An exploration of trolling behaviours in Australian adolescents : an online survey
- Marrington, Jessica, March, Evita, Murray, Sarah, Jeffries, Carla, Machin, Tanya, March, Sonja
- Authors: Marrington, Jessica , March, Evita , Murray, Sarah , Jeffries, Carla , Machin, Tanya , March, Sonja
- Date: 2023
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 18, no. 4 April (2023), p.
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- Description: To understand why people “troll” (i.e., engage in disruptive online behaviour intended to provoke and distress for one’s own amusement), researchers have explored a range of individual differences. These studies have primarily been conducted in adult samples, despite adolescents being a particularly vulnerable group with regards to both being trolled and trolling others. In this study we aimed to (1) explore Australian adolescents’ experiences of trolling, and (2) replicate adult research that has constructed a psychological profile of the Internet troll by examining the utility of personality traits (psychopathy and sadism), self-esteem, empathy (cognitive and affective), and social rewards (negative social potency) to predict adolescents’ trolling behaviours. A sample of 157 Australian adolescents (40.8% male, 58% female, 0.6% non-binary) aged 13–18 years (M = 15.58, SD = 1.71) completed the Global Assessment of Internet Trolling-Revised, Adolescent Measure of Empathy and Sympathy, Rosenberg Self-Esteem Scale, Youth Psychopathy Traits Inventory-Short Version, Social Rewards Questionnaire, Short Sadistic Impulse Scale, and a series of questions related to the experience of trolling. Results showed in the past year, 24.2% of Australian adolescents reported being trolled and 13.4% reported having trolled others. Gender, psychopathy, sadism, self-esteem, cognitive empathy, affective empathy, and “negative social potency” (i.e., enjoyment of antisocial rewards) combined, explained 30.7% of variance in adolescents’ trolling behaviours (p < .001). When accounting for shared variance, gender (male), high psychopathy, and high negative social potency were significant predictors of trolling, aligning with findings of adult samples. Contrary to adult samples, sadism was not a unique predictor of adolescents’ trolling. For adolescents, the variance in trolling explained by sadism was nonsignificant when controlling for negative social potency. These similarities, and differences, in predictors of trolling across adult and adolescent samples may play a critical role in the development of targeted interventions to prevent or manage trolling. © 2023 Marrington et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Authors: Marrington, Jessica , March, Evita , Murray, Sarah , Jeffries, Carla , Machin, Tanya , March, Sonja
- Date: 2023
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 18, no. 4 April (2023), p.
- Full Text:
- Reviewed:
- Description: To understand why people “troll” (i.e., engage in disruptive online behaviour intended to provoke and distress for one’s own amusement), researchers have explored a range of individual differences. These studies have primarily been conducted in adult samples, despite adolescents being a particularly vulnerable group with regards to both being trolled and trolling others. In this study we aimed to (1) explore Australian adolescents’ experiences of trolling, and (2) replicate adult research that has constructed a psychological profile of the Internet troll by examining the utility of personality traits (psychopathy and sadism), self-esteem, empathy (cognitive and affective), and social rewards (negative social potency) to predict adolescents’ trolling behaviours. A sample of 157 Australian adolescents (40.8% male, 58% female, 0.6% non-binary) aged 13–18 years (M = 15.58, SD = 1.71) completed the Global Assessment of Internet Trolling-Revised, Adolescent Measure of Empathy and Sympathy, Rosenberg Self-Esteem Scale, Youth Psychopathy Traits Inventory-Short Version, Social Rewards Questionnaire, Short Sadistic Impulse Scale, and a series of questions related to the experience of trolling. Results showed in the past year, 24.2% of Australian adolescents reported being trolled and 13.4% reported having trolled others. Gender, psychopathy, sadism, self-esteem, cognitive empathy, affective empathy, and “negative social potency” (i.e., enjoyment of antisocial rewards) combined, explained 30.7% of variance in adolescents’ trolling behaviours (p < .001). When accounting for shared variance, gender (male), high psychopathy, and high negative social potency were significant predictors of trolling, aligning with findings of adult samples. Contrary to adult samples, sadism was not a unique predictor of adolescents’ trolling. For adolescents, the variance in trolling explained by sadism was nonsignificant when controlling for negative social potency. These similarities, and differences, in predictors of trolling across adult and adolescent samples may play a critical role in the development of targeted interventions to prevent or manage trolling. © 2023 Marrington et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Yip, Wai, Kho, Antony, Ooi, Ean, Ooi, Ean Tat
- Authors: Yip, Wai , Kho, Antony , Ooi, Ean , Ooi, Ean Tat
- Date: 2023
- Type: Text , Journal article
- Relation: Medical Engineering and Physics Vol. 112, no. (2023), p.
- Full Text: false
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- Description: No-touch bipolar radiofrequency ablation (bRFA) is known to produce incomplete tumour ablation with a ‘butterfly-shaped’ coagulation zone when the interelectrode distance exceeds a certain threshold. Although non-confluent coagulation zone can be avoided by not implementing the no-touch mode, doing so exposes the patient to the risk of tumour track seeding. The present study investigates if prior infusion of saline into the tissue can overcome the issues of non-confluent or butterfly-shaped coagulation. A computational modelling approach based on the finite element method was carried out. A two-compartment model comprising the tumour that is surrounded by healthy liver tissue was developed. Three cases were considered; i) saline infusion into the tumour centre; ii) one-sided saline infusion outside the tumour; and iii) two-sided saline infusion outside the tumour. For each case, three different saline volumes were considered, i.e. 6, 14 and 22 ml. Saline concentration was set to 15% w/v. Numerical results showed that saline infusion into the tumour centre can overcome the butterfly-shaped coagulation only if the infusion volume is sufficient. On the other hand, one-sided infusion outside the tumour did not overcome this. Two-sided infusion outside the tumour produced confluent coagulation zone with the largest volume. Results obtained from the present study suggest that saline infusion, when carried out correctly, can be used to effectively eradicate liver cancer. This presents a practical solution to address non-confluent coagulation zone typical of that during two-probe bRFA treatment. © 2023 IPEM
An intelligent heart disease prediction system based on swarm-artificial neural network
- Nandy, Sudarshan, Adhikari, Mainak, Balasubramanian, Venki, Menon, Varun, Li, Xingwang, Zakarya, Muhammad
- Authors: Nandy, Sudarshan , Adhikari, Mainak , Balasubramanian, Venki , Menon, Varun , Li, Xingwang , Zakarya, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 35, no. 20 (2023), p. 14723-14737
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- Description: The accurate prediction of cardiovascular disease is an essential and challenging task to treat a patient efficiently before occurring a heart attack. In recent times, various intelligent healthcare frameworks have been designed with different machine learning and swarm optimization techniques for cardiovascular disease prediction. However, most of the existing strategies failed to achieve higher accuracy for cardiovascular disease prediction due to the lack of data-recognized techniques and proper prediction methodology. Motivated by the existing challenges, in this paper, we propose an intelligent healthcare framework for predicting cardiovascular heart disease based on Swarm-Artificial Neural Network (Swarm-ANN) strategy. Initially, the proposed Swarm-ANN strategy randomly generates predefined numbers of Neural Networks (NNs) for training and evaluating the framework based on their solution consistency. Additionally, the NN populations are trained by two stages of weight changes and their weight is adjusted by a newly designed heuristic formulation. Finally, the weight of the neurons is modified by sharing the global best weight with other neurons and predicts the accuracy of cardiovascular disease. The proposed Swarm-ANN strategy achieves 95.78% accuracy while predicting the cardiovascular disease of the patients from a benchmark dataset. The simulation results exhibit that the proposed Swarm-ANN strategy outperforms the standard learning techniques in terms of various performance matrices. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
An optimal scheduling method in iot-fog-cloud network using combination of aquila optimizer and african vultures optimization
- Liu, Qing, Kosarirad, Houman, Meisami, Sajad, Alnowibet, Khalid, Hoshyar, Azadeh
- Authors: Liu, Qing , Kosarirad, Houman , Meisami, Sajad , Alnowibet, Khalid , Hoshyar, Azadeh
- Date: 2023
- Type: Text , Journal article
- Relation: Processes Vol. 11, no. 4 (2023), p.
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- Description: Today, fog and cloud computing environments can be used to further develop the Internet of Things (IoT). In such environments, task scheduling is very efficient for executing user requests, and the optimal scheduling of IoT task requests increases the productivity of the IoT-fog-cloud system. In this paper, a hybrid meta-heuristic (MH) algorithm is developed to schedule the IoT requests in IoT-fog-cloud networks using the Aquila Optimizer (AO) and African Vultures Optimization Algorithm (AVOA) called AO_AVOA. In AO_AVOA, the exploration phase of AVOA is improved by using AO operators to obtain the best solution during the process of finding the optimal scheduling solution. A comparison between AO_AVOA and methods of AVOA, AO, Firefly Algorithm (FA), particle swarm optimization (PSO), and Harris Hawks Optimization (HHO) according to performance metrics such as makespan and throughput shows the high ability of AO_AVOA to solve the scheduling problem in IoT-fog-cloud networks. © 2023 by the authors.
- Authors: Liu, Qing , Kosarirad, Houman , Meisami, Sajad , Alnowibet, Khalid , Hoshyar, Azadeh
- Date: 2023
- Type: Text , Journal article
- Relation: Processes Vol. 11, no. 4 (2023), p.
- Full Text:
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- Description: Today, fog and cloud computing environments can be used to further develop the Internet of Things (IoT). In such environments, task scheduling is very efficient for executing user requests, and the optimal scheduling of IoT task requests increases the productivity of the IoT-fog-cloud system. In this paper, a hybrid meta-heuristic (MH) algorithm is developed to schedule the IoT requests in IoT-fog-cloud networks using the Aquila Optimizer (AO) and African Vultures Optimization Algorithm (AVOA) called AO_AVOA. In AO_AVOA, the exploration phase of AVOA is improved by using AO operators to obtain the best solution during the process of finding the optimal scheduling solution. A comparison between AO_AVOA and methods of AVOA, AO, Firefly Algorithm (FA), particle swarm optimization (PSO), and Harris Hawks Optimization (HHO) according to performance metrics such as makespan and throughput shows the high ability of AO_AVOA to solve the scheduling problem in IoT-fog-cloud networks. © 2023 by the authors.
An optimized hybrid deep intrusion detection model (HD-IDM) for enhancing network security
- Ahmad, Iftikhar, Imran, Muhammad, Qayyum, Abdul, Ramzan, Muhammad, Alassafi, Madini
- Authors: Ahmad, Iftikhar , Imran, Muhammad , Qayyum, Abdul , Ramzan, Muhammad , Alassafi, Madini
- Date: 2023
- Type: Text , Journal article
- Relation: Mathematics Vol. 11, no. 21 (2023), p.
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- Description: Detecting cyber intrusions in network traffic is a tough task for cybersecurity. Current methods struggle with the complexity of understanding patterns in network data. To solve this, we present the Hybrid Deep Learning Intrusion Detection Model (HD-IDM), a new way that combines GRU and LSTM classifiers. GRU is good at catching quick patterns, while LSTM handles long-term ones. HD-IDM blends these models using weighted averaging, boosting accuracy, especially with complex patterns. We tested HD-IDM on four datasets: CSE-CIC-IDS2017, CSE-CIC-IDS2018, NSL KDD, and CIC-DDoS2019. The HD-IDM classifier achieved remarkable performance metrics on all datasets. It attains an outstanding accuracy of 99.91%, showcasing its consistent precision across the dataset. With an impressive precision of 99.62%, it excels in accurately categorizing positive cases, crucial for minimizing false positives. Additionally, maintaining a high recall of 99.43%, it effectively identifies the majority of actual positive cases while minimizing false negatives. The F1-score of 99.52% emphasizes its robustness, making it the top choice for classification tasks requiring precision and reliability. It is particularly good at ROC and precision/recall curves, discriminating normal and harmful network activities. While HD-IDM is promising, it has limits. It needs labeled data and may struggle with new intrusion methods. Future work should find ways to handle unlabeled data and adapt to emerging threats. Also, making HD-IDM work faster for real-time use and dealing with scalability challenges is key for its broader use in changing network environments. © 2023 by the authors.
- Authors: Ahmad, Iftikhar , Imran, Muhammad , Qayyum, Abdul , Ramzan, Muhammad , Alassafi, Madini
- Date: 2023
- Type: Text , Journal article
- Relation: Mathematics Vol. 11, no. 21 (2023), p.
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- Description: Detecting cyber intrusions in network traffic is a tough task for cybersecurity. Current methods struggle with the complexity of understanding patterns in network data. To solve this, we present the Hybrid Deep Learning Intrusion Detection Model (HD-IDM), a new way that combines GRU and LSTM classifiers. GRU is good at catching quick patterns, while LSTM handles long-term ones. HD-IDM blends these models using weighted averaging, boosting accuracy, especially with complex patterns. We tested HD-IDM on four datasets: CSE-CIC-IDS2017, CSE-CIC-IDS2018, NSL KDD, and CIC-DDoS2019. The HD-IDM classifier achieved remarkable performance metrics on all datasets. It attains an outstanding accuracy of 99.91%, showcasing its consistent precision across the dataset. With an impressive precision of 99.62%, it excels in accurately categorizing positive cases, crucial for minimizing false positives. Additionally, maintaining a high recall of 99.43%, it effectively identifies the majority of actual positive cases while minimizing false negatives. The F1-score of 99.52% emphasizes its robustness, making it the top choice for classification tasks requiring precision and reliability. It is particularly good at ROC and precision/recall curves, discriminating normal and harmful network activities. While HD-IDM is promising, it has limits. It needs labeled data and may struggle with new intrusion methods. Future work should find ways to handle unlabeled data and adapt to emerging threats. Also, making HD-IDM work faster for real-time use and dealing with scalability challenges is key for its broader use in changing network environments. © 2023 by the authors.
An overview of Australian exercise and sport science degrees
- Kittel, Aden, Stevens, Christopher, Lindsay, Riki, Spittle, Sharna, Spittle, Michael
- Authors: Kittel, Aden , Stevens, Christopher , Lindsay, Riki , Spittle, Sharna , Spittle, Michael
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Education Vol. 8, no. (2023), p.
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- Description: Exercise and Sport Science (EXSS) is a common degree offered at Australian universities, yet there is no systematic overview of this multidisciplinary field of study. This study aimed to determine the broad curriculum content of Australian EXSS degrees by summarizing the units offered, identify most commonly delivered content areas, and capture course information such as work-integrated learning (WIL) requirements and majors offered. Data were gathered through publicly available university course pages, with 30 EXSS courses included and only core units identified. The most common Australian EXSS units were “Exercise Physiology,” “Biomechanics,” “Research Methods and Data Analysis,” “Exercise Prescription and Delivery,” and “Exercise and Sport Psychology.” WIL requirements ranged from 140 to 300 h per course, and five courses offered majors. This study provides an overview of Australian EXSS courses, with the focus on exercise-related components reflecting accreditation requirements. Future research should examine how these courses equip students for the multidisciplinary EXSS industry. Copyright © 2023 Kittel, Stevens, Lindsay, Spittle and Spittle.
- Authors: Kittel, Aden , Stevens, Christopher , Lindsay, Riki , Spittle, Sharna , Spittle, Michael
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Education Vol. 8, no. (2023), p.
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- Description: Exercise and Sport Science (EXSS) is a common degree offered at Australian universities, yet there is no systematic overview of this multidisciplinary field of study. This study aimed to determine the broad curriculum content of Australian EXSS degrees by summarizing the units offered, identify most commonly delivered content areas, and capture course information such as work-integrated learning (WIL) requirements and majors offered. Data were gathered through publicly available university course pages, with 30 EXSS courses included and only core units identified. The most common Australian EXSS units were “Exercise Physiology,” “Biomechanics,” “Research Methods and Data Analysis,” “Exercise Prescription and Delivery,” and “Exercise and Sport Psychology.” WIL requirements ranged from 140 to 300 h per course, and five courses offered majors. This study provides an overview of Australian EXSS courses, with the focus on exercise-related components reflecting accreditation requirements. Future research should examine how these courses equip students for the multidisciplinary EXSS industry. Copyright © 2023 Kittel, Stevens, Lindsay, Spittle and Spittle.
An overview of long covid support services in australia and international clinical guidelines, with a proposed care model in a global context
- Luo, Shiqi, Zheng, Zhen, Bird, Stephen, Plebanski, Magdalena, Figueiredo, Bernardo, Jessup, Rebecca, Stelmach, Wanda, Robinson, Jennifer, Xenos, Sophia, Olasoji, Micheal, Wan, Dawn, Sheahan, Jacob, Itsiopoulos, Catherine
- Authors: Luo, Shiqi , Zheng, Zhen , Bird, Stephen , Plebanski, Magdalena , Figueiredo, Bernardo , Jessup, Rebecca , Stelmach, Wanda , Robinson, Jennifer , Xenos, Sophia , Olasoji, Micheal , Wan, Dawn , Sheahan, Jacob , Itsiopoulos, Catherine
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Public Health Reviews Vol. 44, no. (2023), p.
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- Description: Objective: To identify gaps among Australian Long COVID support services and guidelines alongside recommendations for future health programs. Methods: Electronic databases and seven government health websites were searched for Long COVID-specific programs or clinics available in Australia as well as international and Australian management guidelines. Results: Five Long COVID specific guidelines and sixteen Australian services were reviewed. The majority of Australian services provided multidisciplinary rehabilitation programs with service models generally consistent with international and national guidelines. Most services included physiotherapists and psychologists. While early investigation at week 4 after contraction of COVID-19 is recommended by the Australian, UK and US guidelines, this was not consistently implemented. Conclusion: Besides Long COVID clinics, future solutions should focus on early identification that can be delivered by General Practitioners and all credentialed allied health professions. Study findings highlight an urgent need for innovative care models that address individual patient needs at an affordable cost. We propose a model that focuses on patient-led self-care with further enhancement via multi-disciplinary care tools. Copyright © 2023 Luo, Zheng, Bird, Plebanski, Figueiredo, Jessup, Stelmach, Robinson, Xenos, Olasoji, Wan, Sheahan and Itsiopoulos.
- Authors: Luo, Shiqi , Zheng, Zhen , Bird, Stephen , Plebanski, Magdalena , Figueiredo, Bernardo , Jessup, Rebecca , Stelmach, Wanda , Robinson, Jennifer , Xenos, Sophia , Olasoji, Micheal , Wan, Dawn , Sheahan, Jacob , Itsiopoulos, Catherine
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Public Health Reviews Vol. 44, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Objective: To identify gaps among Australian Long COVID support services and guidelines alongside recommendations for future health programs. Methods: Electronic databases and seven government health websites were searched for Long COVID-specific programs or clinics available in Australia as well as international and Australian management guidelines. Results: Five Long COVID specific guidelines and sixteen Australian services were reviewed. The majority of Australian services provided multidisciplinary rehabilitation programs with service models generally consistent with international and national guidelines. Most services included physiotherapists and psychologists. While early investigation at week 4 after contraction of COVID-19 is recommended by the Australian, UK and US guidelines, this was not consistently implemented. Conclusion: Besides Long COVID clinics, future solutions should focus on early identification that can be delivered by General Practitioners and all credentialed allied health professions. Study findings highlight an urgent need for innovative care models that address individual patient needs at an affordable cost. We propose a model that focuses on patient-led self-care with further enhancement via multi-disciplinary care tools. Copyright © 2023 Luo, Zheng, Bird, Plebanski, Figueiredo, Jessup, Stelmach, Robinson, Xenos, Olasoji, Wan, Sheahan and Itsiopoulos.
An update on the influence of natural climate variability and anthropogenic climate change on tropical cyclones
- Camargo, Suzana, Murakami, Hiroyuki, Bloemendaal, Nadia, Chand, Savin, Deshpande, Medha, Dominguez-Sarmiento, Christian, González-Alemán, Juan, Knutson, Thomas, Lin, I., Moon, Il-Ju, Patricola, Christian, Reed, Kevin, Roberts, Malcolm, Scoccimarro, Enrico, Tam, Chi, Wallace, Elizabeth, Wu, Liguang, Yamada, Yohei, Zhang, Wei, Zhao, Haikun
- Authors: Camargo, Suzana , Murakami, Hiroyuki , Bloemendaal, Nadia , Chand, Savin , Deshpande, Medha , Dominguez-Sarmiento, Christian , González-Alemán, Juan , Knutson, Thomas , Lin, I. , Moon, Il-Ju , Patricola, Christian , Reed, Kevin , Roberts, Malcolm , Scoccimarro, Enrico , Tam, Chi , Wallace, Elizabeth , Wu, Liguang , Yamada, Yohei , Zhang, Wei , Zhao, Haikun
- Date: 2023
- Type: Text , Journal article
- Relation: Tropical Cyclone Research and Review Vol. 12, no. 3 (2023), p. 216-239
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- Description: A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones (IWTC-9) in 2018, improving our understanding of the effect of climate change on tropical cyclones (TCs) and associated hazards and risks. These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change. New modeling and observational studies suggested the potential influence of anthropogenic climate forcings, including greenhouse gases and aerosols, on global and regional TC activity at the decadal and century time scales. However, there are still substantial uncertainties owing to model uncertainty in simulating historical TC decadal variability in the Atlantic, and the limitations of observed TC records. The projected future change in the global number of TCs has become more uncertain since IWTC-9 due to projected increases in TC frequency by a few climate models. A new paradigm, TC seeds, has been proposed, and there is currently a debate on whether seeds can help explain the physical mechanism behind the projected changes in global TC frequency. New studies also highlighted the importance of large-scale environmental fields on TC activity, such as snow cover and air-sea interactions. Future projections on TC translation speed and medicanes are new additional focus topics in our report. Recommendations and future research are proposed relevant to the remaining scientific questions and assisting policymakers. © 2023 The Shanghai Typhoon Institute of China Meteorological Administration
- Authors: Camargo, Suzana , Murakami, Hiroyuki , Bloemendaal, Nadia , Chand, Savin , Deshpande, Medha , Dominguez-Sarmiento, Christian , González-Alemán, Juan , Knutson, Thomas , Lin, I. , Moon, Il-Ju , Patricola, Christian , Reed, Kevin , Roberts, Malcolm , Scoccimarro, Enrico , Tam, Chi , Wallace, Elizabeth , Wu, Liguang , Yamada, Yohei , Zhang, Wei , Zhao, Haikun
- Date: 2023
- Type: Text , Journal article
- Relation: Tropical Cyclone Research and Review Vol. 12, no. 3 (2023), p. 216-239
- Full Text:
- Reviewed:
- Description: A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones (IWTC-9) in 2018, improving our understanding of the effect of climate change on tropical cyclones (TCs) and associated hazards and risks. These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change. New modeling and observational studies suggested the potential influence of anthropogenic climate forcings, including greenhouse gases and aerosols, on global and regional TC activity at the decadal and century time scales. However, there are still substantial uncertainties owing to model uncertainty in simulating historical TC decadal variability in the Atlantic, and the limitations of observed TC records. The projected future change in the global number of TCs has become more uncertain since IWTC-9 due to projected increases in TC frequency by a few climate models. A new paradigm, TC seeds, has been proposed, and there is currently a debate on whether seeds can help explain the physical mechanism behind the projected changes in global TC frequency. New studies also highlighted the importance of large-scale environmental fields on TC activity, such as snow cover and air-sea interactions. Future projections on TC translation speed and medicanes are new additional focus topics in our report. Recommendations and future research are proposed relevant to the remaining scientific questions and assisting policymakers. © 2023 The Shanghai Typhoon Institute of China Meteorological Administration
Analysis and design of a cost-effective single-input and regulatable multioutput WPT system
- Li, Xiaofei, Zheng, Fan, Wang, Heshou, Dai, Xin, Sun, Yue, Hu, Jiefeng
- Authors: Li, Xiaofei , Zheng, Fan , Wang, Heshou , Dai, Xin , Sun, Yue , Hu, Jiefeng
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Transactions on Power Electronics Vol. 38, no. 6 (2023), p. 6939-6944
- Full Text: false
- Reviewed:
- Description: In this letter, a single-input and regulatable multioutput wireless power transfer system is presented. In particular, the system uses positive and negative half-wave rectifiers and a synchronous rectifier to realize multiple output channels. Each output channel is controllable, providing a flexible wireless charger to meet various charging requirements. Moreover, this system utilizes the inherent half-wave-rectifier channels (#B and #C) to detect synchronous signals for the rectifiers rather than using additional synchronous detection circuits, thereby leading to a cost-effective system. Finally, a 300 W laboratory prototype is contrasted with three voltage levels, i.e., 48, 30, and 24 V. With the help of the control logic, this system shows excellent robustness against different occasions, such as load variations, input disturbance, and misalignment. The overall efficiency ranges from 86.7% to 90.6%. © 1986-2012 IEEE.
Analysis of microalgal density estimation by using lasso and image texture features
- Nguyen, Linh, Nguyen, Dung, Nguyen, Thang, Nguyen, Binh, Nghiem, Truong
- Authors: Nguyen, Linh , Nguyen, Dung , Nguyen, Thang , Nguyen, Binh , Nghiem, Truong
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 5 (2023), p.
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- Description: Monitoring and estimating the density of microalgae in a closed cultivation system is a critical task in culturing algae since it allows growers to optimally control both nutrients and cultivating conditions. Among the estimation techniques proposed so far, image-based methods, which are less invasive, nondestructive, and more biosecure, are practically preferred. Nevertheless, the premise behind most of those approaches is simply averaging the pixel values of images as inputs of a regression model to predict density values, which may not provide rich information of the microalgae presenting in the images. In this work, we propose to exploit more advanced texture features extracted from captured images, including confidence intervals of means of pixel values, powers of spatial frequencies presenting in images, and entropies accounting for pixel distribution. These diverse features can provide more information of microalgae, which can lead to more accurate estimation results. More importantly, we propose to use the texture features as inputs of a data-driven model based on L1 regularization, called least absolute shrinkage and selection operator (LASSO), where their coefficients are optimized in a manner that prioritizes more informative features. The LASSO model was then employed to efficiently estimate the density of microalgae presenting in a new image. The proposed approach was validated in real-world experiments monitoring the Chlorella vulgaris microalgae strain, where the obtained results demonstrate its outperformance compared with other methods. More specifically, the average error in the estimation obtained by the proposed approach is 1.54, whereas those obtained by the Gaussian process and gray-scale-based methods are 2.16 and 3.68, respectively © 2023 by the authors.
- Authors: Nguyen, Linh , Nguyen, Dung , Nguyen, Thang , Nguyen, Binh , Nghiem, Truong
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 5 (2023), p.
- Full Text:
- Reviewed:
- Description: Monitoring and estimating the density of microalgae in a closed cultivation system is a critical task in culturing algae since it allows growers to optimally control both nutrients and cultivating conditions. Among the estimation techniques proposed so far, image-based methods, which are less invasive, nondestructive, and more biosecure, are practically preferred. Nevertheless, the premise behind most of those approaches is simply averaging the pixel values of images as inputs of a regression model to predict density values, which may not provide rich information of the microalgae presenting in the images. In this work, we propose to exploit more advanced texture features extracted from captured images, including confidence intervals of means of pixel values, powers of spatial frequencies presenting in images, and entropies accounting for pixel distribution. These diverse features can provide more information of microalgae, which can lead to more accurate estimation results. More importantly, we propose to use the texture features as inputs of a data-driven model based on L1 regularization, called least absolute shrinkage and selection operator (LASSO), where their coefficients are optimized in a manner that prioritizes more informative features. The LASSO model was then employed to efficiently estimate the density of microalgae presenting in a new image. The proposed approach was validated in real-world experiments monitoring the Chlorella vulgaris microalgae strain, where the obtained results demonstrate its outperformance compared with other methods. More specifically, the average error in the estimation obtained by the proposed approach is 1.54, whereas those obtained by the Gaussian process and gray-scale-based methods are 2.16 and 3.68, respectively © 2023 by the authors.
Animal population decline and recovery after severe fire: Relating ecological and life history traits with expert estimates of population impacts from the Australian 2019-20 megafires
- Ensbey, Michelle, Legge, Sarah, Jolly, Chris, Garnett, Stephen, Gallagher, Rachael, Lintermans, Mark, Nimmo, Dale, Rumpff, Libby, Scheele, Ben, Whiterod, Nick, Woinarski, John, Ahyong, Shane, Blackmore, Caroline, Bower, Deborah, Burbidge, Allan, Burns, Phoebe, Butler, Gavin, Catullo, Renee, Chapple, David, Dickman, Christopher, Doyle, Katie, Ferris, Jason, Fisher, Diana, Geyle, Hayley, Gillespie, Graeme, Greenlees, Matt, Hohnen, Rosemary, Hoskin, Conrad, Kennard, Mark, King, Alison, Kuchinke, Diana, Law, Brad, Lawler, Ivan, Lawler, Susan, Loyn, Richard, Lunney, Daniel, Lyon, Jarod, MacHunter, Josephine, Mahony, Michael, Mahony, Stephen, McCormack, Rob, Melville, Jane, Menkhorst, Peter, Michael, Damian, Mitchell, Nicola, Mulder, Eridani, Newell, David, Pearce, Luke, Raadik, Tarmo, Rowley, Jodi, Sitters, Holly, Southwell, Darren, Spencer, Ricky, West, Matt, Zukowski, Sylvia
- Authors: Ensbey, Michelle , Legge, Sarah , Jolly, Chris , Garnett, Stephen , Gallagher, Rachael , Lintermans, Mark , Nimmo, Dale , Rumpff, Libby , Scheele, Ben , Whiterod, Nick , Woinarski, John , Ahyong, Shane , Blackmore, Caroline , Bower, Deborah , Burbidge, Allan , Burns, Phoebe , Butler, Gavin , Catullo, Renee , Chapple, David , Dickman, Christopher , Doyle, Katie , Ferris, Jason , Fisher, Diana , Geyle, Hayley , Gillespie, Graeme , Greenlees, Matt , Hohnen, Rosemary , Hoskin, Conrad , Kennard, Mark , King, Alison , Kuchinke, Diana , Law, Brad , Lawler, Ivan , Lawler, Susan , Loyn, Richard , Lunney, Daniel , Lyon, Jarod , MacHunter, Josephine , Mahony, Michael , Mahony, Stephen , McCormack, Rob , Melville, Jane , Menkhorst, Peter , Michael, Damian , Mitchell, Nicola , Mulder, Eridani , Newell, David , Pearce, Luke , Raadik, Tarmo , Rowley, Jodi , Sitters, Holly , Southwell, Darren , Spencer, Ricky , West, Matt , Zukowski, Sylvia
- Date: 2023
- Type: Text , Journal article
- Relation: Biological conservation Vol. 283, no. (2023), p. 110021
- Full Text:
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- Description: Catastrophic megafires can increase extinction risks identifying species priorities for management and policy support is critical for preparing and responding to future fires. However, empirical data on population loss and recovery post-fire, especially megafire, are limited and taxonomically biased. These gaps could be bridged if species' morphological, behavioural, ecological and life history traits indicated their fire responses. Using expert elicitation that estimated population changes following the 2019–20 Australian megafires for 142 terrestrial and aquatic animal species (from every vertebrate class, one invertebrate group), we examined whether expert estimates of fire-related mortality, mortality in the year post-fire, and recovery trajectories over 10 years/three generations post-fire, were related to species traits. Expert estimates for fire-related mortality were lower for species that could potentially flee or shelter from fire, and that associated with fire-prone habitats. Post-fire mortality estimates were linked to diet, diet specialisation, home range size, and susceptibility to introduced herbivores that damage or compete for resources. Longer-term population recovery estimates were linked to diet/habitat specialisation, susceptibility to introduced species species with slower life histories and shorter subadult dispersal distances also had lower recovery estimates. Across animal groups, experts estimated that recovery was poorest for species with pre-fire population decline and more threatened conservation status. Sustained management is likely needed to recover species with habitat and diet specialisations, slower life histories, pre-existing declines and threatened conservation statuses. This study shows that traits could help inform management priorities before and after future megafires, but further empirical data on animal fire response is essential.
- Authors: Ensbey, Michelle , Legge, Sarah , Jolly, Chris , Garnett, Stephen , Gallagher, Rachael , Lintermans, Mark , Nimmo, Dale , Rumpff, Libby , Scheele, Ben , Whiterod, Nick , Woinarski, John , Ahyong, Shane , Blackmore, Caroline , Bower, Deborah , Burbidge, Allan , Burns, Phoebe , Butler, Gavin , Catullo, Renee , Chapple, David , Dickman, Christopher , Doyle, Katie , Ferris, Jason , Fisher, Diana , Geyle, Hayley , Gillespie, Graeme , Greenlees, Matt , Hohnen, Rosemary , Hoskin, Conrad , Kennard, Mark , King, Alison , Kuchinke, Diana , Law, Brad , Lawler, Ivan , Lawler, Susan , Loyn, Richard , Lunney, Daniel , Lyon, Jarod , MacHunter, Josephine , Mahony, Michael , Mahony, Stephen , McCormack, Rob , Melville, Jane , Menkhorst, Peter , Michael, Damian , Mitchell, Nicola , Mulder, Eridani , Newell, David , Pearce, Luke , Raadik, Tarmo , Rowley, Jodi , Sitters, Holly , Southwell, Darren , Spencer, Ricky , West, Matt , Zukowski, Sylvia
- Date: 2023
- Type: Text , Journal article
- Relation: Biological conservation Vol. 283, no. (2023), p. 110021
- Full Text:
- Reviewed:
- Description: Catastrophic megafires can increase extinction risks identifying species priorities for management and policy support is critical for preparing and responding to future fires. However, empirical data on population loss and recovery post-fire, especially megafire, are limited and taxonomically biased. These gaps could be bridged if species' morphological, behavioural, ecological and life history traits indicated their fire responses. Using expert elicitation that estimated population changes following the 2019–20 Australian megafires for 142 terrestrial and aquatic animal species (from every vertebrate class, one invertebrate group), we examined whether expert estimates of fire-related mortality, mortality in the year post-fire, and recovery trajectories over 10 years/three generations post-fire, were related to species traits. Expert estimates for fire-related mortality were lower for species that could potentially flee or shelter from fire, and that associated with fire-prone habitats. Post-fire mortality estimates were linked to diet, diet specialisation, home range size, and susceptibility to introduced herbivores that damage or compete for resources. Longer-term population recovery estimates were linked to diet/habitat specialisation, susceptibility to introduced species species with slower life histories and shorter subadult dispersal distances also had lower recovery estimates. Across animal groups, experts estimated that recovery was poorest for species with pre-fire population decline and more threatened conservation status. Sustained management is likely needed to recover species with habitat and diet specialisations, slower life histories, pre-existing declines and threatened conservation statuses. This study shows that traits could help inform management priorities before and after future megafires, but further empirical data on animal fire response is essential.
Anti-aliasing deep image classifiers using novel depth adaptive blurring and activation function
- Hossain, Md Tahmid, Teng, Shyh, Lu, Guojun, Rahman, Mohammad Arifur, Sohel, Ferdous
- Authors: Hossain, Md Tahmid , Teng, Shyh , Lu, Guojun , Rahman, Mohammad Arifur , Sohel, Ferdous
- Date: 2023
- Type: Text , Journal article
- Relation: Neurocomputing Vol. 536, no. (2023), p. 164-174
- Full Text: false
- Reviewed:
- Description: Deep convolutional networks are vulnerable to image translation or shift, partly due to common down-sampling layers, e.g., max-pooling and strided convolution. These operations violate the Nyquist sampling rate and cause aliasing. The textbook solution is low-pass filtering (blurring) before down-sampling, which can benefit deep networks as well. Even so, non-linearity units, such as ReLU, often re-introduce the problem, suggesting that blurring alone may not suffice. In this work, first, we analyse deep features with Fourier transform and show that Depth Adaptive Blurring is more effective, as opposed to monotonic blurring. To this end, we propose a novel Depth Adaptive Blur-pool (DAB-pool) module to replace existing down-sampling methods. Second, we introduce a novel activation function – with a built-in low pass filter, as an additional measure, to keep the problem from reappearing. From experiments, we observe generalisation on other forms of transformations and corruptions as well, e.g., rotation, scale, and noise. We evaluate our method under three challenging settings: (1) a variety of image translations; (2) adversarial attacks – both
Antisocial and prosocial online behaviour : exploring the roles of the dark and light triads
- March, Evita, Marrington, Jessica
- Authors: March, Evita , Marrington, Jessica
- Date: 2023
- Type: Text , Journal article
- Relation: Current Psychology Vol. 42, no. 2 (2023), p. 1390-1393
- Full Text: false
- Reviewed:
- Larkman, Chelsea, Mellahn, Kathleen, Han, Weifeng, Rose, Miranda
- Authors: Larkman, Chelsea , Mellahn, Kathleen , Han, Weifeng , Rose, Miranda
- Date: 2023
- Type: Text , Journal article
- Relation: Aphasiology Vol. 37, no. 4 (2023), p. 635-657
- Full Text: false
- Reviewed:
- Description: Growing cultural and linguistic diversity globally is increasingly requiring speech pathologists to provide effective and equitable aphasia rehabilitation to clients with whom they do not share a language. Little is known about how rehabilitation is being adapted and provided when a language mismatch arises between the therapist and the client. This scoping review aims to systematically map the evidence related to aphasia rehabilitation when the speech pathologist and the client do not share a language. A comprehensive search was conducted in September 2020. Twenty studies comprising surveys and/or interviews and descriptive publications were reviewed. Speech pathologists frequently report a lack of confidence, skill, and preparation to work with culturally and linguistically diverse clients with aphasia. Furthermore, there is a shortage of published evidence, guidelines, resources, and access to interpreters to support their practice. Further research is needed into aphasia rehabilitation when there is no shared language between client and speech pathologist, with particular attention to the therapy approach selected and adaptations required for the target language and culture. Information is needed concerning how the speech pathologist and interpreter work together, as well as the experiences of interpreters and people with aphasia and their families.
Application of a universal parasite diagnostic test to biological specimens collected from animals
- Lane, Meredith, Kashani, Mitra, Barratt, Joel, Qvarnstrom, Yvonne, Yabsley, Michael, Garrett, Kayla, Bradbury, Richard
- Authors: Lane, Meredith , Kashani, Mitra , Barratt, Joel , Qvarnstrom, Yvonne , Yabsley, Michael , Garrett, Kayla , Bradbury, Richard
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal for Parasitology: Parasites and Wildlife Vol. 20, no. (2023), p. 20-30
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- Description: A previously described universal parasite diagnostic (nUPDx) based on PCR amplification of the 18S rDNA and deep-amplicon sequencing, can detect human blood parasites with a sensitivity comparable to real-time PCR. To date, the efficacy of this assay has only been assessed on human blood. This study assessed the utility of nUPDx for the detection of parasitic infections in animals using blood, tissues, and other biological sample types from mammals, birds, and reptiles, known to be infected with helminth, apicomplexan, or pentastomid parasites (confirmed by microscopy or PCR), as well as negative samples. nUPDx confirmed apicomplexan and/or nematode infections in 24 of 32 parasite-positive mammals, while also identifying several undetected coinfections. nUPDx detected infections in 6 of 13 positive bird and 1 of 2 positive reptile samples. When applied to 10 whole parasite specimens (worms and arthropods), nUPDx identified all to the genus or family level, and detected one incorrect identification made by morphology. Babesia sp. infections were detected in 5 of the 13 samples that were negative by other diagnostic approaches. While nUPDx did not detect PCR/microscopy-confirmed trichomonads or amoebae in cloacal swabs/tissue from 8 birds and 2 reptiles due to primer template mismatches, 4 previously undetected apicomplexans were detected in these samples. Future efforts to improve the utility of the assay should focus on validation against a larger panel of tissue types and animal species. Overall, nUPDx shows promise for use in both veterinary diagnostics and wildlife surveillance, especially because species-specific PCRs can miss unknown or unexpected pathogens. © 2022
- Authors: Lane, Meredith , Kashani, Mitra , Barratt, Joel , Qvarnstrom, Yvonne , Yabsley, Michael , Garrett, Kayla , Bradbury, Richard
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal for Parasitology: Parasites and Wildlife Vol. 20, no. (2023), p. 20-30
- Full Text:
- Reviewed:
- Description: A previously described universal parasite diagnostic (nUPDx) based on PCR amplification of the 18S rDNA and deep-amplicon sequencing, can detect human blood parasites with a sensitivity comparable to real-time PCR. To date, the efficacy of this assay has only been assessed on human blood. This study assessed the utility of nUPDx for the detection of parasitic infections in animals using blood, tissues, and other biological sample types from mammals, birds, and reptiles, known to be infected with helminth, apicomplexan, or pentastomid parasites (confirmed by microscopy or PCR), as well as negative samples. nUPDx confirmed apicomplexan and/or nematode infections in 24 of 32 parasite-positive mammals, while also identifying several undetected coinfections. nUPDx detected infections in 6 of 13 positive bird and 1 of 2 positive reptile samples. When applied to 10 whole parasite specimens (worms and arthropods), nUPDx identified all to the genus or family level, and detected one incorrect identification made by morphology. Babesia sp. infections were detected in 5 of the 13 samples that were negative by other diagnostic approaches. While nUPDx did not detect PCR/microscopy-confirmed trichomonads or amoebae in cloacal swabs/tissue from 8 birds and 2 reptiles due to primer template mismatches, 4 previously undetected apicomplexans were detected in these samples. Future efforts to improve the utility of the assay should focus on validation against a larger panel of tissue types and animal species. Overall, nUPDx shows promise for use in both veterinary diagnostics and wildlife surveillance, especially because species-specific PCRs can miss unknown or unexpected pathogens. © 2022
Application of KRR, K-NN and GPR algorithms for predicting the soaked CBR of fine-grained plastic soils
- Verma, Gaurav, Kumar, Brind, Kumar, Chintoo, Ray, Arunava, Khandelwal, Manoj
- Authors: Verma, Gaurav , Kumar, Brind , Kumar, Chintoo , Ray, Arunava , Khandelwal, Manoj
- Date: 2023
- Type: Text , Journal article
- Relation: Arabian Journal for Science and Engineering Vol. 48, no. 10 (2023), p. 13901-13927
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- Description: California bearing ratio (CBR) test is one of the comprehensive tests used for the last few decades to design the pavement thickness of roadways, railways and airport runways. Laboratory-performed CBR test is considerably rigorous and time-taking. In a quest for an alternative solution, this study utilizes novel computational approaches, including the kernel ridges regression, K-nearest neighbor and Gaussian process regression (GPR), to predict the soaked CBR value of soils. A vast quantity of 1011 in situ soil samples were collected from an ongoing highway project work site. Two data divisional approaches, i.e., K-Fold and fuzzy c-means (FCM) clustering, were used to separate the dataset into training and testing subsets. Apart from the numerous statistical performance measurement indices, ranking and overfitting analysis were used to identify the best-fitted CBR prediction model. Additionally, the literature models were also tried to validate through present study datasets. From the results of Pearson’s correlation analysis, Sand, Fine Content, Plastic Limit, Plasticity Index, Maximum Dry Density and Optimum Moisture Content were found to be most influencing input parameters in developing the soaked CBR of fine-grained plastic soils. Experimental results also establish the proficiency of the GPR model developed through FCM and K-Fold data division approaches. The K-Fold data division approach was found to be helpful in removing the overfitting of the models. Furthermore, the predictive ability of any model is considerably influenced by the geological location of the soils/materials used for the model development. © 2023, The Author(s).
- Authors: Verma, Gaurav , Kumar, Brind , Kumar, Chintoo , Ray, Arunava , Khandelwal, Manoj
- Date: 2023
- Type: Text , Journal article
- Relation: Arabian Journal for Science and Engineering Vol. 48, no. 10 (2023), p. 13901-13927
- Full Text:
- Reviewed:
- Description: California bearing ratio (CBR) test is one of the comprehensive tests used for the last few decades to design the pavement thickness of roadways, railways and airport runways. Laboratory-performed CBR test is considerably rigorous and time-taking. In a quest for an alternative solution, this study utilizes novel computational approaches, including the kernel ridges regression, K-nearest neighbor and Gaussian process regression (GPR), to predict the soaked CBR value of soils. A vast quantity of 1011 in situ soil samples were collected from an ongoing highway project work site. Two data divisional approaches, i.e., K-Fold and fuzzy c-means (FCM) clustering, were used to separate the dataset into training and testing subsets. Apart from the numerous statistical performance measurement indices, ranking and overfitting analysis were used to identify the best-fitted CBR prediction model. Additionally, the literature models were also tried to validate through present study datasets. From the results of Pearson’s correlation analysis, Sand, Fine Content, Plastic Limit, Plasticity Index, Maximum Dry Density and Optimum Moisture Content were found to be most influencing input parameters in developing the soaked CBR of fine-grained plastic soils. Experimental results also establish the proficiency of the GPR model developed through FCM and K-Fold data division approaches. The K-Fold data division approach was found to be helpful in removing the overfitting of the models. Furthermore, the predictive ability of any model is considerably influenced by the geological location of the soils/materials used for the model development. © 2023, The Author(s).
Application of various robust techniques to study and evaluate the role of effective parameters on rock fragmentation
- Mehrdanesh, Amirhossein, Monjezi, Masoud, Khandelwal, Manoj, Bayat, Parichehr
- Authors: Mehrdanesh, Amirhossein , Monjezi, Masoud , Khandelwal, Manoj , Bayat, Parichehr
- Date: 2023
- Type: Text , Journal article
- Relation: Engineering with Computers Vol. 39, no. 2 (2023), p. 1317-1327
- Full Text:
- Reviewed:
- Description: In this paper, an attempt has been made to implement various robust techniques to predict rock fragmentation due to blasting in open pit mines using effective parameters. As rock fragmentation prediction is very complex and complicated, and due to that various artificial intelligence-based techniques, such as artificial neural network (ANN), classification and regression tree and support vector machines were selected for the modeling. To validate and compare the prediction results, conventional multivariate regression analysis was also utilized on the same data sets. Since accuracy and generality of the modeling is dependent on the number of inputs, it was tried to collect enough required information from four different open pit mines of Iran. According to the obtained results, it was revealed that ANN with a determination coefficient of 0.986 is the most precise method of modeling as compared to the other applied techniques. Also, based on the performed sensitivity analysis, it was observed that the most prevailing parameters on the rock fragmentation are rock quality designation, Schmidt hardness value, mean in-situ block size and the minimum effective ones are hole diameter, burden and spacing. The advantage of back propagation neural network technique for using in this study compared to other soft computing methods is that they are able to describe complex and nonlinear multivariable problems in a transparent way. Furthermore, ANN can be used as a first approach, where much knowledge about the influencing parameters are missing. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
- Authors: Mehrdanesh, Amirhossein , Monjezi, Masoud , Khandelwal, Manoj , Bayat, Parichehr
- Date: 2023
- Type: Text , Journal article
- Relation: Engineering with Computers Vol. 39, no. 2 (2023), p. 1317-1327
- Full Text:
- Reviewed:
- Description: In this paper, an attempt has been made to implement various robust techniques to predict rock fragmentation due to blasting in open pit mines using effective parameters. As rock fragmentation prediction is very complex and complicated, and due to that various artificial intelligence-based techniques, such as artificial neural network (ANN), classification and regression tree and support vector machines were selected for the modeling. To validate and compare the prediction results, conventional multivariate regression analysis was also utilized on the same data sets. Since accuracy and generality of the modeling is dependent on the number of inputs, it was tried to collect enough required information from four different open pit mines of Iran. According to the obtained results, it was revealed that ANN with a determination coefficient of 0.986 is the most precise method of modeling as compared to the other applied techniques. Also, based on the performed sensitivity analysis, it was observed that the most prevailing parameters on the rock fragmentation are rock quality designation, Schmidt hardness value, mean in-situ block size and the minimum effective ones are hole diameter, burden and spacing. The advantage of back propagation neural network technique for using in this study compared to other soft computing methods is that they are able to describe complex and nonlinear multivariable problems in a transparent way. Furthermore, ANN can be used as a first approach, where much knowledge about the influencing parameters are missing. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
Applications of Computed Tomography (CT) in environmental soil and plant sciences
- Zhang, Huan, He, Hailong, Gao, Yanjun, Mady, Ahmed, Filipović, Vilim, Dyck, Miles, Lv, Jialong, Liu, Yang
- Authors: Zhang, Huan , He, Hailong , Gao, Yanjun , Mady, Ahmed , Filipović, Vilim , Dyck, Miles , Lv, Jialong , Liu, Yang
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Soil and Tillage Research Vol. 226, no. (2023), p.
- Full Text: false
- Reviewed:
- Description: Computed tomography (CT) in combination with advanced image processing can be used to non-invasively and non-destructively visualize complex interiors of living and non-living media in 2 and 3-dimensional space. In addition to medical applications, CT has also been widely used in soil and plant science for visual and quantitative descriptions of physical, chemical, and biological properties and processes. The technique has been used successfully on numerous applications. However, with a rapidly evolving CT technologies and expanding applications, a renewed review is desirable. Only a few attempts have been made to collate and review examples of CT applications involving the integrated field of soil and plant research in recent years. Therefore, the objectives of this work were to: (1) briefly introduce the basic principles of CT and image processing; (2) identify the research status and hot spots of CT using bibliometric analysis based on Web of Science literature over the past three decades; (3) provide an overall review of CT applications in soil science for measuring soil properties (e.g., porous soil structure, soil components, soil biology, heat transfer, water flow, and solute transport); and (4) give an overview of applications of CT in plant science to detect morphological structures, plant material properties, and root-soil interaction. Moreover, the limitations of CT and image processing are discussed and future perspectives are given. © 2022 Elsevier B.V.
Applications of machine learning and deep learning in antenna design, optimization, and selection : a review
- Sarker, Nayan, Podder, Prajoy, Mondal, M., Shafin, Sakib, Kamruzzaman, Joarder
- Authors: Sarker, Nayan , Podder, Prajoy , Mondal, M. , Shafin, Sakib , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article , Review
- Relation: IEEE Access Vol. 11, no. (2023), p. 103890-103915
- Full Text:
- Reviewed:
- Description: This review paper provides an overview of the latest developments in artificial intelligence (AI)-based antenna design and optimization for wireless communications. Machine learning (ML) and deep learning (DL) algorithms are applied to antenna engineering to improve the efficiency of the design and optimization processes. The review discusses the use of electromagnetic (EM) simulators such as computer simulation technology (CST) and high-frequency structure simulator (HFSS) for ML and DL-based antenna design, which also covers reinforcement learning (RL)-bases approaches. Various antenna optimization methods including parallel optimization, single and multi-objective optimization, variable fidelity optimization, multilayer ML-assisted optimization, and surrogate-based optimization are discussed. The review also covers the AI-based antenna selection approaches for wireless applications. To support the automation of antenna engineering, the data generation technique with computational electromagnetics software is described and some useful datasets are reported. The review concludes that ML/DL can enhance antenna behavior prediction, reduce the number of simulations, improve computer efficiency, and speed up the antenna design process. © 2013 IEEE.
- Authors: Sarker, Nayan , Podder, Prajoy , Mondal, M. , Shafin, Sakib , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article , Review
- Relation: IEEE Access Vol. 11, no. (2023), p. 103890-103915
- Full Text:
- Reviewed:
- Description: This review paper provides an overview of the latest developments in artificial intelligence (AI)-based antenna design and optimization for wireless communications. Machine learning (ML) and deep learning (DL) algorithms are applied to antenna engineering to improve the efficiency of the design and optimization processes. The review discusses the use of electromagnetic (EM) simulators such as computer simulation technology (CST) and high-frequency structure simulator (HFSS) for ML and DL-based antenna design, which also covers reinforcement learning (RL)-bases approaches. Various antenna optimization methods including parallel optimization, single and multi-objective optimization, variable fidelity optimization, multilayer ML-assisted optimization, and surrogate-based optimization are discussed. The review also covers the AI-based antenna selection approaches for wireless applications. To support the automation of antenna engineering, the data generation technique with computational electromagnetics software is described and some useful datasets are reported. The review concludes that ML/DL can enhance antenna behavior prediction, reduce the number of simulations, improve computer efficiency, and speed up the antenna design process. © 2013 IEEE.
Apprenticeships : the problem of attractiveness and the hindrance of heterogeneity
- Authors: Smith, Erica
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Training and Development Vol. 27, no. 1 (2023), p. 18-38
- Full Text:
- Reviewed:
- Description: This paper examines a question posed in 2019 in the International Journal on Training and Development: ‘How do we solve a problem like apprenticeship?’ Data sources covering a substantial number of countries are used to present findings on, and analyse, initiatives that have been implemented or that have been considered, and then to develop some analytical constructs to help address the question. Fundamental issues such as the status of vocational education and training and the status of apprenticed occupations are important, but the nature of the apprenticeship arrangements, within countries and within industries are also major factors affecting perceived attractiveness. The paper therefore argues that the heterogeneity of apprenticeship systems and arrangements is a major barrier to solving the attractiveness problem. Moreover, the heterogeneity of potential apprenticeship applicants means that marketing campaigns or other efforts to attract more, and higher quality, apprentices need to be cognisant of individuals’ backgrounds, characteristics, and aspirations. Some tentative ways of addressing these matters are presented, but the conclusion is that the topic needs large-scale research. © 2022 The Authors. International Journal of Training and Development published by Brian Towers (BRITOW) and John Wiley & Sons Ltd.
- Authors: Smith, Erica
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Training and Development Vol. 27, no. 1 (2023), p. 18-38
- Full Text:
- Reviewed:
- Description: This paper examines a question posed in 2019 in the International Journal on Training and Development: ‘How do we solve a problem like apprenticeship?’ Data sources covering a substantial number of countries are used to present findings on, and analyse, initiatives that have been implemented or that have been considered, and then to develop some analytical constructs to help address the question. Fundamental issues such as the status of vocational education and training and the status of apprenticed occupations are important, but the nature of the apprenticeship arrangements, within countries and within industries are also major factors affecting perceived attractiveness. The paper therefore argues that the heterogeneity of apprenticeship systems and arrangements is a major barrier to solving the attractiveness problem. Moreover, the heterogeneity of potential apprenticeship applicants means that marketing campaigns or other efforts to attract more, and higher quality, apprentices need to be cognisant of individuals’ backgrounds, characteristics, and aspirations. Some tentative ways of addressing these matters are presented, but the conclusion is that the topic needs large-scale research. © 2022 The Authors. International Journal of Training and Development published by Brian Towers (BRITOW) and John Wiley & Sons Ltd.