Feature nodes : an interaction construct for sharing initiative in design exploration

Exploration with formal design systems comprises an iterative process of specifying problems, finding plausible and alternative solutions, judging the validity of solutions relative to problems and reformulating problems and solutions. Recent advances in formal generative design have developed the mathematics and algorithms to describe and perform conceptual design tasks. However, design remains a human enterprise: formalisms are part of a larger equation comprising human computer interaction. To support the user in designing with formal systems, shared representations that interleave initiative of the designer and the design formalism are necessary. The problem of devising representational structures in which initiative is sometimes taken by the designer and sometimes by a computer in working on a shared design task is reported in this paper. To address this problem, the requirements, representation and
implementation of a shared interaction construct, the feature node, is
described. The feature node facilitates the sharing of initiative in formulating and reformulating problems, generating solutions, making
choices and navigating the history of exploration.

Sink or swim- ageing in Australia

As the number of people under the age of 65 declines, the number over 65 will double in the next half century. By 2031, it is estimated those over 65 will account for more than a quarter of the Australian population. The fastest rate of growth will be in the over-85-years category, projected to double over the next 20 years and to triple over 50 years to include 2.3 million people. Health care providers cannot afford to wait for the inevitable crises this vast demographic shift will provoke. To meet these future demands, educational and health care institutes should consider establishing interdisciplinary think-tanks for multidisciplinary research, policy development and innovations in aged care and health service delivery.
Aust Health Rev 2005: 29(2): 146-150

Knowledge distribution nodes and home based businesses : role of business associations and local council in Casey LGA

This paper examines the stmcture, function and role of local business associations in home based business development within an urban region. Casey local government area (LOA), Victoria, is the focus, where nine local business associations in the area (as well as the local council) are evaluated in the context of support for local-based business development. The evaluation draws upon primary data co llected by surveys of local home based businesses, and follows up by semi-stmctured interviews of representatives from these business associations and the local council. This paper identifies that local business associations are fragmented and have significant overlap in their activities of which the commonest activity is acting as a knowledge distribution node. The cash strapped local council is the most important node. All are restricted by vision and resources. As a result, the services provided have little impact on sustainable business development in Casey.

Knowledge distribution nodes and home based businesses : role of local business associations and local council in Casey LGA

This paper examines the structure, function and role of local business associations in home based business development within an urban region. Casey local government area (LGA), Victoria, is the focus, where nine local business associations in the area (as well as the local council) are evaluated in the context of support for local-based business development. The evaluation draws upon primary data collected by surveys of local home based businesses, and follows up by semi-structured interviews of representatives from these business associations and the local council. This paper identifies that local business associations are fragmented and have significant overlap in their activities, of which the commonest activity is acting as a knowledge distribution node. The cash strapped local council is the most important node. All are restricted by vision and resources. As a result, the services provided have little impact on sustainable business development in Casey.

A simple motion heuristic for controlling mobile sinks in delay tolerant sensor networks

Optimising energy consumption in wireless sensor networks is of dominant importance. Sink mobility is introduced to deal with this problem by approaching the sensor nodes and collecting their data buffers using the less energy demanding single-hop communication. The sink route is very crucial for the data collection operation performed in the network especially when the collection requests generated by the sensors are revealed dynamically to the sink and not known ahead. This paper presents a practical motion heuristic for constructing the sink route based on the dynamic arrival of the collection requests. Three control schemes are proposed for coordinating the interaction of multiple mobile sinks collectively performing the data collection in the network. The main objective is maximising the data collected by each mobile sink while minimising the sleeping time of each sensor awaiting the collection service. Simulation results show the performance of the mobile sinks under the proposed control schemes and the impact of the motion heuristic on the sensors' sleeping time in the network.

Trust evaluation for indirectly connected nodes using link community information

Inspired by recent empirical research on link communities, we borrow some important ideas and concepts for our own research to provide a more reasonable computation model of transitive trust. The key advantages of using link community methodology is to reflect on the nature of the social network features of Hierarchy and Overlap. Our research mainly resolves the computation of trust transitivity in which two nodes do not have any direct links to any link community. In this research, we discover a new direction analyzing trust transitivity. By using a social network game, we found that the link community methodology is a natural way to analyze trust in social networks. We also discovered, even in a small social network, trust has certain community features.

Adaptation of LEACH routing protocol to cognitive radio sensor networks

One of the drawbacks of LEACH protocol is the uncontrolled selection of cluster heads which, in some rounds, leads to the concentration of them in a limited area due to the randomness of the selection procedure. LEACH-C is a variant of LEACH that uses a centralized clustering algorithm and forms good clusters through sink control. According to experimental results, the IEEE 802.15.4 packets are damaged by WLAN interferences in ISM band. It seems that, sensor nodes equipped with cognitive radio capabilities can overcome this problem. In cognitive radio sensor networks (CRSN), routing must be accompanied by channel allocation. This requires spectrum management which can be devolved to cluster heads. For this networks, new duty cycle mechanisms must be designed that jointly consider neighbor discovery, and spectrum sensing/allocation. Cluster-based network architecture is a good choice for effective dynamic spectrum management. In such architecture, cluster heads have a proper spatial distribution and are optimally located all over the network. In this paper, using the physical layer information and preserving the feature of random cluster head selection in LEACH, it has been tried to both move the position of cluster heads to appropriate locations and make their quantity optimal. The simulation results show that the transferal of cluster heads to appropriate locations increases the network lifetime significantly though this comes at the price of early instability appearance. By considering the energy level in cluster head election algorithm, one can overcome the network stability issues too. However, this will move the cluster heads away from their appropriate locations. © 2012 IEEE.

Identifying influential nodes in complex networks: A multiple attributes fusion method

How to identify influential nodes is still an open hot issue in complex networks. Lots of methods (e.g., degree centrality, betweenness centrality or K-shell) are based on the topology of a network. These methods work well in scale-free networks. In order to design a universal method suitable for networks with different topologies, this paper proposes a Multiple Attribute Fusion (MAF) method through combining topological attributes and diffused attributes of a node together. Two fusion strategies have been proposed in this paper. One is based on the attribute union (FU), and the other is based on the attribute ranking (FR). Simulation results in the Susceptible-Infected (SI) model show that our proposed method gains more information propagation efficiency in different types of networks. © 2014 Springer International Publishing.

Identifying influential nodes in complex networks for network immunization

Identifying influential nodes is of theoretical significance in network immunization which is one of important methods to prevent virus propagation through protecting the influential nodes in a network. Lots of methods have been proposed to find these influential nodes based on the topological characteristics of a network (e.g., degree, betweenness or K-shell). Whereas due to the diversity of network topologies, these methods are not always effective in identifying influential nodes in any benchmark networks. We combine the advantages of existing methods based on attribute ranking and propose a universal ranking method, namely MAF (Multiple Attribute Fusion), to identify influential nodes from a complex network. We compare the efficiency of our proposed method with existing immunization strategies in different types of networks. Simulation results in the interactive email model show that the immunized nodes selected by MAF can restrain virus propagation effectively.

Mining mechanism of top-k influential nodes based on voting algorithm in mobile social networks

In recent years, evaluating the influence of nodes and finding top-k influential nodes in social networks, has drawn a wide attention and has become a hot-pot research issue. Considering the characteristics of social networks, we present a novel mechanism to mine the top-k influential nodes in mobile social networks. The proposed mechanism is based on the behaviors analysis of SMS/MMS (simple messaging service / multimedia messaging service) communication between mobile users. We introduce the complex network theory to build a social relation graph, which is used to reveal the relationship among people's social contacts and messages sending. Moreover, intimacy degree is also introduced to characterize social frequency among nodes. Election mechanism is hired to find the most influential node, and then a heap sorting algorithm is used to sort the voting results to find the k most influential nodes. The experimental results show that the mechanism can finds out the most influential top-k nodes efficiently and effectively. © 2013 IEEE.

Combination methods for identifying influential nodes in networks

Identifying influential nodes is of theoretical significance in many domains. Although lots of methods have been proposed to solve this problem, their evaluations are under single-source attack in scale-free networks. Meanwhile, some researches have speculated that the combinations of some methods may achieve more optimal results. In order to evaluate this speculation and design a universal strategy suitable for different types of networks under the consideration of multi-source attacks, this paper proposes an attribute fusion method with two independent strategies to reveal the correlation of existing ranking methods and indicators. One is based on feature union (FU) and the other is based on feature ranking (FR). Two different propagation models in the fields of recommendation system and network immunization are used to simulate the efficiency of our proposed method. Experimental results show that our method can enlarge information spreading and restrain virus propagation in the application of recommendation system and network immunization in different types of networks under the condition of multi-source attacks.

Reliability evaluation for clustered WSNs under malware propagation

We consider a clustered wireless sensor network (WSN) under epidemic-malware propagation conditions and solve the problem of how to evaluate its reliability so as to ensure efficient, continuous, and dependable transmission of sensed data from sensor nodes to the sink. Facing the contradiction between malware intention and continuous-time Markov chain (CTMC) randomness, we introduce a strategic game that can predict malware infection in order to model a successful infection as a CTMC state transition. Next, we devise a novel measure to compute the Mean Time to Failure (MTTF) of a sensor node, which represents the reliability of a sensor node continuously performing tasks such as sensing, transmitting, and fusing data. Since clustered WSNs can be regarded as parallel-serial-parallel systems, the reliability of a clustered WSN can be evaluated via classical reliability theory. Numerical results show the influence of parameters such as the true positive rate and the false positive rate on a sensor node's MTTF. Furthermore, we validate the method of reliability evaluation for a clustered WSN according to the number of sensor nodes in a cluster, the number of clusters in a route, and the number of routes in the WSN.