3,514 research outputs found
Multiple hierarchies : new aspects of an old solution
In this paper, we present the Multiple Annotation approach, which solves two problems: the problem of annotating overlapping structures, and the problem that occurs when documents should be annotated according to different, possibly heterogeneous tag sets. This approach has many advantages: it is based on XML, the modeling of alternative annotations is possible, each level can be viewed separately, and new levels can be added at any time. The files can be regarded as an interrelated unit, with the text serving as the implicit link. Two representations of the information contained in the multiple files (one in Prolog and one in XML) are described. These representations serve as a base for several applications
A Framework for Evaluating Model-Driven Self-adaptive Software Systems
In the last few years, Model Driven Development (MDD), Component-based
Software Development (CBSD), and context-oriented software have become
interesting alternatives for the design and construction of self-adaptive
software systems. In general, the ultimate goal of these technologies is to be
able to reduce development costs and effort, while improving the modularity,
flexibility, adaptability, and reliability of software systems. An analysis of
these technologies shows them all to include the principle of the separation of
concerns, and their further integration is a key factor to obtaining
high-quality and self-adaptable software systems. Each technology identifies
different concerns and deals with them separately in order to specify the
design of the self-adaptive applications, and, at the same time, support
software with adaptability and context-awareness. This research studies the
development methodologies that employ the principles of model-driven
development in building self-adaptive software systems. To this aim, this
article proposes an evaluation framework for analysing and evaluating the
features of model-driven approaches and their ability to support software with
self-adaptability and dependability in highly dynamic contextual environment.
Such evaluation framework can facilitate the software developers on selecting a
development methodology that suits their software requirements and reduces the
development effort of building self-adaptive software systems. This study
highlights the major drawbacks of the propped model-driven approaches in the
related works, and emphasise on considering the volatile aspects of
self-adaptive software in the analysis, design and implementation phases of the
development methodologies. In addition, we argue that the development
methodologies should leave the selection of modelling languages and modelling
tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition,
self-adaptive application, context oriented software developmen
Microsimulation - A Survey of Methods and Applications for Analyzing Economic and Social Policy
This essential dimensions of microsimulation as an instrument to analyze and forecast the individual impacts of alternative economic and social policy measures are surveyed in this study. The basic principles of microsimulation, which is a tool for practical policy advising as well as for research and teaching, are pointed out and the static and dynamic (cross-section and life-cycle) approaches are compared to one another. Present and past developments of microsimulation models and their areas of application are reviewed, focusing on the US, Europe and Australia. Based on general requirements and components of microsimulation models a microsimulation model's actual working mechanism are discussed by a concrete example: the concept and realization of MICSIM, a PC microsimulation model based on a relational database system, an offspring of the Sfb 3 Statitic Microsimulation Model. Common issues of microsimulation modeling are regarded: micro/macro link, behavioural response and the important question of evaluating microsimulation results. The concluding remarks accentuate the increasing use of microcomputers for microsimulation models also for teaching purposes.Microsimulation, Microanalytic Simulation Models, Microanalysis, Economic and Social Policy Analysis
Welding process modelling and control
The research and analysis performed, and software developed, and hardware/software recommendations made during 1992 in development of the PC-based data acquisition system for support of Welding Process Modeling and Control is reported. A need was identified by the Metals Processing Branch of NASA Marshall Space Flight Center, for a mobile data aquisition and analysis system, customized for welding measurement and calibration. Several hardware configurations were evaluated and a PC-based system was chosen. The Welding Measurement System (WMS) is a dedicated instrument, strictly for the use of data aquisition and analysis. Although the WMS supports many of the functions associated with the process control, it is not the intention for this system to be used for welding process control
AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments
This report considers the application of Articial Intelligence (AI) techniques to
the problem of misuse detection and misuse localisation within telecommunications
environments. A broad survey of techniques is provided, that covers inter alia
rule based systems, model-based systems, case based reasoning, pattern matching,
clustering and feature extraction, articial neural networks, genetic algorithms, arti
cial immune systems, agent based systems, data mining and a variety of hybrid
approaches. The report then considers the central issue of event correlation, that
is at the heart of many misuse detection and localisation systems. The notion of
being able to infer misuse by the correlation of individual temporally distributed
events within a multiple data stream environment is explored, and a range of techniques,
covering model based approaches, `programmed' AI and machine learning
paradigms. It is found that, in general, correlation is best achieved via rule based approaches,
but that these suffer from a number of drawbacks, such as the difculty of
developing and maintaining an appropriate knowledge base, and the lack of ability
to generalise from known misuses to new unseen misuses. Two distinct approaches
are evident. One attempts to encode knowledge of known misuses, typically within
rules, and use this to screen events. This approach cannot generally detect misuses
for which it has not been programmed, i.e. it is prone to issuing false negatives.
The other attempts to `learn' the features of event patterns that constitute normal
behaviour, and, by observing patterns that do not match expected behaviour, detect
when a misuse has occurred. This approach is prone to issuing false positives,
i.e. inferring misuse from innocent patterns of behaviour that the system was not
trained to recognise. Contemporary approaches are seen to favour hybridisation,
often combining detection or localisation mechanisms for both abnormal and normal
behaviour, the former to capture known cases of misuse, the latter to capture
unknown cases. In some systems, these mechanisms even work together to update
each other to increase detection rates and lower false positive rates. It is concluded
that hybridisation offers the most promising future direction, but that a rule or state
based component is likely to remain, being the most natural approach to the correlation
of complex events. The challenge, then, is to mitigate the weaknesses of
canonical programmed systems such that learning, generalisation and adaptation
are more readily facilitated
Unit & Dynamic Typing in Hybrid Systems Modeling with CHARON
In scientific applications, dimensional analysis forms a basis for catching errors as it introduces a type-discipline into the equations and formulae. Dimensions in physical quantities are measured via their standard units. However, many programming and modeling tools provide limited support for incorporating these units into the variables. Thus, it is quite difficult for a programmer to ensure dimensional consistency in the code. Different existing standards for units further complicates this problem and an incautious use could cause inconsistencies, often with catastrophic results.
In this paper, we propose an extension of the basic type system in CHARON, a language for modeling of hybrid systems, to include Unit and Dynamic data types. Through a combination of indirect user-guided annotations and typeinference, we address the problem of ensuring both dimensional consistency, and consistency with respect to different unitsystems. Further, we also introduce dynamic data typing, that allows programmers to specify entities that bind at runtime. Such abstractions are particularly useful to program controllers for dynamic environments. We illustrate these benefits with an example on mobile robots
The design and implementation of a smart-parking system for Helsinki Area
The strain on the parking infrastructure for the general public has significantly grown as a result of the ever rising number of vehicles geared by the rapid population growth in urban areas. Consequently, finding a vacant parking space has become quite a challenging task, especially at peak hours. Drivers have to cycle back and forth a number of times before they finally find where to park. This leads to increased fuel consumption, air pollution, and increased likelihood of causing accidents, to mention but a few. Paying for the parking is not straight forward either, as the ticket machines, on top of being located at a distance, in many times, they have several payment methods drivers must prepare for. A system therefore, that would allow drivers to check for the vacant parking places before driving to a busy city, takes care of the parking fee for exact time they have used, manages electronic parking permit, is the right direction towards toppling these difficulties.
The main objective of this project was to design and implement a system that would provide parking occupancy estimation, parking fee payment method, parking permit management and parking analytics for the city authorities. The project had three phases. The first and the second phases used qualitative approaches to validate our hypotheses about parking shortcoming in Helsinki area and the recruitment of participants to the pilot of the project, respectively. The third phase involved the design, implementation and installation of the system. The other objective was to study the challenges a smart parking system would face at different stages of its life cycle.
The objectives of the project were achieved and the considered assumption about the challenges associated with parking in a busy city were validated. A smart parking system will allow drivers to check for available parking spaces beforehand, they are able to pay for the parking fee, they can get electronic parking permits, and the city authority can get parking analytics for the city plannin
Bayesian variable selection and data integration for biological regulatory networks
A substantial focus of research in molecular biology are gene regulatory
networks: the set of transcription factors and target genes which control the
involvement of different biological processes in living cells. Previous
statistical approaches for identifying gene regulatory networks have used gene
expression data, ChIP binding data or promoter sequence data, but each of these
resources provides only partial information. We present a Bayesian hierarchical
model that integrates all three data types in a principled variable selection
framework. The gene expression data are modeled as a function of the unknown
gene regulatory network which has an informed prior distribution based upon
both ChIP binding and promoter sequence data. We also present a variable
weighting methodology for the principled balancing of multiple sources of prior
information. We apply our procedure to the discovery of gene regulatory
relationships in Saccharomyces cerevisiae (Yeast) for which we can use several
external sources of information to validate our results. Our inferred
relationships show greater biological relevance on the external validation
measures than previous data integration methods. Our model also estimates
synergistic and antagonistic interactions between transcription factors, many
of which are validated by previous studies. We also evaluate the results from
our procedure for the weighting for multiple sources of prior information.
Finally, we discuss our methodology in the context of previous approaches to
data integration and Bayesian variable selection.Comment: Published in at http://dx.doi.org/10.1214/07-AOAS130 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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