Efficient data gathering in 3D linear underwater wireless sensor networks using sink mobility
- Akbar, Mariam, Javaid, Nadeem, Khan, Ayesha, Imran, Muhammad, Shoaib, Muhammad, Vasilakos, Athanasios
- Authors: Akbar, Mariam , Javaid, Nadeem , Khan, Ayesha , Imran, Muhammad , Shoaib, Muhammad , Vasilakos, Athanasios
- Date: 2016
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 16, no. 3 (2016), p.
- Full Text:
- Reviewed:
- Description: Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. © 2016 by the authors; licensee MDPI, Basel, Switzerland.
- Authors: Akbar, Mariam , Javaid, Nadeem , Khan, Ayesha , Imran, Muhammad , Shoaib, Muhammad , Vasilakos, Athanasios
- Date: 2016
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 16, no. 3 (2016), p.
- Full Text:
- Reviewed:
- Description: Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. © 2016 by the authors; licensee MDPI, Basel, Switzerland.
A fault-tolerant cascaded switched-capacitor multilevel inverter for domestic applications in smart grids
- Akbari, Ehsan, Teimouri, Ali, Saki, Mojtaba, Rezaei, Mohammad, Hu, Jiefeng, Band, Shahab, Pai, Hao-Ting, Mosavi, Amir
- Authors: Akbari, Ehsan , Teimouri, Ali , Saki, Mojtaba , Rezaei, Mohammad , Hu, Jiefeng , Band, Shahab , Pai, Hao-Ting , Mosavi, Amir
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 110590-110602
- Full Text:
- Reviewed:
- Description: Cascaded multilevel inverters (MLIs) generate an output voltage using series-connected power modules that employ standard configurations of low-voltage components. Each module may employ one or more switched capacitors to double or quadruple its input voltage. The higher number of switched capacitors and semiconductor switches in MLIs compared to conventional two-level inverters has led to concerns about overall system reliability. A fault-tolerant design can mitigate this reliability issue. If one part of the system fails, the MLI can continue its planned operation at a reduced level rather than the entire system failing, which makes the fault tolerance of the MLI particularly important. In this paper, a novel fault location technique is presented that leads to a significant reduction in fault location detection time based on the reliability priority of the components of the proposed fault-tolerant switched capacitor cascaded MLI (CSCMLI). The main contribution of this paper is to reduce the number of MLI switches under fault conditions while operating at lower levels. The fault-tolerant inverter requires fewer switches at higher reliability, and the comparison with similar MLIs shows a faster dynamic response of fault detection and reduced fault location detection time. The experimental results confirm the effectiveness of the presented methods applied in the CSCMLI. Also, all experimental data including processor code, schematic, PCB, and video of CSCMLI operation are attached. © 2013 IEEE.
- Authors: Akbari, Ehsan , Teimouri, Ali , Saki, Mojtaba , Rezaei, Mohammad , Hu, Jiefeng , Band, Shahab , Pai, Hao-Ting , Mosavi, Amir
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 110590-110602
- Full Text:
- Reviewed:
- Description: Cascaded multilevel inverters (MLIs) generate an output voltage using series-connected power modules that employ standard configurations of low-voltage components. Each module may employ one or more switched capacitors to double or quadruple its input voltage. The higher number of switched capacitors and semiconductor switches in MLIs compared to conventional two-level inverters has led to concerns about overall system reliability. A fault-tolerant design can mitigate this reliability issue. If one part of the system fails, the MLI can continue its planned operation at a reduced level rather than the entire system failing, which makes the fault tolerance of the MLI particularly important. In this paper, a novel fault location technique is presented that leads to a significant reduction in fault location detection time based on the reliability priority of the components of the proposed fault-tolerant switched capacitor cascaded MLI (CSCMLI). The main contribution of this paper is to reduce the number of MLI switches under fault conditions while operating at lower levels. The fault-tolerant inverter requires fewer switches at higher reliability, and the comparison with similar MLIs shows a faster dynamic response of fault detection and reduced fault location detection time. The experimental results confirm the effectiveness of the presented methods applied in the CSCMLI. Also, all experimental data including processor code, schematic, PCB, and video of CSCMLI operation are attached. © 2013 IEEE.
Frequency security constrained energy management in an isolated power system
- Akram, Umer, Nadarajah, Mithulanathan, Shah, Rakibuzzaman, Shafiq, Saifullah
- Authors: Akram, Umer , Nadarajah, Mithulanathan , Shah, Rakibuzzaman , Shafiq, Saifullah
- Date: 2020
- Type: Text , Journal article
- Relation: WSEAS Transactions on Power Systems Vol. 15, no. (2020), p. 222-229
- Full Text:
- Reviewed:
- Description: Short-term frequency instability is one of the major challenges that arise due to large-scale penetration of converter interfaced renewable energy sources (RESs) in isolated power systems. The short-term frequency instability is associated with high values of rate of change of frequency (RoCoF) and larger frequency excursions. In this paper, a frequency constrained energy management algorithm is proposed. The proposed algorithm manages the power output of RESs, energy storage system, and electric vehicles (EVs) in such a way that the system keeps nonsynchronous power reserve for providing virtual inertia support to avoid high values of RoCoF and frequency excursions. The non-synchronous power reserve is readily available and when deployed can limit the RoCoF as per the required standard. The proposed management algorithm selects the non-synchronous power reserve from different resources, i.e., RES (solar PV, wind turbine), energy storage, and EV, depending on the availability and system loading conditions. Simulation results show the effectiveness of the proposed algorithm. © 2020 World Scientific and Engineering Academy and Society. All rights reserved.
- Authors: Akram, Umer , Nadarajah, Mithulanathan , Shah, Rakibuzzaman , Shafiq, Saifullah
- Date: 2020
- Type: Text , Journal article
- Relation: WSEAS Transactions on Power Systems Vol. 15, no. (2020), p. 222-229
- Full Text:
- Reviewed:
- Description: Short-term frequency instability is one of the major challenges that arise due to large-scale penetration of converter interfaced renewable energy sources (RESs) in isolated power systems. The short-term frequency instability is associated with high values of rate of change of frequency (RoCoF) and larger frequency excursions. In this paper, a frequency constrained energy management algorithm is proposed. The proposed algorithm manages the power output of RESs, energy storage system, and electric vehicles (EVs) in such a way that the system keeps nonsynchronous power reserve for providing virtual inertia support to avoid high values of RoCoF and frequency excursions. The non-synchronous power reserve is readily available and when deployed can limit the RoCoF as per the required standard. The proposed management algorithm selects the non-synchronous power reserve from different resources, i.e., RES (solar PV, wind turbine), energy storage, and EV, depending on the availability and system loading conditions. Simulation results show the effectiveness of the proposed algorithm. © 2020 World Scientific and Engineering Academy and Society. All rights reserved.
Sizing HESS as inertial and primary frequency reserve in low inertia power system
- Akram, Umer, Mithulananthan, N., Shah, Rakibuzzaman, Pourmousavi, S. Ali
- Authors: Akram, Umer , Mithulananthan, N. , Shah, Rakibuzzaman , Pourmousavi, S. Ali
- Date: 2021
- Type: Text , Journal article
- Relation: IET renewable power generation Vol. 15, no. 1 (2021), p. 99-113
- Full Text:
- Reviewed:
- Description: Energy storage systems are recognised as the potential solution to alleviate the impacts of reduced inertia and intermittency in power systems due to the integration of renewable energy sources. Several energy storage technologies are available in the market with diverse power and energy characteristics, operational limitations, and costs. Besides, frequency regulations in power systems have different requirements, for example, inertial response requires high power for a short period while primary frequency regulation requires steady power for a longer time. Thus, it is crucial to find out the optimum sizes and types of storage technologies for these services. In this paper, a methodology for sizing fast responsive energy storage technologies for inertial response, primary frequency regulation, and both inertial response and primary frequency regulation is developed. The sizing of storage systems for inertial response, primary frequency regulation, and both inertial response and primary frequency regulation is done separately. The sizing of storage for inertial response is done in two steps. A region reduction iterative algorithm is proposed to estimate the storage size for inertial response. The sizing of the storage system for primary frequency regulation is done analytically. The sizing methodology incorporates the frequency dynamics of storage, converters, and other associated controls that affect the frequency response. Moreover, an economic analysis is carried out to find the optimum combination of storage technologies for inertial response, primary frequency regulation, and both inertial response and primary frequency regulation services. The accuracy of the proposed sizing method has been compared with the metaheuristic algorithm based technique. The effectiveness of the proposed method is also compared with those in the literature. Simulation results show that the proposed method outperforms the existing methods in the literature. Finally, the non‐linear simulations revealed the validity of the optimal solutions.
- Authors: Akram, Umer , Mithulananthan, N. , Shah, Rakibuzzaman , Pourmousavi, S. Ali
- Date: 2021
- Type: Text , Journal article
- Relation: IET renewable power generation Vol. 15, no. 1 (2021), p. 99-113
- Full Text:
- Reviewed:
- Description: Energy storage systems are recognised as the potential solution to alleviate the impacts of reduced inertia and intermittency in power systems due to the integration of renewable energy sources. Several energy storage technologies are available in the market with diverse power and energy characteristics, operational limitations, and costs. Besides, frequency regulations in power systems have different requirements, for example, inertial response requires high power for a short period while primary frequency regulation requires steady power for a longer time. Thus, it is crucial to find out the optimum sizes and types of storage technologies for these services. In this paper, a methodology for sizing fast responsive energy storage technologies for inertial response, primary frequency regulation, and both inertial response and primary frequency regulation is developed. The sizing of storage systems for inertial response, primary frequency regulation, and both inertial response and primary frequency regulation is done separately. The sizing of storage for inertial response is done in two steps. A region reduction iterative algorithm is proposed to estimate the storage size for inertial response. The sizing of the storage system for primary frequency regulation is done analytically. The sizing methodology incorporates the frequency dynamics of storage, converters, and other associated controls that affect the frequency response. Moreover, an economic analysis is carried out to find the optimum combination of storage technologies for inertial response, primary frequency regulation, and both inertial response and primary frequency regulation services. The accuracy of the proposed sizing method has been compared with the metaheuristic algorithm based technique. The effectiveness of the proposed method is also compared with those in the literature. Simulation results show that the proposed method outperforms the existing methods in the literature. Finally, the non‐linear simulations revealed the validity of the optimal solutions.
Adapting structuration theory as a comprehensive theory for distance education : The ASTIDE model
- Aktaruzzaman, Md, Plunkett, Margaret
- Authors: Aktaruzzaman, Md , Plunkett, Margaret
- Date: 2016
- Type: Text , Journal article
- Relation: European Journal of Open, Distance and E-Learning Vol. 19, no. 1 (2016), p. 19
- Full Text:
- Reviewed:
- Description: Distance Education (DE) theorists have argued about the requirement for a theory to be comprehensive in a way that can explicate many of the activities associated with DE. Currently, Transactional Distance Theory (TDT) (Moore, 1993) and the Theory of Instructional Dialogue (IDT) (Caspi & Gorsky, 2006) are the most prominent theories, yet they still do not represent a unified and comprehensive theory for DE. This paper provides a review of the existing literature on DE theories and identifies potential gaps in theorising distance education. Building on Giddens’ (1984) work, an innovative approach to theorising DE is proposed through the conceptualisation of the Adapting Structuration Theory In Distance Education (ASTIDE) model as a means to explicate DE operations and practices at the institutional and national/international level. It also presents evidence, from a larger study, of the necessity of a comprehensive model such as the ASTIDE constructed through an investigation into the DE systems of developing and developed countries.
- Authors: Aktaruzzaman, Md , Plunkett, Margaret
- Date: 2016
- Type: Text , Journal article
- Relation: European Journal of Open, Distance and E-Learning Vol. 19, no. 1 (2016), p. 19
- Full Text:
- Reviewed:
- Description: Distance Education (DE) theorists have argued about the requirement for a theory to be comprehensive in a way that can explicate many of the activities associated with DE. Currently, Transactional Distance Theory (TDT) (Moore, 1993) and the Theory of Instructional Dialogue (IDT) (Caspi & Gorsky, 2006) are the most prominent theories, yet they still do not represent a unified and comprehensive theory for DE. This paper provides a review of the existing literature on DE theories and identifies potential gaps in theorising distance education. Building on Giddens’ (1984) work, an innovative approach to theorising DE is proposed through the conceptualisation of the Adapting Structuration Theory In Distance Education (ASTIDE) model as a means to explicate DE operations and practices at the institutional and national/international level. It also presents evidence, from a larger study, of the necessity of a comprehensive model such as the ASTIDE constructed through an investigation into the DE systems of developing and developed countries.
Spatial modelling of bacterial diversity over the selected regions in Bangladesh by next-generation sequencing : role of water temperature
- Akter, Nabila, Wahiduzzaman, Md, Yeasmin, Alea, Islam, Kazi, Luo, Jing-Jia
- Authors: Akter, Nabila , Wahiduzzaman, Md , Yeasmin, Alea , Islam, Kazi , Luo, Jing-Jia
- Date: 2020
- Type: Text , Journal article
- Relation: Applied Sciences (Switzerland) Vol. 10, no. 7 (2020), p.
- Full Text:
- Reviewed:
- Description: In this study, a spatial model has been developed to investigate the role of water temperature to the distribution of bacteria over the selected regions in the Bay of Bengal, located in the southern region of Bangladesh using next-generation sequencing. Bacterial concentration, quantitative polymerase chain reactions, and sequencing were performed on water samples and identified Acidobacteria, Actinobacteria, Bacteroidetes, Chlorobi, Chloroflexi, Cyanobacteria, Firmicutes, Nitrospirae, Planctomycetes, Proteobacteria, and Verrucomicrobia. The spatial model tessellated the parts of the Bay of Bengal with hexagons and analyzed the relationship between the distribution of bacteria and water temperature. A geographically weighted regression was used to observe whether water temperature contributed strongly or weakly to the distribution of bacteria. The residuals were examined to assess the model's fitness. The spatial model has the potential to predict the bacterial diversity in the selected regions of Bangladesh. © 2020 by the authors.
- Authors: Akter, Nabila , Wahiduzzaman, Md , Yeasmin, Alea , Islam, Kazi , Luo, Jing-Jia
- Date: 2020
- Type: Text , Journal article
- Relation: Applied Sciences (Switzerland) Vol. 10, no. 7 (2020), p.
- Full Text:
- Reviewed:
- Description: In this study, a spatial model has been developed to investigate the role of water temperature to the distribution of bacteria over the selected regions in the Bay of Bengal, located in the southern region of Bangladesh using next-generation sequencing. Bacterial concentration, quantitative polymerase chain reactions, and sequencing were performed on water samples and identified Acidobacteria, Actinobacteria, Bacteroidetes, Chlorobi, Chloroflexi, Cyanobacteria, Firmicutes, Nitrospirae, Planctomycetes, Proteobacteria, and Verrucomicrobia. The spatial model tessellated the parts of the Bay of Bengal with hexagons and analyzed the relationship between the distribution of bacteria and water temperature. A geographically weighted regression was used to observe whether water temperature contributed strongly or weakly to the distribution of bacteria. The residuals were examined to assess the model's fitness. The spatial model has the potential to predict the bacterial diversity in the selected regions of Bangladesh. © 2020 by the authors.
How talent capability can shape service analytics capability in the big data environment?
- Akter, Shahriar, Wamba, Samuel, Barrett, Mary, Biswas, Kumar
- Authors: Akter, Shahriar , Wamba, Samuel , Barrett, Mary , Biswas, Kumar
- Date: 2019
- Type: Text , Journal article
- Relation: Journal of Strategic Marketing Vol. 27, no. 6 (2019), p. 521-539
- Full Text:
- Reviewed:
- Description: We know very little about how big data-driven service analytics capabilities (SAC) are built in data-driven service organizations and the potential role of talent capability in facilitating overall SAC and the impact of both on firm performance (FPER). Drawing on the dynamic capabilities (DC) approach, this study investigates the link between SAC and FPER examining the mediating role of talent capability and the moderating influence of a firm’s strategic alignment. On the basis of two Delphi studies and survey data from 267 service analysts in the US and France, the findings show that even though SAC are built on technology, talent and information capabilities, their overall impact on firm performance is mediated by the level of talent capability of service analytics managers. The findings also confirm the critical moderating impact of strategic alignment between dynamic talent capability and firm performance in the big data environment.
- Authors: Akter, Shahriar , Wamba, Samuel , Barrett, Mary , Biswas, Kumar
- Date: 2019
- Type: Text , Journal article
- Relation: Journal of Strategic Marketing Vol. 27, no. 6 (2019), p. 521-539
- Full Text:
- Reviewed:
- Description: We know very little about how big data-driven service analytics capabilities (SAC) are built in data-driven service organizations and the potential role of talent capability in facilitating overall SAC and the impact of both on firm performance (FPER). Drawing on the dynamic capabilities (DC) approach, this study investigates the link between SAC and FPER examining the mediating role of talent capability and the moderating influence of a firm’s strategic alignment. On the basis of two Delphi studies and survey data from 267 service analysts in the US and France, the findings show that even though SAC are built on technology, talent and information capabilities, their overall impact on firm performance is mediated by the level of talent capability of service analytics managers. The findings also confirm the critical moderating impact of strategic alignment between dynamic talent capability and firm performance in the big data environment.
Self-assembled peptide habitats to model tumor metastasis
- Al Balushi, Noora, Boyd-Moss, Mitchell, Samarasinghe, Rasika, Rifai, Aaqil, Franks, Stephanie, Firipis, Kate, Long, Benjamin, Darby, Ian, Nisbet, David, Pouniotis, Dodie, Williams, Richard
- Authors: Al Balushi, Noora , Boyd-Moss, Mitchell , Samarasinghe, Rasika , Rifai, Aaqil , Franks, Stephanie , Firipis, Kate , Long, Benjamin , Darby, Ian , Nisbet, David , Pouniotis, Dodie , Williams, Richard
- Date: 2022
- Type: Text , Journal article
- Relation: Gels Vol. 8, no. 6 (2022), p.
- Full Text:
- Reviewed:
- Description: Metastatic tumours are complex ecosystems; a community of multiple cell types, including cancerous cells, fibroblasts, and immune cells that exist within a supportive and specific microenvironment. The interplay of these cells, together with tissue specific chemical, structural and temporal signals within a three-dimensional (3D) habitat, direct tumour cell behavior, a subtlety that can be easily lost in 2D tissue culture. Here, we investigate a significantly improved tool, consisting of a novel matrix of functionally programmed peptide sequences, self-assembled into a scaffold to enable the growth and the migration of multicellular lung tumour spheroids, as proof-of-concept. This 3D functional model aims to mimic the biological, chemical, and contextual cues of an in vivo tumor more closely than a typically used, unstructured hydrogel, allowing spatial and temporal activity modelling. This approach shows promise as a cancer model, enhancing current understandings of how tumours progress and spread over time within their microenvironment. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Al Balushi, Noora , Boyd-Moss, Mitchell , Samarasinghe, Rasika , Rifai, Aaqil , Franks, Stephanie , Firipis, Kate , Long, Benjamin , Darby, Ian , Nisbet, David , Pouniotis, Dodie , Williams, Richard
- Date: 2022
- Type: Text , Journal article
- Relation: Gels Vol. 8, no. 6 (2022), p.
- Full Text:
- Reviewed:
- Description: Metastatic tumours are complex ecosystems; a community of multiple cell types, including cancerous cells, fibroblasts, and immune cells that exist within a supportive and specific microenvironment. The interplay of these cells, together with tissue specific chemical, structural and temporal signals within a three-dimensional (3D) habitat, direct tumour cell behavior, a subtlety that can be easily lost in 2D tissue culture. Here, we investigate a significantly improved tool, consisting of a novel matrix of functionally programmed peptide sequences, self-assembled into a scaffold to enable the growth and the migration of multicellular lung tumour spheroids, as proof-of-concept. This 3D functional model aims to mimic the biological, chemical, and contextual cues of an in vivo tumor more closely than a typically used, unstructured hydrogel, allowing spatial and temporal activity modelling. This approach shows promise as a cancer model, enhancing current understandings of how tumours progress and spread over time within their microenvironment. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
COVID-19 : psychological distress, fear, and coping strategies among community members across the United Arab Emirates
- Al Dweik, Rania, Rahman, Muhammad Aziz, Ahamed, Fathima, Ramada, Heba, Al Sheble, Yousef, ElTaher, Sondos, Cross, Wendy, Elsori, Deena
- Authors: Al Dweik, Rania , Rahman, Muhammad Aziz , Ahamed, Fathima , Ramada, Heba , Al Sheble, Yousef , ElTaher, Sondos , Cross, Wendy , Elsori, Deena
- Date: 2023
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 18, no. 3 March (2023), p.
- Full Text:
- Reviewed:
- Description: Background The COVID-19 pandemic impacted the psychosocial well-being of the United Arab Emirates [UAE] population like other communities internationally. Objectives We aimed to identify the factors associated with psychological distress, fear, and coping amongst community members across the UAE. Methods We conducted a cross-sectional online survey across the UAE during November 2020. Adults aged
- Authors: Al Dweik, Rania , Rahman, Muhammad Aziz , Ahamed, Fathima , Ramada, Heba , Al Sheble, Yousef , ElTaher, Sondos , Cross, Wendy , Elsori, Deena
- Date: 2023
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 18, no. 3 March (2023), p.
- Full Text:
- Reviewed:
- Description: Background The COVID-19 pandemic impacted the psychosocial well-being of the United Arab Emirates [UAE] population like other communities internationally. Objectives We aimed to identify the factors associated with psychological distress, fear, and coping amongst community members across the UAE. Methods We conducted a cross-sectional online survey across the UAE during November 2020. Adults aged
Hyperbolic smoothing in nonsmooth optimization and applications
- Authors: Al Nuaimat, Alia
- Date: 2014
- Type: Text , Thesis , PhD
- Full Text:
- Description: Nonsmooth nonconvex optimization problems arise in many applications including economics, business and data mining. In these applications objective functions are not necessarily differentiable or convex. Many algorithms have been proposed over the past three decades to solve such problems. In spite of the significant growth in this field, the development of efficient algorithms for solving this kind of problem is still a challenging task. The subgradient method is one of the simplest methods developed for solving these problems. Its convergence was proved only for convex objective functions. This method does not involve any subproblems, neither for finding search directions nor for computation of step lengths, which are fixed ahead of time. Bundle methods and their various modifications are among the most efficient methods for solving nonsmooth optimization problems. These methods involve a quadratic programming subproblem to find search directions. The size of the subproblem may increase significantly with the number of variables, which makes the bundle-type methods unsuitable for large scale nonsmooth optimization problems. The implementation of bundle-type methods, which require the use of the quadratic programming solvers, is not as easy as the implementation of the subgradient methods. Therefore it is beneficial to develop algorithms for nonsmooth nonconvex optimization which are easy to implement and more efficient than the subgradient methods. In this thesis, we develop two new algorithms for solving nonsmooth nonconvex optimization problems based on the use of the hyperbolic smoothing technique and apply them to solve the pumping cost minimization problem in water distribution. Both algorithms use smoothing techniques. The first algorithm is designed for solving finite minimax problems. In order to apply the hyperbolic smoothing we reformulate the objective function in the minimax problem and study the relationship between the original minimax and reformulated problems. We also study the main properties of the hyperbolic smoothing function. Based on these results an algorithm for solving the finite minimax problem is proposed and this algorithm is implemented in GAMS. We present preliminary results of numerical experiments with well-known nonsmooth optimization test problems. We also compare the proposed algorithm with the algorithm that uses the exponential smoothing function as well as with the algorithm based on nonlinear programming reformulation of the finite minimax problem. The second nonsmooth optimization algorithm we developed was used to demonstrate how smooth optimization methods can be applied to solve general nonsmooth (nonconvex) optimization problems. In order to do so we compute subgradients from some neighborhood of the current point and define a system of linear inequalities using these subgradients. Search directions are computed by solving this system. This system is solved by reducing it to the minimization of the convex piecewise linear function over the unit ball. Then the hyperbolic smoothing function is applied to approximate this minimization problem by a sequence of smooth problems which are solved by smooth optimization methods. Such an approach allows one to apply powerful smooth optimization algorithms for solving nonsmooth optimization problems and extend smoothing techniques for solving general nonsmooth nonconvex optimization problems. The convergence of the algorithm based on this approach is studied. The proposed algorithm was implemented in Fortran 95. Preliminary results of numerical experiments are reported and the proposed algorithm is compared with an other five nonsmooth optimization algorithms. We also implement the algorithm in GAMS and compare it with GAMS solvers using results of numerical experiments.
- Description: Doctor of Philosophy
- Authors: Al Nuaimat, Alia
- Date: 2014
- Type: Text , Thesis , PhD
- Full Text:
- Description: Nonsmooth nonconvex optimization problems arise in many applications including economics, business and data mining. In these applications objective functions are not necessarily differentiable or convex. Many algorithms have been proposed over the past three decades to solve such problems. In spite of the significant growth in this field, the development of efficient algorithms for solving this kind of problem is still a challenging task. The subgradient method is one of the simplest methods developed for solving these problems. Its convergence was proved only for convex objective functions. This method does not involve any subproblems, neither for finding search directions nor for computation of step lengths, which are fixed ahead of time. Bundle methods and their various modifications are among the most efficient methods for solving nonsmooth optimization problems. These methods involve a quadratic programming subproblem to find search directions. The size of the subproblem may increase significantly with the number of variables, which makes the bundle-type methods unsuitable for large scale nonsmooth optimization problems. The implementation of bundle-type methods, which require the use of the quadratic programming solvers, is not as easy as the implementation of the subgradient methods. Therefore it is beneficial to develop algorithms for nonsmooth nonconvex optimization which are easy to implement and more efficient than the subgradient methods. In this thesis, we develop two new algorithms for solving nonsmooth nonconvex optimization problems based on the use of the hyperbolic smoothing technique and apply them to solve the pumping cost minimization problem in water distribution. Both algorithms use smoothing techniques. The first algorithm is designed for solving finite minimax problems. In order to apply the hyperbolic smoothing we reformulate the objective function in the minimax problem and study the relationship between the original minimax and reformulated problems. We also study the main properties of the hyperbolic smoothing function. Based on these results an algorithm for solving the finite minimax problem is proposed and this algorithm is implemented in GAMS. We present preliminary results of numerical experiments with well-known nonsmooth optimization test problems. We also compare the proposed algorithm with the algorithm that uses the exponential smoothing function as well as with the algorithm based on nonlinear programming reformulation of the finite minimax problem. The second nonsmooth optimization algorithm we developed was used to demonstrate how smooth optimization methods can be applied to solve general nonsmooth (nonconvex) optimization problems. In order to do so we compute subgradients from some neighborhood of the current point and define a system of linear inequalities using these subgradients. Search directions are computed by solving this system. This system is solved by reducing it to the minimization of the convex piecewise linear function over the unit ball. Then the hyperbolic smoothing function is applied to approximate this minimization problem by a sequence of smooth problems which are solved by smooth optimization methods. Such an approach allows one to apply powerful smooth optimization algorithms for solving nonsmooth optimization problems and extend smoothing techniques for solving general nonsmooth nonconvex optimization problems. The convergence of the algorithm based on this approach is studied. The proposed algorithm was implemented in Fortran 95. Preliminary results of numerical experiments are reported and the proposed algorithm is compared with an other five nonsmooth optimization algorithms. We also implement the algorithm in GAMS and compare it with GAMS solvers using results of numerical experiments.
- Description: Doctor of Philosophy
E-cigarette use among male smokers in Al-Ahsa, Kingdom of Saudi Arabia : a cross-sectional study
- Al Rajeh, Ahmed, Mahmud, Ilias, Al Imam, Mahmudul, Rahman, Muhammad Aziz, Al Shehri, Fariss, Alomayrin, Salman, Alfazae, Nawaf, Elmosaad, Yousif, Alasqah, Ibrahim
- Authors: Al Rajeh, Ahmed , Mahmud, Ilias , Al Imam, Mahmudul , Rahman, Muhammad Aziz , Al Shehri, Fariss , Alomayrin, Salman , Alfazae, Nawaf , Elmosaad, Yousif , Alasqah, Ibrahim
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Environmental Research and Public Health Vol. 20, no. 1 (2023), p.
- Full Text:
- Reviewed:
- Description: E-cigarette use is increasing globally. Recent evidence suggests that e-cigarettes contain harmful substances that could cause adverse health outcomes. This study investigated the prevalence and associated factors of e-cigarette use among male current smokers in Saudi Arabia. We conducted a cross-sectional survey of adult male current smokers in the Al-Ahsa province of Saudi Arabia. Data were collected using a structured questionnaire. We performed logistic regression analyses to investigate the factors associated with e-cigarette use among adult male current smokers. 325 current smokers participated in the study. A third of them (33.5%) were e-cigarette users. Almost all the study participants (97.0%) had heard about e-cigarettes. Participants who were occasional smokers (Odds Ratio (OR): 2.28; 95% Confidence Interval (CI): 1.17–4.41) and had good knowledge perception of e-cigarettes (OR 3.49; 95% CI: 2.07–5.90) had higher odds of using e-cigarettes when compared to regular smokers of conventional cigarettes and current smokers with poor knowledge perception of e-cigarettes, respectively. In contrast, private employees (OR: 0.25, 95% CI: 0.07–0.85), and business owners (OR: 0.09, 95% CI: 0.01–0.63) had lower odds of using e-cigarettes compared to unemployed individuals. Compared with non-e-cigarette users, the rate of conventional cigarette smoking per day was significantly lower among e-cigarette users. Use of e-cigarette (OR: 3.57, 95% CI: 2.14–5.98), believing that e-cigarette quitting is hard (OR: 2.02, 95% CI: 1.17–3.49) and trying to quit e-cigarettes (OR: 2.17, 95% CI: 1.1–4.25) were found to be significant predictors of good knowledge perception of e-cigarettes among the current smokers. The use and knowledge perception of e-cigarettes were higher among occasional conventional male cigarette smokers than regular male smokers in Al-Ahsa province. The use of e-cigarettes as smoking cessation aids should be examined further in the Saudi Arabian setting. © 2022 by the authors.
- Authors: Al Rajeh, Ahmed , Mahmud, Ilias , Al Imam, Mahmudul , Rahman, Muhammad Aziz , Al Shehri, Fariss , Alomayrin, Salman , Alfazae, Nawaf , Elmosaad, Yousif , Alasqah, Ibrahim
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Environmental Research and Public Health Vol. 20, no. 1 (2023), p.
- Full Text:
- Reviewed:
- Description: E-cigarette use is increasing globally. Recent evidence suggests that e-cigarettes contain harmful substances that could cause adverse health outcomes. This study investigated the prevalence and associated factors of e-cigarette use among male current smokers in Saudi Arabia. We conducted a cross-sectional survey of adult male current smokers in the Al-Ahsa province of Saudi Arabia. Data were collected using a structured questionnaire. We performed logistic regression analyses to investigate the factors associated with e-cigarette use among adult male current smokers. 325 current smokers participated in the study. A third of them (33.5%) were e-cigarette users. Almost all the study participants (97.0%) had heard about e-cigarettes. Participants who were occasional smokers (Odds Ratio (OR): 2.28; 95% Confidence Interval (CI): 1.17–4.41) and had good knowledge perception of e-cigarettes (OR 3.49; 95% CI: 2.07–5.90) had higher odds of using e-cigarettes when compared to regular smokers of conventional cigarettes and current smokers with poor knowledge perception of e-cigarettes, respectively. In contrast, private employees (OR: 0.25, 95% CI: 0.07–0.85), and business owners (OR: 0.09, 95% CI: 0.01–0.63) had lower odds of using e-cigarettes compared to unemployed individuals. Compared with non-e-cigarette users, the rate of conventional cigarette smoking per day was significantly lower among e-cigarette users. Use of e-cigarette (OR: 3.57, 95% CI: 2.14–5.98), believing that e-cigarette quitting is hard (OR: 2.02, 95% CI: 1.17–3.49) and trying to quit e-cigarettes (OR: 2.17, 95% CI: 1.1–4.25) were found to be significant predictors of good knowledge perception of e-cigarettes among the current smokers. The use and knowledge perception of e-cigarettes were higher among occasional conventional male cigarette smokers than regular male smokers in Al-Ahsa province. The use of e-cigarettes as smoking cessation aids should be examined further in the Saudi Arabian setting. © 2022 by the authors.
Multiple comorbidities of 21 psychological disorders and relationships with psychosocial variables: A study of the online assessment and diagnostic system within a web-based population
- Al-Asadi, Ali, Klein, Britt, Meyer, Denny
- Authors: Al-Asadi, Ali , Klein, Britt , Meyer, Denny
- Date: 2015
- Type: Text , Journal article
- Relation: Journal of Medical Internet Research Vol. 17, no. 2 (2015), p. 355
- Full Text:
- Reviewed:
- Description: Background: While research in the area of e-mental health has received considerable attention over the last decade, there are still many areas that have not been addressed. One such area is the comorbidity of psychological disorders in a Web-based sample using online assessment and diagnostic tools, and the relationships between comorbidities and psychosocial variables. Objective: We aimed to identify comorbidities of psychological disorders of an online sample using an online diagnostic tool. Based on diagnoses made by an automated online assessment and diagnostic system administered to a large group of online participants, multiple comorbidities (co-occurrences) of 21 psychological disorders for males and females were identified. We examined the relationships between dyadic comorbidities of anxiety and depressive disorders and the psychosocial variables sex, age, suicidal ideation, social support, and quality of life. Methods: An online complex algorithm based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, Text Revision, was used to assign primary and secondary diagnoses of 21 psychological disorders to 12,665 online participants. The frequency of co-occurrences of psychological disorders for males and females were calculated for all disorders. A series of hierarchical loglinear analyses were performed to examine the relationships between the dyadic comorbidities of depression and various anxiety disorders and the variables suicidal ideation, social support, quality of life, sex, and age. Results: A 21-by-21 frequency of co-occurrences of psychological disorders matrix revealed the presence of multiple significant dyadic comorbidities for males and females. Also, for those with some of the dyadic depression and the anxiety disorders, the odds for having suicidal ideation, reporting inadequate social support, and poorer quality of life increased for those with two-disorder comorbidity than for those with only one of the same two disorders. Conclusions: Comorbidities of several psychological disorders using an online assessment tool within a Web-based population were similar to those found in face-to-face clinics using traditional assessment tools. Results provided support for the transdiagnostic approaches and confirmed the positive relationship between comorbidity and suicidal ideation, the negative relationship between comorbidity and social support, and the negative relationship comorbidity and quality of life. © 2015, Journal of Medical Internet Research. All rights reserved.
- Authors: Al-Asadi, Ali , Klein, Britt , Meyer, Denny
- Date: 2015
- Type: Text , Journal article
- Relation: Journal of Medical Internet Research Vol. 17, no. 2 (2015), p. 355
- Full Text:
- Reviewed:
- Description: Background: While research in the area of e-mental health has received considerable attention over the last decade, there are still many areas that have not been addressed. One such area is the comorbidity of psychological disorders in a Web-based sample using online assessment and diagnostic tools, and the relationships between comorbidities and psychosocial variables. Objective: We aimed to identify comorbidities of psychological disorders of an online sample using an online diagnostic tool. Based on diagnoses made by an automated online assessment and diagnostic system administered to a large group of online participants, multiple comorbidities (co-occurrences) of 21 psychological disorders for males and females were identified. We examined the relationships between dyadic comorbidities of anxiety and depressive disorders and the psychosocial variables sex, age, suicidal ideation, social support, and quality of life. Methods: An online complex algorithm based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, Text Revision, was used to assign primary and secondary diagnoses of 21 psychological disorders to 12,665 online participants. The frequency of co-occurrences of psychological disorders for males and females were calculated for all disorders. A series of hierarchical loglinear analyses were performed to examine the relationships between the dyadic comorbidities of depression and various anxiety disorders and the variables suicidal ideation, social support, quality of life, sex, and age. Results: A 21-by-21 frequency of co-occurrences of psychological disorders matrix revealed the presence of multiple significant dyadic comorbidities for males and females. Also, for those with some of the dyadic depression and the anxiety disorders, the odds for having suicidal ideation, reporting inadequate social support, and poorer quality of life increased for those with two-disorder comorbidity than for those with only one of the same two disorders. Conclusions: Comorbidities of several psychological disorders using an online assessment tool within a Web-based population were similar to those found in face-to-face clinics using traditional assessment tools. Results provided support for the transdiagnostic approaches and confirmed the positive relationship between comorbidity and suicidal ideation, the negative relationship between comorbidity and social support, and the negative relationship comorbidity and quality of life. © 2015, Journal of Medical Internet Research. All rights reserved.
Posttreatment attrition and its predictors, attrition bias, and treatment efficacy of the anxiety online programs
- Al-Asadi, Ali, Klein, Britt, Meyer, Denny
- Authors: Al-Asadi, Ali , Klein, Britt , Meyer, Denny
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Medical Internet Research Vol. 16, no. 10 (2014), p. e232
- Full Text:
- Reviewed:
- Description: Background: Although relatively new, the field of e-mental health is becoming more popular with more attention given to researching its various aspects. However, there are many areas that still need further research, especially identifying attrition predictors at various phases of assessment and treatment delivery. Objective: The present study identified the predictors of posttreatment assessment completers based on 24 pre- and posttreatment demographic and personal variables and 1 treatment variable, their impact on attrition bias, and the efficacy of the 5 fully automated self-help anxiety treatment programs for generalized anxiety disorder (GAD), social anxiety disorder (SAD), panic disorder with or without agoraphobia (PD/A), obsessive-compulsive disorder (OCD), and posttraumatic stress disorder (PTSD). Methods: A complex algorithm was used to diagnose participants' mental disorders based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision; DSM-IV-TR). Those who received a primary or secondary diagnosis of 1 of 5 anxiety disorders were offered an online 12-week disorder-specific treatment program. A total of 3199 individuals did not formally drop out of the 12-week treatment cycle, whereas 142 individuals formally dropped out. However, only 347 participants who completed their treatment cycle also completed the posttreatment assessment measures. Based on these measures, predictors of attrition were identified and attrition bias was examined. The efficacy of the 5 treatment programs was assessed based on anxiety-specific severity scores and 5 additional treatment outcome measures. Results: On average, completers of posttreatment assessment measures were more likely to be seeking self-help online programs; have heard about the program from traditional media or from family and friends; were receiving mental health assistance; were more likely to learn best by reading, hearing and doing; had a lower pretreatment Kessler-6 total score; and were older in age. Predicted probabilities resulting from these attrition variables displayed no significant attrition bias using Heckman's method and thus allowing for the use of completer analysis. Six treatment outcome measures (Kessler-6 total score, number of diagnosed disorders, self-confidence in managing mental health issues, quality of life, and the corresponding pre- and posttreatment severity for each program-specific anxiety disorder and for major depressive episode) were used to assess the efficacy of the 5 anxiety treatment programs. Repeated measures MANOVA revealed a significant multivariate time effect for all treatment outcome measures for each treatment program. Follow-up repeated measures ANOVAs revealed significant improvements on all 6 treatment outcome measures for GAD and PTSD, 5 treatment outcome measures were significant for SAD and PD/A, and 4 treatment outcome measures were significant for OCD. Conclusions: Results identified predictors of posttreatment assessment completers and provided further support for the efficacy of self-help online treatment programs for the 5 anxiety disorders
- Authors: Al-Asadi, Ali , Klein, Britt , Meyer, Denny
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Medical Internet Research Vol. 16, no. 10 (2014), p. e232
- Full Text:
- Reviewed:
- Description: Background: Although relatively new, the field of e-mental health is becoming more popular with more attention given to researching its various aspects. However, there are many areas that still need further research, especially identifying attrition predictors at various phases of assessment and treatment delivery. Objective: The present study identified the predictors of posttreatment assessment completers based on 24 pre- and posttreatment demographic and personal variables and 1 treatment variable, their impact on attrition bias, and the efficacy of the 5 fully automated self-help anxiety treatment programs for generalized anxiety disorder (GAD), social anxiety disorder (SAD), panic disorder with or without agoraphobia (PD/A), obsessive-compulsive disorder (OCD), and posttraumatic stress disorder (PTSD). Methods: A complex algorithm was used to diagnose participants' mental disorders based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision; DSM-IV-TR). Those who received a primary or secondary diagnosis of 1 of 5 anxiety disorders were offered an online 12-week disorder-specific treatment program. A total of 3199 individuals did not formally drop out of the 12-week treatment cycle, whereas 142 individuals formally dropped out. However, only 347 participants who completed their treatment cycle also completed the posttreatment assessment measures. Based on these measures, predictors of attrition were identified and attrition bias was examined. The efficacy of the 5 treatment programs was assessed based on anxiety-specific severity scores and 5 additional treatment outcome measures. Results: On average, completers of posttreatment assessment measures were more likely to be seeking self-help online programs; have heard about the program from traditional media or from family and friends; were receiving mental health assistance; were more likely to learn best by reading, hearing and doing; had a lower pretreatment Kessler-6 total score; and were older in age. Predicted probabilities resulting from these attrition variables displayed no significant attrition bias using Heckman's method and thus allowing for the use of completer analysis. Six treatment outcome measures (Kessler-6 total score, number of diagnosed disorders, self-confidence in managing mental health issues, quality of life, and the corresponding pre- and posttreatment severity for each program-specific anxiety disorder and for major depressive episode) were used to assess the efficacy of the 5 anxiety treatment programs. Repeated measures MANOVA revealed a significant multivariate time effect for all treatment outcome measures for each treatment program. Follow-up repeated measures ANOVAs revealed significant improvements on all 6 treatment outcome measures for GAD and PTSD, 5 treatment outcome measures were significant for SAD and PD/A, and 4 treatment outcome measures were significant for OCD. Conclusions: Results identified predictors of posttreatment assessment completers and provided further support for the efficacy of self-help online treatment programs for the 5 anxiety disorders
Pretreatment attrition and formal withdrawal during treatment and their predictors: An exploratory study of the anxiety online data
- Al-Asadi, Ali, Klein, Britt, Meyer, Denny
- Authors: Al-Asadi, Ali , Klein, Britt , Meyer, Denny
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Medical Internet Research Vol. 16, no. 6 (2014), p. e152
- Full Text:
- Reviewed:
- Description: Although in its infancy, the field of e-mental health interventions has been gaining popularity and afforded considerable research attention. However, there are many gaps in the research. One such gap is in the area of attrition predictors at various stages of assessment and treatment delivery. Objective: This exploratory study applied univariate and multivariate analysis to a large dataset provided by the Anxiety Online (now called Mental Health Online) system to identify predictors of attrition in treatment commencers and in those who formally withdrew during treatment based on 24 pretreatment demographic and personal variables and one clinical measure. Methods: Participants were assessed using a complex online algorithm that resulted in primary and secondary diagnoses in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Those who received a primary or secondary diagnosis of 1 of 5 anxiety disorders (generalized anxiety disorder, social anxiety disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and panic disorder) were offered an online 12-week disorder-specific treatment program. Results: Of 9394 potential participants, a total of 3880 clients enrolled and 5514 did not enroll in one of the treatment programs following the completion of pretreatment assessment measures (pretreatment attrition rate: 58.70%). A total of 3199 individuals did not formally withdraw from the 12-week treatment cycle, whereas 142 individuals formally dropped out (formal withdrawal during treatment dropout rate of 4.25%). The treatment commencers differed significantly (P<.001-.03) from the noncommencers on several variables (reason for registering, mental health concerns, postsecondary education, where first heard about Anxiety Online, Kessler-6 score, stage of change, quality of life, relationship status, preferred method of learning, and smoking status). Those who formally withdrew during treatment differed significantly (P=.002-.03) from those who did not formally withdraw in that they were less likely to express concerns about anxiety, stress, and depression; to rate their quality of life as very poor, poor, or good; to report adequate level of social support; and to report readiness to make or were in the process of making changes. Conclusions: This exploratory study identified predictors of pretreatment attrition and formal withdrawal during treatment dropouts for the Anxiety Online program.
- Description: Although in its infancy, the field of e-mental health interventions has been gaining popularity and afforded considerable research attention. However, there are many gaps in the research. One such gap is in the area of attrition predictors at various stages of assessment and treatment delivery. Objective: This exploratory study applied univariate and multivariate analysis to a large dataset provided by the Anxiety Online (now called Mental Health Online) system to identify predictors of attrition in treatment commencers and in those who formally withdrew during treatment based on 24 pretreatment demographic and personal variables and one clinical measure. Methods: Participants were assessed using a complex online algorithm that resulted in primary and secondary diagnoses in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Those who received a primary or secondary diagnosis of 1 of 5 anxiety disorders (generalized anxiety disorder, social anxiety disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and panic disorder) were offered an online 12-week disorder-specific treatment program. Results: Of 9394 potential participants, a total of 3880 clients enrolled and 5514 did not enroll in one of the treatment programs following the completion of pretreatment assessment measures (pretreatment attrition rate: 58.70%). A total of 3199 individuals did not formally withdraw from the 12-week treatment cycle, whereas 142 individuals formally dropped out (formal withdrawal during treatment dropout rate of 4.25%). The treatment commencers differed significantly (P<.001-.03) from the noncommencers on several variables (reason for registering, mental health concerns, postsecondary education, where first heard about Anxiety Online, Kessler-6 score, stage of change, quality of life, relationship status, preferred method of learning, and smoking status). Those who formally withdrew during treatment differed significantly (P=.002-.03) from those who did not formally withdraw in that they were less likely to express concerns about anxiety, stress, and depression; to rate their quality of life as very poor, poor, or good; to report adequate level of social support; and to report readiness to make or were in the process of making changes. Conclusions: This exploratory study identified predictors of pretreatment attrition and formal withdrawal during treatment dropouts for the Anxiety Online program
- Authors: Al-Asadi, Ali , Klein, Britt , Meyer, Denny
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Medical Internet Research Vol. 16, no. 6 (2014), p. e152
- Full Text:
- Reviewed:
- Description: Although in its infancy, the field of e-mental health interventions has been gaining popularity and afforded considerable research attention. However, there are many gaps in the research. One such gap is in the area of attrition predictors at various stages of assessment and treatment delivery. Objective: This exploratory study applied univariate and multivariate analysis to a large dataset provided by the Anxiety Online (now called Mental Health Online) system to identify predictors of attrition in treatment commencers and in those who formally withdrew during treatment based on 24 pretreatment demographic and personal variables and one clinical measure. Methods: Participants were assessed using a complex online algorithm that resulted in primary and secondary diagnoses in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Those who received a primary or secondary diagnosis of 1 of 5 anxiety disorders (generalized anxiety disorder, social anxiety disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and panic disorder) were offered an online 12-week disorder-specific treatment program. Results: Of 9394 potential participants, a total of 3880 clients enrolled and 5514 did not enroll in one of the treatment programs following the completion of pretreatment assessment measures (pretreatment attrition rate: 58.70%). A total of 3199 individuals did not formally withdraw from the 12-week treatment cycle, whereas 142 individuals formally dropped out (formal withdrawal during treatment dropout rate of 4.25%). The treatment commencers differed significantly (P<.001-.03) from the noncommencers on several variables (reason for registering, mental health concerns, postsecondary education, where first heard about Anxiety Online, Kessler-6 score, stage of change, quality of life, relationship status, preferred method of learning, and smoking status). Those who formally withdrew during treatment differed significantly (P=.002-.03) from those who did not formally withdraw in that they were less likely to express concerns about anxiety, stress, and depression; to rate their quality of life as very poor, poor, or good; to report adequate level of social support; and to report readiness to make or were in the process of making changes. Conclusions: This exploratory study identified predictors of pretreatment attrition and formal withdrawal during treatment dropouts for the Anxiety Online program.
- Description: Although in its infancy, the field of e-mental health interventions has been gaining popularity and afforded considerable research attention. However, there are many gaps in the research. One such gap is in the area of attrition predictors at various stages of assessment and treatment delivery. Objective: This exploratory study applied univariate and multivariate analysis to a large dataset provided by the Anxiety Online (now called Mental Health Online) system to identify predictors of attrition in treatment commencers and in those who formally withdrew during treatment based on 24 pretreatment demographic and personal variables and one clinical measure. Methods: Participants were assessed using a complex online algorithm that resulted in primary and secondary diagnoses in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Those who received a primary or secondary diagnosis of 1 of 5 anxiety disorders (generalized anxiety disorder, social anxiety disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and panic disorder) were offered an online 12-week disorder-specific treatment program. Results: Of 9394 potential participants, a total of 3880 clients enrolled and 5514 did not enroll in one of the treatment programs following the completion of pretreatment assessment measures (pretreatment attrition rate: 58.70%). A total of 3199 individuals did not formally withdraw from the 12-week treatment cycle, whereas 142 individuals formally dropped out (formal withdrawal during treatment dropout rate of 4.25%). The treatment commencers differed significantly (P<.001-.03) from the noncommencers on several variables (reason for registering, mental health concerns, postsecondary education, where first heard about Anxiety Online, Kessler-6 score, stage of change, quality of life, relationship status, preferred method of learning, and smoking status). Those who formally withdrew during treatment differed significantly (P=.002-.03) from those who did not formally withdraw in that they were less likely to express concerns about anxiety, stress, and depression; to rate their quality of life as very poor, poor, or good; to report adequate level of social support; and to report readiness to make or were in the process of making changes. Conclusions: This exploratory study identified predictors of pretreatment attrition and formal withdrawal during treatment dropouts for the Anxiety Online program
Comorbidity structure of psychological disorders in the online e-PASS data as predictors of psychosocial adjustment measures: psychological distress, adequate social support, self-confidence, quality of life, and suicidal ideation
- Al-Asadi, Ali, Klein, Britt, Meyer, Denny
- Authors: Al-Asadi, Ali , Klein, Britt , Meyer, Denny
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Medical Internet Research Vol. 16, no. 10 (2014), p. e248
- Full Text:
- Reviewed:
- Description: BACKGROUND: A relative newcomer to the field of psychology, e-mental health has been gaining momentum and has been given considerable research attention. Although several aspects of e-mental health have been studied, 1 aspect has yet to receive attention: the structure of comorbidity of psychological disorders and their relationships with measures of psychosocial adjustment including suicidal ideation in online samples. OBJECTIVE: This exploratory study attempted to identify the structure of comorbidity of 21 psychological disorders assessed by an automated online electronic psychological assessment screening system (e-PASS). The resulting comorbidity factor scores were then used to assess the association between comorbidity factor scores and measures of psychosocial adjustments (ie, psychological distress, suicidal ideation, adequate social support, self-confidence in dealing with mental health issues, and quality of life). METHODS: A total of 13,414 participants were assessed using a complex online algorithm that resulted in primary and secondary Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) diagnoses for 21 psychological disorders on dimensional severity scales. The scores on these severity scales were used in a principal component analysis (PCA) and the resulting comorbidity factor scores were related to 4 measures of psychosocial adjustments. RESULTS: A PCA based on 17 of the 21 psychological disorders resulted in a 4-factor model of comorbidity: anxiety-depression consisting of all anxiety disorders, major depressive episode (MDE), and insomnia; substance abuse consisting of alcohol and drug abuse and dependency; body image-eating consisting of eating disorders, body dysmorphic disorder, and obsessive-compulsive disorders; depression-sleep problems consisting of MDE, insomnia, and hypersomnia. All comorbidity factor scores were significantly associated with psychosocial measures of adjustment (P<.001). They were positively related to psychological distress and suicidal ideation, but negatively related to adequate social support, self-confidence, and quality of life. CONCLUSIONS: This exploratory study identified 4 comorbidity factors in the e-PASS data and these factor scores significantly predicted 5 psychosocial adjustment measures. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN121611000704998; http://www.anzctr.org.au/trial_view.aspx?ID=336143 (Archived by WebCite at http://www.webcitation.org/618r3wvOG).
- Authors: Al-Asadi, Ali , Klein, Britt , Meyer, Denny
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Medical Internet Research Vol. 16, no. 10 (2014), p. e248
- Full Text:
- Reviewed:
- Description: BACKGROUND: A relative newcomer to the field of psychology, e-mental health has been gaining momentum and has been given considerable research attention. Although several aspects of e-mental health have been studied, 1 aspect has yet to receive attention: the structure of comorbidity of psychological disorders and their relationships with measures of psychosocial adjustment including suicidal ideation in online samples. OBJECTIVE: This exploratory study attempted to identify the structure of comorbidity of 21 psychological disorders assessed by an automated online electronic psychological assessment screening system (e-PASS). The resulting comorbidity factor scores were then used to assess the association between comorbidity factor scores and measures of psychosocial adjustments (ie, psychological distress, suicidal ideation, adequate social support, self-confidence in dealing with mental health issues, and quality of life). METHODS: A total of 13,414 participants were assessed using a complex online algorithm that resulted in primary and secondary Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) diagnoses for 21 psychological disorders on dimensional severity scales. The scores on these severity scales were used in a principal component analysis (PCA) and the resulting comorbidity factor scores were related to 4 measures of psychosocial adjustments. RESULTS: A PCA based on 17 of the 21 psychological disorders resulted in a 4-factor model of comorbidity: anxiety-depression consisting of all anxiety disorders, major depressive episode (MDE), and insomnia; substance abuse consisting of alcohol and drug abuse and dependency; body image-eating consisting of eating disorders, body dysmorphic disorder, and obsessive-compulsive disorders; depression-sleep problems consisting of MDE, insomnia, and hypersomnia. All comorbidity factor scores were significantly associated with psychosocial measures of adjustment (P<.001). They were positively related to psychological distress and suicidal ideation, but negatively related to adequate social support, self-confidence, and quality of life. CONCLUSIONS: This exploratory study identified 4 comorbidity factors in the e-PASS data and these factor scores significantly predicted 5 psychosocial adjustment measures. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN121611000704998; http://www.anzctr.org.au/trial_view.aspx?ID=336143 (Archived by WebCite at http://www.webcitation.org/618r3wvOG).
Addition of activated carbon into a cattle diet to mitigate GHG emissions and improve production
- Al-Azzawi, Mohammed, Bowtell, Les, Hancock, Kerry, Preston, Sarah
- Authors: Al-Azzawi, Mohammed , Bowtell, Les , Hancock, Kerry , Preston, Sarah
- Date: 2021
- Type: Text , Journal article
- Relation: Sustainability (Switzerland) Vol. 13, no. 15 (2021), p.
- Full Text:
- Reviewed:
- Description: Globally, the most problematic greenhouse gas (GHG) emissions of ruminant livestock is methane (CH4), with a global warming potential 25 times that of carbon dioxide. This work considers the emissions and production effects of powdered activated carbon (PAC) at 0.5% by dry matter (DM) on methanogenic rumen flora as the major source of dairy cattle enteric methane emissions. In total, 180 dairy cattle located in Brymaroo, Queensland (QLD), Australia, were studied in a three-cycle repeated measures ANOVA format with a 4 week primary interval. Emissions eructated during milking and in faecal deposits were measured, and in addition, 16S rRNA gene sequencing was performed to determine the collective populations of prokaryotic bacteria and archaea as well methanogenic communities for each treatment. Moreover, 0.5% PAC addition reduced CH4 emissions by 30-40% and CO2 emissions by 10%, while improving daily milk production by 3.43%, milk protein by 2.63% and milk fat by 6.32%, on average for the herd (p < 0.001 in all cases). rRNA gene sequencing showed populations of methanogenic flora decreased by 30% on average with a corresponding increase in the nonmethanogenic species. We strongly advocate further on-farm trials with the dietary addition of PAC in ruminant diets to mitigate emissions while maintaining or improving productivity. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Al-Azzawi, Mohammed , Bowtell, Les , Hancock, Kerry , Preston, Sarah
- Date: 2021
- Type: Text , Journal article
- Relation: Sustainability (Switzerland) Vol. 13, no. 15 (2021), p.
- Full Text:
- Reviewed:
- Description: Globally, the most problematic greenhouse gas (GHG) emissions of ruminant livestock is methane (CH4), with a global warming potential 25 times that of carbon dioxide. This work considers the emissions and production effects of powdered activated carbon (PAC) at 0.5% by dry matter (DM) on methanogenic rumen flora as the major source of dairy cattle enteric methane emissions. In total, 180 dairy cattle located in Brymaroo, Queensland (QLD), Australia, were studied in a three-cycle repeated measures ANOVA format with a 4 week primary interval. Emissions eructated during milking and in faecal deposits were measured, and in addition, 16S rRNA gene sequencing was performed to determine the collective populations of prokaryotic bacteria and archaea as well methanogenic communities for each treatment. Moreover, 0.5% PAC addition reduced CH4 emissions by 30-40% and CO2 emissions by 10%, while improving daily milk production by 3.43%, milk protein by 2.63% and milk fat by 6.32%, on average for the herd (p < 0.001 in all cases). rRNA gene sequencing showed populations of methanogenic flora decreased by 30% on average with a corresponding increase in the nonmethanogenic species. We strongly advocate further on-farm trials with the dietary addition of PAC in ruminant diets to mitigate emissions while maintaining or improving productivity. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
The influence of emulsified water fuel containing fresh water microalgae on diesel engine performance, combustion, vibration and emission
- Al-Lwayzy, Saddam, Yusaf, Talal, Saleh, Khalid, Yousif, Belal
- Authors: Al-Lwayzy, Saddam , Yusaf, Talal , Saleh, Khalid , Yousif, Belal
- Date: 2019
- Type: Text , Journal article
- Relation: Energies Vol. 12, no. 13 (2019), p. 1-17
- Full Text:
- Reviewed:
- Description: Microalgae is considered as an excellent potential renewable source of fuel in many forms including powder or slurry. A high percentage of emulsified water in the fuel is reported to reduce diesel engines’ emissions such as NOx, but that will compromise the engine output power. Using microalgae powder as an additive to enhance the emulsified water fuel heating value is the main objective of this work. Diesel engine combustion, vibration, performance and emissions were evaluated for pure cottonseed biodiesel (CS-B100), emulsified water 20% (vol.) in cottonseed biodiesel (CSB-E20) and emulsified water 20% (vol.) containing Fresh Water Microalgae Chlorella Vulgaris (FWM-CV) in cottonseed biodiesel (CSB-ME20). The emulsified water fuels showed a reduction in in-cylinder pressure, vibration, brake power, torque, exhaust gas temperature, CO2 and NOx, while BSFC and O2 were higher than the pure biodiesel (CS-B100). CSB-ME20 produced higher power and torque than CSB-E20 due to the presence of microalgae in the fuel that increased the energy content of the fuel.
- Authors: Al-Lwayzy, Saddam , Yusaf, Talal , Saleh, Khalid , Yousif, Belal
- Date: 2019
- Type: Text , Journal article
- Relation: Energies Vol. 12, no. 13 (2019), p. 1-17
- Full Text:
- Reviewed:
- Description: Microalgae is considered as an excellent potential renewable source of fuel in many forms including powder or slurry. A high percentage of emulsified water in the fuel is reported to reduce diesel engines’ emissions such as NOx, but that will compromise the engine output power. Using microalgae powder as an additive to enhance the emulsified water fuel heating value is the main objective of this work. Diesel engine combustion, vibration, performance and emissions were evaluated for pure cottonseed biodiesel (CS-B100), emulsified water 20% (vol.) in cottonseed biodiesel (CSB-E20) and emulsified water 20% (vol.) containing Fresh Water Microalgae Chlorella Vulgaris (FWM-CV) in cottonseed biodiesel (CSB-ME20). The emulsified water fuels showed a reduction in in-cylinder pressure, vibration, brake power, torque, exhaust gas temperature, CO2 and NOx, while BSFC and O2 were higher than the pure biodiesel (CS-B100). CSB-ME20 produced higher power and torque than CSB-E20 due to the presence of microalgae in the fuel that increased the energy content of the fuel.
The experiences of people with diabetes during covid-19 pandemic lockdown
- Al-Moteri, Modi, Plummer, Virginia, Youssef, Hanan, Yaseen, Ruba, Al Malki, Mohammed, Elryah, Ahmed, Al Karani, Ahmed
- Authors: Al-Moteri, Modi , Plummer, Virginia , Youssef, Hanan , Yaseen, Ruba , Al Malki, Mohammed , Elryah, Ahmed , Al Karani, Ahmed
- Date: 2022
- Type: Text , Journal article
- Relation: International Journal of Environmental Research and Public Health Vol. 19, no. 1 (2022), p.
- Full Text:
- Reviewed:
- Description: Little is known about the theoretical foundation underling the response of people with diabetes managing their everyday routines during COVID-19 pandemic lockdown. Aim: To explore the experience of people with diabetes during COVID-19 pandemic lockdown in light of the risk perception, response and behavioral change theories. Method: A qualitative descriptive design was employed, and Braun and Clark’s six step analysis were used for thematic analysis. Semi-structured interviews were conducted online using Zoom Videos Communication. Result: Five themes were defined as follows: (1) perceived the threat and faced their fears, (2) appraised the damage, (3) identified the challenges, (4) modified their routine, and (5) identified the strengths that facilitate the efficacy of their response. There were eight sub-themes within the themes. Conclusion: The results of this study may provide an opportunity for nurses to reflect on issues highlighted by the patients regarding more effective communication, knowledge and skill development for people to support self-care during national emergencies. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Al-Moteri, Modi , Plummer, Virginia , Youssef, Hanan , Yaseen, Ruba , Al Malki, Mohammed , Elryah, Ahmed , Al Karani, Ahmed
- Date: 2022
- Type: Text , Journal article
- Relation: International Journal of Environmental Research and Public Health Vol. 19, no. 1 (2022), p.
- Full Text:
- Reviewed:
- Description: Little is known about the theoretical foundation underling the response of people with diabetes managing their everyday routines during COVID-19 pandemic lockdown. Aim: To explore the experience of people with diabetes during COVID-19 pandemic lockdown in light of the risk perception, response and behavioral change theories. Method: A qualitative descriptive design was employed, and Braun and Clark’s six step analysis were used for thematic analysis. Semi-structured interviews were conducted online using Zoom Videos Communication. Result: Five themes were defined as follows: (1) perceived the threat and faced their fears, (2) appraised the damage, (3) identified the challenges, (4) modified their routine, and (5) identified the strengths that facilitate the efficacy of their response. There were eight sub-themes within the themes. Conclusion: The results of this study may provide an opportunity for nurses to reflect on issues highlighted by the patients regarding more effective communication, knowledge and skill development for people to support self-care during national emergencies. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
The road to developing standard time for efficient nursing care : a time and motion analysis
- Al-Moteri, Modi, Alzahrani, Amer, Althobiti, Ensherah, Plummer, Virginia, Sahrah, Afnan, Alkhaldi, Maha, Rajab, Eishah, Alsalmi, Amani, Abdullah, Merhamah, Abduelazeez, Afra, Caslangen, Mari-zel, Ismail, Mariam, Alqurashi, Talal
- Authors: Al-Moteri, Modi , Alzahrani, Amer , Althobiti, Ensherah , Plummer, Virginia , Sahrah, Afnan , Alkhaldi, Maha , Rajab, Eishah , Alsalmi, Amani , Abdullah, Merhamah , Abduelazeez, Afra , Caslangen, Mari-zel , Ismail, Mariam , Alqurashi, Talal
- Date: 2023
- Type: Text , Journal article
- Relation: Healthcare (Switzerland) Vol. 11, no. 15 (2023), p.
- Full Text:
- Reviewed:
- Description: (1) Background: The amount of time nurses spend with their patients is essential to improving the quality of patient care. Studies have shown that nurses spend a considerable amount of time on a variety of activities––which are often not taken into account while estimating nurse-to-patient care time allocation––that could potentially be eliminated, combined or delegated with greater productivity. The current study aimed to calculate standard time for each activity category by quantifying the amount of time required by nurses to complete an activity category and determine the adjustment time that can be given during work, as well as determine factors that can be altered to improve the efficiency of nursing care on inpatient general wards of a governmental hospital. (2) Method: A time and motion study was conducted over two weeks using 1-to-1 continuous observations of nurses as they performed their duties on inpatient general wards, while observers recorded each single activity, and specifically the time and movements required to complete those activities. (3) Result: There was 5100 min of observations over 10 working days. Nurses spent 69% (330 min) of time during their 8 h morning shift on direct patient care, (19.4%) ward/room activities (18%), documentation (14%), indirect patient care (12%) and professional communication (5%). Around 94 min of activities seem to be wasted and can be potentially detrimental to nurses’ overall productivity and threaten patient care quality. The standard number of hours that represents the best estimate of a general ward nurse regarding the optimal speed at which the staff nurse can provide care related activities was computed and proposed. (4) Conclusions: The findings obtained from time–motion studies can help in developing more efficient and productive nursing work for more optimal care of patients. © 2023 by the authors.
- Authors: Al-Moteri, Modi , Alzahrani, Amer , Althobiti, Ensherah , Plummer, Virginia , Sahrah, Afnan , Alkhaldi, Maha , Rajab, Eishah , Alsalmi, Amani , Abdullah, Merhamah , Abduelazeez, Afra , Caslangen, Mari-zel , Ismail, Mariam , Alqurashi, Talal
- Date: 2023
- Type: Text , Journal article
- Relation: Healthcare (Switzerland) Vol. 11, no. 15 (2023), p.
- Full Text:
- Reviewed:
- Description: (1) Background: The amount of time nurses spend with their patients is essential to improving the quality of patient care. Studies have shown that nurses spend a considerable amount of time on a variety of activities––which are often not taken into account while estimating nurse-to-patient care time allocation––that could potentially be eliminated, combined or delegated with greater productivity. The current study aimed to calculate standard time for each activity category by quantifying the amount of time required by nurses to complete an activity category and determine the adjustment time that can be given during work, as well as determine factors that can be altered to improve the efficiency of nursing care on inpatient general wards of a governmental hospital. (2) Method: A time and motion study was conducted over two weeks using 1-to-1 continuous observations of nurses as they performed their duties on inpatient general wards, while observers recorded each single activity, and specifically the time and movements required to complete those activities. (3) Result: There was 5100 min of observations over 10 working days. Nurses spent 69% (330 min) of time during their 8 h morning shift on direct patient care, (19.4%) ward/room activities (18%), documentation (14%), indirect patient care (12%) and professional communication (5%). Around 94 min of activities seem to be wasted and can be potentially detrimental to nurses’ overall productivity and threaten patient care quality. The standard number of hours that represents the best estimate of a general ward nurse regarding the optimal speed at which the staff nurse can provide care related activities was computed and proposed. (4) Conclusions: The findings obtained from time–motion studies can help in developing more efficient and productive nursing work for more optimal care of patients. © 2023 by the authors.
A critical analysis of mobility management related issues of wireless sensor networks in cyber physical systems
- Al-Muhtadi, Jalal, Qiang, Ma, Zeb, Khan, Chaudhry, Junaid, Imran, Muhammad
- Authors: Al-Muhtadi, Jalal , Qiang, Ma , Zeb, Khan , Chaudhry, Junaid , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 16363-16376
- Full Text:
- Reviewed:
- Description: Mobility management has been a long-standing issue in mobile wireless sensor networks and especially in the context of cyber physical systems its implications are immense. This paper presents a critical analysis of the current approaches to mobility management by evaluating them against a set of criteria which are essentially inherent characteristics of such systems on which these approaches are expected to provide acceptable performance. We summarize these characteristics by using a quadruple set of metrics. Additionally, using this set we classify the various approaches to mobility management that are discussed in this paper. Finally, the paper concludes by reviewing the main findings and providing suggestions that will be helpful to guide future research efforts in the area. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
- Authors: Al-Muhtadi, Jalal , Qiang, Ma , Zeb, Khan , Chaudhry, Junaid , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 16363-16376
- Full Text:
- Reviewed:
- Description: Mobility management has been a long-standing issue in mobile wireless sensor networks and especially in the context of cyber physical systems its implications are immense. This paper presents a critical analysis of the current approaches to mobility management by evaluating them against a set of criteria which are essentially inherent characteristics of such systems on which these approaches are expected to provide acceptable performance. We summarize these characteristics by using a quadruple set of metrics. Additionally, using this set we classify the various approaches to mobility management that are discussed in this paper. Finally, the paper concludes by reviewing the main findings and providing suggestions that will be helpful to guide future research efforts in the area. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**