Web services enhanced interoperable construction products catalogue

This paper presents a new approach to achieving interoperability between Web-based construction products catalogues. It first introduces the current development of electronic catalogues of construction products. The common system architecture of Web-based electronic products catalogues is discussed, which is followed by a discussion on construction products information standardization and the latest distributed-systems technologies for the communication and exchange of construction products information. The latter part of this paper presents a model of interoperable Web-based construction products catalogue and an implementation of Web services in E-commerce systems to enable the sharing of construction products information.

Intelligent wireless web services: context-aware computing in construction-logistics supply chain

The construction industry has incurred a considerable amount of waste as a result of poor logistics supply chain network management. Therefore, managing logistics in the construction industry is critical. An effective logistic system ensures delivery of the right products and services to the right players at the right time while minimising costs and rewarding all sectors based on value added to the supply chain. This paper reports on an on-going research study on the concept of context-aware services delivery in the construction project supply chain logistics. As part of the emerging wireless technologies, an Intelligent Wireless Web (IWW) using context-aware computing capability represents the next generation ICT application to construction-logistics management. This intelligent system has the potential of serving and improving the construction logistics through access to context-specific data, information and services. Existing mobile communication deployments in the construction industry rely on static modes of information delivery and do not take into account the worker’s changing context and dynamic project conditions. The major problems in these applications are lack of context-specificity in the distribution of information, services and other project resources, and lack of cohesion with the existing desktop based ICT infrastructure. The research works focus on identifying the context dimension such as user context, environmental context and project context, selection of technologies to capture context-parameters such wireless sensors and RFID, selection of supporting technologies such as wireless communication, Semantic Web, Web Services, agents, etc. The process of integration of Context-Aware Computing and Web-Services to facilitate the creation of intelligent collaboration environment for managing construction logistics will take into account all the necessary critical parameters such as storage, transportation, distribution, assembly, etc. within off and on-site project.

Research review: reading comprehension in developmental disorders of language and communication

Background: Deficits in reading airment (SLI), Down syndrome (DS) and autism spectrum disorders (ASD). Methods: In this review (based on a search of the ISI Web of Knowledge database to 2011), the Simple View of Reading is used as a framework for considering reading comprehension in these groups. Conclusions: There is substantial evidence for reading comprehension impairments in SLI and growing evidence that weaknesses in this domain are common in DS and ASD. Further, in these groups reading comprehension is typically more impaired than word recognition. However, there is also evidence that some children and adolescents with DS, ASD and a history of SLI develop reading comprehension and word recognition skills at or above the age appropriate level. This review of the literature indicates that factors including word recognition, oral language, nonverbal ability and working memory may explain reading comprehension difficulties in SLI, DS and ASD. In addition, it highlights methodological issues, implications of poor reading comprehension and fruitful areas for future research.

Documents as 'critical incidents' in organisation to consumer communication

A diary study tracked the paper documents received by nine UK informants over one month. Informants gave simple ratings of individual documents’ attractiveness and the ease of understanding them; more detailed reactions to the documents were gathered through informant diaries and follow-up interviews. The detailed reactions extended beyond the feedback gathered through the rating task. Informants showed sensitivity to the content, language, design and circumstances of receipt of documents, with indications that they developed opinions of originating organizations based on their experience of using their documents. Documents that failed to provide all the information needed, that failed to make their intentions clear (or obscured their intentions) or that were perceived as miss-targeted received negative comment. Repeat experiences of receiving either well- or poorly-conceived documents strengthened informant reactions to individual originating organizations. The paper concludes with recommendations for steps document originators, writers and designers need to take to prepare documents that enhance organization to consumer communication. We recommend that organizations evaluate and act on consumers’ reactions to their documents, beyond user testing in document development or scorecard ratings in use.

Non-uniform data distribution for communication-efficient parallel clustering

Global communicationrequirements andloadimbalanceof someparalleldataminingalgorithms arethe major obstacles to exploitthe computational power of large-scale systems. This work investigates how non-uniform data distributions can be exploited to remove the global communication requirement and to reduce the communication costin parallel data mining algorithms and, in particular, in the k-means algorithm for cluster analysis. In the straightforward parallel formulation of the k-means algorithm, data and computation loads are uniformly distributed over the processing nodes. This approach has excellent load balancing characteristics that may suggest it could scale up to large and extreme-scale parallel computing systems. However, at each iteration step the algorithm requires a global reduction operationwhichhinders thescalabilityoftheapproach.Thisworkstudiesadifferentparallelformulation of the algorithm where the requirement of global communication is removed, while maintaining the same deterministic nature ofthe centralised algorithm. The proposed approach exploits a non-uniform data distribution which can be either found in real-world distributed applications or can be induced by means ofmulti-dimensional binary searchtrees. The approachcanalso be extended to accommodate an approximation error which allows a further reduction ofthe communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing element

Dynamic group communication for large-scale parallel data mining

Exascale systems are the next frontier in high-performance computing and are expected to deliver a performance of the order of 10^18 operations per second using massive multicore processors. Very large- and extreme-scale parallel systems pose critical algorithmic challenges, especially related to concurrency, locality and the need to avoid global communication patterns. This work investigates a novel protocol for dynamic group communication that can be used to remove the global communication requirement and to reduce the communication cost in parallel formulations of iterative data mining algorithms. The protocol is used to provide a communication-efficient parallel formulation of the k-means algorithm for cluster analysis. The approach is based on a collective communication operation for dynamic groups of processes and exploits non-uniform data distributions. Non-uniform data distributions can be either found in real-world distributed applications or induced by means of multidimensional binary search trees. The analysis of the proposed dynamic group communication protocol has shown that it does not introduce significant communication overhead. The parallel clustering algorithm has also been extended to accommodate an approximation error, which allows a further reduction of the communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing elements.

Efficient group communication for large-scale parallel clustering

Global communication requirements and load imbalance of some parallel data mining algorithms are the major obstacles to exploit the computational power of large-scale systems. This work investigates how non-uniform data distributions can be exploited to remove the global communication requirement and to reduce the communication cost in iterative parallel data mining algorithms. In particular, the analysis focuses on one of the most influential and popular data mining methods, the k-means algorithm for cluster analysis. The straightforward parallel formulation of the k-means algorithm requires a global reduction operation at each iteration step, which hinders its scalability. This work studies a different parallel formulation of the algorithm where the requirement of global communication can be relaxed while still providing the exact solution of the centralised k-means algorithm. The proposed approach exploits a non-uniform data distribution which can be either found in real world distributed applications or can be induced by means of multi-dimensional binary search trees. The approach can also be extended to accommodate an approximation error which allows a further reduction of the communication costs.

Prospettive economiche di mercato della produzione ortofrutticola biologica. Indagine sul gradimento dei consumatori

The aims of the present study are to explore the willingness to pay a tax for the abolition of the use of pesticides as well as a premium price per kilo for organically grown fruit. An investigation was carried out in the region of Emilia-Romagna both by means of face to face questionnaires administered randomly in large supermarkets and via the World Wide Web. The results of econometric estimates show that consumers in this region appear to be particularly sensitive to the ban of pesticides and willing to pay higher prices for such products.