Looking beyond people, equipment and environment : Is a systems theory model of accident causation required to understand injuries and near misses during outdoor activities?
- Goode, Natassia, Salmon, Paul, Lenne, Michael, Finch, Caroline
- Authors: Goode, Natassia , Salmon, Paul , Lenne, Michael , Finch, Caroline
- Date: 2015
- Type: Text , Conference paper
- Relation: 6th International Conference on Applied Human Factors and Ergonomics (Ahfe 2015) and the Affiliated Conferences, Ahfe 2015; Las Vegas, USA; 26th-30th July 2015; published in Procedia Manufacturing Vol. 3, p. 1125-1131
- Relation: http://purl.org/au-research/grants/nhmrc/1058737
- Full Text:
- Reviewed:
- Description: The National Incident Database (NID) provides a standardised, industry-wide, approach to incident reporting for the outdoor sector in New Zealand (NZ). The aim of this study was to determine whether the NID contributing factor categories (i. e. people, equipment and environment) are sufficient for classifying the data that has been collected on accident causation by the NID, or whether a systems theory framework is required. A sample of injury and near miss reports (n = 228) were extracted from the NID and analysed. All contributing factors identified were classified according to Rasmussen's (1997) Risk Management Framework (RRMF), which was adapted to describe the " led outdoor activity system". In total, 58 different contributing factor categories were identified across the 228 incidents. Factors were classified across all levels of the framework, which indicates that the NID categories are inadequate. The findings also demonstrate that RRMF is appropriate for classifying the contributing factors involved in less severe injuries and near misses that do not have in-depth investigations associated with them. (C) 2015 The Authors. Published by Elsevier B.V.
- Authors: Goode, Natassia , Salmon, Paul , Lenne, Michael , Finch, Caroline
- Date: 2015
- Type: Text , Conference paper
- Relation: 6th International Conference on Applied Human Factors and Ergonomics (Ahfe 2015) and the Affiliated Conferences, Ahfe 2015; Las Vegas, USA; 26th-30th July 2015; published in Procedia Manufacturing Vol. 3, p. 1125-1131
- Relation: http://purl.org/au-research/grants/nhmrc/1058737
- Full Text:
- Reviewed:
- Description: The National Incident Database (NID) provides a standardised, industry-wide, approach to incident reporting for the outdoor sector in New Zealand (NZ). The aim of this study was to determine whether the NID contributing factor categories (i. e. people, equipment and environment) are sufficient for classifying the data that has been collected on accident causation by the NID, or whether a systems theory framework is required. A sample of injury and near miss reports (n = 228) were extracted from the NID and analysed. All contributing factors identified were classified according to Rasmussen's (1997) Risk Management Framework (RRMF), which was adapted to describe the " led outdoor activity system". In total, 58 different contributing factor categories were identified across the 228 incidents. Factors were classified across all levels of the framework, which indicates that the NID categories are inadequate. The findings also demonstrate that RRMF is appropriate for classifying the contributing factors involved in less severe injuries and near misses that do not have in-depth investigations associated with them. (C) 2015 The Authors. Published by Elsevier B.V.
As simple as pressing a button? A review of the literature on BigBlueButton
- Authors: Ukoha, Chukwuma
- Date: 2021
- Type: Text , Conference paper
- Relation: 6th Information Systems International Conference, ISICO 2021, Virtual, Online 7 August 2021through 8 August 2021, Procedia Computer Science Vol. 197, p. 503-511
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- Description: BigBlueButton is an open source virtual classroom software. Since this software was released in 2009, many studies have explored how to use it, especially for e-learning. However, to date, there is no published systematic synthesis of the relevant literature on the subject. This literature review appraises the effectiveness of BigBlueButton in educational settings and pulls relevant pieces of information together into a readable format. The main conclusion is that BigBlueButton is intuitive, interoperable with other software and has the potential to positively affect the learning performance of students. Despite the features and functionalities of BigBlueButton, several limitations are apparent: web conference educators have less control over online teaching compared with their face-to-face counterparts, practical subjects are difficult to teach through web conferencing, technical challenges may affect web-conferencing sessions, web conferencing requires skills additional to those of conventional teaching, cultural differences may affect students' attitudes towards web conference-based learning and educators that teach through web conferencing may feel isolated in their role, both geographically and collegially. By reviewing the features, potential impacts and limitations of BigBlueButton, this study contributes to the growing literature on web conferencing systems and provides insights into the role of BigBlueButton in e-learning. © 2021 The Authors. Published by Elsevier B.V.
- Authors: Ukoha, Chukwuma
- Date: 2021
- Type: Text , Conference paper
- Relation: 6th Information Systems International Conference, ISICO 2021, Virtual, Online 7 August 2021through 8 August 2021, Procedia Computer Science Vol. 197, p. 503-511
- Full Text:
- Reviewed:
- Description: BigBlueButton is an open source virtual classroom software. Since this software was released in 2009, many studies have explored how to use it, especially for e-learning. However, to date, there is no published systematic synthesis of the relevant literature on the subject. This literature review appraises the effectiveness of BigBlueButton in educational settings and pulls relevant pieces of information together into a readable format. The main conclusion is that BigBlueButton is intuitive, interoperable with other software and has the potential to positively affect the learning performance of students. Despite the features and functionalities of BigBlueButton, several limitations are apparent: web conference educators have less control over online teaching compared with their face-to-face counterparts, practical subjects are difficult to teach through web conferencing, technical challenges may affect web-conferencing sessions, web conferencing requires skills additional to those of conventional teaching, cultural differences may affect students' attitudes towards web conference-based learning and educators that teach through web conferencing may feel isolated in their role, both geographically and collegially. By reviewing the features, potential impacts and limitations of BigBlueButton, this study contributes to the growing literature on web conferencing systems and provides insights into the role of BigBlueButton in e-learning. © 2021 The Authors. Published by Elsevier B.V.
Real-time distributed trajectory planning for mobile robots
- Nguyen, Binh, Nghiem, Truong, Nguyen, Linh, Nguyen, Anh, Nguyen, Thang
- Authors: Nguyen, Binh , Nghiem, Truong , Nguyen, Linh , Nguyen, Anh , Nguyen, Thang
- Date: 2023
- Type: Text , Conference paper
- Relation: 22nd IFAC World Congress Vol. 56, p. 2152-2157
- Full Text:
- Reviewed:
- Description: Efficiently planning trajectories for nonholonomic mobile robots in formation tracking is a fundamental yet challenging problem. Nonholonomic constraints, complexity in collision avoidance, and limited computing resources prevent the robots from being practically deployed in realistic applications. This paper addresses these difficulties by modeling each mobile platform as a nonholonomic motion and formulating trajectory planning as an optimization problem using model predictive control (MPC). That is, the optimization problem is subject to both nonholonomic motions and collision avoidance. To reduce computing costs in real time, the nonholonomic constraints are convexified by finding the closest nominal points to the nonholonomic motion, which are then incorporated into a convex optimization problem. Additionally, the predicted values from the previous MPC step are utilized to form linear avoidance conditions for the next step, preventing collisions among robots. The formulated optimization problem is solved by the alternating direction method of multiplier (ADMM) in a distributed manner, which makes the proposed trajectory planning method scalable. More importantly, the convergence of the proposed planning algorithm is theoretically proved while its effectiveness is validated in a synthetic environment. Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
- Authors: Nguyen, Binh , Nghiem, Truong , Nguyen, Linh , Nguyen, Anh , Nguyen, Thang
- Date: 2023
- Type: Text , Conference paper
- Relation: 22nd IFAC World Congress Vol. 56, p. 2152-2157
- Full Text:
- Reviewed:
- Description: Efficiently planning trajectories for nonholonomic mobile robots in formation tracking is a fundamental yet challenging problem. Nonholonomic constraints, complexity in collision avoidance, and limited computing resources prevent the robots from being practically deployed in realistic applications. This paper addresses these difficulties by modeling each mobile platform as a nonholonomic motion and formulating trajectory planning as an optimization problem using model predictive control (MPC). That is, the optimization problem is subject to both nonholonomic motions and collision avoidance. To reduce computing costs in real time, the nonholonomic constraints are convexified by finding the closest nominal points to the nonholonomic motion, which are then incorporated into a convex optimization problem. Additionally, the predicted values from the previous MPC step are utilized to form linear avoidance conditions for the next step, preventing collisions among robots. The formulated optimization problem is solved by the alternating direction method of multiplier (ADMM) in a distributed manner, which makes the proposed trajectory planning method scalable. More importantly, the convergence of the proposed planning algorithm is theoretically proved while its effectiveness is validated in a synthetic environment. Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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