Search results for "Extraction"

Ekstrakcja fosforu z osadów ściekowych i popiołów ze spalania osadów - analiza problemu

2016

Fosfor jako pierwiastek niezbędny do produkcji rolniczej, w miarę wyczerpywania się zasobów fosforytów, staje się komponentem coraz bardziej deficytowym. Koniecznym wydaje się wdrożenie metod taniego i efektywnego odzysku tego pierwiastka z wszelkiego rodzaju odpadów. Szczególnie cennym źródłem fosforu są popioły z osadów ściekowych i same osady. Optymalizacja metod sekwencyjnej ekstrakcji fosforu zawartego w popiele z termicznego przekształcania osadów ściekowych i odwodnionych osadów pozwala na wybór efektywnej i nieskomplikowanej technologicznie możliwości odzysku fosforu, przy jednoczesnym zachowaniu niskiego obciążenia eluatu metalami ciężkimi, które są jedną z głównych przyczyn ograni…

Metody wydzielania, zatężania i oznaczania związków fenolowych z próbek środowiskowych i żywności

2011

Identification of metalloporphyrins extracted from the copper bearing black shale of fore sudetic monocline (Poland)

2006

Abstract Metalloporphyrins were isolated from copper-bearing black shale ores. The shale originates from the Lubin copper mine (Poland). The porphyrins have been extracted by way of a Soxhlet apparatus, and then purified using column chromatography. In order to identify the extracted porphyrins complexes UV–Vis, mass spectrometry and EPR analytical techniques have been used.

A review of sustainable and intensified techniques for extraction of food and natural products

2020

International audience; This review presents innovative extraction techniques and their role in promoting sustainable ingredients forthe food, cosmetic and pharmaceutical industries. These techniques (such as microwave, ultrasound, pulseelectricfield, instant controlled pressure drop, sub- and super-criticalfluid processing, extrusion, mechano-chemistry, high pressure, and ohmic, UV and IR heating) use or produce less solvent, energy, and hazards.This review will provide the necessary theoretical background and some details about green extractiontechniques, their mechanisms, some applications, and environmental impacts. We will pay special attentionto the strategies and present them as succ…

Influence of anxiety and anesthetic vasoconstrictors upon hemodynamic parameters during dental procedures in controlled hypertensive and non-hyperten…

2020

Background To determine the influence of dental anxiety and the vasoconstrictor used in local anesthesia upon different hemodynamic parameters - systolic (SBP) and diastolic blood pressure (DBP), heart rate (HR) and peripheral oxygen saturation (SatO2) - during dental extraction and oral hygiene. The safety of local anesthesia with vasoconstrictor in patients with medically controlled hypertension was also assessed. Material and methods A total of 159 patients were divided into two groups according to the dental treatment received: tooth extraction (n = 106) and oral hygiene (n = 53). The hemodynamic parameters (SBP, DBP, HR and SatO2) were recorded throughout dental treatment. Patient anxi…

Multiple Classifiers and Data Fusion for Robust Diagnosis of Gearbox Mixed Faults

2019

Detection and isolation of single and mixed faults in a gearbox are very important to enhance the system reliability, lifetime, and service availability. This paper proposes a hybrid learning algorithm, consisting of multilayer perceptron (MLP)- and convolutional neural network (CNN)-based classifiers, for diagnosis of gearbox mixed faults. Domain knowledge features are required to train the MLP classifier, while the CNN classifier can learn features itself, allowing to reduce the required knowledge features for the counterpart. Vibration data from an experimental setup with gearbox mixed faults is used to validate the effectiveness of the algorithms and compare them with conventional metho…

Multiscale Attention-Based Prototypical Network For Few-Shot Semantic Segmentation

2021

International audience; Deep learning-based image understanding techniques require a large number of labeled images for training. Few-shot semantic segmentation, on the contrary, aims at generalizing the segmentation ability of the model to new categories given only a few labeled samples. To tackle this problem, we propose a novel prototypical network (MAPnet) with multiscale feature attention. To fully exploit the representative features of target classes, we firstly extract rich contextual information of labeled support images via a multiscale feature enhancement module. The learned prototypes from support features provide further semantic guidance on the query image. Then we adaptively i…

Proposition of Convolutional Neural Network Based System for Skin Cancer Detection

2019

Skin cancer automated diagnosis tools play a vital role in timely screening, helping dermatologists focus on melanoma cases. Best arts on automated melanoma screening use deep learning-based approaches, especially deep convolutional neural networks (CNN) to improve performances. Because of the large number of parameters that could be involved during training in CNN many training samples are needed to avoid overfitting problem. Gabor filtering can efficiently extract spatial information including edges and textures, which may reduce the features extraction burden to CNN. In this paper, we proposed a Gabor Convolutional Network (GCN) model to improve the performance of automated diagnosis of …

Combination Of Handcrafted And Deep Learning-Based Features For 3d Mesh Quality Assessment

2020

We propose in this paper a novel objective method to evaluate the perceived visual quality of 3D meshes. The proposed method in no-reference, it relies only on the distorted mesh for the quality estimation. It is based on a pre-trained convolutional neural network (i.e VGG to extract features from the distorted mesh) and handcrafted features extracted directly from the 3D mesh (i.e curvature and dihedral angle). A General Regression Neural Network (GRNN) is used to learn the statistical parameters of the feature vectors and estimate the quality score. Experimental results from for subjective databases (LIRIS masking, LIRIS/EPFL generalpurpose, UWB compression and LEETA simplification) and c…

Robust auto calibration technique for stereo camera

2017

Calibration of the internal and external parameters of a stereo vision camera is a well-known research problem in the computer vision. Usually, to get accurate 3D results the camera should be manually calibrate accurately as well. This paper proposes a robust approach to Auto Calibration stereo camera Without intervention of the user. There are several methods and techniques of calibration that have been proven, in this work we exploiting the geometric constraint, namely, the epipolar geometry. We specifically focuses to use 7 techniques for Features Extraction (SURF, BRISK, FAST, FREAK, MinEigen, MSERF, SIFT), however tries to establish the correspondences between points extracted in stere…