AIMC Topic: Affect

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Moral artificial intelligence and machine puritanism.

The Behavioral and brain sciences
Puritanism may evolve into a technological variant based on norms of delegation of actions and perceptions to artificial intelligence. Instead of training self-control, people may be expected to cede their agency to self-controlled machines. The cost...

Online music-assisted rehabilitation system for depressed people based on deep learning.

Progress in neuro-psychopharmacology & biological psychiatry
The processing of negative emotions is closely related to the occurrence of depression, and improving the mood of patients with depression has an important effect on improving symptoms. This article applies deep learning to the diagnosis and treatmen...

Something's Fishy About It: How Opinion Congeniality and Explainability Affect Motivated Attribution to Artificial Intelligence Versus Human Comment Moderators.

Cyberpsychology, behavior and social networking
An online experiment ( = 384) examined when and how the identity of the comment moderator (artificial intelligence [AI] vs. human) on a news website affects the extent to which individuals (a) suspect political motives for comment removal and (b) bel...

Multi-Modal Song Mood Detection with Deep Learning.

Sensors (Basel, Switzerland)
The production and consumption of music in the contemporary era results in big data generation and creates new needs for automated and more effective management of these data. Automated music mood detection constitutes an active task in the field of ...

The Influence of Fluid Intake Behavior on Cognition and Mood among College Students in Baoding, China.

Annals of nutrition & metabolism
INTRODUCTION: Water is a critical nutrient, and it is important for the maintenance of the physiological function of the human body [1-3]. In addition to fluid amounts, f...

Understanding Attitudes to Change to Healthier Hydration Habits: The Case of High Sugar: Low Water Drinkers in Mexico.

Annals of nutrition & metabolism
Adults consuming sugar-sweetened beverages (SSBs) are at increased risk of becoming overweight/obese and developing lifestyle-related diseases. Furthermore, a low water intake is associated with increased health risks, such as CKD. These issues are e...

Preictal state detection using prodromal symptoms: A machine learning approach.

Epilepsia
A reliable identification of a high-risk state for upcoming seizures may allow for preemptive treatment and improve the quality of patients' lives. We evaluated the ability of prodromal symptoms to predict preictal states using a machine learning (ML...

Let's not be indifferent about robots: Neutral ratings on bipolar measures mask ambivalence in attitudes towards robots.

PloS one
Ambivalence, the simultaneous experience of both positive and negative feelings about one and the same attitude object, has been investigated within psychological attitude research for decades. Ambivalence is interpreted as an attitudinal conflict wi...

Analysing the predictive capacity and dose-response of wellness in load monitoring.

Journal of sports sciences
This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offerin...

Can We Ditch Feature Engineering? End-to-End Deep Learning for Affect Recognition from Physiological Sensor Data.

Sensors (Basel, Switzerland)
To further extend the applicability of wearable sensors in various domains such as mobile health systems and the automotive industry, new methods for accurately extracting subtle physiological information from these wearable sensors are required. How...