3,024 research outputs found
Semi-Automated Nasal PAP Mask Sizing using Facial Photographs
We present a semi-automated system for sizing nasal Positive Airway Pressure
(PAP) masks based upon a neural network model that was trained with facial
photographs of both PAP mask users and non-users. It demonstrated an accuracy
of 72% in correctly sizing a mask and 96% accuracy sizing to within 1 mask size
group. The semi-automated system performed comparably to sizing from manual
measurements taken from the same images which produced 89% and 100% accuracy
respectively.Comment: 4 pages, 3 figures, 4 tables, IEEE Engineering Medicine and Biology
Conference 201
Affective Facial Expression Processing via Simulation: A Probabilistic Model
Understanding the mental state of other people is an important skill for
intelligent agents and robots to operate within social environments. However,
the mental processes involved in `mind-reading' are complex. One explanation of
such processes is Simulation Theory - it is supported by a large body of
neuropsychological research. Yet, determining the best computational model or
theory to use in simulation-style emotion detection, is far from being
understood.
In this work, we use Simulation Theory and neuroscience findings on
Mirror-Neuron Systems as the basis for a novel computational model, as a way to
handle affective facial expressions. The model is based on a probabilistic
mapping of observations from multiple identities onto a single fixed identity
(`internal transcoding of external stimuli'), and then onto a latent space
(`phenomenological response'). Together with the proposed architecture we
present some promising preliminary resultsComment: Annual International Conference on Biologically Inspired Cognitive
Architectures - BICA 201
Explicit tracking of uncertainty increases the power of quantitative rule-of-thumb reasoning in cell biology
"Back-of-the-envelope" or "rule-of-thumb" calculations involving rough
estimates of quantities play a central scientific role in developing intuition
about the structure and behaviour of physical systems, for example in so-called
`Fermi problems' in the physical sciences. Such calculations can be used to
powerfully and quantitatively reason about biological systems, particularly at
the interface between physics and biology. However, substantial uncertainties
are often associated with values in cell biology, and performing calculations
without taking this uncertainty into account may limit the extent to which
results can be interpreted for a given problem. We present a means to
facilitate such calculations where uncertainties are explicitly tracked through
the line of reasoning, and introduce a `probabilistic calculator' called
Caladis, a web tool freely available at www.caladis.org, designed to perform
this tracking. This approach allows users to perform more statistically robust
calculations in cell biology despite having uncertain values, and to identify
which quantities need to be measured more precisely in order to make confident
statements, facilitating efficient experimental design. We illustrate the use
of our tool for tracking uncertainty in several example biological
calculations, showing that the results yield powerful and interpretable
statistics on the quantities of interest. We also demonstrate that the outcomes
of calculations may differ from point estimates when uncertainty is accurately
tracked. An integral link between Caladis and the Bionumbers repository of
biological quantities further facilitates the straightforward location,
selection, and use of a wealth of experimental data in cell biological
calculations.Comment: 8 pages, 3 figure
Cotenants Trumping Cotenants: The Eighth Circuit Takes a Diverse Stance on Cotenants\u27 Authority under the Fourth Amendment
Reluctantly, John Adams mailed the envelope addressed to his wife, Abigail, knowing the contents could bring about his death. This letter, mailed to his dear friend, contained a description of his pleas for independence to the Continental Congress, a description that if located by the British, would most certainly subject him to charges of treason. Immediately after Mr. Adams dispatched his letter, he was approached by a British intelligence officer requesting to review the letter. Mr. Adams denied the officer\u27s request and sent him on his way. Later, when the letter arrived to the unsuspecting Abigail, it was accompanied by a British officer who asked if he could examine the letter. Ignorant as to the letter\u27s contents, Abigail consented to the request and the officer discovered the treasonous materials, resulting in the seizure of the letter and the subsequent arrest of Mr. Adams. Would our founding fathers have considered this particular exercise of police power beyond reproach? While this fictional illustration is distinguishable from the more disturbing factual scenario presented in United States v. Hudspeth, it nevertheless embodies the same question: If two individuals have common authority over a piece of property, can government officials purposely ignore one party\u27s express refusal to search and instead accept the consent of the other party? Hudspeth asks this question in the unforgiving light of the despicable acts of a pedophile; where a computer containing child pornography takes the place of John Adams\u27 rebellious letter. In light of its deplorable factual setting, Hudspeth is a case which must be viewed with an objective eye. In doing so, it is helpful to keep the analogy of John Adams\u27s letter in mind, as one may be, albeit unconsciously, predisposed to the persecution of pedophiles. Because Hudspeth is a case which not only implicates the rights of a pedophile, but the rights of all citizens who wish to object to governmental searches and seizures of their property, objectivity is essential to arriving at the correct conclusion
Induction of defeasible logic theories in the legal domain
The market for intelligent legal information systems remains relatively untapped and while this might be interpreted as an indication that it is simply impossible to produce a system that satisfies the needs of the legal community, an analysis of previous attempts at producing such systems reveals a common set of deficiencies that in-part explain why there have been no overwhelming successes to date. Defeasible logic, a logic with proven successes at representing legal knowledge, seems to overcome many of these deficiencies and is a promising approach to representing legal knowledge. Unfortunately, an immediate application of technology to the challenges in this domain is an expensive and computationally intractable problem. So, in light of the benefits, we seek to find a practical algorithm that uses heuristics to discover an approximate solution. As an outcome of this work, we have developed an algorithm that integrates defeasible logic into a decision support system by automatically deriving its knowledge from databases of precedents. Experiments with the new algorithm are very promising - delivering results comparable to and exceeding other approaches
An algorithm for the induction Of defeasible logic theories from databases
Defeasible logic is a non-monotonic logic with applications in rule-based domains such as law. To ease the development and improve the accuracy of expert systems based on defeasible logic, it is desirable to automatically induce a theory of the logic from a training set of precedent data. Empirical evidence suggests that minimal theories that describe the training set tend to be more faithful representations of reality. We show via transformation from the hitting set problem that this global minimization problem is intractable, belonging to the class of NP optimisation problems. Given the inherent difficulty of finding the optimal solution, we instead use heuristics and demonstrate that a best-first, greedy, branch and bound algorithm can be used to find good theories in short time. This approach displays significant improvements in both accuracy and theory size as compared to recent work in the area that post-processed the output of an Aprori association rule-mining algorithm, with comparable execution times
Entangled subspaces and generic local state discrimination with pre-shared entanglement
Walgate and Scott have determined the maximum number of generic pure quantum
states in multipartite space that can be unambiguously discriminated by an LOCC
measurement [Journal of Physics A: Mathematical and Theoretical, 41:375305, 08
2008]. In this work, we determine this number in a more general setting in
which the local parties have access to pre-shared entanglement in the form of a
resource state. We find that, for an arbitrary pure resource state, this number
is equal to the Krull dimension of (the closure of) the set of pure states
obtainable from the resource state by SLOCC. This dimension is known for
several resource states, for example the GHZ state.
Local state discrimination is closely related to the topic of entangled
subspaces, which we study in its own right. We introduce -entangled
subspaces, which naturally generalize previously studied spaces to higher
multipartite entanglement. We use algebraic geometric methods to determine the
maximum dimension of an -entangled subspace, and present novel explicit
constructions of such spaces. We obtain similar results for symmetric and
antisymmetric -entangled subspaces, which correspond to entangled subspaces
of bosonic and fermionic systems, respectively.Comment: 32 pages, feedback welcom
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