Optimization of NMP extraction in 1, 3-butadiene production line

N-methylpyrrolidone is a powerful solvent for variety of chemical processes due to its vast chemical properties. It has been used in manufacturing processes of polymers, detergents, pharmaceuticals rubber and many more chemical substances. However, it creates large amount of residue in some of these processes which has to be dealt with. Many well known methods such as BASF in rubber producing units have tried to regenerate the solvent at the end of each run, however, there is still discarding of large amount of residue containing NMP, which over time, could cause environmental concerns. In this study, we have tried to optimize regeneration of the NMP extraction from butadiene production. It is shown that at higher temperatures NMP is separated from the residue with close to 90% efficiency, and the solvent residue proved to be the most effective with a 6: 1 ratio.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

A Technique for Digital Color Image Watermarking Using ICA

With the increase of use of digital media the need for the methods of multimedia protection becomes extremely important. The number of the solutions to the problem from encryption to watermarking is large and is growing every year. In this work digital image watermarking is considered, specifically a novel method of digital watermarking of color and spectral images. An overview of existing methods watermarking of color and grayscale images is given in the paper. Methods using independent component analysis (ICA) for detection and the ones using discrete wavelet transform (DWT) and discrete cosine transform (DCT) are considered in more detail. A novel method of watermarking proposed in this paper allows embedding of a color or spectral watermark image into color or spectral image consequently and successful extraction of the watermark out of the resultant watermarked image. A number of experiments have been performed on the quality of extraction depending on the parameters of the embedding procedure. Another set of experiments included the test of the robustness of the algorithm proposed. Three techniques have been chosen for that purpose: median filter, low-pass filter (LPF) and discrete cosine transform (DCT), which are a part of a widely known StirMark - Image Watermarking Robustness Test. The study shows that the proposed watermarking technique is fragile, i.e. watermark is altered by simple image processing operations. Moreover, we have found that the contents of the image to be watermarked do not affect the quality of the extraction. Mixing coefficients, that determine the amount of the key and watermark image in the result, should not exceed 1% of the original. The algorithm proposed has proven to be successful in the task of watermark embedding and extraction.

Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants

This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.

Detection of soybean planted areas through orbital images based on culture spectral dynamics

The soybean is important to the economy of Brazil, so the estimation of the planted area and the production with higher antecedence and reliability becomes essential. Techniques related to Remote Sensing may help to obtain this information at lower cost and less subjectivity in relation to traditional surveys. The aim of this study is to estimate the planted area with soybean culture in the crop of 2008/2009 in cities in the west of the state of Paraná, in Brazil, based on the spectral dynamics of the culture and through the use of the specific system of analysis for images of Landsat 5/TM satellite. The obtained results were satisfactory, because the classification supervised by Maximum Verisimilitude - MaxVer along with the techniques of the specific system of analysis for satellite images has allowed an estimate of soybean planted area (soybean mask), obtaining values ​​of the metrics of Global Accuracy with an average of 79.05% and Kappa Index over 63.50% in all cities. The monitoring of a reference area was of great importance for determining the vegetative phase in which the culture is more different from the other targets, facilitating the choice of training samples (ROIs) and avoiding misclassifications.

Influence of data acquisition geometry on soybean spectral response simulated by the prosail model

View angle and directional effects significantly affect reflectance and vegetation indices, especially when daily images collected by large field-of-view (FOV) sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) are used. In this study, the PROSAIL radiative transfer model was chosen to evaluate the impact of the geometry of data acquisition on soybean reflectance and two vegetation indices (Normalized Difference Vegetation Index - NDVI and Enhanced Vegetation Index -EVI) by varying biochemical and biophysical parameters of the crop. Input values for PROSAIL simulation were based on the literature and were adjusted by the comparison between simulated and real satellite soybean spectra acquired by the MODIS/Terra and hyperspectral Hyperion/Earth Observing-One (EO-1). Results showed that the influence of the view angle and view direction on reflectance was stronger with decreasing leaf area index (LAI) and chlorophyll concentration. Because of the greater dependence on the near-infrared reflectance, the EVI was much more sensitive to viewing geometry than NDVI presenting larger values in the backscattering direction. The contrary was observed for NDVI in the forward scattering direction. In relation to the LAI, NDVI was much more isotropic for closed soybean canopies than for incomplete canopies and a contrary behavior was verified for EVI.

Evaluation of protein extraction methods to obtain protein concentrate from cassava leaf

The cassava leaf, waste generated in the harvest of the roots, is characterized by high content of protein, vitamins and minerals; however, its use is limited due to the high fiber content and antinutritional substances, which can be removed by obtaining protein concentrates. In this context, the objective of this study was to evaluate protein extraction processes, aiming the use of cassava leaves (Manihot esculenta Crantz) as an alternative protein. Four methods were tested: 1) Coagulation of Proteins by Lowering the Temperature, 2) Extraction by Isoelectric Precipitation, 3) Solubilization of Proteins and 4) Fermentation of Filter Leaf Juice. To obtain the concentrates, the use of fresh or dried leaves and extraction in one or two steps were also evaluated. The solubilization of proteins (method 3) showed a higher extraction yield; however, with concentrate of low quality. The fermentation of the juice (method 4) produced concentrates with higher quality and lower costs and the isoelectric precipitation (method 2) promoted the obtention of concentrates in less time, both with good prospects for use. The use of two extraction steps was not advantageous to the process and there was no difference between the use of fresh or dried leaf, and the use of fresh leaves is presented as a good option for the simplicity of the method.

Cassava starch extraction effluent treatment in a one phase tubular horizontal pilot reactor with support medium

The cassava starch industries generate a large volume of wastewater effluent that, stabilized in ponds, wastes its biogas energy and pollutes the atmosphere. To contribute with the reversion of this reality, this manipueira treatment research was developed in one phase anaerobic horizontal pilot reactor with support medium in bamboo pieces. The reactor was excavated into the ground and sealed with geomembrane in HDPE, having a volume equal to 33.6 m³ and continuous feeding by gravity. The stability indicators were pH, volatile acidity/total alkalinity ratio and biogas production. The statistical analyses were performed by a completely randomized design, with answers submitted to multivariate analysis. The organical loads in COD were 0.556; 0.670; 0.678 and 0.770 g L-1 and in volatile solids (VS) of 0.659; 0.608; 0.570 and 0.761 g L-1 for the hydraulic retention times (HRT) of 13.0; 11.5; 10.0 and 7.0 days, respectively. The reductions in COD were 88; 80; 88 and 67% and for VS of 76; 77; 65 and 61%. The biogas productions relatively to the consumed COD were 0.368; 0.795; 0.891 and 0.907 Lg-1, for the consumed VS of 0.524; 0.930; 1.757 and 0.952 Lg-1 and volumetric of 0.131; 0.330; 0.430 and 0.374 L L-1 d-1. The reactor remained stable and the bamboo pieces, in visual examination at the end of the experiment, showed to be in good physical conditions.

HYDROPHOBIC MEMBRANE TECHNOLOGY FOR AMMONIA EXTRACTION FROM WASTEWATERS

ABSTRACT Total Ammoniacal Nitrogen - TAN (NH3 + NH4+) in wastewaters cause environmental degradation concerns due to their negative impacts on air, soil and water. Several technologies are available for TAN removal from the wastewaters. One emerging technology is the use of hydrophobic membrane as non-destructive NH3 extraction. In this paper the authors discuss the uses of gas permeable membrane (GPM) and its physicochemical characteristics that influence gas mass transfer rate, diffusion and recovery mechanisms of NH3 from liquid sources (e.g. animal wastewater). Several aspects of NH3 extraction from liquid manure and other TAN generation sources using GPM technology as well as its applicability for NH3 mitigation from liquid effluents and possible recovery as a nutrient for plant growth are also discussed in this review.

Feature selection using Fuzzy Entropy measures with Yu's Similarity measure

In this study, feature selection in classification based problems is highlighted. The role of feature selection methods is to select important features by discarding redundant and irrelevant features in the data set, we investigated this case by using fuzzy entropy measures. We developed fuzzy entropy based feature selection method using Yu's similarity and test this using similarity classifier. As the similarity classifier we used Yu's similarity, we tested our similarity on the real world data set which is dermatological data set. By performing feature selection based on fuzzy entropy measures before classification on our data set the empirical results were very promising, the highest classification accuracy of 98.83% was achieved when testing our similarity measure to the data set. The achieved results were then compared with some other results previously obtained using different similarity classifiers, the obtained results show better accuracy than the one achieved before. The used methods helped to reduce the dimensionality of the used data set, to speed up the computation time of a learning algorithm and therefore have simplified the classification task

Novel Regression Methods For Spectral Data

Singular Value Decomposition (SVD), Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) are some of the mathematical pre- liminaries that are discussed prior to explaining PLS and PCR models. Both PLS and PCR are applied to real spectral data and their di erences and similarities are discussed in this thesis. The challenge lies in establishing the optimum number of components to be included in either of the models but this has been overcome by using various diagnostic tools suggested in this thesis. Correspondence analysis (CA) and PLS were applied to ecological data. The idea of CA was to correlate the macrophytes species and lakes. The di erences between PLS model for ecological data and PLS for spectral data are noted and explained in this thesis. i

The Design and Implementation of a Power Management Feature to a Configuration Management System

Green IT is a term that covers various tasks and concepts that are related to reducing the environmental impact of IT. At enterprise level, Green IT has significant potential to generate sustainable cost savings: the total amount of devices is growing and electricity prices are rising. The lifecycle of a computer can be made more environmentally sustainable using Green IT, e.g. by using energy efficient components and by implementing device power management. The challenge using power management at enterprise level is how to measure and follow-up the impact of power management policies? During the thesis a power management feature was developed to a configuration management system. The feature can be used to automatically power down and power on PCs using a pre-defined schedule and to estimate the total power usage of devices. Measurements indicate that using the feature the device power consumption can be monitored quite precisely and the power consumption can be reduced, which generates electricity cost savings and reduces the environmental impact of IT.

Intrapartum hypoxia and power spectral analysis of fetal heart rate variability

Reliable detection of intrapartum fetal acidosis is crucial for preventing morbidity. Hypoxia-related changes of fetal heart rate variability (FHRV) are controlled by the autonomic nervous system. Subtle changes in FHRV that cannot be identified by inspection can be detected and quantified by power spectral analysis. Sympathetic activity relates to low-frequency FHRV and parasympathetic activity to both low- and high-frequency FHRV. The aim was to study whether intra partum fetal acidosis can be detected by analyzing spectral powers of FHRV, and whether spectral powers associate with hypoxia-induced changes in the fetal electrocardiogram and with the pH of fetal blood samples taken intrapartum. The FHRV of 817 R-R interval recordings, collected as a part of European multicenter studies, were analyzed. Acidosis was defined as cord pH ≤ 7.05 or scalp pH ≤ 7.20, and metabolic acidosis as cord pH ≤ 7.05 and base deficit ≥ 12 mmol/l. Intrapartum hypoxia increased the spectral powers of FHRV. As fetal acidosis deepened, FHRV decreased: fetuses with significant birth acidosis had, after an initial increase, a drop in spectral powers near delivery, suggesting a breakdown of fetal compensation. Furthermore, a change in excess of 30% of the low-to-high frequency ratio of FHRV was associated with fetal metabolic acidosis. The results suggest that a decrease in the spectral powers of FHRV signals concern for fetal wellbeing. A single measure alone cannot be used to reveal fetal hypoxia since the spectral powers vary widely intra-individually. With technical developments, continuous assessment of intra-individual changes in spectral powers of FHRV might aid in the detection of fetal compromise due to hypoxia.

Theoretical Analysis and Numerical Simulation of Spectral Radiative Properties of Combustion Gases in Oxy/Air-Fired Combustion Systems

Energy efficiency is one of the major objectives which should be achieved in order to implement the limited energy resources of the world in a sustainable way. Since radiative heat transfer is the dominant heat transfer mechanism in most of fossil fuel combustion systems, more accurate insight and models may cause improvement in the energy efficiency of the new designed combustion systems. The radiative properties of combustion gases are highly wavelength dependent. Better models for calculating the radiative properties of combustion gases are highly required in the modeling of large scale industrial combustion systems. With detailed knowledge of spectral radiative properties of gases, the modeling of combustion processes in the different applications can be more accurate. In order to propose a new method for effective non gray modeling of radiative heat transfer in combustion systems, different models for the spectral properties of gases including SNBM, EWBM, and WSGGM have been studied in this research. Using this detailed analysis of different approaches, the thesis presents new methods for gray and non gray radiative heat transfer modeling in homogeneous and inhomogeneous H2O–CO2 mixtures at atmospheric pressure. The proposed method is able to support the modeling of a wide range of combustion systems including the oxy-fired combustion scenario. The new methods are based on implementing some pre-obtained correlations for the total emissivity and band absorption coefficient of H2O–CO2 mixtures in different temperatures, gas compositions, and optical path lengths. They can be easily used within any commercial CFD software for radiative heat transfer modeling resulting in more accurate, simple, and fast calculations. The new methods were successfully used in CFD modeling by applying them to industrial scale backpass channel under oxy-fired conditions. The developed approaches are more accurate compared with other methods; moreover, they can provide complete explanation and detailed analysis of the radiation heat transfer in different systems under different combustion conditions. The methods were verified by applying them to some benchmarks, and they showed a good level of accuracy and computational speed compared to other methods. Furthermore, the implementation of the suggested banded approach in CFD software is very easy and straightforward.

Recovery of carboxylic acids from aqueous streams by extraction and back extraction

Separation of carboxylic acids from aqueous streams is an important part of their manufacturing process. The aqueous solutions are usually dilute containing less than 10 % acids. Separation by distillation is difficult as the boiling points of acids are only marginally higher than that of water. Because of this distillation is not only difficult but also expensive due to the evaporation of large amounts of water. Carboxylic acids have traditionally been precipitated as calcium salts. The yields of these processes are usually relatively low and the chemical costs high. Especially the decomposition of calcium salts with sulfuric acid produces large amounts of calcium sulfate sludge. Solvent extraction has been studied as an alternative method for recovery of carboxylic acids. Solvent extraction is based on mixing of two immiscible liquids and the transfer of the wanted components form one liquid to another due to equilibrium difference. In the case of carboxylic acids, the acids are transferred from aqueous phase to organic solvent due to physical and chemical interactions. The acids and the extractant form complexes which are soluble in the organic phase. The extraction efficiency is affected by many factors, for instance initial acid concentration, type and concentration of the extractant, pH, temperature and extraction time. In this paper, the effects of initial acid concentration, type of extractant and temperature on extraction efficiency were studied. As carboxylic acids are usually the products of the processes, they are wanted to be recovered. Hence the acids have to be removed from the organic phase after the extraction. The removal of acids from the organic phase also regenerates the extractant which can be then recycled in the process. The regeneration of the extractant was studied by back-extracting i.e. stripping the acids form the organic solution into diluent sodium hydroxide solution. In the solvent regeneration, the regenerability of different extractants and the effect of initial acid concentration and temperature were studied.