AIMC Topic: Food

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Table Cleaning Task by Human Support Robot Using Deep Learning Technique.

Sensors (Basel, Switzerland) Mar 18, 2020
This work presents a table cleaning and inspection method using a Human Support Robot (HSR) which can operate in a typical food court setting. The HSR is able to perform a cleanliness inspection and also clean the food litter on the table by implemen...
Algorithms Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer Food Sanitation Self-Help Devices Interior Design and Furnishings Robotics Limit of Detection Workload
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Interpretable machine learning for predicting biomethane production in industrial-scale anaerobic co-digestion.

The Science of the total environment Dec 23, 2019
The objective of this study is to apply machine learning models to accurately predict daily biomethane production in an industrial-scale co-digestion facility. The methodology involved applying elasticnet, random forest, and extreme gradient boosting...
Refuse Disposal Methane Food Machine Learning Anaerobiosis
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HyperFoods: Machine intelligent mapping of cancer-beating molecules in foods.

Scientific reports Jul 3, 2019
Recent data indicate that up-to 30-40% of cancers can be prevented by dietary and lifestyle measures alone. Herein, we introduce a unique network-based machine learning platform to identify putative food-based cancer-beating molecules. These have bee...
Humans Drug Repositioning Metabolic Networks and Pathways Food Neoplasms Artificial Intelligence Antineoplastic Agents Databases, Factual Food Analysis Diet
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Predicting nationwide obesity from food sales using machine learning.

Health informatics journal May 19, 2019
The obesity epidemic progresses everywhere across the globe, and implementing frequent nationwide surveys to measure the percentage of obese population is costly. Conversely, country-level food sales information can be accessed inexpensively through ...
Obesity Food Commerce Humans Machine Learning Support Vector Machine
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Innovation hotspots in food waste treatment, biogas, and anaerobic digestion technology: A natural language processing approach.

The Science of the total environment Apr 7, 2019
The objective of this study is to apply natural language processing to identifying innovative technology trends related to food waste treatment, biogas, and anaerobic digestion. The methodology used involved analyzing large volumes of text data mined...
Biofuels Food Refuse Disposal Anaerobiosis Methane Bioreactors Natural Language Processing
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Appetite ratings of foods are predictable with an in vitro advanced gastrointestinal model in combination with an in silico artificial neural network.

Food research international (Ottawa, Ont.) Mar 25, 2019
The expected increase of global obesity prevalence makes it necessary to have information about the effects of meal intakes on the feeling of appetite. Because human clinical studies are time and cost intensive, there is a need for a reliable alterna...
Viscosity Food Meals Satiation Appetite Models, Biological Gastrointestinal Tract Humans Digestion Neural Networks, Computer Computer Simulation Equipment Design
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Ultrasonic pretreatment of food waste to accelerate enzymatic hydrolysis for glucose production.

Ultrasonics sonochemistry Dec 28, 2018
Recovering valuable materials from food waste by applying the concept of a bio-refinery is attracting considerable interest. To this effect, we investigated the possibility of enhancing the enzymatic hydrolysis of food waste using ultrasonic technolo...
Waste Products Glucan 1,4-alpha-Glucosidase Glucose Hydrolysis Ultrasonic Waves Food Temperature Particle Size Kinetics
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Demographic, Clinical, and Allergic Characteristics of Children with Eosinophilic Esophagitis in Isfahan, Iran.

Iranian journal of allergy, asthma, and immunology Dec 3, 2018
Eosinophilic esophagitis (EoE) is a chronic immune-mediated disease isolated to the esophagus Food allergy is thought to play an important role in the pathophysiology of EOE. The aim of this study is to evaluate demographic features and sensitivity o...
Eczema Adolescent Child, Preschool Fish Proteins Child Skin Tests Immunoglobulin E Allergens Humans Male Eosinophilic Esophagitis Food Female Iran Infant Sesamum Asthma Prevalence
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Machine Learning Methods as a Tool for Predicting Risk of Illness Applying Next-Generation Sequencing Data.

Risk analysis : an official publication of the Society for Risk Analysis Nov 21, 2018
Next-generation sequencing (NGS) data present an untapped potential to improve microbial risk assessment (MRA) through increased specificity and redefinition of the hazard. Most of the MRA models do not account for differences in survivability and vi...
Humans Phenotype Sensitivity and Specificity Machine Learning Algorithms Genetic Variation High-Throughput Nucleotide Sequencing Probability Listeriosis Linear Models Food Risk Assessment Foodborne Diseases Databases, Genetic Listeria monocytogenes Food Microbiology Virulence
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Combining deep residual neural network features with supervised machine learning algorithms to classify diverse food image datasets.

Computers in biology and medicine Feb 17, 2018
Obesity is increasing worldwide and can cause many chronic conditions such as type-2 diabetes, heart disease, sleep apnea, and some cancers. Monitoring dietary intake through food logging is a key method to maintain a healthy lifestyle to prevent and...
Image Processing, Computer-Assisted Food Neural Networks, Computer Machine Learning Databases, Factual Humans
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