Limits of stakeholder participation in sustainable development : "where facts are few, experts are many"

Extract from: The Mediterranean coastal areas from watershed to the sea : interactions and changes / by L.F. Cassar ... [et al.]. Proceedings of the MEDCORE International conference, Florence, 10th-14th November 2005The notion of including stakeholders, those affected (positively or negatively) by a sustainable development programme in both its design and implementation, has become a central concern for those implementing such programmes. Such an approach is often referred to as ‘stakeholder participation’, as ‘participatory development’ or more simply still as ‘participation’. How best to achieve this has been the topic of a substantial literature, with a host of different methodologies presented and promoted. Each has its own advantages and disadvantages, but there has been surprisingly little discussion in the sustainable development literature as to the limits and dangers of participation irrespective of the approach employed to ‘best’ facilitate it. Inter-linked with the limits of participation is the role of specialists and expert opinion in sustainable development. This paper discusses the results of participatory exercises conducted in Gozo (Malta) between 2003 and 2005. On the positive side, participation yielded many useful and interesting insights and invoked a sense of ‘involvement’ in sustainable development, but there were problems and these are discussed in this paper. For example, the outcome of the exercise crucially depends upon representation, and a simplified vision of ‘community’ often employed in participation to make it practicable can load the process in favour of certain stakeholder groups at the expense of others.peer-reviewe

Application of artificial neural network in market segmentation: A review on recent trends

Despite the significance of Artificial Neural Network (ANN) algorithm to market segmentation, there is a need of a comprehensive literature review and a classification system for it towards identification of future trend of market segmentation research. The present work is the first identifiable academic literature review of the application of neural network based techniques to segmentation. Our study has provided an academic database of literature between the periods of 2000-2010 and proposed a classification scheme for the articles. One thousands (1000) articles have been identified, and around 100 relevant selected articles have been subsequently reviewed and classified based on the major focus of each paper. Findings of this study indicated that the research area of ANN based applications are receiving most research attention and self organizing map based applications are second in position to be used in segmentation. The commonly used models for market segmentation are data mining, intelligent system etc. Our analysis furnishes a roadmap to guide future research and aid knowledge accretion and establishment pertaining to the application of ANN based techniques in market segmentation. Thus the present work will significantly contribute to both the industry and academic research in business and marketing as a sustainable valuable knowledge source of market segmentation with the future trend of ANN application in segmentation.Comment: 24 pages, 7 figures,3 Table

Identifying Heavy-Flavor Jets Using Vectors of Locally Aggregated Descriptors

Jets of collimated particles serve a multitude of purposes in high energy collisions. Recently, studies of jet interaction with the quark-gluon plasma (QGP) created in high energy heavy ion collisions are of growing interest, particularly towards understanding partonic energy loss in the QGP medium and its related modifications of the jet shower and fragmentation. Since the QGP is a colored medium, the extent of jet quenching and consequently, the transport properties of the medium are expected to be sensitive to fundamental properties of the jets such as the flavor of the parton that initiates the jet. Identifying the jet flavor enables an extraction of the mass dependence in jet-QGP interactions. We present a novel approach to tagging heavy-flavor jets at collider experiments utilizing the information contained within jet constituents via the \texttt{JetVLAD} model architecture. We show the performance of this model in proton-proton collisions at center of mass energy $\sqrt{s} = 200$ GeV as characterized by common metrics and showcase its ability to extract high purity heavy-flavor jet sample at various jet momenta and realistic production cross-sections including a brief discussion on the impact of out-of-time pile-up. Such studies open new opportunities for future high purity heavy-flavor measurements at jet energies accessible at current and future collider experiments.Comment: 18 pages, 6 figures and 3 tables. Accepted by JINS

Collaborative knowledge management - A construction case study

Due to the new threats and challenges faced by the construction industry today, construction companies must seek new solutions in order to remain ahead of the competition. Knowledge has been identified to be a significant organisational resource, which if used effectively can provide competitive advantage. A lot of emphasis is being put on how to identify, capture and share knowledge in today's organisations. It has been argued over the years that due to the fragmented nature of the construction industry and ad-hoc nature of the construction projects, capture and reuse of valuable knowledge gathered during a construction project pose a challenge. As a result critical mistakes are repeated on projects and construction professionals have to kee