Modeling social information skills

In a modern economy, the most important resource consists in\ud human talent: competent, knowledgeable people. Locating the right person for\ud the task is often a prerequisite to complex problem-solving, and experienced\ud professionals possess the social skills required to find appropriate human\ud expertise. These skills can be reproduced more and more with specific\ud computer software, an approach defining the new field of social information\ud retrieval. We will analyze the social skills involved and show how to model\ud them on computer. Current methods will be described, notably information\ud retrieval techniques and social network theory. A generic architecture and its\ud functions will be outlined and compared with recent work. We will try in this\ud way to estimate the perspectives of this recent domain

Research methods and methodologies for studying organisational learning

The purpose of this paper is to compare and evaluate the main research methods and methodologies for studying organisational learning (OL), and propose a framework for their selection. It presents a comprehensive review of literature on OL, learning organisation (LO) and research methods and reports evidence on recent developments in research methods for studying OL. The paper highlighted on the purists and pragmatists’ views of research methodologies as basis of the study. The results revealed that the research methods and methodologies for studying OL do not reflect on the differing views of the purists and pragmatists’ debate but rather conform to the convergence ideologies of the two camps. Particularly, the outcomes augment the use of triangulation and suggest that the choice of method(s) should be consistent with research aims and epistemological philosophy of OL. Consequently, the study recommends OL Research Methods Framework as a useful guide for selecting a suitable approach in the area. The paper recommends ethnography for future research consideration

ETHICAL LEADERSHIP IN HIGHER EDUCATION: EVOLUTION OF INSTITUTIONAL ETHICS LOGIC

In higher education, we face a decade in which institutional integrity and legitimacy is under fire. In the words of Charles Dickens, this is certainly \u27the worst of times\u27 both economically and ethically for our nation, as well as for our colleges and universities. While members of higher education call for student academic ethics reform, ethical infractions by institutional leaders and faculty permeate professional literature and news--student loan scandals, charges of plagiarism, and falsified research, are but a few. This study begins with the premise that perhaps our efforts toward reform should focus on a better holistic understanding of system dynamics. The research question driving this study is, \u27How does the interaction of agent work-related ethical beliefs and knowledge, perceived pressures, and institutional agents or entities influence the evolution of institutional ethics logic over time?\u27 Grounded theory methods provided the framework for this study; this research used a complexity leadership and network lens in which to examine a university\u27s ethics logic, as defined by participants. Complexity leadership proposes operating within a framework of mechanism-based theorizing (Uhl-Bien & Marion, in press). The Organizational Risk Analyzer (ORA) assisted coding and analysis of data, and DyNet, a modeling platform, assisted in manipulating data for an understanding of interrelated complexity mechanisms embedded in university ethics logic. Findings incorporate a faculty ethics logic model, as well as a model of dynamical processes of university ethics logic evolution. The evolution model recognizes that: * The leadership process shifts by leader function, context, or structure. * The process underlying network robustness reflects holistic shifts in relationships with the addition or removal of nodes and links, and represents different or new patterns of behavior * The process of agentic correlation shifts as nodal presence or relationships change * The process of information diffusion shifts as network context, structure, or content changes Theoretical, methodological, higher education implications conclude the study

Tree-formed Verification Data for Trusted Platforms

The establishment of trust relationships to a computing platform relies on validation processes. Validation allows an external entity to build trust in the expected behaviour of the platform based on provided evidence of the platform's configuration. In a process like remote attestation, the 'trusted' platform submits verification data created during a start up process. These data consist of hardware-protected values of platform configuration registers, containing nested measurement values, e.g., hash values, of loaded or started components. Commonly, the register values are created in linear order by a hardware-secured operation. Fine-grained diagnosis of components, based on the linear order of verification data and associated measurement logs, is not optimal. We propose a method to use tree-formed verification data to validate a platform. Component measurement values represent leaves, and protected registers represent roots of a hash tree. We describe the basic mechanism of validating a platform using tree-formed measurement logs and root registers and show an logarithmic speed-up for the search of faults. Secure creation of a tree is possible using a limited number of hardware-protected registers and a single protected operation. In this way, the security of tree-formed verification data is maintained.Comment: 15 pages, 11 figures, v3: Reference added, v4: Revised, accepted for publication in Computers and Securit

Agoric computation: trust and cyber-physical systems

In the past two decades advances in miniaturisation and economies of scale have led to the emergence of billions of connected components that have provided both a spur and a blueprint for the development of smart products acting in specialised environments which are uniquely identifiable, localisable, and capable of autonomy. Adopting the computational perspective of multi-agent systems (MAS) as a technological abstraction married with the engineering perspective of cyber-physical systems (CPS) has provided fertile ground for designing, developing and deploying software applications in smart automated context such as manufacturing, power grids, avionics, healthcare and logistics, capable of being decentralised, intelligent, reconfigurable, modular, flexible, robust, adaptive and responsive. Current agent technologies are, however, ill suited for information-based environments, making it difficult to formalise and implement multiagent systems based on inherently dynamical functional concepts such as trust and reliability, which present special challenges when scaling from small to large systems of agents. To overcome such challenges, it is useful to adopt a unified approach which we term agoric computation, integrating logical, mathematical and programming concepts towards the development of agent-based solutions based on recursive, compositional principles, where smaller systems feed via directed information flows into larger hierarchical systems that define their global environment. Considering information as an integral part of the environment naturally defines a web of operations where components of a systems are wired in some way and each set of inputs and outputs are allowed to carry some value. These operations are stateless abstractions and procedures that act on some stateful cells that cumulate partial information, and it is possible to compose such abstractions into higher-level ones, using a publish-and-subscribe interaction model that keeps track of update messages between abstractions and values in the data. In this thesis we review the logical and mathematical basis of such abstractions and take steps towards the software implementation of agoric modelling as a framework for simulation and verification of the reliability of increasingly complex systems, and report on experimental results related to a few select applications, such as stigmergic interaction in mobile robotics, integrating raw data into agent perceptions, trust and trustworthiness in orchestrated open systems, computing the epistemic cost of trust when reasoning in networks of agents seeded with contradictory information, and trust models for distributed ledgers in the Internet of Things (IoT); and provide a roadmap for future developments of our research

Personality Expression in Body Motion Dynamics:Enactive, Embodied and Complex Systems Perspectives

We explored personality expression through body motion using enactive/complex systems perspectives. We invited 105 adults (aged 18-33, 70% women) to talk for 15-minutes about three self-referencing topics (introduction, bodily perception/sensory life, socio-emotional life). A video frame-by-frame differentiation method provided time-series to perform Recurrence Quantification Analysis (RQA), extracting four measures (Determinism/Entropy/Laminarity/MeanLine). Multilevel models linked Big-Five traits (IPIP-NEO-120) to embodied dynamics. Neuroticism predicted lower determinism and fluctuating dynamics when talking about bodily perception/sensory life and socioemotional life; less complexity and stability when talking about socioemotional life, and post-task negative affect. Extraversion predicted regular/deterministic dynamics when talking about bodily perception/sensory life. Conscientiousness predicted less deterministic and more variability. Agreeableness predicted low post-task negative affect. The results are discussed integrating enactive/complexity, and personality perspectives