormwater, saving energy consumption, decreasing noise pollution, improving runoff quality, improving life quality, and so forth. Besides, atmospheric water harvesting methods are considered a nonconventional water source. There are many studies about the analysis and advantages of green walls and atmospheric water harvesting conducted separately. However, the use of a combined system that uses fog harvesting in the irrigation of green walls has received less attention in previous studies, and therefore in this research, the feasibility of a novel green wall platform was investigated. At first, the potential of using green walls and atmospheric water harvesting in different climates was analyzed. Then a new combined system was proposed and explained. The study results determined that atmospheric water harvesting can be applied as a source of irrigation for green facilities, particularly in the dry season and in periods with lower precipitation. In the Mediterranean climate, summer fog harvesting yields 1.4–4.6 L/m2/day, and the water consumption of green walls is about 4–8 L/day/m2. This can improve one issue of green walls in an urban environment, which is irrigation in summer. Furthermore, the novel system would protect plants from severe conditions, improve buildings’ thermal behavior by decreasing direct sunlight, and increase conventional green walls’ efficiency and advantages.
Behrouz Pirouz; Michele Turco; Stefania Anna Palermo. A Novel Idea for Improving the Efficiency of Green Walls in Urban Environment (an Innovative Design and Technique). Water 2020, 12, 3524 .
AMA StyleBehrouz Pirouz, Michele Turco, Stefania Anna Palermo. A Novel Idea for Improving the Efficiency of Green Walls in Urban Environment (an Innovative Design and Technique). Water. 2020; 12 (12):3524.
Chicago/Turabian StyleBehrouz Pirouz; Michele Turco; Stefania Anna Palermo. 2020. "A Novel Idea for Improving the Efficiency of Green Walls in Urban Environment (an Innovative Design and Technique)." Water 12, no. 12: 3524.
Electrical and energy production have a noticeable water footprint, and buildings′ share of global energy consumption is about 40%. This study presents a comprehensive experimental analysis of different thermal impacts and water consumption of green roofs in a Mediterranean climate. The study aims to investigate the use of water directly for green roofs and reduce the water footprint of energy in summer and winter due to its thermal impacts. The measurements were carried out for an extensive green roof with an area of 55 m2 and a thickness of 22 cm, and direct water consumption by a green roof and direct and indirect water consumption by cooling and heating systems were analyzed. According to the analysis, in summer, the maximum roof temperature on a conventional roof was 72 °C, while under the green roof it was 30.3 °C. In winter, the minimum roof temperature on a conventional roof was −8.6 °C, while under the green roof it was 7.4 °C. These results show that green roofs affect energy consumption in summer and winter, and the corresponding thermal requirements for the building have a water footprint regarding energy production. In summer, the thermal reduction in the water footprint by a green roof was 48 m3 if an evaporative air conditioner is used and 8.9 m3 for a compression air conditioner, whereas the water consumed in the green roof was 8.2 m3. Therefore, using water directly in the green roof would reduce the energy consumption in buildings, and thus less water has to be used in power plants to provide the same thermal impact. In winter, green roofs′ water consumption was higher than the thermal water footprint; however, there is no need to irrigate the green roof as the water consumed comes from precipitation. This experimental analysis determines that in the Mediterranean climate, green roofs allow the achievement of the same thermal conditions for buildings in both summer and winter, with a reduction in water consumption.
Behrouz Pirouz; Stefania Palermo; Mario Maiolo; Natale Arcuri; Patrizia Piro. Decreasing Water Footprint of Electricity and Heat by Extensive Green Roofs: Case of Southern Italy. Sustainability 2020, 12, 10178 .
AMA StyleBehrouz Pirouz, Stefania Palermo, Mario Maiolo, Natale Arcuri, Patrizia Piro. Decreasing Water Footprint of Electricity and Heat by Extensive Green Roofs: Case of Southern Italy. Sustainability. 2020; 12 (23):10178.
Chicago/Turabian StyleBehrouz Pirouz; Stefania Palermo; Mario Maiolo; Natale Arcuri; Patrizia Piro. 2020. "Decreasing Water Footprint of Electricity and Heat by Extensive Green Roofs: Case of Southern Italy." Sustainability 12, no. 23: 10178.
The real-time control (RTC) system is a valid and cost-effective solution for urban stormwater management. This paper aims to evaluate the beneficial effect on urban flooding risk mitigation produced by applying RTC techniques to an urban drainage network by considering different control configuration scenarios. To achieve the aim, a distributed real-time system, validated in previous studies, was considered. This approach uses a smart moveable gates system, controlled by software agents, managed by a swarm intelligence algorithm. By running the different scenarios by a customized version of the Storm Water Management Model (SWMM), the findings obtained show a redistribution of conduits filling degrees, exploiting the whole system storage capacity, with a significant reduction of node flooding and total flood volume.
Mario Maiolo; Stefania Anna Palermo; Anna Chiara Brusco; Behrouz Pirouz; Michele Turco; Andrea Vinci; Giandomenico Spezzano; Patrizia Piro. On the Use of a Real-Time Control Approach for Urban Stormwater Management. Water 2020, 12, 2842 .
AMA StyleMario Maiolo, Stefania Anna Palermo, Anna Chiara Brusco, Behrouz Pirouz, Michele Turco, Andrea Vinci, Giandomenico Spezzano, Patrizia Piro. On the Use of a Real-Time Control Approach for Urban Stormwater Management. Water. 2020; 12 (10):2842.
Chicago/Turabian StyleMario Maiolo; Stefania Anna Palermo; Anna Chiara Brusco; Behrouz Pirouz; Michele Turco; Andrea Vinci; Giandomenico Spezzano; Patrizia Piro. 2020. "On the Use of a Real-Time Control Approach for Urban Stormwater Management." Water 12, no. 10: 2842.
The outbreak of the new Coronavirus (COVID-19) pandemic has prompted investigations on various aspects. This research aims to study the possible correlation between the numbers of swab tests and the trend of confirmed cases of infection, while paying particular attention to the sickness level. The study is carried out in relation to the Italian case, but the result is of more general importance, particularly for countries with limited ICU (intensive care units) availability. The statistical analysis showed that, by increasing the number of tests, the trend of home isolation cases was positive. However, the trend of mild cases admitted to hospitals, intensive case cases, and daily deaths were all negative. The result of the statistical analysis provided the basis for an AI study by ANN. In addition, the results were validated using a multivariate linear regression (MLR) approach. Our main result was to identify a significant statistical effect of a reduction of pressure on the health care system due to an increase in tests. The relevance of this result is not confined to the COVID-19 outbreak, because the high demand of hospitalizations and ICU treatments due to this pandemic has an indirect effect on the possibility of guaranteeing an adequate treatment for other high-fatality diseases, such as, e.g., cardiological and oncological ones. Our results show that swab testing may play a significant role in decreasing stress on the health system. Therefore, this case study is relevant, in particular, for plans to control the pandemic in countries with a limited capacity for admissions to ICU units.
Behzad Pirouz; Hana Javadi Nejad; Galileo Violini; Behrouz Pirouz. The Role of Artificial Intelligence, MLR and Statistical Analysis in Investigations about the Correlation of Swab Tests and Stress on Health Care Systems by COVID-19. Information 2020, 11, 454 .
AMA StyleBehzad Pirouz, Hana Javadi Nejad, Galileo Violini, Behrouz Pirouz. The Role of Artificial Intelligence, MLR and Statistical Analysis in Investigations about the Correlation of Swab Tests and Stress on Health Care Systems by COVID-19. Information. 2020; 11 (9):454.
Chicago/Turabian StyleBehzad Pirouz; Hana Javadi Nejad; Galileo Violini; Behrouz Pirouz. 2020. "The Role of Artificial Intelligence, MLR and Statistical Analysis in Investigations about the Correlation of Swab Tests and Stress on Health Care Systems by COVID-19." Information 11, no. 9: 454.
The outbreak of the new Coronavirus (COVID-19) pandemic has prompted investigations on various aspects. This research aims to study the possible correlation between the numbers of swab tests and confirmed cases of infection, with special attention to the sickness level. The study is carried out with reference to the Italian case, but the result is of more general importance, in particular for countries with limited availability of ICUs (intensive care units). The statistical analysis shows correlation between the number of swab tests and those of daily positive cases, mild cases admitted to hospital, intensive care cases, recovery, and death rate, and provides a basis to carry on an AI study. The results were validated using a multivariate linear regression (MLR) approach. Our main result is the identification of a significant statistical effect of reduction of the pressure on the Health system as result of the increase of the tests. The relevance of this result is not confined to the COVID-19 outbreak, because the high demand of hospitalizations and ICU treatments due to this pandemic has an indirect effect on the possibility of guaranteeing an adequate treatment for other high-fatality disease, such as e.g. cardiological, and oncological. Our results show that swab testing may play a major role to decrease the stress on the Health system of a country. Therefore, this case study is relevant in particular for the planning of the control of the pandemic in countries with a limited capacity of admission to ICU’s units.
Behzad Pirouz; Hana Javadi Nejad; Galileo Violini; Behrouz Pirouz. The Role of Swab Tests to Decrease the Stress by COVID-19 on the Health System using AI, MLR & Statistical Analysis. 2020, 1 .
AMA StyleBehzad Pirouz, Hana Javadi Nejad, Galileo Violini, Behrouz Pirouz. The Role of Swab Tests to Decrease the Stress by COVID-19 on the Health System using AI, MLR & Statistical Analysis. . 2020; ():1.
Chicago/Turabian StyleBehzad Pirouz; Hana Javadi Nejad; Galileo Violini; Behrouz Pirouz. 2020. "The Role of Swab Tests to Decrease the Stress by COVID-19 on the Health System using AI, MLR & Statistical Analysis." , no. : 1.
Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new coronavirus (COVID-19) as an infectious disease showed that it has undesirable social, environmental, and economic impacts, and leads to serious challenges and threats. Additionally, investigating the prioritization parameters is of vital importance to reducing the negative impacts of this global crisis. Hence, the main aim of this study is to prioritize and analyze the role of certain environmental parameters. For this purpose, four cities in Italy were selected as a case study and some notable climate parameters—such as daily average temperature, relative humidity, wind speed—and an urban parameter, population density, were considered as input data set, with confirmed cases of COVID-19 being the output dataset. In this paper, two artificial intelligence techniques, including an artificial neural network (ANN) based on particle swarm optimization (PSO) algorithm and differential evolution (DE) algorithm, were used for prioritizing climate and urban parameters. The analysis is based on the feature selection process and then the obtained results from the proposed models compared to select the best one. Finally, the difference in cost function was about 0.0001 between the performances of the two models, hence, the two methods were not different in cost function, however, ANN-PSO was found to be better, because it reached to the desired precision level in lesser iterations than ANN-DE. In addition, the priority of two variables, urban parameter, and relative humidity, were the highest to predict the confirmed cases of COVID-19.
Sina Shaffiee Haghshenas; Behrouz Pirouz; Behzad Pirouz; Patrizia Piro; Kyoung-Sae Na; Seo-Eun Cho; Zong Woo Geem. Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications. International Journal of Environmental Research and Public Health 2020, 17, 3730 .
AMA StyleSina Shaffiee Haghshenas, Behrouz Pirouz, Behzad Pirouz, Patrizia Piro, Kyoung-Sae Na, Seo-Eun Cho, Zong Woo Geem. Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications. International Journal of Environmental Research and Public Health. 2020; 17 (10):3730.
Chicago/Turabian StyleSina Shaffiee Haghshenas; Behrouz Pirouz; Behzad Pirouz; Patrizia Piro; Kyoung-Sae Na; Seo-Eun Cho; Zong Woo Geem. 2020. "Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications." International Journal of Environmental Research and Public Health 17, no. 10: 3730.
Sustainable development has been a controversial global topic, and as a complex concept in recent years, it plays a key role in creating a favorable future for societies. Meanwhile, there are several problems in the process of implementing this approach, like epidemic diseases. Hence, in this study, the impact of climate and urban factors on confirmed cases of COVID-19 (a new type of coronavirus) with the trend and multivariate linear regression (MLR) has been investigated to propose a more accurate prediction model. For this propose, some important climate parameters, including daily average temperature, relative humidity, and wind speed, in addition to urban parameters such as population density, were considered, and their impacts on confirmed cases of COVID-19 were analyzed. The analysis was performed for three case studies in Italy, and the application of the proposed method has been investigated. The impacts of parameters have been considered with a delay time from one to nine days to find out the most suitable combination. The result of the analysis demonstrates the effectiveness of the proposed model and the impact of climate parameters on the trend of confirmed cases. The research hypothesis approved by the MLR model and the present assessment method could be applied by considering several variables that exhibit the exact delay of them to new confirmed cases of COVID-19.
Behrouz Pirouz; Sina Shaffiee Haghshenas; Behzad Pirouz; Patrizia Piro. Development of an Assessment Method for Investigating the Impact of Climate and Urban Parameters in Confirmed Cases of COVID-19: A New Challenge in Sustainable Development. International Journal of Environmental Research and Public Health 2020, 17, 2801 .
AMA StyleBehrouz Pirouz, Sina Shaffiee Haghshenas, Behzad Pirouz, Patrizia Piro. Development of an Assessment Method for Investigating the Impact of Climate and Urban Parameters in Confirmed Cases of COVID-19: A New Challenge in Sustainable Development. International Journal of Environmental Research and Public Health. 2020; 17 (8):2801.
Chicago/Turabian StyleBehrouz Pirouz; Sina Shaffiee Haghshenas; Behzad Pirouz; Patrizia Piro. 2020. "Development of an Assessment Method for Investigating the Impact of Climate and Urban Parameters in Confirmed Cases of COVID-19: A New Challenge in Sustainable Development." International Journal of Environmental Research and Public Health 17, no. 8: 2801.
AIMSThe main purpose of this study is to investigate the correlation between the average daily temperature and the rate of coronavirus epidemic growth in the infected regions.BACKGROUNDThe rapid outbreak of the new Coronavirus (COVID-19) pandemic and the spread of the virus worldwide, especially in the Northern Hemisphere, have prompted various investigations about the impact of environmental factors on the rate of development of this epidemic. Different studies have called attention to various parameters that may have influenced the spread of the virus, and in particular, the impact of climatic parameters has been emphasized.OBJECTIVEThe main hypothesis object of our research is that between regions exhibiting a significant difference in the mean daily temperature, a significant difference is also observed in the average cumulative daily rate of confirmed cases and that this does not happen if there is no significant difference in mean daily temperature.METHODThe research hypothesis was investigated through statistical analysis. The F-test was used to test whether there is significant equality of variances for each pair of case studies, and then, by the T- Test, the existence of a significant difference was investigated. In all statistical tests, the confidence level of 95% is considered. In order to minimize the impact on the results of factors like the policy of the government or cultural differences among countries (food, exercise, weight, etc.), three case studies within five countries, namely Iran, Italy, Germany, Spain, and United States were compared separately.RESULTThis statistical analysis shows that there is a correlation between the average temperature and the epidemic rate, and this is especially evident when differences in average daily temperature are significantly larger, as it happens for Bandar Abbas in Iran, Milan in Italy, Santa Cruz in Spain, and Los Angeles in the US. Besides, the analysis of the average air temperatures shows that the epidemic rates of COVID-19 were higher in the case studies with a lower average temperature. Instead, when no significant differences exist in the average daily temperature of two cities in the same country, there is no significant difference in the average cumulative daily rate of confirmed cases.CONCLUSIONIn all five selected countries, we found that when there is a significant difference in the daily mean temperature between two regions of a country, a significant difference also exists in the average cumulative daily rate of confirmed cases. Conversely, if there are no significant differences in the mean daily temperature of two regions in the same country, no significant difference is observed in the average cumulative daily rate of confirmed cases for these regions. In conclusion, the results of this study support the research hypothesis and confirm the effectiveness of the proposed method for analysis of the epidemic rates.
Behzad Pirouz; Amirsina Golmohammadi; Hasti Saeidpour Masouleh; Galileo Violini; Behrouz Pirouz. Relationship between Average Daily Temperature and Average Cumulative Daily Rate of Confirmed Cases of COVID-19. 2020, 1 .
AMA StyleBehzad Pirouz, Amirsina Golmohammadi, Hasti Saeidpour Masouleh, Galileo Violini, Behrouz Pirouz. Relationship between Average Daily Temperature and Average Cumulative Daily Rate of Confirmed Cases of COVID-19. . 2020; ():1.
Chicago/Turabian StyleBehzad Pirouz; Amirsina Golmohammadi; Hasti Saeidpour Masouleh; Galileo Violini; Behrouz Pirouz. 2020. "Relationship between Average Daily Temperature and Average Cumulative Daily Rate of Confirmed Cases of COVID-19." , no. : 1.
Nowadays, sustainable development is considered a key concept and solution in creating a promising and prosperous future for human societies. Nevertheless, there are some predicted and unpredicted problems that epidemic diseases are real and complex problems. Hence, in this research work, a serious challenge in the sustainable development process was investigated using the classification of confirmed cases of COVID-19 (new version of Coronavirus) as one of the epidemic diseases. Hence, binary classification modeling was used by the group method of data handling (GMDH) type of neural network as one of the artificial intelligence methods. For this purpose, the Hubei province in China was selected as a case study to construct the proposed model, and some important factors, namely maximum, minimum, and average daily temperature, the density of a city, relative humidity, and wind speed, were considered as the input dataset, and the number of confirmed cases was selected as the output dataset for 30 days. The proposed binary classification model provides higher performance capacity in predicting the confirmed cases. In addition, regression analysis has been done and the trend of confirmed cases compared with the fluctuations of daily weather parameters (wind, humidity, and average temperature). The results demonstrated that the relative humidity and maximum daily temperature had the highest impact on the confirmed cases. The relative humidity in the main case study, with an average of 77.9%, affected positively, and maximum daily temperature, with an average of 15.4 °C, affected negatively, the confirmed cases.
Behrouz Pirouz; Sina Shaffiee Haghshenas; Patrizia Piro. Investigating a Serious Challenge in the Sustainable Development Process: Analysis of Confirmed cases of COVID-19 (New Type of Coronavirus) Through a Binary Classification Using Artificial Intelligence and Regression Analysis. Sustainability 2020, 12, 2427 .
AMA StyleBehrouz Pirouz, Sina Shaffiee Haghshenas, Patrizia Piro. Investigating a Serious Challenge in the Sustainable Development Process: Analysis of Confirmed cases of COVID-19 (New Type of Coronavirus) Through a Binary Classification Using Artificial Intelligence and Regression Analysis. Sustainability. 2020; 12 (6):2427.
Chicago/Turabian StyleBehrouz Pirouz; Sina Shaffiee Haghshenas; Patrizia Piro. 2020. "Investigating a Serious Challenge in the Sustainable Development Process: Analysis of Confirmed cases of COVID-19 (New Type of Coronavirus) Through a Binary Classification Using Artificial Intelligence and Regression Analysis." Sustainability 12, no. 6: 2427.
The role of the industrial sector in total greenhouse gas (GHG) emissions and resource consumption is well-known, and many industrial activities may have a negative environmental impact. The solution to decreasing the negative effects cannot be effective without the consideration of sustainable development. There are several methods for sustainability evaluation, such as tools based on products, processes, or plants besides supply chain or life cycle analysis, and there are different rating systems suggesting 80, 140, or more indicators for assessment. The critical point is the limits such as required techniques and budget in using all indicators for all factories in the beginning. Moreover, the weight of each indicator might change based on the selected alternative that it is not a fixed value and could change in a new case study. In this regard, to determine the impact and weight of different indicators in sustainable factories, a multi-layer Triangular Fuzzy Analytic Hierarchy Process (TFAHP) approach was developed, and the application of the method was described and verified. The defined layers are six; for each layer, the pairwise comparison matrix was developed, and the total aggregated score concerning the sustainability goal for each alternative was calculated that shows the Relative Importance Coefficient (RIC). The method is formulated in a way that allows adding the new indicators in all layers as the verification shows, and thus, there are no limits for using any green rating systems. Therefore, the presented approach by TFAHP would provide an additional tool toward the sustainable development of factories.
Behrouz Pirouz; Natale Arcuri; Behzad Pirouz; Stefania Anna Palermo; Michele Turco; Mario Maiolo. Development of an Assessment Method for Evaluation of Sustainable Factories. Sustainability 2020, 12, 1841 .
AMA StyleBehrouz Pirouz, Natale Arcuri, Behzad Pirouz, Stefania Anna Palermo, Michele Turco, Mario Maiolo. Development of an Assessment Method for Evaluation of Sustainable Factories. Sustainability. 2020; 12 (5):1841.
Chicago/Turabian StyleBehrouz Pirouz; Natale Arcuri; Behzad Pirouz; Stefania Anna Palermo; Michele Turco; Mario Maiolo. 2020. "Development of an Assessment Method for Evaluation of Sustainable Factories." Sustainability 12, no. 5: 1841.
Rainwater harvesting systems represent sustainable solutions that meet the challenges of water saving and surface runoff mitigation. The collected rainwater can be re-used for several purposes such as irrigation of green roofs and garden, flushing toilets, etc. Optimizing the water usage in each such use is a significant goal. To achieve this goal, we have considered TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Rough Set method as Multi-Objective Optimization approaches by analyzing different case studies. TOPSIS was used to compare algorithms and evaluate the performance of alternatives, while Rough Set method was applied as a machine learning method to optimize rainwater-harvesting systems. Results by Rough Set method provided a baseline for decision-making and the minimal decision algorithm were obtained as six rules. In addition, The TOPSIS method ranked all case studies, and because we used several correlated attributes, the findings are more accurate from other simple ranking method. Therefore, the numerical optimization of rainwater harvesting systems will improve the knowledge from previous studies in the field, and provide an additional tool to identify the optimal rainwater reuse in order to save water and reduce the surface runoff discharged into the sewer system.
Stefania Anna Palermo; Vito Cataldo Talarico; Behrouz Pirouz. Optimizing Rainwater Harvesting Systems for Non-potable Water Uses and Surface Runoff Mitigation. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 570 -582.
AMA StyleStefania Anna Palermo, Vito Cataldo Talarico, Behrouz Pirouz. Optimizing Rainwater Harvesting Systems for Non-potable Water Uses and Surface Runoff Mitigation. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():570-582.
Chicago/Turabian StyleStefania Anna Palermo; Vito Cataldo Talarico; Behrouz Pirouz. 2020. "Optimizing Rainwater Harvesting Systems for Non-potable Water Uses and Surface Runoff Mitigation." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 570-582.
Urbanization affects ecosystem health and downstream communities by changing the natural flow regime. In this context, Low Impact Development (LID) systems are important tools in sustainable development. There are many aspects in design and operation of LID systems and the choice of the selected LID and its location in the basin can affect the results. In this regard, the Mathematical Optimization Approaches can be an ideal method to optimize LIDs use. Here we consider the application of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Rough Set theory (multiple attributes decision-making method). An advantage of using the Rough Set method in LID systems is that the selected decisions are explicit, and the method is not limited by restrictive assumptions. This new mathematical optimization approach for LID systems improves previous studies on this subject. Moreover, it provides an additional tool for the analysis of essential attributes to select and optimize the best LID system for a project.
Behrouz Pirouz; Stefania Anna Palermo; Michele Turco; Patrizia Piro. New Mathematical Optimization Approaches for LID Systems. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 583 -595.
AMA StyleBehrouz Pirouz, Stefania Anna Palermo, Michele Turco, Patrizia Piro. New Mathematical Optimization Approaches for LID Systems. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():583-595.
Chicago/Turabian StyleBehrouz Pirouz; Stefania Anna Palermo; Michele Turco; Patrizia Piro. 2020. "New Mathematical Optimization Approaches for LID Systems." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 583-595.
The GHGs emissions by different activities show that the main part that is 25% belongs to electricity and heat production and the industrial activities counting as 21% of total emission. About 37% of the electricity consumption in Europe belongs to manufacturing and share of industrial activities in GHGs are among 30% to 40%. The electricity production trends show that the proportion of the renewables energy is going to reach to 20% in Europe by 2020 and according to the new energy targets, the minimum use of renewable energy must be 27% by 2030 and decarbonizing by 2050. For the industrial sector as a main energy consumer several elements affect the total energy consumption that start from the mining of the raw materials, transporting the materials to factories, grid network and finally the product to the end users and landfilling/recycling the used products. In this regards, to analyse all factors together a new multi-objective dynamic model has been developed. Moreover, to achieve eco-factories, the main solutions have been provided and dynamically analysed by the model. The results show that, all possible factors must be considered at the same time and applying just some approaches such as solar panels and forgetting the other factors such as end user, life cycle analysis and many other factors will not achieve the sustainability goals. The multi-objective dynamic models can be used as an appropriate approach to check the role of all solutions in achieving eco and sustainable factories.
Behrouz Pirouz; Natale Arcuri; Mario Maiolo; Vito Cataldo Talarico; Patrizia Piro. A new multi-objective dynamic model to close the gaps in sustainable development of industrial sector. IOP Conference Series: Earth and Environmental Science 2020, 410, 012074 .
AMA StyleBehrouz Pirouz, Natale Arcuri, Mario Maiolo, Vito Cataldo Talarico, Patrizia Piro. A new multi-objective dynamic model to close the gaps in sustainable development of industrial sector. IOP Conference Series: Earth and Environmental Science. 2020; 410 (1):012074.
Chicago/Turabian StyleBehrouz Pirouz; Natale Arcuri; Mario Maiolo; Vito Cataldo Talarico; Patrizia Piro. 2020. "A new multi-objective dynamic model to close the gaps in sustainable development of industrial sector." IOP Conference Series: Earth and Environmental Science 410, no. 1: 012074.
Buildings portion in global energy consumption is 40%, and in the building envelope, the roof is a crucial point for improving indoor temperature, especially in the last and second last floors. Studies show that green roofs can be applied to moderate roof temperature and affect the indoor temperature in summer and winter. However, the performance of green roofs depends on several parameters such as climate, irrigation, layer materials, and thickness. In this context, the present research deals with a comprehensive experimental analysis of different thermal impacts of green roofs in summer and winter in a Mediterranean climate. Measurements carried out in one year in three different types of green roofs with different thicknesses, layers, and with and without the insulation layer. The analysis determined the possible period that indoor cooling or heating might be required with and without green roofs and demonstrated the positive impact of green roofs in moderating the roof temperature and temperature fluctuations, which in summer was remarkable. In conclusion, since in the Mediterranean climate, the thermal differences between green roofs and conventional roofs in summer are much higher than winter, it seems that the green roof without an insulation layer would show better performance.
Mario Maiolo; Behrouz Pirouz; Roberto Bruno; Stefania Anna Palermo; Natale Arcuri; Patrizia Piro. The Role of the Extensive Green Roofs on Decreasing Building Energy Consumption in the Mediterranean Climate. Sustainability 2020, 12, 359 .
AMA StyleMario Maiolo, Behrouz Pirouz, Roberto Bruno, Stefania Anna Palermo, Natale Arcuri, Patrizia Piro. The Role of the Extensive Green Roofs on Decreasing Building Energy Consumption in the Mediterranean Climate. Sustainability. 2020; 12 (1):359.
Chicago/Turabian StyleMario Maiolo; Behrouz Pirouz; Roberto Bruno; Stefania Anna Palermo; Natale Arcuri; Patrizia Piro. 2020. "The Role of the Extensive Green Roofs on Decreasing Building Energy Consumption in the Mediterranean Climate." Sustainability 12, no. 1: 359.
Behrouz Pirouz; Mario Maiolo. The Role of Power Consumption and Type of Air Conditioner in Direct and Indirect Water Consumption. Journal of Sustainable Development of Energy, Water and Environment Systems 2018, 6, 665 -673.
AMA StyleBehrouz Pirouz, Mario Maiolo. The Role of Power Consumption and Type of Air Conditioner in Direct and Indirect Water Consumption. Journal of Sustainable Development of Energy, Water and Environment Systems. 2018; 6 (4):665-673.
Chicago/Turabian StyleBehrouz Pirouz; Mario Maiolo. 2018. "The Role of Power Consumption and Type of Air Conditioner in Direct and Indirect Water Consumption." Journal of Sustainable Development of Energy, Water and Environment Systems 6, no. 4: 665-673.