8364 research outputs found
Sort by
Participants’ Utilitarian Choice Is Influenced by Gamble Presentation and Age
Get PDFNo prior behavioral science research has delved into the impact of gamble presentation (horizontal or vertical) on individuals’ utilitarian behavior, despite evidence suggesting that such choices can be influenced by comparing attributes like probability and money in gambles. This article addresses this gap by exploring the influence of gamble presentation on utilitarian behavior. A two-factor independent measures design was employed to explore the influence of the type of gamble presentation and age on participants’ utilitarian decision-making preferences. The findings showed a reduced likelihood of participants choosing the non-utilitarian gamble with vertically presented gambles compared to horizontal ones. Consequently, participants’ utilitarian behavior was influenced by between-gamble comparisons of available attributes, with utilitarian choices (e.g., choosing Gamble A) being more prevalent in vertical presentations due to a straightforward comparison on the probability attribute. Furthermore, the results also revealed that older participants take more time than their younger counterparts when making utilitarian errors. We attribute this to their abundant knowledge and experience. Future research should explore the comparative psychological processing used by participants in risky decision-making tasks
Ultra-Wide Band Radar Empowered Driver Drowsiness Detection with Convolutional Spatial Feature Engineering and Artificial Intelligence
Get PDFDriving while drowsy poses significant risks, including reduced cognitive function and the potential for accidents, which can lead to severe consequences such as trauma, economic losses, injuries, or death. The use of artificial intelligence can enable effective detection of driver drowsiness, helping to prevent accidents and enhance driver performance. This research aims to address the crucial need for real-time and accurate drowsiness detection to mitigate the impact of fatigue-related accidents. Leveraging ultra-wideband radar data collected over five minutes, the dataset was segmented into one-minute chunks and transformed into grayscale images. Spatial features are retrieved from the images using a two-dimensional Convolutional Neural Network. Following that, these features were used to train and test multiple machine learning classifiers. The ensemble classifier RF-XGB-SVM, which combines Random Forest, XGBoost, and Support Vector Machine using a hard voting criterion, performed admirably with an accuracy of 96.6%. Additionally, the proposed approach was validated with a robust k-fold score of 97% and a standard deviation of 0.018, demonstrating significant results. The dataset is augmented using Generative Adversarial Networks, resulting in improved accuracies for all models. Among them, the RF-XGB-SVM model outperformed the rest with an accuracy score of 99.58%
Respiratory muscles's thermographic analysis in asthmatic youth with and without bronchospasm induced by eucapnic voluntary hyperpnea
Get PDFObjective
To compare the thermographic pattern of regions of interest (ROI) of respiratory muscles in young asthmatics with and without bronchospasm induced by eucapnic voluntary hyperpnea (EVH).
Materials and Methods
Cross-sectional study carried out with 55 young (55% male and 45% females) aged 12.5 ± 3.3 years, divided in nine nonasthmatics, 22 asthmatics without exercise-induced bronchospasm compatible response (EIB-cr) and 24 asthmatics with EIB-cr. The diagnosis of EIB was given to subjects with a fall in forced expiratory volume in the first second (FEV1) ≥ 10% compared to baseline. Thermographic recordings of respiratory muscles were delimited in ROI of the sternocleidomastoid (SCM), pectoral, and rectus abdominis intention area. Thermal captures and FEV1 were taken before and 5, 10, 15 and 30 min after EVH.
Results
Twenty-four (52.1%) of asthmatics had EIB-cr. There was a decrease in temperature at 10 min after EVH test in the SCM, pectoral and rectus abdominis ROIs in all groups (both with p < 0.05). There was a decrease in temperature (% basal) in asthmatic with EIB-cr compared to nonasthmatics in the rectus abdominis area (p < 0.05).
Conclusion
There was a decrease in temperature in the ROIs of different muscle groups, especially in asthmatics. The greater drop in FEV1 observed in individuals with EIB-cr was initially associated with a decrease in skin temperature, with a difference between the nonasthmatics in the abdominal muscle area. It is likely that this decrease in temperature occurred due to a temporary displacement of blood flow to the most used muscle groups, with a decrease in the region of the skin evaluated in the thermography
Machine learning model of acoustic signatures: Towards digitalised thermal spray manufacturing
Get PDFThermal spraying, an important industrial surface manufacturing process in sectors such as aerospace, energy and biomedical, remains a skill intensive process often involving multiple trial runs impacting the yield. The core research challenge in digitalisation of thermal spraying process lies in instrumenting the manufacturing platform as the process includes harsh conditions, including UV Rays, high-plasma temperature, dusty chemical environment, and spray booth inaccessibility. This paper introduces a novel application of machine learning to the acoustic emission spectra of thermal spraying. By transitioning from the amplitude-time domain to a Fourier-transformed frequency-time domain, it is possible to predict anomalies in real-time, a crucial step towards sustainable material and manufacturing digitalization. Our experimental results also indicate that this method is suitable for industrial applications by generating useful data that can be used to develop Visual Geometry Group (VGG) transfer learning models to overcome the traditional limitations of convoluted neural networks (CNN)
Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control
Get PDFInterval Type-2 Fuzzy Logic Control (IT2FLC) possesses a high control ability in a way that it can optimally handle the presence of uncertainty in a system dynamic. However, the design of such a control scheme is a challenging task due to its complex structure and nonlinear behavior. A Manta Ray Foraging Optimization (MRFO) is a promising algorithm that can be applied to optimize the control design. However, MRFO still suffers the local optima problem due to unbalance exploration-exploitation of the MRFO agents and hence limiting the performance of the desired control. In this paper, Standard, Quasi, Super, and Quasi-Reflected opposition strategies are integrated into the MRFO structure. Each strategy enhances the exploration-exploitation capability and offers different approaches of varying agent’s step size relative to the algorithm’s iteration. The proposed opposition-based MRFO (OMRFO) algorithms are applied to optimize the IT2FLC control design for a laboratory-scaled inverted pendulum system. Moreover, as the algorithms are also promising strategies to other problems, they are applied to solve 50D of 30 IEEE CEC14 benchmark functions representing problems with different features. Performance analysis of the algorithms is statistically conducted using Wilcoxon sign rank and Friedman tests. The result shows that the performance of MRFO and Quasi-Reflected-OMRFO are equal, while all other OMRFO variants show a significant improvement and better rank over the MRFO. The Super and Quasi OMRFO-IT2FLC schemes acquired the best responses for the cart and pendulum, respectively
Perspectives of autistic adolescent girls and women on the determinants of their mental health and social and emotional well-being: A systematic review and thematic synthesis of lived experience
Get PDFAutistic girls and women experience more mental health difficulties and poorer well-being than their non-autistic peers. Little emphasis has been placed on the perspectives of the girls and women within the literature. This review aims to provide an overview of the factors that impact autistic females’ emotional and social well-being and mental health, as described in self-report qualitative studies. The protocol for the present review was pre-registered on PROSPERO (CRD42020184983), and this article follows Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PsycInfo, Academic Search Complete and MEDLINE were systematically searched using a pre-defined search string. This yielded 877 unique records, which were systematically screened by two reviewers, resulting in 52 eligible studies. Structured data extraction and quality appraisal were completed. The present review presents the perspectives of 973 autistic females aged 13–70+. Thematic synthesis identified three themes and nine subthemes. Our findings suggest that autistic girls’ and women’s experiences can be conceptualised within a social model, where biological and psychological factors (‘The Autistic Neurotype’) are experienced through the lens of social factors (‘The Neurotypical World’ and ‘Stigma’), together shaping well-being and mental health outcomes.
Lay abstract
Difficulties with mental health and low levels of well-being are more common among autistic girls and women than non-autistic people, but we do not fully understand why. Research does not focus enough on what autistic girls and women could tell us about this. This review aims to summarise the studies where autistic girls and women explain things that affect their mental health and well-being to help us understand how to prevent these difficulties from developing. Three research databases were searched to find possibly relevant studies. There were 877 studies found, which two researchers screened according to particular criteria. They found 52 studies that could be included in this review. One researcher evaluated the quality of these studies and extracted the key information from them. This review summarises the views of 973 autistic girls and women aged between 13 and 70+. The findings from the 52 studies were analysed, and we found many factors that affect the mental health and well-being of autistic girls and women. These factors fall into two categories: (1) difficulties living in a world not designed for autistic people and (2) the impact of stigma due to being autistic
Kinematics from the Active Point of View
Get PDFThere are essentially two ways to keep track of a rigid body. In the passive view each rigid body carries a coordinate frame and the position and orientation of the body is specified by giving the transformation which relates coordinates in a standard reference frame to the local
frame moving with the body.
In the active view there is a single fixed coordinate frame. The position and orientation of a rigid body is specified by the transformation which moves the body from a standard (home) position to its current position.
When there are several bodies and when bodies also carry several different frames it can be hard to account for all the different frames. The alternative active view simplifies much of the labour of setting up the forward kinematics and dynamics of serial robots. This active view is completely equivalent to the passive view, but the passive view seems to be preferred in current texts on robotics
Buckling resistance of hot‐finished CHS beam‐columns using FE modelling and machine learning
Get PDFThe use of circular hollow sections (CHS) has increased in recent years owing to its excellent mechanical behaviour including axial compression and torsional resistance as well as its aesthetic appearance. They are popular in a wide range of structural members including beams, columns, trusses and arches. The behaviour of hot-finished CHS beam-columns made from normal and high strength steel is the main focus of this paper. A particular attention is given to predict the ultimate buckling resistance of CHS beam-columns using the recent advancement of the artificial neural network (ANN). FE models were established and validated to generate an extensive parametric study. The ANN model is trained and validated using a total of 3439 data points collected from the generated FE models and experimental tests available in the literature. A comprehensive comparative analysis with the design rules in Eurocode 3 is conducted to evaluate the performance of the developed ANN model. It is shown that the proposed ANN based design formula provides a reliable means for predicting the buckling resistance of the CHS beam-columns. This formula can be easily implemented in any programming software, providing an excellent basis for engineers and designers to predict the buckling resistance resistance of the CHS beam-columns with a straightforward procedure in an efficient and sustainable manner with least computational time
Dataset related to "A multicentric, single arm, prospective, stratified clinical investigation to evaluate MammoWave’s ability in breast lesions detection"
Get PDFMicrowave imaging is a safe and promising new technology in breast radiology, avoiding discomfort of breast compression and usage of ionizing radiation. This dataset relates to a paper which presents the first prospective microwave breast imaging study during which both symptomatic and asymptomatic subjects were recruited. Specifically, a prospective multicentre international clinical trial was performed in 2020-2021, to investigate the capability of a microwave imaging device (MammoWave) in allowing distinction between breasts with no radiological finding (NF) and breasts with radiological findings (WF), i.e., with benign or malignant lesions. Each breast scan was performed with the volunteers lying on a dedicated examination table in a comfortable prone position. MammoWave output was compared to reference standard (i.e., radiologic study obtained within the last month and integrated with histological one if available and deemed necessary by responsible investigator) to classify breasts into NF/WF categories. MammoWave output consists of a selection of microwave images’ features (determined prior to trials’ start), which allow distinction between NF and WF breasts (using statistical significance p<0.05). 353 women were enrolled in the study (mean age 51 years ± 12 [SD], minimum age 19, maximum age 78); MammoWave data from the first 15 women of each site, all with NF breasts, were used for calibration. Following central assessor evaluation, 111 NF (48 dense) and 272 WF (136 dense) breasts were used for comparison with MammoWave output. 272 WF comprised 182 benign findings and 90 malignant histology-confirmed cancer. A sensitivity of 82.3% was achieved (95%CI: 0.78-0.87); sensitivity is maintained when limiting the investigation to histology-confirmed breasts cancer only (90 histology-confirmed breasts cancer have been included in this analysis, having sizes ranging from 3 mm to 60 mm). Specificity value of approximately 50% was achieved as expected, since thresholds were calculated (for each feature) using median value obtained after recruiting the first 15 women (of each site), all NF. This prospective trial may represent another step for introducing microwave imaging into clinical practice, for helping in breast lesion identification in asymptomatic women
The relationships between expressed emotion, cortisol, and EEG alpha asymmetry
Get PDFFamilies can express high criticism, hostility and emotional over-involvement towards a person with or at risk of mental health problems. Perceiving such high expressed emotion (EE) can be a major psychological stressor for individuals, especially those at risk of mental health problems. To reveal the biological mechanisms underlying the effect of EE on health, this study investigated physiological response (salivary cortisol, frontal alpha asymmetry (FAA)) to verbal criticism and their relationship to anxiety and perceived EE. Using a repeated-measures design, healthy participants attended three testing sessions on non-consecutive days. On each day, participants listened to one of three types of auditory stimuli, namely criticism, neutral or praise, and Electroencephalography (EEG) and salivary cortisol were measured. Results showed a reduction in cortisol following criticism but there was no significant change in FAA. Post-criticism cortisol concentration negatively correlated with perceived EE after controlling for baseline mood. Our findings suggest that salivary cortisol change responds to criticism in non-clinical populations might be largely driven by individual differences in the perception of criticism (e.g., arousal and relevance). Criticisms expressed by audio comments may not be explicitly perceived as an acute emotional stressor, and thus, physiological change responds to criticisms could be minimum