PhD Students’ Research Group Networks: a Qualitative Approach

This article examines the networks within the research groups where Spanish PhD students are pursuing their doctorate. Capó et al. (2007) used quantitative data to predict PhD students’ publishing performance from their background, attitudes, supervisors’ performance and research group networks. Variables related to the research group network had a negligible explanatory power on student performance once the remaining variables had been accounted for. In this article, a qualitative follow up of the same students is carried out using extreme case sampling and indepth interviews. The qualitative research shows networking as important for students. Out of the 115 aspects that students mention in the interviews as relevant to publishing in the qualitative research, 92 have to do with their supervisors, their research group or their network as a whole. Similarly, out of the 50 hindrances mentioned, 20 have to do with the networks or relations. The most commonly mentioned network-related topics are research group members pushing PhD students to publish, meeting researchers outside the research group, existence of other PhD students in the group, help with the PhD from group members, supervisor’s interest in the thesis, the possibility of discussing with experts on the PhD’s topic and frequent contact with the supervisor and research group members. Some of these characteristics were not, however, measured in the conventional quantitative social network survey

Towards open access networks – prototyping with the Lappeenranta model

The provision of Internet access to large numbers has traditionally been under the control of operators, who have built closed access networks for connecting customers. As the access network (i.e. the last mile to the customer) is generally the most expensive part of the network because of the vast amount of cable required, many operators have been reluctant to build access networks in rural areas. There are problems also in urban areas, as incumbent operators may use various tactics to make it difficult for competitors to enter the market. Open access networking, where the goal is to connect multiple operators and other types of service providers to a shared network, changes the way in which networks are used. This change in network structure dismantles vertical integration in service provision and enables true competition as no service provider can prevent others fromcompeting in the open access network. This thesis describes the development from traditional closed access networks towards open access networking and analyses different types of open access solution. The thesis introduces a new open access network approach (The Lappeenranta Model) in greater detail. The Lappeenranta Model is compared to other types of open access networks. The thesis shows that end users and service providers see local open access and services as beneficial. In addition, the thesis discusses open access networking in a multidisciplinary fashion, focusing on the real-world challenges of open access networks.

Reward networks in the brain as captured by connectivity measures

An assortment of human behaviors is thought to be driven by rewards including reinforcement learning, novelty processing, learning, decision making, economic choice, incentive motivation, and addiction. In each case the ventral tegmental area/ventral striatum (nucleus accumbens) (VTAVS) system has been implicated as a key structure by functional imaging studies, mostly on the basis of standard, univariate analyses. Here we propose that standard functional magnetic resonance imaging analysis needs to be complemented by methods that take into account the differential connectivity of the VTAVS system in the different behavioral contexts in order to describe reward based processes more appropriately. We fi rst consider the wider network for reward processing as it emerged from animal experimentation. Subsequently, an example for a method to assess functional connectivity is given. Finally, we illustrate the usefulness of such analyses by examples regarding reward valuation, reward expectation and the role of reward in addiction.

On Fault Tolerance Methods for Networks-on-Chip

Technology scaling has proceeded into dimensions in which the reliability of manufactured devices is becoming endangered. The reliability decrease is a consequence of physical limitations, relative increase of variations, and decreasing noise margins, among others. A promising solution for bringing the reliability of circuits back to a desired level is the use of design methods which introduce tolerance against possible faults in an integrated circuit. This thesis studies and presents fault tolerance methods for network-onchip (NoC) which is a design paradigm targeted for very large systems-onchip. In a NoC resources, such as processors and memories, are connected to a communication network; comparable to the Internet. Fault tolerance in such a system can be achieved at many abstraction levels. The thesis studies the origin of faults in modern technologies and explains the classification to transient, intermittent and permanent faults. A survey of fault tolerance methods is presented to demonstrate the diversity of available methods. Networks-on-chip are approached by exploring their main design choices: the selection of a topology, routing protocol, and flow control method. Fault tolerance methods for NoCs are studied at different layers of the OSI reference model. The data link layer provides a reliable communication link over a physical channel. Error control coding is an efficient fault tolerance method especially against transient faults at this abstraction level. Error control coding methods suitable for on-chip communication are studied and their implementations presented. Error control coding loses its effectiveness in the presence of intermittent and permanent faults. Therefore, other solutions against them are presented. The introduction of spare wires and split transmissions are shown to provide good tolerance against intermittent and permanent errors and their combination to error control coding is illustrated. At the network layer positioned above the data link layer, fault tolerance can be achieved with the design of fault tolerant network topologies and routing algorithms. Both of these approaches are presented in the thesis together with realizations in the both categories. The thesis concludes that an optimal fault tolerance solution contains carefully co-designed elements from different abstraction levels

Use of neural networks in robot positioning of large flexible redundant manipulators

Deflection compensation of flexible boom structures in robot positioning is usually done using tables containing the magnitude of the deflection with inverse kinematics solutions of a rigid structure. The number of table values increases greatly if the working area of the boom is large and the required positioning accuracy is high. The inverse kinematics problems are very nonlinear, and if the structure is redundant, in some cases it cannot be solved in a closed form. If the structural flexibility of the manipulator arms is taken into account, the problem is almost impossible to solve using analytical methods. Neural networks offer a possibility to approximate any linear or nonlinear function. This study presents four different methods of using neural networks in the static deflection compensation and inverse kinematics solution of a flexible hydraulically driven manipulator. The training information required for training neural networks is obtained by employing a simulation model that includes elasticity characteristics. The functionality of the presented methods is tested based on the simulated and measured results of positioning accuracy. The simulated positioning accuracy is tested in 25 separate coordinate points. For each point, the positioning is tested with five different mass loads. The mean positioning error of a manipulator decreased from 31.9 mm to 4.1 mm in the test points. This accuracy enables the use of flexible manipulators in the positioning of larger objects. The measured positioning accuracy is tested in 9 separate points using three different mass loads. The mean positioning error decreased from 10.6 mm to 4.7 mm and the maximum error from 27.5 mm to 11.0 mm.

A Fair and Secure Cluster Formation Process for Ad Hoc Networks

An efficient approach for organizing large ad hoc networks is to divide the nodesinto multiple clusters and designate, for each cluster, a clusterhead which is responsible forholding intercluster control information. The role of a clusterhead entails rights and duties.On the one hand, it has a dominant position in front of the others because it manages theconnectivity and has access to other node¿s sensitive information. But on the other hand, theclusterhead role also has some associated costs. Hence, in order to prevent malicious nodesfrom taking control of the group in a fraudulent way and avoid selfish attacks from suitablenodes, the clusterhead needs to be elected in a secure way. In this paper we present a novelsolution that guarantees the clusterhead is elected in a cheat-proof manner.

Cryptographic Energy Costs are Assumable in Ad Hoc Networks

Performance of symmetric and asymmetriccryptography algorithms in small devices is presented. Both temporaland energy costs are measured and compared with the basicfunctional costs of a device. We demonstrate that cryptographicpower costs are not a limiting factor of the autonomy of a deviceand explain how processing delays can be conveniently managedto minimize their impact.

Review of Robust Cooperative Spectrum Sensing Techniques for Cognitive Radio Networks

Cognitive radio networks sense spectrum occupancy and manage themselvesto operate in unused bands without disturbing licensed users. The detection capability of aradio system can be enhanced if the sensing process is performed jointly by a group of nodesso that the effects of wireless fading and shadowing can be minimized. However, taking acollaborative approach poses new security threats to the system as nodes can report falsesensing data to reach a wrong decision. This paper makes a review of secure cooperativespectrum sensing in cognitive radio networks. The main objective of these protocols is toprovide an accurate resolution about the availability of some spectrum channels, ensuring thecontribution from incapable users as well as malicious ones is discarded. Issues, advantagesand disadvantages of such protocols are investigated and summarized.

Security, Privacy and Anonymity in Legal Distribution of Copyrighted Multimedia Content over Peer-to-Peer Networks: A Brief Overview

Peer-reviewed

Secure and Anonymous Multimedia Content Distribution in Peer-to-Peer Networks

Peer-reviewed

The effects of social networks on work-team effectiveness

This is a study of team social networks, their antecedents and outcomes. In focusing attention on the structural configuration of the team this research contributes to a new wave of thinking concerning group social capital. The research site was a random sample of Finnish work organisations. The data consisted of 499 employees in 76 teams representing 48 different organisations. A systematic literature review and quantitative methods were used in conducting the research: the former primarily to establish the current theoretical position on the relationships among the variables and the latter to test these relationships. Social network analysis was the primary method used in identifying the social-network relations among the work-team members. The first and key contribution of this study is that it relates the structuralnetwork properties of work teams to behavioural outcomes, attitudinal outcomes and, ultimately, team performance. Moreover, it shows that addressing attitudinal outcomes is also important in terms of team performance; attitudinal outcomes (team identity) mediated the relationship between the team’s performance and its social network. The second contribution is that it examines the possible antecedents of the social structure. It is thus one response to Salancik’s (1995) call for a network theory in that it explains why certain network characteristics exist. Itdemonstrates that irrespective of whether or not a team is heterogeneous in terms of age or gender, educational diversity may protect it from centralisation. However, heterogeneity in terms of gender turned out to have a negative impact on density. Thirdly, given the observation that the benefits of (team) networks are typically theorised and modelled without reference to the nature of the relationships comprising the structure, the study directly tested whether team knowledge mediated the effects of instrumental and expressive network relationships on team performance. Furthermore, with its focus on expressive networks that link the workplace to a more informal world, which have been rather neglected in previous research, it enhances knowledge of teams andnetworks. The results indicate that knowledge sharing fully mediates the influence of complementarities between dense and fragmented instrumental network relationships, thus providing empirical validation of the implicit understanding that networks transfer knowledge. Fourthly, the study findings suggest that an optimal configuration of the work-team social-network structure combines both bridging and bonding social relationships.

Strategic Development of Electricity Distribution Networks – Concept and Methods

Strategic development of distribution networks plays a key role in the asset management in electricity distribution companies. Owing to the capital-intensive nature of the field and longspan operations of companies, the significance of a strategy is emphasised. A well-devised strategy combines awareness of challenges posed by the operating environment and the future targets of the distribution company. Economic regulation, ageing infrastructure, scarcity of resources and tightening supply requirements with challenges created by the climate change put a pressure on the strategy work. On the other hand, technology development related to network automation and underground cabling assists in answering these challenges. This dissertation aims at developing process knowledge and establishing a methodological framework by which key issues related to network development can be addressed. Moreover, the work develops tools by which the effects of changes in the operating environment on the distribution business can be analysed in the strategy work. To this end, the work discusses certain characteristics of the distribution business and describes the strategy process at a principle level. Further, the work defines the subtasks in the strategy process and presents the key elements in the strategy work and long-term network planning. The work delineates the factors having either a direct or indirect effect on strategic planning and development needs in the networks; in particular, outage costs constitute an important part of the economic regulation of the distribution business, reliability being thus a key driver in network planning. The dissertation describes the methodology and tools applied to cost and reliability analyses in the strategy work. The work focuses on determination of the techno-economic feasibility of different network development technologies; these feasibility surveys are linked to the economic regulation model of the distribution business, in particular from the viewpoint of reliability of electricity supply and allowed return. The work introduces the asset management system developed for research purposes and to support the strategy work, the calculation elements of the system and initial data used in the network analysis. The key elements of this asset management system are utilised in the dissertation. Finally, the study addresses the stages of strategic decision-making and compilation of investment strategies. Further, the work illustrates implementation of strategic planning in an actual distribution company environment.

Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.

Description of epidemics of coffee rust with neural networks

The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination (R²) were used. The best model developed with neural networks had an MSD of 4.36 and an MPE of 2.43%. This model used the variables of minimum temperature, production, relative humidity of the air, and irradiance 30 days before the evaluation of disease. The best regression model was developed from 29 selected climatic variables in the network. The summary statistics for this model were: MPE=6.58%, MSE=4.36, and R²=0.80. The elaborated neural networks from a time series also were evaluated to describe the epidemic. The incidence of coffee rust at four previous fortnights resulted in a model with MPE=4.72% and an MSD=3.95.