Identification of Software Specifications through Quality Function Deployment

Vlad, R.C.; Benyoucef, Lyès; Vlad, S.

doi:10.1109/aqtr.2006.254603

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…The QFD is an overall concept that correlates design quality with user requirements (Sankaran et al, 2008;Slinger, 1992). It has been used in several domains including decision support and crisis management (Vlad et al, 2006;Kara-Zaitri and Al-Daihan, 1999). The technique uses matrices to collect, analyse and manage goals towards a final product.…”

Section: Quality Function Deployment (Qfd)mentioning

confidence: 99%

An AHP-QFD approach to developing DSS for crisis management

Kabeil

2010

IJMDM

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The paper defines and demonstrates the use of a framework for developing a DSS for crisis management. The framework is based on the analytical hierarchy process (AHP) and the quality function deployment (QFD) technique. The AHP is used for defining and assigning relative weights for a comprehensive list of requirements that covers all expected crises of a crisis management centre. The QFD is used for defining and assigning relative weights for design components that support the defined requirements. An example of applying the framework for developing a conceptual design of DSS in a crisis management centre is demonstrated.Reference to this paper should be made as follows: Kabeil, M.M. (2010) 'An AHP-QFD approach to developing DSS for crisis management', Int.

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Section: Quality Function Deployment (Qfd)mentioning

confidence: 99%

An AHP-QFD approach to developing DSS for crisis management

Kabeil

2010

IJMDM

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“…In [18] authors have shown the identification of software specification through Quality Function deployment. In this paper the authors have designed and implemented the GRailChem project to improve the effectiveness and the efficiency of the freight transportation between source and destination.…”

Section: Background and Related Workmentioning

confidence: 99%

More on Elicitation of Software Requirements and Prioritization Using AHP

Sadiq

Ahmed

Asim³

et al. 2010

2010 International Conference on Data Storage and Data Engineering

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The first method developed to translate customer requirements into software specification was the Quality Function deployment (QFD) and the second approach to the identification of software specification comes from the software engineering. Requirements may be defined as a demand or need. In software engineering, a requirement is a description of what a system should do. System may have dozen to thousands of requirements.Software requirements stipulate what must be accomplished, transformed, produced or provided. It is well documented that requirement engineering saves money. There are several techniques to elicit the software requirements like JAD, misuse, RAD, Web Surveys etc. In this paper we have used the Web Surveys approach to elicit the software requirements for a railway projects. The main objective of this paper is to improve the effectiveness and the efficiency of the freight transportation between source and destination using optimization algorithm.

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“…Nowadays, there are many methods of individual identification of dairy cows (Qiao et al, 2021). In traditional dairy farming, individual identification methods include ear tag, skin brand, neck chain or neck clip, and radio frequency identification (RFID) (Arcidiacono et al, 2017; Barron et al, 2009; Vlad et al, 2012; Voulodimos et al, 2010; Zin et al, 2020). However, the traditional method of identification of dairy cows is not reliable because there are many uncertain factors, and it depends on the marking method and equipment rather than dairy cow individual (Awad, 2016; Neethirajan et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Individual identification of dairy cows based on deep learning and feature fusion

Kou

et al. 2022

Animal Science Journal

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Individual identification of dairy cows is one of the most important prerequisites for an intelligent dairy farming. Herein, a new method of individual identification of dairy cows based on the fusion of deep and shallow features of dairy cow's trunk image is proposed. Our aim is to obtain low-cost, touch-free, and high-accuracy individual identification of dairy cows. First, the model of VGG-16 is improved. Second, the multiple overlapping pooling layer in the improved VGG-16 model is used as a feature extractor to extract the features of dairy cow's trunk image, and the global average pooling (GAP) layer was used to replace the traditional flatten layer to reduce the dimensions of the extracted shallow and deep features. Finally, the features after the dimensionality reduction are fused using the Concat method and input the fusion of new features into the support vector machine (SVM) classifier for classification. The proposed method was trained and tested on the dataset of 3151 cow trunk images captured by us. Experimental results showed that this method not only has better recognition accuracy of 99.48% than the VGG-16, AlexNet, and ResNet-50 models but also has fewer model parameters, faster convergence speed, and stronger generalization ability.

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Identification of Software Specifications through Quality Function Deployment

Cited by 4 publications

References 8 publications

An AHP-QFD approach to developing DSS for crisis management

An AHP-QFD approach to developing DSS for crisis management

More on Elicitation of Software Requirements and Prioritization Using AHP

Individual identification of dairy cows based on deep learning and feature fusion

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