The relationship between smoking status and smoking cessation practice for health workers in Surabaya
- Artanti, Kurnia, Martini, Santi, Mahmudah, Mahmudah, Widati, Sri, Adila, Diva, Rahman, Muhammad Aziz
- Authors: Artanti, Kurnia , Martini, Santi , Mahmudah, Mahmudah , Widati, Sri , Adila, Diva , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Public Health in Africa Vol. 14, no. S2 (2023), p.
- Full Text:
- Reviewed:
- Description: Background. Indonesia is one of the countries that have a high smoker prevalence globally. Therefore, a smoking cessation pro- gram is key to reducing the smoking prevalence in Indonesia. The role of health workers is necessary for smoking cessation pro-grams. However, smoking behavior among health workers could limit smoking cessation practices for patients. Objective. This study aims to analyze smoking behavior and 5A smoking cessation (Ask, Advice, Assess, Assist, and Arrange) practices among health workers. Materials and Methods. This study design is cross-sectional with a simple random sampling from the population of health workers in Surabaya. The total sample of this study counted 60 health workers. The data were analyzed in univariate and bivariate using SPSS 18 application. Bivariate analysis using a chi-square or Fisher exact test was conducted to analyze the relationship between smoking status and 5A smoking cessation practice. Results. Report of main outcomes or findings, including (where relevant) levels of statistical significance and confidence intervals. The result of this study shows that the asking practice was the most practiced item in the 5A model among health workers (98.3%). There was no significant association between smoking behavior and 5A implementation among health workers (PR=0.40; 95%CI: 0.52-5.30; P=1.67). Conclusions. There was no significant association between respondents’ characteristics, smoking cessation training, and pro-fessional roles with 5A implementation. © the Author(s), 2023.
- Authors: Artanti, Kurnia , Martini, Santi , Mahmudah, Mahmudah , Widati, Sri , Adila, Diva , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Public Health in Africa Vol. 14, no. S2 (2023), p.
- Full Text:
- Reviewed:
- Description: Background. Indonesia is one of the countries that have a high smoker prevalence globally. Therefore, a smoking cessation pro- gram is key to reducing the smoking prevalence in Indonesia. The role of health workers is necessary for smoking cessation pro-grams. However, smoking behavior among health workers could limit smoking cessation practices for patients. Objective. This study aims to analyze smoking behavior and 5A smoking cessation (Ask, Advice, Assess, Assist, and Arrange) practices among health workers. Materials and Methods. This study design is cross-sectional with a simple random sampling from the population of health workers in Surabaya. The total sample of this study counted 60 health workers. The data were analyzed in univariate and bivariate using SPSS 18 application. Bivariate analysis using a chi-square or Fisher exact test was conducted to analyze the relationship between smoking status and 5A smoking cessation practice. Results. Report of main outcomes or findings, including (where relevant) levels of statistical significance and confidence intervals. The result of this study shows that the asking practice was the most practiced item in the 5A model among health workers (98.3%). There was no significant association between smoking behavior and 5A implementation among health workers (PR=0.40; 95%CI: 0.52-5.30; P=1.67). Conclusions. There was no significant association between respondents’ characteristics, smoking cessation training, and pro-fessional roles with 5A implementation. © the Author(s), 2023.
Prediction of blast-induced ground vibration at a limestone quarry : an artificial intelligence approach
- Arthur, Clement, Bhatawdekar, Ramesh, Mohamad, Edy, Sabri, Mohanad, Bohra, Manish, Khandelwal, Manoj, Kwon, Sangki
- Authors: Arthur, Clement , Bhatawdekar, Ramesh , Mohamad, Edy , Sabri, Mohanad , Bohra, Manish , Khandelwal, Manoj , Kwon, Sangki
- Date: 2022
- Type: Text , Journal article
- Relation: Applied Sciences (Switzerland) Vol. 12, no. 18 (2022), p.
- Full Text:
- Reviewed:
- Description: Ground vibration is one of the most unfavourable environmental effects of blasting activities, which can cause serious damage to neighboring homes and structures. As a result, effective forecasting of their severity is critical to controlling and reducing their recurrence. There are several conventional vibration predictor equations available proposed by different researchers but most of them are based on only two parameters, i.e., explosive charge used per delay and distance between blast face to the monitoring point. It is a well-known fact that blasting results are influenced by a number of blast design parameters, such as burden, spacing, powder factor, etc. but these are not being considered in any of the available conventional predictors and due to that they show a high error in predicting blast vibrations. Nowadays, artificial intelligence has been widely used in blast engineering. Thus, three artificial intelligence approaches, namely Gaussian process regression (GPR), extreme learning machine (ELM) and backpropagation neural network (BPNN) were used in this study to estimate ground vibration caused by blasting in Shree Cement Ras Limestone Mine in India. To achieve that aim, 101 blasting datasets with powder factor, average depth, distance, spacing, burden, charge weight, and stemming length as input parameters were collected from the mine site. For comparison purposes, a simple multivariate regression analysis (MVRA) model as well as, a nonparametric regression-based technique known as multivariate adaptive regression splines (MARS) was also constructed using the same datasets. This study serves as a foundational study for the comparison of GPR, BPNN, ELM, MARS and MVRA to ascertain their respective predictive performances. Eighty-one (81) datasets representing 80% of the total blasting datasets were used to construct and train the various predictive models while 20 data samples (20%) were utilized for evaluating the predictive capabilities of the developed predictive models. Using the testing datasets, major indicators of performance, namely mean squared error (MSE), variance accounted for (VAF), correlation coefficient (R) and coefficient of determination (R2) were compared as statistical evaluators of model performance. This study revealed that the GPR model exhibited superior predictive capability in comparison to the MARS, BPNN, ELM and MVRA. The GPR model showed the highest VAF, R and R2 values of 99.1728%, 0.9985 and 0.9971 respectively and the lowest MSE of 0.0903. As a result, the blast engineer can employ GPR as an effective and appropriate method for forecasting blast-induced ground vibration. © 2022 by the authors.
- Authors: Arthur, Clement , Bhatawdekar, Ramesh , Mohamad, Edy , Sabri, Mohanad , Bohra, Manish , Khandelwal, Manoj , Kwon, Sangki
- Date: 2022
- Type: Text , Journal article
- Relation: Applied Sciences (Switzerland) Vol. 12, no. 18 (2022), p.
- Full Text:
- Reviewed:
- Description: Ground vibration is one of the most unfavourable environmental effects of blasting activities, which can cause serious damage to neighboring homes and structures. As a result, effective forecasting of their severity is critical to controlling and reducing their recurrence. There are several conventional vibration predictor equations available proposed by different researchers but most of them are based on only two parameters, i.e., explosive charge used per delay and distance between blast face to the monitoring point. It is a well-known fact that blasting results are influenced by a number of blast design parameters, such as burden, spacing, powder factor, etc. but these are not being considered in any of the available conventional predictors and due to that they show a high error in predicting blast vibrations. Nowadays, artificial intelligence has been widely used in blast engineering. Thus, three artificial intelligence approaches, namely Gaussian process regression (GPR), extreme learning machine (ELM) and backpropagation neural network (BPNN) were used in this study to estimate ground vibration caused by blasting in Shree Cement Ras Limestone Mine in India. To achieve that aim, 101 blasting datasets with powder factor, average depth, distance, spacing, burden, charge weight, and stemming length as input parameters were collected from the mine site. For comparison purposes, a simple multivariate regression analysis (MVRA) model as well as, a nonparametric regression-based technique known as multivariate adaptive regression splines (MARS) was also constructed using the same datasets. This study serves as a foundational study for the comparison of GPR, BPNN, ELM, MARS and MVRA to ascertain their respective predictive performances. Eighty-one (81) datasets representing 80% of the total blasting datasets were used to construct and train the various predictive models while 20 data samples (20%) were utilized for evaluating the predictive capabilities of the developed predictive models. Using the testing datasets, major indicators of performance, namely mean squared error (MSE), variance accounted for (VAF), correlation coefficient (R) and coefficient of determination (R2) were compared as statistical evaluators of model performance. This study revealed that the GPR model exhibited superior predictive capability in comparison to the MARS, BPNN, ELM and MVRA. The GPR model showed the highest VAF, R and R2 values of 99.1728%, 0.9985 and 0.9971 respectively and the lowest MSE of 0.0903. As a result, the blast engineer can employ GPR as an effective and appropriate method for forecasting blast-induced ground vibration. © 2022 by the authors.
DQN approach for adaptive self-healing of VNFs in cloud-native network
- Arulappan, Arunkumar, Mahanti, Aniket, Passi, Kalpdrum, Srinivasan, Thiruvenkadam, Naha, Ranesh, Raja, Gunasekaran
- Authors: Arulappan, Arunkumar , Mahanti, Aniket , Passi, Kalpdrum , Srinivasan, Thiruvenkadam , Naha, Ranesh , Raja, Gunasekaran
- Date: 2024
- Type: Text , Journal article
- Relation: IEEE Access Vol. 12, no. (2024), p. 34489-34504
- Full Text:
- Reviewed:
- Description: The transformation from physical network function to Virtual Network Function (VNF) requires a fundamental design change in how applications and services are tested and assured in a hybrid virtual network. Once the VNFs are onboarded in a cloud network infrastructure, operators need to test VNFs in real-time at the time of instantiation automatically. This paper explicitly analyses the problem of adaptive self-healing of a Virtual Machine (VM) allocated by the VNF with the Deep Reinforcement Learning (DRL) approach. The DRL-based big data collection and analytics engine performs aggregation to probe and analyze data for troubleshooting and performance management. This engine helps to determine corrective actions (self-healing), such as scaling or migrating VNFs. Hence, we proposed a Deep Queue Learning (DQL) based Deep Queue Networks (DQN) mechanism for self-healing VNFs in the virtualized infrastructure manager. Virtual network probes of closed-loop orchestration perform the automation of the VNF and provide analytics for real-time, policy-driven orchestration in an open networking automation platform through the stochastic gradient descent method for VNF service assurance and network reliability. The proposed DQN/DDQN mechanism optimizes the price and lowers the cost by 18% for resource usage without disrupting the Quality of Service (QoS) provided by the VNF. The outcome of adaptive self-healing of the VNFs enhances the computational performance by 27% compared to other state-of-the-art algorithms. © 2013 IEEE.
- Authors: Arulappan, Arunkumar , Mahanti, Aniket , Passi, Kalpdrum , Srinivasan, Thiruvenkadam , Naha, Ranesh , Raja, Gunasekaran
- Date: 2024
- Type: Text , Journal article
- Relation: IEEE Access Vol. 12, no. (2024), p. 34489-34504
- Full Text:
- Reviewed:
- Description: The transformation from physical network function to Virtual Network Function (VNF) requires a fundamental design change in how applications and services are tested and assured in a hybrid virtual network. Once the VNFs are onboarded in a cloud network infrastructure, operators need to test VNFs in real-time at the time of instantiation automatically. This paper explicitly analyses the problem of adaptive self-healing of a Virtual Machine (VM) allocated by the VNF with the Deep Reinforcement Learning (DRL) approach. The DRL-based big data collection and analytics engine performs aggregation to probe and analyze data for troubleshooting and performance management. This engine helps to determine corrective actions (self-healing), such as scaling or migrating VNFs. Hence, we proposed a Deep Queue Learning (DQL) based Deep Queue Networks (DQN) mechanism for self-healing VNFs in the virtualized infrastructure manager. Virtual network probes of closed-loop orchestration perform the automation of the VNF and provide analytics for real-time, policy-driven orchestration in an open networking automation platform through the stochastic gradient descent method for VNF service assurance and network reliability. The proposed DQN/DDQN mechanism optimizes the price and lowers the cost by 18% for resource usage without disrupting the Quality of Service (QoS) provided by the VNF. The outcome of adaptive self-healing of the VNFs enhances the computational performance by 27% compared to other state-of-the-art algorithms. © 2013 IEEE.
Managing the resource allocation for the COVID-19 pandemic in healthcare institutions : a pluralistic perspective
- Arunmozhi, Manimuthu, Persis, Jinil, Sreedharan, V., Chakraborty, Ayon, Zouadi, Tarik, Khamlichi, Hanane
- Authors: Arunmozhi, Manimuthu , Persis, Jinil , Sreedharan, V. , Chakraborty, Ayon , Zouadi, Tarik , Khamlichi, Hanane
- Date: 2022
- Type: Text , Journal article
- Relation: International Journal of Quality and Reliability Management Vol. 39, no. 9 (2022), p. 2184-2204
- Full Text:
- Reviewed:
- Description: Purpose: As COVID-19 outbreak has created a global crisis, treating patients with minimum resources and traditional methods has become a hectic task. In this technological era, the rapid growth of coronavirus has affected the countries in lightspeed manner. Therefore, the present study proposes a model to analyse the resource allocation for the COVID-19 pandemic from a pluralistic perspective. Design/methodology/approach: The present study has combined data analytics with the K-mean clustering and probability queueing theory (PQT) and analysed the evolution of COVID-19 all over the world from the data obtained from public repositories. By using K-mean clustering, partitioning of patients’ records along with their status of hospitalization can be mapped and clustered. After K-mean analysis, cluster functions are trained and modelled along with eigen vectors and eigen functions. Findings: After successful iterative training, the model is programmed using R functions and given as input to Bayesian filter for predictive model analysis. Through the proposed model, disposal rate; PPE (personal protective equipment) utilization and recycle rate for different countries were calculated. Research limitations/implications: Using probabilistic queueing theory and clustering, the study was able to predict the resource allocation for patients. Also, the study has tried to model the failure quotient ratio upon unsuccessful delivery rate in crisis condition. Practical implications: The study has gathered epidemiological and clinical data from various government websites and research laboratories. Using these data, the study has identified the COVID-19 impact in various countries. Further, effective decision-making for resource allocation in pluralistic setting has being evaluated for the practitioner's reference. Originality/value: Further, the proposed model is a two-stage approach for vulnerability mapping in a pandemic situation in a healthcare setting for resource allocation and utilization. © 2021, Emerald Publishing Limited.
- Authors: Arunmozhi, Manimuthu , Persis, Jinil , Sreedharan, V. , Chakraborty, Ayon , Zouadi, Tarik , Khamlichi, Hanane
- Date: 2022
- Type: Text , Journal article
- Relation: International Journal of Quality and Reliability Management Vol. 39, no. 9 (2022), p. 2184-2204
- Full Text:
- Reviewed:
- Description: Purpose: As COVID-19 outbreak has created a global crisis, treating patients with minimum resources and traditional methods has become a hectic task. In this technological era, the rapid growth of coronavirus has affected the countries in lightspeed manner. Therefore, the present study proposes a model to analyse the resource allocation for the COVID-19 pandemic from a pluralistic perspective. Design/methodology/approach: The present study has combined data analytics with the K-mean clustering and probability queueing theory (PQT) and analysed the evolution of COVID-19 all over the world from the data obtained from public repositories. By using K-mean clustering, partitioning of patients’ records along with their status of hospitalization can be mapped and clustered. After K-mean analysis, cluster functions are trained and modelled along with eigen vectors and eigen functions. Findings: After successful iterative training, the model is programmed using R functions and given as input to Bayesian filter for predictive model analysis. Through the proposed model, disposal rate; PPE (personal protective equipment) utilization and recycle rate for different countries were calculated. Research limitations/implications: Using probabilistic queueing theory and clustering, the study was able to predict the resource allocation for patients. Also, the study has tried to model the failure quotient ratio upon unsuccessful delivery rate in crisis condition. Practical implications: The study has gathered epidemiological and clinical data from various government websites and research laboratories. Using these data, the study has identified the COVID-19 impact in various countries. Further, effective decision-making for resource allocation in pluralistic setting has being evaluated for the practitioner's reference. Originality/value: Further, the proposed model is a two-stage approach for vulnerability mapping in a pandemic situation in a healthcare setting for resource allocation and utilization. © 2021, Emerald Publishing Limited.
Global lessons from successful rhinoceros conservation in Nepal
- Aryal, Achyut, Acharya, Krishna, Shrestha, Uttam Babu, Dhakal, Maheshwar, Raubenhiemer, David, Wright, Wendy
- Authors: Aryal, Achyut , Acharya, Krishna , Shrestha, Uttam Babu , Dhakal, Maheshwar , Raubenhiemer, David , Wright, Wendy
- Date: 2017
- Type: Text , Journal article
- Relation: Conservation Biology Vol. 31, no. 6 (2017), p. 1494-1497
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- Reviewed:
- Authors: Aryal, Achyut , Acharya, Krishna , Shrestha, Uttam Babu , Dhakal, Maheshwar , Raubenhiemer, David , Wright, Wendy
- Date: 2017
- Type: Text , Journal article
- Relation: Conservation Biology Vol. 31, no. 6 (2017), p. 1494-1497
- Full Text:
- Reviewed:
The impacts of water pricing and non-pricing policies on sustainable water resources management : A case of Ghorveh Plain at Kurdistan province, Iran
- Asaadi, Mohammad, Mortazavi, Seyed, Zamani, Omid, Najafi, Gholam, Yusaf, Talal, Hoseini, Seyed
- Authors: Asaadi, Mohammad , Mortazavi, Seyed , Zamani, Omid , Najafi, Gholam , Yusaf, Talal , Hoseini, Seyed
- Date: 2019
- Type: Text , Journal article
- Relation: Energies Vol. 12, no. 14 (2019), p. 1-16
- Full Text:
- Reviewed:
- Description: As with other regions of Iran, due to excessive extraction of groundwater for intense agricultural activity, Ghorveh plain, a water-scarce irrigation district in the west of Iran, has faced a serious water crisis during the last decade. The present study investigates the impacts of two scenario policies, namely, non-price policy (as a supply-oriented policy) and water pricing policies (as a demand-oriented policy) on agricultural sector of Ghorveh Plain, using positive mathematical programming (PMP). The model was calibrated by using farm-level data for the crop years in 2016-2017. Our findings indicate that applying water supply constraint policy will change the land use and cropping pattern to the crops with higher water productivity. The increase of water resource constraints can lead to the increase of water economic return which indicates a rising value of water resources shortage, warning the producers of the agriculture sector to allocate water to the crops with higher economic value under the water resources shortage conditions. In addition, the findings underline that in a situation where the price of irrigation water is low due to the low elasticity of water demand in the agriculture sector, formulating the economic instruments such as rising water prices does not solely suffice to achieve sustainable water resource management. However, mixed scenarios emphasized that the water distribution policies should be aligned with the increases in water cost.
- Authors: Asaadi, Mohammad , Mortazavi, Seyed , Zamani, Omid , Najafi, Gholam , Yusaf, Talal , Hoseini, Seyed
- Date: 2019
- Type: Text , Journal article
- Relation: Energies Vol. 12, no. 14 (2019), p. 1-16
- Full Text:
- Reviewed:
- Description: As with other regions of Iran, due to excessive extraction of groundwater for intense agricultural activity, Ghorveh plain, a water-scarce irrigation district in the west of Iran, has faced a serious water crisis during the last decade. The present study investigates the impacts of two scenario policies, namely, non-price policy (as a supply-oriented policy) and water pricing policies (as a demand-oriented policy) on agricultural sector of Ghorveh Plain, using positive mathematical programming (PMP). The model was calibrated by using farm-level data for the crop years in 2016-2017. Our findings indicate that applying water supply constraint policy will change the land use and cropping pattern to the crops with higher water productivity. The increase of water resource constraints can lead to the increase of water economic return which indicates a rising value of water resources shortage, warning the producers of the agriculture sector to allocate water to the crops with higher economic value under the water resources shortage conditions. In addition, the findings underline that in a situation where the price of irrigation water is low due to the low elasticity of water demand in the agriculture sector, formulating the economic instruments such as rising water prices does not solely suffice to achieve sustainable water resource management. However, mixed scenarios emphasized that the water distribution policies should be aligned with the increases in water cost.
The effects of plyometric training on change-of-direction ability : A meta-analysis
- Asadi, Abbas, Arazi, Hamid, Young, Warren, De Villarreal, Eduardo
- Authors: Asadi, Abbas , Arazi, Hamid , Young, Warren , De Villarreal, Eduardo
- Date: 2016
- Type: Text , Journal article , Review
- Relation: International Journal of Sports Physiology and Performance Vol. 11, no. 5 (2016), p. 563-573
- Full Text:
- Reviewed:
- Description: Purpose: To show a clear picture about the possible variables of enhancements of change-of-direction (COD) ability using longitudinal plyometric-training (PT) studies and determine specific factors that influence the training effects. Methods: A computerized search was performed, and 24 articles with a total of 46 effect sizes (ESs) in an experimental group and 25 ESs in a control group were reviewed to analyze the role of various factors on the impact of PT on COD performance. Results: The results showed that participants with good ftness levels obtained greater improvements in COD performance (P <.05), and basketball players gained more benefits of PT than other athletes. Also, men obtained COD results similar to those of women after PT. In relation to the variables of PT design, it appears that 7 wk (with 2 sessions/wk) using moderate intensity and 100 jumps per training session with a 72-h rest interval tends to improve COD ability. Performing PT with a combination of different types of plyometric exercises such as drop jumps + vertical jumps + standing long jumps is better than 1 form of exercise. Conclusion: It is apparent that PT can be effective at improving COD ability. The loading parameters are essential for exercise professionals, coaches, and strength and conditioning professionals with regard to the most appropriate dose-response trends to optimize plyometric-induced COD-ability gains. © 2016 Human Kinetics, Inc.
- Authors: Asadi, Abbas , Arazi, Hamid , Young, Warren , De Villarreal, Eduardo
- Date: 2016
- Type: Text , Journal article , Review
- Relation: International Journal of Sports Physiology and Performance Vol. 11, no. 5 (2016), p. 563-573
- Full Text:
- Reviewed:
- Description: Purpose: To show a clear picture about the possible variables of enhancements of change-of-direction (COD) ability using longitudinal plyometric-training (PT) studies and determine specific factors that influence the training effects. Methods: A computerized search was performed, and 24 articles with a total of 46 effect sizes (ESs) in an experimental group and 25 ESs in a control group were reviewed to analyze the role of various factors on the impact of PT on COD performance. Results: The results showed that participants with good ftness levels obtained greater improvements in COD performance (P <.05), and basketball players gained more benefits of PT than other athletes. Also, men obtained COD results similar to those of women after PT. In relation to the variables of PT design, it appears that 7 wk (with 2 sessions/wk) using moderate intensity and 100 jumps per training session with a 72-h rest interval tends to improve COD ability. Performing PT with a combination of different types of plyometric exercises such as drop jumps + vertical jumps + standing long jumps is better than 1 form of exercise. Conclusion: It is apparent that PT can be effective at improving COD ability. The loading parameters are essential for exercise professionals, coaches, and strength and conditioning professionals with regard to the most appropriate dose-response trends to optimize plyometric-induced COD-ability gains. © 2016 Human Kinetics, Inc.
Comparing sustainability claims with assurance in organic agriculture standards
- Ascui, Francisco, Farmery, Anna, Gale, Fred
- Authors: Ascui, Francisco , Farmery, Anna , Gale, Fred
- Date: 2020
- Type: Text , Journal article
- Relation: Australasian Journal of Environmental Management Vol. 27, no. 1 (2020), p. 22-41
- Full Text:
- Reviewed:
- Description: Voluntary organic standard-setting organisations (SSOs) depend upon public trust in the truth claims implied by their labels: that the product in question has been produced using organic methods. They create and maintain this trust through assurance frameworks based on third-party verification of compliance with organic standards. It is therefore potentially problematic if an SSO makes additional claims that are not capable of being supported by their assurance frameworks. We investigate the claims made about the sustainability of organic agriculture by three voluntary organic SSOs, compared with assurance provisions within their standards. The analysis covers Australia, which has 53 per cent of the world's certified organic farmland; and is extended internationally by including the IFOAM standard, with which a further 49 organic standards are affiliated worldwide. We find that while these standards generally contain principles and requirements that support sustainability claims, they lack well-specified means of verification in most cases other than the ‘core’ claims to exclude synthetic chemical inputs and genetically modified organisms. This assurance gap creates the risk of a consumer backlash. We discuss two ways to mitigate this risk: by strengthening verification within standards; and/or by employing new agricultural information and communication technologies to support claims outside the certification process. © 2019, © 2019 Environment Institute of Australia and New Zealand Inc.
- Authors: Ascui, Francisco , Farmery, Anna , Gale, Fred
- Date: 2020
- Type: Text , Journal article
- Relation: Australasian Journal of Environmental Management Vol. 27, no. 1 (2020), p. 22-41
- Full Text:
- Reviewed:
- Description: Voluntary organic standard-setting organisations (SSOs) depend upon public trust in the truth claims implied by their labels: that the product in question has been produced using organic methods. They create and maintain this trust through assurance frameworks based on third-party verification of compliance with organic standards. It is therefore potentially problematic if an SSO makes additional claims that are not capable of being supported by their assurance frameworks. We investigate the claims made about the sustainability of organic agriculture by three voluntary organic SSOs, compared with assurance provisions within their standards. The analysis covers Australia, which has 53 per cent of the world's certified organic farmland; and is extended internationally by including the IFOAM standard, with which a further 49 organic standards are affiliated worldwide. We find that while these standards generally contain principles and requirements that support sustainability claims, they lack well-specified means of verification in most cases other than the ‘core’ claims to exclude synthetic chemical inputs and genetically modified organisms. This assurance gap creates the risk of a consumer backlash. We discuss two ways to mitigate this risk: by strengthening verification within standards; and/or by employing new agricultural information and communication technologies to support claims outside the certification process. © 2019, © 2019 Environment Institute of Australia and New Zealand Inc.
Implementing natural capital credit risk assessment in agricultural lending
- Ascui, Francisco, Cojoianu, Theodor
- Authors: Ascui, Francisco , Cojoianu, Theodor
- Date: 2019
- Type: Text , Journal article
- Relation: Business Strategy and the Environment Vol. 28, no. 6 (2019), p. 1234-1249
- Full Text:
- Reviewed:
- Description: Agriculture has critical impacts and dependencies on natural capital, and agricultural lenders are therefore exposed to natural capital credit risk through their loans to farmers. Currently, however, lenders lack any detailed guidance for assessing natural capital credit risk in agriculture and are challenged by the fact that the relevant material risks vary considerably by agricultural sector and geography. This paper develops a natural capital credit risk assessment framework based on a bottom-up review of the material risks associated with natural capital impacts and dependencies for Australian beef production. It demonstrates that implementing natural capital credit risk assessment is feasible in agricultural lending, using a combination of quantitative and qualitative inputs. Implementation challenges include the complexity and interconnectedness of natural capital processes, data availability and cost, spatial data analytical capacity, and the need for transformational change, both within lending organisations and across the banking sector. © 2019 John Wiley & Sons, Ltd and ERP Environment
- Authors: Ascui, Francisco , Cojoianu, Theodor
- Date: 2019
- Type: Text , Journal article
- Relation: Business Strategy and the Environment Vol. 28, no. 6 (2019), p. 1234-1249
- Full Text:
- Reviewed:
- Description: Agriculture has critical impacts and dependencies on natural capital, and agricultural lenders are therefore exposed to natural capital credit risk through their loans to farmers. Currently, however, lenders lack any detailed guidance for assessing natural capital credit risk in agriculture and are challenged by the fact that the relevant material risks vary considerably by agricultural sector and geography. This paper develops a natural capital credit risk assessment framework based on a bottom-up review of the material risks associated with natural capital impacts and dependencies for Australian beef production. It demonstrates that implementing natural capital credit risk assessment is feasible in agricultural lending, using a combination of quantitative and qualitative inputs. Implementation challenges include the complexity and interconnectedness of natural capital processes, data availability and cost, spatial data analytical capacity, and the need for transformational change, both within lending organisations and across the banking sector. © 2019 John Wiley & Sons, Ltd and ERP Environment
Is operationalising natural capital risk assessment practicable?
- Ascui, Francisco, Ball, Alex, Kahn, Lewis, Rowe, James
- Authors: Ascui, Francisco , Ball, Alex , Kahn, Lewis , Rowe, James
- Date: 2021
- Type: Text , Journal article
- Relation: Ecosystem Services Vol. 52, no. (2021), p.
- Full Text:
- Reviewed:
- Description: Financial institutions are indirectly exposed to risks associated with the impacts and dependencies on natural capital and ecosystem services of the companies that they invest in, lend to, and insure. This is particularly true for banks lending to agriculture: a sector with both significant impacts and critical dependencies on natural capital. Bank lending is a vital source of new finance for the sector, which is essential to achieve sustainable intensification targets. Yet current credit decision-making practice is still based on conventional financial and management indicators, lacking any systematic assessment of natural capital risks, especially those associated with dependencies. Operationalising natural capital risk assessment requires practicable indicators and data to evaluate the most material natural capital risks for a given sub-sector and geography, but it is unclear to what extent these are available. We assess the practicability of natural capital dependency risk indicators and data sources for a critical case study of Australian sheep production. We find that at least moderately practicable indicators and data sources are available to assess the 11 major dependency risks that are material for this industry. Challenges remain in determining risk thresholds for most indicators, and quantifying risk impacts on profitability. © 2021 Elsevier B.V.
- Authors: Ascui, Francisco , Ball, Alex , Kahn, Lewis , Rowe, James
- Date: 2021
- Type: Text , Journal article
- Relation: Ecosystem Services Vol. 52, no. (2021), p.
- Full Text:
- Reviewed:
- Description: Financial institutions are indirectly exposed to risks associated with the impacts and dependencies on natural capital and ecosystem services of the companies that they invest in, lend to, and insure. This is particularly true for banks lending to agriculture: a sector with both significant impacts and critical dependencies on natural capital. Bank lending is a vital source of new finance for the sector, which is essential to achieve sustainable intensification targets. Yet current credit decision-making practice is still based on conventional financial and management indicators, lacking any systematic assessment of natural capital risks, especially those associated with dependencies. Operationalising natural capital risk assessment requires practicable indicators and data to evaluate the most material natural capital risks for a given sub-sector and geography, but it is unclear to what extent these are available. We assess the practicability of natural capital dependency risk indicators and data sources for a critical case study of Australian sheep production. We find that at least moderately practicable indicators and data sources are available to assess the 11 major dependency risks that are material for this industry. Challenges remain in determining risk thresholds for most indicators, and quantifying risk impacts on profitability. © 2021 Elsevier B.V.
Salmon, sensors, and translation : the agency of Big Data in environmental governance
- Ascui, Francisco, Haward, Marcus, Lovell, Heather
- Authors: Ascui, Francisco , Haward, Marcus , Lovell, Heather
- Date: 2018
- Type: Text , Journal article , Article
- Relation: Environment and Planning D: Society and Space Vol. 36, no. 5 (2018), p. 905-925
- Full Text:
- Reviewed:
- Description: This paper explores the emerging role of Big Data in environmental governance. We focus on the case of salmon aquaculture management from 2011 to 2017 in Macquarie Harbour, Australia, and compare this with the foundational case that inspired the development of the concept of ‘translation’ in actor-network theory, that of scallop domestication in St Brieuc Bay, France, in the 1970s. A key difference is the salience of environmental data in the contemporary case. Recent dramatic events in the environmental governance of Macquarie Harbour have been driven by increasing spatial and temporal resolution of environmental monitoring, including real-time data collection from sensors mounted on the fish themselves. The resulting environmental data now takes centre stage in increasingly heated debates over how the harbour should be managed: overturning long-held assumptions about environmental interactions, inducing changes in regulatory practices and institutions, fracturing historical alliances and shaping the on-going legitimacy of the industry. Environmental Big Data is now a key actor within the networks that constitute and enact environmental governance. Given its new and unpredictable agency, control over access to data is likely to become critical in future power struggles over environmental resources and their governance. © The Author(s) 2018.
- Authors: Ascui, Francisco , Haward, Marcus , Lovell, Heather
- Date: 2018
- Type: Text , Journal article , Article
- Relation: Environment and Planning D: Society and Space Vol. 36, no. 5 (2018), p. 905-925
- Full Text:
- Reviewed:
- Description: This paper explores the emerging role of Big Data in environmental governance. We focus on the case of salmon aquaculture management from 2011 to 2017 in Macquarie Harbour, Australia, and compare this with the foundational case that inspired the development of the concept of ‘translation’ in actor-network theory, that of scallop domestication in St Brieuc Bay, France, in the 1970s. A key difference is the salience of environmental data in the contemporary case. Recent dramatic events in the environmental governance of Macquarie Harbour have been driven by increasing spatial and temporal resolution of environmental monitoring, including real-time data collection from sensors mounted on the fish themselves. The resulting environmental data now takes centre stage in increasingly heated debates over how the harbour should be managed: overturning long-held assumptions about environmental interactions, inducing changes in regulatory practices and institutions, fracturing historical alliances and shaping the on-going legitimacy of the industry. Environmental Big Data is now a key actor within the networks that constitute and enact environmental governance. Given its new and unpredictable agency, control over access to data is likely to become critical in future power struggles over environmental resources and their governance. © The Author(s) 2018.
Prevalence of and factors associated with anaemia in women of reproductive age in Bangladesh, Maldives and Nepal : evidence from nationally-representative survey data
- Ashfikur Rahman, Md, Sazedur Rahman, Md, Rahman, Muhammad Aziz, Szymlek-Gay, Ewa, Uddin, Riaz, Islam, Sheikh
- Authors: Ashfikur Rahman, Md , Sazedur Rahman, Md , Rahman, Muhammad Aziz , Szymlek-Gay, Ewa , Uddin, Riaz , Islam, Sheikh
- Date: 2021
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 16, no. 1 January (2021), p.
- Full Text:
- Reviewed:
- Description: Background Anaemia is a significant public health problem in most South-Asian countries, causing increased maternal and child mortality and morbidity. This study aimed to estimate the prevalence of and factors associated with anaemia in women of reproductive age in Bangladesh, Maldives, and Nepal. Methods We used the nationally-representative Demographic and Health Surveys Program data collected from women of reproductive age (15-49 years) in 2011 in Bangladesh (n = 5678), 2016 in Maldives (n = 6837), and 2016 in Nepal (n = 6419). Anaemia was categorized as mild (haemoglobin [Hb] of 10.0-10.9 g/dL for pregnant women and 11.0-11.9 g/dL for non-pregnant women), moderate (Hb of 7.0-9.9 g/dL for pregnant women and 8.0-10.9 g/dL for non-pregnant women), and severe (Hb <7.0 g/dL for pregnant women and <8.0 g/dL for non-pregnant women). Multinomial logistic regression analyses were used to identify factors associated with anaemia. Results The prevalence of anaemia was 41.8% in Bangladesh, 58.5% in Maldives, and 40.6% in Nepal. In Bangladesh, postpartum amenorrhoeic, non-educated, and pregnant women were more likely to have moderate/severe anaemia compared to women who were menopausal, had secondary education, and were not pregnant, respectively. In Maldives, residence in urban areas, underweight, having undergone female sterilization, current pregnancy, and menstruation in the last six weeks were associated with increased odds of moderate/severe anaemia. In Nepal, factors associated with increased odds of moderate/ severe anaemia were having undergone female sterilization and current pregnancy. Conclusion Anaemia remains a significant public health issue among 15-49-year-old women in Bangladesh, Maldives, and Nepal, which requires urgent attention. Effective policies and programmes for the control and prevention of anaemia should take into account the unique factors associated with anaemia identified in each country. In all three countries, strategies for the prevention and control of anaemia should particularly focus on women who are pregnant, underweight, or have undergone sterilization. © 2021 Rahman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Authors: Ashfikur Rahman, Md , Sazedur Rahman, Md , Rahman, Muhammad Aziz , Szymlek-Gay, Ewa , Uddin, Riaz , Islam, Sheikh
- Date: 2021
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 16, no. 1 January (2021), p.
- Full Text:
- Reviewed:
- Description: Background Anaemia is a significant public health problem in most South-Asian countries, causing increased maternal and child mortality and morbidity. This study aimed to estimate the prevalence of and factors associated with anaemia in women of reproductive age in Bangladesh, Maldives, and Nepal. Methods We used the nationally-representative Demographic and Health Surveys Program data collected from women of reproductive age (15-49 years) in 2011 in Bangladesh (n = 5678), 2016 in Maldives (n = 6837), and 2016 in Nepal (n = 6419). Anaemia was categorized as mild (haemoglobin [Hb] of 10.0-10.9 g/dL for pregnant women and 11.0-11.9 g/dL for non-pregnant women), moderate (Hb of 7.0-9.9 g/dL for pregnant women and 8.0-10.9 g/dL for non-pregnant women), and severe (Hb <7.0 g/dL for pregnant women and <8.0 g/dL for non-pregnant women). Multinomial logistic regression analyses were used to identify factors associated with anaemia. Results The prevalence of anaemia was 41.8% in Bangladesh, 58.5% in Maldives, and 40.6% in Nepal. In Bangladesh, postpartum amenorrhoeic, non-educated, and pregnant women were more likely to have moderate/severe anaemia compared to women who were menopausal, had secondary education, and were not pregnant, respectively. In Maldives, residence in urban areas, underweight, having undergone female sterilization, current pregnancy, and menstruation in the last six weeks were associated with increased odds of moderate/severe anaemia. In Nepal, factors associated with increased odds of moderate/ severe anaemia were having undergone female sterilization and current pregnancy. Conclusion Anaemia remains a significant public health issue among 15-49-year-old women in Bangladesh, Maldives, and Nepal, which requires urgent attention. Effective policies and programmes for the control and prevention of anaemia should take into account the unique factors associated with anaemia identified in each country. In all three countries, strategies for the prevention and control of anaemia should particularly focus on women who are pregnant, underweight, or have undergone sterilization. © 2021 Rahman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The role of sustainability control systems in translating CSR into performance in Iran
- Asiaei, Kaveh, Bontis, Nick, Barani, Omid, Moghaddam, Majid, Sidhu, Jasvinder
- Authors: Asiaei, Kaveh , Bontis, Nick , Barani, Omid , Moghaddam, Majid , Sidhu, Jasvinder
- Date: 2022
- Type: Text , Journal article
- Relation: Management Decision Vol. 60, no. 5 (2022), p. 1438-1468
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- Reviewed:
- Description: Purpose: This study aims to explore the extent to which companies rely on sustainability management control systems (SMCS) to translate corporate social responsibility (CSR) into superior performance building upon the premise of the natural resource orchestration perspective. Design/methodology/approach: Data were collected based on a survey data set from 118 Chief Financial Officers of publicly listed companies in Iran. The theoretical model was tested using partial least squares structural equation modeling (PLS-SEM, SmartPLS 3.0) as a method that enjoys minimum demands concerning normality assumptions and sample size. Findings: The findings support the full mediation effect of SMCS on the relationship between CSR and organizational performance. This implies that CSR affects performance only through the mediating role of SMCS. Practical implications: The central premise in the proposed theoretical framework is that the utilization of proper management control mechanisms (i.e. SMCS) can help the organization to better synchronize, measure and manage – i.e. “orchestrate” – the social, environmental and economic impacts, and this, in turn, leads to improved organizational performance. Originality/value: To the best of the authors’ knowledge, this is the first study of its kind, building on a unique synthesis of the agency cost perspective and resource orchestration theory, to introduce the “natural resource orchestration” approach for examining the intervening role of SMCS between CSR and organizational performance. © 2021, Emerald Publishing Limited.
- Authors: Asiaei, Kaveh , Bontis, Nick , Barani, Omid , Moghaddam, Majid , Sidhu, Jasvinder
- Date: 2022
- Type: Text , Journal article
- Relation: Management Decision Vol. 60, no. 5 (2022), p. 1438-1468
- Full Text:
- Reviewed:
- Description: Purpose: This study aims to explore the extent to which companies rely on sustainability management control systems (SMCS) to translate corporate social responsibility (CSR) into superior performance building upon the premise of the natural resource orchestration perspective. Design/methodology/approach: Data were collected based on a survey data set from 118 Chief Financial Officers of publicly listed companies in Iran. The theoretical model was tested using partial least squares structural equation modeling (PLS-SEM, SmartPLS 3.0) as a method that enjoys minimum demands concerning normality assumptions and sample size. Findings: The findings support the full mediation effect of SMCS on the relationship between CSR and organizational performance. This implies that CSR affects performance only through the mediating role of SMCS. Practical implications: The central premise in the proposed theoretical framework is that the utilization of proper management control mechanisms (i.e. SMCS) can help the organization to better synchronize, measure and manage – i.e. “orchestrate” – the social, environmental and economic impacts, and this, in turn, leads to improved organizational performance. Originality/value: To the best of the authors’ knowledge, this is the first study of its kind, building on a unique synthesis of the agency cost perspective and resource orchestration theory, to introduce the “natural resource orchestration” approach for examining the intervening role of SMCS between CSR and organizational performance. © 2021, Emerald Publishing Limited.
Corporate social responsibility and performance measurement systems in Iran : a levers of control perspective
- Asiaei, Kaveh, O'Connor, Neale, Moghaddam, Majid, Bontis, Nick, Sidhu, Jasvinder
- Authors: Asiaei, Kaveh , O'Connor, Neale , Moghaddam, Majid , Bontis, Nick , Sidhu, Jasvinder
- Date: 2023
- Type: Text , Journal article
- Relation: Corporate Social Responsibility and Environmental Management Vol. 30, no. 2 (2023), p. 574-588
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- Description: This study draws on Simons' levers of control model to explore how companies rely on the balanced use of diagnostic and interactive performance measurement systems (PMS) to translate corporate social responsibility (CSR) into superior performance. Data were collected based on a survey data set from 98 CFOs of public listed companies in Iran. The theoretical model was tested using partial least squares structural equation modeling (PLS-SEM, SmartPLS 3.0), which enjoys minimum demands concerning normality assumptions and sample size. The findings show that CSR is positively associated with PMS and organizational performance. Moreover, CSR is indirectly related to organizational performance through the mediating effect of PMS. This study extends the previous literature by simultaneously incorporating resource orchestration theory in the management accounting and CSR settings. The findings provide further insights into the issue of how adopting proper management control mechanisms (e.g., balanced use of PMS) can support organizations in orchestrating the social, environmental, and economic impacts more effectively. © 2022 The Authors. Corporate Social Responsibility and Environmental Management published by ERP Environment and John Wiley & Sons Ltd.
- Authors: Asiaei, Kaveh , O'Connor, Neale , Moghaddam, Majid , Bontis, Nick , Sidhu, Jasvinder
- Date: 2023
- Type: Text , Journal article
- Relation: Corporate Social Responsibility and Environmental Management Vol. 30, no. 2 (2023), p. 574-588
- Full Text:
- Reviewed:
- Description: This study draws on Simons' levers of control model to explore how companies rely on the balanced use of diagnostic and interactive performance measurement systems (PMS) to translate corporate social responsibility (CSR) into superior performance. Data were collected based on a survey data set from 98 CFOs of public listed companies in Iran. The theoretical model was tested using partial least squares structural equation modeling (PLS-SEM, SmartPLS 3.0), which enjoys minimum demands concerning normality assumptions and sample size. The findings show that CSR is positively associated with PMS and organizational performance. Moreover, CSR is indirectly related to organizational performance through the mediating effect of PMS. This study extends the previous literature by simultaneously incorporating resource orchestration theory in the management accounting and CSR settings. The findings provide further insights into the issue of how adopting proper management control mechanisms (e.g., balanced use of PMS) can support organizations in orchestrating the social, environmental, and economic impacts more effectively. © 2022 The Authors. Corporate Social Responsibility and Environmental Management published by ERP Environment and John Wiley & Sons Ltd.
Water quality management using hybrid machine learning and data mining algorithms : an indexing approach
- Aslam, Bilal, Maqsoom, Ahsen, Cheema, Ali, Ullah, Fahim, Alharbi, Abdullah, Imran, Muhammad
- Authors: Aslam, Bilal , Maqsoom, Ahsen , Cheema, Ali , Ullah, Fahim , Alharbi, Abdullah , Imran, Muhammad
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 119692-119705
- Full Text:
- Reviewed:
- Description: One of the key functions of global water resource management authorities is river water quality (WQ) assessment. A water quality index (WQI) is developed for water assessments considering numerous quality-related variables. WQI assessments typically take a long time and are prone to errors during sub-indices generation. This can be tackled through the latest machine learning (ML) techniques renowned for superior accuracy. In this study, water samples were taken from the wells in the study area (North Pakistan) to develop WQI prediction models. Four standalone algorithms, i.e., random trees (RT), random forest (RF), M5P, and reduced error pruning tree (REPT), were used in this study. In addition, 12 hybrid data-mining algorithms (a combination of standalone, bagging (BA), cross-validation parameter selection (CVPS), and randomizable filtered classification (RFC)) were also used. Using the 10-fold cross-validation technique, the data were separated into two groups (70:30) for algorithm creation. Ten random input permutations were created using Pearson correlation coefficients to identify the best possible combination of datasets for improving the algorithm prediction. The variables with very low correlations performed poorly, whereas hybrid algorithms increased the prediction capability of numerous standalone algorithms. Hybrid RT-Artificial Neural Network (RT-ANN) with RMSE = 2.319, MAE = 2.248, NSE = 0.945, and PBIAS = -0.64 outperformed all other algorithms. Most algorithms overestimated WQI values except for BA-RF, RF, BA-REPT, REPT, RFC-M5P, RFC-REPT, and ANN- Adaptive Network-Based Fuzzy Inference System (ANFIS). © 2013 IEEE.
- Authors: Aslam, Bilal , Maqsoom, Ahsen , Cheema, Ali , Ullah, Fahim , Alharbi, Abdullah , Imran, Muhammad
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 119692-119705
- Full Text:
- Reviewed:
- Description: One of the key functions of global water resource management authorities is river water quality (WQ) assessment. A water quality index (WQI) is developed for water assessments considering numerous quality-related variables. WQI assessments typically take a long time and are prone to errors during sub-indices generation. This can be tackled through the latest machine learning (ML) techniques renowned for superior accuracy. In this study, water samples were taken from the wells in the study area (North Pakistan) to develop WQI prediction models. Four standalone algorithms, i.e., random trees (RT), random forest (RF), M5P, and reduced error pruning tree (REPT), were used in this study. In addition, 12 hybrid data-mining algorithms (a combination of standalone, bagging (BA), cross-validation parameter selection (CVPS), and randomizable filtered classification (RFC)) were also used. Using the 10-fold cross-validation technique, the data were separated into two groups (70:30) for algorithm creation. Ten random input permutations were created using Pearson correlation coefficients to identify the best possible combination of datasets for improving the algorithm prediction. The variables with very low correlations performed poorly, whereas hybrid algorithms increased the prediction capability of numerous standalone algorithms. Hybrid RT-Artificial Neural Network (RT-ANN) with RMSE = 2.319, MAE = 2.248, NSE = 0.945, and PBIAS = -0.64 outperformed all other algorithms. Most algorithms overestimated WQI values except for BA-RF, RF, BA-REPT, REPT, RFC-M5P, RFC-REPT, and ANN- Adaptive Network-Based Fuzzy Inference System (ANFIS). © 2013 IEEE.
A complex act - teacher educators share their perspectives of practicum assessment
- Aspden, Karyn, McLachlan, Claire
- Authors: Aspden, Karyn , McLachlan, Claire
- Date: 2017
- Type: Text , Journal article
- Relation: Waikato journal of education Vol. 22, no. 3 (2017), p. 21-32
- Full Text:
- Reviewed:
- Description: Reports the findings of a doctoral study that examined the assessment of practicum in early childhood initial teacher education and, in particular, the way in which practicum assessment was enacted and experienced by early childhood student teachers, associate teachers, and teacher educators within institutional contexts. Provides insights into how teacher educators define their role, what they look for and hope for in the assessment process, as well as the challenges faced in making authentic, appropriate and informed assessment decisions. Source: National Library of New Zealand Te Puna Matauranga o Aotearoa, licensed by the Department of Internal Affairs for re-use under the Creative Commons Attribution 3.0 New Zealand Licence.
- Authors: Aspden, Karyn , McLachlan, Claire
- Date: 2017
- Type: Text , Journal article
- Relation: Waikato journal of education Vol. 22, no. 3 (2017), p. 21-32
- Full Text:
- Reviewed:
- Description: Reports the findings of a doctoral study that examined the assessment of practicum in early childhood initial teacher education and, in particular, the way in which practicum assessment was enacted and experienced by early childhood student teachers, associate teachers, and teacher educators within institutional contexts. Provides insights into how teacher educators define their role, what they look for and hope for in the assessment process, as well as the challenges faced in making authentic, appropriate and informed assessment decisions. Source: National Library of New Zealand Te Puna Matauranga o Aotearoa, licensed by the Department of Internal Affairs for re-use under the Creative Commons Attribution 3.0 New Zealand Licence.
A preliminary profiling of internet money mules : An Australian perspective
- Aston, Manny, McCombie, Stephen, Reardon, Ben, Watters, Paul
- Authors: Aston, Manny , McCombie, Stephen , Reardon, Ben , Watters, Paul
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at 2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC '09, Brisbane, Queensland : 7th-9th July 2009 p. 482-487
- Full Text:
- Description: Along with the massive growth in Internet commerce over the last ten years there has been a corresponding boom in Internet related crime, or cybercrime. According to research recently released by the Australian Bureau of Statistics in 2006 57,000 Australians aged 15 years and over fell victim to phishing and related Internet scams. Of all the victims of cybercrime, only one group is potentially subject to criminal prosecution: `Internet money mules'-those who, either knowingly or unknowingly, launder money. This paper examines the demographic profile-specifically age, gender and postcode-related to 660 confirmed money mule incidents recorded during the calendar year 2007, for a major Australian financial institution. This data is compared to ABS statistics of Internet usage in 2006. There is clear evidence of a strong gender bias towards males, particularly in the older age group. This is directly relevant when considering education and training programs for both corporations and the community on the issues surrounding Internet money mule scams and in ultimately understanding the problem of Internet banking fraud.
- Description: 2003007858
- Authors: Aston, Manny , McCombie, Stephen , Reardon, Ben , Watters, Paul
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at 2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC '09, Brisbane, Queensland : 7th-9th July 2009 p. 482-487
- Full Text:
- Description: Along with the massive growth in Internet commerce over the last ten years there has been a corresponding boom in Internet related crime, or cybercrime. According to research recently released by the Australian Bureau of Statistics in 2006 57,000 Australians aged 15 years and over fell victim to phishing and related Internet scams. Of all the victims of cybercrime, only one group is potentially subject to criminal prosecution: `Internet money mules'-those who, either knowingly or unknowingly, launder money. This paper examines the demographic profile-specifically age, gender and postcode-related to 660 confirmed money mule incidents recorded during the calendar year 2007, for a major Australian financial institution. This data is compared to ABS statistics of Internet usage in 2006. There is clear evidence of a strong gender bias towards males, particularly in the older age group. This is directly relevant when considering education and training programs for both corporations and the community on the issues surrounding Internet money mule scams and in ultimately understanding the problem of Internet banking fraud.
- Description: 2003007858
Algae-based models to configure consumptive flows for ecological benefit in the highly regulated MacKenzie River, south-east Australia
- Authors: Atazadeh, Ehsan
- Date: 2017
- Type: Text , Thesis , PhD
- Full Text:
- Description: Many river ecosystems, especially those in arid and semi-arid, are experiencing severe stress due to the increasing demands on the ecosystem services they provide, coupled with anthropogenic catchment impacts and factors associated with climate change and weather extremes. The flow regime of the Mackenzie River was substantially modified since the construction of a water supply reservoir on its upper reach in 1887. Water is now regulated at several locations downstream of the reservoir, creating a substantially modified flow regime, impacting key environmental values of the river. The river receives an environmental flow allocation and the river channel is used to transfer water dedicated for consumptive use. Water Quality and algal monitoring formed the basis of models that were developed evaluate the ecological condition of this working river under base flow and before, during and after freshes that deliver water to users. Samples of diatoms, soft algae and measurements of water quality were analysed at ten sampling sites for three years (between February 2012 and November 2014) along the MacKenzie River in different seasons and under different flow regimes to understand the spatial and temporal variation in the relationship between algal communities and water quality, and so stream condition. Baseline information on algal communities and water quality was collected during base flow conditions, while experiments on the effect of water releases on algal communities were based on flow regime variations (manipulated flow regimes), specifically on the algae community structure, water quality and ecosystem function. These comprised cease to flow (0 ML/day), low flows (10-15 ML/day), freshes (35-40 ML/day) and high flow (55ML/day) conditions. Physical and chemical characteristics of water, including pH, temperature, turbidity, electrical conductivity, dissolved oxygen, total nitrogen, phosphorus and cations and anions were measured. Biological properties of the algal periphyton communities, including dry mass, ash-free dry mass, chlorophyll-a concentration and species composition, were also measured. Furthermore, the DSIAR (Diatom Species Index for Australian Rivers) score was calculated to classify the condition of the waterway. The results showed the algal species composition changed under different flow regimes along the river. The sensitivity of diatoms to changes in water quality and flow rates deemed them useful indicators of river condition. The results indicated that flows tended to improve DSIAR scores and diatoms versus green algae and cyanobacteria biomass measures in the mid and lower reaches. The biological properties of the algal periphyton communities, and the species composition, varied between sites under different flow regimes. The accumulation of dry mass (not ash-free) decreased downstream during freshes, however the accumulation of AFDM (ash-free dry mass) gradually increased downstream. The results showed that the concentration of chlorophyll-a decreased downstream under water release events. The Pearson’s correlation matrix revealed flow regimes had a significant influence on the water chemistry characteristics and biological properties. The principal component analysis (PCA) illustrated that upstream species of algae were associated with low pH and temperature and higher DO. In contrast downstream species were associated with higher turbidity, TSS, conductivity, TN, and TDS. The correspondence analysis (CA) and detrended correspondence analysis (DCA) showed a split between algal assemblages during water release events in comparison with before and after water release. The canonical correspondence analysis (CCA) identified five significant environmental variables including pH, TSS, Turbidity, TN and TP explaining algal assemblage and structure along the river. The collected data were used to develop ecological response models based on algae communities living under different flow regimes in the MacKenzie River. The algae-based models across a hydraulic gradient may be useful in water management efforts to find sustainable solutions in the river by balancing environmental and human values. The empirical data and models showed the lower reaches of the river to be in poor condition under low flows, but this condition improved under flows of 35 ML/day, as indicated by the reduction in green algae and cyanobacteria and improvement in DSIAR scores. The results are presented to tailor discharge and duration of the river flows by amalgamation of consumptive and environmental flows to improve the condition of the stream thereby supplementing the flows dedicated to environmental outcomes. Ultimately the findings can be used by management to configure consumptive flows to enhance the for ecological condition of the MacKenzie River.
- Description: Doctor of Philosophy
- Authors: Atazadeh, Ehsan
- Date: 2017
- Type: Text , Thesis , PhD
- Full Text:
- Description: Many river ecosystems, especially those in arid and semi-arid, are experiencing severe stress due to the increasing demands on the ecosystem services they provide, coupled with anthropogenic catchment impacts and factors associated with climate change and weather extremes. The flow regime of the Mackenzie River was substantially modified since the construction of a water supply reservoir on its upper reach in 1887. Water is now regulated at several locations downstream of the reservoir, creating a substantially modified flow regime, impacting key environmental values of the river. The river receives an environmental flow allocation and the river channel is used to transfer water dedicated for consumptive use. Water Quality and algal monitoring formed the basis of models that were developed evaluate the ecological condition of this working river under base flow and before, during and after freshes that deliver water to users. Samples of diatoms, soft algae and measurements of water quality were analysed at ten sampling sites for three years (between February 2012 and November 2014) along the MacKenzie River in different seasons and under different flow regimes to understand the spatial and temporal variation in the relationship between algal communities and water quality, and so stream condition. Baseline information on algal communities and water quality was collected during base flow conditions, while experiments on the effect of water releases on algal communities were based on flow regime variations (manipulated flow regimes), specifically on the algae community structure, water quality and ecosystem function. These comprised cease to flow (0 ML/day), low flows (10-15 ML/day), freshes (35-40 ML/day) and high flow (55ML/day) conditions. Physical and chemical characteristics of water, including pH, temperature, turbidity, electrical conductivity, dissolved oxygen, total nitrogen, phosphorus and cations and anions were measured. Biological properties of the algal periphyton communities, including dry mass, ash-free dry mass, chlorophyll-a concentration and species composition, were also measured. Furthermore, the DSIAR (Diatom Species Index for Australian Rivers) score was calculated to classify the condition of the waterway. The results showed the algal species composition changed under different flow regimes along the river. The sensitivity of diatoms to changes in water quality and flow rates deemed them useful indicators of river condition. The results indicated that flows tended to improve DSIAR scores and diatoms versus green algae and cyanobacteria biomass measures in the mid and lower reaches. The biological properties of the algal periphyton communities, and the species composition, varied between sites under different flow regimes. The accumulation of dry mass (not ash-free) decreased downstream during freshes, however the accumulation of AFDM (ash-free dry mass) gradually increased downstream. The results showed that the concentration of chlorophyll-a decreased downstream under water release events. The Pearson’s correlation matrix revealed flow regimes had a significant influence on the water chemistry characteristics and biological properties. The principal component analysis (PCA) illustrated that upstream species of algae were associated with low pH and temperature and higher DO. In contrast downstream species were associated with higher turbidity, TSS, conductivity, TN, and TDS. The correspondence analysis (CA) and detrended correspondence analysis (DCA) showed a split between algal assemblages during water release events in comparison with before and after water release. The canonical correspondence analysis (CCA) identified five significant environmental variables including pH, TSS, Turbidity, TN and TP explaining algal assemblage and structure along the river. The collected data were used to develop ecological response models based on algae communities living under different flow regimes in the MacKenzie River. The algae-based models across a hydraulic gradient may be useful in water management efforts to find sustainable solutions in the river by balancing environmental and human values. The empirical data and models showed the lower reaches of the river to be in poor condition under low flows, but this condition improved under flows of 35 ML/day, as indicated by the reduction in green algae and cyanobacteria and improvement in DSIAR scores. The results are presented to tailor discharge and duration of the river flows by amalgamation of consumptive and environmental flows to improve the condition of the stream thereby supplementing the flows dedicated to environmental outcomes. Ultimately the findings can be used by management to configure consumptive flows to enhance the for ecological condition of the MacKenzie River.
- Description: Doctor of Philosophy
Importance of environmental flows in the Wimmera catchment, Southeast Australia
- Atazadeh, Ehsan, Barton, Andrew, Razeghi, Jafar
- Authors: Atazadeh, Ehsan , Barton, Andrew , Razeghi, Jafar
- Date: 2021
- Type: Text , Journal article
- Relation: Limnological Review Vol. 20, no. 4 (2021), p. 185-198
- Full Text:
- Reviewed:
- Description: In this paper the environment, climate, vegetation, indigenous and European settlement history, stream flow patterns, water quality and water resources development in western Victoria, Australia are studied. The last part of the paper focuses on the MacKenzie River, a tributary of the Wimmera River located on the northern slopes of the Grampians Ranges in western Victoria, Australia. Water release along the MacKenzie River was regulated to improve water quality, stream condition and river health especially in the downstream reaches. The upstream section tends to receive water most days of the year due to releases to secure the requirements of water supply for the city of Horsham and its recreational and conservation values, which is diverted into Mt Zero Channel. Below this the middle and downstream sections receive a more intermittent supply. Annually, a total of 10,000 dam3 of water is released from Wartook Reservoir into the MacKenzie River. Of this volume, only about 4,000 dam3 was released explicitly for environmental purposes. The remaining 6,000 dam3 was released to meet consumptive demands and to transfer water to downstream reservoirs. The empirical data and models showed the lower reaches of the river to be in poor condition under low flows, but this condition improved under flows of 35 dam3 per day, as indicated. The results are presented to tailor discharge and duration of the river flows by amalgamation of consumptive and environmental flows to improve the condition of the stream, thereby supplementing the flows dedicated to environmental outcomes. Ultimately the findings can be used by management to configure consumptive flows that would enhance the ecological condition of the MacKenzie River. © 2020 Ehsan Atazadeh et al., published by Sciendo 2020.
- Authors: Atazadeh, Ehsan , Barton, Andrew , Razeghi, Jafar
- Date: 2021
- Type: Text , Journal article
- Relation: Limnological Review Vol. 20, no. 4 (2021), p. 185-198
- Full Text:
- Reviewed:
- Description: In this paper the environment, climate, vegetation, indigenous and European settlement history, stream flow patterns, water quality and water resources development in western Victoria, Australia are studied. The last part of the paper focuses on the MacKenzie River, a tributary of the Wimmera River located on the northern slopes of the Grampians Ranges in western Victoria, Australia. Water release along the MacKenzie River was regulated to improve water quality, stream condition and river health especially in the downstream reaches. The upstream section tends to receive water most days of the year due to releases to secure the requirements of water supply for the city of Horsham and its recreational and conservation values, which is diverted into Mt Zero Channel. Below this the middle and downstream sections receive a more intermittent supply. Annually, a total of 10,000 dam3 of water is released from Wartook Reservoir into the MacKenzie River. Of this volume, only about 4,000 dam3 was released explicitly for environmental purposes. The remaining 6,000 dam3 was released to meet consumptive demands and to transfer water to downstream reservoirs. The empirical data and models showed the lower reaches of the river to be in poor condition under low flows, but this condition improved under flows of 35 dam3 per day, as indicated. The results are presented to tailor discharge and duration of the river flows by amalgamation of consumptive and environmental flows to improve the condition of the stream, thereby supplementing the flows dedicated to environmental outcomes. Ultimately the findings can be used by management to configure consumptive flows that would enhance the ecological condition of the MacKenzie River. © 2020 Ehsan Atazadeh et al., published by Sciendo 2020.
Our corporate who art in heaven
- Atkins, Rosalind, De Medici, eX
- Authors: Atkins, Rosalind , De Medici, eX
- Date: 2012
- Type: Text , Visual art work
- Full Text: false
- Authors: Atkins, Rosalind , De Medici, eX
- Date: 2012
- Type: Text , Visual art work
- Full Text: false