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Evaluation and Improvement of an Organizational Resource Applying Strategy Patterns
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作者 Maria Fernanda Papa Belen Rivera +1 位作者 Pablo Becker Luis Olsina 《Journal of Software Engineering and Applications》 2016年第4期128-146,共19页
For any software company that frequently performs quality assurance activities devoted to measurement, evaluation (ME) and change/improvement (MEC) projects, ME and MEC strategies can be valuable organizational assets... For any software company that frequently performs quality assurance activities devoted to measurement, evaluation (ME) and change/improvement (MEC) projects, ME and MEC strategies can be valuable organizational assets. In this paper, we analyze the improvement of a ME strategy, which can be considered an organizational resource to be applied to quality assurance activities. This resource is called the GOCAME (Goal-Oriented Context-Aware Measurement and Evaluation) strategy. AME/MEC strategy embraces the next three integrated capabilities: 1) the ME/MEC domain conceptual base and framework;2) the process perspective specifications;and, 3) the method specifications. The improvement of GOCAME was performed instantiating two strategy patterns. A strategy pattern is a reusable solution to recurrent problems in ME/MEC projects. For an improvement goal, the selected MEC strategy pattern allows instantiating in a project a set of tailored activities and methods for measurement, evaluation, analysis and change. Particularly, we instantiate the GoME_1QV (Goal-oriented Measurement and Evaluation for One Quality View) strategy pattern to understand the GOCAME current quality state and compare it with the so-called GQM+ Strategies. First, this evaluation and analysis allows us to know the GOCAME strengths and weaknesses with regard to the quality of the three capabilities. Second, we instantiate the GoMEC_1QV (Goal-oriented Measurement, Evaluation and Change for One Quality View) strategy pattern to improve the GOCAME current state, producing as result a new version of the GOCAME strategy. 展开更多
关键词 Strategy Pattern quality view EVALUATION Change IMPROVEMENT
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A NEW OBJECTIVE STEREOSCOPIC IMAGE ASSESSMENT MODEL BASED ON STEREOSCOPIC PERCEPTION
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作者 Zhu Jiangying Jiang Gangyi +4 位作者 Yu Mei Wang Xiaodong Chen Fen Shao Feng Peng Zongju 《Journal of Electronics(China)》 2013年第5期469-475,共7页
In order to establish a stereoscopic image quality assessment method which is consistent with human visual perception,we propose an objective stereoscopic image quality assessment method.It takes into account the stro... In order to establish a stereoscopic image quality assessment method which is consistent with human visual perception,we propose an objective stereoscopic image quality assessment method.It takes into account the strong correlation and high degree of structural between pixels of image.This method contains two models.One is the quality synthetic assessment of left-right view images,which is based on human visual characteristics,we use the Singular Value Decomposition(SVD)that can represent the degree of the distortion,and combine the qualities of left and right images by the characteristics of binocular superposition.The other model is stereoscopic perception quality assessment,due to strong stability of image’s singular value characteristics,we calculate the distance of the singular values and structural characteristic similarity of the absolute difference maps,and utilize the statistical value of the global error to evaluate stereoscopic perception.Finally,we combine two models to describe the stereoscopic image quality.Experimental results show that the correlation coefficients of the proposed assessment method and the human subjective perception are above 0.93,and the mean square errors are all less than 6.2,under JPEG,JP2K compression,Gaussian blurring,Gaussian white noise,H.264 coding distortion,and hybrid cross distortion.It indicates that the proposed stereoscopic objective method is consistent with human visual properties and also of availability. 展开更多
关键词 Stereoscopic image quality assessment quality synthetic assessment of left and right view images Stereoscopic perception Singular Value Decomposition(SVD
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