The use of polyacrylamides (PAMs) for removing natural organic matter (NOM) from Paraiba do Sul River (Brazil)

This work assesses the efficiency of polyacrylamides for natural organic matter (NOM) removal from Paraiba do Sul River (Brazil) raw water for drinking purposes. Jar tests were performed following an experimental design protocol. Three kinds of polyacrylamides (anionic, cationic, and non-ionic) at 0.2 mg L(-1) were tested. After coagulation, turbidity, DOC, UVA(254) and SCAN (UV-absorbing material) were determined. Color and pH were also measured. It was found that polyacrylamides did not reduce the amounts of alum and lime needed in the process and that the amount of alum alone for removing UV-absorbing organic matter is significantly higher. Efficiency of the coagulation process decreased as follows: non-ionic -> cationic -> anionic -> no polyacrylamide. Removal efficiencies for the best case were: 100%, 90%, 83%, and 68% for turbidity, DOC, UVA(254), and SCAN, respectively.

Removal of phenol in high salinity media by a hybrid process (activated sludge plus photocatalysis)

The degradation of phenol by a hybrid process (activated sludge + photocatalysis) in a high salinity medium (50 g L-1 of chloride) has been investigated. The sludge used from a municipal wastewater facility was adapted to the high salt concentrations prior to use. The photocatalytic conditions were optimized by means of a factorial experimental design. TiO2 P25 from Degussa was used as the photocatalyst. The initial phenol concentration was approximately 200 mg L-1 and complete removal of phenol and a mineralization degree above 98% were achieved within 25 h of treatment (24 h of biological treatment and I h of photocatalysis). From HPLC analyses, five hydroxylated intermediates formed during oxidation have been identified. The main ones were catechol and hydroquinone, followed by 1,2,4-benzenetriol, 2-hydroxy- 1,4-benzoquinone, and pyrogallol, in this order. No formation of organochlorine compounds was observed. Therefore, the proposed hybrid process showed itself to be suited to treat phenol in the presence of high contents of salt. (c) 2007 Elsevier B.V. All rights reserved.

Removal of Zn(2+) from Electroplating Wastewater Using Modified Wood Sawdust and Sugarcane Bagasse

This paper describes the preparation of new adsorbents derived from sugarcane bagasse and wood sawdust (Manilkara sp.) to remove zinc (II) ions from electroplating wastewater. The first part deals with the chemical modification of sugarcane bagasse and wood sawdust, using succinic anhydride to introduce carboxylic acid functions into the material. The obtained materials (modified sugarcane bagasse MB2 and modified wood sawdust MS2) were then characterized by infrared spectroscopy (IR) and used in adsorption experiments. The adsorption experiments evaluates Zn(2+) removal from aqueous single metal solution and real electroplating wastewater on both batch and continuous experiments using fixed-bed columns prepared in laboratorial scale with the obtained adsorbents. Adsorption isotherms were then developed using Langmuir model and the Thomas kinetic model. The calculated Zn(2+) adsorption capacities were found to be 145 mg/g for MS2 and 125 mg/g for MB2 in single metal aqueous solution, whereas for the industrial wastewater these values were 61 mg/g for MS2 and 55 mg/g for MB2.

Ink-Jet Printing of Color Optical Filters for LCD Applications

At the age of multi-media, portable electronic devices such as mobile phones, personal digital assistant and handheld gaming systems have increased the demand for high performance displays with low cost production. Inkjet printing color optical filters (COF) for LCD applications seem to be an interesting alternative to decrease the production costs. The advantage of inkjet printing technology is to be fast, accurate, easy to run and cheaper than other technologies. In this master thesis work, we used various disciplines such as optical microscopy, rheology, inkjet printing, profilometering and colorimetry. The specific aim of the thesis was to investigate the feasibility of using company-A pigment formulation in inkjet production of COF for active matrix LCD applications. Ideal viscosity parameters were determined from 10 to 20mPa·s for easy inkjet printing at room temperature. The red pigments used are fully dispersed into the solvent and present an excellent homogenous repartition after printing. Thickness investigations revealed that the printed COF were equal or slightly thicker than typically manufactured ones. The colorimetry investigations demonstrated color coordinates very close to the NTSC red standard. LED backlighting seems to be a valuable solution to combine with the printed COF regarding to the spectrum and color analysis. The results on this thesis will increase the understanding of inkjet printing company-A pigments to produce COF for LCD applications.

Processanalys vid Color Print Sweden AB med fokusering på prepressavdelningen

This thesis work has introduced process orientation at the printing company Color Print Sweden AB. The outcome ofthis work is a survey of the work flow at the prepress department. To visualise the production process at the companya comprehensive mapping of the main process, order-to-delivery, has been made. The work has detected a couple ofcritical elements in the existing process. These elements are the following: initial check of material delivered to the prepressdepartment as well as the control made of the plotter print-out, digital test print and plate. To guarantee the qualityof the prints it is very important that the work made in the prepress department is optimized. This survey can thereforebe used as a basis for continuous improvement in the processes at Color Print Sweden AB. This work has alsoresulted in a template that Color Print Sweden AB can use to design routine descriptions to ensure that specific worktasks are performed the right way by everyone and all the time.

Color Segmentation using LVQ-Learning Vector Quantization

This thesis aims to present a color segmentation approach for traffic sign recognition based on LVQ neural networks. The RGB images were converted into HSV color space, and segmented using LVQ depending on the hue and saturation values of each pixel in the HSV color space. LVQ neural network was used to segment red, blue and yellow colors on the road and traffic signs to detect and recognize them. LVQ was effectively applied to 536 sampled images taken from different countries in different conditions with 89% accuracy and the execution time of each image among 31 images was calculated in between 0.726sec to 0.844sec. The method was tested in different environmental conditions and LVQ showed its capacity to reasonably segment color despite remarkable illumination differences. The results showed high robustness.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

Color detection and segmentation for road and traffic signs

This paper aims to present three new methods for color detection and segmentation of road signs. The images are taken by a digital camera mounted in a car. The RGB images are converted into IHLS color space, and new methods are applied to extract the colors of the road signs under consideration. The methods are tested on hundreds of outdoor images in different light conditions, and they show high robustness. This project is part of the research taking place in Dalarna University / Sweden in the field of the ITS.

Application Of Real-Time Control Strategy To Improve Nitrogen Removal In Wastewater Treatment

Biological nitrogen removal is an important task in the wastewater treatment. However, the actual removal of total nitrogen (TN) in the wastewater treatment plant (WWTP) is often unsatisfactory due to several causes, one of which is the insufficient availability of carbon source. One possible approach to improve the nitrogen removal therefore is addition of external carbon source, while the amount of which is directly related to operation cost of a WWTP. It is obviously necessary to determine the accurate amount of addition of external carbon source according to the demand depending on the influent wastewater quality. This study focused on the real-time control of external carbon source addition based on the on-line monitoring of influent wastewater quality. The relationship between the influent wastewater quality (specifically the concentration of COD and ammonia) and the demand of carbon source was investigated through experiments on a pilot-scale A/O reactor (1m3) at the Nanjing WWTP, China. The minimum doses of carbon source addition at different situations of influent wastewater quality were determined to ensure the effluent wastewater quality meets the discharge standard. The obtained relationship is expected to be applied in the full-scale WWTPs. .