922 resultados para multi-column process
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Web document cluster analysis plays an important role in information retrieval by organizing large amounts of documents into a small number of meaningful clusters. Traditional web document clustering is based on the Vector Space Model (VSM), which takes into account only two-level (document and term) knowledge granularity but ignores the bridging paragraph granularity. However, this two-level granularity may lead to unsatisfactory clustering results with “false correlation”. In order to deal with the problem, a Hierarchical Representation Model with Multi-granularity (HRMM), which consists of five-layer representation of data and a twophase clustering process is proposed based on granular computing and article structure theory. To deal with the zero-valued similarity problemresulted from the sparse term-paragraphmatrix, an ontology based strategy and a tolerance-rough-set based strategy are introduced into HRMM. By using granular computing, structural knowledge hidden in documents can be more efficiently and effectively captured in HRMM and thus web document clusters with higher quality can be generated. Extensive experiments show that HRMM, HRMM with tolerancerough-set strategy, and HRMM with ontology all outperform VSM and a representative non VSM-based algorithm, WFP, significantly in terms of the F-Score.
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Renewable alternatives such as biofuels and optimisation of the engine operating parameters can enhance engine performance and reduce emissions. The temperature of the engine coolant is known to have significant influence on engine performance and emissions. Whereas much existing literature describes the effects of coolant temperature in engines using fossil derived fuels, very few studies have investigated these effects when biofuel is used as an alternative fuel. Jatropha oil is a non-edible biofuel which can substitute fossil diesel for compression ignition (CI) engine use. However, due to the high viscosity of Jatropha oil, technique such as transesterification, preheating the oil, mixing with other fuel is recommended for improved combustion and reduced emissions. In this study, Jatropha oil was blended separately with ethanol and butanol, at ratios of 80:20 and 70:30. The fuel properties of all four blends were measured and compared with diesel and jatropha oil. It was found that the 80% jatropha oil + 20% butanol blend was the most suitable alternative, as its properties were closest to that of diesel. A 2 cylinder Yanmar engine was used; the cooling water temperature was varied between 50°C and 95°C. In general, it was found that when the temperature of the cooling water was increased, the combustion process enhanced for both diesel and Jatropha-Butanol blend. The CO2 emissions for both diesel and biofuel blend were observed to increase with temperature. As a result CO, O2 and lambda values were observed to decrease when cooling water temperature increased. When the engine was operated using diesel, NOX emissions correlated in an opposite manner to smoke opacity; however, when the biofuel blend was used, NOX emissions and smoke opacity correlated in an identical manner. The brake thermal efficiencies were found to increase slightly as the temperature was increased. In contrast, for all fuels, the volumetric efficiency was observed to decrease as the coolant temperature was increased. Brake specific fuel consumption was observed to decrease as the temperature was increased and was higher on average when the biofuel was used, in comparison to diesel. The study concludes that the effects of engine coolant temperature on engine performance and emission characteristics differ between biofuel blend and fossil diesel operation. The coolant temperature needs to be optimised depending on the type of biofuel for optimum engine performance and reduced emissions.
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Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.
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A critical review of the literature concerning organic derivatives of hydrazine, the ammonia-chlorine reaction and the electrolytic formation of hydrazine has been carried out. Apparatus was constructed to study the electrolysis of liquid ammonia, the formation of chloramine and the fixation of chloramine with a ketone to form an isohydrazone. In the latter case the reaction was carried out in a 3" diameter stirred tank and also in a 1" diameter, 2' high column reactor where the liquid phase was continuously recirculated. Two methods of analysis of azines and isohydrazones in a ketone solution have been developed. One is a colorimetric technique using p-dimethylaminobenzaldehyde and the other involves the hydrolysis of the organic derivative to hydrazine sulphate. Hydrazine was detected in low concentration in some of the electrolytic experiments carried out but it was concluded that this method did not show sufficient promise to warrant further investigation. The gas phase formation of chloramine and acetone isohydrazone has also been studied but in this system difficulties were encountered with the chlorine jet blocking with ammonium chloride. The formation of isohydrazones in a stirred tank reactor has been investigated in some detail and the effect of several parameters was determined. The yield was found to be extremely sensitive to chlorine concentration and in order to obtain yields of more than 90 per cent, the molar concentration of chlorine in the gas phase had to be of the order of 5 per cent. An optimum temperature in the region of 0°C was also detected. These results disagree with those quoted in previous studies but extensive experimental work has confirmed the information presented in this thesis. It has also been shown that at high yields the chloramine formation reaction took place in the gas phase.
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Digestate from the anaerobic digestion conversion process is widely used as a farm land fertiliser. This study proposes an alternative use as a source of energy. Dried digestate was pyrolysed and the resulting oil was blended with waste cooking oil and butanol (10, 20 and 30 vol.%). The physical and chemical properties of the pyrolysis oil blends were measured and compared with pure fossil diesel and waste cooking oil. The blends were tested in a multi-cylinder indirect injection compression ignition engine.Engine combustion, exhaust gas emissions and performance parameters were measured and compared with pure fossil diesel operation. The ASTM copper corrosion values for 20% and 30% pyrolysis blends were 2c, compared to 1b for fossil diesel. The kinematic viscosities of the blends at 40 C were 5–7 times higher than that of fossil diesel. Digested pyrolysis oil blends produced lower in-cylinder peak pressures than fossil diesel and waste cooking oil operation. The maximum heat release rates of the blends were approximately 8% higher than with fossil diesel. The ignition delay periods of the blends were higher; pyrolysis oil blends started to combust late and once combustion started burnt quicker than fossil diesel. The total burning duration of the 20% and 30% blends were decreased by 12% and 3% compared to fossil diesel. At full engine load, the brake thermal efficiencies of the blends were decreased by about 3–7% when compared to fossil diesel. The pyrolysis blends gave lower smoke levels; at full engine load, smoke level of the 20% blend was 44% lower than fossil diesel. In comparison to fossil diesel and at full load, the brake specific fuel consumption (wt.) of the 30% and 20% blends were approximately 32% and 15% higher. At full engine load, the CO emission of the 20% and 30% blends were decreased by 39% and 66% with respect to the fossil diesel. Blends CO2 emissions were similar to that of fossil diesel; at full engine load, 30% blend produced approximately 5% higher CO2 emission than fossil diesel. The study concludes that on the basis of short term engine experiment up to 30% blend of pyrolysis oil from digestate of arable crops can be used in a compression ignition engine.
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Purpose – The purpose of this research is to develop a holistic approach to maximize the customer service level while minimizing the logistics cost by using an integrated multiple criteria decision making (MCDM) method for the contemporary transshipment problem. Unlike the prevalent optimization techniques, this paper proposes an integrated approach which considers both quantitative and qualitative factors in order to maximize the benefits of service deliverers and customers under uncertain environments. Design/methodology/approach – This paper proposes a fuzzy-based integer linear programming model, based on the existing literature and validated with an example case. The model integrates the developed fuzzy modification of the analytic hierarchy process (FAHP), and solves the multi-criteria transshipment problem. Findings – This paper provides several novel insights about how to transform a company from a cost-based model to a service-dominated model by using an integrated MCDM method. It suggests that the contemporary customer-driven supply chain remains and increases its competitiveness from two aspects: optimizing the cost and providing the best service simultaneously. Research limitations/implications – This research used one illustrative industry case to exemplify the developed method. Considering the generalization of the research findings and the complexity of the transshipment service network, more cases across multiple industries are necessary to further enhance the validity of the research output. Practical implications – The paper includes implications for the evaluation and selection of transshipment service suppliers, the construction of optimal transshipment network as well as managing the network. Originality/value – The major advantages of this generic approach are that both quantitative and qualitative factors under fuzzy environment are considered simultaneously and also the viewpoints of service deliverers and customers are focused. Therefore, it is believed that it is useful and applicable for the transshipment service network design.
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Servitization is the process by which manufacturers add services to their product offerings and even replace products with services. The capabilities necessary to develop and deliver advanced services as part of servitization are often discussed in the literature from the manufacturer’s perspective, e.g., having a service-focused culture or the ability to sell solutions. Recent research has acknowledged the important role of customers and, to a lesser extent, other actors (e.g., intermediaries) in bringing about successful servitization, particularly for use-oriented and results-oriented advanced services. The objective of this study is to identify the capabilities required to successful develop advanced services as part of servitization by considering the perspective of manufacturers, intermediaries and customers. This study involved interviews with 33 managers in 28 large UK-based companies from these three groups, about servitization capabilities. The findings suggest that there are eight broad capabilities that are important for advanced services; 1) personnel with expertise and deep technical product knowledge, 2) methodologies for improving operational processes, helping to manage risk and reduce costs, 3) the evolution from being a product- focused manufacturer to embracing a services culture, 4) developing trusting relationships with other actors in the network to support the delivery of advanced services, 5) new innovation activities focused on financing contracts (e.g., ‘gain share’) and technology implementation (e.g., Web-based applications), 6) customer intimacy through understanding their business challenges in order to develop suitable solutions, 7) extensive infrastructure (e.g., personnel, service centres) to deliver a local service, and 8) the ability to tailor service offerings to each customer’s requirements and deliver these responsively to changing needs. The capabilities required to develop and deliver advanced services align to a need to enhance the operational performance of supplied products throughout their lifecycles and as such require greater investment than the capabilities for base and intermediate services.
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Biodiesel production is a very promising area due to the relevance that it is an environmental-friendly diesel fuel alternative to fossil fuel derived diesel fuels. Nowadays, most industrial applications of biodiesel production are performed by the transesterification of renewable biological sources based on homogeneous acid catalysts, which requires downstream neutralization and separation leading to a series of technical and environmental problems. However, heterogeneous catalyst can solve these issues, and be used as a better alternative for biodiesel production. Thus, a heuristic diffusion-reaction kinetic model has been established to simulate the transesterification of alkyl ester with methanol over a series of heterogeneous Cs-doped heteropolyacid catalysts. The novelty of this framework lies in detailed modeling of surface reacting kinetic phenomena and integrating that with particle-level transport phenomena all the way through to process design and optimisation, which has been done for biodiesel production process for the first time. This multi-disciplinary research combining chemistry, chemical engineering and process integration offers better insights into catalyst design and process intensification for the industrial application of Cs-doped heteropolyacid catalysts for biodiesel production. A case study of the transesterification of tributyrin with methanol has been demonstrated to establish the effectiveness of this methodology.
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Biodiesel production is a very promising area due to the relevance that it is an environmental-friendly diesel fuel alternative to fossil fuel derived diesel fuels. Nowadays, most industrial applications of biodiesel production are performed by the transesterification of renewable biological sources based on homogeneous acid catalysts, which requires downstream neutralization and separation leading to a series of technical and environmental problems. However, heterogeneous catalyst can solve these issues, and be used as a better alternative for biodiesel production. Thus, a heuristic diffusion-reaction kinetic model has been established to simulate the transesterification of alkyl ester with methanol over a series of heterogeneous Cs-doped heteropolyacid catalysts. The novelty of this framework lies in detailed modeling of surface reacting kinetic phenomena and integrating that with particle-level transport phenomena all the way through to process design and optimisation, which has been done for biodiesel production process for the first time. This multi-disciplinary research combining chemistry, chemical engineering and process integration offers better insights into catalyst design and process intensification for the industrial application of Cs-doped heteropolyacid catalysts for biodiesel production. A case study of the transesterification of tributyrin with methanol has been demonstrated to establish the effectiveness of this methodology.
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Listening is typically the first language skill to develop in first language (L1) users and has been recognized as a basic and fundamental tool for communication. Despite the importance of listening, aural abilities are often taken for granted, and many people overlook their dependency on listening and the complexities that combine to enable this multi-faceted skill. When second language (L2) students are learning their new language, listening is crucial, as it provides access to oral input and facilitates social interaction. Yet L2 students find listening challenging, and L2 teachers often lack sufficient pedagogy to help learners develop listening abilities that they can use in and beyond the classroom. In an effort to provide a pedagogic alternative to more traditional and limited L2 listening instruction, this thesis investigated the viability of listening strategy instruction (LSI) over three semesters at a private university in Japan through a qualitative action research (AR) intervention. An LSI program was planned and implemented with six classes over the course of three AR phases. Two teachers used the LSI with 121 learners throughout the project. Following each AR phase, student and teacher perceptions of the methodology were investigated via questionnaires and interviews, which were primary data collection methods. Secondary research methods (class observations, pre/post-semester test scores, and a research journal) supplemented the primary methods. Data were analyzed and triangulated for emerging themes related to participants’ perceptions of LSI and the viability thereof. These data showed consistent positive perceptions of LSI on the parts of both learners and teachers, although some aspects of LSI required additional refinement. This project provided insights on LSI specific to the university context in Japan and also produced principles for LSI program planning and implementation that can inform the broader L2 education community.
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Error and uncertainty in remotely sensed data come from several sources, and can be increased or mitigated by the processing to which that data is subjected (e.g. resampling, atmospheric correction). Historically the effects of such uncertainty have only been considered overall and evaluated in a confusion matrix which becomes high-level meta-data, and so is commonly ignored. However, some of the sources of uncertainty can be explicity identified and modelled, and their effects (which often vary across space and time) visualized. Others can be considered overall, but their spatial effects can still be visualized. This process of visualization is of particular value for users who need to assess the importance of data uncertainty for their own practical applications. This paper describes a Java-based toolkit, which uses interactive and linked views to enable visualization of data uncertainty by a variety of means. This allows users to consider error and uncertainty as integral elements of image data, to be viewed and explored, rather than as labels or indices attached to the data. © 2002 Elsevier Science Ltd. All rights reserved.
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The concept of data independence designates the techniques that allow data to be changed without affecting the applications that process it. The different structures of the information bases require corresponded tools for supporting data independence. A kind of information bases (the Multi-dimensional Numbered Information Spaces) are pointed in the paper. The data independence in such information bases is discussed.
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Integrated supplier selection and order allocation is an important decision for both designing and operating supply chains. This decision is often influenced by the concerned stakeholders, suppliers, plant operators and customers in different tiers. As firms continue to seek competitive advantage through supply chain design and operations they aim to create optimized supply chains. This calls for on one hand consideration of multiple conflicting criteria and on the other hand consideration of uncertainties of demand and supply. Although there are studies on supplier selection using advanced mathematical models to cover a stochastic approach, multiple criteria decision making techniques and multiple stakeholder requirements separately, according to authors' knowledge there is no work that integrates these three aspects in a common framework. This paper proposes an integrated method for dealing with such problems using a combined Analytic Hierarchy Process-Quality Function Deployment (AHP-QFD) and chance constrained optimization algorithm approach that selects appropriate suppliers and allocates orders optimally between them. The effectiveness of the proposed decision support system has been demonstrated through application and validation in the bioenergy industry.
On Multi-Dimensional Random Walk Models Approximating Symmetric Space-Fractional Diffusion Processes
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Mathematics Subject Classification: 26A33, 47B06, 47G30, 60G50, 60G52, 60G60.
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Марусия Н. Славчова-Божкова - В настоящата работа се обобщава една гранична теорема за докритичен многомерен разклоняващ се процес, зависещ от възрастта на частиците с два типа имиграция. Целта е да се обобщи аналогичен резултат в едномерния случай като се прилагат “coupling” метода, теория на възстановяването и регенериращи процеси.