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Cross disciplinary teaching : a pedagogical model to support teachers in the development and implementation of outdoor learning opportunities

- Neville, Ian, Petrass, Lauren, Ben, Francis

  • Authors: Neville, Ian , Petrass, Lauren , Ben, Francis
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Journal of Outdoor and Environmental Education Vol. 26, no. 1 (2023), p. 1-21
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  • Description: There is a growing body of empirical evidence documenting the positive effects associated with participation in environmental education and outdoor learning for students, teachers and the wider community. Despite this, there has been a substantial reduction in outdoor learning opportunities for school students, possibly due to the focus on evidenced-based outcomes, high-stakes standardised testing programs, and a lack of teacher knowledge, confidence and expertise in teaching and learning outdoors. Accordingly, this study presents an evidenced based model to support teaching practice. The model will assist teachers in the development and implementation of outdoor learning opportunities and offers applied examples that address curriculum outcomes. A comprehensive literature review methodology was implemented to identify peer-reviewed literature on teaching and learning outdoors and outdoor pedagogies. A thematic synthesis and constant comparative technique enabled development of themes, from which three themes emerged: the environment; the learner; and the educator, which inform the proposed model offered by the authors. The three interrelated components (the environment, the learner and the educator) require consideration for students to gain maximum benefit from outdoor learning experiences. The model, coupled with the applied examples, supports teachers to plan and facilitate immersive outdoor experiences that promote learning. © 2022, The Author(s).

Cross-sectional study of soil-transmitted helminthiases in black belt region of Alabama, USA

- Poole, Claudette, Barker, Troy, Bradbury, Richard, Capone, Drew, Chatham, Amy, Handali, Sukwan, Rodriguez, Eduardo, Qvarnstrom, Yvonne, Brown, Joe

  • Authors: Poole, Claudette , Barker, Troy , Bradbury, Richard , Capone, Drew , Chatham, Amy , Handali, Sukwan , Rodriguez, Eduardo , Qvarnstrom, Yvonne , Brown, Joe
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Emerging Infectious Diseases Vol. 29, no. 12 (2023), p. 2461-2470
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  • Description: We conducted a cross-sectional study to determine the prevalence of soil-transmitted helminthiases (STH) in areas of rural Alabama, USA, that have sanitation deficits. We enrolled 777 children; 704 submitted stool specimens and 227 a dried blood spot sample. We microscopically examined stool specimens from all 704 children by using Mini-FLOTAC for helminth eggs. We tested a subset by using molecular techniques: real-time PCR analysis for 5 STH species, TaqMan Array Cards for enteric helminths, and digital PCR for Necator americanus hookworm. We analyzed dried blood spots for Strongyloides stercoralis and Toxocara spp. roundworms by using serologic testing. Despite 12% of our cohort reporting living in homes that directly discharge untreated domestic wastewater, stool testing for STH was negative; however, 5% of dried blood spots were positive for Toxocara spp. roundworms. Survey data suggests substantial numbers of children in this region may be exposed to raw sewage, which is itself a major public health concern. © 2023 Centers for Disease Control and Prevention (CDC). All rights reserved.

Cultivating whole-heartedness in the academy during a time of COVID : insights from/within an inter-collegial friendship

- Green, Monica, McClam, Sherie

  • Authors: Green, Monica , McClam, Sherie
  • Date: 2023
  • Type: Text , Book chapter
  • Relation: Reflections on Valuing Wellbeing in Higher Education : Reforming Our Acts of Self-care Chapter 9 p. 111-124
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  • Description: This chapter explores how we, Sherie (American) and Monica (Australian), two feminist teacher educators and collaborators, used reflective dialogic exchanges to examine our academic lives during the COVID-19 pandemic in 2020. The underpinning personal and emotional layers of our wholehearted conversations sit within our robust inter-collegial friendship, which offers us critical support and reminders about the importance of self-care/compassion in our navigation of academic complexities and obligations. The chapter is framed by three of Brene Brown’s ‘wholehearted’ provocations or prompts that we used to explore our respective lived COVID-19 experiences within the broader milieu of contemporary academia. The chapter concludes with insights about the ways in which collegial friendships contribute to academic wellbeing and self-care. © 2023 selection and editorial matter, Narelle Lemon.

Cultural landscapes : human impacts on wetlands

- Mills, Keely, Jones, Matthew, Hunt, Laura, Saulnier-Talbot, Emilie, Elias, Deevena, Nankabirwa, Angela, Lejju, Julius, Gell, Peter

  • Authors: Mills, Keely , Jones, Matthew , Hunt, Laura , Saulnier-Talbot, Emilie , Elias, Deevena , Nankabirwa, Angela , Lejju, Julius , Gell, Peter
  • Date: 2023
  • Type: Text , Book chapter
  • Relation: Ramsar Wetlands: Values, Assessment, Management Chapter 10 p. 237-258
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  • Description: Wetlands provide a wealth of ecosystem services to people, including ecological, economic, and socio-cultural benefits. However, more than 30% of freshwater species are threatened with extinction, and freshwater biodiversity is declining faster than that observed in oceans or forests. When it comes to the management of wetlands, it often occurs too late and when ecosystem services to people are at risk of being lost. It is easy to observe and monitor the recent impacts of people on wetland systems, but the changes we see today are a product of hundreds, even thousands of years of direct and indirect human impact. Without a deeper understanding of the long-term context of human impacts on wetland systems, it is impossible to manage the problems they experience (such as changes in hydrology, nutrient loading, acidification, and salinisation). Despite the 20th century being the period in which humans have exerted the greatest impact on wetland systems, it was also the period in which we developed a greater appreciation of wetlands as anthropogenically altered landscapes, and, maybe paradoxically, the benefits that accrue from healthy wetlands. Palaeolimnological approaches allow an understanding of wetland system variability over millennial scales, providing background context for anthropogenically forced change. This palaeo-perspective enables a deeper understanding of the long-term context of human impacts on wetland systems and can provide a fresh perspective when managing impacted systems. © 2023 Elsevier Inc. All rights reserved.

Cyan Moon crew preparation for the Sydney To Hobart Yacht Race March 2023

- Porter, Joanne, Simic, Megan, Talpey, Scott, Fenton, Sam, Casey, Meghan, McNeal, Dominic, Statham, Dixie, Prokopiv, Valerie, Miller, Libby

  • Authors: Porter, Joanne , Simic, Megan , Talpey, Scott , Fenton, Sam , Casey, Meghan , McNeal, Dominic , Statham, Dixie , Prokopiv, Valerie , Miller, Libby
  • Date: 2023
  • Type: Text , Technical report , Report
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  • Description: The Collaborative Evaluation & Research Centre (formally CERG) evaluated the crew’s experiences pre and post yacht events using a mixed methods approach. The Cyan yacht had a crew of 12 and competed in a number of events in the racing calendar leading up to the Sydney to Hobart race in January 2023. This was the first time that this boat and many of the crew competed in the Sydney to Hobart yacht race.

Cyberbullying, mental health, and lesbian, gay, and bisexual youth with disabilities : intersectionalities and environmental risks

- Gates, Trevor, Bills, Kaycee, Bennett, Bindi, Kelly, Brian

  • Authors: Gates, Trevor , Bills, Kaycee , Bennett, Bindi , Kelly, Brian
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Journal of Child and Family Studies Vol. 32, no. 10 (2023), p. 3159-3166
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  • Description: Lesbian, gay, and bisexual youth with disabilities are at risk for being cyberbullied. Additionally, these risks can be compounded by other intersectional factors, such as cultural identity. Youth with multiple marginalized identities are at risk for stress, discrimination, and poor mental health outcomes as a result of bullying. However, research exploring the intersections between risk, sexual identity, and disability is sparse. In this article, we begin to address this gap in a diverse sample of lesbian, gay, and bisexual youth who have reported being cyberbullied in the Youth Risk Behavior Surveillance System. We discuss implications for child and family studies, identifying opportunities for further discussion on risk, mental health, and person-in-environment factors for lesbian, gay, and bisexual youth with disabilities. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Cytoskeletal plakins in epithelial ovarian cancer

- Wesley, Tamsin

  • Authors: Wesley, Tamsin
  • Date: 2023
  • Type: Text , Thesis , PhD
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  • Description: The plakin family of cytoskeletal proteins play an important role in cancer progression yet are under-studied in cancer, especially ovarian cancer. These large cytoskeletal proteins have primary roles in the maintenance of cytoskeletal integrity. They are also associated with scaffolds of intermediate filaments and hemidesmosomal adhesion complexes mediating signalling pathways that regulate cellular growth, migration, invasion and differentiation, as well as a stress response. Abnormalities of plakins, and the closely related spectraplakins, result in serious pathologies of skin, striated muscle and nervous tissue. Their prevalence in epithelial cells suggests that plakins may play a role in epithelial ovarian cancer progression and recurrence. This thesis sought to explore the expression of plakin proteins, particularly plectin (PLEC), desmoplakin (DSP), periplakin (PPL) and envoplakin (EVPL) in ovarian cancer progression, comparing surgical stages, historical Silverberg histological grading and current World Health Organisation (WHO) pathological classification of ovarian tumour types. The study also investigated the potential role that the plakin family of proteins may play in regulating cancer cell growth, survival, migration, invasion and drug resistance. It highlights potential relationships between plakins and epithelial-mesenchymal transition (EMT) and relates how these interactions may affect ovarian cancer progression, chemoresistance and ultimately recurrence. This study hypothesises that the molecular changes in the expression of plakins in benign ovarian tumours compared to various grades and stages of ovarian carcinomas, as well as floating cellular aggregates (spheroids) in the peritoneal ascites microenvironment, may contribute to the progression of the disease. It also attempts to understand these crucial changes in plakin expression in response to chemotherapy treatment and relate these findings in the perspective of disease recurrence.
  • Description: Doctor of Philosophy

Data evolution governance for ontology-based digital twin product lifecycle management

- Ren, Zijie, Shi, Jianhua, Imran, Muhammad

  • Authors: Ren, Zijie , Shi, Jianhua , Imran, Muhammad
  • Date: 2023
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Industrial Informatics Vol. 19, no. 2 (2023), p. 1791-1802
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  • Description: Product lifecycle management (PLM) is an effective method for enhancing the market competitiveness of modern manufacturing industries. The digital twin is characterized by a profound integration of physics and information systems, which provides a technical means for integrating multisource information and breaking the time and space barrier of communication at each link of the lifecycle. Currently, however, the application of this technology focuses primarily on the product itself and 'service-oriented' application results. There is a lack of focus on twin data and its internal evolutionary mechanisms separately. In the management of global data resources, the benefits of digital twin technology cannot be fully realized. This article applies ontology technology in an innovative manner to the field of the digital twin to increase the reusability of twin data. Initially, a four-layered ontology-based twin data management architecture is presented. Then, a three-dimensional and three-granularity unified evolution model of full lifecycle twin data is proposed, as well as its ontology model. Then, the service mode of data components at each stage of the lifecycle is defined, a knowledge-sharing plane is established in the digital twin, and a data governance method based on ontology reasoning using data components on the shared plane is proposed. The ICandyBox simulation platform is then used to demonstrate the concept of the proposed method, and future research directions are proposed. © 2005-2012 IEEE.

Data Industry

- Das, Amritam, Kolluri, Ramachandra, Mareels, Iven

  • Authors: Das, Amritam , Kolluri, Ramachandra , Mareels, Iven
  • Date: 2023
  • Type: Text , Book chapter
  • Relation: The impact of automatic control research on industrial innovation : enabling a sustainable future Chapter 2 p. 15-41
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  • Description: Digitization is at the heart of the fourth industrial revolution, Industry 4.0, and/or Society 5.0. The fourth industrial revolution evolved from the work started with control and automation of manufacturing processes in the third industrial revolution, and brings automation to bear on all engineered processes, be it physical, or administrative. Digitization promises to bring objective, evidence-based, decision-making to all aspects of society, at scale, so as to enable us to steer toward a sustainable society. Data centers embody the core information technology that supports this cyberphysical world. Ensuring that this technology (data centers) itself develops in a sustainable manner not only requires careful orchestration of the available compute, storage, and communication resources but also how we manufacture, maintain, and recycle. This chapter focuses on the former, and provides hints toward the latter. The data center story that unfolds presents itself as a microcosmos of the broader sustainability questions affecting our world, and how we can approach them. ©2024 The Institute of Electrical and Electronics Engineers, Inc.

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
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  • 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

- Tang, Tao

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.
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  • 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
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  • 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.
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  • 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
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  • 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
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  • 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.

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.
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  • 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.
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  • 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
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  • 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
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  • 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.