Maximum Physically Consistent Trajectories

Trajectories are usually collected with physical sensors, which are prone to errors and cause outliers in the data. We aim to identify such outliers via the physical properties of the tracked entity, that is, we consider its physical possibility to visit combinations of measurements. We describe optimal algorithms to compute maximum subsequences of measurements that are consistent with (simplified) physics models. Our results are output-sensitive with respect to the number k of outliers in a trajectory of n measurements. Specifically, we describe an O ( n log n log 2 k )-time algorithm for 2D trajectories using a model with unbounded acceleration but bounded velocity, and an O(nk) -time algorithm for any model where consistency is “concatenable”: a consistent subsequence that ends where another begins together form a consistent sequence. We also consider acceleration-bounded models that are not concatenable. We show how to compute the maximum subsequence for such models in O ( n k 2 log k ) time, under appropriate realism conditions. Finally, we experimentally explore the performance of our algorithms on several large real-world sets of trajectories. Our experiments show that we are generally able to retain larger fractions of noisy trajectories than previous work and simpler greedy approaches. We also observe that the speed-bounded model may in practice approximate the acceleration-bounded model quite well, though we observed some variation between datasets.

Artificial Intelligent Algorithm to control Circuits Structuring of Flexible remote Experiments in Engineering within a Switching Matrix Architecture

This paper presents the development of an artificial intelligent algorithm to control circuits structuring of flexible remote experiments in engineering fields of electronics and electricity within a switching matrix architecture. In addition, this paper presents a technical analyze and characterization of VISIR system to point itsadvantages and its inconveniences.The developedartificial intelligent algorithm controlsthe interconnections between electrical and electronic components and monitorsthe power supplying and measurements conducting onVISIR system.We also developed an electronic board to provide the physical possibility of connecting any component to any other component on VISIR’s switching system, and thereby manifesting a switching matrix architecture within VISIR. The developed switching matrix architecture and the developed algorithm enable to have flexible remote experiments in engineeringfields of electronics and electricitywhile havingresilient control on circuits structuring for e-learning purposes.Inaddition, they open the way to havemore circuit combinations of experiments by offering the possibility of connecting any component to any other componentwhile respecting the electrical limits of current and voltage.

Wittgenstein on 'Imaginability' as a Criterion for Logical Possibility

Throughout his whole work, Wittgenstein seizes on a distinction between logical and physical possibility, and impossibility. Despite this continuity and although, Wittgenstein brings in this distinction in various contexts and from different vantage points, he often solely brushes over it without elaborating in detail. In the so-called Big Typescript, however, he dedicates himself not only to the distinction between logical and physical possibility but also to the distinction between logical possibility and impossibility in particular investigations. In the course of these investigations, another aspect arises and is tossed and turned repeatedly by Wittgenstein – namely, the place of “imaginability” in these considerations. On the basis of three focussed chapters in the Big Typescript, I argue that “imaginability” as an utterance of the form “being able to imagine ‘what it would be like’” can be allocated the place of a criterion for logical possibility. To this end, I will first outline the chapters 96., 27. and 26. in one section each. Although in these chapters, Wittgenstein only indicates rather than claiming explicitly “imaginability” to be a criterion for logical possibility, I will discuss in the last section how this conclusion can be drawn by combining the results of the previous sections.

¿Qué hace físicamente posible a un mundo posible?

There is a widely extended viewpoint about physical possibility, what we will call Standard Approach, which holds that the physically possible is delimited by the nomological structure of physical theories: to be physically possible is to be in accordance with the physical laws, to be physically impossible is to be prohibited by physical laws and to be physically necessary is to be demanded by the physical laws. However, it is possible to show that this approach is too relaxed and permissive when it comes to collecting and systematizing many of the modal intuitions present in the physical community. In this work we will argue, on the one hand, that the notion of physical possibility is more complex and richer than suggested by the standard approach and, on the other hand, that it is necessary to add some extra elements to the characterization of physical possibility in order to that it is adequate in scientific contexts.

Impossability Theory

My preferred solution to the Grandfather Paradox is to say that time travellers have the ability to do the metaphysically impossible (and so I can kill my grandfather), even though they never will. This requires physical possibility to outstrip metaphysical possibility. This chapter argues that, given the dialectic one must be in when considering the Grandfather Paradox, it’s reasonable to assume just that. It then argues that, given that assumption, impossability theory follows. The rest of the chapter explains Jack Spencer’s argument for the same conclusion, before discussing how impossability theory can be applied to a selection of paradoxes other than the Grandfather Paradox, and which have nothing to do with time travel.

Determinism, Counterpredictive Devices, and the Impossibility of Laplacean Intelligences

In a famous passage drawing implications from determinism, Laplace introduced the image an intelligence who knew the positions and momenta of all of the particles of which the universe is composed, and asserted that in a deterministic universe such an intelligence would be able to predict everything that happens over its entire history. It is not, however, difficult to establish the physical possibility of a counterpredictive device, i.e., a device designed to act counter to any revealed prediction of its behavior. What would happen if a Laplacean intelligence were put into communication with such a device and forced to reveal its prediction of what the device would do on some occasion? On the one hand, it seems that the Laplacean Intelligence should be able to predict the device's behavior. On the other hand, it seems like that device should be able to act counter to the prediction. An examination of the puzzle leads to clarification of what determinism does (and does not) entail, with some insights about various other things along the way.

SAD computers and two versions of the Church–Turing Thesis

Recent work on hypercomputation has raised new objections against the Church–Turing Thesis. In this paper, I focus on the challenge posed by a particular kind of hypercomputer, namely, SAD computers. I first consider deterministic and probabilistic barriers to the physical possibility of SAD computation. These barriers suggest several ways to defend a Physical version of the Church–Turing Thesis. I then argue against Hogarth’s analogy between non-Turing computability and non-Euclidean geometry, showing that it is a non-sequitur. I conclude that the Effective version of the Church–Turing Thesis is unaffected by SAD computation.Published in British Journal for the Philosophy of Science 60.4: 765–92.