scholarly journals Development of an Automated Pain Facial Expression Detection System for Sheep (Ovis Aries)

Animals ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 196 ◽  
Author(s):  
Krista McLennan ◽  
Marwa Mahmoud
Keyword(s):  
Facial Expression ◽  
Detection System ◽  
Ovis Aries ◽  
Expression Recognition ◽  
Use Of Technology ◽  
Assessment And Treatment ◽  
The Individual ◽  
Individual Farm ◽  
And Control ◽  
The Impact

The use of technology to optimize the production and management of each individual animal is becoming key to good farming. There is a need for the real-time systematic detection and control of disease in animals in order to limit the impact on animal welfare and food supply. Diseases such as footrot and mastitis cause significant pain in sheep, and so early detection is vital to ensuring effective treatment and preventing the spread across the flock. Facial expression scoring to assess pain in humans and non-humans is now well utilized, and the Sheep Pain Facial Expression Scale (SPFES) is a tool that can reliably detect pain in this species. The SPFES currently requires manual scoring, leaving it open to observer bias, and it is also time-consuming. The ability of a computer to automatically detect and direct a producer as to where assessment and treatment are needed would increase the chances of controlling the spread of disease. It would also aid in the prevention of resistance across the individual, farm, and landscape at both national and international levels. In this paper, we present our framework for an integrated novel system based on techniques originally applied for human facial expression recognition that could be implemented at the farm level. To the authors’ knowledge, this is the first time that this technology has been applied to sheep to assess pain.

scholarly journals "The brain can't cope": Insights about reading from people with chronic aphasia

2018 ◽  
Author(s):  
Janet Webster ◽  
Amy Samouelle ◽  
Julie Morris
Keyword(s):  
Reading Ability ◽  
Reading Difficulties ◽  
World Health Organisation ◽  
Structured Interview ◽  
World Health ◽  
Use Of Technology ◽  
Assessment And Treatment ◽  
The Individual ◽  
Reading Activities ◽  
The Impact

Background: Reading difficulties are a common feature of aphasia. There has been limited in-depth investigation of how individuals perceive their difficulties and the impact of their reading difficulties on everyday activities.Aims: This study explored the reading experiences of people with aphasia, asking them to describe pre- and post-morbid reading, considering aspects relevant to the different components of the International Classification of Disability and Functioning (ICF) (World Health Organisation (WHO), 2002). It also considered the relationship between use of technology (computers and mobile phones) and reading.Methods & Procedures: Ten people with chronic, mild to moderate aphasia participated in the study. A semi-structured interview was carried out. Responses were transcribed verbatim and then analysed using the framework method. Themes were identified for pre-morbid reading, current (post-morbid) reading and for questions related to technology.Outcomes: The results highlight the complexity of factors influencing reading and the individual variation in reading ability, the importance and frequency of reading and reading activities. Post-morbidly, there was a perceived decline in reading ability, with multi-faceted reading difficulties reported. Importantly, changes in reading activity reflected changes in role (for example, employment status) as well as change due to the reading difficulties. It was difficult to determine the influence of reading difficulties on the use of technology.Conclusions: The implications for the assessment and treatment of reading in aphasia are explored.

U.S. Regulatory Approaches: A Critical Appraisal

1992 ◽  
Vol 25 (3) ◽  
pp. 13-21
Author(s):  
R. L. Williamson
Keyword(s):  
Decision Making ◽  
Command And Control ◽  
Regulatory System ◽  
Federal Agencies ◽  
Toxic Substances ◽  
Use Of Technology ◽  
Treatment Technologies ◽  
New Treatment ◽  
And Control ◽  
The Impact

The American approach to environmental regulation is characterized by fragmentation of responsibilities, primary reliance on command and control regulations, extraordinary complexity, a preference for identifiable standards, and heavy resort to litigation. This system has provided important benefits, including significant reduction of environmental contamination, substantial use of science in decision-making, broad participatory rights, and the stimulation of new treatment technologies. However, these gains have been achieved at excessive cost. Too much reliance is placed on command and control methods and especially on technology-based standards. There is too much resort to litigation, and inadequate input from science. Participatory rights are being undermined, and there is a poor allocation of decision-making among the federal agencies and the states. Over-regulation sometimes leads to under-regulation, and insufficient attention is given to the impact on small entities. The responsibility for these difficulties rests with everyone, including the federal agencies, the Congress, the general public and the courts. Changes in the regulatory system are needed. We should abandon the use of technology-based standards to control toxic substances under the Clean Water Act in favor of strong health- and environmentally based standards, coupled with taxes on toxic substances in wastewater.

scholarly journals Facial Expression Recognition of Instructor Using Deep Features and Extreme Learning Machine

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yusra Khalid Bhatti ◽  
Afshan Jamil ◽  
Nudrat Nida ◽  
Muhammad Haroon Yousaf ◽  
Serestina Viriri ◽  
...  
Keyword(s):  
Facial Expression ◽  
Extreme Learning Machine ◽  
Facial Expressions ◽  
Classroom Environment ◽  
Facial Expression Recognition ◽  
Parameter Tuning ◽  
Expression Recognition ◽  
Fast Learning ◽  
Learning Machine ◽  
The Impact

Classroom communication involves teacher’s behavior and student’s responses. Extensive research has been done on the analysis of student’s facial expressions, but the impact of instructor’s facial expressions is yet an unexplored area of research. Facial expression recognition has the potential to predict the impact of teacher’s emotions in a classroom environment. Intelligent assessment of instructor behavior during lecture delivery not only might improve the learning environment but also could save time and resources utilized in manual assessment strategies. To address the issue of manual assessment, we propose an instructor’s facial expression recognition approach within a classroom using a feedforward learning model. First, the face is detected from the acquired lecture videos and key frames are selected, discarding all the redundant frames for effective high-level feature extraction. Then, deep features are extracted using multiple convolution neural networks along with parameter tuning which are then fed to a classifier. For fast learning and good generalization of the algorithm, a regularized extreme learning machine (RELM) classifier is employed which classifies five different expressions of the instructor within the classroom. Experiments are conducted on a newly created instructor’s facial expression dataset in classroom environments plus three benchmark facial datasets, i.e., Cohn–Kanade, the Japanese Female Facial Expression (JAFFE) dataset, and the Facial Expression Recognition 2013 (FER2013) dataset. Furthermore, the proposed method is compared with state-of-the-art techniques, traditional classifiers, and convolutional neural models. Experimentation results indicate significant performance gain on parameters such as accuracy, F1-score, and recall.

Facial Expression and Sex Recognition in Schizophrenia and Depression

2005 ◽  
Vol 50 (9) ◽  
pp. 525-533 ◽  
Author(s):  
Benoit Bediou ◽  
Pierre Krolak-Salmon ◽  
Mohamed Saoud ◽  
Marie-Anne Henaff ◽  
Michael Burt ◽  
...  
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Recognition Task ◽  
Expression Recognition ◽  
Sex Recognition ◽  
Control Subjects ◽  
Healthy Control ◽  
And Control ◽  
Expression Processing ◽  
Selective Impairment

Background: Impaired facial expression recognition in schizophrenia patients contributes to abnormal social functioning and may predict functional outcome in these patients. Facial expression processing involves individual neural networks that have been shown to malfunction in schizophrenia. Whether these patients have a selective deficit in facial expression recognition or a more global impairment in face processing remains controversial. Objective: To investigate whether patients with schizophrenia exhibit a selective impairment in facial emotional expression recognition, compared with patients with major depression and healthy control subjects. Methods: We studied performance in facial expression recognition and facial sex recognition paradigms, using original morphed faces, in a population with schizophrenia ( n = 29) and compared their scores with those of depression patients ( n = 20) and control subjects ( n = 20). Results: Schizophrenia patients achieved lower scores than both other groups in the expression recognition task, particularly in fear and disgust recognition. Sex recognition was unimpaired. Conclusion: Facial expression recognition is impaired in schizophrenia, whereas sex recognition is preserved, which highly suggests an abnormal processing of changeable facial features in this disease. A dysfunction of the top-down retrograde modulation coming from limbic and paralimbic structures on visual areas is hypothesized.

scholarly journals Evaluation of Data Augmentation Techniques for Facial Expression Recognition Systems

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1892
Author(s):  
Simone Porcu ◽  
Alessandro Floris ◽  
Luigi Atzori
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Data Augmentation ◽  
Generative Adversarial Networks ◽  
Geometric Transformation ◽  
Expression Recognition ◽  
Learning Approaches ◽  
Geometric Transformations ◽  
Augmentation Techniques ◽  
The Impact

Most Facial Expression Recognition (FER) systems rely on machine learning approaches that require large databases for an effective training. As these are not easily available, a good solution is to augment the databases with appropriate data augmentation (DA) techniques, which are typically based on either geometric transformation or oversampling augmentations (e.g., generative adversarial networks (GANs)). However, it is not always easy to understand which DA technique may be more convenient for FER systems because most state-of-the-art experiments use different settings which makes the impact of DA techniques not comparable. To advance in this respect, in this paper, we evaluate and compare the impact of using well-established DA techniques on the emotion recognition accuracy of a FER system based on the well-known VGG16 convolutional neural network (CNN). In particular, we consider both geometric transformations and GAN to increase the amount of training images. We performed cross-database evaluations: training with the "augmented" KDEF database and testing with two different databases (CK+ and ExpW). The best results were obtained combining horizontal reflection, translation and GAN, bringing an accuracy increase of approximately 30%. This outperforms alternative approaches, except for the one technique that could however rely on a quite bigger database.

Determining the Quality and Impact of an E-Mentoring Program on At-Risk Youth

2015 ◽  
Vol 6 (2) ◽  
pp. 13-26
Author(s):  
Diane W. Culpepper ◽  
Victor M. Hernandez-Gantes ◽  
William E. Blank
Keyword(s):  
At Risk ◽  
Dropout Prevention ◽  
Test Scores ◽  
Self Esteem ◽  
Mentoring Program ◽  
Control Groups ◽  
Use Of Technology ◽  
And Control ◽  
The Impact

The purpose of this study was to determine the quality of an e-mentoring program and the impact of participation on at-risk high school students enrolled in dropout prevention programs. The quality of the program was evaluated based on the ease of implementation, use of technology, and overall satisfaction. Indicators of student's self-esteem, career decision, attendance, and GED test scores were used to gauge the impact of participation. Design-based research methods were used to compare the participation of students in mentored and control groups. The results indicated a high level of satisfaction with ease of implementation, use of technology, and overall program quality. However, there were no significant differences between the mentored and control groups regarding self-esteem, career indecision, attendance, and GED test scores. Since the GED dropout prevention program provides guidance and mentorship by the coordinator, further research is suggested to account for the role of program and other contributing variables. Also, further research is suggested on the ancillary benefits of e-mentoring.

Multiple Realities of Women’s Work Experiences in Coaching and Athletic Management

2000 ◽  
Vol 9 (2) ◽  
pp. 1-26 ◽  
Author(s):  
Sue Inglis ◽  
Karen E. Danylchuk ◽  
Donna L. Pastore
Keyword(s):  
Women's Work ◽  
Work Experiences ◽  
Multiple Realities ◽  
Women’S Work ◽  
Power And Control ◽  
Management Positions ◽  
The Individual ◽  
And Control ◽  
The Impact ◽  
Athletic Management

This paper is an exploration of the multiple realities of women’s work experiences in coaching and athletic management positions. Eleven women who had previously coached or directed women’s athletics programs were interviewed using a semi-structured approach. Three general categories emerged from the data — Support, Gender Differences, and Change. The work experiences reflect problems the women encountered at work, how organizations can be empowering, and the impact empowered women can have on the social construction of work. Based upon the data, we suggest that the individual search for empowerment takes different forms, yet also acknowledges that systemic changes must take place in order to improve the work environment for women. These findings are significant because they validate women’s experiences and contribute to the understanding of work experiences of those who are underrepresented and often left out of key circles of power and control.

scholarly journals Acceptance of cloud computing in the Malaysian public sector: A proposed model

2019 ◽  
Vol 11 ◽  
pp. 184797901988070 ◽  
Author(s):  
Mohd Talmizie Amron ◽  
Roslina Ibrahim ◽  
Nur Azaliah Abu Bakar ◽  
Suriayati Chuprat
Keyword(s):  
Cloud Computing ◽  
Public Sector ◽  
Technological Factor ◽  
The Public ◽  
Use Of Technology ◽  
The People ◽  
Proposed Model ◽  
Government Project ◽  
The Individual ◽  
The Impact

The Malaysian government has initiated a cloud government project as an integration of cloud computing and unified communication-based applications toward the digital and cloud work environment. However, the impact studies have found that the implementation of this project has several weaknesses such as lack of infrastructure support, weak IT knowledge, and lack of awareness among public sector employees causing applications not to be fully utilized. Therefore, it is crucial to conduct a study to measure the acceptance of government cloud project because there has been much investment in the project. This study applied Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Readiness Index (TRI) and several factors to develop the research model which is divided into two main factors: technological and human. The technological factor might determine the likelihood of its acceptance by the public sector and might stimulate them to accept it. The human factor as the characteristics of the people in the public sector that may contribute to creating the need for and ability to accept cloud computing. This proposed model will be used to evaluate the individual acceptance of cloud computing in the Malaysian public sector. For future work, this model needs to be enriched with interview sessions and quantitative surveys to validate the findings.

scholarly journals Efficacy of Facial Exercises in Facial Expression Categorization in Schizophrenia

2021 ◽  
Vol 11 (7) ◽  
pp. 825
Author(s):  
Francesco Pancotti ◽  
Sonia Mele ◽  
Vincenzo Callegari ◽  
Raffaella Bivi ◽  
Francesca Saracino ◽  
...  
Keyword(s):  
Facial Expression ◽  
Physical Training ◽  
Muscle Activation ◽  
Positive Impact ◽  
Control Group ◽  
Expression Recognition ◽  
Emotional Understanding ◽  
Facial Emotions ◽  
Facial Movements ◽  
And Control

Embodied cognition theories suggest that observation of facial expression induces the same pattern of muscle activation, and that this contributes to emotion recognition. Consequently, the inability to form facial expressions would affect emotional understanding. Patients with schizophrenia show a reduced ability to express and perceive facial emotions. We assumed that a physical training specifically developed to mobilize facial muscles could improve the ability to perform facial movements, and, consequently, spontaneous mimicry and facial expression recognition. Twenty-four inpatient participants with schizophrenia were randomly assigned to the experimental and control group. At the beginning and at the end of the study, both groups were submitted to a facial expression categorization test and their data compared. The experimental group underwent a training period during which the lip muscles, and the muscles around the eyes were mobilized through the execution of transitive actions. Participants were trained three times a week for five weeks. Results showed a positive impact of the physical training in the recognition of others’ facial emotions, specifically for the responses of “fear”, the emotion for which the recognition deficit in the test is most severe. This evidence suggests that a specific deficit of the sensorimotor system may result in a specific cognitive deficit.

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