Search results for "artificial intelligence"
showing 10 items of 6122 documents
An Observation Framework for Multi-Agent Systems
2009
Existing middleware platforms for multi-agent systems (MAS) do not provide general support for observation. On the other hand, observation is considered to be an important mechanism needed for realizing effective and efficient coordination of agents. This paper describes a framework called Agent Observable Environment (AOE) for observation-based interaction in MAS. The framework provides 1) possibility to model MAS components with RDFbased observable soft-bodies, 2) support for both query and publish/subscribe style ontology-driven observation, and 3) ability to restrict the visibility of observable information using observation rules. Additionally, we report on an implementation of the fra…
A Deep Learning Model for Automatic Sleep Scoring using Multimodality Time Series
2021
Sleep scoring is a fundamental but time-consuming process in any sleep laboratory. Automatic sleep scoring is crucial and urgent to help address the increasing unmet need for sleep research. Therefore, this paper aims to develop an end-to-end deep learning architecture using raw polysomnographic recordings to automate sleep scoring. The proposed model adopts two-dimensional convolutional neural networks (2D-CNN) to automatically learn features from multi-modality signals, together with a "squeeze and excitation" block for recalibrating channel-wise feature responses. The learnt representations are finally fed to a softmax classifier to generate predictions for each sleep stage. The model pe…
Skills Behind the Robotics : How to Re-educate Workers for the Future
2019
The aim of this study is to respond to the educational needs of the future, considering automation and robotics. It is inevitable that automation and robotics are changing our lives and they create challenges for the future work life and education. In this study, we investigate what is the educational background of the unemployed people who are in danger of being replaced by automation and what is their educational resilience for adapting work life changes. The data of this study consist of the latest PIAAC data (The Programme for the International Assessment of Adult Competencies). Based on the research we develop a model for re-educating the people who have lost their jobs. peerReviewed
Super-Resolution Images Methodology Applied to UAV Datasets to Road Pavement Monitoring
2022
The increasingly widespread use of smartphones as real cameras on drones has allowed an ever-greater development of several algorithms to improve the image’s refinement. Although the latest generations of drone cameras let the user achieve high resolution images, the large number of pixels to be processed and the acquisitions from multiple lengths for stereo-view often fail to guarantee satisfactory results. In particular, high flight altitudes strongly impact the accuracy, and result in images which are undefined or blurry. This is not acceptable in the field of road pavement monitoring. In that case, the conventional algorithms used for the image resolution conversion, such as the bilinea…
A novel pilot study of automatic identification of EMF radiation effect on brain using computer vision and machine learning
2020
Abstract Electromagnetic field (EMF) radiations from mobile phones and cell tower affect brain of humans and other organisms in many ways. Exposure to EMF could lead to neurological changes causing morphological or chemical changes in the brain and other internal organs. Cellular level analysis to measure and identify the effect of mobile radiations is an expensive and long process as it requires preparing the cell suspension for the analysis. This paper presents a novel pilot study to identify changes in brain morphology under EMF exposure considering drosophila melanogaster as a specimen. The brain is automatically segmented, obtaining microscopic images from which discriminatory geometri…
Robust Automated Assessment of Human Blastocyst Quality using Deep Learning
2018
AbstractMorphology assessment has become the standard method for evaluation of embryo quality and selecting human blastocysts for transfer inin vitro fertilization(IVF). This process is highly subjective for some embryos and thus prone to human bias. As a result, morphological assessment results may vary extensively between embryologists and in some cases may fail to accurately predict embryo implantation and live birth potential. Here we postulated that an artificial intelligence (AI) approach trained on thousands of embryos can reliably predict embryo quality without human intervention.To test this hypothesis, we implemented an AI approach based on deep neural networks (DNNs). Our approac…
On the Influence of Grammars on Crossover in Grammatical Evolution
2021
Standard grammatical evolution (GE) uses a one-point crossover (“ripple crossover”) that exchanges codons between two genotypes. The two resulting genotypes are then mapped to their respective phenotypes using a Backus-Naur form grammar. This article studies how different types of grammars affect the resulting individuals of a ripple crossover. We distinguish different grammars based on the expected number of non-terminals chosen when mapping genotype codons to phenotypes, \(B_{avg}\). The grammars only differ in \(B_{avg}\) but can express the same phenotypes. We perform crossover operations on the genotypes and find that grammars with \(B_{avg} > 1\) lead to high numbers of either very sm…
Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization
2019
AbstractVisual morphology assessment is routinely used for evaluating of embryo quality and selecting human blastocysts for transfer after in vitro fertilization (IVF). However, the assessment produces different results between embryologists and as a result, the success rate of IVF remains low. To overcome uncertainties in embryo quality, multiple embryos are often implanted resulting in undesired multiple pregnancies and complications. Unlike in other imaging fields, human embryology and IVF have not yet leveraged artificial intelligence (AI) for unbiased, automated embryo assessment. We postulated that an AI approach trained on thousands of embryos can reliably predict embryo quality with…
On the suffix automaton with mismatches
2007
International audience; In this paper we focus on the construction of the minimal deterministic finite automaton S_k that recognizes the set of suffixes of a word w up to k errors. We present an algorithm that makes use of S_k in order to accept in an efficient way the language of all suffixes of w up to k errors in every window of size r, where r is the value of the repetition index of w. Moreover, we give some experimental results on some well-known words, like prefixes of Fibonacci and Thue-Morse words, and we make a conjecture on the size of the suffix automaton with mismatches.
Anemia management in end stage renal disease patients undergoing dialysis: a comprehensive approach through machine learning techniques and mathemati…
2016
Kidney impairment has global consequences in the organism homeostasis and a disorder like Chronic Kidney Disease (CKD) might eventually exacerbates into End Stage Renal Disease (ESRD) where a complete renal replacement therapy like dialysis is necessary. Dialysis partially reintegrates the blood ltration process; however, even when it is associated to a pharmacological therapy, this is not su fficient to completely replace the renal endocrine role and causes the development of common complications, like CKD secondary anemia (CKD-anemia) The availability of exogenous Erythropoiesis Stimulating Agents (ESA, synthetic molecules with similar structure and same mechanism of action as human eryth…