937 resultados para Quality analysis
Resumo:
A capillary electrophoresis with electrochemical detection(CE-ED) method was developed for the quality analysis of herbal medicine products prepared from the same herb of Herba Sarcandrae: Fufang Caoshanhu tablets, Qingrexiaoyanning capsules, and Xuekang oral liquids. Under the optimal analysis conditions, the low detection limit[1.0x10(-7) mol/L(S/N=3)] and the wide linear range(1.0x10(-7)-1.0x10(-4) mol/L) were obtained for quality standard compound of isofraxidin. The precisions of the peak current and the migration time(as RSDs) for the real sample analysis were 2.0%-2.6%, and 1.2%-1.8% for isofraxidin, respectively.
Resumo:
Purpose – This case study presents an impact assessment of Corporate Social Responsibility (CSR) programs of the TFM Company in order to understand how they contribute to the sustainable development of communities in areas in which they operate. Design/Methodology/Approach - Data for this study was collected using qualitative data methods that included semi-structured interviews and Focus Group Discussions most of them audio and video recorded. Documentary analysis and a field visit were also undertaken for the purpose of quality analysis of the CSR programs on the terrain. Data collected was analyzed using the Seven Questions to sustainability (7Qs) framework, an evaluation tool developed by the Mining, Minerals and Sustainable Development (MMSD) North America chapter. Content analysis method was on the other hand used to examine the interviews and FGDs of the study participants. Findings - Results shows that CSR programs of TFM SA do contribute to community development, as there have been notable changes in the communities’ living conditions. But whether they have contributed to sustainable development is not yet the case as programs that enhance the capacity of communities and other stakeholders to support these projects development beyond the implementation stage and the mines operation lifetime need to be considered and implemented. Originality/Value – In DRC, there is paucity of information of research studies that focus on impact assessment of CSR programs in general and specifically those of mining companies and their contribution to sustainable development of local communities. Many of the available studies cover issues of minerals and conflict or conflict minerals as mostly referred to. This study addressees this gap.
Resumo:
This research studies urban soundscapes through the comparative analysis of twelve public open spaces in the city of Córdoba (Argentina), taken as case studies. The work aims to examine selection of indicators and assessment tools intended to characterize soundscape quality. The field study was carried out through surveys and acoustic and psychoacoustic indicators, that are used together to objectively describe the sound quality of urban spaces. The study shows that, while there is a relationship of these indicators with the sound quality of the spaces, this is not linear. Their relative importance or influence depends on the interrelations occurring between the parameters studied. A model analyzing and correlating the parameters with the sound quality, based on the postulates of fuzzy logic, was applied as a tool of analysis, and it was seen to achieve a very close approximation to the subjective or perceptual response of the inhabitants. This close match between the model results and the perceptual response of the users confirms the fuzzy model as an effective tool for the study, not only of soundscapes, but also for those situations in which objective parameters must be related to the perceptual response of users.
Resumo:
Mode of access: Internet.
Resumo:
Mode of access: Internet.
Resumo:
"4 September 1981."
Resumo:
"9 July 1981."
Resumo:
Cover title.
Resumo:
Cover title.
Resumo:
Bibliography: p. 31-1-31-4.
Resumo:
Field robots often rely on laser range finders (LRFs) to detect obstacles and navigate autonomously. Despite recent progress in sensing technology and perception algorithms, adverse environmental conditions, such as the presence of smoke, remain a challenging issue for these robots. In this paper, we investigate the possibility to improve laser-based perception applications by anticipating situations when laser data are affected by smoke, using supervised learning and state-of-the-art visual image quality analysis. We propose to train a k-nearest-neighbour (kNN) classifier to recognise situations where a laser scan is likely to be affected by smoke, based on visual data quality features. This method is evaluated experimentally using a mobile robot equipped with LRFs and a visual camera. The strengths and limitations of the technique are identified and discussed, and we show that the method is beneficial if conservative decisions are the most appropriate.