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The special issue of “Networks in space and in time: methods and applications” contributes to the debate on contextual analysis in network science. It includes seven research papers that shed light on the analysis of network phenomena studied within geographic space and across temporal dimensions. In these papers, methodological issues as well as specific applications are described from different fields. We take the seven papers, study their citations and texts, and relate them to the broader literature. By exploiting the bibliographic information and the textual data of these seven documents, citation analysis and lexical correspondence analysis allow us to evaluate the connections among the papers included in this issue.
In this paper, we present a novel stochastic framework for network-based bilateral teleoperation systems. A Bayesian approach, which provides robust tracking performance in real-world applications, is proposed to estimate and predict the stochastic variables and compensate for the unreliable network conditions. Combining with a practical approach in transport and application layers of the Internet, this paper demonstrates a high performance and efficient prediction and estimation method for bilateral teleoperation system. Experimental results show that the proposed Bayesian approach estimates and predicts true position and force data over unreliable network conditions, and therefore, improves the performance of overall teleoperation systems.
The axioms of iteration theories, or iteration categories, capture the equational properties of fixed point operations in several computationally significant categories. Iteration categories may be axiomatized by the Conway identities and identities associated with finite automata. We show that the Conway identities and the identities associated with the members of a subclass $\mathcal{Q}$ of finite automata is complete for iteration categories iff for every finite simple group G there is an automaton Q ∈ $\mathcal{Q}$ such that G is a quotient of a group in the monoid M(Q) of the automaton Q. We also prove a stronger result that concerns identities associated with finite automata with a distinguished initial state.
This paper is about the precision performance evaluation of an XY-theta platform, with a patented kinematic design. Indeed, this platform is held by a serial redundant robot arm actuated with four revolute joints. The platform offers a wide 300 × 300 mm workspace, whereas the whole mechanism is extremely compact. Any workpiece on the platform can be positioned under a vertical axis to be grasped or manufactured in a two-step approach: in a coarse positioning mode, the four revolute joints are controlled to position and orientate the workpiece with a position error of less than 10 μm; in a fine positioning mode, two revolute joints are mechanically blocked while two others are controlled to reduce the final error to below 2 μm. The mechanism design and the choice of the blocked and moving joints are optimized to enhance the positioning performances in the two-step positioning method. In this paper, the platform positioning repeatability and its spatial resolution are characterized with the help of a camera. The advantage of this method is that it avoids any mechanical contact and can be implemented easily. Then, these results are compared to our previous precision performance evaluation obtained with the stationary cube method. Finally, the positioning repeatability is estimated at 6.5 μm in the coarse positioning mode and 1.4 μm in the fine positioning mode. Between the coarse and fine mode, the repeatability is thus improved by the factor of four, as predicted by the theory.
We provide infinitary proof theories for three common semantic theories of truth: strong Kleene, van Fraassen supervaluation and Cantini supervaluation. The value of these systems is that they provide an easy method of proving simple facts about semantic theories. Moreover we shall show that they also give us a simpler understanding of the computational complexity of these definitions and provide a direct proof that the closure ordinal for Kripke’s definition is $\omega _1^{CK}$. This work can be understood as an effort to provide a proof-theoretic counterpart to Welch’s game-theoretic (Welch, 2009).
High-dimensional data appear in many fields, and their analysis has become increasingly important in modern statistics. However, it has long been observed that several well-known methods in multivariate analysis become inefficient, or even misleading, when the data dimension p is larger than, say, several tens. A seminal example is the well-known inefficiency of Hotelling's T2-test in such cases. This example shows that classical large sample limits may no longer hold for high-dimensional data; statisticians must seek new limiting theorems in these instances. Thus, the theory of random matrices (RMT) serves as a much-needed and welcome alternative framework. Based on the authors' own research, this book provides a firsthand introduction to new high-dimensional statistical methods derived from RMT. The book begins with a detailed introduction to useful tools from RMT, and then presents a series of high-dimensional problems with solutions provided by RMT methods.
In the course of the previous 42 chapters we have introduced numerous more or less rational principles which our agent, dwelling in an unknown structure M for L, might choose to adopt in order to address the question
Q: In the situation of zero knowledge, logically, or rationally, what belief should I give to a sentence θ ∈ SL being true in M?
We have argued from the start, via the Dutch Book argument, that it is rational to identify belief with probability, in the sense that it should satisfy conditions (P1–3), At this point the facet of ‘rational’, or at least ‘irrational’, being used is that it is irrational to agree to bets which guarantee one a certain loss. In general however we have offered no definition of ‘logical’ or ‘rational’. Instead we have embraced certain overarching meta-principles, or slogans, which we may feel are ‘rational’, just in the way that we may feel that something is funny without being able to define what we mean by ‘funny’.
We have particularly focused on four such slogans: That it is rational to:
(i) Obey symmetries: If, in context, θ and θ′ are linked by a symmetry then they should be assigned equal probability.
(ii) Ignore irrelevant information: If θ′ is irrelevant to θ then conditioning θ on θ′ should not change the probability assigned to θ.
(iii) Enhance your probabilities on receipt of (positively) relevant information: If θ′ is supportive of θ then conditioning θ on θ′ should increase, or at least not decrease, the probability assigned to θ.
(iv) Respect analogies: The more θ′ is like θ the more conditioning on θ′ should enhance the probability assigned to θ.
Of course these are just templates for principles.
In Part 1 we placed no conditions on the arity of the relation symbols in L, the restriction to unary only happened in Part 2. In this third part we shall again allow into our language binary, ternary etc. relation symbols. As we have seen, despite the logical simplicity of unary languages, for example every formula becomes equivalent to a boolean combination of Π1 and Σ1 formulae, Unary PIL has still a rather rich theory. For this reason it is hardly surprising that with very few exceptions (for example Gaifman [30], Gaifman & Snir [32], Scott & Krauss [132], Krauss [69], Hilpinen [46] and Hoover [52]) ‘Inductive Logic’ meant ‘Unary Inductive Logic’ up to the end of the 20th century.
Of course there was an awareness of this further challenge, Carnap [12, p123 -4] and Kemeny [61], [64] both made this point. There were at least two other reasons why the move to the polyadic was so delayed. The first is that simple, everyday examples of induction with non-unary relations are rather scarce. However they do exist and we do seem to have some intuitions about them. For example suppose that you are planting an orchard and you read that apples of variety A are good pollinators and apples of variety B are readily pollinated. Then you might expect that if you plant an A apple next to a B apple you will be rewarded with an abundant harvest, at least from the latter tree. In this case one might conclude that you had applied some sort of polyadic induction to reach this conclusion, and that may be it has a logical structure worthy of further investigation.
Having said that it is still far from clear what probability functions should be proposed here (and possibly this is a third reason for the delay).
Having derived some of the basic properties of probability functions we will now take a short diversion to give what we consider to be the most compelling argument in this context, namely the Dutch Book argument originating with Ramsey [122] and de Finetti [25], in favour of an agent's ‘degrees of belief’ satisfying (P1–3), and hence being identified with a probability function, albeit subjective probability since it is ostensibly the property of the agent in question. Of course this could really be said to be an aside to the purely mathematical study of PIL and hence dispensable. The advantage of considering this argument however is that by linking belief and subjective probability it better enables us to appreciate and translate into mathematical formalism the many rational principles we shall later encounter.
The idea of the Dutch Book argument is that it identifies ‘belief’ with willingness to bet. So suppose, as in the context of PIL explained above, we have an agent inhabiting some unknown structure M ∈ T L (which one imagines will eventually be revealed to decide the wager) and that θ ∈ SL, 0 ≤ p ≤ 1 and for a stake s > 0 the agent is offered a choice of one of two wagers:
(Bet1p) Win s(1 − p) if M ⊧ θ, lose sp if M ⊭ θ.
(Bet2p) Win sp if M ⊭ θ, lose s (1 − p) if M ⊧ θ.
If the agent would not be happy to accept Bet1p we assume that it is because the agent thinks that the bet is to his/her disadvantage and hence to the advantage of the bookmaker. But in that case Bet2p allows the agent to swap roles with the bookmaker so s/he should now see that bet as being to his/her advantage, and hence acceptable. In summary then, we may suppose that for any 0 ≤ p ≤ 1 at least one of Bet1p and Bet2p is acceptable to the agent. In particular we may assume that Bet10 and Bet21 are acceptable since in both cases the agent has nothing to lose and everything to gain.