Environment
Z. Poormolaie; M. Mohammadi; M. Ghafoori; E. Khayyami
Abstract
The aim of this study was to determine the air quality index (AQI) and to investigate its relationship with meteorological parameters in Mashhad for 2014. In this study, moment concentrations of air pollutants in Mashhad for 2014 were prepared and the amount of AQI was calculated and air quality was ...
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The aim of this study was to determine the air quality index (AQI) and to investigate its relationship with meteorological parameters in Mashhad for 2014. In this study, moment concentrations of air pollutants in Mashhad for 2014 were prepared and the amount of AQI was calculated and air quality was determined. Then, data analysis was performed using Kruskal-Wallis and Mann-Whitney tests at a significant level of 5% in SPSSV.23 software. Finally, data related to meteorological parameters were prepared during 2014 and ARIMA time series model and R software (3.3.0) were used to investigate its relationship with air index pollutants in non-delayed and one day late modes. The results showed that air quality of Mashhad was in a very bad condition in terms of maintaining the health of community members, especially sensitive groups, as the concentration of pollutants in this city was higher than Iranian standard (100) in 245 days of the study period. The PM2.5 was the most important pollutant during the study. It was also found that among the climatic parameters, temperature and pressure have the greatest direct effect on the concentration of air pollutants. Moreover, results showed the immediate effect of temperature on the concentration of air pollutants, although other atmospheric elements are able to significantly affect the outcome over time and with a time delay (one day in this study). The results indicated that quality of model computation depends on changes in atmospheric parameters, so that a quantitative measurement for each pollutant can be achieved based on meteorological data.
Environment
H. Hassanpour; Z. Mortezaie; A. Beghdadi
Abstract
Video surveillance systems are widely used in the public and private sectors for maintaining security and healthcare purposes. Performance of surveillance systems directly depends on their accuracy in re-identification. There are three regions in a camera view, including person’s body, background, ...
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Video surveillance systems are widely used in the public and private sectors for maintaining security and healthcare purposes. Performance of surveillance systems directly depends on their accuracy in re-identification. There are three regions in a camera view, including person’s body, background, and possible carried object by the person. Background, in existing approaches, is either overlooked or treated like a person’s body in re-identification. In this paper, these three regions are considered in re-identification but with different importance. In our proposed technique, first, the input image is semantically segmented into the three regions using a deep semantic segmentation approach. Then, the effect of each region on characteristic features of people is tuned depending on the region’s importance in re-identification. The proposed technique, leveraging robust descriptors, such as the Gaussian of Gaussian (GOG) and Hierarchical Gaussian Descriptors (HGD), can enhance existing methods in dealing with the challenging issues such as partial occlusion caused by carried objects and background in re-identification. Experimental results on commonly used people re-identification datasets demonstrate effectiveness of the proposed technique in improving performance of existing re-identification methods.
Environment
H. Tamadon Ghareghie; M. Yazdi; D. Yousefi Kebria; H. Aminirad
Abstract
Soil contamination is considered a controversial issue in most countries. Nowadays, it is important to clearly understand how pollutants influence the soil from different sources. Today, hydrocarbons are one of the most important sources of soil contaminants, which is considered as a fundamental issue ...
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Soil contamination is considered a controversial issue in most countries. Nowadays, it is important to clearly understand how pollutants influence the soil from different sources. Today, hydrocarbons are one of the most important sources of soil contaminants, which is considered as a fundamental issue at the global level. The current study aims to analyze and model the effect of simultaneous parameters (time and concentration) of phenols and naphthalene with different percentages (10, 15, 20 and 25%) together with the amount of bentonite in fine-grained sandy soil. The designed experiments made use of response surface methodology (RSM) and Design-Expert software to carry out a computer-based simulation. According to the proposed model, the amount of bentonite is most affected by the permeability of the soil. The obtained results also showed that the permeability significantly decreases in the light of increasing the percentage of phenol and naphthalene coupled with the amount of bentonite and the age of contamination. On average, an 80% reduction of permeability was observed in contaminated soil, which was found in the soil contaminated with naphthalene. According to the results of the synergistic effects of time, the considerable impacts of both the percentage of hydrocarbon pollutants and the amount of bentonite on the reduction of permeability are quite evident.
Environment
M. O. Ezugwu; F. O. Akhimien; Z. Y. Hamza
Abstract
Characterization and quantification of solid waste in Equity girls hostel blocks, Igbinedion University Okada was carried out to provide data for waste management strategy in the University. The waste survey was done for 3 months by collecting generated wastes from various rooms on a daily basis excluding ...
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Characterization and quantification of solid waste in Equity girls hostel blocks, Igbinedion University Okada was carried out to provide data for waste management strategy in the University. The waste survey was done for 3 months by collecting generated wastes from various rooms on a daily basis excluding Sundays. The collected wastes were segregated and sorted into their various constituents and weighed using an automatic weighing scale. Waste per capita per head was also determined by estimating the total number of students/population in the study area. Identified wastes constituents were plastics, paper, glass, bottles, organic wastes, etc. The total amount of waste recorded was 1605.65kg for 3 months. Organic wastes recorded the highest amount of wastes generated with a total of 304.542kg (19%) followed by glass/bottles recorded as 250.993kg (16%). Waste per capita per day was estimated as 0.045kg. From the wastes stream, some wastes were identified as reusable and recyclable which can generate income for the university when properly handled and it will indirectly aid in decreasing the volume and amount of wastes to be disposed. Organic wastes have been identified to constitute the highest amount of waste in the waste stream. These organic wastes are degradable and can be utilized for crop production and agricultural purposes which invariably contribute to waste stream reduction. Adopting efficient waste mangement strategy will create wealth, reduce pollution and demand on raw materials, and provide a greener environment.
Environment
H. Esmaeil Yazdi; A. M. Salehi
Abstract
Proper acoustic design is especially important in some buildings. For example, in concert halls, one of the desirable functional features is the proper transmission of music. In this regard, an indicator that can effectively show the quality of the received sound is the sound intensity, which is the ...
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Proper acoustic design is especially important in some buildings. For example, in concert halls, one of the desirable functional features is the proper transmission of music. In this regard, an indicator that can effectively show the quality of the received sound is the sound intensity, which is the purpose of this study is a way to optimize this indicator. Among the most effective variables that will affect the intensity of the received sound and also the important characteristics of the sound source are the frequency and octave of the sound, as well as the distance between the sound source and the receiver. In this research, a new method was proposed to investigate the effect of these three variables on the received sound intensity. In this regard, ODEON software, one of the most powerful software in acoustic design, was used and data analyses were implemented. Then, using full factorial method (one of the experimental design methods), targeted scenarios based on three independent variables were identified and by using the results of simulated scenarios, the linear relationship between the dependent variable (sound intensity) and independent variables (frequency, octave and distance) were developed. Using this linear relationship, it was found that the octave of sound has the greatest effect on sound intensity, and sound frequency and distance from the sound source were inversely related to the sound intensity.
Environment
V. Montazeri; B. ZareNezhad; A. Ghazi
Abstract
The nanofluid-based gas hydrate formation process employing copper oxide (CuO) nanoparticles have been experimentally investigated in this work. Different concentrations of nanofluids are injected into the reactor at the operating condition of 29 bar, 274.15 K, and impeller speed of 100 rpm. It was observed ...
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The nanofluid-based gas hydrate formation process employing copper oxide (CuO) nanoparticles have been experimentally investigated in this work. Different concentrations of nanofluids are injected into the reactor at the operating condition of 29 bar, 274.15 K, and impeller speed of 100 rpm. It was observed that the kinetics of the carbon dioxide hydrate formation process was greatly affected by the nanoparticles. The remarkable point was that at a very low concentration of 20 ppm, a considerable improvement on the carbon dioxide hydrate formation kinetic without using any surfactant was obtained. At the concentration of 20 ppm, the values of the initial rate of hydrate formation, growth time, and induction time were 0.0495, 194.5, and 4.4 min, respectively, which these results can be of great importance for the use of carbon dioxide hydrate in various industries. The results indicated that the kinetics of gas hydrate formation was also severely influenced by the impeller speed and initial gas pressure. The rate of CO2 captured in the hydrate crystalline lattice is also modeled by the first-order kinetic model. It was seen that this model can be used to predict the rate of hydrate formation with considerable accuracy.
Environment
E. Samadpour Shahrak; H. Sattari Sarbangholi; M. S. Moosavi
Abstract
One of the crucial factors for the presence of more people outdoors is to create comfortable conditions. This issue is significant for the elderly due to the different physical conditions. The purpose of this study is to improve the micro-climatic condition around residential complexes considering the ...
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One of the crucial factors for the presence of more people outdoors is to create comfortable conditions. This issue is significant for the elderly due to the different physical conditions. The purpose of this study is to improve the micro-climatic condition around residential complexes considering the elderly in a linear type. For this purpose, two physical indicators, the ratio of the height of buildings to their distance from each other (H/D) and the orientation of them towards the street, were investigated. Regarding H/D, ratios of 0.5, 1, 1.5, and 2, and about the orientation factor, angles of 135° to 200° were examined. This study was conducted outdoors around residential complexes in Iran, Tabriz, with a cold semi-arid climate. Envi-met software model 4.4.5 was used for the simulation. The days June 22 and December 22, 2020 were selected as one of the hottest and coldest day of the year. Two indexes of the Predicted Mean Vote (PMV) and the Universal Thermal Climate Index (UTCI) were examined as essential thermal comfort indexes. Also, for validation, local and field data in six days (21, 22, 23 June in summer and 21, 22, 23 December in winter) were extracted and compared with the data of the software. The results display, the ratio of H/D=1.5 and the angles of 135° and 145° were the most suitable comfort conditions.
Environment
R. Farhadi; M. Hadavifar; M. Moeinaddini; M. Amintoosi
Abstract
Today, air pollution in urban areas is a major issue that have been affecting human health and the environment. Over the years artificial neural network methods has been used for prediction of pollutants concentration in many metropolitans. In the present study data were obtained from department of environment ...
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Today, air pollution in urban areas is a major issue that have been affecting human health and the environment. Over the years artificial neural network methods has been used for prediction of pollutants concentration in many metropolitans. In the present study data were obtained from department of environment and air quality controlling stations in city of Tehran from March 2012 to October 2013. Prediction of CO and PM10 contaminations during cold and warm seasons under the influence of instability indices and meteorological parameters was done using the artificial neural network. Results of the modeling process showed that the highest correlation coefficient was obtained 0.84 for PM10 in warm season. On the contrary, the highest correlation coefficient of CO in cold season was 0.78. Also, the effect of instability indices on air pollution was investigated. The highest CO concentration occurred during cold seasons (R2= 0.81), while the lowest concentration was in warm season (R2= 0.72). In case of PM, the highest concentration occurred during warm seasons (R2= 0.84), while the lowest concentration was in cold season (R2=0.75).
Environment
T. Yahaya; O. Ologe; C. Yaro; L. Abdullahi; H. Abubakar; A. Gazal; J. Abubakar
Abstract
The increasing prevalence of water-borne diseases necessitates periodic monitoring of domestic and drinking water sources. The current study assessed the safety of well water in the four emirate zones (Gwandu, Yauri, Argungu, and Zuru) of Kebbi State, Nigeria. Using normal procedures, samples of well ...
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The increasing prevalence of water-borne diseases necessitates periodic monitoring of domestic and drinking water sources. The current study assessed the safety of well water in the four emirate zones (Gwandu, Yauri, Argungu, and Zuru) of Kebbi State, Nigeria. Using normal procedures, samples of well water were examined for heavy metals, physicochemical characteristics, and microorganisms, and the results were compared to the World Health Organization (WHO) drinking water criteria. The heavy metals’ chronic daily ingestion (CDI) and hazard quotient (HQ) were also determined. The results showed that well water in the four emirate zones had normal temperature, biochemical oxygen demand (BOD), dissolved oxygen (DO), total suspended solids (TSS), and zinc (Zn). However, non-permissible concentrations of lead (Pb), iron (Fe), cadmium (Cd), chromium (Cr), and pH (Gwandu and Argungu only) were detected in all the water samples. Except for Cd and Cr in children, the CDI and HQ of the heavy metals were normal. The microbiological examinations revealed that the water samples from the four zones had abnormal levels of Bacillus species (bacteria), Escherichia coli (bacteria), Staphylococcus aureus (bacteria), Aspergillus niger (fungi), Mucor racemosa (fungi), and Paecilomyces variotti (fungi). The results obtained suggest that well water in the four zones is not suitable for human consumption unless treated.
Environment
R. A. Olaoye; S. O. Ojoawo; O. Bamigbade; N. Alimi; I. O. Rasaq; T. Oladejo
Abstract
The adhesion of metal ions from wastewater to surface of a material in an adsorption process had proven to be effective for remediation of wastewater before discharge. There is a growing demand to utilize alternative low-cost adsorbents for the removal of heavy metals from galvanic wastewater in most ...
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The adhesion of metal ions from wastewater to surface of a material in an adsorption process had proven to be effective for remediation of wastewater before discharge. There is a growing demand to utilize alternative low-cost adsorbents for the removal of heavy metals from galvanic wastewater in most developing countries. Cow bones are cheap, readily available and can be sourced locally from slaughterhouses and abattoir. Therefore, their use as an alternative adsorbent for remediation of galvanic wastewater had to be assessed. In this study, the efficacy of cow bone char (CBC) was assessed for simultaneous heavy metal ions removal from real life galvanic wastewater in a competitive adsorption process. The galvanic wastewater was characterized using atomic adsorption spectrophotometry while the CBC was characterized using X-ray Fluorescence (XRF), Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR). Batch experiment was performed to determine the effect of adsorbent dose, contact time and agitation speed on the removal efficiency of heavy metal ions from the galvanized wastewater. The concentrations of Mn2+, Fe2+, Zn2+, Pb2+ and Cr2+ in the raw wastewater exceeded the WHO and EPA standards. The adsorbent revealed a significant distribution of well-developed porous, rough surfaces with cracks characterized by different functional groups for the efficient adsorption process. The optimum adsorbent dose for all the metal ions was 0.04 g/100 mL at an optimum contact time of 60 minutes except for Fe2+ with optimum contact time of 20 minutes, and agitation speed of 150 rpm. The maximum metal removal efficiencies obtained for Mn2+, Fe2+, Zn2+, Pb2+ and Cr2were 99.7%, 100%, 99%, 90% and 85% +, respectively. The average adsorption capacity for Mn2+, Fe2+, Zn2+, Pb2+ and Cr2+were 0.44 mg/g, 26.7 mg/g, 78.5 mg/g, 0.133 mg/g for and 10.36 mg/g, respectively. CBC offers efficient and cost-effective removal of selected metal ions from galvanized wastewater.
Environment
M. Moallem; H. Hassanpour; A. A. Pouyan
Abstract
Smart homes enable many people, especially the elderly and patients, to live alone and maintain their independence and comfort. The realization of this goal depends on monitoring all activities in the house to report any observed anomaly immediately to their relatives or nurses. Anomaly detection in ...
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Smart homes enable many people, especially the elderly and patients, to live alone and maintain their independence and comfort. The realization of this goal depends on monitoring all activities in the house to report any observed anomaly immediately to their relatives or nurses. Anomaly detection in smart homes, just by existing data, is not an easy task. In this work, we train a recurrent network with raw outputs of binary sensors, including motion and door sensors, to predict which sensor will be switched on/off in the next event, and how long this on/off mode will last. Then, using Beam Search, we extend this event into k sequences of consecutive events to determine the possible range of upcoming activities. The error of this prediction i.e., the distance between these possible sequences and the real string of events is evaluated using several innovative methods for measuring the spatio-temporal similarity of the sequences. Modeling this error as a Gaussian distribution allows to assess the likelihood of anomaly scores. The input sequences that are ranked higher than a certain threshold will be considered as abnormal activities. The results of the experiments showed that this method enables the detection of abnormal activities with desirable accuracy.
Environment
V. Kanthe; S. Deo; M. Murmu
Abstract
In this research paper, the effect on autogenous healing in concrete by cementitious material such as fly ash (FA) and rice husk ash (RHA) are reported. The utilization of waste byproduct are the interest in research for healing of concrete. The non-destructive testing and microstructure analysis were ...
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In this research paper, the effect on autogenous healing in concrete by cementitious material such as fly ash (FA) and rice husk ash (RHA) are reported. The utilization of waste byproduct are the interest in research for healing of concrete. The non-destructive testing and microstructure analysis were conducted to quantify autogenous healing in concrete. The concrete specimens prepared with different proportion of FA and RHA. The satisfactory results of non- destructive test were obtained with respect to the durability of concrete. In the chemical and microstructure analysis the calcium carbonate crystals formed on healed cracks surface and dense particle packing in the matrix of concrete were observed. This type of ternary blend is useful for making durable and sustainable concrete structure. The utilization of industrial and agricultural byproduct reduces the effect of environmental pollution and also reduces the consumption of cement with the same reduction in CO2 emition from cement industry.
Environment
E. S. Aghaee Meybodi; M. Ghasemzadeh
Abstract
Prediction of software vulnerabilities-severity is of particular importance. Its most important application is that managers can first deal with the most dangerous vulnerabilities when they have limited resources. This research shows how we can use the former patterns of software vulnerabilities-severity ...
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Prediction of software vulnerabilities-severity is of particular importance. Its most important application is that managers can first deal with the most dangerous vulnerabilities when they have limited resources. This research shows how we can use the former patterns of software vulnerabilities-severity along with machine learning methods to predict the vulnerabilities severity of that software in the future. In this regard, we used the SVM, Decision Trees (DT), Random Forests (RF), K Nearest Neighbors (KNN), bagging and AdaBoost algorithms along with the already reported vulnerabilities of Google Android applications, Apple Safari and the Flash Player. The experimental results showed that the Bagging algorithm can predict Google Android vulnerability with accuracy of 78.21% and f1-measure equal to 77%, the vulnerability of the Flash Player software with accuracy of 82.37% and f1-measure equal to 87.73% and predict the vulnerability severity of the Apple Safari with accuracy of 70.58% and f1-measure equal to 70%. The novelty of this research is introduction of a new method for prediction of software vulnerabilities severity.
