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Feeding Behavior

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Development of swarm behavior in artificial learning agents that adapt to different foraging environments.

PloS one
Collective behavior, and swarm formation in particular, has been studied from several perspectives within a large variety of fields, ranging from biology to physics. In this work, we apply Projective Simulation to model each individual as an artifici...

Deep neural networks based automated extraction of dugong feeding trails from UAV images in the intertidal seagrass beds.

PloS one
Dugongs (Dugong dugon) are seagrass specialists distributed in shallow coastal waters in tropical and subtropical seas. The area and distribution of the dugongs' feeding trails, which are unvegetated winding tracks left after feeding, have been used ...

A controllable dual-catapult system inspired by the biomechanics of the dragonfly larvae's predatory strike.

Science robotics
The biomechanics underlying the predatory strike of dragonfly larvae is not yet understood. Dragonfly larvae are aquatic ambush predators, capturing their prey with a strongly modified extensible mouthpart. The current theory of hydraulic pressure be...

Aging-related markers in rat urine revealed by dynamic metabolic profiling using machine learning.

Aging
The process of aging and metabolism is intimately intertwined; thus, developing biomarkers related to metabolism is critical for delaying aging. However, few studies have identified reliable markers that reflect aging trajectories based on machine le...

An Innovative Machine Learning Approach to Predict the Dietary Fiber Content of Packaged Foods.

Nutrients
Underconsumption of dietary fiber is prevalent worldwide and is associated with multiple adverse health conditions. Despite the importance of fiber, the labeling of fiber content on packaged foods and beverages is voluntary in most countries, making ...

Evaluation of a Novel Artificial Intelligence System to Monitor and Assess Energy and Macronutrient Intake in Hospitalised Older Patients.

Nutrients
Malnutrition is common, especially among older, hospitalised patients, and is associated with higher mortality, longer hospitalisation stays, infections, and loss of muscle mass. It is therefore of utmost importance to employ a proper method for diet...

Design of Residents' Sports Nutrition Data Monitoring System Based on Genetic Algorithm.

Computational intelligence and neuroscience
With the development of modern Internet technology, the health assessment model based on computer technology has gradually become a research hotspot. In the process of studying the health level of residents, exercise status and diet nutrition are imp...

Enabling Eating Detection in a Free-living Environment: Integrative Engineering and Machine Learning Study.

Journal of medical Internet research
BACKGROUND: Monitoring eating is central to the care of many conditions such as diabetes, eating disorders, heart diseases, and dementia. However, automatic tracking of eating in a free-living environment remains a challenge because of the lack of a ...

Intake monitoring in free-living conditions: Overview and lessons we have learned.

Appetite
The progress in artificial intelligence and machine learning algorithms over the past decade has enabled the development of new methods for the objective measurement of eating, including both the measurement of eating episodes as well as the measurem...

Thought on Food: A Systematic Review of Current Approaches and Challenges for Food Intake Detection.

Sensors (Basel, Switzerland)
Nowadays, individuals have very stressful lifestyles, affecting their nutritional habits. In the early stages of life, teenagers begin to exhibit bad habits and inadequate nutrition. Likewise, other people with dementia, Alzheimer's disease, or other...