1,720,981 research outputs found
Microalgae: An alternative source of biodiesel for the compression ignition (CI) engine
No full textThis thesis is a comprehensive study of microalgae biodiesel for the compression ignition engine. It examines microalgae growing conditions, the extraction process and physiochemical properties with a wide range of microalgae species. It also evaluates microalgae biodiesel with regards to engine performance and emission characteristics and explains the difficulties and potentiality of microalgae as a biodiesel. In doing so, an extensive analysis of different extraction methods and engine testing was conducted and a comprehensive study on microalgae biodiesel is presented
Environmental incidents in a developing country and\ud corporate environmental disclosures : a study of a multinational gas company
No full textPurpose – The purpose of this paper is to examine the environmental disclosure initiatives of Niko Resources Ltd – a Canada-based multinational oil and gas company – following the two major environmental blowouts at a gas field in Bangladesh in 2005. As part of the examination, the authors particularly focus on whether Niko's disclosure strategy was associated with public concern pertaining to the blowouts. \ud
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Design/methodology/approach – The authors reviewed news articles about Niko's environmental incidents in Bangladesh and Niko's communication media, including annual reports, press releases and stand-alone social responsibility report over the period 2004-2007, to understand whether news media attention as proxy for public concern has an impact on Niko's disclosure practices in relation to the affected local community in Bangladesh. \ud
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Findings – The findings show that Niko did not provide any non-financial environmental information within its annual reports and press releases as a part of its responsibility to the local community which was affected by the blowouts, but it did produce a stand-alone report to address the issue. However, financial environmental disclosures, such as the environmental contingent liability disclosure, were adequately provided through annual reports to meet the regulatory requirements concerning environmental persecutions. The findings also suggest that Niko's non-financial disclosure within a stand-alone report was associated with the public pressures as measured by negative media coverage towards the Niko blowouts. \ud
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Research limitations/implications – This paper concludes that the motive for Niko's non-financial environmental disclosure, via a stand-alone report, reflected survival considerations: the company's reaction did not suggest any real attempt to hold broader accountability for its activities in a developing country
Effect of temperature and moisture on high pressure lipid/oil extraction from microalgae
No full textCommercially viable carbon–neutral biodiesel production from microalgae has potential for replacing depleting petroleum diesel. The process of biodiesel production from microalgae involves harvesting, drying and extraction of lipids which are energy- and cost-intensive processes. The development of effective large-scale lipid extraction processes which overcome the complexity of microalgae cell structure is considered one of the most vital requirements for commercial production. Thus the aim of this work was to investigate suitable extraction methods with optimised conditions to progress opportunities for sustainable microalgal biodiesel production. In this study, the green microalgal species consortium, Tarong polyculture was used to investigate lipid extraction with hexane (solvent) under high pressure and variable temperature and biomass moisture conditions using an Accelerated Solvent Extraction (ASE) method. The performance of high pressure solvent extraction was examined over a range of different process and sample conditions (dry biomass to water ratios (DBWRs): 100%, 75%, 50% and 25% and temperatures from 70 to 120 °C, process time 5–15 min). Maximum total lipid yields were achieved at 50% and 75% sample dryness at temperatures of 90–120 °C. We show that individual fatty acids (Palmitic acid C16:0; Stearic acid C18:0; Oleic acid C18:1; Linolenic acid C18:3) extraction optima are influenced by temperature and sample dryness, consequently affecting microalgal biodiesel quality parameters. Higher heating values and kinematic viscosity were compliant with biodiesel quality standards under all extraction conditions used. Our results indicate that biodiesel quality can be positively manipulated by selecting process extraction conditions that favour extraction of saturated and mono-unsaturated fatty acids over optimal extraction conditions for polyunsaturated fatty acids, yielding positive effects on cetane number and iodine values. Exceeding biodiesel standards for these two parameters opens blending opportunities with biodiesels that fall outside the minimal cetane and maximal iodine values
Modeling of a magneto-rheological (MR) fluid damper using a self tuning fuzzy mechanism
No full textA magneto-rheological (MR) fluid damper is a semi-active control device that has recently begun to receive more attention
in the vibration control community. However, the inherent nonlinear nature of the MR fluid damper makes it challenging to
use this device to achieve high damping control system performance. The development of an accurate modeling method for a MR
fluid damper is necessary because of its unique characteristics. Our goal was to develop an alternative method for modeling
an MR fluid damper by using a self tuning fuzzy (STF) method based on neural technique. The behavior of the researched damper
is directly estimated through a fuzzy mapping system. To improve the accuracy of the STF model, a back propagation and a gradient
descent method are used to train online the fuzzy parameters to minimize the model error function. A series of simulations
were done to validate the effectiveness of the suggested modeling method when compared with the data measured from experiments
on a test rig with a researched MR fluid damper. Finally, modeling results show that the proposed STF interference system
trained online by using neural technique could describe well the behavior of the MR fluid damper without need of calculation
time for generating the model parameter
Influence of fatty acid structure on fuel properties of algae derived biodiesel
Full text linkPhysical and chemical properties of biofuel are influenced by structural features of fatty acid such as chain length, degree of unsaturation and branching of the chain. A simple and reliable calculation method to estimate fuel property is therefore needed to avoid experimental testing which is difficult, costly and time consuming. Typically in commercial biodiesel production such testing is done for every batch of fuel produced. In this study 9 different algae species were selected that were likely to be suitable for subtropical climates. The fatty acid methyl esters (FAMEs) of all algae species were analysed and the fuel properties like cetane number (CN), cold filter plugging point (CFPP), kinematic viscosity (KV), density and higher heating value (HHV) were determined. The relation of each fatty acid with particular fuel property is analysed using multivariate and multi-criteria decision method (MCDM) software. They showed that some fatty acids have major influences on the fuel properties whereas others have minimal influence. Based on the fuel properties and amounts of lipid content rank order is drawn by PROMETHEE-GAIA which helped to select the best algae species for biodiesel production in subtropical climates. Three species had fatty acid profiles that gave the best fuel properties although only one of these (Nannochloropsis oculata) is considered the best choice because of its higher lipid content
Efficient data driven multi source fusion
Full text linkData/information fusion is an integral component of many existing and emerging applications; e.g., remote sensing, smart cars, Internet of Things (IoT), and Big Data, to name a few. While fusion aims to achieve better results than what any one individual input can provide, often the challenge is to determine the underlying mathematics for aggregation suitable for an application. In this dissertation, I focus on the following three aspects of aggregation: (i) efficient data-driven learning and optimization, (ii) extensions and new aggregation methods, and (iii) feature and decision level fusion for machine learning with applications to signal and image processing. The Choquet integral (ChI), a powerful nonlinear aggregation operator, is a parametric way (with respect to the fuzzy measure (FM)) to generate a wealth of aggregation operators. The FM has 2N variables and N(2N − 1) constraints for N inputs. As a result, learning the ChI parameters from data quickly becomes impractical for most applications. Herein, I propose a scalable learning procedure (which is linear with respect to training sample size) for the ChI that identifies and optimizes only data-supported variables. As such, the computational complexity of the learning algorithm is proportional to the complexity of the solver used. This method also includes an imputation framework to obtain scalar values for data-unsupported (aka missing) variables and a compression algorithm (lossy or losselss) of the learned variables. I also propose a genetic algorithm (GA) to optimize the ChI for non-convex, multi-modal, and/or analytical objective functions. This algorithm introduces two operators that automatically preserve the constraints; therefore there is no need to explicitly enforce the constraints as is required by traditional GA algorithms. In addition, this algorithm provides an efficient representation of the search space with the minimal set of vertices. Furthermore, I study different strategies for extending the fuzzy integral for missing data and I propose a GOAL programming framework to aggregate inputs from heterogeneous sources for the ChI learning. Last, my work in remote sensing involves visual clustering based band group selection and Lp-norm multiple kernel learning based feature level fusion in hyperspectral image processing to enhance pixel level classification
Popularity Characterization and Modelling for User-generated Videos
Full text linkUser-generated content systems such as YouTube have become highly popular. It is difficult to under- stand and predict content popularity in such systems. Characterizing and modelling content popularity can provide deeper insights into system design trade-offs and enable prediction of system behaviour in advance.
Borghol et al. collected two datasets of YouTube video weekly view counts over eight months in 2008/09, namely a “recently-uploaded” dataset and a “keyword-search” dataset, and analyzed the popular- ity characteristics of the videos in the recently-uploaded dataset including the video popularity evolution over time. Based on the observed characteristics, they developed a model that can generate synthetic video weekly view counts whose characteristics with respect to video popularity evolution match those observed in the recently-uploaded dataset.
For this thesis, new weekly view count data was collected over two months in 2011 for the videos in the recently-uploaded and keyword-search datasets of Borghol et al. This data was used to evaluate the accuracy of the Borghol et al. model when used to generate synthetic view counts for a much longer time period than the eight month period previously considered. Although the model yielded distributions of total (lifetime) video view counts that match the empirical distributions, significant differences between the model and em- pirical data were observed. These differences appear to arise because of particular popularity characteristics that change over time rather than being week-invariant as assumed in the model.
This thesis also characterizes how video popularity evolves beyond the eight month period considered by Borghol et al., and studies the characteristics of the keyword-search dataset with respect to content popu- larity, popularity evolution, and sampling biases. Finally, the thesis studies the popularity characteristics of the videos in the recently-uploaded and keyword-search datasets for which additional view count data could not be collected, owing to the removal of these videos from YouTube
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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