AIMC Topic: Environment

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Reactive navigation in extremely dense and highly intricate environments.

PloS one
Reactive navigation is a well-known paradigm for controlling an autonomous mobile robot, which suggests making all control decisions through some light processing of the current/recent sensor data. Among the many advantages of this paradigm are: 1) t...

Optic flow-based collision-free strategies: From insects to robots.

Arthropod structure & development
Flying insects are able to fly smartly in an unpredictable environment. It has been found that flying insects have smart neurons inside their tiny brains that are sensitive to visual motion also called optic flow. Consequently, flying insects rely ma...

Continuous detection of human fall using multimodal features from Kinect sensors in scalable environment.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automatic detection of human fall is a key problem in video surveillance and home monitoring. Existing methods using unimodal data (RGB / depth / skeleton) may suffer from the drawbacks of inadequate lighting condition or u...

Deep Learning for Plant Identification in Natural Environment.

Computational intelligence and neuroscience
Plant image identification has become an interdisciplinary focus in both botanical taxonomy and computer vision. The first plant image dataset collected by mobile phone in natural scene is presented, which contains 10,000 images of 100 ornamental pla...

A fuzzy logic-based tool to assess beef cattle ranching sustainability in complex environmental systems.

Journal of environmental management
One of the most relevant issues in discussion worldwide nowadays is the concept of sustainability. However, sustainability assessment is a difficult task due to the complexity of factors involved in the natural world added to the human interference. ...

How evolution learns to generalise: Using the principles of learning theory to understand the evolution of developmental organisation.

PLoS computational biology
One of the most intriguing questions in evolution is how organisms exhibit suitable phenotypic variation to rapidly adapt in novel selective environments. Such variability is crucial for evolvability, but poorly understood. In particular, how can nat...

Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach.

Computational intelligence and neuroscience
Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In th...

An Evolutionary Method for Financial Forecasting in Microscopic High-Speed Trading Environment.

Computational intelligence and neuroscience
The advancement of information technology in financial applications nowadays have led to fast market-driven events that prompt flash decision-making and actions issued by computer algorithms. As a result, today's markets experience intense activity i...

Preschoolers Flexibly Adapt to Linguistic Input in a Noisy Channel.

Psychological science
Because linguistic communication is inherently noisy and uncertain, adult language comprehenders integrate bottom-up cues from speech perception with top-down expectations about what speakers are likely to say. Further, in line with the predictions o...

Robust Satisficing Decision Making for Unmanned Aerial Vehicle Complex Missions under Severe Uncertainty.

PloS one
This paper presents a robust satisficing decision-making method for Unmanned Aerial Vehicles (UAVs) executing complex missions in an uncertain environment. Motivated by the info-gap decision theory, we formulate this problem as a novel robust satisfi...