Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Scaling Up Sustainable Finance and Investment in the Global South

Creating economically and politically legitimate solutions to tackle climate change is one of the most pressing and challenging issues of our time. For emerging and developing economies, the task is made more difficult due to a lack of financing, increasing debt accumulation and the need to address domestic socio-economic issues. This eBook provides a comprehensive overview of the financing gap that emerging and developing countries face to meet the Sustainable Development Goals and Paris climate goals. It provides detailed country- and region-level analysis of the challenges and opportunities of scaling up sustainable finance and investment and discusses the range of instruments that could be used to reach these climate and development objectives

Genomics-Assisted Crop Improvement, Vol 2: Genomics Applications in Crops

Genomics research has great potential to revolutionize the discipline of plant breeding. This two-volume set provides a critical assessment of genomics tools and approaches for crop breeding. Volume 1, entitled "Genomics Approaches and Platforms", illustrates state-of-the-art genomics approaches and platforms presently available for crop improvement. Volume 2, entitled "Genomics Applications in Crops", compiles crop-specific studies that summarize both the achievements and limitations of genomics research for crop improvement. We hope that these two volumes, while providing new ideas and opportunities to those working in crop breeding, will help graduate students and teachers to develop a better understanding of the applications of crop genomics to plant research and breeding

Development of a Robust Data Mining Method Using CBFS and RSM

Abstract. Data mining (DM) has emerged as one of the key features of many applications on information system. While Data Analysis (DA) represents a significant advance in the type of analytical tools currently available, there are limitations to its capability. In order to address one of the limitations on the DA capabilities of identifying a causal relationship, we propose an integrated approach, called robust data mining (RDM), which can reduce dimensionality of the large data set, may provide detailed statistical relationships among the factors and robust factor settings. The primary objective of this paper is twofold. First, we show how DM techniques can be effectively applied into a wastewater treatment process design by applying a correlation-based feature selection (CBFS) method. This method may be far more effective than any other methods when a large number of input factors are considered on a process design procedure. Second, we then show how DM results can be integrated into a robust design (RD) paradigm based on the selected significant factors. Our numerical example clearly shows that the proposed RDM method can efficiently find significant factors and the optimal settings by reducing dimensionality. 1