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.
Compliance with the zero suicide initiative by mental health clinicians at a regional mental health service : development and testing of a clinical audit tool
- Porter, Joanne, Dabkowski, Elissa, Connolly, Owen, Prokopiv, Valerie
- Authors: Porter, Joanne , Dabkowski, Elissa , Connolly, Owen , Prokopiv, Valerie
- Date: 2023
- Type: Text , Journal article
- Relation: Nursing Reports Vol. 13, no. 1 (2023), p. 29-42
- Full Text:
- Reviewed:
- Description: Aim: The aim of this study is to investigate the compliance of mental health clinicians in applying the Zero Suicide (ZS) approach to their clinical practice in a rural and regional health community setting. Methods: A retrospective clinical audit of six mental health teams was undertaken at a single site. A clinical audit tool was developed and validated using a six-step approach. The data was extracted and analysed via descriptive and inferential statistics and compared to a specialised mental health team, experienced with the ZS approach. Results: A total of 334 clinical records were extracted for January, April, August, November 2019 and June 2020. The clinical audit and analysis confirmed that the mental health teams are not consistently using the assessments from their training and are therefore not implementing all of these elements into their practice. This could have implications for the risk formulation and treatment for people at risk of suicide. Conclusions: The use of a validated clinical audit tool can be beneficial to establish compliance with the mental health clinicians and to determine any areas requiring further improvement. Further education and reinforcement may be required to ensure consistency with incorporating the elements of ZS into everyday clinical practice. © 2022 by the authors.
- Authors: Porter, Joanne , Dabkowski, Elissa , Connolly, Owen , Prokopiv, Valerie
- Date: 2023
- Type: Text , Journal article
- Relation: Nursing Reports Vol. 13, no. 1 (2023), p. 29-42
- Full Text:
- Reviewed:
- Description: Aim: The aim of this study is to investigate the compliance of mental health clinicians in applying the Zero Suicide (ZS) approach to their clinical practice in a rural and regional health community setting. Methods: A retrospective clinical audit of six mental health teams was undertaken at a single site. A clinical audit tool was developed and validated using a six-step approach. The data was extracted and analysed via descriptive and inferential statistics and compared to a specialised mental health team, experienced with the ZS approach. Results: A total of 334 clinical records were extracted for January, April, August, November 2019 and June 2020. The clinical audit and analysis confirmed that the mental health teams are not consistently using the assessments from their training and are therefore not implementing all of these elements into their practice. This could have implications for the risk formulation and treatment for people at risk of suicide. Conclusions: The use of a validated clinical audit tool can be beneficial to establish compliance with the mental health clinicians and to determine any areas requiring further improvement. Further education and reinforcement may be required to ensure consistency with incorporating the elements of ZS into everyday clinical practice. © 2022 by the authors.
Compulsive exercise and its relationship with mental health and psychosocial wellbeing in recreational exercisers and athletes
- Cosh, Suzanne, McNeil, Dominic, Tully, Phillip
- Authors: Cosh, Suzanne , McNeil, Dominic , Tully, Phillip
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Science and Medicine in Sport Vol. 26, no. 7 (2023), p. 338-344
- Full Text:
- Reviewed:
- Description: Objectives: Better understanding of compulsive exercise is needed in sports medicine. Whilst compulsive exercise may impact mental health, the limited research exploring the relationship between compulsive exercise and psychosocial outcomes is equivocal. The majority of studies have examined eating disorder populations where the eating disorder pathology might account for distress. This study explores relationships between compulsive exercise and mental health. Design: Cross-sectional observational study. Methods: Australian recreational exercisers and athletes (N = 1157; Mage 36.4, standard deviation = 12.9, 77 % female) recruited through sporting organisations, clubs, and gyms, completed measures of compulsive exercise, depression, anxiety, stress, life satisfaction, social physique anxiety, and self-esteem. Regression analyses examined relationships between dimensions of compulsive exercise and wellbeing. Results: After adjustment for eating disorder symptoms and sporting level, compulsive exercise was associated with increased risk of clinically-significant anxiety, depression, and stress symptoms. Compulsive exercise was also associated with lower life satisfaction and self-esteem, and higher social physique anxiety. Notably, different dimensions of compulsive exercise had varying relationships with outcomes, and avoidance and rule-driven behaviour and lack of exercise enjoyment were associated with poorer mental health and wellbeing. Conclusions: Results suggest that compulsive exercise is uniquely associated with a range of psychosocial and mental health outcomes. Results support the need to improve identification and treatment of compulsive exercise in sport and exercise settings. Results highlight that mental health intervention is an important component of treatment, and treatments targeting symptoms related to avoidance and rule-driven behaviour, and anhedonia may be valuable treatment components for those with compulsive exercise. © 2023 The Author(s)
- Authors: Cosh, Suzanne , McNeil, Dominic , Tully, Phillip
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Science and Medicine in Sport Vol. 26, no. 7 (2023), p. 338-344
- Full Text:
- Reviewed:
- Description: Objectives: Better understanding of compulsive exercise is needed in sports medicine. Whilst compulsive exercise may impact mental health, the limited research exploring the relationship between compulsive exercise and psychosocial outcomes is equivocal. The majority of studies have examined eating disorder populations where the eating disorder pathology might account for distress. This study explores relationships between compulsive exercise and mental health. Design: Cross-sectional observational study. Methods: Australian recreational exercisers and athletes (N = 1157; Mage 36.4, standard deviation = 12.9, 77 % female) recruited through sporting organisations, clubs, and gyms, completed measures of compulsive exercise, depression, anxiety, stress, life satisfaction, social physique anxiety, and self-esteem. Regression analyses examined relationships between dimensions of compulsive exercise and wellbeing. Results: After adjustment for eating disorder symptoms and sporting level, compulsive exercise was associated with increased risk of clinically-significant anxiety, depression, and stress symptoms. Compulsive exercise was also associated with lower life satisfaction and self-esteem, and higher social physique anxiety. Notably, different dimensions of compulsive exercise had varying relationships with outcomes, and avoidance and rule-driven behaviour and lack of exercise enjoyment were associated with poorer mental health and wellbeing. Conclusions: Results suggest that compulsive exercise is uniquely associated with a range of psychosocial and mental health outcomes. Results support the need to improve identification and treatment of compulsive exercise in sport and exercise settings. Results highlight that mental health intervention is an important component of treatment, and treatments targeting symptoms related to avoidance and rule-driven behaviour, and anhedonia may be valuable treatment components for those with compulsive exercise. © 2023 The Author(s)
Concussion assessment and management — what do community-level cricket participants know?
- Kodikara, Dulan, Plumb, Mandy, Twomey, Dara
- Authors: Kodikara, Dulan , Plumb, Mandy , Twomey, Dara
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Science and Medicine in Sport Vol. 26, no. 9 (2023), p. 448-453
- Full Text:
- Reviewed:
- Description: Objectives: To explore Australian cricket participants' knowledge of concussion assessment and management, and awareness of current concussion guidelines. Design: Cross-sectional survey. Methods: Novel and validated surveys were disseminated online, among over 16 year Australian cricket players and officials at the end of the 2018/19 cricket season. Data were collected on knowledge and awareness of concussion and analysed using descriptive statistics and crosstabulations. Further comparisons were made for the players between injured and non-injured, and helmet wearers and non-helmet wearers using Fisher's exact statistical test. Results: Both players (n = 224, 93 %) and officials (n = 36, 100 %) demonstrated strong knowledge of the importance of immediately evaluating suspected concussions. In comparison with players without helmets (n = 11), those using helmets (n = 135) considered replacing their helmets after a concussion to be vital to concussion assessment (p = 0.02). Overall, 80–97 % of players and 81–97 % of officials understood the importance of many factors regarding concussion management. When concussion management knowledge was compared by injury status, injured players (n = 17, 94 %) believed someone with a concussion should be hospitalised immediately, in contrast to non-injured players (n = 154, 69 %) (p = 0.04). Players (63 %) were less aware of concussion guidelines than officials (81 %). Conclusions: Overall, the knowledge of concussion assessment and management was satisfactory. However, there were discrepancies among players on some aspects of awareness of concussion guidelines. Increasing players' familiarity and experience in using the concussion guidelines is warranted. Targeted campaigns are needed to further improve concussion recognition and treatment at community-level cricket, so all participants play a role in making cricket a safe sport. © 2023
- Authors: Kodikara, Dulan , Plumb, Mandy , Twomey, Dara
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Science and Medicine in Sport Vol. 26, no. 9 (2023), p. 448-453
- Full Text:
- Reviewed:
- Description: Objectives: To explore Australian cricket participants' knowledge of concussion assessment and management, and awareness of current concussion guidelines. Design: Cross-sectional survey. Methods: Novel and validated surveys were disseminated online, among over 16 year Australian cricket players and officials at the end of the 2018/19 cricket season. Data were collected on knowledge and awareness of concussion and analysed using descriptive statistics and crosstabulations. Further comparisons were made for the players between injured and non-injured, and helmet wearers and non-helmet wearers using Fisher's exact statistical test. Results: Both players (n = 224, 93 %) and officials (n = 36, 100 %) demonstrated strong knowledge of the importance of immediately evaluating suspected concussions. In comparison with players without helmets (n = 11), those using helmets (n = 135) considered replacing their helmets after a concussion to be vital to concussion assessment (p = 0.02). Overall, 80–97 % of players and 81–97 % of officials understood the importance of many factors regarding concussion management. When concussion management knowledge was compared by injury status, injured players (n = 17, 94 %) believed someone with a concussion should be hospitalised immediately, in contrast to non-injured players (n = 154, 69 %) (p = 0.04). Players (63 %) were less aware of concussion guidelines than officials (81 %). Conclusions: Overall, the knowledge of concussion assessment and management was satisfactory. However, there were discrepancies among players on some aspects of awareness of concussion guidelines. Increasing players' familiarity and experience in using the concussion guidelines is warranted. Targeted campaigns are needed to further improve concussion recognition and treatment at community-level cricket, so all participants play a role in making cricket a safe sport. © 2023
Considering the need for movement variability in motor imagery training : implications for sport and rehabilitation
- Lindsay, Riki, Spittle, Sharna, Spittle, Michael
- Authors: Lindsay, Riki , Spittle, Sharna , Spittle, Michael
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 14, no. (2023), p.
- Full Text:
- Reviewed:
- Authors: Lindsay, Riki , Spittle, Sharna , Spittle, Michael
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 14, no. (2023), p.
- Full Text:
- Reviewed:
Construction of generalized shape functions over arbitrary polytopes based on scaled boundary finite element method's solution of Poisson's equation
- Xiao, B., Natarajan, Sundararajan, Birk, Carolin, Ooi, Ean Hin, Song, Chongmin, Ooi, Ean Tat
- Authors: Xiao, B. , Natarajan, Sundararajan , Birk, Carolin , Ooi, Ean Hin , Song, Chongmin , Ooi, Ean Tat
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal for Numerical Methods in Engineering Vol. 124, no. 17 (2023), p. 3603-3636
- Full Text:
- Reviewed:
- Description: A general technique to develop arbitrary-sided polygonal elements based on the scaled boundary finite element method is presented. Shape functions are derived from the solution of the Poisson's equation in contrast to the well-known Laplace shape functions that are only linearly complete. The application of the Poisson shape functions can be complete up to any specific order. The shape functions retain the advantage of the scaled boundary finite element method allowing direct formulation on polygons with arbitrary number of sides and quadtree meshes. The resulting formulation is similar to the finite element method where each field variable is interpolated by the same set of shape functions in parametric space and differs only in the integration of the stiffness and mass matrices. Well-established finite element procedures can be applied with the developed shape functions, to solve a variety of engineering problems including, for example, coupled field problems, phase field fracture, and addressing volumetric locking in the near-incompressibility limit by adopting a mixed formulation. Application of the formulation is demonstrated in several engineering problems. Optimal convergence rates are observed. © 2023 The Authors. International Journal for Numerical Methods in Engineering published by John Wiley & Sons Ltd.
- Authors: Xiao, B. , Natarajan, Sundararajan , Birk, Carolin , Ooi, Ean Hin , Song, Chongmin , Ooi, Ean Tat
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal for Numerical Methods in Engineering Vol. 124, no. 17 (2023), p. 3603-3636
- Full Text:
- Reviewed:
- Description: A general technique to develop arbitrary-sided polygonal elements based on the scaled boundary finite element method is presented. Shape functions are derived from the solution of the Poisson's equation in contrast to the well-known Laplace shape functions that are only linearly complete. The application of the Poisson shape functions can be complete up to any specific order. The shape functions retain the advantage of the scaled boundary finite element method allowing direct formulation on polygons with arbitrary number of sides and quadtree meshes. The resulting formulation is similar to the finite element method where each field variable is interpolated by the same set of shape functions in parametric space and differs only in the integration of the stiffness and mass matrices. Well-established finite element procedures can be applied with the developed shape functions, to solve a variety of engineering problems including, for example, coupled field problems, phase field fracture, and addressing volumetric locking in the near-incompressibility limit by adopting a mixed formulation. Application of the formulation is demonstrated in several engineering problems. Optimal convergence rates are observed. © 2023 The Authors. International Journal for Numerical Methods in Engineering published by John Wiley & Sons Ltd.
Converting optimum compaction properties of fine-grained soils between rational energy levels
- Soltani, Amin, Azimi, Mahdieh, O'Kelly, Brendan, Horpibulsuk, Suksun
- Authors: Soltani, Amin , Azimi, Mahdieh , O'Kelly, Brendan , Horpibulsuk, Suksun
- Date: 2023
- Type: Text , Journal article
- Relation: Transportation Geotechnics Vol. 42, no. (2023), p.
- Full Text:
- Reviewed:
- Description: This study introduces a practical energy conversion (EC)-type modeling framework capable of converting the optimum compaction properties of fine-grained soils between any two rational compaction energy levels (CELs). Model development/calibration was carried out using a database of 242 compaction test results — the largest and most diverse database of its kind, to date, entailing 76 fine-grained soils (covering liquid limits of 16–256%), with each soil tested for at least three different CELs. On establishing the framework, an independent database of 91 compaction test results (consisting of 34 fine-grained soils tested for varying CELs) was employed for its validation. The proposed EC-based models employ measured optimum water content (OWC) and maximum dry unit weight (MDUW) values obtained for a rational CEL (preferably standard Proctor) to predict the same for higher and/or lower compactive efforts (covering 214–5416 kJ/m3). The 95% lower and upper statistical agreement limits between the predicted/converted and measured OWCs were obtained as
- Authors: Soltani, Amin , Azimi, Mahdieh , O'Kelly, Brendan , Horpibulsuk, Suksun
- Date: 2023
- Type: Text , Journal article
- Relation: Transportation Geotechnics Vol. 42, no. (2023), p.
- Full Text:
- Reviewed:
- Description: This study introduces a practical energy conversion (EC)-type modeling framework capable of converting the optimum compaction properties of fine-grained soils between any two rational compaction energy levels (CELs). Model development/calibration was carried out using a database of 242 compaction test results — the largest and most diverse database of its kind, to date, entailing 76 fine-grained soils (covering liquid limits of 16–256%), with each soil tested for at least three different CELs. On establishing the framework, an independent database of 91 compaction test results (consisting of 34 fine-grained soils tested for varying CELs) was employed for its validation. The proposed EC-based models employ measured optimum water content (OWC) and maximum dry unit weight (MDUW) values obtained for a rational CEL (preferably standard Proctor) to predict the same for higher and/or lower compactive efforts (covering 214–5416 kJ/m3). The 95% lower and upper statistical agreement limits between the predicted/converted and measured OWCs were obtained as
Corporate social responsibility and performance measurement systems in Iran : a levers of control perspective
- Asiaei, Kaveh, O'Connor, Neale, Moghaddam, Majid, Bontis, Nick, Sidhu, Jasvinder
- Authors: Asiaei, Kaveh , O'Connor, Neale , Moghaddam, Majid , Bontis, Nick , Sidhu, Jasvinder
- Date: 2023
- Type: Text , Journal article
- Relation: Corporate Social Responsibility and Environmental Management Vol. 30, no. 2 (2023), p. 574-588
- Full Text:
- Reviewed:
- Description: This study draws on Simons' levers of control model to explore how companies rely on the balanced use of diagnostic and interactive performance measurement systems (PMS) to translate corporate social responsibility (CSR) into superior performance. Data were collected based on a survey data set from 98 CFOs of public listed companies in Iran. The theoretical model was tested using partial least squares structural equation modeling (PLS-SEM, SmartPLS 3.0), which enjoys minimum demands concerning normality assumptions and sample size. The findings show that CSR is positively associated with PMS and organizational performance. Moreover, CSR is indirectly related to organizational performance through the mediating effect of PMS. This study extends the previous literature by simultaneously incorporating resource orchestration theory in the management accounting and CSR settings. The findings provide further insights into the issue of how adopting proper management control mechanisms (e.g., balanced use of PMS) can support organizations in orchestrating the social, environmental, and economic impacts more effectively. © 2022 The Authors. Corporate Social Responsibility and Environmental Management published by ERP Environment and John Wiley & Sons Ltd.
- Authors: Asiaei, Kaveh , O'Connor, Neale , Moghaddam, Majid , Bontis, Nick , Sidhu, Jasvinder
- Date: 2023
- Type: Text , Journal article
- Relation: Corporate Social Responsibility and Environmental Management Vol. 30, no. 2 (2023), p. 574-588
- Full Text:
- Reviewed:
- Description: This study draws on Simons' levers of control model to explore how companies rely on the balanced use of diagnostic and interactive performance measurement systems (PMS) to translate corporate social responsibility (CSR) into superior performance. Data were collected based on a survey data set from 98 CFOs of public listed companies in Iran. The theoretical model was tested using partial least squares structural equation modeling (PLS-SEM, SmartPLS 3.0), which enjoys minimum demands concerning normality assumptions and sample size. The findings show that CSR is positively associated with PMS and organizational performance. Moreover, CSR is indirectly related to organizational performance through the mediating effect of PMS. This study extends the previous literature by simultaneously incorporating resource orchestration theory in the management accounting and CSR settings. The findings provide further insights into the issue of how adopting proper management control mechanisms (e.g., balanced use of PMS) can support organizations in orchestrating the social, environmental, and economic impacts more effectively. © 2022 The Authors. Corporate Social Responsibility and Environmental Management published by ERP Environment and John Wiley & Sons Ltd.
COVID-19 : factors associated with the psychological distress, fear and resilient coping strategies among community members in Saudi Arabia
- Alharbi, Talal, Alqurashi, Alaa, Mahmud, Ilias, Alharbi, Rayan, Islam, Sheikh, Almustanyir, Sami, Maklad, Ahmed, AlSarraj, Ahmad, Mughaiss, Lujain, Al-Tawfiq, Jaffar, Ahmed, Ahmed, Barry, Mazin, Ghozy, Sherief, Alabdan, Lulwah, Alif, Sheikh, Sultana, Farhana, Salehin, Masudus, Banik, Biswajit, Cross, Wendy, Rahman, Muhammad Aziz
- Authors: Alharbi, Talal , Alqurashi, Alaa , Mahmud, Ilias , Alharbi, Rayan , Islam, Sheikh , Almustanyir, Sami , Maklad, Ahmed , AlSarraj, Ahmad , Mughaiss, Lujain , Al-Tawfiq, Jaffar , Ahmed, Ahmed , Barry, Mazin , Ghozy, Sherief , Alabdan, Lulwah , Alif, Sheikh , Sultana, Farhana , Salehin, Masudus , Banik, Biswajit , Cross, Wendy , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: Healthcare (Switzerland) Vol. 11, no. 8 (2023), p.
- Full Text:
- Reviewed:
- Description: (1) Background: COVID-19 caused the worst international public health crisis, accompanied by major global economic downturns and mass-scale job losses, which impacted the psychosocial wellbeing of the worldwide population, including Saudi Arabia. Evidence of the high-risk groups impacted by the pandemic has been non-existent in Saudi Arabia. Therefore, this study examined factors associated with psychosocial distress, fear of COVID-19 and coping strategies among the general population in Saudi Arabia. (2) Methods: A cross-sectional study was conducted in healthcare and community settings in the Saudi Arabia using an anonymous online questionnaire. The Kessler Psychological Distress Scale (K-10), Fear of COVID-19 Scale (FCV-19S) and Brief Resilient Coping Scale (BRCS) were used to assess psychological distress, fear and coping strategies, respectively. Multivariate logistic regressions were used, and an Adjusted Odds Ratio (AOR) with 95% Confidence Intervals (CIs) was reported. (3) Results: Among 803 participants, 70% (n = 556) were females, and the median age was 27 years; 35% (n = 278) were frontline or essential service workers; and 24% (n = 195) reported comorbid conditions including mental health illness. Of the respondents, 175 (21.8%) and 207 (25.8%) reported high and very high psychological distress, respectively. Factors associated with moderate to high levels of psychological distress were: youth, females, non-Saudi nationals, those experiencing a change in employment or a negative financial impact, having comorbidities, and current smoking. A high level of fear was reported by 89 participants (11.1%), and this was associated with being ex-smokers (3.72, 1.14–12.14, 0.029) and changes in employment (3.42, 1.91–6.11, 0.000). A high resilience was reported by 115 participants (14.3%), and 333 participants (41.5%) had medium resilience. Financial impact and contact with known/suspected cases (1.63, 1.12–2.38, 0.011) were associated with low, medium, to high resilient coping. (4) Conclusions: People in Saudi Arabia were at a higher risk of psychosocial distress along with medium-high resilience during the COVID-19 pandemic, warranting urgent attention from healthcare providers and policymakers to provide specific mental health support strategies for their current wellbeing and to avoid a post-pandemic mental health crisis. © 2023 by the authors.
- Authors: Alharbi, Talal , Alqurashi, Alaa , Mahmud, Ilias , Alharbi, Rayan , Islam, Sheikh , Almustanyir, Sami , Maklad, Ahmed , AlSarraj, Ahmad , Mughaiss, Lujain , Al-Tawfiq, Jaffar , Ahmed, Ahmed , Barry, Mazin , Ghozy, Sherief , Alabdan, Lulwah , Alif, Sheikh , Sultana, Farhana , Salehin, Masudus , Banik, Biswajit , Cross, Wendy , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: Healthcare (Switzerland) Vol. 11, no. 8 (2023), p.
- Full Text:
- Reviewed:
- Description: (1) Background: COVID-19 caused the worst international public health crisis, accompanied by major global economic downturns and mass-scale job losses, which impacted the psychosocial wellbeing of the worldwide population, including Saudi Arabia. Evidence of the high-risk groups impacted by the pandemic has been non-existent in Saudi Arabia. Therefore, this study examined factors associated with psychosocial distress, fear of COVID-19 and coping strategies among the general population in Saudi Arabia. (2) Methods: A cross-sectional study was conducted in healthcare and community settings in the Saudi Arabia using an anonymous online questionnaire. The Kessler Psychological Distress Scale (K-10), Fear of COVID-19 Scale (FCV-19S) and Brief Resilient Coping Scale (BRCS) were used to assess psychological distress, fear and coping strategies, respectively. Multivariate logistic regressions were used, and an Adjusted Odds Ratio (AOR) with 95% Confidence Intervals (CIs) was reported. (3) Results: Among 803 participants, 70% (n = 556) were females, and the median age was 27 years; 35% (n = 278) were frontline or essential service workers; and 24% (n = 195) reported comorbid conditions including mental health illness. Of the respondents, 175 (21.8%) and 207 (25.8%) reported high and very high psychological distress, respectively. Factors associated with moderate to high levels of psychological distress were: youth, females, non-Saudi nationals, those experiencing a change in employment or a negative financial impact, having comorbidities, and current smoking. A high level of fear was reported by 89 participants (11.1%), and this was associated with being ex-smokers (3.72, 1.14–12.14, 0.029) and changes in employment (3.42, 1.91–6.11, 0.000). A high resilience was reported by 115 participants (14.3%), and 333 participants (41.5%) had medium resilience. Financial impact and contact with known/suspected cases (1.63, 1.12–2.38, 0.011) were associated with low, medium, to high resilient coping. (4) Conclusions: People in Saudi Arabia were at a higher risk of psychosocial distress along with medium-high resilience during the COVID-19 pandemic, warranting urgent attention from healthcare providers and policymakers to provide specific mental health support strategies for their current wellbeing and to avoid a post-pandemic mental health crisis. © 2023 by the authors.
COVID-19 : psychological distress, fear, and coping strategies among community members across the United Arab Emirates
- Al Dweik, Rania, Rahman, Muhammad Aziz, Ahamed, Fathima, Ramada, Heba, Al Sheble, Yousef, ElTaher, Sondos, Cross, Wendy, Elsori, Deena
- Authors: Al Dweik, Rania , Rahman, Muhammad Aziz , Ahamed, Fathima , Ramada, Heba , Al Sheble, Yousef , ElTaher, Sondos , Cross, Wendy , Elsori, Deena
- Date: 2023
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 18, no. 3 March (2023), p.
- Full Text:
- Reviewed:
- Description: Background The COVID-19 pandemic impacted the psychosocial well-being of the United Arab Emirates [UAE] population like other communities internationally. Objectives We aimed to identify the factors associated with psychological distress, fear, and coping amongst community members across the UAE. Methods We conducted a cross-sectional online survey across the UAE during November 2020. Adults aged
- Authors: Al Dweik, Rania , Rahman, Muhammad Aziz , Ahamed, Fathima , Ramada, Heba , Al Sheble, Yousef , ElTaher, Sondos , Cross, Wendy , Elsori, Deena
- Date: 2023
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 18, no. 3 March (2023), p.
- Full Text:
- Reviewed:
- Description: Background The COVID-19 pandemic impacted the psychosocial well-being of the United Arab Emirates [UAE] population like other communities internationally. Objectives We aimed to identify the factors associated with psychological distress, fear, and coping amongst community members across the UAE. Methods We conducted a cross-sectional online survey across the UAE during November 2020. Adults aged
COVID-19 effects on public finance and SDG priorities in developing countries : comparative evidence from Bangladesh and Sri Lanka
- Colombage, Sisira, Barua, Suborna, Nanayakkara, Madurika, Colombage, Udari
- Authors: Colombage, Sisira , Barua, Suborna , Nanayakkara, Madurika , Colombage, Udari
- Date: 2023
- Type: Text , Journal article
- Relation: European Journal of Development Research Vol. 35, no. 1 (2023), p. 85-111
- Full Text:
- Reviewed:
- Description: The COVID-19 pandemic, an unprecedented global health crisis, rapidly transferred into a global economic and social crisis. The pandemic has threatened the world’s commitment to achieve Sustainable Development Goals (SDGs) by 2030 as governments in developing countries have shifted their priorities from attaining SDGs, to providing urgent financial needs to save lives and prevent recession in hopes for a rapid economic recovery. The rerouting of public funding priorities has undermined the progress and achievement of SDGs. We employed a mixed-method and carried out a comparative study using pre- and post-public financial data of two developing countries in South Asia; Bangladesh and Sri Lanka. A threefold analysis was conducted to investigate the evolution of the COVID-19 pandemic in two countries, the impact of the pandemic on external and internal public finance and the effect of the pandemic in shifting the policy priorities from SDGs to economic survival. This study found that both countries are highly vulnerable to the COVID-19 pandemic and are suffering from the lack of financing from external sources through the private sector as well as an increasing foreign debt. There is mounting pressure on the fiscal balance in both countries. © 2022, The Author(s).
- Authors: Colombage, Sisira , Barua, Suborna , Nanayakkara, Madurika , Colombage, Udari
- Date: 2023
- Type: Text , Journal article
- Relation: European Journal of Development Research Vol. 35, no. 1 (2023), p. 85-111
- Full Text:
- Reviewed:
- Description: The COVID-19 pandemic, an unprecedented global health crisis, rapidly transferred into a global economic and social crisis. The pandemic has threatened the world’s commitment to achieve Sustainable Development Goals (SDGs) by 2030 as governments in developing countries have shifted their priorities from attaining SDGs, to providing urgent financial needs to save lives and prevent recession in hopes for a rapid economic recovery. The rerouting of public funding priorities has undermined the progress and achievement of SDGs. We employed a mixed-method and carried out a comparative study using pre- and post-public financial data of two developing countries in South Asia; Bangladesh and Sri Lanka. A threefold analysis was conducted to investigate the evolution of the COVID-19 pandemic in two countries, the impact of the pandemic on external and internal public finance and the effect of the pandemic in shifting the policy priorities from SDGs to economic survival. This study found that both countries are highly vulnerable to the COVID-19 pandemic and are suffering from the lack of financing from external sources through the private sector as well as an increasing foreign debt. There is mounting pressure on the fiscal balance in both countries. © 2022, The Author(s).
Critical data detection for dynamically adjustable product quality in IIoT-enabled manufacturing
- Sen, Sachin, Karmakar, Gour, Pang, Shaoning
- Authors: Sen, Sachin , Karmakar, Gour , Pang, Shaoning
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 49464-49480
- Full Text:
- Reviewed:
- Description: The IIoT technologies, due to the widespread use of sensors, generate massive data that are key in providing innovative and efficient industrial management, operation, and product quality control processes. The significance of data has prompted relevant research communities and application developers how to harness the values of these data in secure manufacturing. Critical data analysis, identification of critical factors to improve the manufacturing process and critical data associated with product quality have been investigated in the current literature. However, the current works on product quality control are mainly based on static data analysis, where data may change, but there is no way to adjust them dynamically. Thus, they are not applicable for product quality control, at which point their adjustment is instantly required. However, many manufacturing systems exist, like beverages and food, where ingredients must be adjusted instantaneously to maintain product quality. To address this research gap, we introduce a method that identifies the critical data based on their ranking by exploiting three criticality assessment criteria that capture the instantaneous product quality change during manufacturing. These three criteria are - (1) correlation, (2) percentage quality change and (3) sensitivity for the assessment of data criticality. The product quality is estimated using polynomial regression (POLY), SVM, and DNN. The proposed method is validated using wine manufacturing data. Our proposed method accurately identifies critical data, where SVM produces the lowest average production quality prediction error (10.40%) compared with that of POLY (11%) and DNN (14.40%). © 2013 IEEE.
- Authors: Sen, Sachin , Karmakar, Gour , Pang, Shaoning
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 49464-49480
- Full Text:
- Reviewed:
- Description: The IIoT technologies, due to the widespread use of sensors, generate massive data that are key in providing innovative and efficient industrial management, operation, and product quality control processes. The significance of data has prompted relevant research communities and application developers how to harness the values of these data in secure manufacturing. Critical data analysis, identification of critical factors to improve the manufacturing process and critical data associated with product quality have been investigated in the current literature. However, the current works on product quality control are mainly based on static data analysis, where data may change, but there is no way to adjust them dynamically. Thus, they are not applicable for product quality control, at which point their adjustment is instantly required. However, many manufacturing systems exist, like beverages and food, where ingredients must be adjusted instantaneously to maintain product quality. To address this research gap, we introduce a method that identifies the critical data based on their ranking by exploiting three criticality assessment criteria that capture the instantaneous product quality change during manufacturing. These three criteria are - (1) correlation, (2) percentage quality change and (3) sensitivity for the assessment of data criticality. The product quality is estimated using polynomial regression (POLY), SVM, and DNN. The proposed method is validated using wine manufacturing data. Our proposed method accurately identifies critical data, where SVM produces the lowest average production quality prediction error (10.40%) compared with that of POLY (11%) and DNN (14.40%). © 2013 IEEE.
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
- Full Text:
- Reviewed:
- 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).
- 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
- Full Text:
- Reviewed:
- 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
- Full Text:
- Reviewed:
- 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.
- 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
- Full Text:
- Reviewed:
- 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.
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
- Full Text:
- 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.
- 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
- Full Text:
- 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.
Deep learning : survey of environmental and camera impacts on internet of things images
- Kaur, Roopdeep, Karmakar, Gour, Xia, Feng, Imran, Muhammad
- Authors: Kaur, Roopdeep , Karmakar, Gour , Xia, Feng , Imran, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Artificial Intelligence Review Vol. 56, no. 9 (2023), p. 9605-9638
- Full Text:
- Reviewed:
- Description: Internet of Things (IoT) images are captivating growing attention because of their wide range of applications which requires visual analysis to drive automation. However, IoT images are predominantly captured from outdoor environments and thus are inherently impacted by the camera and environmental parameters which can adversely affect corresponding applications. Deep Learning (DL) has been widely adopted in the field of image processing and computer vision and can reduce the impact of these parameters on IoT images. Albeit, there are many DL-based techniques available in the current literature for analyzing and reducing the environmental and camera impacts on IoT images. However, to the best of our knowledge, no survey paper presents state-of-the-art DL-based approaches for this purpose. Motivated by this, for the first time, we present a Systematic Literature Review (SLR) of existing DL techniques available for analyzing and reducing environmental and camera lens impacts on IoT images. As part of this SLR, firstly, we reiterate and highlight the significance of IoT images in their respective applications. Secondly, we describe the DL techniques employed for assessing the environmental and camera lens distortion impacts on IoT images. Thirdly, we illustrate how DL can be effective in reducing the impact of environmental and camera lens distortion in IoT images. Finally, along with the critical reflection on the advantages and limitations of the techniques, we also present ways to address the research challenges of existing techniques and identify some further researches to advance the relevant research areas. © 2023, The Author(s).
- Authors: Kaur, Roopdeep , Karmakar, Gour , Xia, Feng , Imran, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Artificial Intelligence Review Vol. 56, no. 9 (2023), p. 9605-9638
- Full Text:
- Reviewed:
- Description: Internet of Things (IoT) images are captivating growing attention because of their wide range of applications which requires visual analysis to drive automation. However, IoT images are predominantly captured from outdoor environments and thus are inherently impacted by the camera and environmental parameters which can adversely affect corresponding applications. Deep Learning (DL) has been widely adopted in the field of image processing and computer vision and can reduce the impact of these parameters on IoT images. Albeit, there are many DL-based techniques available in the current literature for analyzing and reducing the environmental and camera impacts on IoT images. However, to the best of our knowledge, no survey paper presents state-of-the-art DL-based approaches for this purpose. Motivated by this, for the first time, we present a Systematic Literature Review (SLR) of existing DL techniques available for analyzing and reducing environmental and camera lens impacts on IoT images. As part of this SLR, firstly, we reiterate and highlight the significance of IoT images in their respective applications. Secondly, we describe the DL techniques employed for assessing the environmental and camera lens distortion impacts on IoT images. Thirdly, we illustrate how DL can be effective in reducing the impact of environmental and camera lens distortion in IoT images. Finally, along with the critical reflection on the advantages and limitations of the techniques, we also present ways to address the research challenges of existing techniques and identify some further researches to advance the relevant research areas. © 2023, The Author(s).
Deep learning and federated learning for screening COVID-19 : a review
- Mondal, M., Bharati, Subrato, Podder, Prajoy, Kamruzzaman, Joarder
- Authors: Mondal, M. , Bharati, Subrato , Podder, Prajoy , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article , Review
- Relation: BioMedInformatics Vol. 3, no. 3 (2023), p. 691-713
- Full Text:
- Reviewed:
- Description: Since December 2019, a novel coronavirus disease (COVID-19) has infected millions of individuals. This paper conducts a thorough study of the use of deep learning (DL) and federated learning (FL) approaches to COVID-19 screening. To begin, an evaluation of research articles published between 1 January 2020 and 28 June 2023 is presented, considering the preferred reporting items of systematic reviews and meta-analysis (PRISMA) guidelines. The review compares various datasets on medical imaging, including X-ray, computed tomography (CT) scans, and ultrasound images, in terms of the number of images, COVID-19 samples, and classes in the datasets. Following that, a description of existing DL algorithms applied to various datasets is offered. Additionally, a summary of recent work on FL for COVID-19 screening is provided. Efforts to improve the quality of FL models are comprehensively reviewed and objectively evaluated. © 2023 by the authors.
- Authors: Mondal, M. , Bharati, Subrato , Podder, Prajoy , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article , Review
- Relation: BioMedInformatics Vol. 3, no. 3 (2023), p. 691-713
- Full Text:
- Reviewed:
- Description: Since December 2019, a novel coronavirus disease (COVID-19) has infected millions of individuals. This paper conducts a thorough study of the use of deep learning (DL) and federated learning (FL) approaches to COVID-19 screening. To begin, an evaluation of research articles published between 1 January 2020 and 28 June 2023 is presented, considering the preferred reporting items of systematic reviews and meta-analysis (PRISMA) guidelines. The review compares various datasets on medical imaging, including X-ray, computed tomography (CT) scans, and ultrasound images, in terms of the number of images, COVID-19 samples, and classes in the datasets. Following that, a description of existing DL algorithms applied to various datasets is offered. Additionally, a summary of recent work on FL for COVID-19 screening is provided. Efforts to improve the quality of FL models are comprehensively reviewed and objectively evaluated. © 2023 by the authors.
Defending SDN against packet injection attacks using deep learning
- Phu, Anh, Li, Bo, Ullah, Faheem, Ul Huque, Tanvir, Naha, Ranesh, Babar, Muhammad, Nguyen, Hung
- Authors: Phu, Anh , Li, Bo , Ullah, Faheem , Ul Huque, Tanvir , Naha, Ranesh , Babar, Muhammad , Nguyen, Hung
- Date: 2023
- Type: Text , Journal article
- Relation: Computer Networks Vol. 234, no. (2023), p.
- Full Text:
- Reviewed:
- Description: The (logically) centralized architecture of software-defined networks makes them an easy target for packet injection attacks. In these attacks, the attacker injects malicious packets into the SDN network to affect the services and performance of the SDN controller and overflows the capacity of the SDN switches. Such attacks have been shown to ultimately stop the network functioning in real-time, leading to network breakdowns. There have been significant works on detecting and defending against similar DoS attacks in non-SDN networks, but detection and protection techniques for SDN against packet injection attacks are still in their infancy. Furthermore, many of the proposed solutions have been shown to be easily bypassed by simple modifications to the attacking packets or by altering the attacking profile. In this paper, we develop novel Graph Convolutional Neural Network models and algorithms for grouping network nodes/users into security classes by learning from network data. We start with two simple classes — nodes that engage in suspicious packet injection attacks and nodes that are not. From these classes, we then partition the network into separate segments with different security policies using distributed Ryu controllers in an SDN network. We show in experiments on an emulated SDN that our detection solution outperforms alternative approaches with above 99% detection accuracy for various types (both old and new) of injection attacks. More importantly, our mitigation solution maintains continuous functions of non-compromised nodes while isolating compromised/suspicious nodes in real-time. All code and data are publicly available for the reproducibility of our results. © 2023 The Author(s)
- Authors: Phu, Anh , Li, Bo , Ullah, Faheem , Ul Huque, Tanvir , Naha, Ranesh , Babar, Muhammad , Nguyen, Hung
- Date: 2023
- Type: Text , Journal article
- Relation: Computer Networks Vol. 234, no. (2023), p.
- Full Text:
- Reviewed:
- Description: The (logically) centralized architecture of software-defined networks makes them an easy target for packet injection attacks. In these attacks, the attacker injects malicious packets into the SDN network to affect the services and performance of the SDN controller and overflows the capacity of the SDN switches. Such attacks have been shown to ultimately stop the network functioning in real-time, leading to network breakdowns. There have been significant works on detecting and defending against similar DoS attacks in non-SDN networks, but detection and protection techniques for SDN against packet injection attacks are still in their infancy. Furthermore, many of the proposed solutions have been shown to be easily bypassed by simple modifications to the attacking packets or by altering the attacking profile. In this paper, we develop novel Graph Convolutional Neural Network models and algorithms for grouping network nodes/users into security classes by learning from network data. We start with two simple classes — nodes that engage in suspicious packet injection attacks and nodes that are not. From these classes, we then partition the network into separate segments with different security policies using distributed Ryu controllers in an SDN network. We show in experiments on an emulated SDN that our detection solution outperforms alternative approaches with above 99% detection accuracy for various types (both old and new) of injection attacks. More importantly, our mitigation solution maintains continuous functions of non-compromised nodes while isolating compromised/suspicious nodes in real-time. All code and data are publicly available for the reproducibility of our results. © 2023 The Author(s)
Depth-based sampling and steering constraints for memoryless local planners
- Nguyen, Binh, Nguyen, Linh, Choudhury, Tanveer, Keogh, Kathleen, Murshed, Manzur
- Authors: Nguyen, Binh , Nguyen, Linh , Choudhury, Tanveer , Keogh, Kathleen , Murshed, Manzur
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Intelligent and Robotic Systems: Theory and Applications Vol. 109, no. 3 (2023), p.
- Full Text:
- Reviewed:
- Description: By utilizing only depth information, the paper introduces a novel two-stage planning approach that enhances computational efficiency and planning performances for memoryless local planners. First, a depth-based sampling technique is proposed to identify and eliminate a specific type of in-collision trajectories among sampled candidates. Specifically, all trajectories that have obscured endpoints are found through querying the depth values and will then be excluded from the sampled set, which can significantly reduce the computational workload required in collision checking. Subsequently, we apply a tailored local planning algorithm that employs a direction cost function and a depth-based steering mechanism to prevent the robot from being trapped in local minima. Our planning algorithm is theoretically proven to be complete in convex obstacle scenarios. To validate the effectiveness of our DEpth-based both Sampling and Steering (DESS) approaches, we conducted experiments in simulated environments where a quadrotor flew through cluttered regions with multiple various-sized obstacles. The experimental results show that DESS significantly reduces computation time in local planning compared to the uniform sampling method, resulting in the planned trajectory with a lower minimized cost. More importantly, our success rates for navigation to different destinations in testing scenarios are improved considerably compared to the fixed-yawing approach. © 2023, The Author(s).
- Authors: Nguyen, Binh , Nguyen, Linh , Choudhury, Tanveer , Keogh, Kathleen , Murshed, Manzur
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Intelligent and Robotic Systems: Theory and Applications Vol. 109, no. 3 (2023), p.
- Full Text:
- Reviewed:
- Description: By utilizing only depth information, the paper introduces a novel two-stage planning approach that enhances computational efficiency and planning performances for memoryless local planners. First, a depth-based sampling technique is proposed to identify and eliminate a specific type of in-collision trajectories among sampled candidates. Specifically, all trajectories that have obscured endpoints are found through querying the depth values and will then be excluded from the sampled set, which can significantly reduce the computational workload required in collision checking. Subsequently, we apply a tailored local planning algorithm that employs a direction cost function and a depth-based steering mechanism to prevent the robot from being trapped in local minima. Our planning algorithm is theoretically proven to be complete in convex obstacle scenarios. To validate the effectiveness of our DEpth-based both Sampling and Steering (DESS) approaches, we conducted experiments in simulated environments where a quadrotor flew through cluttered regions with multiple various-sized obstacles. The experimental results show that DESS significantly reduces computation time in local planning compared to the uniform sampling method, resulting in the planned trajectory with a lower minimized cost. More importantly, our success rates for navigation to different destinations in testing scenarios are improved considerably compared to the fixed-yawing approach. © 2023, The Author(s).
Determination of munsell soil colour using smartphones
- Nodi, Sadia, Paul, Manoranjan, Robinson, Nathan, Wang, Liang, Rehman, Sabih
- Authors: Nodi, Sadia , Paul, Manoranjan , Robinson, Nathan , Wang, Liang , Rehman, Sabih
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 6 (2023), p.
- Full Text:
- Reviewed:
- Description: Soil colour is one of the most important factors in agriculture for monitoring soil health and determining its properties. For this purpose, Munsell soil colour charts are widely used by archaeologists, scientists, and farmers. The process of determining soil colour from the chart is subjective and error-prone. In this study, we used popular smartphones to capture soil colours from images in the Munsell Soil Colour Book (MSCB) to determine the colour digitally. These captured soil colours are then compared with the true colour determined using a commonly used sensor (Nix Pro-2). We have observed that there are colour reading discrepancies between smartphone and Nix Pro-provided readings. To address this issue, we investigated different colour models and finally introduced a colour-intensity relationship between the images captured by Nix Pro and smartphones by exploring different distance functions. Thus, the aim of this study is to determine the Munsell soil colour accurately from the MSCB by adjusting the pixel intensity of the smartphone-captured images. Without any adjustment when the accuracy of individual Munsell soil colour determination is only (Formula presented.) for the top 5 predictions, the accuracy of the proposed method is (Formula presented.), which is significant. © 2023 by the authors.
- Authors: Nodi, Sadia , Paul, Manoranjan , Robinson, Nathan , Wang, Liang , Rehman, Sabih
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 6 (2023), p.
- Full Text:
- Reviewed:
- Description: Soil colour is one of the most important factors in agriculture for monitoring soil health and determining its properties. For this purpose, Munsell soil colour charts are widely used by archaeologists, scientists, and farmers. The process of determining soil colour from the chart is subjective and error-prone. In this study, we used popular smartphones to capture soil colours from images in the Munsell Soil Colour Book (MSCB) to determine the colour digitally. These captured soil colours are then compared with the true colour determined using a commonly used sensor (Nix Pro-2). We have observed that there are colour reading discrepancies between smartphone and Nix Pro-provided readings. To address this issue, we investigated different colour models and finally introduced a colour-intensity relationship between the images captured by Nix Pro and smartphones by exploring different distance functions. Thus, the aim of this study is to determine the Munsell soil colour accurately from the MSCB by adjusting the pixel intensity of the smartphone-captured images. Without any adjustment when the accuracy of individual Munsell soil colour determination is only (Formula presented.) for the top 5 predictions, the accuracy of the proposed method is (Formula presented.), which is significant. © 2023 by the authors.