The impact of institutional, instrumental and interpersonal underpinnings on network dynamics and outcomes

Networks form a key part of the infrastructure of contemporary governance arrangements and, as such, are likely to continue for some time. Networks can take many forms and be formed for many reasons. Some networks have been explicitly designed to generate a collective response to an issue; some arise from a top down perspective through mandate or coercion; while others rely more heavily on interpersonal relations and doing the right thing. In this paper, these three different perspectives are referred to as the “3I”s: Instrumental, Institutional or Interpersonal. It is proposed that these underlying motivations will affect the process dynamics within the different types of networks in different ways and therefore influence the type of outcomes achieved. This proposition is tested through a number of case studies. An understanding of these differences will lead to more effective design, management and clearer expectations of what can be achieved through networks.

Predictive compensation for variable network delays and packet losses in networked control systems

Networked control systems (NCSs) offer many advantages over conventional control; however, they also demonstrate challenging problems such as network-induced delay and packet losses. This paper proposes an approach of predictive compensation for simultaneous network-induced delays and packet losses. Different from the majority of existing NCS control methods, the proposed approach addresses co-design of both network and controller. It also alleviates the requirements of precise process models and full understanding of NCS network dynamics. For a series of possible sensor-to-actuator delays, the controller computes a series of corresponding redundant control values. Then, it sends out those control values in a single packet to the actuator. Once receiving the control packet, the actuator measures the actual sensor-to-actuator delay and computes the control signals from the control packet. When packet dropout occurs, the actuator utilizes past control packets to generate an appropriate control signal. The effectiveness of the approach is demonstrated through examples.

Collective dynamics and control of a 3-D small-world network with time delays

The paper presents a detailed analysis on the collective dynamics and delayed state feedback control of a three-dimensional delayed small-world network. The trivial equilibrium of the model is first investigated, showing that the uncontrolled model exhibits complicated unbounded behavior. Then three control strategies, namely a position feedback control, a velocity feedback control, and a hybrid control combined velocity with acceleration feedback, are then introduced to stabilize this unstable system. It is shown in these three control schemes that only the hybrid control can easily stabilize the 3-D network system. And with properly chosen delay and gain in the delayed feedback path, the hybrid controlled model may have stable equilibrium, or periodic solutions resulting from the Hopf bifurcation, or complex stranger attractor from the period-doubling bifurcation. Moreover, the direction of Hopf bifurcation and stability of the bifurcation periodic solutions are analyzed. The results are further extended to any "d" dimensional network. It shows that to stabilize a "d" dimensional delayed small-world network, at least a "d – 1" order completed differential feedback is needed. This work provides a constructive suggestion for the high dimensional delayed systems.

Fractal and complex network analyses of protein molecular dynamics

Based on protein molecular dynamics, we investigate the fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuation analysis (MF-DFA) and the topological and fractal properties of their converted horizontal visibility graphs (HVGs). The energy parameters of protein dynamics we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. The shape of the h(q)h(q) curves from MF-DFA indicates that these time series are multifractal. The numerical values of the exponent h(2)h(2) of MF-DFA show that the series of total energy and potential energy are non-stationary and anti-persistent; the other time series are stationary and persistent apart from series of pressure (with H≈0.5H≈0.5 indicating the absence of long-range correlation). The degree distributions of their converted HVGs show that these networks are exponential. The results of fractal analysis show that fractality exists in these converted HVGs. For each energy, pressure or volume parameter, it is found that the values of h(2)h(2) of MF-DFA on the time series, exponent λλ of the exponential degree distribution and fractal dimension dBdB of their converted HVGs do not change much for different proteins (indicating some universality). We also found that after taking average over all proteins, there is a linear relationship between 〈h(2)〉〈h(2)〉 (from MF-DFA on time series) and 〈dB〉〈dB〉 of the converted HVGs for different energy, pressure and volume.

Using complex network metrics to predict the persistence of metapopulations with asymmetric connectivity patterns

Almost all metapopulation modelling assumes that connectivity between patches is only a function of distance, and is therefore symmetric. However, connectivity will not depend only on the distance between the patches, as some paths are easy to traverse, while others are difficult. When colonising organisms interact with the heterogeneous landscape between patches, connectivity patterns will invariably be asymmetric. There have been few attempts to theoretically assess the effects of asymmetric connectivity patterns on the dynamics of metapopulations. In this paper, we use the framework of complex networks to investigate whether metapopulation dynamics can be determined by directly analysing the asymmetric connectivity patterns that link the patches. Our analyses focus on “patch occupancy” metapopulation models, which only consider whether a patch is occupied or not. We propose three easily calculated network metrics: the “asymmetry” and “average path strength” of the connectivity pattern, and the “centrality” of each patch. Together, these metrics can be used to predict the length of time a metapopulation is expected to persist, and the relative contribution of each patch to a metapopulation’s viability. Our results clearly demonstrate the negative effect that asymmetry has on metapopulation persistence. Complex network analyses represent a useful new tool for understanding the dynamics of species existing in fragmented landscapes, particularly those existing in large metapopulations.

User-representative feature selection for keystroke dynamics

Continuous user authentication with keystroke dynamics uses characters sequences as features. Since users can type characters in any order, it is imperative to find character sequences (n-graphs) that are representative of user typing behavior. The contemporary feature selection approaches do not guarantee selecting frequently-typed features which may cause less accurate statistical user-representation. Furthermore, the selected features do not inherently reflect user typing behavior. We propose four statistical based feature selection techniques that mitigate limitations of existing approaches. The first technique selects the most frequently occurring features. The other three consider different user typing behaviors by selecting: n-graphs that are typed quickly; n-graphs that are typed with consistent time; and n-graphs that have large time variance among users. We use Gunetti’s keystroke dataset and k-means clustering algorithm for our experiments. The results show that among the proposed techniques, the most-frequent feature selection technique can effectively find user representative features. We further substantiate our results by comparing the most-frequent feature selection technique with three existing approaches (popular Italian words, common n-graphs, and least frequent ngraphs). We find that it performs better than the existing approaches after selecting a certain number of most-frequent n-graphs.

Investigating the dynamics of the psychological contract : how and why individuals' contract beliefs change

The overall objective of this thesis is to explore how and why the content of individuals' psychological contracts changes over time. The contract is generally understood as "individual beliefs, shaped by the organisation, regarding the terms of an exchange agreement between individuals and their organisation" (Rousseau, 1995, p. 9). With an overall study sampling frame of 320 graduate organisational newcomers, a mixed method longitudinal research design comprised of three sequential, inter-related studies is employed in order to capture the change process. From the 15 semi-structured interviews conducted in Study 1, the key findings included identifying a relatively high degree of mutuality between employees' and their managers' reciprocal contract beliefs around the time of organisational entry. Also, at this time, individuals had developed specific components of their contract content through a mix of social network information (regarding broader employment expectations) and perceptions of various elements of their particular organisation's reputation (for more firm-specific expectations). Study 2 utilised a four-wave survey approach (available to the full sampling frame) over the 14 months following organisational entry to explore the 'shape' of individuals' contract change trajectories and the role of four theorised change predictors in driving these trajectories. The predictors represented an organisational-level informational cue (perceptions of corporate reputation), a dyadic-level informational cue (perceptions of manager-employee relationship quality) and two individual difference variables (affect and hardiness). Through the use of individual growth modelling, the findings showed differences in the general change patterns across contract content components of perceived employer (exhibiting generally quadratic change patterns) and employee (exhibiting generally no-change patterns) obligations. Further, individuals differentially used the predictor variables to construct beliefs about specific contract content. While both organisational- and dyadic-level cues were focused upon to construct employer obligation beliefs, organisational-level cues and individual difference variables were focused upon to construct employee obligation beliefs. Through undertaking 26 semi-structured interviews, Study 3 focused upon gaining a richer understanding of why participants' contracts changed, or otherwise, over the study period, with a particular focus upon the roles of breach and violation. Breach refers to an employee's perception that an employer obligation has not been met and violation refers to the negative and affective employee reactions which may ensue following a breach. The main contribution of these findings was identifying that subsequent to a breach or violation event a range of 'remediation effects' could be activated by employees which, depending upon their effectiveness, served to instigate either breach or contract repair or both. These effects mostly instigated broader contract repair and were generally cognitive strategies enacted by an individual to re-evaluate the breach situation and re-focus upon other positive aspects of the employment relationship. As such, the findings offered new evidence for a clear distinction between remedial effects which serve to only repair the breach (and thus the contract) and effects which only repair the contract more broadly; however, when effective, both resulted in individuals again viewing their employment relationships positively. Overall, in response to the overarching research question of this thesis, how and why individuals' psychological contract beliefs change, individuals do indeed draw upon various information sources, particularly at the organisational-level, as cues or guides in shaping their contract content. Further, the 'shapes' of the changes in beliefs about employer and employee obligations generally follow different, and not necessarily linear, trajectories over time. Finally, both breach and violation and also remedial actions, which address these occurrences either by remedying the breach itself (and thus the contract) or the contract only, play central roles in guiding individuals' contract changes to greater or lesser degrees. The findings from the thesis provide both academics and practitioners with greater insights into how employees construct their contract beliefs over time, the salient informational cues used to do this and how the effects of breach and violation can be mitigated through creating an environment which facilitates the use of effective remediation strategies.

Langevin dynamics modeling of the water diffusion tensor in partially aligned collagen networks

In this work, a Langevin dynamics model of the diffusion of water in articular cartilage was developed. Numerical simulations of the translational dynamics of water molecules and their interaction with collagen fibers were used to study the quantitative relationship between the organization of the collagen fiber network and the diffusion tensor of water in model cartilage. Langevin dynamics was used to simulate water diffusion in both ordered and partially disordered cartilage models. In addition, an analytical approach was developed to estimate the diffusion tensor for a network comprising a given distribution of fiber orientations. The key findings are that (1) an approximately linear relationship was observed between collagen volume fraction and the fractional anisotropy of the diffusion tensor in fiber networks of a given degree of alignment, (2) for any given fiber volume fraction, fractional anisotropy follows a fiber alignment dependency similar to the square of the second Legendre polynomial of cos(θ), with the minimum anisotropy occurring at approximately the magic angle (θMA), and (3) a decrease in the principal eigenvalue and an increase in the transverse eigenvalues is observed as the fiber orientation angle θ progresses from 0◦ to 90◦. The corresponding diffusion ellipsoids are prolate for θ < θMA, spherical for θ ≈ θMA, and oblate for θ > θMA. Expansion of the model to include discrimination between the combined effects of alignment disorder and collagen fiber volume fraction on the diffusion tensor is discussed.

Mapping the dynamics of the project management field : project management in action (part 6)

This is the sixth part of a Letter from the Editor series where the results are presented of an ongoing research undertaken in order to investigate the dynamic of the evolution of the field of project management and the key trends. Dynamics of networks is a key feature in strategic diagrams analysis. The radical change in the configuration of a network between two periods, or the change at subnetwork level reflects the dynamic of science. I present here an example of subnetwork comparison over the four periods of time considered in this study. I will develop and discuss an example of subnetwork transformation in future Letter from the Editor article..

From homepages to network profiles : balancing personal and social identity

The World Wide Web constitutes one of the most important inventions of the late 20th century: it has changed culture, society, business, communication, politics, and many other fields of human endeavour, not least also by providing a more user-friendly pathway of access to its major underlying technology, the Internet itself. Key phases in its development can be charted, especially by how it has been used to present and share information – and here, the personal or professional, private or official homepage stands in as a useful representation of wider Web trends overall. From hand-coded beginnings through several successive stages of experimentation and standardisation, to the shifting balance between personal sites and social networks, the homepage demonstrates how the Web itself, and its place in our lives, have changed.

A neural-network based flight controller for UASs

This paper presents a nonlinear gust-attenuation controller based on constrained neural-network (NN) theory. The controller aims to achieve sufficient stability and handling quality for a fixed-wing unmanned aerial system (UAS) in a gusty environment when control inputs are subjected to constraints. Constraints in inputs emulate situations where aircraft actuators fail requiring the aircraft to be operated with fail-safe capability. The proposed controller enables gust-attenuation property and stabilizes the aircraft dynamics in a gusty environment. The proposed flight controller is obtained by solving the Hamilton-Jacobi-Isaacs (HJI) equations based on an policy iteration (PI) approach. Performance of the controller is evaluated using a high-fidelity six degree-of-freedom Shadow UAS model. Simulations show that our controller demonstrates great performance improvement in a gusty environment, especially in angle-of-attack (AOA), pitch and pitch rate. Comparative studies are conducted with the proportional-integral-derivative (PID) controllers, justifying the efficiency of our controller and verifying its suitability for integration into the design of flight control systems for forced landing of UASs.

Measuring global economic interdependence : a hierarchical network approach

This paper investigates the business cycle co-movement across countries and regions since 1950 as a measure for quantifying the economic interdependence in the ongoing globalisation process. Our methodological approach is based on analysis of a correlation matrix and the networks it contains. Such an approach summarises the interaction and interdependence of all elements, and it represents a more accurate measure of the global interdependence involved in an economic system. Our results show (1) the dynamics of interdependence has been driven more by synchronisation in regional growth patterns than by the synchronisation of the world economy, and (2) world crisis periods dramatically increase the global co-movement in the world economy.

Visualization : A powerful tool for effective teaching of dynamics

Dynamics is an essential core engineering subject and it is considered as one of the hardest subjects in the engineering discipline. Many students acknowledged that Dynamics is very hard to understand and comprehend the abstract concepts through traditional teaching methods with normal tutorials and assignments. In this study, we conducted an investigation on the application of visualization technique to help students learning the unit with the fundamental theory displayed in the physical space. The research was conducted based on the following five basic steps of Action Learning Cycle including: Identifying problem, Planning action, Implementing, Evaluating, and Reporting. Through our studies, we have concluded that visualization technique can definitely help students in learning and comprehending the abstract theories and concepts of Dynamics.