The fierce global competition and market turbulence has been forcing the enterprises towards to the integration and intelligence for supply chain management, and the seamless information sharing and collaboration as well as operation agility are the challenges which need to be conquered, in terms of the highly distributed and heterogeneous resources located in separated warehouses. Although a number of works have been done to achieve the aforementioned targets, few of them are able to provide an overall integration and intelligence support for such system management. In this context, a novel intelligent supply chain integration and management system based on Cloud of Things is presented, in order to provide flexible and agile approaches to facilitate the resource sharing and participant collaboration in the whole supply chain life cycle. Furthermore, the enabling technologies, such as intelligent supply chain condition perception, heterogeneous network access convergence, and resource servicisation, are also studied. Finally, a case study together with the prototype system is implemented and demonstrates that the developed system can efficiently realise the integration of supply chain processes in the form of services, and also provide the effective intelligence support for physical resource management, so as to achieve an overall performance assurance for the system operation.

No abstract

Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document. When citing, please reference the published version. Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.

No abstract

A case of septicemia with meningitis due to non-O1/non-O139 Vibrio cholerae in a neonate is reported. The genotype and phenotype of the isolate were examined in relation to the major virulence genes. The isolate was shown to be non-toxin but cytotoxin-producing, distinguished from the dominant clone of non-O1/non-O139V. cholerae by multilocus sequence typing.

/npsi/ctrl?lang=en http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?lang=fr Access and use of this website and the material on it are subject to the Terms and Conditions set forth at http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/jsp/nparc_cp.jsp?lang=en NRC Publications Archive Archives des publications du CNRCThis publication could be one of several versions: author's original, accepted manuscript or the publisher's version. / La version de cette publication peut être l'une des suivantes : la version prépublication de l'auteur, la version acceptée du manuscrit ou la version de l'éditeur. For the publisher's version, please access the DOI link below./ Pour consulter la version de l'éditeur, utilisez le lien DOI ci-dessous.http://dx.doi.org/10.1016/j.eswa. 2009.04.034 International Journal of Expert Systems and Applications, 36, 10, pp. 12480-12490, 2009-12-01 A weighted ontology-based semantic similarity algorithm for web services Liu, M.; Shen, W.; Hao, Q.; Yan, J. The material in this document is covered by the provisions of the Copyright Act, by Canadian laws, policies, regulations and international agreements. Such provisions serve to identify the information source and, in specific instances, to prohibit reproduction of materials without written permission. For more information visit http://laws.justice.gc.ca/en/showtdm/cs/C-42Les renseignements dans ce document sont protégés par la Loi sur le droit d'auteur, par les lois, les politiques et les règlements du Canada et des accords internationaux. Ces dispositions permettent d'identifier la source de l'information et, dans certains cas, d'interdire la copie de documents sans permission écrite. Pour obtenir de plus amples renseignements : http://lois.justice.gc.ca/fr/showtdm/cs/C-42 1 A weighted ontology-based semantic similarity algorithm for web service

No abstract

No abstract