Online social networking services involve communication activities between large number of individuals over the public Internet and their crawled records are often regarded as proxies of real (i.e., offline) interaction structure. However, structure observed in these records might differ from real counterparts because individuals may behave differently online and non-human accounts may even participate. To understand the difference between online and real social networks, we investigate an empirical communication network between users on Twitter, which is perhaps one of the largest social networking services. We define a network of user pairs that send reciprocal messages. Based on the correlation between degree of adjacent nodes observed in this network, we hypothesize that this network differs from conventional understandings in the sense that there is a small number of distinctive users that we call outsiders. Outsiders do not belong to any user groups but they are connected with different groups, while not being well connected with each other. We identify outsiders by maximizing the degree assortativity coefficient of the network via node removal, thereby confirming that local structural properties of outsiders identified are consistent with our hypothesis. Our findings suggest that the existence of outsiders should be considered when using Twitter communication networks for social network analysis.

In this paper, we consider a d-node GI|GI|1 tandem queue with i.i.d. inter-arrival process and service processes that are independent of each other. Our main interest is to estimate the probability to reach a high level N in a busy cycle of the system using simulation. As crude simulation does not give a sufficient precision in reasonable time, we use importance sampling. We introduce a method to find a state-independent change of measure and we show that this is equivalent to a change of measure that was earlier, but implicitly, described by Parekh and Walrand [8]. We also show that this change of measure is the only exponential state-independent change of measure that may result in an asymptotically efficient estimator. Lastly, we provide necessary conditions for this state-independent change of measure to give an asymptotically efficient estimator.

In this paper, we introduce the notion of expansion tree for linear logic. As in Miller's original work, we have a shallow reading of an expansion tree that corresponds to the conclusion of the proof, and a deep reading which is a formula that can be proved by propositional rules. We focus our attention to MLL2, and we also present a deep inference system for that logic. This allows us to give a syntactic proof to a version of Herbrand's theorem.

This paper explores the structural changes in the international organization of automotive production since the early 1990s. We apply descriptive network measures to international trade data for the period 1993–2013 for three automotive component groups with different technological intensity, with the aim of understanding (1) how the automotive international trade network has changed since the beginning of the 1990s; (2) whether regionalization has increased over time; (3) how the role that rising powers play within and between regions interacts with regionalization patterns. Our findings suggest that the structure of trade has changed significantly over the last two decades in all components. The network for electric and electrical parts and engines has evolved to become more hierarchical, with a cohesive core tied to hangers-on in the periphery, while the opposite has happened for rubber and metal. Regionalization patterns also show important differences across components. Finally, we have found an apparent association between the strengthening of regionalization patterns and the role played by traditional players and rising powers.

The paper introduces the use of radial basis functions (RBFs) to generate smooth point-to-point joint trajectories for robot manipulators. First, Gaussian RBF interpolation is introduced taking into account boundary conditions. Then, the proposed approach is compared with classical planning techniques based on polynomial and trigonometric models. Also, the trajectory planning problem involving via-points is solved using the proposed RBF interpolation technique. The obtained trajectories are then compared with those synthesized using algebraic and trigonometric splines. Finally, the proposed method is tested for the six-joint PUMA 560 robot in two cases (minimum time and minimum time-jerk) and results are compared with those of other planning techniques. Numerical results demonstrate the advantage of the proposed technique, offering an effective solution to generate trajectories with short execution time and smooth profile.

By increasing the amount of data in computer networks, searching and finding suitable information will be harder for users. One of the most widespread forms of information on such networks are textual documents. So exploring these documents to get information about their content is difficult and sometimes impossible. Multi-document text summarization systems are an aid to producing a summary with a fixed and predefined length, while covering the maximum content of the input documents. This paper presents a novel method for multi-document extractive summarization based on textual entailment relations and sentence compression via formulating the problem as a knapsack problem. In this approach, sentences of documents are ranked according to the extended Tf-Idf method, then entailment scores of selected sentences are computed. Through these scores, the final score of each sentence is calculated. Finally, by decreasing the lengths of sentences via sentence compression, the problem has been solved by greedy and dynamic Programming approaches to the knapsack problem. Experiments on standard summarization datasets and evaluating the results based on the Rouge system show that the suggested method, according to the best of our knowledge, has increased F-measure of query-based summarization systems by two per cent and F-measure of general summarization systems by five per cent.

We give the first polynomial upper bound on the mixing time of the edge-flip Markov chain for unbiased dyadic tilings, resolving an open problem originally posed by Janson, Randall and Spencer in 2002 [14]. A dyadic tiling of size n is a tiling of the unit square by n non-overlapping dyadic rectangles, each of area 1/n, where a dyadic rectangle is any rectangle that can be written in the form [a2−s, (a + 1)2−s] × [b2−t, (b + 1)2−t] for a, b, s, t ∈ ℤ⩾ 0. The edge-flip Markov chain selects a random edge of the tiling and replaces it with its perpendicular bisector if doing so yields a valid dyadic tiling. Specifically, we show that the relaxation time of the edge-flip Markov chain for dyadic tilings is at most O(n4.09), which implies that the mixing time is at most O(n5.09). We complement this by showing that the relaxation time is at least Ω(n1.38), improving upon the previously best lower bound of Ω(n log n) coming from the diameter of the chain.

Bisimulation proofs play a central role in programming languages in establishing rich properties such as contextual equivalence. They are also challenging to mechanize, since they require a combination of inductive and coinductive reasoning on open terms. In this paper, we describe mechanizing the property that similarity in the call-by-name lambda calculus is a pre-congruence using Howe’s method in the Beluga formal reasoning system. The development relies on three key ingredients: (1) we give a higher order abstract syntax (HOAS) encoding of lambda terms together with their operational semantics as intrinsically typed terms, thereby avoiding not only the need to deal with binders, renaming and substitutions, but keeping all typing invariants implicit; (2) we take advantage of Beluga’s support for representing open terms using built-in contexts and simultaneous substitutions: this allows us to directly state central definitions such as open simulation without resorting to the usual inductive closure operation and to encode very elegantly notoriously painful proofs such as the substitutivity of the Howe relation; (3) we exploit the possibility of reasoning by coinduction in Beluga’s reasoning logic. The end result is succinct and elegant, thanks to the high-level abstractions and primitives Beluga provides. We believe that this mechanization is a significant example that illustrates Beluga’s strength at mechanizing challenging (co)inductive proofs using HOAS encodings.

We study I(T), the number of inversions in a tree T with its vertices labelled uniformly at random, which is a generalization of inversions in permutations. We first show that the cumulants of I(T) have explicit formulas involving the k-total common ancestors of T (an extension of the total path length). Then we consider Xn, the normalized version of I(Tn), for a sequence of trees Tn. For fixed Tn's, we prove a sufficient condition for Xn to converge in distribution. As an application, we identify the limit of Xn for complete b-ary trees. For Tn being split trees [16], we show that Xn converges to the unique solution of a distributional equation. Finally, when Tn's are conditional Galton–Watson trees, we show that Xn converges to a random variable defined in terms of Brownian excursions. By exploiting the connection between inversions and the total path length, we are able to give results that significantly strengthen and broaden previous work by Panholzer and Seitz [46].

This article presents a new method to automatically simplify English sentences. The approach is designed to reduce the number of compound clauses and nominally bound relative clauses in input sentences. The article provides an overview of a corpus annotated with information about various explicit signs of syntactic complexity and describes the two major components of a sentence simplification method that works by exploiting information on the signs occurring in the sentences of a text. The first component is a sign tagger which automatically classifies signs in accordance with the annotation scheme used to annotate the corpus. The second component is an iterative rule-based sentence transformation tool. Exploiting the sign tagger in conjunction with other NLP components, the sentence transformation tool automatically rewrites long sentences containing compound clauses and nominally bound relative clauses as sequences of shorter single-clause sentences. Evaluation of the different components reveals acceptable performance in rewriting sentences containing compound clauses but less accuracy when rewriting sentences containing nominally bound relative clauses. A detailed error analysis revealed that the major sources of error include inaccurate sign tagging, the relatively limited coverage of the rules used to rewrite sentences, and an inability to discriminate between various subtypes of clause coordination. Despite this, the system performed well in comparison with two baselines. This finding was reinforced by automatic estimations of the readability of system output and by surveys of readers’ opinions about the accuracy, accessibility, and meaning of this output.

This study adds to the literature on computer-mediated communication (CMC) by examining the impact of online voice recording (VR) activities and peer-to-peer videoconferencing (VC) conversations on the development of beginning Spanish learners’ speaking performance. Specifically, this paper explores (1) whether VR and VC activities promote oral proficiency, and if so, whether those gains can be seen both in presentational and interpersonal modes of communication; and (2) whether VR and VC activities foster oral proficiency in similar ways to face-to-face (F2F) communication. A quasi-experimental, pre-/post-test design was used in the study. Three sections of a first semester Spanish course were assigned to one of the following conditions: F2F, VR, and VC. Complexity, accuracy, and fluency measures were used to analyze learners’ speaking performance in the two tasks. A mixed effects model analysis was used to investigate differences across time as well as among groups. Results show that both F2F communication and VR activities promote complexity and fluency in presentational tasks and fluency in interpersonal tasks, although F2F produces superior results regarding complexity in presentational tasks. VC activities promote complexity and fluency in presentational tasks and complexity, accuracy, and fluency in interpersonal tasks. Overall, this study shows that medium is not merely a delivery device but has important implications for learning outcomes. In this sense, these findings contribute to answering the wider question of how the use of technology in second language instruction plays a decisive role in current teaching practices.

This paper introduces a novel 2R1T parallel manipulator redundantly actuated by pneumatic muscles for lower-limb rehabilitation. First, the conceptual design of the proposed 3-DOF parallel mechanism is presented. Then, the inverse kinematics and the generalized Jacobian analysis are carried out. Based on the generalized Jacobian and the constraint characteristics of the mechanism, the force/motion transmissibility of the redundantly actuated parallel mechanism is investigated via four individual cases without actuation redundancy, leading to a suitable local transmission index for the evaluation of kinematic performance of the proposed mechanism. Finally, the design variables are optimized by maximizing the mean value of the local transmission index with the aid of genetic algorithm. The numerical result shows that the proposed parallel mechanism can achieve a good kinematic performance in its task workspace.

A Q-learning approach is often used for navigation in static environments where state space is easy to define. In this paper, a new Q-learning approach is proposed for navigation in dynamic environments by imitating human reasoning. As a model-free method, a Q-learning method does not require the environmental model in advance. The state space and the reward function in the proposed approach are defined according to human perception and evaluation, respectively. Specifically, approximate regions instead of accurate measurements are used to define states. Moreover, due to the limitation of robot dynamics, actions for each state are calculated by introducing a dynamic window that takes robot dynamics into account. The conducted tests show that the obstacle avoidance rate of the proposed approach can reach 90.5% after training, and the robot can always operate below the dynamics limitation.

This paper presents the design, analysis, and experimental validation of a miniature modular inchworm robot (MMIR). Inchworm robots are capable of maneuvering in confined spaces due to their small size, a desirable characteristic for surveillance, exploration and search and rescue operations. This paper presents two generations of the MMIR (Version 1—V1 and Version 2—V2) that utilize anisotropic friction skin and an undulatory rectilinear gait to produce locomotion. This paper highlights design improvements and a multi-body dynamics approach to model and simulate the system. The MMIR V2 incorporates a slider-crank four-bar mechanism and a relative body revolute joint to produce high-frequency relative translation and rotation to increase forward velocity and enable turning capabilities. Friction analysis and locomotion experiments were conducted to assess the systems performance on various surfaces, validate the dynamic model and simulation results, and measure the maximum forward velocity. The MMIR V1 and V2 were able to achieve maximum forward velocities of 12.7 mm/s and 137.9 mm/s, respectively. These results are compared to reported results of similar robots published in the literature.

Consider the practically relevant situation in which a robotic system is assigned a task to be executed in an environment that contains moving obstacles. Generating collision-free motions that allow the robot to execute the task while complying with its control input limitations is a challenging problem, whose solution must be sought in the robot state space extended with time. We describe a general planning framework which can be tailored to robots described by either kinematic or dynamic models. The main component is a control-based scheme for producing configuration space subtrajectories along which the task constraint is continuously satisfied. The geometric motion and time history along each subtrajectory are generated separately in order to guarantee feasibility of the latter and at the same time make the scheme intrinsically more flexible. A randomized algorithm then explores the search space by repeatedly invoking the motion generation scheme and checking the produced subtrajectories for collisions. The proposed framework is shown to provide a probabilistically complete planner both in the kinematic and the dynamic case. Modified versions of the planners based on the exploration–exploitation approach are also devised to improve search efficiency or optimize a performance criterion along the solution. We present results in various scenarios involving non-holonomic mobile robots and fixed-based manipulators to show the performance of the planner.

Previous researches on analysis of stability of haptic simulation largely assume that the virtual environment is passive. But the virtual environment can become non-passive due to various reasons including discretization errors and interaction dynamics between virtual tools and objects. This paper provides an analysis of the stability and performance of the haptic simulation involving non-passive virtual environment. The dynamic interaction between the virtual tools and the objects is modeled using the two-port networks. The analysis is carried out using a velocity and force mapping matrix for six-DOF simulation. New stability condition resulting from the analysis is applied to an example simulation of a one-DOF virtual wall. Maximum stiffness satisfying the stability condition established in the previous literature, and the proposed condition is compared with the maximum stiffness experimentally determined with various time steps. The newly proposed stability condition manifests less standard deviation of errors than the widely applied absolute stability condition.

This paper presents a novel approach to implement bilateral control loops between local haptic devices and remote industrial manipulators using a layer of simulation and virtual reality. The remote scene of manipulation has been visualized in an open-source software environment, where forward and inverse kinematics of the manipulators can be computed. Therefore, the explicit knowledge of mathematical models of the robots is not required for the implementation of the proposed bilateral control schemes. A haptic coupling has been designed between the human operator and the task in the remote environment. Virtually introduced force feedback has contributed to the performance of the proposed bilateral loop by facilitating the adaptation of unexperienced human operators. Teleoperation of one remote manipulator has been experimentally demonstrated with the proposed controllers. Structural modularity of the bilateral haptic control schemes makes them directly extendable for the teleoperation of multiple collaborative robots. Stability and transparency of the proposed bilateral haptic controllers have been theoretically and experimentally investigated.

Standard conditionals $\varphi > \psi$, by which I roughly mean variably strict conditionals à la Stalnaker and Lewis, are trivially true for impossible antecedents. This article investigates three modifications in a doxastic setting. For the neutral conditional, all impossible-antecedent conditionals are false, for the doxastic conditional they are only true if the consequent is absolutely necessary, and for the metaphysical conditional only if the consequent is ‘model-implied’ by the antecedent. I motivate these conditionals logically, and also doxastically by properties of conditional belief and belief revision. For this I show that the Lewisian hierarchy of conditional logics can be reproduced within ranking semantics, provided we slightly stretch the notion of a ranking function. Given this, acceptance of a conditional can be interpreted as a conditional belief. The epistemic and the neutral conditional deviate from Lewis’ weakest system $V$, in that ID ($\varphi > \varphi$) or even CN ($\varphi > \top$) are dropped, and new axioms appear. The logic of the metaphysical conditional is completely axiomatised by $V$ to which we add the known Kripke axioms T5 for the outer modality. Related completeness results for variations of the ranking semantics are obtained as corollaries.

This paper presents an optimal trajectory planning method for industrial robots. The paper specially focuses on the applications of path tracking. The problem is to plan the trajectory with a specified geometric path, while allowing the position and orientation of the path to be arbitrarily selected within the specific ranges. The special contributions of the paper include (1) an optimal path tracking formulation focusing on the least time and energy consumption without violating the kinematic constraints, (2) a special mechanism to discretize a prescribed path integration for segment interpolation to fulfill the optimization requirements of a task with its constraints, (3) a novel genetic algorithm (GA) optimization approach that transforms a target path to be tracked as a curve with optimal translation and orientation with respect to the world Cartesian coordinate frame, (4) an integration of the interval analysis, piecewise planning and GA algorithm to overcome the challenges for solving the special trajectory planning and path tracking optimization problem. Simulation study shows that it is an insufficient condition to define a trajectory just based on the consideration that each point on the trajectory should be reachable. Simulation results also demonstrate that the optimal trajectory for a path tracking problem can be obtained effectively and efficiently using the proposed method. The proposed method has the properties of broad adaptability, high feasibility and capability to achieve global optimization.