34,872 research outputs found
Towards a framework for investigating tangible environments for learning
External representations have been shown to play a key role in mediating cognition. Tangible environments offer the opportunity for novel representational formats and combinations, potentially increasing representational power for supporting learning. However, we currently know little about the specific learning benefits of tangible environments, and have no established framework within which to analyse the ways that external representations work in tangible environments to support learning. Taking external representation as the central focus, this paper proposes a framework for investigating the effect of tangible technologies on interaction and cognition. Key artefact-action-representation relationships are identified, and classified to form a structure for investigating the differential cognitive effects of these features. An example scenario from our current research is presented to illustrate how the framework can be used as a method for investigating the effectiveness of differential designs for supporting science learning
Model the System from Adversary Viewpoint: Threats Identification and Modeling
Security attacks are hard to understand, often expressed with unfriendly and
limited details, making it difficult for security experts and for security
analysts to create intelligible security specifications. For instance, to
explain Why (attack objective), What (i.e., system assets, goals, etc.), and
How (attack method), adversary achieved his attack goals. We introduce in this
paper a security attack meta-model for our SysML-Sec framework, developed to
improve the threat identification and modeling through the explicit
representation of security concerns with knowledge representation techniques.
Our proposed meta-model enables the specification of these concerns through
ontological concepts which define the semantics of the security artifacts and
introduced using SysML-Sec diagrams. This meta-model also enables representing
the relationships that tie several such concepts together. This representation
is then used for reasoning about the knowledge introduced by system designers
as well as security experts through the graphical environment of the SysML-Sec
framework.Comment: In Proceedings AIDP 2014, arXiv:1410.322
The use of non-intrusive user logging to capture engineering rationale, knowledge and intent during the product life cycle
Within the context of Life Cycle Engineering it is important that structured engineering information and knowledge are captured at all phases of the product life cycle for future reference. This is especially the case for long life cycle projects which see a large number of engineering decisions made at the early to mid-stages of a product's life cycle that are needed to inform engineering decisions later on in the process. A key aspect of technology management will be the capturing of knowledge through out the product life cycle. Numerous attempts have been made to apply knowledge capture techniques to formalise engineering decision rationale and processes; however, these tend to be associated with substantial overheads on the engineer and the company through cognitive process interruptions and additional costs/time. Indeed, when life cycle deadlines come closer these capturing techniques are abandoned due the need to produce a final solution. This paper describes work carried out for non-intrusively capturing and formalising product life cycle knowledge by demonstrating the automated capture of engineering processes/rationale using user logging via an immersive virtual reality system for cable harness design and assembly planning. Associated post-experimental analyses are described which demonstrate the formalisation of structured design processes and decision representations in the form of IDEF diagrams and structured engineering change information. Potential future research directions involving more thorough logging of users are also outlined
A Product Line Systems Engineering Process for Variability Identification and Reduction
Software Product Line Engineering has attracted attention in the last two
decades due to its promising capabilities to reduce costs and time to market
through reuse of requirements and components. In practice, developing system
level product lines in a large-scale company is not an easy task as there may
be thousands of variants and multiple disciplines involved. The manual reuse of
legacy system models at domain engineering to build reusable system libraries
and configurations of variants to derive target products can be infeasible. To
tackle this challenge, a Product Line Systems Engineering process is proposed.
Specifically, the process extends research in the System Orthogonal Variability
Model to support hierarchical variability modeling with formal definitions;
utilizes Systems Engineering concepts and legacy system models to build the
hierarchy for the variability model and to identify essential relations between
variants; and finally, analyzes the identified relations to reduce the number
of variation points. The process, which is automated by computational
algorithms, is demonstrated through an illustrative example on generalized
Rolls-Royce aircraft engine control systems. To evaluate the effectiveness of
the process in the reduction of variation points, it is further applied to case
studies in different engineering domains at different levels of complexity.
Subject to system model availability, reduction of 14% to 40% in the number of
variation points are demonstrated in the case studies.Comment: 12 pages, 6 figures, 2 tables; submitted to the IEEE Systems Journal
on 3rd June 201
Verifying service continuity in a satellite reconfiguration procedure: application to a satellite
The paper discusses the use of the TURTLE UML profile to model and verify service continuity during dynamic reconfiguration of embedded software, and space-based telecommunication software in particular. TURTLE extends UML class diagrams with composition operators, and activity diagrams with temporal operators. Translating TURTLE to the formal description technique RT-LOTOS gives the profile a formal semantics and makes it possible to reuse verification techniques implemented by the RTL, the RT-LOTOS toolkit developed at LAAS-CNRS. The paper proposes a modeling and formal validation methodology based on TURTLE and RTL, and discusses its application to a payload software application in charge of an embedded packet switch. The paper demonstrates the benefits of using TURTLE to prove service continuity for dynamic reconfiguration of embedded software
Modelling learning behaviour of intelligent agents using UML 2.0
This thesis aims to explore and demonstrate the ability of the new standard of
structural and behavioural components in Unified Modelling Language (UML 2.0 / 2004)
to model the learning behaviour of Intelligent Agents. The thesis adopts the research
direction that views agent-oriented systems as an extension to object-oriented systems. In
view of the fact that UML has been the de facto standard for modelling object-oriented
systems, this thesis concentrates on exploring such modelling potential with Intelligent
Agent-oriented systems. Intelligent Agents are Agents that have the capability to learn and
reach agreement with other Agents or users. The research focuses on modelling the
learning behaviour of a single Intelligent Agent, as it is the core of multi-agent systems.
During the writing of the thesis, the only work done to use UML 2.0 to model
structural components of Agents was from the Foundation for Intelligent Physical Agent
(FIPA). The research builds upon, explores, and utilises this work and provides further
development to model the structural components of learning behaviour of Intelligent
Agents. The research also shows the ability of UML version 2.0 behaviour diagrams,
namely activity diagrams and sequence diagrams, to model the learning behaviour of
Intelligent Agents that use learning from observation and discovery as well as learning
from examples of strategies. The research also evaluates if UML 2.0 state machine
diagrams can model specific reinforcement learning algorithms, namely dynamic
programming, Monte Carlo, and temporal difference algorithms. The thesis includes user
guides of UML 2.0 activity, sequence, and state machine diagrams to allow researchers in
agent-oriented systems to use the UML 2.0 diagrams in modelling the learning components
of Intelligent Agents.
The capacity for learning is a crucial feature of Intelligent Agents. The research
identifies different learning components required to model the learning behaviour of
Intelligent Agents such as learning goals, learning strategies, and learning feedback
methods. In recent years, the Agent-oriented research has been geared towards the agency
dimension of Intelligent Agents. Thus, there is a need to conduct more research on the
intelligence dimension of Intelligent Agents, such as negotiation and argumentation skills.
The research shows that behavioural components of UML 2.0 are capable of
modelling the learning behaviour of Intelligent Agents while structural components of
UML 2.0 need extension to cover structural requirements of Agents and Intelligent Agents.
UML 2.0 has an extension mechanism to fulfil Agents and Intelligent Agents for such
requirements. This thesis will lead to increasing interest in the intelligence dimension
rather than the agency dimension of Intelligent Agents, and pave the way for objectoriented
methodologies to shift more easily to paradigms of Intelligent Agent-oriented
systems.The British
Council, the University of Plymouth and the Arab-British Chamber Charitable Foundation
Evolving information systems: meeting the ever-changing environment
To meet the demands of organizations and their ever-changing environment, information systems are required which are able to evolve to the same extent as organizations do. Such a system has to support changes in all time-and application-dependent aspects. In this paper, requirements and a conceptual framework for evolving information systems are presented. This framework includes an architecture for such systems and a revision of the traditional notion of update. Based on this evolutionary notion of update (recording, correction and forgetting) a state transition-oriented model on three levels of abstraction (event level, recording level, correction level) is introduced. Examples are provided to illustrate the conceptual framework for evolving information systems
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