Search results for "Artificial"
showing 10 items of 7394 documents
Benchmark database for fine-grained image classification of benthic macroinvertebrates
2018
Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categori…
A nondestructive intelligent approach to real‐time evaluation of chicken meat freshness based on computer vision technique
2019
In this study, the capability of a procedure based on combination of computer vision (CV) and artificial intelligence techniques examined for intelligent and nondestructive prediction of chicken meat freshness during the spoilage process at 4°C. The proposed system comprises the following stages: capture images, image preprocessing, image processing, computing channels, feature extraction, feature selection by a hybrid of genetic algorithm (GA) and artificial neuronal network (ANN), and prediction by using ANN. The number of neurons in input layer was determined 33 (selected features) and freshness used as the output. The ideal ANN model was obtained with 33‐10‐1 topology. The high performa…
Management Elements for Two Alburninae Species, Alburnus alburnus (Linnaeus, 1758) and Alburnoides bipunctatus (Bloch, 1782) Based on a Decision-Supp…
2019
Abstract ADONIS:CE has been used as a base to create a support-system management decision-making model for Alburnus alburnus (Linnaeus, 1758) and Alburnoides bipunctatus (Bloch, 1782) species. Investigation of the habitat necessities and the identification of the necessary elements for a good status of conservation of these two fish species populations has revealed the pressures and threats to these congener species, for which specific management activities have been finally recommended.
Decision support systems (DSS) for wastewater treatment plants - A review of the state of the art.
2019
The use of decision support systems (DSS) allows integrating all the issues related with sustainable development in view of providing a useful support to solve multi-scenario problems. In this work an extensive review on the DSSs applied to wastewater treatment plants (WWTPs) is presented. The main aim of the work is to provide an updated compendium on DSSs in view of supporting researchers and engineers on the selection of the most suitable method to address their management/operation/design problems. Results showed that DSSs were mostly used as a comprehensive tool that is capable of integrating several data and a multi-criteria perspective in order to provide more reliable results. Only …
Anaerobic membrane bioreactors (AnMBR) treating urban wastewater in mild climates
2020
[EN] Feasibility of an AnMBR demonstration plant treating urban wastewater (UWW) at temperatures around 25-30 degrees C was assessed during a 350-day experimental period. The plant was fed with the effluent from the pretreatment of a full-scale municipal WWTP, characterized by high COD and sulfate concentrations. Biodegradability of the UWW reached values up to 87%, although a portion of the biodegradable COD was consumed by sulfate reducing organisms. Effluent COD remained below effluent discharge limits, achieving COD removals above 90%. System operation resulted in a reduction of sludge production of 36-58% compared to theoretical aerobic sludge productions. The membranes were operated a…
A plant-wide modelling comparison between membrane bioreactors and conventional activated sludge
2020
Abstract A comprehensive plant-wide mathematical modelling comparison between conventional activated sludge (CAS) and Membrane bioreactor (MBR) systems is presented. The main aim of this study is to highlight the key features of CAS and MBR in order to provide a guide for an effective plant operation. A scenario analysis was performed to investigate the influence on direct and indirect greenhouse gas (GHG) emissions and operating costs of (i) the composition of inflow wastewater (scenario 1), (ii) operating conditions (scenario 2) and (iii) oxygen transfer efficiency (scenario 3). Scenarios show higher indirect GHG emissions for MBR than CAS, which result is related to the higher energy con…
Simple learning rules to cope with changing environments
2008
10 pages; International audience; We consider an agent that must choose repeatedly among several actions. Each action has a certain probability of giving the agent an energy reward, and costs may be associated with switching between actions. The agent does not know which action has the highest reward probability, and the probabilities change randomly over time. We study two learning rules that have been widely used to model decision-making processes in animals-one deterministic and the other stochastic. In particular, we examine the influence of the rules' 'learning rate' on the agent's energy gain. We compare the performance of each rule with the best performance attainable when the agent …
Thompson Sampling Based Active Learning in Probabilistic Programs with Application to Travel Time Estimation
2019
The pertinent problem of Traveling Time Estimation (TTE) is to estimate the travel time, given a start location and a destination, solely based on the coordinates of the points under consideration. This is typically solved by fitting a function based on a sequence of observations. However, it can be expensive or slow to obtain labeled data or measurements to calibrate the estimation function. Active Learning tries to alleviate this problem by actively selecting samples that minimize the total number of samples needed to do accurate inference. Probabilistic Programming Languages (PPL) give us the opportunities to apply powerful Bayesian inference to model problems that involve uncertainties.…
Temperate Fish Detection and Classification: a Deep Learning based Approach
2021
A wide range of applications in marine ecology extensively uses underwater cameras. Still, to efficiently process the vast amount of data generated, we need to develop tools that can automatically detect and recognize species captured on film. Classifying fish species from videos and images in natural environments can be challenging because of noise and variation in illumination and the surrounding habitat. In this paper, we propose a two-step deep learning approach for the detection and classification of temperate fishes without pre-filtering. The first step is to detect each single fish in an image, independent of species and sex. For this purpose, we employ the You Only Look Once (YOLO) …
Machine learning predictions of trophic status indicators and plankton dynamic in coastal lagoons
2018
Abstract Multivariate trophic indices provide an efficient way to assess and classify the eutrophication level and ecological status of a given water body, but their computation requires the availability of experimental information on many parameters, including biological data, that might not always be available. Here we show that machine learning techniques – once trained against a full data set – can be used to infer plankton biomass information from chemical and physical parameter only, so that trophic index can then be computed without using additional biological data. More specifically, we reconstruct plankton information from chemical and physical data, and this information together w…