251 resultados para extraction efficiency


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Airport efficiency is important because it has a direct impact on customer safety and satisfaction and therefore the financial performance and sustainability of airports, airlines, and affiliated service providers. This is especially so in a world characterized by an increasing volume of both domestic and international air travel, price and other forms of competition between rival airports, airport hubs and airlines, and rapid and sometimes unexpected changes in airline routes and carriers. It also reflects expansion in the number of airports handling regional, national, and international traffic and the growth of complementary airport facilities including industrial, commercial, and retail premises. This has fostered a steadily increasing volume of research aimed at modeling and providing best-practice measures and estimates of airport efficiency using mathematical and econometric frontiers. The purpose of this chapter is to review these various methods as they apply to airports throughout the world. Apart from discussing the strengths and weaknesses of the different approaches and their key findings, the paper also examines the steps faced by researchers as they move through the modeling process in defining airport inputs and outputs and the purported efficiency drivers. Accordingly, the chapter provides guidance to those conducting empirical research on airport efficiency and serves as an aid for aviation regulators and airport operators among others interpreting airport efficiency research outcomes.

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Two transgenic callus lines of rice, stably expressing a β-glucuronidase (GUS) gene, were supertransformed with a set of constructs designed to silence the resident GUS gene. An inverted-repeat (i/r) GUS construct, designed to produce mRNA with self-complementarity, was much more effective than simple sense and antisense constructs at inducing silencing. Supertransforming rice calluses with a direct-repeat (d/r) construct, although not as effective as those with the i/r construct, was also substantially more effective in silencing the resident GUS gene than the simple sense and antisense constructs. DNA hybridisation analyses revealed that every callus line supertransformed with either simple sense or antisense constructs, and subsequently showing GUS silencing, had the silence-inducing transgenes integrated into the plant genome in inverted-repeat configurations. The silenced lines containing i/r and d/r constructs did not necessarily have inverted-repeat T-DNA insertions. There was significant methylation of the GUS sequences in most of the silenced lines but not in the unsilenced lines. However, demethylation treatment of silenced lines with 5-azacytidine did not reverse the post-transcriptional gene silencing (PTGS) of GUS. Whereas the levels of RNA specific to the resident GUS gene were uniformly low in the silenced lines, RNA specific to the inducer transgenes accumulated to a substantial level, and the majority of the i/r RNA was unpolyadenylated. Altogether, these results suggest that both sense- and antisense-mediated gene suppression share a similar molecular basis, that unpolyadenylated RNA plays an important role in PTGS, and that methylation is not essential for PTGS.

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Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.

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As of today, opinion mining has been widely used to iden- tify the strength and weakness of products (e.g., cameras) or services (e.g., services in medical clinics or hospitals) based upon people's feed- back such as user reviews. Feature extraction is a crucial step for opinion mining which has been used to collect useful information from user reviews. Most existing approaches only find individual features of a product without the structural relationships between the features which usually exists. In this paper, we propose an approach to extract features and feature relationship, represented as tree structure called a feature hi- erarchy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature hierarchy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that the proposed feature extraction approach can identify more correct features than the baseline model. Even though the datasets used in the experiment are about cameras, our work can be ap- plied to generate features about a service such as the services in hospitals or clinics.

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Guaranteeing the quality of extracted features that describe relevant knowledge to users or topics is a challenge because of the large number of extracted features. Most popular existing term-based feature selection methods suffer from noisy feature extraction, which is irrelevant to the user needs (noisy). One popular method is to extract phrases or n-grams to describe the relevant knowledge. However, extracted n-grams and phrases usually contain a lot of noise. This paper proposes a method for reducing the noise in n-grams. The method first extracts more specific features (terms) to remove noisy features. The method then uses an extended random set to accurately weight n-grams based on their distribution in the documents and their terms distribution in n-grams. The proposed approach not only reduces the number of extracted n-grams but also improves the performance. The experimental results on Reuters Corpus Volume 1 (RCV1) data collection and TREC topics show that the proposed method significantly outperforms the state-of-art methods underpinned by Okapi BM25, tf*idf and Rocchio.

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In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Moreover, several optimization techniques are also proposed to reduce the cost of estimating the confidence of imputation queries at both the tuple-level and the database-level. Experiments based on several real-world data collections demonstrate not only the effectiveness of WebPut compared to existing approaches, but also the efficiency of our proposed algorithms and optimization techniques.

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ZnO is a promising photoanode material for dye-sensitized solar cells (DSCs) due to its high bulk electron mobility and because different geometrical structures can easily be tailored. Although various strategies have been taken to improve ZnO-based DSC efficiencies, their performances are still far lower than TiO2 counterparts, mainly because low conductivity Zn2+–dye complexes form on the ZnO surfaces. Here, cone-shaped ZnO nanocrystals with exposed reactive O-terminated {101̅1} facets were synthesized and applied in DSC devices. The devices were compared with DSCs made from more commonly used rod-shaped ZnO nanocrystals where {101̅0} facets are predominantly exposed. When cone-shaped ZnO nanocrystals were used, DSCs sensitized with C218, N719, and D205 dyes universally displayed better power conversion efficiency, with the highest photoconversion efficiency of 4.36% observed with the C218 dye. First-principles calculations indicated that the enhanced DSCs performance with ZnO nanocone photoanodes could be attributed to the strength of binding between the dye molecules and reactive O-terminated {101̅1} ZnO facets and that more effective use of dye molecules occurred due to a significantly less dye aggregation on these ZnO surfaces compared to other ZnO facets.

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Changes in the molecular structure of polymer antioxidants such as hindered amine light stabilisers (HALS) is central to their efficacy in retarding polymer degradation and therefore requires careful monitoring during their in-service lifetime. The HALS, bis-(1-octyloxy-2,2,6,6-tetramethyl-4-piperidinyl) sebacate (TIN123) and bis-(1,2,2,6,6-pentamethyl-4-piperidinyl) sebacate (TIN292), were formulated in different polymer systems and then exposed to various curing and ageing treatments to simulate in-service use. Samples of these coatings were then analysed directly using liquid extraction surface analysis (LESA) coupled with a triple quadrupole mass spectrometer. Analysis of TIN123 formulated in a cross-linked polyester revealed that the polymer matrix protected TIN123 from undergoing extensive thermal degradation that would normally occur at 292 degrees C, specifically, changes at the 1- and 4-positions of the piperidine groups. The effect of thermal versus photo-oxidative degradation was also compared for TIN292 formulated in polyacrylate films by monitoring the in situ conversion of N-CH3 substituted piperidines to N-H. The analysis confirmed that UV light was required for the conversion of N-CH3 moieties to N-H - a major pathway in the antioxidant protection of polymers - whereas this conversion was not observed with thermal degradation. The use of tandem mass spectrometric techniques, including precursor-ion scanning, is shown to be highly sensitive and specific for detecting molecular-level changes in HALS compounds and, when coupled with LESA, able to monitor these changes in situ with speed and reproducibility. (C) 2013 Elsevier B. V. All rights reserved.

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Aims Pathology notification for a Cancer Registry is regarded as the most valid information for the confirmation of a diagnosis of cancer. In view of the importance of pathology data, an automatic medical text analysis system (Medtex) is being developed to perform electronic Cancer Registry data extraction and coding of important clinical information embedded within pathology reports. Methods The system automatically scans HL7 messages received from a Queensland pathology information system and analyses the reports for terms and concepts relevant to a cancer notification. A multitude of data items for cancer notification such as primary site, histological type, stage, and other synoptic data are classified by the system. The underlying extraction and classification technology is based on SNOMED CT1 2. The Queensland Cancer Registry business rules3 and International Classification of Diseases – Oncology – Version 34 have been incorporated. Results The cancer notification services show that the classification of notifiable reports can be achieved with sensitivities of 98% and specificities of 96%5, while the coding of cancer notification items such as basis of diagnosis, histological type and grade, primary site and laterality can be extracted with an overall accuracy of 80%6. In the case of lung cancer staging, the automated stages produced were accurate enough for the purposes of population level research and indicative staging prior to multi-disciplinary team meetings2 7. Medtex also allows for detailed tumour stream synoptic reporting8. Conclusions Medtex demonstrates how medical free-text processing could enable the automation of some Cancer Registry processes. Over 70% of Cancer Registry coding resources are devoted to information acquisition. The development of a clinical decision support system to unlock information from medical free-text could significantly reduce costs arising from duplicated processes and enable improved decision support, enhancing efficiency and timeliness of cancer information for Cancer Registries.

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Standard Monte Carlo (sMC) simulation models have been widely used in AEC industry research to address system uncertainties. Although the benefits of probabilistic simulation analyses over deterministic methods are well documented, the sMC simulation technique is quite sensitive to the probability distributions of the input variables. This phenomenon becomes highly pronounced when the region of interest within the joint probability distribution (a function of the input variables) is small. In such cases, the standard Monte Carlo approach is often impractical from a computational standpoint. In this paper, a comparative analysis of standard Monte Carlo simulation to Markov Chain Monte Carlo with subset simulation (MCMC/ss) is presented. The MCMC/ss technique constitutes a more complex simulation method (relative to sMC), wherein a structured sampling algorithm is employed in place of completely randomized sampling. Consequently, gains in computational efficiency can be made. The two simulation methods are compared via theoretical case studies.

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Energy efficiency is a complex topic to integrate into higher education curricula, with limited success internationally or in Australia. This paper discusses one of the successful initiatives within the Energy Efficiency Training Program, which was jointly managed and implemented by the New South Wales Office of Environment and Heritage and Department of Education and Communities. The state government initiative aimed to increase the knowledge and skills of the New South Wales workforce, help business to identify and implement energy efficiency projects, and provide professional development for the training providers. Key sectors targeted included property, construction, manufacturing and services. The Program was externally evaluated over the three years 2011 to 2013 and a range of insights were gained through these facilitated reflective opportunities, confirming and building upon literature on the topic to date. This paper presents lessons learned from the engineering part of the program (‘the project’), spanning government agencies, academic institutions, and academia. The paper begins with a contextual summary, followed by a synthesis of key learnings and implications for future training initiatives. It is intended that sharing these lessons will contribute to literature in the field, and assist other organisations in Australia and overseas planning similar initiatives.

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Two sources of uncertainty in the X ray computed tomography imaging of polymer gel dosimeters are investigated in the paper.The first cause is a change in postirradiation density, which is proportional to the computed tomography signal and is associated with a volume change. The second cause of uncertainty is reconstruction noise.A simple technique that increases the residual signal to noise ratio by almost two orders of magnitude is examined.

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RATIONALE: Polymer-based surface coatings in outdoor applications experience accelerated degradation due to exposure to solar radiation, oxygen and atmospheric pollutants. These deleterious agents cause undesirable changes to the aesthetic and mechanical properties of the polymer, reducing its lifetime. The use of antioxidants such as hindered amine light stabilisers (HALS) retards these degradative processes; however, mechanisms for HALS action and polymer degradation are poorly understood. METHODS: Detection of the HALS TINUVINW123 (bis(1-octyloxy-2,2,6,6-tetramethyl-4-piperidyl) sebacate) and the polymer degradation products directly from a polyester-based coil coating was achieved by liquid extraction surface analysis (LESA) coupled to a triple quadrupole QTRAPW 5500 mass spectrometer. The detection of TINUVINW123 and melamine was confirmed by the characteristic fragmentation pattern observed in LESA-MS/MS spectra that was identical to that reported for authentic samples. RESULTS: Analysis of an unstabilised coil coating by LESA-MS after exposure to 4 years of outdoor field testing revealed the presence of melamine (1,3,5-triazine-2,4,6-triamine) as a polymer degradation product at elevated levels. Changes to the physical appearance of the coil coating, including powder-like deposits on the coating's surface, were observed to coincide with melamine deposits and are indicative of the phenomenon known as polymer ' blooming'. CONCLUSIONS: For the first time, in situ detection of analytes from a thermoset polymer coating was accomplished without any sample preparation, providing advantages over traditional extraction-analysis approaches and some contemporary ambient MS methods. Detection of HALS and polymer degradation products such as melamine provides insight into the mechanisms by which degradation occurs and suggests LESA-MS is a powerful new tool for polymer analysis. Copyright (C) 2012 John Wiley & Sons, Ltd.

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Efforts to reduce carbon emissions in the buildings sector have been focused on encouraging green design, construction and building operation; however, the business case is not very compelling if considering the energy cost savings alone. In recent years green building has been driven by a sense that it will improve the productivity of occupants,i something with much greater economic returns than energy savings. Reducing energy demand in green commercial buildings in a way that encourages greater productivity is not yet well understood as it involves a set of complex and interdependent factors. This paper outlines an investigation into these factors and focuses on better understanding the performance of and interaction between: design elements, internal environmental quality, occupant experience, tenant/leasing agreements, and building regulation and management. In doing so the paper presents a framework for improving energy efficiency in existing commercial buildings by considering a range of interconnected and synergistic elements.

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The Australian Government’s Skills for the Carbon Challenge (SCC) initiative aims to accelerate industry and the education sectors response to climate change. As part of the SCC initiative, the Department of Industry, Innovation, Climate Change, Science, Research and Tertiary Education (DIICCSRTE) provided funding to investigate the state of energy efficiency education in engineering-related Australian Technical and Further Education (TAFE) Programs. The following document reports on the outcomes of a multi-stage consultation project that engaged with participants from over 80% of TAFE institutions across Australia with the aim of supporting and enhancing future critical skills development in this area. Specifically, this report presents the findings of a national survey, based on a series of TAFE educator focus groups, conducted in May 2013 aimed at understanding the experiences and insights of Australian TAFE educators teaching engineering-related courses. Responses were received from 224 TAFE Educators across 50 of the 61 TAFE institutions in Australia (82% response rate).