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.

Antigen-presenting cells in draining lymph nodes of goats repeatedly infested by the Cayenne tick Amblyomma cajennense nymphs

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Immune response pattern of the popliteal lymph nodes of dogs with visceral leishmaniasis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Roteamento em Redes de Sensores Sem Fios Com Base Em Aprendizagem Por Reforço

The use of wireless sensor and actuator networks in industry has been increasing past few years, bringing multiple benefits compared to wired systems, like network flexibility and manageability. Such networks consists of a possibly large number of small and autonomous sensor and actuator devices with wireless communication capabilities. The data collected by sensors are sent directly or through intermediary nodes along the network to a base station called sink node. The data routing in this environment is an essential matter since it is strictly bounded to the energy efficiency, thus the network lifetime. This work investigates the application of a routing technique based on Reinforcement Learning s Q-Learning algorithm to a wireless sensor network by using an NS-2 simulated environment. Several metrics like energy consumption, data packet delivery rates and delays are used to validate de proposal comparing it with another solutions existing in the literature

Polymorphisms of Lewis and Secretor genes are related to breast cancer and metastasis in axillary lymph nodes

ABH and Lewis antigen expression has been associated with cancer development and prognosis, tumor differentiation, and metastasis. Considering that invasive ductal breast carcinoma (IDC) presents multiple molecular alterations, the aim of the present study was to determine whether the polymorphism of ABO, Lewis, and Secretor genes, as well as ABO phenotyping, could be associated with tumor differentiation and lymph nodes metastasis. Seventy-six women with IDC and 78 healthy female blood donors were submitted to ABO phenotyping/genotyping and Lewis and Secretor genotyping. Phenotyping was performed by hemagglutination and genotyping by the polymerase chain reaction with sequence-specific primers. ABO, Lewis, and Secretor genes were classified by individual single nucleotide polymorphism at sites 59, 1067, 202, and 314 of the Lewis gene, 428 of the Secretor gene, and 261 (O1 allele), 526 (O2 and B allele), and 703 (B allele). No association was found between breast cancer and ABO antigen expression (P = 0.9323) or genotype (P = 0.9356). Lewis-negative genotype was associated with IDC (P = 0.0126) but not with anatomoclinical parameters. Nonsecretor genotype was associated with axillary lymph node metastasis (P = 0.0149). In conclusion, Lewis and Secretor genotyping could be useful to predict respectively breast cancer susceptibility and axillary lymph nodes metastasis.