Beyond Covid-19 : women entrepreneurs and e-commerce policy in the Asia-Pacific
- Braun, Patrice, Birdthistle, Naomi, Flynn, Antoinette
- Authors: Braun, Patrice , Birdthistle, Naomi , Flynn, Antoinette
- Date: 2023
- Type: Text , Book chapter
- Relation: Women's Entrepreneurship Policy: A Global Perspective Chapter 8 p. 192-213
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- Authors: Braun, Patrice , Birdthistle, Naomi , Flynn, Antoinette
- Date: 2023
- Type: Text , Book chapter
- Relation: Women's Entrepreneurship Policy: A Global Perspective Chapter 8 p. 192-213
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Beyond survival : strengthening community-based support for parents receiving a family service intervention
- Goff, Rachel, Sadowski, Christina, Bagley, Kerryn
- Authors: Goff, Rachel , Sadowski, Christina , Bagley, Kerryn
- Date: 2023
- Type: Text , Journal article
- Relation: Child and Family Social Work Vol. 28, no. 2 (2023), p. 491-502
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- Description: This paper presents parents' experiences of community support and their recommendations for how their communities, and the services within them, might support their families. Generated through a human-centred design methodology and using a desire-centred framework, the findings suggest that parents receiving a family service require support invoking feelings of intimacy, trust, reciprocity, inclusivity, connection and belonging. Parents' recommendations for community support include addressing material and attitudinal constraints impacting on engagement with services; creating non-judgmental services tailored to their needs but accessed as a last resort; and creating peer-based opportunities to support each other. Parents reflect that moving beyond basic survival of risk and vulnerability to a position where thriving is possible requires purposeful integration of parent's existing and desired community into service interventions. Facilitating deliberate change at the intersection of community and service support is pertinent to current and future social work policy and practice. Wider opportunities for understanding and enabling the needs and aspirations of parents, which are often overlooked because of a focus on addressing risk and vulnerability, are considered. © 2022 The Authors. Child & Family Social Work published by John Wiley & Sons Ltd.
- Authors: Goff, Rachel , Sadowski, Christina , Bagley, Kerryn
- Date: 2023
- Type: Text , Journal article
- Relation: Child and Family Social Work Vol. 28, no. 2 (2023), p. 491-502
- Full Text:
- Reviewed:
- Description: This paper presents parents' experiences of community support and their recommendations for how their communities, and the services within them, might support their families. Generated through a human-centred design methodology and using a desire-centred framework, the findings suggest that parents receiving a family service require support invoking feelings of intimacy, trust, reciprocity, inclusivity, connection and belonging. Parents' recommendations for community support include addressing material and attitudinal constraints impacting on engagement with services; creating non-judgmental services tailored to their needs but accessed as a last resort; and creating peer-based opportunities to support each other. Parents reflect that moving beyond basic survival of risk and vulnerability to a position where thriving is possible requires purposeful integration of parent's existing and desired community into service interventions. Facilitating deliberate change at the intersection of community and service support is pertinent to current and future social work policy and practice. Wider opportunities for understanding and enabling the needs and aspirations of parents, which are often overlooked because of a focus on addressing risk and vulnerability, are considered. © 2022 The Authors. Child & Family Social Work published by John Wiley & Sons Ltd.
Blockchain technology and application : an overview
- Dong, Shi, Abbas, Khushnood, Li, Meixi, Kamruzzaman, Joarder
- Authors: Dong, Shi , Abbas, Khushnood , Li, Meixi , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article
- Relation: PeerJ Computer Science Vol. 9, no. (2023), p.
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- Description: In recent years, with the rise of digital currency, its underlying technology, blockchain, has become increasingly well-known. This technology has several key characteristics, including decentralization, time-stamped data, consensus mechanism, traceability, programmability, security, and credibility, and block data is essentially tamper-proof. Due to these characteristics, blockchain can address the shortcomings of traditional financial institutions. As a result, this emerging technology has garnered significant attention from financial intermediaries, technology-based companies, and government agencies. This article offers an overview of the fundamentals of blockchain technology and its various applications. The introduction defines blockchain and explains its fundamental working principles, emphasizing features such as decentralization, immutability, and transparency. The article then traces the evolution of blockchain, from its inception in cryptocurrency to its development as a versatile tool with diverse potential applications. The main body of the article explores fundamentals of block chain systems, its limitations, various applications, applicability etc. Finally, the study concludes by discussing the present state of blockchain technology and its future potential, as well as the challenges that must be surmounted to unlock its full potential. © Copyright 2023 Dong et al
- Authors: Dong, Shi , Abbas, Khushnood , Li, Meixi , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article
- Relation: PeerJ Computer Science Vol. 9, no. (2023), p.
- Full Text:
- Reviewed:
- Description: In recent years, with the rise of digital currency, its underlying technology, blockchain, has become increasingly well-known. This technology has several key characteristics, including decentralization, time-stamped data, consensus mechanism, traceability, programmability, security, and credibility, and block data is essentially tamper-proof. Due to these characteristics, blockchain can address the shortcomings of traditional financial institutions. As a result, this emerging technology has garnered significant attention from financial intermediaries, technology-based companies, and government agencies. This article offers an overview of the fundamentals of blockchain technology and its various applications. The introduction defines blockchain and explains its fundamental working principles, emphasizing features such as decentralization, immutability, and transparency. The article then traces the evolution of blockchain, from its inception in cryptocurrency to its development as a versatile tool with diverse potential applications. The main body of the article explores fundamentals of block chain systems, its limitations, various applications, applicability etc. Finally, the study concludes by discussing the present state of blockchain technology and its future potential, as well as the challenges that must be surmounted to unlock its full potential. © Copyright 2023 Dong et al
Bundle enrichment method for nonsmooth difference of convex programming problems
- Gaudioso, Manilo, Taheri, Sona, Bagirov, Adil, Karmitsa, Napsu
- Authors: Gaudioso, Manilo , Taheri, Sona , Bagirov, Adil , Karmitsa, Napsu
- Date: 2023
- Type: Text , Journal article
- Relation: Algorithms Vol. 16, no. 8 (2023), p.
- Relation: http://purl.org/au-research/grants/arc/DP190100580
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- Description: The Bundle Enrichment Method (BEM-DC) is introduced for solving nonsmooth difference of convex (DC) programming problems. The novelty of the method consists of the dynamic management of the bundle. More specifically, a DC model, being the difference of two convex piecewise affine functions, is formulated. The (global) minimization of the model is tackled by solving a set of convex problems whose cardinality depends on the number of linearizations adopted to approximate the second DC component function. The new bundle management policy distributes the information coming from previous iterations to separately model the DC components of the objective function. Such a distribution is driven by the sign of linearization errors. If the displacement suggested by the model minimization provides no sufficient decrease of the objective function, then the temporary enrichment of the cutting plane approximation of just the first DC component function takes place until either the termination of the algorithm is certified or a sufficient decrease is achieved. The convergence of the BEM-DC method is studied, and computational results on a set of academic test problems with nonsmooth DC objective functions are provided. © 2023 by the authors.
- Authors: Gaudioso, Manilo , Taheri, Sona , Bagirov, Adil , Karmitsa, Napsu
- Date: 2023
- Type: Text , Journal article
- Relation: Algorithms Vol. 16, no. 8 (2023), p.
- Relation: http://purl.org/au-research/grants/arc/DP190100580
- Full Text:
- Reviewed:
- Description: The Bundle Enrichment Method (BEM-DC) is introduced for solving nonsmooth difference of convex (DC) programming problems. The novelty of the method consists of the dynamic management of the bundle. More specifically, a DC model, being the difference of two convex piecewise affine functions, is formulated. The (global) minimization of the model is tackled by solving a set of convex problems whose cardinality depends on the number of linearizations adopted to approximate the second DC component function. The new bundle management policy distributes the information coming from previous iterations to separately model the DC components of the objective function. Such a distribution is driven by the sign of linearization errors. If the displacement suggested by the model minimization provides no sufficient decrease of the objective function, then the temporary enrichment of the cutting plane approximation of just the first DC component function takes place until either the termination of the algorithm is certified or a sufficient decrease is achieved. The convergence of the BEM-DC method is studied, and computational results on a set of academic test problems with nonsmooth DC objective functions are provided. © 2023 by the authors.
Cancer classification utilizing voting classifier with ensemble feature selection method and transcriptomic data
- Khatun, Rabea, Akter, Maksuda, Islam, Md Manowarul, Uddin, Md Ashraf, Talukder, Md Alamin, Kamruzzaman, Joarder, Azad, Akm, Paul, Bikash, Almoyad, Muhammad, Aryal, Sunil, Moni, Mohammad
- Authors: Khatun, Rabea , Akter, Maksuda , Islam, Md Manowarul , Uddin, Md Ashraf , Talukder, Md Alamin , Kamruzzaman, Joarder , Azad, Akm , Paul, Bikash , Almoyad, Muhammad , Aryal, Sunil , Moni, Mohammad
- Date: 2023
- Type: Text , Journal article
- Relation: Genes Vol. 14, no. 9 (2023), p.
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- Description: Biomarker-based cancer identification and classification tools are widely used in bioinformatics and machine learning fields. However, the high dimensionality of microarray gene expression data poses a challenge for identifying important genes in cancer diagnosis. Many feature selection algorithms optimize cancer diagnosis by selecting optimal features. This article proposes an ensemble rank-based feature selection method (EFSM) and an ensemble weighted average voting classifier (VT) to overcome this challenge. The EFSM uses a ranking method that aggregates features from individual selection methods to efficiently discover the most relevant and useful features. The VT combines support vector machine, k-nearest neighbor, and decision tree algorithms to create an ensemble model. The proposed method was tested on three benchmark datasets and compared to existing built-in ensemble models. The results show that our model achieved higher accuracy, with 100% for leukaemia, 94.74% for colon cancer, and 94.34% for the 11-tumor dataset. This study concludes by identifying a subset of the most important cancer-causing genes and demonstrating their significance compared to the original data. The proposed approach surpasses existing strategies in accuracy and stability, significantly impacting the development of ML-based gene analysis. It detects vital genes with higher precision and stability than other existing methods. © 2023 by the authors.
- Authors: Khatun, Rabea , Akter, Maksuda , Islam, Md Manowarul , Uddin, Md Ashraf , Talukder, Md Alamin , Kamruzzaman, Joarder , Azad, Akm , Paul, Bikash , Almoyad, Muhammad , Aryal, Sunil , Moni, Mohammad
- Date: 2023
- Type: Text , Journal article
- Relation: Genes Vol. 14, no. 9 (2023), p.
- Full Text:
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- Description: Biomarker-based cancer identification and classification tools are widely used in bioinformatics and machine learning fields. However, the high dimensionality of microarray gene expression data poses a challenge for identifying important genes in cancer diagnosis. Many feature selection algorithms optimize cancer diagnosis by selecting optimal features. This article proposes an ensemble rank-based feature selection method (EFSM) and an ensemble weighted average voting classifier (VT) to overcome this challenge. The EFSM uses a ranking method that aggregates features from individual selection methods to efficiently discover the most relevant and useful features. The VT combines support vector machine, k-nearest neighbor, and decision tree algorithms to create an ensemble model. The proposed method was tested on three benchmark datasets and compared to existing built-in ensemble models. The results show that our model achieved higher accuracy, with 100% for leukaemia, 94.74% for colon cancer, and 94.34% for the 11-tumor dataset. This study concludes by identifying a subset of the most important cancer-causing genes and demonstrating their significance compared to the original data. The proposed approach surpasses existing strategies in accuracy and stability, significantly impacting the development of ML-based gene analysis. It detects vital genes with higher precision and stability than other existing methods. © 2023 by the authors.
CenGCN : centralized convolutional networks with vertex imbalance for scale-free graphs
- Xia, Feng, Wang, Lei, Tang, Tao, Chen, Xin, Kong, Xiangjie, Oatley, Giles, King, Irwin
- Authors: Xia, Feng , Wang, Lei , Tang, Tao , Chen, Xin , Kong, Xiangjie , Oatley, Giles , King, Irwin
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Transactions on Knowledge and Data Engineering Vol. 35, no. 5 (2023), p. 4555-4569
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- Description: Graph Convolutional Networks (GCNs) have achieved impressive performance in a wide variety of areas, attracting considerable attention. The core step of GCNs is the information-passing framework that considers all information from neighbors to the central vertex to be equally important. Such equal importance, however, is inadequate for scale-free networks, where hub vertices propagate more dominant information due to vertex imbalance. In this paper, we propose a novel centrality-based framework named CenGCN to address the inequality of information. This framework first quantifies the similarity between hub vertices and their neighbors by label propagation with hub vertices. Based on this similarity and centrality indices, the framework transforms the graph by increasing or decreasing the weights of edges connecting hub vertices and adding self-connections to vertices. In each non-output layer of the GCN, this framework uses a hub attention mechanism to assign new weights to connected non-hub vertices based on their common information with hub vertices. We present two variants CenGCN_D and CenGCN_E, based on degree centrality and eigenvector centrality, respectively. We also conduct comprehensive experiments, including vertex classification, link prediction, vertex clustering, and network visualization. The results demonstrate that the two variants significantly outperform state-of-the-art baselines. © 1989-2012 IEEE.
- Authors: Xia, Feng , Wang, Lei , Tang, Tao , Chen, Xin , Kong, Xiangjie , Oatley, Giles , King, Irwin
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Transactions on Knowledge and Data Engineering Vol. 35, no. 5 (2023), p. 4555-4569
- Full Text:
- Reviewed:
- Description: Graph Convolutional Networks (GCNs) have achieved impressive performance in a wide variety of areas, attracting considerable attention. The core step of GCNs is the information-passing framework that considers all information from neighbors to the central vertex to be equally important. Such equal importance, however, is inadequate for scale-free networks, where hub vertices propagate more dominant information due to vertex imbalance. In this paper, we propose a novel centrality-based framework named CenGCN to address the inequality of information. This framework first quantifies the similarity between hub vertices and their neighbors by label propagation with hub vertices. Based on this similarity and centrality indices, the framework transforms the graph by increasing or decreasing the weights of edges connecting hub vertices and adding self-connections to vertices. In each non-output layer of the GCN, this framework uses a hub attention mechanism to assign new weights to connected non-hub vertices based on their common information with hub vertices. We present two variants CenGCN_D and CenGCN_E, based on degree centrality and eigenvector centrality, respectively. We also conduct comprehensive experiments, including vertex classification, link prediction, vertex clustering, and network visualization. The results demonstrate that the two variants significantly outperform state-of-the-art baselines. © 1989-2012 IEEE.
Changes in lesson plans as teachers participate in a professional development on statistical literacy
- Tran, Dung, Nguyen, An Thi, Nguyen, Duyen, Ta, Phuong, Pham, Nga, Huynh, Binh
- Authors: Tran, Dung , Nguyen, An Thi , Nguyen, Duyen , Ta, Phuong , Pham, Nga , Huynh, Binh
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Learning, Teaching and Educational Research Vol. 22, no. 5 (2023), p. 281-301
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- Description: Research on mathematics teacher knowledge has gained momentum recently; however, research on teacher planning is scarce, especially using lesson plans as the primary data source. This study examines how teachers' lesson plans change as they participate in a professional development, supporting them in implementing the Vietnamese reformed Curriculum 2018. Using a design-based research methodology, we developed a research-informed framework that assesses teachers' lesson plans for developing students' statistical literacy as emphasized in the mathematics Curriculum. Informed by research literature and data collected from teachers, the framework including seven criteria was shared and used by 61 teachers to reflect on the quality of their lessons. The analysis of 38 lesson plans shows all criteria have improved from pre- to post-lesson plans. The teachers included more explicit and comprehensive learning intentions in their post-lessons. Tasks in the post-lesson plans afforded more opportunities for students to develop statistical literacy, helped them engage in the statistical investigation using real data, and included multiple representations. Finally, the post-lesson plans tended to follow the constructivist teaching principles. Implications on ways to develop teachers' planning competence and suggestions for future studies are included. © 2023 Authors.
- Authors: Tran, Dung , Nguyen, An Thi , Nguyen, Duyen , Ta, Phuong , Pham, Nga , Huynh, Binh
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Learning, Teaching and Educational Research Vol. 22, no. 5 (2023), p. 281-301
- Full Text:
- Reviewed:
- Description: Research on mathematics teacher knowledge has gained momentum recently; however, research on teacher planning is scarce, especially using lesson plans as the primary data source. This study examines how teachers' lesson plans change as they participate in a professional development, supporting them in implementing the Vietnamese reformed Curriculum 2018. Using a design-based research methodology, we developed a research-informed framework that assesses teachers' lesson plans for developing students' statistical literacy as emphasized in the mathematics Curriculum. Informed by research literature and data collected from teachers, the framework including seven criteria was shared and used by 61 teachers to reflect on the quality of their lessons. The analysis of 38 lesson plans shows all criteria have improved from pre- to post-lesson plans. The teachers included more explicit and comprehensive learning intentions in their post-lessons. Tasks in the post-lesson plans afforded more opportunities for students to develop statistical literacy, helped them engage in the statistical investigation using real data, and included multiple representations. Finally, the post-lesson plans tended to follow the constructivist teaching principles. Implications on ways to develop teachers' planning competence and suggestions for future studies are included. © 2023 Authors.
Characterizing Australia's east coast cyclones (1950–2019)
- Gray, Jessie, Verdon-Kidd, Danielle, Jaffrés, Jasmine, Hewson, Michael, Clarke, John, Sharma, Krishneel, English, Nathan
- Authors: Gray, Jessie , Verdon-Kidd, Danielle , Jaffrés, Jasmine , Hewson, Michael , Clarke, John , Sharma, Krishneel , English, Nathan
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 43, no. 7 (2023), p. 3324-3352
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- Description: East coast cyclones (ECCs) provide an essential reprieve from dry periods across eastern Australia. They also deliver flood-producing rains with significant economic, social and environmental impacts. Assessing and comparing the influence of different types of cyclones is hindered by an incomplete understanding of ECC typology, given their widely variable spatial and temporal characteristics. This study employs a track-clustering method (probabilistic, curve-aligned regression model) to identify key cyclonic pathways for ECCs from 1950 to 2019. Six spatially independent clusters were successfully distinguished and further sub-classified (coastal, continental and tropical) based on their genesis location. The seasonality and long-term variability, intensity (maximum Laplacian value ± 2 days) and event-based rainfall were then evaluated for each cluster to quantify the impact of these lows on Australia. The highest quantity of land-based rainfall per event is associated with the tropical cluster (Cluster 6), whereas widespread rainfall was also found to occur in the two continental clusters (clusters 4 and 5). Cyclone tracks orientated close to the coast (clusters 1, 2 and 3) were determined to be the least impactful in terms of rainfall and intensity, despite being the most common cyclone type. In terms of interannual variability, sea surface temperature anomalies suggest an increased cyclone frequency for clusters 1 (austral winter) and 4 (austral spring) during a central Pacific El Niño. Furthermore, cyclone incidence during IOD-negative conditions was more pronounced in winter for clusters 1, 2, 3— and clusters 4 and 5 in spring. All cyclones also predominantly occurred in SAM-positive conditions. However, winter ECCs for clusters 1 and 3 had a higher frequency in SAM-negative. This new typology of ECCs via spatial clustering provides crucial insights into the systems that produce extreme rainfall across eastern Australia and should be used to inform future hazard management of cyclone events. © 2023 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
- Authors: Gray, Jessie , Verdon-Kidd, Danielle , Jaffrés, Jasmine , Hewson, Michael , Clarke, John , Sharma, Krishneel , English, Nathan
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 43, no. 7 (2023), p. 3324-3352
- Full Text:
- Reviewed:
- Description: East coast cyclones (ECCs) provide an essential reprieve from dry periods across eastern Australia. They also deliver flood-producing rains with significant economic, social and environmental impacts. Assessing and comparing the influence of different types of cyclones is hindered by an incomplete understanding of ECC typology, given their widely variable spatial and temporal characteristics. This study employs a track-clustering method (probabilistic, curve-aligned regression model) to identify key cyclonic pathways for ECCs from 1950 to 2019. Six spatially independent clusters were successfully distinguished and further sub-classified (coastal, continental and tropical) based on their genesis location. The seasonality and long-term variability, intensity (maximum Laplacian value ± 2 days) and event-based rainfall were then evaluated for each cluster to quantify the impact of these lows on Australia. The highest quantity of land-based rainfall per event is associated with the tropical cluster (Cluster 6), whereas widespread rainfall was also found to occur in the two continental clusters (clusters 4 and 5). Cyclone tracks orientated close to the coast (clusters 1, 2 and 3) were determined to be the least impactful in terms of rainfall and intensity, despite being the most common cyclone type. In terms of interannual variability, sea surface temperature anomalies suggest an increased cyclone frequency for clusters 1 (austral winter) and 4 (austral spring) during a central Pacific El Niño. Furthermore, cyclone incidence during IOD-negative conditions was more pronounced in winter for clusters 1, 2, 3— and clusters 4 and 5 in spring. All cyclones also predominantly occurred in SAM-positive conditions. However, winter ECCs for clusters 1 and 3 had a higher frequency in SAM-negative. This new typology of ECCs via spatial clustering provides crucial insights into the systems that produce extreme rainfall across eastern Australia and should be used to inform future hazard management of cyclone events. © 2023 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
Charophytes of Australia’s Northern Territory – I. Tribe Chareae
- Casanova, Michelle, Karol, Kenneth
- Authors: Casanova, Michelle , Karol, Kenneth
- Date: 2023
- Type: Text , Journal article
- Relation: Australian Systematic Botany Vol. 36, no. 1 (2023), p. 38-79
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- Description: This study of Northern Territory charophytes documents 22 species in 3 of the genera in tribe Chareae, family Characeae, including 15 previously described species (Chara benthamii, C. erythrogyna, C. globularis, C. karolii, C. lucida, C. porteri, C. protocharoides, C. setosa, C. submollusca, C. wightii, C. zeylanica, Lamprothamnium capitatum, L. compactum, L. stipitatum, Lychnothamnus barbatus) of which 2 are new for the Australian flora (C. erythrogyna and C. wightii), as well as 5 varieties raised to species rank (C. aridicola, C. arnhemensis, C. bancroftii, C. behriana, C. duriuscula), and 2 newly described species (C. lamprothamniformis, C. schultae). Three previously reported species in the tribe (C. braunii, C. corallina, C. fibrosa) are not recorded from the Northern Territory in this study, as previous records were based on erroneous identifications or localities. Although Northern Territory specimens of Lychnothamnus barbatus have not been seen, it has been included in this treatment, because it occurs in south-eastern Queensland, the Gulf of Carpentaria, Papua New Guinea and Timor-Leste. A key, illustrations and descriptions of all the species are provided.
- Authors: Casanova, Michelle , Karol, Kenneth
- Date: 2023
- Type: Text , Journal article
- Relation: Australian Systematic Botany Vol. 36, no. 1 (2023), p. 38-79
- Full Text:
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- Description: This study of Northern Territory charophytes documents 22 species in 3 of the genera in tribe Chareae, family Characeae, including 15 previously described species (Chara benthamii, C. erythrogyna, C. globularis, C. karolii, C. lucida, C. porteri, C. protocharoides, C. setosa, C. submollusca, C. wightii, C. zeylanica, Lamprothamnium capitatum, L. compactum, L. stipitatum, Lychnothamnus barbatus) of which 2 are new for the Australian flora (C. erythrogyna and C. wightii), as well as 5 varieties raised to species rank (C. aridicola, C. arnhemensis, C. bancroftii, C. behriana, C. duriuscula), and 2 newly described species (C. lamprothamniformis, C. schultae). Three previously reported species in the tribe (C. braunii, C. corallina, C. fibrosa) are not recorded from the Northern Territory in this study, as previous records were based on erroneous identifications or localities. Although Northern Territory specimens of Lychnothamnus barbatus have not been seen, it has been included in this treatment, because it occurs in south-eastern Queensland, the Gulf of Carpentaria, Papua New Guinea and Timor-Leste. A key, illustrations and descriptions of all the species are provided.
Charophytes of Australia’s Northern Territory – II. Tribe Nitelleae
- Casanova, Michelle, Karol, Kenneth
- Authors: Casanova, Michelle , Karol, Kenneth
- Date: 2023
- Type: Text , Journal article
- Relation: Australian Systematic Botany Vol. 36, no. 4 (2023), p. 322-353
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- Description: This study of Northern Territory charophytes deals with the tribe Nitelleae in family Characeae. We recognise 16 species of Nitella for the Territory. The list includes seven previously described species (Nitella belangeri, N. biformis, N. congesta, N. heterophylla, N. micklei, N. myriotricha and N.tumulosa, of which N. belangeri and N. tumulosa are newly recorded for the Australian flora), and nine newly described species (N. acanthospora, N. boreali-australis, N. crocodylus, N. limosa, N.martinii, N. nitida, N. oollooensis, N. silicea and N. townsendii). Of the five previously reported Nitella species in the Northern Territory (N. hyalina, N. myriotricha, N. penicillata, N. pseudoflabellata and N. subtilissima), only N. myriotricha is recorded in this study, because the other records were based on erroneous identifications or localities. All Nitella species described here can be distinguished on the basis of their morphology and reproductive arrangement. Keys, illustrations and descriptions of all the species are provided.
- Authors: Casanova, Michelle , Karol, Kenneth
- Date: 2023
- Type: Text , Journal article
- Relation: Australian Systematic Botany Vol. 36, no. 4 (2023), p. 322-353
- Full Text:
- Reviewed:
- Description: This study of Northern Territory charophytes deals with the tribe Nitelleae in family Characeae. We recognise 16 species of Nitella for the Territory. The list includes seven previously described species (Nitella belangeri, N. biformis, N. congesta, N. heterophylla, N. micklei, N. myriotricha and N.tumulosa, of which N. belangeri and N. tumulosa are newly recorded for the Australian flora), and nine newly described species (N. acanthospora, N. boreali-australis, N. crocodylus, N. limosa, N.martinii, N. nitida, N. oollooensis, N. silicea and N. townsendii). Of the five previously reported Nitella species in the Northern Territory (N. hyalina, N. myriotricha, N. penicillata, N. pseudoflabellata and N. subtilissima), only N. myriotricha is recorded in this study, because the other records were based on erroneous identifications or localities. All Nitella species described here can be distinguished on the basis of their morphology and reproductive arrangement. Keys, illustrations and descriptions of all the species are provided.
Chinese students’ decisions to study in Australia after the COVID pandemic-based on the PESTLE factor analysis
- Paynter, Merryn, Sharpe, Wen, Halabi, Abdel, Reimers, Vaughan, Ma, Hongming, Johnstone, Carolyn
- Authors: Paynter, Merryn , Sharpe, Wen , Halabi, Abdel , Reimers, Vaughan , Ma, Hongming , Johnstone, Carolyn
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Intercultural Relations Vol. 96, no. (2023), p.
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- Description: The purpose of this study is to explore the impact of the PESTLE (Political, Economic, Social, Technological, Legal, and Environmental) framework on the motivations of Chinese students to pursue a higher education degree at Australian universities following the COVID-19 pandemic. We conduct a survey with a unique sample of 446 Chinese undergraduate students who are looking to study a postgraduate degree abroad. Seldom used in an educational setting, our empirical findings show a positive effect of PESTLE, particularly the economic factor, on students’ choice to study abroad, which is contrary to the null hypothesis. This study has broader implications for university administrators as it suggests that the PESTLE model can be a useful tool in analyzing education choices at a time of uncertainty. © 2023 The Authors
- Authors: Paynter, Merryn , Sharpe, Wen , Halabi, Abdel , Reimers, Vaughan , Ma, Hongming , Johnstone, Carolyn
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Intercultural Relations Vol. 96, no. (2023), p.
- Full Text:
- Reviewed:
- Description: The purpose of this study is to explore the impact of the PESTLE (Political, Economic, Social, Technological, Legal, and Environmental) framework on the motivations of Chinese students to pursue a higher education degree at Australian universities following the COVID-19 pandemic. We conduct a survey with a unique sample of 446 Chinese undergraduate students who are looking to study a postgraduate degree abroad. Seldom used in an educational setting, our empirical findings show a positive effect of PESTLE, particularly the economic factor, on students’ choice to study abroad, which is contrary to the null hypothesis. This study has broader implications for university administrators as it suggests that the PESTLE model can be a useful tool in analyzing education choices at a time of uncertainty. © 2023 The Authors
Classification of methods to reduce clinical alarm signals for remote patient monitoring : a critical review
- Arora, Teena, Balasubramanian, Venki, Stranieri, Andrew, Shenhan, Mai, Buyya, Rajkumar, Islam, Sardar
- Authors: Arora, Teena , Balasubramanian, Venki , Stranieri, Andrew , Shenhan, Mai , Buyya, Rajkumar , Islam, Sardar
- Date: 2023
- Type: Text , Book chapter
- Relation: Cloud Computing in Medical Imaging Chapter 10 p. 173-194
- Full Text:
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- Authors: Arora, Teena , Balasubramanian, Venki , Stranieri, Andrew , Shenhan, Mai , Buyya, Rajkumar , Islam, Sardar
- Date: 2023
- Type: Text , Book chapter
- Relation: Cloud Computing in Medical Imaging Chapter 10 p. 173-194
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- Reviewed:
Classifying excessive exercise : examining the relationship between compulsive exercise with obsessive-compulsive disorder symptoms and disordered eating symptoms
- Cosh, Suzanne, Eshkevari, Ertimiss, McNeil, Dominic, Tully, Phillip
- Authors: Cosh, Suzanne , Eshkevari, Ertimiss , McNeil, Dominic , Tully, Phillip
- Date: 2023
- Type: Text , Journal article
- Relation: European Eating Disorders Review Vol. 31, no. 6 (2023), p. 769-780
- Full Text:
- Reviewed:
- Description: Objective: There remains a lack of consensus around nosology for compulsive exercise (CE). Although widely observed in eating disorders (ED), CE shares theoretical overlap with obsessive-compulsive disorder (OCD), where exercise compulsions occur in response to obsessions. Yet, there is limited and mixed evidence of a relationship between CE with OCD. This study aims to explore the appropriate diagnostic classification of CE through examination of CE in relation to OCD, obsessional thinking, and ED symptoms. Method: Two hundred and eighty one adults with mental health symptoms, dieting, and exercise behaviour completed measures of OCD, CE, and disordered eating symptoms. Regression and Receiver Operating Characteristic analyses examined relationships between dimensions of CE with OCD and ED symptoms, and the predictive ability of CE assessment for detecting threshold OCD and ED symptoms. Results: CE assessment was poor at predicting threshold OCD symptoms, probable Anorexia Nervosa, and Binge Eating Disorder and moderate at detecting probable disordered eating and Bulimia Nervosa. Associations between CE and OCD symptoms were not significant after adjustment for ED symptoms. Obsessional thinking was associated only with lack of exercise enjoyment. Conclusions: Results indicate that excessive exercise might represent a distinct disorder, with some shared traits across CE, OCD and ED symptoms. Findings question the utility of adaptation of OCD diagnostic criteria for CE. Assessment and treatment implications are considered. © 2023 The Authors. European Eating Disorders Review published by Eating Disorders Association and John Wiley & Sons Ltd.
- Authors: Cosh, Suzanne , Eshkevari, Ertimiss , McNeil, Dominic , Tully, Phillip
- Date: 2023
- Type: Text , Journal article
- Relation: European Eating Disorders Review Vol. 31, no. 6 (2023), p. 769-780
- Full Text:
- Reviewed:
- Description: Objective: There remains a lack of consensus around nosology for compulsive exercise (CE). Although widely observed in eating disorders (ED), CE shares theoretical overlap with obsessive-compulsive disorder (OCD), where exercise compulsions occur in response to obsessions. Yet, there is limited and mixed evidence of a relationship between CE with OCD. This study aims to explore the appropriate diagnostic classification of CE through examination of CE in relation to OCD, obsessional thinking, and ED symptoms. Method: Two hundred and eighty one adults with mental health symptoms, dieting, and exercise behaviour completed measures of OCD, CE, and disordered eating symptoms. Regression and Receiver Operating Characteristic analyses examined relationships between dimensions of CE with OCD and ED symptoms, and the predictive ability of CE assessment for detecting threshold OCD and ED symptoms. Results: CE assessment was poor at predicting threshold OCD symptoms, probable Anorexia Nervosa, and Binge Eating Disorder and moderate at detecting probable disordered eating and Bulimia Nervosa. Associations between CE and OCD symptoms were not significant after adjustment for ED symptoms. Obsessional thinking was associated only with lack of exercise enjoyment. Conclusions: Results indicate that excessive exercise might represent a distinct disorder, with some shared traits across CE, OCD and ED symptoms. Findings question the utility of adaptation of OCD diagnostic criteria for CE. Assessment and treatment implications are considered. © 2023 The Authors. European Eating Disorders Review published by Eating Disorders Association and John Wiley & Sons Ltd.
Clustering tropical cyclone genesis on ENSO timescales in the southwest Pacific
- Tu’uholoaki, Moleni, Espejo, Antonio, Singh, Awnesh, Damlamian, Herve, Wandres, Moritz, Chand, Savin, Mendez, Fernando, Fa’anunu, Ofa
- Authors: Tu’uholoaki, Moleni , Espejo, Antonio , Singh, Awnesh , Damlamian, Herve , Wandres, Moritz , Chand, Savin , Mendez, Fernando , Fa’anunu, Ofa
- Date: 2023
- Type: Text , Journal article
- Relation: Climate Dynamics Vol. 60, no. 11-12 (2023), p. 3353-3368
- Full Text:
- Reviewed:
- Description: Tropical cyclones (TCs) as a natural hazard pose a major threat and risk to the human population globally. This threat is expected to increase in a warming climate as the frequency of severe TCs is expected to increase. In this study, the influence of different monthly sea surface temperature (SST) patterns on the locations and frequency of tropical cyclone genesis (TCG) in the Southwest Pacific (SWP) region is investigated. Using principal component analysis and k-means clustering of monthly SST between 1970 and 2019, nine statistically different SST patterns are identified. Our findings show that the more prominent ENSO patterns such as the Modoki El Niño (i.e., Modoki I and Modoki II) and Eastern Pacific (EP) El Niño impact the frequency and location of TCG significantly. Our results enhance the overall understanding of the TCG variability and the relationship between TCG and SST configurations in the SWP region. The results of this study may support early warning system in SWP by improving seasonal outlooks and quantification of the level of TC-related risks for the vulnerable Pacific Island communities. © 2022, The Author(s).
- Authors: Tu’uholoaki, Moleni , Espejo, Antonio , Singh, Awnesh , Damlamian, Herve , Wandres, Moritz , Chand, Savin , Mendez, Fernando , Fa’anunu, Ofa
- Date: 2023
- Type: Text , Journal article
- Relation: Climate Dynamics Vol. 60, no. 11-12 (2023), p. 3353-3368
- Full Text:
- Reviewed:
- Description: Tropical cyclones (TCs) as a natural hazard pose a major threat and risk to the human population globally. This threat is expected to increase in a warming climate as the frequency of severe TCs is expected to increase. In this study, the influence of different monthly sea surface temperature (SST) patterns on the locations and frequency of tropical cyclone genesis (TCG) in the Southwest Pacific (SWP) region is investigated. Using principal component analysis and k-means clustering of monthly SST between 1970 and 2019, nine statistically different SST patterns are identified. Our findings show that the more prominent ENSO patterns such as the Modoki El Niño (i.e., Modoki I and Modoki II) and Eastern Pacific (EP) El Niño impact the frequency and location of TCG significantly. Our results enhance the overall understanding of the TCG variability and the relationship between TCG and SST configurations in the SWP region. The results of this study may support early warning system in SWP by improving seasonal outlooks and quantification of the level of TC-related risks for the vulnerable Pacific Island communities. © 2022, The Author(s).
Coaches’ use of remote coaching : experiences from paralympic sport
- Taylor, Sarah, Renshaw, Ian, Pinder, Ross, Polman, Remco, Russell, Scott
- Authors: Taylor, Sarah , Renshaw, Ian , Pinder, Ross , Polman, Remco , Russell, Scott
- Date: 2023
- Type: Text , Journal article
- Relation: International Sport Coaching Journal Vol. 10, no. 3 special issue (2023), p. 316-327
- Full Text:
- Reviewed:
- Description: Remote coaching via the use of digital technologies has been utilized within Paralympic Sports since 2015 to address challenges experienced by coaches. These technologies have connected coaches and athletes in real time, alleviating time and travel costs. However, very little is known about the experience of coaching in these environments. Therefore, the aim of this study was to explore the experiences of coaches’ use of remote coaching technologies. Seven coaches from five Paralympic Sports were recruited for this study and participated in semistructured interviews. Additionally, observations were conducted of remote coaching sessions that were part of their regular training schedules. Coaches’ insights highlight that remote technologies created opportunities to increase coach–athlete interactions and positively impact the development of interpersonal relationships. This allowed coaches to explore and exploit newly discovered information from within training environments to aid athletes in skill development. Additionally, remote coaching provided unexpected opportunities for coach development. However, coaches also reported new environmental and logistical challenges which disrupted their usual coaching approach. Overall, remote coaching technologies were perceived as being beneficial despite the challenges experienced. However, future research that looks to understand how to impact coach and athlete development through the online environment is encouraged. © 2023 Human Kinetics, Inc.
- Authors: Taylor, Sarah , Renshaw, Ian , Pinder, Ross , Polman, Remco , Russell, Scott
- Date: 2023
- Type: Text , Journal article
- Relation: International Sport Coaching Journal Vol. 10, no. 3 special issue (2023), p. 316-327
- Full Text:
- Reviewed:
- Description: Remote coaching via the use of digital technologies has been utilized within Paralympic Sports since 2015 to address challenges experienced by coaches. These technologies have connected coaches and athletes in real time, alleviating time and travel costs. However, very little is known about the experience of coaching in these environments. Therefore, the aim of this study was to explore the experiences of coaches’ use of remote coaching technologies. Seven coaches from five Paralympic Sports were recruited for this study and participated in semistructured interviews. Additionally, observations were conducted of remote coaching sessions that were part of their regular training schedules. Coaches’ insights highlight that remote technologies created opportunities to increase coach–athlete interactions and positively impact the development of interpersonal relationships. This allowed coaches to explore and exploit newly discovered information from within training environments to aid athletes in skill development. Additionally, remote coaching provided unexpected opportunities for coach development. However, coaches also reported new environmental and logistical challenges which disrupted their usual coaching approach. Overall, remote coaching technologies were perceived as being beneficial despite the challenges experienced. However, future research that looks to understand how to impact coach and athlete development through the online environment is encouraged. © 2023 Human Kinetics, Inc.
Coaching and talent development in esports : a theoretical framework and suggestions for future research
- Bubna, Kabir, Trotter, Michael, Watson, Matthew, Polman, Remco
- Authors: Bubna, Kabir , Trotter, Michael , Watson, Matthew , Polman, Remco
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 14, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Esports is a growing phenomenon that is capturing the attention of individuals worldwide, and has grown to provide professional and lucrative careers for those who reach the upper echelons. One question that arises, is how esports athletes develop the necessary skills required to improve and compete. This perspective piece opens the door to skill acquisition within esports and how research through an ecological approach can benefit researchers and practitioners as they understand the various perception-action couplings and decision-making challenges faced by esports athletes. We will identify and discuss what constraints look like in esports, the role of affordances, and theorize the implementation of a constraints-led approach in contrasting esports genres. As esports is technology-heavy in nature and generally sedentary, the use of eye-tracking technology is argued to represent an effective method to better understand perceptual attunement between individuals and teams. Future research into skill acquisition in esports is needed to develop a clearer picture of what makes the greatest esports player so great, and how newer players can be developed effectively. Copyright © 2023 Bubna, Trotter, Watson and Polman.
- Authors: Bubna, Kabir , Trotter, Michael , Watson, Matthew , Polman, Remco
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 14, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Esports is a growing phenomenon that is capturing the attention of individuals worldwide, and has grown to provide professional and lucrative careers for those who reach the upper echelons. One question that arises, is how esports athletes develop the necessary skills required to improve and compete. This perspective piece opens the door to skill acquisition within esports and how research through an ecological approach can benefit researchers and practitioners as they understand the various perception-action couplings and decision-making challenges faced by esports athletes. We will identify and discuss what constraints look like in esports, the role of affordances, and theorize the implementation of a constraints-led approach in contrasting esports genres. As esports is technology-heavy in nature and generally sedentary, the use of eye-tracking technology is argued to represent an effective method to better understand perceptual attunement between individuals and teams. Future research into skill acquisition in esports is needed to develop a clearer picture of what makes the greatest esports player so great, and how newer players can be developed effectively. Copyright © 2023 Bubna, Trotter, Watson and Polman.
Coconut water : a sports drink alternative?
- O’Brien, Brendan, Bell, Leo, Hennessy, Declan, Denham, Joshua, Paton, Carl
- Authors: O’Brien, Brendan , Bell, Leo , Hennessy, Declan , Denham, Joshua , Paton, Carl
- Date: 2023
- Type: Text , Journal article
- Relation: Sports Vol. 11, no. 9 (2023), p.
- Full Text:
- Reviewed:
- Description: Coconut water is used as an alternative to conventional sports drinks for hydration during endurance cycling; however, evidence supporting its use is limited. This study determined if drinking coconut water compared to a sports drink altered cycling performance and physiology. In a randomized crossover trial, 19 experienced male (n = 15) and female (n = 4) cyclists (age 30 ± 9 years, body mass 79 ± 11 kg, (Formula presented.) O2 peak 55 ± 8 mL·kg
- Authors: O’Brien, Brendan , Bell, Leo , Hennessy, Declan , Denham, Joshua , Paton, Carl
- Date: 2023
- Type: Text , Journal article
- Relation: Sports Vol. 11, no. 9 (2023), p.
- Full Text:
- Reviewed:
- Description: Coconut water is used as an alternative to conventional sports drinks for hydration during endurance cycling; however, evidence supporting its use is limited. This study determined if drinking coconut water compared to a sports drink altered cycling performance and physiology. In a randomized crossover trial, 19 experienced male (n = 15) and female (n = 4) cyclists (age 30 ± 9 years, body mass 79 ± 11 kg, (Formula presented.) O2 peak 55 ± 8 mL·kg
Cognitive behavioral therapy-based treatments for insomnia and nightmares in adults with trauma symptoms : a systematic review
- Isaac, Fadia, Toukhsati, Samia, DiBenedetto, Mirella, Kennedy, Gerard
- Authors: Isaac, Fadia , Toukhsati, Samia , DiBenedetto, Mirella , Kennedy, Gerard
- Date: 2023
- Type: Text , Journal article
- Relation: Current Psychology Vol. 42, no. 27 (2023), p. 23495-23505
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- Authors: Isaac, Fadia , Toukhsati, Samia , DiBenedetto, Mirella , Kennedy, Gerard
- Date: 2023
- Type: Text , Journal article
- Relation: Current Psychology Vol. 42, no. 27 (2023), p. 23495-23505
- Full Text:
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Comparative analysis of machine and deep learning models for soil properties prediction from hyperspectral visual band
- Datta, Dristi, Paul, Manoranjan, Murshed, Manzur, Teng, Shyh Wei, Schmidtke, Leigh
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2023
- Type: Text , Journal article
- Relation: Environments Vol. 10, no. 5 (2023), p. 77
- Full Text:
- Reviewed:
- Description: Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for studying their correlation with plant health and food production. However, conventional methods such as oven-drying and chemical analysis are laborious, expensive, and only feasible for a limited land area. With the advent of remote sensing technologies like multi/hyperspectral imaging, it is now possible to predict soil properties non-invasive and cost-effectively for a large expanse of bare land. Recent research shows the possibility of predicting those soil contents from a wide range of hyperspectral data using good prediction algorithms. However, these kinds of hyperspectral sensors are expensive and not widely available. Therefore, this paper investigates different machine and deep learning techniques to predict soil nutrient properties using only the red (R), green (G), and blue (B) bands data to propose a suitable machine/deep learning model that can be used as a rapid soil test. Another objective of this research is to observe and compare the prediction accuracy in three cases i. hyperspectral band ii. full spectrum of the visual band, and iii. three-channel of RGB band and provide a guideline to the user on which spectrum information they should use to predict those soil properties. The outcome of this research helps to develop a mobile application that is easy to use for a quick soil test. This research also explores learning-based algorithms with significant feature combinations and their performance comparisons in predicting soil properties from visual band data. For this, we also explore the impact of dimensional reduction (i.e., principal component analysis) and transformations (i.e., empirical mode decomposition) of features. The results show that the proposed model can comparably predict the soil contents from the three-channel RGB data.
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2023
- Type: Text , Journal article
- Relation: Environments Vol. 10, no. 5 (2023), p. 77
- Full Text:
- Reviewed:
- Description: Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for studying their correlation with plant health and food production. However, conventional methods such as oven-drying and chemical analysis are laborious, expensive, and only feasible for a limited land area. With the advent of remote sensing technologies like multi/hyperspectral imaging, it is now possible to predict soil properties non-invasive and cost-effectively for a large expanse of bare land. Recent research shows the possibility of predicting those soil contents from a wide range of hyperspectral data using good prediction algorithms. However, these kinds of hyperspectral sensors are expensive and not widely available. Therefore, this paper investigates different machine and deep learning techniques to predict soil nutrient properties using only the red (R), green (G), and blue (B) bands data to propose a suitable machine/deep learning model that can be used as a rapid soil test. Another objective of this research is to observe and compare the prediction accuracy in three cases i. hyperspectral band ii. full spectrum of the visual band, and iii. three-channel of RGB band and provide a guideline to the user on which spectrum information they should use to predict those soil properties. The outcome of this research helps to develop a mobile application that is easy to use for a quick soil test. This research also explores learning-based algorithms with significant feature combinations and their performance comparisons in predicting soil properties from visual band data. For this, we also explore the impact of dimensional reduction (i.e., principal component analysis) and transformations (i.e., empirical mode decomposition) of features. The results show that the proposed model can comparably predict the soil contents from the three-channel RGB data.
Comparative evaluation of empirical approaches and artificial intelligence techniques for predicting uniaxial compressive strength of rock
- Li, Chuanqi, Zhou, Jian, Dias, Daniel, Du, Kun, Khandelwal, Manoj
- Authors: Li, Chuanqi , Zhou, Jian , Dias, Daniel , Du, Kun , Khandelwal, Manoj
- Date: 2023
- Type: Text , Journal article
- Relation: Geosciences (Switzerland) Vol. 13, no. 10 (2023), p.
- Full Text:
- Reviewed:
- Description: The uniaxial compressive strength (UCS) of rocks is one of the key parameters for evaluating the safety and stability of civil and mining structures. In this study, 386 rock samples containing four properties named the load strength (PLS), the porosity (Pn), the P-wave velocity (Vp), and the Schmidt hardness rebound number (SHR) are utilized to predict the UCS using several typical empirical equations (EA) and artificial intelligence (AI) methods, i.e., 16 single regression (SR) equations, 2 multiple regression (MR) equations, and the random forest (RF) models optimized by grey wolf optimization (GWO), moth flame optimization (MFO), lion swarm optimization (LSO), and sparrow search algorithm (SSA). The root mean square error (RMSE), determination coefficient (R2), Willmott’s index (WI), and variance accounted for (VAF) are used to evaluate the predictive performance of all developed models. The evaluation results show that the overall performance of AI models is superior to empirical approaches, especially the LSO-RF model. In addition, the most important input variable is the Pn for predicting the UCS. Therefore, AI techniques are considered as more efficient and accurate approaches to replace the empirical equations for predicting the UCS of these collected rock samples, which provides a reliable and effective idea to predict the rock UCS in the filed site. © 2023 by the authors.
- Authors: Li, Chuanqi , Zhou, Jian , Dias, Daniel , Du, Kun , Khandelwal, Manoj
- Date: 2023
- Type: Text , Journal article
- Relation: Geosciences (Switzerland) Vol. 13, no. 10 (2023), p.
- Full Text:
- Reviewed:
- Description: The uniaxial compressive strength (UCS) of rocks is one of the key parameters for evaluating the safety and stability of civil and mining structures. In this study, 386 rock samples containing four properties named the load strength (PLS), the porosity (Pn), the P-wave velocity (Vp), and the Schmidt hardness rebound number (SHR) are utilized to predict the UCS using several typical empirical equations (EA) and artificial intelligence (AI) methods, i.e., 16 single regression (SR) equations, 2 multiple regression (MR) equations, and the random forest (RF) models optimized by grey wolf optimization (GWO), moth flame optimization (MFO), lion swarm optimization (LSO), and sparrow search algorithm (SSA). The root mean square error (RMSE), determination coefficient (R2), Willmott’s index (WI), and variance accounted for (VAF) are used to evaluate the predictive performance of all developed models. The evaluation results show that the overall performance of AI models is superior to empirical approaches, especially the LSO-RF model. In addition, the most important input variable is the Pn for predicting the UCS. Therefore, AI techniques are considered as more efficient and accurate approaches to replace the empirical equations for predicting the UCS of these collected rock samples, which provides a reliable and effective idea to predict the rock UCS in the filed site. © 2023 by the authors.