Data-driven multi-resolution probabilistic energy and reserve bidding of wind power
- Hosseini, Seyyed, Toubeau, Jean-Francois, De Greve, Zacharie, Wang, Yi, Amjady, Nima, Vallee, Francois
- Authors: Hosseini, Seyyed , Toubeau, Jean-Francois , De Greve, Zacharie , Wang, Yi , Amjady, Nima , Vallee, Francois
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE transactions on power systems Vol. 38, no. 1 (2023), p. 1-1
- Full Text: false
- Reviewed:
- Description: The current wind farm control schemes qualify wind power producers (WPPs) to provide balancing services in complement to energy in modern electricity markets. In this context, WPPs are responsible for real-time deviations in both energy and reserve market floors, which are settled at different time scales. WPPs should adjust their output to cope with fast wind variations, which are critical in the balancing stage. In this paper, we devise a reliable high-temporal-resolution day-ahead bidding framework for WPPs considering the ultra-short-term wind stochasticity. To that end, the model for the bidding strategy is enriched with a probabilistic constraint controlling the confidence level on reserve bids to enhance the reliability of the offered capacity. Additionally, an original Auxiliary Classifier Wasserstein Generative Adversarial Network (ACWGAN) is proposed to generate high-temporal-resolution wind speed scenarios to be embedded into the bidding framework. The numerical results firstly confirm the superiority of the proposed ACWGAN over the other GAN-based alternatives. Then, the effectiveness of the proposed data-driven method over its single-resolution counterpart and other scenario representation methods is verified regarding the minimization of the negative impact of wind variability on WPPs' profit and reliability of offered reserve bids.
Data-efficient graph learning meets ethical challenges
- Authors: Tang, Tao
- Date: 2023
- Type: Text , Conference paper
- Relation: 16th ACM International Conference on Web Search and Data Mining, WSDM 2023, Singapore, 27 February to 3 March 2023, WSDM 2023 - Proceedings of the 16th ACM International Conference on Web Search and Data Mining p. 1218-1219
- Full Text: false
- Reviewed:
- Description: Recommender systems have achieved great success in our daily life. In recent years, the ethical concerns of AI systems have gained lots of attention. At the same time, graph learning techniques are powerful in modelling the complex relations among users and items under recommender system applications. These graph learning- based methods are data hungry, which brought a significant data efficiency challenge. In this proposal, I introduce my PhD research from three aspects: 1) Efficient privacy-preserving recommendation for imbalanced data. 2) Efficient recommendation model training for Insufficient samples. 3) Explainability in the social recommendation. Challenges and solutions of the above research problems have been proposed in this proposal. © 2023 Owner/Author.
Dating in the dark : vulnerable narcissism predicts inauthentic self-presentation in online dating
- Willis, Megan, Oliver, Eliza, March, Evita
- Authors: Willis, Megan , Oliver, Eliza , March, Evita
- Date: 2023
- Type: Text , Journal article
- Relation: Telematics and Informatics Vol. 81, no. (2023), p.
- Full Text: false
- Reviewed:
- Description: The current study investigated whether Dark Triad traits (vulnerable and grandiose narcissism, primary and secondary psychopathy, and Machiavellianism views and tactics) predicted inauthentic self-presentation whilst dating online, and whether those who reported engaging in antisocial dating behaviours were higher on Dark Triad traits, and more likely to self-present inauthentically in online dating. Online daters (N = 313) were recruited via Prolific and completed measures to assess Dark Triad traits, inauthenticity, and antisocial dating behaviours (i.e., ghosting and breadcrumbing). Vulnerable narcissism was a significant predictor of online dating inauthentic self-presentation. No other Dark Triad traits emerged as significant predictors. Online dating inauthentic self-presentation was significantly higher for those who had breadcrumbed someone. Those who had ghosted someone had significantly greater vulnerable narcissism and secondary psychopathy, and those who had breadcrumbed someone had significantly greater vulnerable narcissism and Machiavellianism views than those who had not. As previous research has demonstrated that individuals high on vulnerable narcissism are more likely to perpetrate intimate partner violence, online daters should consider evidence of inauthenticity to be ‘red flags’ for potential harm as interactions continue. Especially given the current study demonstrated those who had previously ghosted and breadcrumbed were higher on vulnerable narcissism. © 2023 Elsevier Ltd
Decentralized content sharing in mobile ad-hoc networks : a survey
- Kaisar, Shahriar, Kamruzzaman, Joarder, Karmakar, Gour, Rashid, Md Mamunur
- Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour , Rashid, Md Mamunur
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Digital Communications and Networks Vol. 9, no. 6 (2023), p. 1363-1398
- Full Text:
- Reviewed:
- Description: The evolution of smart mobile devices has significantly impacted the way we generate and share contents and introduced a huge volume of Internet traffic. To address this issue and take advantage of the short-range communication capabilities of smart mobile devices, the decentralized content sharing approach has emerged as a suitable and promising alternative. Decentralized content sharing uses a peer-to-peer network among co-located smart mobile device users to fulfil content requests. Several articles have been published to date to address its different aspects including group management, interest extraction, message forwarding, participation incentive, and content replication. This survey paper summarizes and critically analyzes recent advancements in decentralized content sharing and highlights potential research issues that need further consideration. © 2022 Chongqing University of Posts and Telecommunications
- Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour , Rashid, Md Mamunur
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Digital Communications and Networks Vol. 9, no. 6 (2023), p. 1363-1398
- Full Text:
- Reviewed:
- Description: The evolution of smart mobile devices has significantly impacted the way we generate and share contents and introduced a huge volume of Internet traffic. To address this issue and take advantage of the short-range communication capabilities of smart mobile devices, the decentralized content sharing approach has emerged as a suitable and promising alternative. Decentralized content sharing uses a peer-to-peer network among co-located smart mobile device users to fulfil content requests. Several articles have been published to date to address its different aspects including group management, interest extraction, message forwarding, participation incentive, and content replication. This survey paper summarizes and critically analyzes recent advancements in decentralized content sharing and highlights potential research issues that need further consideration. © 2022 Chongqing University of Posts and Telecommunications
Decoding employee ambidexterity : understanding drivers, constraints, and performance implications for thriving in the evolving work landscapes - a scoping review
- Joseph, Jane, Firmin, Sally, Oseni, Taiwo, Stranieri, Andrew
- Authors: Joseph, Jane , Firmin, Sally , Oseni, Taiwo , Stranieri, Andrew
- Date: 2023
- Type: Text , Journal article
- Relation: Heliyon Vol. 9, no. 12 (2023), p.
- Full Text:
- Reviewed:
- Description: Employee ambidexterity (EA) is becoming increasingly recognised as a significant factor in enhancing individual and organisational performance across diverse industries. Ambidexterity refers to the capacity to exploit and explore organisational resources simultaneously. Scholars from diverse industry sectors have been motivated to delve deeper into the topic of EA due to its growing popularity. The objective of conducting a scoping review was to scrutinise the existing literature and identify the key drivers and constraints that impact EA to thrive in the changing work landscape. The insights gained from this review can assist decision-makers in formulating effective strategies to cultivate the ambidexterity skills of their workforce and achieve desirable outcomes. This review adheres to the PRISMA-ScR protocol. Articles were obtained from databases including Scopus, Web of Science, and EBSCOhost (Academic Search Complete, Business Source Complete). The body of literature concerning EA is in its nascent stage. 23 articles assessing EA's performance outcomes were identified using targeted search terms and thorough screening. After conducting a thorough thematic analysis using the iterative categorisation (IC) technique, tailored for scoping a review, we successfully identified twenty-nine factors contributing to the enhancement of EA, meticulously organised into five distinct categories: organisational factors, social connectedness, employee behaviour, employee personality, and work environment related factors. Similarly, we discovered four factors that impede EA: functional tenure, team identification, bounded discretion, and conscientiousness. Our findings underscore the profound impact of employee ambidexterity on distinct types of performance. Among the sixteen types of performance reported to be enhanced by EA, ten are linked to individual performance, while six are tied to organisational performance. Notably, our analysis revealed that nearly all studies have relied on cross-sectional research methods except for one. However, we advocate for the exploration of longitudinal studies as they hold the promise of offering a more comprehensive understanding of EA. The paper presents valuable insights into how to cultivate ambidextrous capabilities in the workforce for unparalleled success in today's rapidly evolving work environment. Additionally, it identifies several intriguing avenues for future research that could further elucidate and bridge existing knowledge gaps. © 2023
- Authors: Joseph, Jane , Firmin, Sally , Oseni, Taiwo , Stranieri, Andrew
- Date: 2023
- Type: Text , Journal article
- Relation: Heliyon Vol. 9, no. 12 (2023), p.
- Full Text:
- Reviewed:
- Description: Employee ambidexterity (EA) is becoming increasingly recognised as a significant factor in enhancing individual and organisational performance across diverse industries. Ambidexterity refers to the capacity to exploit and explore organisational resources simultaneously. Scholars from diverse industry sectors have been motivated to delve deeper into the topic of EA due to its growing popularity. The objective of conducting a scoping review was to scrutinise the existing literature and identify the key drivers and constraints that impact EA to thrive in the changing work landscape. The insights gained from this review can assist decision-makers in formulating effective strategies to cultivate the ambidexterity skills of their workforce and achieve desirable outcomes. This review adheres to the PRISMA-ScR protocol. Articles were obtained from databases including Scopus, Web of Science, and EBSCOhost (Academic Search Complete, Business Source Complete). The body of literature concerning EA is in its nascent stage. 23 articles assessing EA's performance outcomes were identified using targeted search terms and thorough screening. After conducting a thorough thematic analysis using the iterative categorisation (IC) technique, tailored for scoping a review, we successfully identified twenty-nine factors contributing to the enhancement of EA, meticulously organised into five distinct categories: organisational factors, social connectedness, employee behaviour, employee personality, and work environment related factors. Similarly, we discovered four factors that impede EA: functional tenure, team identification, bounded discretion, and conscientiousness. Our findings underscore the profound impact of employee ambidexterity on distinct types of performance. Among the sixteen types of performance reported to be enhanced by EA, ten are linked to individual performance, while six are tied to organisational performance. Notably, our analysis revealed that nearly all studies have relied on cross-sectional research methods except for one. However, we advocate for the exploration of longitudinal studies as they hold the promise of offering a more comprehensive understanding of EA. The paper presents valuable insights into how to cultivate ambidextrous capabilities in the workforce for unparalleled success in today's rapidly evolving work environment. Additionally, it identifies several intriguing avenues for future research that could further elucidate and bridge existing knowledge gaps. © 2023
Deep learning : survey of environmental and camera impacts on internet of things images
- Kaur, Roopdeep, Karmakar, Gour, Xia, Feng, Imran, Muhammad
- Authors: Kaur, Roopdeep , Karmakar, Gour , Xia, Feng , Imran, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Artificial Intelligence Review Vol. 56, no. 9 (2023), p. 9605-9638
- Full Text:
- Reviewed:
- Description: Internet of Things (IoT) images are captivating growing attention because of their wide range of applications which requires visual analysis to drive automation. However, IoT images are predominantly captured from outdoor environments and thus are inherently impacted by the camera and environmental parameters which can adversely affect corresponding applications. Deep Learning (DL) has been widely adopted in the field of image processing and computer vision and can reduce the impact of these parameters on IoT images. Albeit, there are many DL-based techniques available in the current literature for analyzing and reducing the environmental and camera impacts on IoT images. However, to the best of our knowledge, no survey paper presents state-of-the-art DL-based approaches for this purpose. Motivated by this, for the first time, we present a Systematic Literature Review (SLR) of existing DL techniques available for analyzing and reducing environmental and camera lens impacts on IoT images. As part of this SLR, firstly, we reiterate and highlight the significance of IoT images in their respective applications. Secondly, we describe the DL techniques employed for assessing the environmental and camera lens distortion impacts on IoT images. Thirdly, we illustrate how DL can be effective in reducing the impact of environmental and camera lens distortion in IoT images. Finally, along with the critical reflection on the advantages and limitations of the techniques, we also present ways to address the research challenges of existing techniques and identify some further researches to advance the relevant research areas. © 2023, The Author(s).
- Authors: Kaur, Roopdeep , Karmakar, Gour , Xia, Feng , Imran, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Artificial Intelligence Review Vol. 56, no. 9 (2023), p. 9605-9638
- Full Text:
- Reviewed:
- Description: Internet of Things (IoT) images are captivating growing attention because of their wide range of applications which requires visual analysis to drive automation. However, IoT images are predominantly captured from outdoor environments and thus are inherently impacted by the camera and environmental parameters which can adversely affect corresponding applications. Deep Learning (DL) has been widely adopted in the field of image processing and computer vision and can reduce the impact of these parameters on IoT images. Albeit, there are many DL-based techniques available in the current literature for analyzing and reducing the environmental and camera impacts on IoT images. However, to the best of our knowledge, no survey paper presents state-of-the-art DL-based approaches for this purpose. Motivated by this, for the first time, we present a Systematic Literature Review (SLR) of existing DL techniques available for analyzing and reducing environmental and camera lens impacts on IoT images. As part of this SLR, firstly, we reiterate and highlight the significance of IoT images in their respective applications. Secondly, we describe the DL techniques employed for assessing the environmental and camera lens distortion impacts on IoT images. Thirdly, we illustrate how DL can be effective in reducing the impact of environmental and camera lens distortion in IoT images. Finally, along with the critical reflection on the advantages and limitations of the techniques, we also present ways to address the research challenges of existing techniques and identify some further researches to advance the relevant research areas. © 2023, The Author(s).
Deep learning and federated learning for screening COVID-19 : a review
- Mondal, M., Bharati, Subrato, Podder, Prajoy, Kamruzzaman, Joarder
- Authors: Mondal, M. , Bharati, Subrato , Podder, Prajoy , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article , Review
- Relation: BioMedInformatics Vol. 3, no. 3 (2023), p. 691-713
- Full Text:
- Reviewed:
- Description: Since December 2019, a novel coronavirus disease (COVID-19) has infected millions of individuals. This paper conducts a thorough study of the use of deep learning (DL) and federated learning (FL) approaches to COVID-19 screening. To begin, an evaluation of research articles published between 1 January 2020 and 28 June 2023 is presented, considering the preferred reporting items of systematic reviews and meta-analysis (PRISMA) guidelines. The review compares various datasets on medical imaging, including X-ray, computed tomography (CT) scans, and ultrasound images, in terms of the number of images, COVID-19 samples, and classes in the datasets. Following that, a description of existing DL algorithms applied to various datasets is offered. Additionally, a summary of recent work on FL for COVID-19 screening is provided. Efforts to improve the quality of FL models are comprehensively reviewed and objectively evaluated. © 2023 by the authors.
- Authors: Mondal, M. , Bharati, Subrato , Podder, Prajoy , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article , Review
- Relation: BioMedInformatics Vol. 3, no. 3 (2023), p. 691-713
- Full Text:
- Reviewed:
- Description: Since December 2019, a novel coronavirus disease (COVID-19) has infected millions of individuals. This paper conducts a thorough study of the use of deep learning (DL) and federated learning (FL) approaches to COVID-19 screening. To begin, an evaluation of research articles published between 1 January 2020 and 28 June 2023 is presented, considering the preferred reporting items of systematic reviews and meta-analysis (PRISMA) guidelines. The review compares various datasets on medical imaging, including X-ray, computed tomography (CT) scans, and ultrasound images, in terms of the number of images, COVID-19 samples, and classes in the datasets. Following that, a description of existing DL algorithms applied to various datasets is offered. Additionally, a summary of recent work on FL for COVID-19 screening is provided. Efforts to improve the quality of FL models are comprehensively reviewed and objectively evaluated. © 2023 by the authors.
Deep learning-based digital image forgery detection using transfer learning
- Qazi, Emad, Zia, Tanveer, Imran, Muhammad, Faheem, Muhammad
- Authors: Qazi, Emad , Zia, Tanveer , Imran, Muhammad , Faheem, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Intelligent Automation and Soft Computing Vol. 38, no. 3 (2023), p. 225-240
- Full Text:
- Reviewed:
- Description: Deep learning is considered one of the most efficient and reliable methods through which the legitimacy of a digital image can be verified. In the current cyber world where deepfakes have shaken the global community, confirming the legitimacy of a digital image is of great importance. With the advancements made in deep learning techniques, now we can efficiently train and develop state-of-the-art digital image forensic models. The most traditional and widely used method by researchers is convolution neural networks (CNN) for verification of image authenticity but it consumes a considerable number of resources and requires a large dataset for training. Therefore, in this study, a transfer learning based deep learning technique for image forgery detection is proposed. The proposed methodology consists of three modules namely; preprocessing module, convolutional module, and the classification module. By using our proposed technique, the training time is drastically reduced by utilizing the pre-trained weights. The performance of the proposed technique is evaluated by using benchmark datasets, i.e., BOW and BOSSBase that detect five forensic types which include JPEG compression, contrast enhancement (CE), median filtering (MF), additive Gaussian noise, and resampling. We evaluated the performance of our proposed technique by conducting various experiments and case scenarios and achieved an accuracy of 99.92%. The results show the superiority of the proposed system. © 2023, Tech Science Press. All rights reserved.
- Authors: Qazi, Emad , Zia, Tanveer , Imran, Muhammad , Faheem, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Intelligent Automation and Soft Computing Vol. 38, no. 3 (2023), p. 225-240
- Full Text:
- Reviewed:
- Description: Deep learning is considered one of the most efficient and reliable methods through which the legitimacy of a digital image can be verified. In the current cyber world where deepfakes have shaken the global community, confirming the legitimacy of a digital image is of great importance. With the advancements made in deep learning techniques, now we can efficiently train and develop state-of-the-art digital image forensic models. The most traditional and widely used method by researchers is convolution neural networks (CNN) for verification of image authenticity but it consumes a considerable number of resources and requires a large dataset for training. Therefore, in this study, a transfer learning based deep learning technique for image forgery detection is proposed. The proposed methodology consists of three modules namely; preprocessing module, convolutional module, and the classification module. By using our proposed technique, the training time is drastically reduced by utilizing the pre-trained weights. The performance of the proposed technique is evaluated by using benchmark datasets, i.e., BOW and BOSSBase that detect five forensic types which include JPEG compression, contrast enhancement (CE), median filtering (MF), additive Gaussian noise, and resampling. We evaluated the performance of our proposed technique by conducting various experiments and case scenarios and achieved an accuracy of 99.92%. The results show the superiority of the proposed system. © 2023, Tech Science Press. All rights reserved.
Deep outdated fact detection in knowledge graphs
- Tu, Huiling, Yu, Shuo, Saikrishna, Vidya, Xia, Feng, Verspoor, Karin
- Authors: Tu, Huiling , Yu, Shuo , Saikrishna, Vidya , Xia, Feng , Verspoor, Karin
- Date: 2023
- Type: Text , Conference paper
- Relation: 23rd IEEE International Conference on Data Mining Workshops, ICDMW 2023, Shanghai, China, 1-4 December 2023, 23rd IEEE International Conference on Data Mining Workshops Proceedings p. 1443-1452
- Full Text:
- Reviewed:
- Description: Knowledge graphs (KGs) have garnered significant attention for their vast potential across diverse domains. However, the issue of outdated facts poses a challenge to KGs, affecting their overall quality as real-world information evolves. Existing solutions for outdated fact detection often rely on manual recognition. In response, this paper presents DEAN (Deep outdatEd fAct detectioN), a novel deep learning-based framework designed to identify outdated facts within KGs. DEAN distinguishes itself by capturing implicit structural information among facts through comprehensive modeling of both entities and relations. To effectively uncover latent out-of-date information, DEAN employs a contrastive approach based on a pre-defined Relations-to-Nodes (R2N) graph, weighted by the number of entities. Experimental results demonstrate the effectiveness and superiority of DEAN over state-of-the-art baseline methods. © 2023 IEEE.
- Authors: Tu, Huiling , Yu, Shuo , Saikrishna, Vidya , Xia, Feng , Verspoor, Karin
- Date: 2023
- Type: Text , Conference paper
- Relation: 23rd IEEE International Conference on Data Mining Workshops, ICDMW 2023, Shanghai, China, 1-4 December 2023, 23rd IEEE International Conference on Data Mining Workshops Proceedings p. 1443-1452
- Full Text:
- Reviewed:
- Description: Knowledge graphs (KGs) have garnered significant attention for their vast potential across diverse domains. However, the issue of outdated facts poses a challenge to KGs, affecting their overall quality as real-world information evolves. Existing solutions for outdated fact detection often rely on manual recognition. In response, this paper presents DEAN (Deep outdatEd fAct detectioN), a novel deep learning-based framework designed to identify outdated facts within KGs. DEAN distinguishes itself by capturing implicit structural information among facts through comprehensive modeling of both entities and relations. To effectively uncover latent out-of-date information, DEAN employs a contrastive approach based on a pre-defined Relations-to-Nodes (R2N) graph, weighted by the number of entities. Experimental results demonstrate the effectiveness and superiority of DEAN over state-of-the-art baseline methods. © 2023 IEEE.
Defending SDN against packet injection attacks using deep learning
- Phu, Anh, Li, Bo, Ullah, Faheem, Ul Huque, Tanvir, Naha, Ranesh, Babar, Muhammad, Nguyen, Hung
- Authors: Phu, Anh , Li, Bo , Ullah, Faheem , Ul Huque, Tanvir , Naha, Ranesh , Babar, Muhammad , Nguyen, Hung
- Date: 2023
- Type: Text , Journal article
- Relation: Computer Networks Vol. 234, no. (2023), p.
- Full Text:
- Reviewed:
- Description: The (logically) centralized architecture of software-defined networks makes them an easy target for packet injection attacks. In these attacks, the attacker injects malicious packets into the SDN network to affect the services and performance of the SDN controller and overflows the capacity of the SDN switches. Such attacks have been shown to ultimately stop the network functioning in real-time, leading to network breakdowns. There have been significant works on detecting and defending against similar DoS attacks in non-SDN networks, but detection and protection techniques for SDN against packet injection attacks are still in their infancy. Furthermore, many of the proposed solutions have been shown to be easily bypassed by simple modifications to the attacking packets or by altering the attacking profile. In this paper, we develop novel Graph Convolutional Neural Network models and algorithms for grouping network nodes/users into security classes by learning from network data. We start with two simple classes — nodes that engage in suspicious packet injection attacks and nodes that are not. From these classes, we then partition the network into separate segments with different security policies using distributed Ryu controllers in an SDN network. We show in experiments on an emulated SDN that our detection solution outperforms alternative approaches with above 99% detection accuracy for various types (both old and new) of injection attacks. More importantly, our mitigation solution maintains continuous functions of non-compromised nodes while isolating compromised/suspicious nodes in real-time. All code and data are publicly available for the reproducibility of our results. © 2023 The Author(s)
- Authors: Phu, Anh , Li, Bo , Ullah, Faheem , Ul Huque, Tanvir , Naha, Ranesh , Babar, Muhammad , Nguyen, Hung
- Date: 2023
- Type: Text , Journal article
- Relation: Computer Networks Vol. 234, no. (2023), p.
- Full Text:
- Reviewed:
- Description: The (logically) centralized architecture of software-defined networks makes them an easy target for packet injection attacks. In these attacks, the attacker injects malicious packets into the SDN network to affect the services and performance of the SDN controller and overflows the capacity of the SDN switches. Such attacks have been shown to ultimately stop the network functioning in real-time, leading to network breakdowns. There have been significant works on detecting and defending against similar DoS attacks in non-SDN networks, but detection and protection techniques for SDN against packet injection attacks are still in their infancy. Furthermore, many of the proposed solutions have been shown to be easily bypassed by simple modifications to the attacking packets or by altering the attacking profile. In this paper, we develop novel Graph Convolutional Neural Network models and algorithms for grouping network nodes/users into security classes by learning from network data. We start with two simple classes — nodes that engage in suspicious packet injection attacks and nodes that are not. From these classes, we then partition the network into separate segments with different security policies using distributed Ryu controllers in an SDN network. We show in experiments on an emulated SDN that our detection solution outperforms alternative approaches with above 99% detection accuracy for various types (both old and new) of injection attacks. More importantly, our mitigation solution maintains continuous functions of non-compromised nodes while isolating compromised/suspicious nodes in real-time. All code and data are publicly available for the reproducibility of our results. © 2023 The Author(s)
Depth-based sampling and steering constraints for memoryless local planners
- Nguyen, Binh, Nguyen, Linh, Choudhury, Tanveer, Keogh, Kathleen, Murshed, Manzur
- Authors: Nguyen, Binh , Nguyen, Linh , Choudhury, Tanveer , Keogh, Kathleen , Murshed, Manzur
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Intelligent and Robotic Systems: Theory and Applications Vol. 109, no. 3 (2023), p.
- Full Text:
- Reviewed:
- Description: By utilizing only depth information, the paper introduces a novel two-stage planning approach that enhances computational efficiency and planning performances for memoryless local planners. First, a depth-based sampling technique is proposed to identify and eliminate a specific type of in-collision trajectories among sampled candidates. Specifically, all trajectories that have obscured endpoints are found through querying the depth values and will then be excluded from the sampled set, which can significantly reduce the computational workload required in collision checking. Subsequently, we apply a tailored local planning algorithm that employs a direction cost function and a depth-based steering mechanism to prevent the robot from being trapped in local minima. Our planning algorithm is theoretically proven to be complete in convex obstacle scenarios. To validate the effectiveness of our DEpth-based both Sampling and Steering (DESS) approaches, we conducted experiments in simulated environments where a quadrotor flew through cluttered regions with multiple various-sized obstacles. The experimental results show that DESS significantly reduces computation time in local planning compared to the uniform sampling method, resulting in the planned trajectory with a lower minimized cost. More importantly, our success rates for navigation to different destinations in testing scenarios are improved considerably compared to the fixed-yawing approach. © 2023, The Author(s).
- Authors: Nguyen, Binh , Nguyen, Linh , Choudhury, Tanveer , Keogh, Kathleen , Murshed, Manzur
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Intelligent and Robotic Systems: Theory and Applications Vol. 109, no. 3 (2023), p.
- Full Text:
- Reviewed:
- Description: By utilizing only depth information, the paper introduces a novel two-stage planning approach that enhances computational efficiency and planning performances for memoryless local planners. First, a depth-based sampling technique is proposed to identify and eliminate a specific type of in-collision trajectories among sampled candidates. Specifically, all trajectories that have obscured endpoints are found through querying the depth values and will then be excluded from the sampled set, which can significantly reduce the computational workload required in collision checking. Subsequently, we apply a tailored local planning algorithm that employs a direction cost function and a depth-based steering mechanism to prevent the robot from being trapped in local minima. Our planning algorithm is theoretically proven to be complete in convex obstacle scenarios. To validate the effectiveness of our DEpth-based both Sampling and Steering (DESS) approaches, we conducted experiments in simulated environments where a quadrotor flew through cluttered regions with multiple various-sized obstacles. The experimental results show that DESS significantly reduces computation time in local planning compared to the uniform sampling method, resulting in the planned trajectory with a lower minimized cost. More importantly, our success rates for navigation to different destinations in testing scenarios are improved considerably compared to the fixed-yawing approach. © 2023, The Author(s).
Design of energy storage for frequency stability in low-inertia power grid
- Akram, Umer, Mithulananthan, N, Shah, Rakibuzzaman, Alzahrani, Saeed
- Authors: Akram, Umer , Mithulananthan, N , Shah, Rakibuzzaman , Alzahrani, Saeed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Systems Journal Vol. 17, no. 3 (2023), p. 4763-4774
- Full Text: false
- Reviewed:
- Description: Short-term frequency instability is one of the major concerns in power systems with high percentage of converter-interfaced renewable energy sources. Energy storage system (ESS) has proven to be a viable solution for the problem of short-term frequency instability by fast frequency response (FFR). However, the appropriate location, size, and operating strategy of ESS are the main challenges for FFR. Power injection at some buses in large grids may lead to angular separation and instability. In addition, oversizing ESS could lead to huge investments without appropriate returns and under sizing may jeopardizes grid stability. Capacity estimation of ESS for FFR considering the suitable location and overall deployment strategies are missing in the current literature for large power grids. Hence, this research proposes a technique to place and size ESS for better FFR in power grids. The proposed technique consists of two steps. In the first step, a methodology based on frequency dynamic signature (FDS) is developed to identify the most suitable location. In the second step, the required capacity of the ESS is estimated based on a step reduction iterative algorithm (SRIA). SRIA and FDS consider the complete dynamics of power system components that affect the frequency dynamics of the system. The proposed methodology is thoroughly verified for various operating conditions in IEEE 39-bus using DIgSILENT PowerFactory. © 2007-2012 IEEE.
Detection and explanation of anomalies in healthcare data
- Samariya, Durgesh, Ma, Jiangang, Aryal, Sunil, Zhao, Xiaohui
- Authors: Samariya, Durgesh , Ma, Jiangang , Aryal, Sunil , Zhao, Xiaohui
- Date: 2023
- Type: Text , Journal article
- Relation: Health Information Science and Systems Vol. 11, no. 1 (2023), p. 20-20
- Full Text: false
- Reviewed:
- Description: The growth of databases in the healthcare domain opens multiple doors for machine learning and artificial intelligence technology. Many medical devices are available in the medical field however, medical errors remain a severe challenge. Different algorithms are developed to identify and solve medical errors, such as detecting anomalous readings, anomalous health conditions of a patient, etc. However, they fail to answer why those entries are considered an anomaly. This research gap leads to an outlying aspect mining problem. The problem of outlying aspect mining aims to discover the set of features (a.k.a subspace) in which the given data point is dramatically different than others. In this paper, we present a framework that detects anomalies in healthcare data and then provides an explanation of anomalies. This paper aims to effectively and efficiently detect anomalies and explain why they are considered anomalies by detecting outlying aspects. First, we re-introduced four anomaly detection techniques and outlying aspect mining algorithms. Then, we evaluate the performance of anomaly detection techniques and choose the best anomaly detection algorithm. Later, we detect the top k anomaly as a query and detect their outlying aspect. Lastly, we evaluate their performance on 16 real-world healthcare datasets. The experimental results show that the latest isolation-based outlying aspect mining measure, SiNNE, has outstanding performance on this task and has promising results.
Determination of munsell soil colour using smartphones
- Nodi, Sadia, Paul, Manoranjan, Robinson, Nathan, Wang, Liang, Rehman, Sabih
- Authors: Nodi, Sadia , Paul, Manoranjan , Robinson, Nathan , Wang, Liang , Rehman, Sabih
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 6 (2023), p.
- Full Text:
- Reviewed:
- Description: Soil colour is one of the most important factors in agriculture for monitoring soil health and determining its properties. For this purpose, Munsell soil colour charts are widely used by archaeologists, scientists, and farmers. The process of determining soil colour from the chart is subjective and error-prone. In this study, we used popular smartphones to capture soil colours from images in the Munsell Soil Colour Book (MSCB) to determine the colour digitally. These captured soil colours are then compared with the true colour determined using a commonly used sensor (Nix Pro-2). We have observed that there are colour reading discrepancies between smartphone and Nix Pro-provided readings. To address this issue, we investigated different colour models and finally introduced a colour-intensity relationship between the images captured by Nix Pro and smartphones by exploring different distance functions. Thus, the aim of this study is to determine the Munsell soil colour accurately from the MSCB by adjusting the pixel intensity of the smartphone-captured images. Without any adjustment when the accuracy of individual Munsell soil colour determination is only (Formula presented.) for the top 5 predictions, the accuracy of the proposed method is (Formula presented.), which is significant. © 2023 by the authors.
- Authors: Nodi, Sadia , Paul, Manoranjan , Robinson, Nathan , Wang, Liang , Rehman, Sabih
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 6 (2023), p.
- Full Text:
- Reviewed:
- Description: Soil colour is one of the most important factors in agriculture for monitoring soil health and determining its properties. For this purpose, Munsell soil colour charts are widely used by archaeologists, scientists, and farmers. The process of determining soil colour from the chart is subjective and error-prone. In this study, we used popular smartphones to capture soil colours from images in the Munsell Soil Colour Book (MSCB) to determine the colour digitally. These captured soil colours are then compared with the true colour determined using a commonly used sensor (Nix Pro-2). We have observed that there are colour reading discrepancies between smartphone and Nix Pro-provided readings. To address this issue, we investigated different colour models and finally introduced a colour-intensity relationship between the images captured by Nix Pro and smartphones by exploring different distance functions. Thus, the aim of this study is to determine the Munsell soil colour accurately from the MSCB by adjusting the pixel intensity of the smartphone-captured images. Without any adjustment when the accuracy of individual Munsell soil colour determination is only (Formula presented.) for the top 5 predictions, the accuracy of the proposed method is (Formula presented.), which is significant. © 2023 by the authors.
Developing entrustable professional activities to enhance application of an aggression prevention protocol
- Maguire, Tessa, Willetts, Georgina, McKenna, Brian, Daffern, Michael, Garvey, Loretta
- Authors: Maguire, Tessa , Willetts, Georgina , McKenna, Brian , Daffern, Michael , Garvey, Loretta
- Date: 2023
- Type: Text , Journal article
- Relation: Nurse Education in Practice Vol. 73, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Aim: The research aim of this study was to seek feedback from prevention of aggression training experts about the suitability of Entrustable Professional Activities (EPAs) as an assessment tool for an Aggression Prevention Protocol. The protocol was designed to structure intervention to prevent aggression and reduce the use of restrictive practices following risk assessment using a validated instrument (the Dynamic Appraisal of Situational Aggression). Background: Preventing aggression and limiting the use of restrictive practices are key priorities for inpatient mental health services. Assessing clinical activities using a competence framework has limitations, particularly when determining complex interventions. EPAs could provide a suitable method for assessing complex clinical activities like de-escalation and limit setting, which comprise some of the interventions in the Aggression Prevention Protocol. EPAs are new to forensic mental health nursing; therefore, feedback was sought regarding the utility of EPAs to assess aggression prevention interventions. Methods: Data were collected via focus groups including 11 aggression prevention experts from Australia and New Zealand. A thematic analysis, comparative analysis and a Strength, Weakness, Opportunity and Threats analysis was conducted. Results: Three themes were interpreted from the data: 1) Frameworks such as the APP are needed to work towards elimination of restrictive practices; 2) APP-EPAs afford an opportunity to set the standard for practice; and 3) ‘who watches the watchers’, were identified by the experts as well as areas to enhance EPAs prior to introduction into practice. Conclusions: EPAs address a practice-gap and offer a framework to assist movement towards elimination of restrictive practices, while prompting best-practice, self-reflection and practice improvement guidance. © 2023
- Authors: Maguire, Tessa , Willetts, Georgina , McKenna, Brian , Daffern, Michael , Garvey, Loretta
- Date: 2023
- Type: Text , Journal article
- Relation: Nurse Education in Practice Vol. 73, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Aim: The research aim of this study was to seek feedback from prevention of aggression training experts about the suitability of Entrustable Professional Activities (EPAs) as an assessment tool for an Aggression Prevention Protocol. The protocol was designed to structure intervention to prevent aggression and reduce the use of restrictive practices following risk assessment using a validated instrument (the Dynamic Appraisal of Situational Aggression). Background: Preventing aggression and limiting the use of restrictive practices are key priorities for inpatient mental health services. Assessing clinical activities using a competence framework has limitations, particularly when determining complex interventions. EPAs could provide a suitable method for assessing complex clinical activities like de-escalation and limit setting, which comprise some of the interventions in the Aggression Prevention Protocol. EPAs are new to forensic mental health nursing; therefore, feedback was sought regarding the utility of EPAs to assess aggression prevention interventions. Methods: Data were collected via focus groups including 11 aggression prevention experts from Australia and New Zealand. A thematic analysis, comparative analysis and a Strength, Weakness, Opportunity and Threats analysis was conducted. Results: Three themes were interpreted from the data: 1) Frameworks such as the APP are needed to work towards elimination of restrictive practices; 2) APP-EPAs afford an opportunity to set the standard for practice; and 3) ‘who watches the watchers’, were identified by the experts as well as areas to enhance EPAs prior to introduction into practice. Conclusions: EPAs address a practice-gap and offer a framework to assist movement towards elimination of restrictive practices, while prompting best-practice, self-reflection and practice improvement guidance. © 2023
Developing rights-based standards for children having tests, treatments, examinations and interventions: using a collaborative, multi-phased, multi-method and multi-stakeholder approach to build consensus
- Bray, Lucy, Carter, Bernie, Kiernan, Joann, Horowicz, Ed, Dixon, Katie, Ridley, James, Robinson, Carol, Simmons, Anna, Craske, Jennie, Sinha, Stephanie, Morton, Liza, Nafria, Begonya, Forsner, Maria, Rullander, Anna-Clara, Nilsson, Stefan, Darcy, Laura, Karlsson, Katarina, Hubbuck, Cath, Brenner, Maria, Spencer-Little, Sian, Evans, Kath, Rowland, Andrew, Hilliard, Carol, Preston, Jennifer, Leroy, Piet, Roland, Damian, Booth, Lisa, Davies, Jean, Saron, Holly, Peck, Blake
- Authors: Bray, Lucy , Carter, Bernie , Kiernan, Joann , Horowicz, Ed , Dixon, Katie , Ridley, James , Robinson, Carol , Simmons, Anna , Craske, Jennie , Sinha, Stephanie , Morton, Liza , Nafria, Begonya , Forsner, Maria , Rullander, Anna-Clara , Nilsson, Stefan , Darcy, Laura , Karlsson, Katarina , Hubbuck, Cath , Brenner, Maria , Spencer-Little, Sian , Evans, Kath , Rowland, Andrew , Hilliard, Carol , Preston, Jennifer , Leroy, Piet , Roland, Damian , Booth, Lisa , Davies, Jean , Saron, Holly , Peck, Blake
- Date: 2023
- Type: Text , Journal article
- Relation: European Journal of Pediatrics Vol. 182, no. 10 (2023), p. 4707-4721
- Full Text:
- Reviewed:
- Description: Children continue to experience harm when undergoing clinical procedures despite increased evidence of the need to improve the provision of child-centred care. The international ISupport collaboration aimed to develop standards to outline and explain good procedural practice and the rights of children within the context of a clinical procedure. The rights-based standards for children undergoing tests, treatments, investigations, examinations and interventions were developed using an iterative, multi-phased, multi-method and multi-stakeholder consensus building approach. This consensus approach used a range of online and face to face methods across three phases to ensure ongoing engagement with multiple stakeholders. The views and perspectives of 203 children and young people, 78 parents and 418 multi-disciplinary professionals gathered over a two year period (2020–2022) informed the development of international rights-based standards for the care of children having tests, treatments, examinations and interventions. The standards are the first to reach international multi-stakeholder consensus on definitions of supportive and restraining holds. Conclusion: This is the first study of its kind which outlines international rights-based procedural care standards from multi-stakeholder perspectives. The standards offer health professionals and educators clear evidence-based tools to support discussions and practice changes to challenge prevailing assumptions about holding or restraining children and instead encourage a focus on the interests and rights of the child. What is Known: • Children continue to experience short and long-term harm when undergoing clinical procedures despite increased evidence of the need to improve the provision of child-centred care. • Professionals report uncertainty and tensions in applying evidence-based practice to children’s procedural care. What is New: • This is the first study of its kind which has developed international rights-based procedural care standards from multi-stakeholder perspectives. • The standards are the first to reach international multi-stakeholder consensus on definitions of supportive and restraining holds. © 2023, The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Blake Peck” is provided in this record**
- Authors: Bray, Lucy , Carter, Bernie , Kiernan, Joann , Horowicz, Ed , Dixon, Katie , Ridley, James , Robinson, Carol , Simmons, Anna , Craske, Jennie , Sinha, Stephanie , Morton, Liza , Nafria, Begonya , Forsner, Maria , Rullander, Anna-Clara , Nilsson, Stefan , Darcy, Laura , Karlsson, Katarina , Hubbuck, Cath , Brenner, Maria , Spencer-Little, Sian , Evans, Kath , Rowland, Andrew , Hilliard, Carol , Preston, Jennifer , Leroy, Piet , Roland, Damian , Booth, Lisa , Davies, Jean , Saron, Holly , Peck, Blake
- Date: 2023
- Type: Text , Journal article
- Relation: European Journal of Pediatrics Vol. 182, no. 10 (2023), p. 4707-4721
- Full Text:
- Reviewed:
- Description: Children continue to experience harm when undergoing clinical procedures despite increased evidence of the need to improve the provision of child-centred care. The international ISupport collaboration aimed to develop standards to outline and explain good procedural practice and the rights of children within the context of a clinical procedure. The rights-based standards for children undergoing tests, treatments, investigations, examinations and interventions were developed using an iterative, multi-phased, multi-method and multi-stakeholder consensus building approach. This consensus approach used a range of online and face to face methods across three phases to ensure ongoing engagement with multiple stakeholders. The views and perspectives of 203 children and young people, 78 parents and 418 multi-disciplinary professionals gathered over a two year period (2020–2022) informed the development of international rights-based standards for the care of children having tests, treatments, examinations and interventions. The standards are the first to reach international multi-stakeholder consensus on definitions of supportive and restraining holds. Conclusion: This is the first study of its kind which outlines international rights-based procedural care standards from multi-stakeholder perspectives. The standards offer health professionals and educators clear evidence-based tools to support discussions and practice changes to challenge prevailing assumptions about holding or restraining children and instead encourage a focus on the interests and rights of the child. What is Known: • Children continue to experience short and long-term harm when undergoing clinical procedures despite increased evidence of the need to improve the provision of child-centred care. • Professionals report uncertainty and tensions in applying evidence-based practice to children’s procedural care. What is New: • This is the first study of its kind which has developed international rights-based procedural care standards from multi-stakeholder perspectives. • The standards are the first to reach international multi-stakeholder consensus on definitions of supportive and restraining holds. © 2023, The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Blake Peck” is provided in this record**
Development and validation of the feminist social identity scale
- Poll, Alex, Critchley, Christine
- Authors: Poll, Alex , Critchley, Christine
- Date: 2023
- Type: Text , Journal article
- Relation: Current psychology Vol. 42, no. 15 (2023), p. 12614-12629
- Full Text: false
- Reviewed:
- Description: Feminist identity is a multidimensional construct, associated with significant physical and psychological outcomes. Despite this, it has previously been largely conceptualised and measured as unidimensional. To address this limitation, we developed a multidimensional measure of feminist identity using the framework of social identity theory. A total of 1493 respondents (81.8% women, 16.6% men, 1.5% other genders) aged between 18 and 75 years ( M= 31.55, SD =11.37) completed an online survey. Following Confirmatory Factor Analysis, expert evaluation ( N = 21), and testing of the model in a separate sample ( N = 504), the Feminist Social Identity Scale (FSIS) was created. The FSIS is comprised of 36-items which measure feminist identity across 12 subscales and has excellent internal consistency, test-retest reliability, and validity indices. Latent Class Analysis revealed that the FSIS successfully distinguishes between different levels of feminist identity. The FSIS will aid future researchers to examine feminist identity as a multidimensional construct, avoiding the limitations of single construct measures.
Development of a long-term climatology of tropical 1 cyclones and depressions for the South Pacific 2 Ocean basin
- Authors: Yeasmin, Alea
- Date: 2023
- Type: Text , Thesis , PhD
- Full Text:
- Description: Tropical cyclones (TCs) are one of the most destructive synoptic systems that can cause enormous loss of life and property damages in the South Pacific Island nations. The impact of tropical depressions (TDs, i.e., weaker systems that do not develop into TCs) can also be staggering in the region in terms of heavy flooding and landslides, but a lack of complete records (reliable data prior to 1950) often hinders research involving TD impacts. A methodology has been developed here to detect TDs in the ERA-5 (the fifth generation European Centre for Medium-Range Weather Forecasts-ECMWF atmospheric reanalysis of the global climate) and 20CR (the Twentieth Century Reanalysis) dataset using the Okubo–Weiss–Zeta parameter (OWZP) detection scheme. The new South Pacific Enhanced Archive for Tropical Cyclones dataset (SPEArTC), the Dvorak analysis of satellite-based cloud patterns over the South Pacific Ocean basin, rainfall dataset for various stations in the South Pacific and historical archives have been utilised to validate ERA5/20CR-derived TCs and TDs. Results indicate that the OWZP method shows substantial skill in capturing the realistic climatological distribution of TCs and TDs for the South Pacific Ocean in both reanalyses dataset. The 20CR-derived TCs and TDs resemble several key characteristics of the observational records, including spatial distribution of genesis locations and track shapes. This gives us confidence that the 20CR-derived long-term records of TCs and TDs can serve as an effective tool for examining historical changes in various characteristics of TCs and TDs, particularly in the context of anthropogenic climate change. Utilizing the reconstructed proxies of TCs and TDs, their climatic connections with the El Niño Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO), and the combined ENSO-IPO phases have been examined. Results show clear spatial shifts in TC activity between La Niña and El Niño phases with activity in the region 1400-1700E (1700-2200E) occurring during La Niña (El Niño) events. However, when IPO is considered synergistically with ENSO phases, we found that the combination of El Niño and the positive phase of IPO (+IPO) substantially enhances TC numbers (may be artifact influence) in both domains, noting the modulation between the two phases themselves. Similarly, La Niña and the negative phase of the IPO (-IPO) is found to enhance TC numbers in 1400-1700E. It is shown for the first time that the combined phases of El Niño and +IPO account for increased TC activity, as opposed to the combined phase of La Niña and -IPO, in the eastern sub-region. Similarly, the combined phase of La Niña and +IPO, as opposed to the combined phase of El Niño and -IPO, account for increased TC activity in the western sub-region. However, unlike TCs, the patterns of ENSO variability seem to be reversed for TDs. Changes in large-scale environmental conditions, such as environmental vertical wind shear, low-level cyclonic relative vorticity, mid-tropospheric relative humidity and sea surface temperature are linked to the various modes of variability patterns and their synergistic relationships. Results can have substantial implications, particularly on the predictability of TCs and TDs associated with the two important modes of natural variability in the South Pacific.
- Description: Doctor of Philosophy
- Authors: Yeasmin, Alea
- Date: 2023
- Type: Text , Thesis , PhD
- Full Text:
- Description: Tropical cyclones (TCs) are one of the most destructive synoptic systems that can cause enormous loss of life and property damages in the South Pacific Island nations. The impact of tropical depressions (TDs, i.e., weaker systems that do not develop into TCs) can also be staggering in the region in terms of heavy flooding and landslides, but a lack of complete records (reliable data prior to 1950) often hinders research involving TD impacts. A methodology has been developed here to detect TDs in the ERA-5 (the fifth generation European Centre for Medium-Range Weather Forecasts-ECMWF atmospheric reanalysis of the global climate) and 20CR (the Twentieth Century Reanalysis) dataset using the Okubo–Weiss–Zeta parameter (OWZP) detection scheme. The new South Pacific Enhanced Archive for Tropical Cyclones dataset (SPEArTC), the Dvorak analysis of satellite-based cloud patterns over the South Pacific Ocean basin, rainfall dataset for various stations in the South Pacific and historical archives have been utilised to validate ERA5/20CR-derived TCs and TDs. Results indicate that the OWZP method shows substantial skill in capturing the realistic climatological distribution of TCs and TDs for the South Pacific Ocean in both reanalyses dataset. The 20CR-derived TCs and TDs resemble several key characteristics of the observational records, including spatial distribution of genesis locations and track shapes. This gives us confidence that the 20CR-derived long-term records of TCs and TDs can serve as an effective tool for examining historical changes in various characteristics of TCs and TDs, particularly in the context of anthropogenic climate change. Utilizing the reconstructed proxies of TCs and TDs, their climatic connections with the El Niño Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO), and the combined ENSO-IPO phases have been examined. Results show clear spatial shifts in TC activity between La Niña and El Niño phases with activity in the region 1400-1700E (1700-2200E) occurring during La Niña (El Niño) events. However, when IPO is considered synergistically with ENSO phases, we found that the combination of El Niño and the positive phase of IPO (+IPO) substantially enhances TC numbers (may be artifact influence) in both domains, noting the modulation between the two phases themselves. Similarly, La Niña and the negative phase of the IPO (-IPO) is found to enhance TC numbers in 1400-1700E. It is shown for the first time that the combined phases of El Niño and +IPO account for increased TC activity, as opposed to the combined phase of La Niña and -IPO, in the eastern sub-region. Similarly, the combined phase of La Niña and +IPO, as opposed to the combined phase of El Niño and -IPO, account for increased TC activity in the western sub-region. However, unlike TCs, the patterns of ENSO variability seem to be reversed for TDs. Changes in large-scale environmental conditions, such as environmental vertical wind shear, low-level cyclonic relative vorticity, mid-tropospheric relative humidity and sea surface temperature are linked to the various modes of variability patterns and their synergistic relationships. Results can have substantial implications, particularly on the predictability of TCs and TDs associated with the two important modes of natural variability in the South Pacific.
- Description: Doctor of Philosophy
- Meaklim, Hailey, Rehm, Imogen, Junge, Moira, Monfries, Melissa, Kennedy, Gerard, Bucks, Romola, Meltzer, Lisa, Jackson, Melinda
- Authors: Meaklim, Hailey , Rehm, Imogen , Junge, Moira , Monfries, Melissa , Kennedy, Gerard , Bucks, Romola , Meltzer, Lisa , Jackson, Melinda
- Date: 2023
- Type: Text , Journal article
- Relation: Behavioral Sleep Medicine Vol. 21, no. 6 (2023), p. 787-801
- Full Text: false
- Reviewed:
- Description: Objectives: Despite the clear influence of poor sleep on mental health, sleep education has been neglected in psychology training programs. Here, we develop a novel behavioral sleep medicine (BSM) education workshop, the Sleep Psychology Workshop, designed for integration within graduate psychology programs. We also examined the potential efficacy and acceptability of the workshop to upskill trainee psychologists in sleep and insomnia management. Methods: The Sleep Psychology Workshop was developed using a modified Delphi Method. Eleven trainee psychologists completing their Master of Psychology degrees (90% female, 24.4 ± 1.6 years old) attended the workshop, delivered as three, two-hour lectures (total of six hours). Sleep knowledge, attitudes, and practice assessments were completed pre-and post-intervention using the GradPsyKAPS Questionnaire. A focus group and 6-month follow-up survey captured feedback and qualitative data. Results: Trainees’ sleep knowledge quiz scores (% correct) increased from 60% to 79% pre- to post-workshop (p =.002). Trainees’ self-efficacy to use common sleep-related assessment instruments and empirically supported interventions to manage sleep disturbances increased, along with their confidence to manage insomnia (all p < .02). Participant feedback was positive, with 91% of trainees rating the workshop as “excellent” and qualitative data highlighting trainees developing practical skills in BSM. Six months post-intervention, 100% of trainees endorsed routinely asking their clients about sleep, with 82% reporting improvements in their own sleep. Conclusions: The Sleep Psychology Workshop is a potentially effective and acceptable introductory BSM education program for trainee psychologists, ready for integration within the graduate psychology curriculum. © 2023 Taylor & Francis Group, LLC.
Development of a short form of the cardiac distress inventory
- Le Grande, Michael, Murphy, Barbara, Rogerson, Michelle, Ski, Chantal, Amerena, John, Smith, Julian, Hoover, Valerie, Alvarenga, Marlies, Higgins, Rosemary, Thompson, David, Jackson, Alun
- Authors: Le Grande, Michael , Murphy, Barbara , Rogerson, Michelle , Ski, Chantal , Amerena, John , Smith, Julian , Hoover, Valerie , Alvarenga, Marlies , Higgins, Rosemary , Thompson, David , Jackson, Alun
- Date: 2023
- Type: Text , Journal article
- Relation: BMC Cardiovascular Disorders Vol. 23, no. 1 (2023), p.
- Full Text:
- Reviewed:
- Description: Background: Cardiac distress may be viewed as a persistent negative emotional state that spans multiple psychosocial domains and challenges a patient’s capacity to cope with living with their heart condition. The Cardiac Distress Inventory (CDI) is a disease-specific clinical assessment tool that captures the complexity of this distress. In busy settings such as primary care, cardiac rehabilitation, and counselling services, however, there is a need to administer briefer tools to aid in identification and screening. The aim of the present study was to develop a short, valid screening version of the CDI. Methods: A total of 405 participants reporting an acute coronary event in the previous 12 months was recruited from three hospitals, through social media and by direct enrolment on the study website. Participants completed an online survey which included the full version of the CDI and general distress measures including the Kessler K6, Patient Health Questionnaire-4, and Emotion Thermometers. Relationship of the CDI with these instruments, Rasch analysis model fit and clinical expertise were all used to select items for the short form (CDI-SF). Construct validity and receiver operating characteristics in relation to the Kessler K6 were examined. Results: The final 12 item CDI-SF exhibited excellent internal consistency indicative of unidimensionality and good convergent and discriminant validity in comparison to clinical status measures, all indicative of good construct validity. Using the K6 validated cutoff of
- Authors: Le Grande, Michael , Murphy, Barbara , Rogerson, Michelle , Ski, Chantal , Amerena, John , Smith, Julian , Hoover, Valerie , Alvarenga, Marlies , Higgins, Rosemary , Thompson, David , Jackson, Alun
- Date: 2023
- Type: Text , Journal article
- Relation: BMC Cardiovascular Disorders Vol. 23, no. 1 (2023), p.
- Full Text:
- Reviewed:
- Description: Background: Cardiac distress may be viewed as a persistent negative emotional state that spans multiple psychosocial domains and challenges a patient’s capacity to cope with living with their heart condition. The Cardiac Distress Inventory (CDI) is a disease-specific clinical assessment tool that captures the complexity of this distress. In busy settings such as primary care, cardiac rehabilitation, and counselling services, however, there is a need to administer briefer tools to aid in identification and screening. The aim of the present study was to develop a short, valid screening version of the CDI. Methods: A total of 405 participants reporting an acute coronary event in the previous 12 months was recruited from three hospitals, through social media and by direct enrolment on the study website. Participants completed an online survey which included the full version of the CDI and general distress measures including the Kessler K6, Patient Health Questionnaire-4, and Emotion Thermometers. Relationship of the CDI with these instruments, Rasch analysis model fit and clinical expertise were all used to select items for the short form (CDI-SF). Construct validity and receiver operating characteristics in relation to the Kessler K6 were examined. Results: The final 12 item CDI-SF exhibited excellent internal consistency indicative of unidimensionality and good convergent and discriminant validity in comparison to clinical status measures, all indicative of good construct validity. Using the K6 validated cutoff of