AIMC Topic: Bees

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Habitat Suitability Modelling for the Red Dwarf Honeybee (Apis florea (Linnaeus)) and Its Distribution Prediction Using Machine Learning and Cloud Computing.

Neotropical entomology Dec 17, 2024
Apis florea bees were recently identified in Egypt, marking the second occurrence of this species on the African continent. The objective of this study was to track the distribution of A. florea in Egypt and evaluate its potential for invasive behavi...
Machine Learning Temperature Egypt Bees Animal Distribution Animals Ecosystem
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Optimal feature selection for heart disease prediction using modified Artificial Bee colony (M-ABC) and K-nearest neighbors (KNN).

Scientific reports Oct 31, 2024
Heart disease is a complex and widespread illness that affects a significant number of people worldwide. Machine learning provides a way forward for early heart disease diagnosis. A classification model has been developed for the present study to pre...
Heart Diseases Bees Humans Machine Learning Algorithms
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Bee Together: Joining Bee Audio Datasets for Hive Extrapolation in AI-Based Monitoring.

Sensors (Basel, Switzerland) Sep 19, 2024
Beehive health monitoring has gained interest in the study of bees in biology, ecology, and agriculture. As audio sensors are less intrusive, a number of audio datasets (mainly labeled with the presence of a queen in the hive) have appeared in the li...
Animals Bees Artificial Intelligence Algorithms
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Improving Human Activity Recognition With Wearable Sensors Through BEE: Leveraging Early Exit and Gradient Boosting.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 18, 2024
Early-exiting has recently provided an ideal solution for accelerating activity inference by attaching internal classifiers to deep neural networks. It allows easy activity samples to be predicted at shallower layers, without executing deeper layers,...
Deep Learning Wearable Electronic Devices Pattern Recognition, Automated Machine Learning Bees Humans Algorithms Neural Networks, Computer Human Activities
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Non-Intrusive System for Honeybee Recognition Based on Audio Signals and Maximum Likelihood Classification by Autoencoder.

Sensors (Basel, Switzerland) Aug 21, 2024
Artificial intelligence and Internet of Things are playing an increasingly important role in monitoring beehives. In this paper, we propose a method for automatic recognition of honeybee type by analyzing the sound generated by worker bees and drone ...
Bees Likelihood Functions Neural Networks, Computer Animals Algorithms Signal Processing, Computer-Assisted Artificial Intelligence
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Robotic flytrap with an ultra-sensitive 'trichome' and fast-response 'lobes'.

Bioinspiration & biomimetics Aug 14, 2024
Nature abounds with examples of ultra-sensitive perception and agile body transformation for highly efficient predation as well as extraordinary adaptation to complex environments. Flytraps, as a representative example, could effectively detect the m...
Equipment Design Biomimetics Bees Animals Robotics Touch Flight, Animal
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Investigating the impact of climate variables on the organic honey yield in Turkey using XGBoost machine learning.

Journal of the science of food and agriculture Aug 9, 2024
BACKGROUND: The Turkish organic honey industry, a major player in the global market, faces challenges due to climate fluctuations. Understanding the influence of climate factors on honey production is vital for sustainable farming and economic stabil...
Organic Agriculture Beekeeping Climate Change Humidity Wind Animals Honey Bees Turkey Machine Learning Temperature
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High-resolution proteomics and machine-learning identify protein classifiers of honey made by Sicilian black honeybees (Apis mellifera ssp. sicula).

Food research international (Ottawa, Ont.) Aug 8, 2024
Apis mellifera ssp. sicula, also known as the Sicilian black honeybee, is a Slow Food Presidium that produces honey with outstanding nutraceutical properties, including high antioxidant capacity. In this study, we used high-resolution proteomics to p...
Animals Proteomics Bees Proteome Machine Learning Insect Proteins Honey
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Bee-inspired insights: Unleashing the potential of artificial bee colony optimized hybrid neural networks for enhanced groundwater level time series prediction.

Environmental monitoring and assessment Jul 11, 2024
Analysis of the change in groundwater used as a drinking and irrigation water source is of critical importance in terms of monitoring aquifers, planning water resources, energy production, combating climate change, and agricultural production. Theref...
Environmental Monitoring Bees Animals Groundwater Neural Networks, Computer Algorithms
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Varroa Mite Counting Based on Hyperspectral Imaging.

Sensors (Basel, Switzerland) Jul 9, 2024
Varroa mite infestation poses a severe threat to honeybee colonies globally. This study investigates the feasibility of utilizing the HS-Cam and machine learning techniques for Varroa mite counting. The methodology involves image acquisition, dimensi...
Animals Bees Image Processing, Computer-Assisted Support Vector Machine Hyperspectral Imaging Machine Learning Principal Component Analysis Varroidae Algorithms
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