327,550 research outputs found
Transfer Learning for Improving Model Predictions in Highly Configurable Software
Modern software systems are built to be used in dynamic environments using
configuration capabilities to adapt to changes and external uncertainties. In a
self-adaptation context, we are often interested in reasoning about the
performance of the systems under different configurations. Usually, we learn a
black-box model based on real measurements to predict the performance of the
system given a specific configuration. However, as modern systems become more
complex, there are many configuration parameters that may interact and we end
up learning an exponentially large configuration space. Naturally, this does
not scale when relying on real measurements in the actual changing environment.
We propose a different solution: Instead of taking the measurements from the
real system, we learn the model using samples from other sources, such as
simulators that approximate performance of the real system at low cost. We
define a cost model that transform the traditional view of model learning into
a multi-objective problem that not only takes into account model accuracy but
also measurements effort as well. We evaluate our cost-aware transfer learning
solution using real-world configurable software including (i) a robotic system,
(ii) 3 different stream processing applications, and (iii) a NoSQL database
system. The experimental results demonstrate that our approach can achieve (a)
a high prediction accuracy, as well as (b) a high model reliability.Comment: To be published in the proceedings of the 12th International
Symposium on Software Engineering for Adaptive and Self-Managing Systems
(SEAMS'17
Media Presence and Inner Presence: The Sense of Presence in Virtual Reality Technologies
Abstract. Presence is widely accepted as the key concept to be considered in any research involving human interaction with Virtual Reality (VR). Since its original description, the concept of presence has developed over the past decade to be considered by many researchers as the essence of any experience in a virtual environment. The VR generating systems comprise two main parts: a technological component and a psychological experience. The different relevance given to them produced two different but coexisting visions of presence: the rationalist and the psychological/ecological points of view. The rationalist point of view considers a VR system as a collection of specific machines with the necessity of the inclusion \ud
of the concept of presence. The researchers agreeing with this approach describe the sense of presence as a function of the experience of a given medium (Media Presence). The main result of this approach is the definition of presence as the perceptual illusion of non-mediation produced by means of the disappearance of the medium from the conscious attention of the subject. At the other extreme, there \ud
is the psychological or ecological perspective (Inner Presence). Specifically, this perspective considers presence as a neuropsychological phenomenon, evolved from the interplay of our biological and cultural inheritance, whose goal is the control of the human activity. \ud
Given its key role and the rate at which new approaches to understanding and examining presence are appearing, this chapter draws together current research on presence to provide an up to date overview of the most widely accepted approaches to its understanding and measurement
Robust PCA as Bilinear Decomposition with Outlier-Sparsity Regularization
Principal component analysis (PCA) is widely used for dimensionality
reduction, with well-documented merits in various applications involving
high-dimensional data, including computer vision, preference measurement, and
bioinformatics. In this context, the fresh look advocated here permeates
benefits from variable selection and compressive sampling, to robustify PCA
against outliers. A least-trimmed squares estimator of a low-rank bilinear
factor analysis model is shown closely related to that obtained from an
-(pseudo)norm-regularized criterion encouraging sparsity in a matrix
explicitly modeling the outliers. This connection suggests robust PCA schemes
based on convex relaxation, which lead naturally to a family of robust
estimators encompassing Huber's optimal M-class as a special case. Outliers are
identified by tuning a regularization parameter, which amounts to controlling
sparsity of the outlier matrix along the whole robustification path of (group)
least-absolute shrinkage and selection operator (Lasso) solutions. Beyond its
neat ties to robust statistics, the developed outlier-aware PCA framework is
versatile to accommodate novel and scalable algorithms to: i) track the
low-rank signal subspace robustly, as new data are acquired in real time; and
ii) determine principal components robustly in (possibly) infinite-dimensional
feature spaces. Synthetic and real data tests corroborate the effectiveness of
the proposed robust PCA schemes, when used to identify aberrant responses in
personality assessment surveys, as well as unveil communities in social
networks, and intruders from video surveillance data.Comment: 30 pages, submitted to IEEE Transactions on Signal Processin
A methodical approach to performance measurement experiments : measure and measurement specification
This report describes a methodical approach to performance measurement experiments. This approach gives a blueprint for the whole trajectory from the notion of performance measures and how to define them via planning, instrumentation and execution of the experiments to interpretation of the results. The first stage of the approach, Measurement Initialisation, has been worked out completely. It is shown that a well-defined system description allows a procedural approach to defining performance measures and to identifying parameters that might affect it. For the second stage of the approach, Measurement Planning, concepts are defined that enable a clear experiment description or specification. It is highlighted what actually is being measured when executing an experiment. A brief example that illustrates the value of the method and a comparison with an existing method - that of Jain - complete this report
EMC-aware analysis and design of a low-cost receiver circuit under injection locking and pulling
In low-cost receiver applications, the preselect filter is often omitted in order to reduce the footprint of the total system. However, the immunity of the receiver can be severely compromised by this approach. This paper focuses on the effects of co-located sources on the local oscillator (LO), specifically injection locking and pulling. To this end, a low-cost radio receiver (RF) front-end is designed for operation in the 2 : 4 5 GHz industrial, scientific and medical (ISM) radio band. In addition to the effects on the oscillator, the consequences on the receiver's performance are evaluated as well. For the first time in literature, this work demonstrates the critical necessity to take the potentially detrimental effects caused by injection locking and pulling into account during Electromagnetic Compatibility (EMC)-aware design
A Survey of Green Networking Research
Reduction of unnecessary energy consumption is becoming a major concern in
wired networking, because of the potential economical benefits and of its
expected environmental impact. These issues, usually referred to as "green
networking", relate to embedding energy-awareness in the design, in the devices
and in the protocols of networks. In this work, we first formulate a more
precise definition of the "green" attribute. We furthermore identify a few
paradigms that are the key enablers of energy-aware networking research. We
then overview the current state of the art and provide a taxonomy of the
relevant work, with a special focus on wired networking. At a high level, we
identify four branches of green networking research that stem from different
observations on the root causes of energy waste, namely (i) Adaptive Link Rate,
(ii) Interface proxying, (iii) Energy-aware infrastructures and (iv)
Energy-aware applications. In this work, we do not only explore specific
proposals pertaining to each of the above branches, but also offer a
perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate;
Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications.
18 pages, 6 figures, 2 table
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