Abstract
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Maryam Khashij, Arash Dalvand, Mohammad Mehralian, Ali Asghar Ebrahimi and Rasoul Khosravi
The purpose of this paper is to analyze zero valent iron nanoparticles (NZVIs) by a novel green method, taken from Thymus vulgaris (TV) plant extract, were synthesized and applied…
Abstract
Purpose
The purpose of this paper is to analyze zero valent iron nanoparticles (NZVIs) by a novel green method, taken from Thymus vulgaris (TV) plant extract, were synthesized and applied to degrade reactive black 5 (RB5) azo dye.
Design/methodology/approach
The optimum conditions for the highest removal of RB5 dye were determined. Characterization of NZVIs was done by scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM) and X-ray diffraction (XRD). The NZVIs were used for the removal of dye RB5, and the parameters affecting were discussed like pH, initial concentration, contact time and NZVIs dosage.
Findings
The characterization results of NZVIs by SEM, TEM, FTIR and XRD show that polyphenols, organic acids and proteins reduce not only the green synthesis of NZVIs but also the aggregation of nanoparticles. The maximum dye removal efficiency of 99.6 per cent occurred at pH 4, NZVIs dose of 600 mg/L, and contact time of 5 min. The adsorption of RB5 dye onto the NZVIs surface and scavenging of the azo bond (−N = N) by the strong reduction of NZVIs were the proposed mechanisms for dye removal. The application of NZVIs to treat wastewater containing reactive dye shows high degradation efficiency.
Research limitations/implications
The findings may greatly benefit the application of the NZVIs taken from Thymus vulgaris (TV) in the fields of dye adsorption.
Practical implications
The present study is novel because it incorporated the morphological and structural properties of the synthesized NZVIs using a native plant of Iran and studied the capability of green-synthesized NZVIs to remove RB5 as a water contaminant.
Social implications
The native plant presented here can be developed for reduced environmental pollution before discharge to accepted water.
Originality/value
The NZVIs is prepared via green-synthesized method, which is prepared with leaves of TV. There are two main innovations. One is that the novel NZVIs is prepared successfully by native plant via green-synthesized method. The other is that the optimized conditions were obtained for the removal of RB5 dye as a water contaminant. Furthermore, to the best of our knowledge, no study has ever investigated the removal of RB5 by NZVIs produced using a native plant in Iran.
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Mohammad Olfat, Azadeh Rezvani, Pouria Khosravi, Sajjad Shokouhyar and Atieh Sedaghat
Although online social networks (SNs) (e.g. Facebook, LinkedIn and Instagram) have been used by employees for various work- or non-work-related motives, there has been lack of…
Abstract
Purpose
Although online social networks (SNs) (e.g. Facebook, LinkedIn and Instagram) have been used by employees for various work- or non-work-related motives, there has been lack of research on the use of such networks in the workplace. The purpose of this paper is to draw on commitment theory and the tricomponent attitude model to explain the role organisational commitment plays in predicting the work-related use of online SNs and the mediating role a constructive employee voice may have in this relationship.
Design/methodology/approach
The research was conducted among the employees of seven different companies within seven different industries. The validity of the measures and structural models was evaluated using partial least squares structural equation modelling (PLS-SEM).
Findings
The results indicated that organisational commitment promotes employees’ work-related use of online SNs directly and also indirectly via the mediating role of a constructive voice.
Originality/value
This study is among the few studies which have used the tricomponent attitude model to investigate employees’ behaviour in the workplace, in particular work-related use of online SNs. In terms of theory, this study contributes to expanding the boundaries of knowledge as SNs are considered a challenge in contemporary organisations. Organisations can convert this challenge from a potential threat to an actual opportunity by reinforcing “organisational commitment”.
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Qingang Xiong, Arash Khosravi, Narjes Nabipour, Mohammad Hossein Doranehgard, Aida Sabaghmoghadam and David Ross
This paper aims to numerically investigate the nanofluid flow, heat transfer and entropy generation during natural convection in an annulus.
Abstract
Purpose
This paper aims to numerically investigate the nanofluid flow, heat transfer and entropy generation during natural convection in an annulus.
Design/methodology/approach
The lattice Boltzmann method is used to simulate the velocity and temperature fields. Furthermore, some special modifications are applied to make the lattice Boltzmann method capable for simulation in the curved boundary conditions. The annulus is filled with CuO-water nanofluid. The dynamic viscosity of nanofluid is estimated using KLL (Koo-Kleinstreuer-Li) model, and the nanoparticle shape effect is taken account in calculating the thermal conductivity. On the other hand, the local/volumetric entropy generation is used to show the irreversibility under influence of different parameters.
Findings
The effect of considered governing parameters including Rayleigh number (103<Ra < 106); nanoparticle concentration (0<<0.04) and configuration of annulus on the flow structure; temperature field; and local and total entropy generation and heat transfer rate are presented.
Originality/value
The originality of this work is using of lattice Boltzmann method is simulation of natural convection in a curved configuration and using of Koo–Kleinstreuer–Li correlation for simulation of nanofluid.
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Mohammad Ranjbar Ezzatabadi, Ameneh Khosravi, Mohammad Amin Bahrami and Sima Rafiei
Developing country workers mainly face important challenges when examining equality in health services utilization among the population and identifying influential factors. The…
Abstract
Purpose
Developing country workers mainly face important challenges when examining equality in health services utilization among the population and identifying influential factors. The purpose of this paper us to: understand health service use among households with different socio-economic status in Isfahan province; and to investigate probable inequality determinants in service utilization.
Design/methodology/approach
Almost 1,040 households living in Isfahan province participated in this cross-sectional study in 2013. Data were collected by a questionnaire with three sections: demographic characteristics; socio-economic status; and health services utilization. The concentration index was applied to measure inequality. Analysts used STATA 11.
Findings
Economic status, educational level, insurance coverage and household gender were the most influential factors on health services utilization. Those with a high socio-economic level were more likely to demand and use such services; although self-medication patterns showed an opposite trend.
Practical implications
Female-headed families face with more difficulties in access to basic human needs including health. Supportive policies are needed to meet their demands.
Originality/value
The authors used principle component analysis to assess households’ economic situation, which reduced the variables into a single index.
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Sara Valadi-khorram, Mohammad Reza Amiri and Mohammad Karim Saberi
Considering the important role of public libraries in providing health information service as well as user feedback in improving the quality of health information services, the…
Abstract
Purpose
Considering the important role of public libraries in providing health information service as well as user feedback in improving the quality of health information services, the purpose of this study is to evaluate the quality of health information service in public libraries of Hamadan, Iran, on the basis of the modified LibQUAL model
Design/methodology/approach
This practical research was conducted in an analytic-survey method. The statistical population consists of all members of public libraries of Hamadan over 18 years old (12,237 people), and the sample size is calculated to be 373 people. The stratified sampling method was used, and within each class, a convenience sampling method was used. The modified LibQUAL questionnaire was used to gather data. For checking normality of data distribution, the Kolmogorov–Smirnov test and for analyzing date, descriptive statistics and also Chi-square and Wilcoxon tests were applied using SPSS 25.
Findings
The users' minimum level of public libraries in all three dimensions is an average level. The users' desired level of “information control” is higher than other dimensions. The users' perceived level in dimensions of “human resources” and “information control” is high level, while users' perceived level in “educational service” is an “average” level. There is a superiority gap between desired and perceived level in all dimensions, but the adequacy gap was seen only in the dimension of “educational service.”
Research limitations/implications
In this study, the quality of health information services provided in public libraries is evaluated by the LibQUAL model.
Practical implications
The results of this research can help managers and librarians of public libraries in measuring the quality of health information services and improving the quality of services provided by libraries. Besides, they can take a more accurate planning and pathologic approach, to eliminate the gap between minimum and desired expectations of users and libraries’ real services.
Originality/value
In this study, the quality of health information services provided in public libraries is evaluated by LibQUAL tool.
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Hadi Mahamivanan, Navid Ghassemi, Mohammad Tayarani Darbandy, Afshin Shoeibi, Sadiq Hussain, Farnad Nasirzadeh, Roohallah Alizadehsani, Darius Nahavandi, Abbas Khosravi and Saeid Nahavandi
This paper aims to propose a new deep learning technique to detect the type of material to improve automated construction quality monitoring.
Abstract
Purpose
This paper aims to propose a new deep learning technique to detect the type of material to improve automated construction quality monitoring.
Design/methodology/approach
A new data augmentation approach that has improved the model robustness against different illumination conditions and overfitting is proposed. This study uses data augmentation at test time and adds outlier samples to training set to prevent over-fitted network training. For data augmentation at test time, five segments are extracted from each sample image and fed to the network. For these images, the network outputting average values is used as the final prediction. Then, the proposed approach is evaluated on multiple deep networks used as material classifiers. The fully connected layers are removed from the end of the networks, and only convolutional layers are retained.
Findings
The proposed method is evaluated on recognizing 11 types of building materials which include 1,231 images taken from several construction sites. Each image resolution is 4,000 × 3,000. The images are captured with different illumination and camera positions. Different illumination conditions lead to trained networks that are more robust against various environmental conditions. Using VGG16 model, an accuracy of 97.35% is achieved outperforming existing approaches.
Practical implications
It is believed that the proposed method presents a new and robust tool for detecting and classifying different material types. The automated detection of material will aid to monitor the quality and see whether the right type of material has been used in the project based on contract specifications. In addition, the proposed model can be used as a guideline for performing quality control (QC) in construction projects based on project quality plan. It can also be used as an input for automated progress monitoring because the material type detection will provide a critical input for object detection.
Originality/value
Several studies have been conducted to perform quality management, but there are some issues that need to be addressed. In most previous studies, a very limited number of material types were examined. In addition, although some studies have reported high accuracy to detect material types (Bunrit et al., 2020), their accuracy is dramatically reduced when they are used to detect materials with similar texture and color. In this research, the authors propose a new method to solve the mentioned shortcomings.
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Mohammad Reza Fallah and Maryam Soori
The concentration of women entrepreneurs on influential events such as the development of green entrepreneurship, which lead to the coordination and dynamic balance between…
Abstract
Purpose
The concentration of women entrepreneurs on influential events such as the development of green entrepreneurship, which lead to the coordination and dynamic balance between economic and environmental goals, can create a bright future for businesses with sustainable and environmentally friendly architecture. The main purpose of this study is to provide a framework for the successful entry of women entrepreneurs into green entrepreneurship.
Design/methodology/approach
The present qualitative applied descriptive-analytical study was conducted on a population of women entrepreneurs working in green businesses. This population was obtained by the non-probability chain sampling method and an exploratory interview with the saturation of 12 individuals. Thematic analysis was used to analyze the findings.
Findings
The results revealed that creating shared value, inclusive social acceptance, multifaceted interactions and green dynamic bedding are effective in the entry of women entrepreneurs into green entrepreneurship in the form of “competitive empowerment” and “multiplied green synergy”. Thus, managers and planners should consider some factors, including shared value, social acceptance, inclusive acceptance, building green culture, knowledge flows, multiple participation, networking dimension, green marketing, competitiveness, creating platforms, green technologies and risk management.
Originality/value
This research tries to present a framework for the entry of women entrepreneurs into green entrepreneurship area.
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Mohammad Amin Shayegan and Saeed Aghabozorgi
Pattern recognition systems often have to handle problem of large volume of training data sets including duplicate and similar training samples. This problem leads to large memory…
Abstract
Purpose
Pattern recognition systems often have to handle problem of large volume of training data sets including duplicate and similar training samples. This problem leads to large memory requirement for saving and processing data, and the time complexity for training algorithms. The purpose of the paper is to reduce the volume of training part of a data set – in order to increase the system speed, without any significant decrease in system accuracy.
Design/methodology/approach
A new technique for data set size reduction – using a version of modified frequency diagram approach – is presented. In order to reduce processing time, the proposed method compares the samples of a class to other samples in the same class, instead of comparing samples from different classes. It only removes patterns that are similar to the generated class template in each class. To achieve this aim, no feature extraction operation was carried out, in order to produce more precise assessment on the proposed data size reduction technique.
Findings
The results from the experiments, and according to one of the biggest handwritten numeral standard optical character recognition (OCR) data sets, Hoda, show a 14.88 percent decrease in data set volume without significant decrease in performance.
Practical implications
The proposed technique is effective for size reduction for all pictorial databases such as OCR data sets.
Originality/value
State-of-the-art algorithms currently used for data set size reduction usually remove samples near to class's centers, or support vector (SV) samples between different classes. However, the samples near to a class center have valuable information about class characteristics, and they are necessary to build a system model. Also, SV s are important samples to evaluate the system efficiency. The proposed technique, unlike the other available methods, keeps both outlier samples, as well as the samples close to the class centers.