In designing and developing large complex products, people use models to describe and organize interrelated elements in both product systems (architecture, use cases, constraints...) and process systems (activities, deliverables, roles...). However, exchanged information is often incomplete, vague and not entirely determined at the beginning of the project and during its evolution. Our project ...

Misspecified models and noisy covariate measurements are two common sources of bias in statistical inferences. While there is considerable literature on the consequences of each problem in isolation, this article investigates the effect of both problems in tandem. In the context of linear models, the large-sample error in estimating the regression function is partitioned into two terms, one res...

Starting with our work on the characterization of the imprecision error in programs using floating-point-numbers, by abstract interpretation, this paper shows that there are numerous perspectives, if one wants to fully qualify the numerical quality of control systems, as found in the aeronautical and automotive industry, for instance. Some very common functions (e.g. integrators) are hard to st...

Identification and removal of imprecision in polynomial regression, originating from random errors (noise) in the independent variable data is discussed. The truncation error-to-noise ratio (TNR) is used to discriminate between imprecision dominated by collinearity, or numerical error propagation, or inflated variance due to noise in the independent variable. It is shown that after the source o...

This paper investigates the causes of imprecision of the observations and uncertainty of the authors who create Volunteer Geographic Information (VGI), i.e., georeferenced contents generated by volunteers when participating in some citizen science project. Specifically, various aspects of imprecision and uncertainty of VGI are outlined and, to cope with them, a knowledge-based approach is sugge...

The CLIA'88 classified all clinical laboratory testing as waived, moderate, or high complexity. The eight original waived tests were characterized as simple, accurate, error-free, risk-free, and suitable for home use by non-laboratory professionals. The subjective nature of the classification process was challenged immediately. The Clinical Laboratory Improvement Advisory Committee asked the CD...

Most algorithms in computational geometry tend to assume that all input is exact, with no imprecision or error. Most real-world data however, has some imprecision (for example due to measurement error). Thus, there exists a need for algorithms that can produce meaningful output for imprecise input data. In this thesis, I present results on the computation of upper and lower bounds on various ba...

Current techniques for power-aware VLIW instruction scheduling assumed that the power consumption parameters are precisely known. In reality, there will always be some degree of imprecision. In this paper, we propose to apply rough programming to handle the imprecision involved. The power-aware instruction scheduling problem is formulated as a chance-constraint rough program. A problem-specific...

Published estimates of the imprecision characteristics of immunoassays are often based on quantities of data that seem to be inadequate. The increasing use of imprecision profiles has not necessarily improved the situation. We describe and illustrate a method of computing 95% confidence intervals for profiles estimated directly from replicated assay results. The data used were chosen to mimic t...

In applications such as multimedia that tolerate imprecise results, approximate computing techniques can sacrifice precision to save power or time. One aspect of approximate computing is imprecise storage in multi-level cells (MLCs). Computer words that are too large for a single MLC must be distributed across multiple approximate MLCs. The wordlevel imprecision depends on how the words are spl...