David Taniar

Computational Science and Its Applications - ICCSA 2006

Lets read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd computational science and its applications iccsa 2006 international conference glasgow uk may 8 11 2006 proceedings part iii lecture notes in computer science to read.

Computational Science and Its Applications – ICCSA 2012

The neoclassical production function assumes that economic growth depends on exogenous factors of production centred on capital, labour and technology. However, residual variables, notably social capabilities and knowledge, are neglected. This study seeks to highlight that, in fact, they are key variables for understanding the economic growth and recent structural changes of an industrial cluster, both in technical and organizational terms. In this work, the peculiarity of knowledge and in particular of tacit knowledge form a crucial element in the social capabilities that are associated with enlarging knowledge learning processes and network diffusion. The aim of this research is to analyse the key role that knowledge and innovations play in the local wedding system of Bari in Puglia. They are the decisive factors in the survival of firms in a global market for the creation of competitive advantage and provide a basis for continuous innovation. The relationship between innovation and knowledge is discussed in the theoretical part of the paper, while the empirical aspect remains based upon results of consumer and producer surveys. The objective is to show how innovation, including demand-driven, can influence companies’ behaviours.

Voronoi-Based Continuous

Digital ecosystems are formed by “digital organisms” in complex, dynamic, and interrelated ecosystems and utilize multiple technologies to provide cost-efficient digital services and value-creating activities. A distributed wireless mobile network that serves as the underlying infrastructure to digital ecosystems provides important applications to the digital ecosystems, two of which are mobile navigation and continuous mobile information services. Most information and query services in a mobile environment are continuous mobile query processing or continuous k nearest neighbor (CKNN), which finds the locations where interest points or interest objects change while mobile users are moving. These locations are known as “split nodes.” All of the existing works on CKNN divide the query path into segments, which is a segment of road separated by two intersections, and then, the process to find split nodes is applied to each segment. Since there are many segments (due to many intersections, obviously), processing each segment is naturally inefficient. In this paper, we propose an alternative solution to overcome this problem. We use the Voronoi diagram for CKNN [called Voronoi CKNN (VCKNN)]. Our proposed approach does not need to divide the query path into segments, hence improving the overall query processing performance. Our experiment verified the applicability of the VCKNN approach to solve CKNN queries.

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The smart phone usage and multimedia devices have been increasing yearly and predictions indicate drastic increase in the upcoming years. Recently, various wireless technologies have been introduced to add flexibility to these gadgets. As data plans offered by the network service providers are expensive, users are inclined to utilize freely accessible and commonly available Wi-Fi networks indoors. LTE (Long Term Evolution) has been a topic of discussion in providing high data rates outdoors and various service providers are planning to roll out LTE networks all over the world. The objective of this presentation is to compare usefulness of these two leading wireless schemes based on LTE and Wireless Mesh Networks (WMN) and bring forward their advantages for indoor and outdoor environments. We also investigate to see if a hybrid LTE-WMN network may be feasible. Both these networks are heterogeneous in nature, employ cognitive approach and support multi hop communication. The main motivation behind this work is to utilize similarities in these networks, explore their capability of offering high data rates and generally have large coverage areas. In this work, we compare both these networks in terms of their data rates, range, cost, throughput, and power consumption. We also compare 802.11n based WMN with Femto cell in an indoor coverage scenario, while for outdoors; 802.16 based WMN is compared with LTE. The main objective is to help users select a network that could provide enhanced performance in a cost effective manner. More information can be found at http://www.iccsa.org/invited-speakers Neoclassical Growth Theory, Regions and Spatial Externalities

Nearest Neighbor Search in Mobile Navigation

The parallel fuzzy c-means (PFCM) algorithm for clustering large data sets is proposed in this paper. The proposed algorithm is designed to run on parallel computers of the Single Program Multiple Data (SPMD) model type with the Message Passing Interface (MPI). A comparison is made between PFCM and an existing parallel k-means (PKM) algorithm in terms of their parallelisation capability and scalability. In an implementation of PFCM to cluster a large data set from an insurance company, the proposed algorithm is demonstrated to have almost ideal speedups as well as an excellent scaleup with respect to the size of the data sets.

Computational Science and Its Applications – ICCSA 2013

Association rule mining is an active data mining research area. However, most ARM algorithms cater to a centralized environment. In contrast to previous ARM algorithms, we have developed a distributed algorithm, called optimized distributed association mining, for geographically distributed data sets. ODAM generates support counts of candidate itemsets quicker than the other DARM algorithms and reduces the size of average transactions, data sets, and message exchanges.

Parallel Fuzzy c-Means Clustering for Large Data Sets

Data mining applications have enormously altered the strategic decision-making processes of organizations. The application of association rules algorithms is one of the well-known data mining techniques that have been developed to cope with multidimensional databases. However, most of these algorithms focus on multidimensional data models for transactional data. As data warehouses can be presented using a multidimensional model, in this paper we provide another perspective to mine association rules in data warehouses by focusing on a measurement of summarized data. We propose four algorithms — VAvg, HAvg, WMAvg, and ModusFilter — to provide efficient data initialization for mining association rules in data warehouses by concentrating on the measurement of aggregate data. Then we apply those algorithms both on a non-repeatable predicate, which is known as mining normal association rules, using GenNLI, and a repeatable predicate using ComDims and GenHLI, which is known as mining hybrid association rules.

ODAM: An optimized distributed association rule mining algorithm

Digital ecosystems offer cost-effective digital services that attract and benefit the species within them (i.e., humans, organizations, and computers). As a cornerstone technology for digital information delivery, data broadcast provides a strong backbone for the digital ecosystem infrastructure. Its scalability feature is highly significant for various digital ecosystem applications, including mobile broadcast services. This paper proposes a novel structure and access for mobile data broadcast. The proposed scheme addresses the tradeoff for minimizing query-access and tuning times by specifying a new message structure. Correspondingly, a new access and processing mode for mobile clients is required. We study the effectiveness of the proposed approach in minimizing query-access time while maintaining low tuning time. The results of our experiments are used to make comparisons with existing approaches. The results affirm the effectiveness of our proposed scheme.

Mining Association Rules in Data Warehouses

The use of Voronoi diagram has traditionally been applied to computational geometry and multimedia problems. In this paper, we will show how Voronoi diagram can be applied to spatial query processing, and in particular to Reverse Nearest Neighbor (RNN) queries. Spatial and geographical query processing, in general, and RNN in particular, are becoming more important, as online maps are now widely available. In this paper, using the concept of Voronoi diagram, we classify RNN into four types depending on whether the query point and the interest objects are the generator points of the Voronoi Polygon or not. Our approach is based on manipulating Network Voronoi Diagram properties and applying a progressive incremental network expansion for finding the polygon inner network distances required to solve RNN queries. Our experimentation results show that our approaches have good response times in answering RNN queries.

A Novel Structure and Access Mechanism for Mobile Data Broadcast in Digital Ecosystems

Developing a data warehouse for XML documents involves two major processes: one of creating it, by processing XML raw documents into a specified data warehouse repository; and the other of querying it, by applying techniques to better answer users’ queries. This paper focuses on the first part; that is identifying a systematic approach for building a data warehouse of XML documents, specifically for transferring data from an underlying XML database into a defined XML data warehouse. The proposed methodology on building XML data warehouses covers processes including data cleaning and integration, summarization, intermediate XML documents, and updating/linking existing documents and creating fact tables. In this paper, we also present a case study on how to put this methodology into practice. We utilise the XQuery technology in all of the above processes.