Combinatorial Design of Secure Lightweight Data Dispersal Schemes (Work in Progress)

Dispersing a data object into a set of data shares is an elemental stage in distributed communication and storage systems. In comparison to data replication, data dispersal with redundancy saves space and bandwidth. Moreover, dispersing a data object to distinct communication links or storage sites limits adversarial access to whole data and tolerates loss of a part of data shares. Existing data dispersal schemes have been proposed mostly based on various mathematical transformations on the data which induce high computation overhead. This paper presents a novel data dispersal scheme where each part of a data object is replicated, without encoding, into a subset of data shares according to combinatorial design theory. Particularly, data parts are mapped to points and data shares are mapped to lines of a projective plane. Data parts are then distributed to data shares using the point and line incidence relations in the plane so that certain subsets of data shares collectively possess all data parts. The presented scheme incorporates combinatorial design theory with inseparability transformation to achieve secure data dispersal at reduced computation, communication and storage costs. Rigorous formal analysis and experimental study demonstrate significant cost-benefits of the presented scheme in comparison to existing methods.

Three-User Cognitive Channels with Cumulative Message Sharing: An Achievable Rate Region

In this paper, an achievable rate region for the three-user discrete memoryless interference channel with asymmetric transmitter cooperation is derived. The three-user channel facilitates different ways of message sharing between the transmitters. We introduce a manner of noncausal (genie aided) unidirectional message-sharing, which we term cumulative message sharing. We consider receivers with predetermined decoding capabilities, and define a cognitive interference channel. We then derive an achievable rate region for this channel by employing a coding scheme which is a combination of superposition and Gel'fand-Pinsker coding techniques.

Is it tweet-worthy? Privacy in a time of sharing.

Information professionals and information organisations use Twitter in a variety of ways. Typically both organisations and the individuals that work for them have separate identities on Twitter, but often individuals identify their organization through their profile or Twitter content. This paper considers the way information professionals use Twitter and their practices with regard to privacy, personal disclosure and identifying their organisational affiliations. Drawing on data from a research study involving a questionnaire and social media observation, the paper will provoke discussion about information professionals’ use of Twitter, personal and organizational identity, and the value of Twitter for professional development. In keeping with the subject matter, a curated set of social media content will be available in lieu of a formal paper.

Conceptualising social media support for tacit knowledge sharing: physicians’ perspectives and experiences

Purpose – This paper aims to explore the potential contributions of social media in supporting tacit knowledge sharing, according to the physicians’ perspectives and experiences. Design/methodology/approach – Adopting a qualitative survey design, 24 physicians were interviewed. Purposive and snowball sampling were used to select the participants. Thematic analysis approach was used for data analysis. Findings – The study revealed five major themes and over 20 sub-themes as potential contributions of social media to tacit knowledge flow among physicians. The themes included socialising, practising, networking, storytelling and encountering. In addition, with the help of the literature and the supporting data, the study proposed a conceptual model that explains the potential contribution of social media to tacit knowledge sharing. Research limitations/implications – The study had both theoretical (the difficulty of distinguishing tacit and explicit knowledge in practice) and practical limitations (small sample size). The study findings have implications for the healthcare industry whose clinical teams are not always physically co-located but must exchange their critical experiential and tacit knowledge. Originality/value – The study has opened up a new discussion of this area by demonstrating and conceptualising how social media tools may facilitate tacit knowledge sharing.

Cost Sharing Mechanisms for Business Clusters with Strategic Firms

A business cluster is a co-located group of micro, small, medium scale enterprises. Such firms can benefit significantly from their co-location through shared infrastructure and shared services. Cost sharing becomes an important issue in such sharing arrangements especially when the firms exhibit strategic behavior. There are many cost sharing methods and mechanisms proposed in the literature based on game theoretic foundations. These mechanisms satisfy a variety of efficiency and fairness properties such as allocative efficiency, budget balance, individual rationality, consumer sovereignty, strategyproofness, and group strategyproofness. In this paper, we motivate the problem of cost sharing in a business cluster with strategic firms and illustrate different cost sharing mechanisms through the example of a cluster of firms sharing a logistics service. Next we look into the problem of a business cluster sharing ICT (information and communication technologies) infrastructure and explore the use of cost sharing mechanisms.

Deterministic schemes for key distribution in wireless sensor networks

In this paper, we propose a new security metric for measuring resilience of a symmetric key distribution scheme in wireless sensor network. A polynomial-based and a novel complete connectivity schemes are proposed and an analytical comparison, in terms of security and connectivity, between the schemes is shown. Motivated by the schemes, we derive general expressions for security and connectivity. A number of conclusions are made using these general expressions.

Cultures of sharing in 3D printing: What can we learn from the licence choices of Thingiverse users?

This article contributes to the discussion by analysing how users of the leading online 3D printing design repository Thingiverse manage their intellectual property (IP). 3D printing represents a fruitful case study for exploring the relationship between IP norms and practitioner culture. Although additive manufacturing technology has existed for decades, 3D printing is on the cusp of a breakout into the technological mainstream – hardware prices are falling; designs are circulating widely; consumer-friendly platforms are multiplying; and technological literacy is rising. Analysing metadata from more than 68,000 Thingiverse design files collected from the site, we examine the licensing choices made by users and explore the way this shapes the sharing practices of the site’s users. We also consider how these choices and practices connect with wider attitudes towards sharing and intellectual property in 3D printing communities. A particular focus of the article is how Thingiverse structures its regulatory framework to avoid IP liability, and the extent to which this may have a bearing on users’ conduct. The paper has three sections. First, we will offer a description of Thingiverse and how it operates in the 3D printing ecosystem, noting the legal issues that have arisen regarding Thingiverse’s Terms of Use and its allocation of intellectual property rights. Different types of Thingiverse licences will be detailed and explained. Second, the empirical metadata we have collected from Thingiverse will be presented, including the methods used to obtain this information. Third, we will present findings from this data on licence choice and the public availability of user designs. Fourth, we will look at the implications of these findings and our conclusions regarding the particular kind of sharing ethic that is present in Thingiverse; we also consider the “closed” aspects of this community and what this means for current debates about “open” innovation.

Regulating ride-sharing in the peer economy

This magazine article examines the challenges of digital disruption and the way the struggle for legitimacy is playing out in mainstream and social media. Using ride-sharing as a case study, our team at the QUT Digital media research centre seeks to develop the tools policy-makers need to make evidence-based policy decisions in response to digital disruption.

Paper 1: The disruptive forces of the sharing economy

Overview: - The sharing economy unlocks a previously unused value of goods and labour, and causes disruption in established industries. - The pattern of disruption is similar regardless of the industry that's impacted. While the initial phases of disruption are transformational for many (e.g. lost jobs), often the industries end up stronger than before they were before the disruption. - Due to different in setting, upholding and enforcing standards, it is hard to assess the regulatory trade-offs. Safety, labour relations and social fairness are important factors to consider across the industry.

Direct torque control schemes for split-phase induction machine

In this paper, direct torque control (DTC) algorithms for a split-phase induction machine (SPIM) are established. An SPIM has two sets of three-phase stator windings, with a shift of thirty electrical degrees between them. The significant contributions of this paper are: 1) two new methods of DTC technique for an SPIM are developed, called Resultant Flux Control Method and Individual Flux Control Method and 2) advantages and disadvantages of both methods are discussed. High torque ripple is a disadvantage for three-phase DTC. It is found that torque ripple in an SPIM can be significantly reduced without increasing the switching frequency.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

Social Media as a Form of Organizational Knowledge Sharing

This study investigates the role of social media as a form of organizational knowledge sharing. Social media is investigated in terms of the Web 2.0 technologies that organizations provide their employees as tools of internal communication. This study is anchored in the theoretical understanding of social media as technologies which enable both knowledge collection and knowledge donation. This study investigates the factors influencing employees’ use of social media in their working environment. The study presents the multidisciplinary research tradition concerning knowledge sharing. Social media is analyzed especially in relation to internal communication and knowledge sharing. Based on previous studies, it is assumed that personal, organizational, and technological factors influence employees’ use of social media in their working environment. The research represents a case study focusing on the employees of the Finnish company Wärtsilä. Wärtsilä represents an eligible case organization for this study given that it puts in use several Web 2.0 tools in its intranet. The research is based on quantitative methods. In total 343 answers were obtained with the aid of an online survey which was available in Wärtsilä’s intranet. The associations between the variables are analyzed with the aid of correlations. Finally, with the aid of multiple linear regression analysis the causality between the assumed factors and the use of social media is tested. The analysis demonstrates that personal, organizational and technological factors influence the respondents’ use of social media. As strong predictive variables emerge the benefits that respondents expect to receive from using social media and respondents’ experience in using Web 2.0 in their private lives. Also organizational factors such as managers’ and colleagues’ activeness and organizational guidelines for using social media form a causal relationship with the use of social media. In addition, respondents’ understanding of their responsibilities affects their use of social media. The more social media is considered as a part of individual responsibilities, the more frequently social media is used. Finally, technological factors must be recognized. The more user-friendly social media tools are considered and the better technical skills respondents have, the more frequently social media is used in the working environment. The central references in relation to knowledge sharing include Chun Wei Choo’s (2006) work Knowing Organization, Ikujiro Nonaka and Hirotaka Takeuchi’s (1995) work The Knowledge Creating Company and Linda Argote’s (1999) work Organizational Learning.