AIMC Topic: Environment

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Decision Tree Algorithm Identifies Stroke Patients Likely Discharge Home After Rehabilitation Using Functional and Environmental Predictors.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Feb 3, 2021
BACKGROUND AND PURPOSE: The importance of environmental factors for stroke patients to achieve home discharge was not scientifically proven. There are limited studies on the application of the decision tree algorithm with various functional and envir...
Recovery of Function Predictive Value of Tests Databases, Factual Disability Evaluation Female Time Factors Motor Activity Aged Treatment Outcome Environment Decision Trees Aged, 80 and over Stroke Rehabilitation Male Middle Aged Humans Machine Learning Decision Support Techniques Functional Status Patient Discharge Stroke
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Domain randomization-enhanced deep learning models for bird detection.

Scientific reports Jan 12, 2021
Automatic bird detection in ornithological analyses is limited by the accuracy of existing models, due to the lack of training data and the difficulties in extracting the fine-grained features required to distinguish bird species. Here we apply the d...
Deep Learning Weather Random Allocation Animals Birds Environment Animal Migration
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Deep learning for automated analysis of fish abundance: the benefits of training across multiple habitats.

Environmental monitoring and assessment Oct 12, 2020
Environmental monitoring guides conservation and is particularly important for aquatic habitats which are heavily impacted by human activities. Underwater cameras and uncrewed devices monitor aquatic wildlife, but manual processing of footage is a si...
Deep Learning Environmental Monitoring Fishes Animals Ecosystem Environment Humans
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Quantifying the usage of small public spaces using deep convolutional neural network.

PloS one Oct 2, 2020
Small public spaces are the key built environment elements that provide venues for various of activities. However, existing measurements or approaches could not efficiently and effectively quantify how small public spaces are being used. In this pape...
Geography Deep Learning Environment Residence Characteristics
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Intuitionistic Fuzzy Hierarchical Multi-Criteria Decision Making for Evaluating Performances of Low-Carbon Tourism Scenic Spots.

International journal of environmental research and public health Aug 28, 2020
Low-carbon tourism is an effective solution to cope with the goal conflict between developing tourist economy and responding to carbon emission reduction and ecological environment protection. Tourism scenic spots are important carriers of tourist ac...
Carbon Decision Making Environment Travel Leisure Activities Carbon Footprint Models, Theoretical Fuzzy Logic Humans China
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[The use of artificial neural networks to classify the social vulnerability of municipalities in Rio Grande do Norte State, Brazil].

Cadernos de saude publica Aug 28, 2020
The objective was to apply artificial neural networks to classify municipalities (counties) in Rio Grande do Norte State, Brazil, according to their social vulnerability. This was an ecological study using 17 variables that reflected epidemiological,...
Neural Networks, Computer Brazil Cities Geography Humans Environment
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Multilevel approach to male fertility by machine learning highlights a hidden link between haematological and spermatogenetic cells.

Andrology Jun 21, 2020
BACKGROUND: Male infertility represents a complex clinical condition requiring an accurate multilevel assessment, in which machine learning technology, combining large data series in non-linear and highly interactive ways, could be innovatively appli...
Humans Machine Learning Algorithms Databases, Factual Retrospective Studies Infertility, Male Male Lymphocyte Count Erythrocyte Count Longitudinal Studies Hematopoiesis Spermatogenesis Female Semen Analysis Environment Adult
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Environmental influences on evolvable robots.

PloS one May 29, 2020
The field of Evolutionary Robotics addresses the challenge of automatically designing robotic systems. Furthermore, the field can also support biological investigations related to evolution. In this paper, we evolve (simulated) modular robots under d...
Seasons Environment Phenotype Robotics Algorithms
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ToyArchitecture: Unsupervised learning of interpretable models of the environment.

PloS one May 18, 2020
Research in Artificial Intelligence (AI) has focused mostly on two extremes: either on small improvements in narrow AI domains, or on universal theoretical frameworks which are often uncomputable, or lack practical implementations. In this paper we a...
Reinforcement, Psychology Learning Neural Networks, Computer Unsupervised Machine Learning Artificial Intelligence Environment Algorithms Humans
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Deep Multi-Critic Network for accelerating Policy Learning in multi-agent environments.

Neural networks : the official journal of the International Neural Network Society May 4, 2020
Humans live among other humans, not in isolation. Therefore, the ability to learn and behave in multi-agent environments is essential for any autonomous system that intends to interact with people. Due to the presence of multiple simultaneous learner...
Environment Machine Learning Learning Models, Neurological Humans
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