18,108 research outputs found
An overview of decision table literature 1982-1995.
This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.
User producer interaction in context: a classification
Science, Technology and Innovation Studies show that intensified user producer interaction (UPI) increases chances for successful innovations, especially in the case of emerging technology. It is not always clear, however, what type of interaction is necessary in a particular context. This paper proposes a conceptualization of contexts in terms of three dimensions â the phase of technology development, the flexibility of the technology, and the heterogeneity of user populations â resulting in a classification scheme with eight different contextual situations. The paper identifies and classifies types of interaction, like demand articulation, interactive learning, learning by using and domestication. It appears that each contextual situation demands a different set of UPI types. To illustrate the potential value of the classification scheme, four examples of innovations with varying technological and user characteristics are explored: the refrigerator, clinical anaesthesia, video cassette recording, and the bicycle. For each example the relevant UPI types are discussed and it is shown how these types highlight certain activities and interactions during key events of innovation processes. Finally, some directions for further research are suggested alongside a number of comments on the utility of the classification
Supply Chain Practice, Supply Chain Performance Indicators and Competitive Advantage of Australian Beef Enterprises: A Conceptual Framework
This research focuses on an Australian agribusiness supply chain, the Australian Beef Supply Chain. The definition of the Australian Beef Supply Chain is the chain or sequence of all activities from the breeding property to the domestic or overseas consumers. The beef sector in Australia is undergoing rapid change because of globalisation, a highly competitive beef market (local and export), quicker production cycle and delivery times and consequently reduced inventories, a general speed-up of the rate of change in the business environment, the trend toward more outsourcing of activities, and the rapid development of IT. In this business environment, advanced supply chain systems have the potential to provide significant contributions to Australian beef industry performance. A conceptual framework of the research project has been proposed. There are three elements of conceptual framework. Firstly, supply chain practice of Australian beef industry consists of five sub-elements such as strategic supplier partnerships, customer relationships, information sharing, information quality and a lean system. Moreover, there is an antecedent of cooperative behaviour such as trust and commitment influencing supply chain practice and supply chain performance indicators. Secondly, supply chain performance indicators include four sub-elements such as flexibility, efficiency, food quality and responsiveness. Finally, the competitive advantage framework of the Australian beef enterprises consists of price, quality, export sales growth and time to market. As a further step of the research after developing the conceptual framework, the research project focuses the analysis on how the antecedents of the sub-elements of supply chain practice affect supply chain performance in Australian beef enterprises, how trust and commitment in trading partners affect supply chain performance, how attributes such as flexibility, efficiency, food quality and responsiveness influence the sub-elements of competitive advantage. The research project leads on to further work on how Australian beef enterprises measure their supply chain performance and what the major difficulties are arising when implementing supply chain management in the Australian beef industry and what kind of changes can be made to beef supply chains to enhance their performance.Agribusiness,
Do you own a Volkswagen? Values as non-functional requirements
Of late, there has been renewed interest in determining the role and relative importance of (moral) values in the design of software and its acceptance. Events such as the Snowden revelations and the more recent case of the Volkswagen "defeat deviceâ software have further emphasised the importance of values and ethics in general. This paper posits a view that values accompanied by an appropriate framework derived from non-functional requirements can be used by designers and developers as means for discourse of ethical concerns of the design of software. The position is based on the Volkswagen dieselgate case study and a qualitative analysis of developers views from Reddit discussion forums. The paper proposes an extension of an existing classification of requirements to include value concerns
An Automated Framework for the Extraction of Semantic Legal Metadata from Legal Texts
Semantic legal metadata provides information that helps with understanding
and interpreting legal provisions. Such metadata is therefore important for the
systematic analysis of legal requirements. However, manually enhancing a large
legal corpus with semantic metadata is prohibitively expensive. Our work is
motivated by two observations: (1) the existing requirements engineering (RE)
literature does not provide a harmonized view on the semantic metadata types
that are useful for legal requirements analysis; (2) automated support for the
extraction of semantic legal metadata is scarce, and it does not exploit the
full potential of artificial intelligence technologies, notably natural
language processing (NLP) and machine learning (ML). Our objective is to take
steps toward overcoming these limitations. To do so, we review and reconcile
the semantic legal metadata types proposed in the RE literature. Subsequently,
we devise an automated extraction approach for the identified metadata types
using NLP and ML. We evaluate our approach through two case studies over the
Luxembourgish legislation. Our results indicate a high accuracy in the
generation of metadata annotations. In particular, in the two case studies, we
were able to obtain precision scores of 97.2% and 82.4% and recall scores of
94.9% and 92.4%
A taxonomy of software engineering challenges for machine learning systems: An empirical investigation
Artificial intelligence enabled systems have been an inevitable part of everyday life. However, efficient software engineering principles and processes need to be considered and extended when developing AI- enabled systems. The objective of this study is to identify and classify software engineering challenges that are faced by different companies when developing software-intensive systems that incorporate machine learning components. Using case study approach, we explored the development of machine learning systems from six different companies across various domains and identified main software engineering challenges. The challenges are mapped into a proposed taxonomy that depicts the evolution of use of ML components in software-intensive system in industrial settings. Our study provides insights to software engineering community and research to guide discussions and future research into applied machine learning
- âŚ