The renormalized Hamiltonian truncation method in the large ETE_T expansion

Hamiltonian Truncation Methods are a useful numerical tool to study strongly coupled QFTs. In this work we present a new method to compute the exact corrections, at any order, in the Hamiltonian Truncation approach presented by Rychkov et al. in Refs. [1-3]. The method is general but as an example we calculate the exact $g^2$ and some of the $g^3$ contributions for the $\phi^4$ theory in two dimensions. The coefficients of the local expansion calculated in Ref. [1] are shown to be given by phase space integrals. In addition we find new approximations to speed up the numerical calculations and implement them to compute the lowest energy levels at strong coupling. A simple diagrammatic representation of the corrections and various tests are also introduced.Comment: JHEP version, typos fixed in Appendix and eq. (23

On the shape of a pure O-sequence

An order ideal is a finite poset X of (monic) monomials such that, whenever M is in X and N divides M, then N is in X. If all, say t, maximal monomials of X have the same degree, then X is pure (of type t). A pure O-sequence is the vector, h=(1,h_1,...,h_e), counting the monomials of X in each degree. Equivalently, in the language of commutative algebra, pure O-sequences are the h-vectors of monomial Artinian level algebras. Pure O-sequences had their origin in one of Richard Stanley's early works in this area, and have since played a significant role in at least three disciplines: the study of simplicial complexes and their f-vectors, level algebras, and matroids. This monograph is intended to be the first systematic study of the theory of pure O-sequences. Our work, making an extensive use of algebraic and combinatorial techniques, includes: (i) A characterization of the first half of a pure O-sequence, which gives the exact converse to an algebraic g-theorem of Hausel; (ii) A study of (the failing of) the unimodality property; (iii) The problem of enumerating pure O-sequences, including a proof that almost all O-sequences are pure, and the asymptotic enumeration of socle degree 3 pure O-sequences of type t; (iv) The Interval Conjecture for Pure O-sequences (ICP), which represents perhaps the strongest possible structural result short of an (impossible?) characterization; (v) A pithy connection of the ICP with Stanley's matroid h-vector conjecture; (vi) A specific study of pure O-sequences of type 2, including a proof of the Weak Lefschetz Property in codimension 3 in characteristic zero. As a corollary, pure O-sequences of codimension 3 and type 2 are unimodal (over any field); (vii) An analysis of the extent to which the Weak and Strong Lefschetz Properties can fail for monomial algebras; (viii) Some observations about pure f-vectors, an important special case of pure O-sequences.Comment: iii + 77 pages monograph, to appear as an AMS Memoir. Several, mostly minor revisions with respect to last year's versio

Dynamic bayesian networks for learning interactions between assistive robotic walker and human users

Detection of individuals intentions and actions from a stream of human behaviour is an open problem. Yet for robotic agents to be truly perceived as human-friendly entities they need to respond naturally to the physical interactions with the surrounding environment, most notably with the user. This paper proposes a generative probabilistic approach in the form of Dynamic Bayesian Networks (DBN) to seamlessly account for users attitudes. A model is presented which can learn to recognize a subset of possible actions by the user of a gait stability support power rollator walker, such as standing up, sitting down or assistive strolling, and adapt the behaviour of the device accordingly. The communication between the user and the device is implicit, without any explicit intention such as a keypad or voice.The end result is a decision making mechanism that best matches the users cognitive attitude towards a set of assistive tasks, effectively incorporating the evolving activity model of the user in the process. The proposed framework is evaluated in real-life condition. © 2010 Springer-Verlag Berlin Heidelberg

Planning stable and efficient paths for articulated mobile robots on challenging terrains

An analytical strategy to generate stable paths for a reconfigurable vehicle while also meeting additional navigational objectives is herein proposed. The work is motivated by robots traversing over challenging terrains during search and rescue operations, such as those equipped with manipulator arms and/or flippers. The proposed solution looks at minimizing the length of the traversed path and the energy expenditure in changing postures, yet also accounts for additional constraints in terms of sensor visibility (i.e arm configurations close to those orthogonal to the horizontal global plane which can afford a wider sensor view) and traction (i.e. flipper angles that provide the largest trackterrain interaction area). The validity of the proposed planning approach is evaluated with a multitracked robot fitted with flippers and a range camera at the end of a manipulator arm while navigating over two challenging 3D terrain data sets: one in a mock-up urban search and rescue arena (USAR), and a second one from a publicly available quasi-outdoor rover testing facility (UTIAS)

Probabilistic stable motion planning with stability uncertainty for articulated vehicles on challenging terrains

© 2015, Springer Science+Business Media New York. A probabilistic stable motion planning strategy applicable to reconfigurable robots is presented in this paper. The methodology derives a novel statistical stability criterion from the cumulative distribution of a tip-over metric. The measure is dynamically updated with imprecise terrain information, localization and robot kinematics to plan safety-constrained paths which simultaneously allow the widest possible visibility of the surroundings by simultaneously assuming highest feasible vantage robot configurations. The proposed probabilistic stability metric allows more conservative poses through areas with higher levels of uncertainty, while avoiding unnecessary caution in poses assumed at well-known terrain sections. The implementation with the well known grid based A* algorithm and also a sampling based RRT planner are presented. The validity of the proposed approach is evaluated with a multi-tracked robot fitted with a manipulator arm and a range camera using two challenging elevation terrains data sets: one obtained whilst operating the robot in a mock-up urban search and rescue arena, and the other from a publicly available dataset of a quasi-outdoor rover testing facility

Utilising Tree-Based Ensemble Learning for Speaker Segmentation

Part 2: Learning-Ensemble LearningInternational audienceIn audio and speech processing, accurate detection of the changing points between multiple speakers in speech segments is an important stage for several applications such as speaker identification and tracking. Bayesian Information Criteria (BIC)-based approaches are the most traditionally used ones as they proved to be very effective for such task. The main criticism levelled against BIC-based approaches is the use of a penalty parameter in the BIC function. The use of this parameters consequently means that a fine tuning is required for each variation of the acoustic conditions. When tuned for a certain condition, the model becomes biased to the data used for training limiting the model’s generalisation ability.In this paper, we propose a BIC-based tuning-free approach for speaker segmentation through the use of ensemble-based learning. A forest of segmentation trees is constructed in which each tree is trained using a sampled version of the speech segment. During the tree construction process, a set of randomly selected points in the input sequence is examined as potential segmentation points. The point that yields the highest ΔBIC is chosen and the same process is repeated for the resultant left and right segments. The tree is constructed where each node corresponds to the highest ΔBIC with the associated point index. After building the forest and using all trees, the accumulated ΔBIC for each point is calculated and the positions of the local maximums are considered as speaker changing points. The proposed approach is tested on artificially created conversations from the TIMIT database. The approach proposed show very accurate results comparable to those achieved by the-state-of-the-art methods with a 9% (absolute) higher F1 compared with the standard ΔBIC with optimally tuned penalty parameter

SuDS and amphibians - are constructed wetlands really benefitting nature and people?

While urbanisation is a major threat to global biodiversity, it also brings opportunities for some species. Sustainable Drainage Systems (SuDS) have been installed in all Scottish cities to reduce flood and pollution risk and they can also offer new habitats for wildlife. We studied SuDS in Inverness and the Scottish Central Belt to assess their value as amphibian breeding sites, habitats, and as places where urban people can experience nature. The nine-year study revealed that many SuDS were of similar ecological quality to wider countryside ponds but that the quality of ponds is not equitably distributed between neighbourhoods inhabited by different socio-economic classes. However, the findings suggest ways to improve the design and management of SuDS for people and nature, making access to high quality ponds available to all social groups

An Audio-visual Solution to Sound Source Localization and Tracking with Applications to HRI

Robot audition is an emerging and growing branch in the robotic community and is necessary for a natural Human-Robot Interaction (HRI). In this paper, we propose a framework that integrates advances from Simultaneous Localization And Mapping (SLAM), bearing-only target tracking, and robot audition techniques into a unifed system for sound source identification, localization, and tracking. In indoors, acoustic observations are often highly noisy and corrupted due to reverberations, the robot ego-motion and background noise, and possible discontinuous nature of them. Therefore, in everyday interaction scenarios, the system requires accommodating for outliers, robust data association, and appropriate management of the landmarks, i.e. sound sources. We solve the robot self-localization and environment representation problems using an RGB-D SLAM algorithm, and sound source localization and tracking using recursive Bayesian estimation in the form of the extended Kalman Filter with unknown data associations and an unknown number of landmarks. The experimental results show that the proposed system performs well in the medium-sized cluttered indoor environment

User quality of experience of mulsemedia applications

User Quality of Experience (QoE) is of fundamental importance in multimedia applications and has been extensively studied for decades. However, user QoE in the context of the emerging multiple-sensorial media (mulsemedia) services, which involve different media components than the traditional multimedia applications, have not been comprehensively studied. This article presents the results of subjective tests which have investigated user perception of mulsemedia content. In particular, the impact of intensity of certain mulsemedia components including haptic and airflow on user-perceived experience are studied. Results demonstrate that by making use of mulsemedia the overall user enjoyment levels increased by up to 77%

Exploration in Information Distribution Maps

In this paper, a novel solution for autonomous robotic exploration is proposed. The distribution of information in an unknown environment is modeled as an unsteady diffusion process, which can be an appropriate mathematical formulation and analogy for expanding, time-varying, and dynamic environments. This information distribution map is the solution of the diffusion process partial differential equation, and is regressed from sensor data as a Gaussian Process. Optimization of the process parameters leads to an optimal frontier map which describes regions of interest for further exploration. Since the presented approach considers a continuous model of the environment, it can be used to plan smooth exploration paths exploiting the structural dependencies of the environment whilst handling sparse sensors measurements. The performance of the proposed approach is evaluated through simulation results in the well-known Freiburg and Cave maps