Creative clusters and universities : the cluster concept in economics and geography

This paper considers the history of the cluster concept in urban economic geography, and its relationship to recent debates about creative cities. It then looks at the role that universities can play in the development of a creative cluster, as well as some of the potential pitfalls.

Calculations of capacitive couplings in induction generators to analyse shaft voltage

This paper deals with the analysis of the parameters which are effective in shaft voltage generation of induction generators. It focuses on different parasitic capacitive couplings by mathematical equations, finite element simulations and experiments. The effects of different design parameters have been studied on proposed capacitances and resultant shaft voltage. Some parameters can change proposed capacitive coupling such as: stator slot tooth, the gap between slot tooth and winding, and the height of the slot tooth, as well as the air gap between the rotor and the stator. This analysis can be used in a primary stage of a generator design to reduce motor shaft voltage and avoid additional costs of resultant bearing current mitigation.

Up the junction? Exploiting knowledge-based development through supply chain and SME cluster interactions

Maximisation of Knowledge-Based Development (KBD) benefits requires effective dissemination and utilisation mechanisms to accompany the initial knowledge creation process. This work highlights the potential for interactions between Supply Chains (SCs) and Small and Medium sized Enterprise Clusters (SMECs), (including via ‘junction’ firms which are members of both networks), to facilitate such effective dissemination and utilisation of knowledge. In both these network types there are firms that readily utilise their relationships and ties for ongoing business success through innovation. The following chapter highlights the potential for such beneficial interactions between SCs and SMECs in key elements of KBD, particularly knowledge management, innovation and technology transfer. Because there has been little focus on the interactions between SCs and SMECs, particularly when firms simultaneously belong to both, this chapter examines the conduits through which information and knowledge can be transferred and utilised. It shows that each network type has its own distinct advantages in the types of information searched for and transferred amongst network member firms. Comparing and contrasting these advantages shows opportunities for both networks to leverage the knowledge sharing strengths of each other, through these ‘junctions’ to address their own weaknesses, allowing implications to be drawn concerning new ways of utilising relationships for mutual network gains.

Using honeypots to analyse anomalous Internet activities

Monitoring Internet traffic is critical in order to acquire a good understanding of threats to computer and network security and in designing efficient computer security systems. Researchers and network administrators have applied several approaches to monitoring traffic for malicious content. These techniques include monitoring network components, aggregating IDS alerts, and monitoring unused IP address spaces. Another method for monitoring and analyzing malicious traffic, which has been widely tried and accepted, is the use of honeypots. Honeypots are very valuable security resources for gathering artefacts associated with a variety of Internet attack activities. As honeypots run no production services, any contact with them is considered potentially malicious or suspicious by definition. This unique characteristic of the honeypot reduces the amount of collected traffic and makes it a more valuable source of information than other existing techniques. Currently, there is insufficient research in the honeypot data analysis field. To date, most of the work on honeypots has been devoted to the design of new honeypots or optimizing the current ones. Approaches for analyzing data collected from honeypots, especially low-interaction honeypots, are presently immature, while analysis techniques are manual and focus mainly on identifying existing attacks. This research addresses the need for developing more advanced techniques for analyzing Internet traffic data collected from low-interaction honeypots. We believe that characterizing honeypot traffic will improve the security of networks and, if the honeypot data is handled in time, give early signs of new vulnerabilities or breakouts of new automated malicious codes, such as worms. The outcomes of this research include: • Identification of repeated use of attack tools and attack processes through grouping activities that exhibit similar packet inter-arrival time distributions using the cliquing algorithm; • Application of principal component analysis to detect the structure of attackers’ activities present in low-interaction honeypots and to visualize attackers’ behaviors; • Detection of new attacks in low-interaction honeypot traffic through the use of the principal component’s residual space and the square prediction error statistic; • Real-time detection of new attacks using recursive principal component analysis; • A proof of concept implementation for honeypot traffic analysis and real time monitoring.

Cluster-based Intrusion Detection (CBID) architecture for mobile ad hoc networks

The ad hoc networks are vulnerable to attacks due to distributed nature and lack of infrastructure. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. The clustering protocols can be taken as an additional advantage in these processing constrained networks to collaboratively detect intrusions with less power usage and minimal overhead. Existing clustering protocols are not suitable for intrusion detection purposes, because they are linked with the routes. The route establishment and route renewal affects the clusters and as a consequence, the processing and traffic overhead increases due to instability of clusters. The ad hoc networks are battery and power constraint, and therefore a trusted monitoring node should be available to detect and respond against intrusions in time. This can be achieved only if the clusters are stable for a long period of time. If the clusters are regularly changed due to routes, the intrusion detection will not prove to be effective. Therefore, a generalized clustering algorithm has been proposed that can run on top of any routing protocol and can monitor the intrusions constantly irrespective of the routes. The proposed simplified clustering scheme has been used to detect intrusions, resulting in high detection rates and low processing and memory overhead irrespective of the routes, connections, traffic types and mobility of nodes in the network. Clustering is also useful to detect intrusions collaboratively since an individual node can neither detect the malicious node alone nor it can take action against that node on its own.

Cluster-based network model for time-course gene expression data

We propose a model-based approach to unify clustering and network modeling using time-course gene expression data. Specifically, our approach uses a mixture model to cluster genes. Genes within the same cluster share a similar expression profile. The network is built over cluster-specific expression profiles using state-space models. We discuss the application of our model to simulated data as well as to time-course gene expression data arising from animal models on prostate cancer progression. The latter application shows that with a combined statistical/bioinformatics analyses, we are able to extract gene-to-gene relationships supported by the literature as well as new plausible relationships.

Mineralized human primary osteoblast matrices as a model system to analyse interactions of prostate cancer cells with the bone microenvironment

Prostate cancer metastasis is reliant on the reciprocal interactions between cancer cells and the bone niche/micro-environment. The production of suitable matrices to study metastasis, carcinogenesis and in particular prostate cancer/bone micro-environment interaction has been limited to specific protein matrices or matrix secreted by immortalised cell lines that may have undergone transformation processes altering signaling pathways and modifying gene or receptor expression. We hypothesize that matrices produced by primary human osteoblasts are a suitable means to develop an in vitro model system for bone metastasis research mimicking in vivo conditions. We have used a decellularized matrix secreted from primary human osteoblasts as a model for prostate cancer function in the bone micro-environment. We show that this collagen I rich matrix is of fibrillar appearance, highly mineralized, and contains proteins, such as osteocalcin, osteonectin and osteopontin, and growth factors characteristic of bone extracellular matrix (ECM). LNCaP and PC3 cells grown on this matrix, adhere strongly, proliferate, and express markers consistent with a loss of epithelial phenotype. Moreover, growth of these cells on the matrix is accompanied by the induction of genes associated with attachment, migration, increased invasive potential, Ca2+ signaling and osteolysis. In summary, we show that growth of prostate cancer cells on matrices produced by primary human osteoblasts mimics key features of prostate cancer bone metastases and thus is a suitable model system to study the tumor/bone micro-environment interaction in this disease.

Case management educational intervention with public health nurses : cluster randomized controlled trial

Aim: This paper is a report of a study conducted to determine the effectiveness of a community case management collaborative education intervention in terms of satisfaction, learning and performance among public health nurses. Background: Previous evaluation studies of case management continuing professional education often failed to demonstrate effectiveness across a range of outcomes and had methodological weaknesses such as small convenience samples and lack of control groups. Method: A cluster randomised controlled trial was conducted between September 2005 and February 2006. Ten health centre clusters (5 control, 5 intervention) recruited 163 public health nurses in Taiwan to the trial. After pre-tests for baseline measurements, public health nurses in intervention centres received an educational intervention of four half-day workshops. Post-tests for both groups were conducted after the intervention. Two-way repeated measures analysis of variance was performed to evaluate the effect of the intervention on target outcomes. Results: A total of 161 participants completed the pre- and post-intervention measurements. This was almost a 99% response rate. Results revealed that 97% of those in the experimental group were satisfied with the programme. There were statistically significant differences between the two groups in knowledge (p = 0.001), confidence in case management skills (p = 0.001), preparedness for case manager role activities (p = 0.001), self-reported frequency in using skills (p = 0.001), and role activities (p = 0.004). Conclusion: Collaboration between academic and clinical nurses is an effective strategy to prepare nurses for rapidly-changing roles.

Connected Communities and Creative Economy; Clash, cluster, complexity, creativity

After a brief personal orientation, this presentation offers an opening section on „clash, cluster, complexity, cities‟ – making the case that innovation (both creative and economic) proceeds not only from incremental improvements within an expert-pipeline process, but also from the clash of different systems, generations, and cultures. The argument is that cultural complexity arises from such clashes, and that clustering is the solution to problems of complexity. The classic, 10,000-year-old, institutional form taken by such clusters is … cities. Hence, a creative city is one where clashing and competitive complexity is clustered… and, latterly, networked.

Cluster analysis of movement patterns in multiarticular actions: A tutorial

The present paper proposes a technical analysis method for extracting information about movement patterning in studies of motor control, based on a cluster analysis of movement kinematics. In a tutorial fashion, data from three different experiments are presented to exemplify and validate the technical method. When applied to three different basketball-shooting techniques, the method clearly distinguished between the different patterns. When applied to a cyclical wrist supination-pronation task, the cluster analysis provided the same results as an analysis using the conventional discrete relative phase measure. Finally, when analyzing throwing performance constrained by distance to target, the method grouped movement patterns together according to throwing distance. In conclusion, the proposed technical method provides a valuable tool to improve understanding of coordination and control in different movement models, including multiarticular actions.

Developing a creative cluster in a postindustrial city : CIDS and Manchester

This paper takes the establishment and demise of Manchester’s Creative Industries Development Service as an exemplary case study for the ways in which creative industry policy has intersected with urban economic policy over the last decade. It argues that the creative industries required specific kinds of economic development agencies which would be able to act as ‘intermediary’ between the distinct languages of policy makers and ‘creatives’. The paper discusses the tensions inherent in such an approach and how CIDS attempted to manage them. It suggests that which particular circumstances might have intervened the main reason for the demise of the CIDS was the domination of the ‘economic’ over the ‘cultural logic’ both of which are embedded within the creative industries policy discourse.