Space and culture: Tradition verses culture

This paper proposes to examine contemporary culture, through communication and technology, in an attempt to expose some of these new or altered spatial concepts evident in film and built form, such as ratefaction and saturation

Effective web service discovery using a combination of a semantic model and a data mining technique

With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

Implication of 3D culture system for study of prostate cancer (CaP) mediated bone metastasis

Introduction : For the past decade, three dimensional (3D) culture has served as a foundation for regenerative medicine study. With an increasing awareness of the importance of cell-cell and cell-extracellular matrix interactions which are lacking in 2D culture system, 3D culture system has been employed for many other applications namely cancer research. Through development of various biomaterials and utilization of tissue engineering technology, many in vivo physiological responses are now better understood. The cellular and molecular communication of cancer cells and their microenvironment, for instance can be studied in vitro in 3D culture system without relying on animal models alone. Predilection of prostate cancer (CaP) to bone remains obscure due to the complexity of the mechanisms and lack of proper model for the studies. In this study, we aim to investigate the interaction between CaP cells and osteoblasts simulating the natural bone metastasis. We also further investigate the invasiveness of CaP cells and response of androgen sensitve CaP cells, LNCaP to synthetic androgen.----- Method : Human osteoblast (hOB) scaffolds were prepared by seeding hOB on medical grade polycaprolactone-tricalcium phosphate (mPLC-TCP) scaffolds and induced to produce bone matrix. CaP cell lines namely wild type PC3 (PC3-N), overexpressed prostate specific antigen PC3 (PC3k3s5) and LNCaP were seeded on hOB scaffolds as co-cultures. Morphology of cells was examined by Phalloidin-DAPI and SEM imaging. Gelatin zymography was performed on the 48 hours conditioned media (CM) from co-cultures to determine matrix metalloproteinase (MMP) activity. Gene expression of hOB/LNCaP co-cultures which were treated for 48 hours with 1nM synthetic androgen R1881 were analysed by quantitative real time PCR (qRT-PCR).----- Results : Co-culture of PCC/hOB revealed that the morphology of PCCs on the tissue engineered bone matrix varied from homogenous to heterogenous clusters. Enzymatically inactive pro-MMP2 was detected in CM from hOBs and PCCs cultured on scaffolds. Elevation in MMP9 activity was found only in hOB/PC3N co-culture. hOB/LNCaP co-culture showed increase in expression of key enzymes associated with steroid production which also corresponded to an increase in prostate specific antigen (PSA) and MMP9.----- Conclusions : Upregulation of MMP9 indicates involvement of ECM degradation during cancer invasion and bone metastases. Expression of enzymes involved in CaP progression, PSA, which is not expressed in osteoblasts, demonstrates that crosstalk between PCCs and osteoblasts may play a part in the aggressiveness of CaP. The presence of steroidogenic enzymes, particularly, RDH5, in osteoblasts and stimulated expression in co-culture, may indicate osteoblast production of potent androgens, fuelling cancer cell proliferation. Based on these results, this practical 3D culture system may provide greater understanding into CaP mediated bone metastasis. This allows the role of the CaP/hOB interaction with regards to invasive property and steroidogenesis to be further explored.

A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

Data mining on prices of highway project main material based on WEB

The management of main material prices of provincial highway project quota has problems of lag and blindness. Framework of provincial highway project quota data MIS and main material price data warehouse were established based on WEB firstly. Then concrete processes of provincial highway project main material prices were brought forward based on BP neural network algorithmic. After that standard BP algorithmic, additional momentum modify BP network algorithmic, self-adaptive study speed improved BP network algorithmic were compared in predicting highway project main prices. The result indicated that it is feasible to predict highway main material prices using BP NN, and using self-adaptive study speed improved BP network algorithmic is the relatively best one.

Building an ontology and process architecture for engineering asset management

Historically, asset management focused primarily on the reliability and maintainability of assets; organisations have since then accepted the notion that a much larger array of processes govern the life and use of an asset. With this, asset management’s new paradigm seeks a holistic, multi-disciplinary approach to the management of physical assets. A growing number of organisations now seek to develop integrated asset management frameworks and bodies of knowledge. This research seeks to complement existing outputs of the mentioned organisations through the development of an asset management ontology. Ontologies define a common vocabulary for both researchers and practitioners who need to share information in a chosen domain. A by-product of ontology development is the realisation of a process architecture, of which there is also no evidence in published literature. To develop the ontology and subsequent asset management process architecture, a standard knowledge-engineering methodology is followed. This involves text analysis, definition and classification of terms and visualisation through an appropriate tool (in this case, the Protégé application was used). The result of this research is the first attempt at developing an asset management ontology and process architecture.

Multilineage differentiation potential of bone and cartilage cells derived from explant culture

To date, mesenchymal stem cells (MSCs) from various tissues have been reported, but the yield and differentiation potential of different tissue-derived MSCs is still not clear. This study was undertaken in an attempt to investigate the multilineage stem cell potential of bone and cartilage explant cultures in comparison with bone marrow derived mesenchymal stem cells (BMSCs). The results showed that the surface antigen expression of tissue-derived cells was consistent with that of mesenchymal stem cells, such as lacking the haematopoietic and common leukocyte markers (CD34, CD45) while expressing markers related to adhesion (CD29, CD166) and stem cells (CD90, CD105). The tissue-derived cells were able to differentiate into osteoblast, chondrocyte and adipocyte lineage pathways when stimulated in the appropriate differentiating conditions. However, compared with BMSCs, tissue-derived cells showed less capacity for multilineage differentiation when the level of differentiation was assessed in monolayer culture by analysing the expression of tissue-specific genes by reverse transcription polymerase chain reaction (RT-PCR) and histology. In high density pellet cultures, tissue-derived cells were able to differentiate into chondrocytes, expressing chondrocyte markers such as proteoglycans, type II collagen and aggrecan. Taken together, these results indicate that cells derived from tissue explant cultures reserved certain degree of differentiation properties of MSCs in vitro.

Assessing organizational culture? value management to the rescue

As part of a Doctor of Business Administration degree programme jointly run by Curtin University, Perth, Australia and Lingnan University, Hong Kong, a research thesis relating organizational effectiveness to the organizational culture of Hong Kong construction firms involved in public housing is being undertaken. Organizational effectiveness is measured by the Housing Department (HD) Performance Assessment Scoring System (PASS) and organizational culture traits and strengths have been measured by using the Denison Organizational Culture Survey (OCS), developed by Daniel Denison and William S. Neale and based on 16 years of research involving over 1,000 organizations. The PASS scores of building contractors are compared with the OCS scores to determine if there is any significant correlation between highly effective companies and particular organizational strengths and traits. Profiles are then drawn using the Denison Model and can be compared against ‘norms’ for the industry sector on which the survey has been carried out. The next stage of the work is to present the results of the survey to individual companies, conduct focus group interviews to test the results, discover more detail on that company’s culture and discuss possible actions based on the results. It is in this latter stage that certain value management techniques may well prove very useful.

Tissue engineering of articular cartilage with biomimetic zones

Articular cartilage damage is a persistent and increasing problem with the aging population, and treatments to achieve biological repair or restoration remain a challenge. Cartilage tissue engineering approaches have been investigated for over 20 years, but have yet to achieve the consistency and effectiveness for widespread clinical use. One of the potential reasons for this is that the engineered tissues do not have or establish the normal zonal organization of cells and extracellular matrix that appears critical for normal tissue function. A number of approaches are being taken currently to engineer tissue that more closely mimics the organization of native articular cartilage. This review focuses on the zonal organization of native articular cartilage, strategies being used to develop such organization, the reorganization that occurs after culture or implantation, and future prospects for the tissue engineering of articular cartilage with biomimetic zones.

Creativity, culture and tourism : the case of Istanbul and London film industries

During the last decade many cities have sought to promote creativity as a driver for economic growth. They have done this by encouraging specific sectors of creative industries. This paper focuses on the film industry as one of these sectors which also has a high level of interaction with place. Film industry, has had an important role in incubating the creativity potential. It can be a powerful magnet for creative people, fostering indigenous creativity and attracting outside talent, and might thus contribute to the formation of creative cities. This recent research suggests that the film industry has positively effect on tourism by increasing place recognition through the locations used in films and for cities that host film festivals. Film festivals provide events, workshops and experiences that allow visitors to express themselves through interaction with the place and its living culture. This paper examines the importance of creative industries for both urban development and sustainable tourism. To explore the relation between creative tourism, culture and the film industry and its effect on successful tourism planning this paper presents the preliminary findings of case studies of the film industry in Beyo

A role mining inspired approach to representing user behaviour in ERP systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the most predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Application of text mining in analysing road crashes for road asset management

Traffic safety is a major concern world-wide. It is in both the sociological and economic interests of society that attempts should be made to identify the major and multiple contributory factors to those road crashes. This paper presents a text mining based method to better understand the contextual relationships inherent in road crashes. By examining and analyzing the crash report data in Queensland from year 2004 and year 2005, this paper identifies and reports the major and multiple contributory factors to those crashes. The outcome of this study will support road asset management in reducing road crashes.

Project culture in the Chinese construction industry : perceptions of contractors

In recent years culture has become one of the most studied topics in project management research. Some studies have investigated the influence of culture at different levels – such as national culture, industry culture, organisational culture and professional culture. As a project-based industry, the construction industry needs to have more insight concerning cultural issues at the project level and their influence on the performance of construction projects. Few studies, however, have focused on culture at the project level. This paper uses a questionnaire survey to determine the perceptions of Chinese contractors about the impact of project culture on the performance of local construction projects. This is augmented by a series of in-depth interviews with senior executive managers in the industry. The findings indicate that specific project culture does contribute significantly towards project outcomes. In particular, goal orientation and flexibility, as two dimensions of project culture, have a negative statistical correlation with perceived satisfaction of the process, commercial success, future business opportunities, lessons learnt from the project, satisfaction with the relationships, and overall performance. This paper also indicates that the affordability of developing an appropriate project culture is a major concern for industry practitioners.

Personalised ontology learning and mining for web information gathering

Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated user needs for e±cient mechanisms for information and knowledge location, selection, and retrieval. How to gather useful and meaningful information from the Web becomes challenging to users. The capture of user information needs is key to delivering users' desired information, and user pro¯les can help to capture information needs. However, e®ectively acquiring user pro¯les is di±cult. It is argued that if user background knowledge can be speci¯ed by ontolo- gies, more accurate user pro¯les can be acquired and thus information needs can be captured e®ectively. Web users implicitly possess concept models that are obtained from their experience and education, and use the concept models in information gathering. Prior to this work, much research has attempted to use ontologies to specify user background knowledge and user concept models. However, these works have a drawback in that they cannot move beyond the subsumption of super - and sub-class structure to emphasising the speci¯c se- mantic relations in a single computational model. This has also been a challenge for years in the knowledge engineering community. Thus, using ontologies to represent user concept models and to acquire user pro¯les remains an unsolved problem in personalised Web information gathering and knowledge engineering. In this thesis, an ontology learning and mining model is proposed to acquire user pro¯les for personalised Web information gathering. The proposed compu- tational model emphasises the speci¯c is-a and part-of semantic relations in one computational model. The world knowledge and users' Local Instance Reposito- ries are used to attempt to discover and specify user background knowledge. From a world knowledge base, personalised ontologies are constructed by adopting au- tomatic or semi-automatic techniques to extract user interest concepts, focusing on user information needs. A multidimensional ontology mining method, Speci- ¯city and Exhaustivity, is also introduced in this thesis for analysing the user background knowledge discovered and speci¯ed in user personalised ontologies. The ontology learning and mining model is evaluated by comparing with human- based and state-of-the-art computational models in experiments, using a large, standard data set. The experimental results are promising for evaluation. The proposed ontology learning and mining model in this thesis helps to develop a better understanding of user pro¯le acquisition, thus providing better design of personalised Web information gathering systems. The contributions are increasingly signi¯cant, given both the rapid explosion of Web information in recent years and today's accessibility to the Internet and the full text world.