We study the complexity of deciding the equality of streams specified by systems of equations. There are several notions of stream models in the literature, each generating a different semantics of stream equality. We pinpoint the complexity of each of these notions in the arithmetical or analytical hierarchy. Their complexity ranges from low levels of the arithmetical hierarchy such as Π02 for the most relaxed stream models, to levels of the analytical hierarchy such as Π11 and up to subsuming the entire analytical hierarchy for more restrictive but natural stream models. Since all these classes properly include both the semi-decidable and co-semi-decidable classes, it follows that regardless of the stream semantics employed, there is no complete proof system or algorithm for determining equality or inequality of streams. We also discuss several related problems, such as the existence and uniqueness of stream solutions for systems of equations, as well as the equality of such solutions.

In this paper, the backstepping strategy is used to design an adaptive tracking controller for rigid-link electrically driven robots in the presence of parametric uncertainties in kinematics, manipulator dynamics, and actuator dynamics. To avoid acceleration measurements, two techniques are exploited. One technique adds compensation control terms to the control law signal. The other uses a linear in variable property of the Jacobian matrix. Global asymptotic convergence of the end-effector motion tracking errors is shown via Lyapunov analysis. Simulation results are presented to show the effectiveness of the proposed control scheme.

This paper focuses on practical application of a mobile manipulator by presenting the development and control of a two-wheel mobile robot with two arms called a balancing service robot (BSR) designated for indoor services. The mobile manipulator requires not only robust balancing position control but also force control to interact with objects. Movements with two wheels are controlled to satisfy stable balancing control for navigation and manipulation with two arms to perform given tasks. The robot is required to deal with external forces to maintain balance. The position-based impedance force control method (the admittance control) is utilized by filtering the force with the impedance function to react to the applied force from the operator. Experimental studies of navigation control under balancing condition and interacting control with a human operator are demonstrated. Experimental results confirm that the robot has smooth reaction against the disturbance induced by the applied external force.

Redundant actuation for the parallel kinematic machine (PKM) is a well-known technique for overcoming general drawbacks of the PKM by helping it to avoid singularity and enhance stiffness characteristics, among others. Torque distribution plays a critical role in redundant actuation because this actuation causes the PKM to consume too much energy or put a substantial amount of stress on joints and links. This paper proposes a new torque distribution method for reducing the maximum torque of the actuator of a planar PKM. Here the main idea behind the proposed method is the use of superposition of a particular solution for a non-redundant case and an optimized null-space solution for a redundant case with a constant coefficient. The optimal value of a null-space solution can be easily determined by checking only the intersection points of the profile of the actuator's torque as the coefficient varies. We consider three cases of planar PKMs—2-, 3-, and 4-RRR PKMs—and present a detailed procedure for deriving a kinematic solution for the 2-RRR PKM based on Screw theory. We compare the proposed method with the minimum-norm pseudo-inverse method and assess a limitation of the proposed method. The torque distribution algorithm can be used to determine the number of actuators in an efficient manner and to reduce energy consumption.

Rapid and efficient dynamic stability control has been one of the important motivations in legged robot research, especially for legged robots running at high speed and/or on rough terrain. This paper presents a feasible control strategy, named Hybrid Feedback Control (HFC), for running systems based on the spring-loaded inverted pendulum principle (SLIP). The HFC strategy, which comprises two modules (i.e., touchdown angle control and energy compensation), predicts and regulates touchdown angle of the current cycle and need-to-complement energy input of the next cycle through hybrid feedback of flying apex state. This strategy can significantly reduce the computational complexity and enable the system to quickly converge to its control target, meeting the requirements of real-time control. Simulation experiments on various terrains were conducted to verify the adaptability of our HFC strategy. Results of these simulation experiments show that the approach herein can realize the periodical stability control of SLIP systems on different terrain conditions quickly and effectively.

This study aims to investigate barriers to the adoption of information and communication technology (ICT) for teachers of Chinese as a foreign language (CFL) in US universities. Although the development of ICT for teaching is growing, few published studies address ICT specifically regarding CFL teaching. Therefore, this study has reviewed the existing ICT literature's treatment of important ICT-related matters, including barrier factors, and has examined them in the context of CFL teaching. The current study features a mixed method, consisting of a survey and semi-structured interviews. Of the 47 CFL teachers who participated in the study, five volunteered for in-depth interviews. According to our findings, the most critical barriers to these CFL teachers’ adoption of ICT were insufficient support and insufficient time for developing technology-driven pedagogy and activities. These issues are reflected in CFL teachers’ unique subject expertise and workloads in existing universities’ curricula and approaches to instruction. In addition, age influences CFL teachers’ confidence in their use of ICT for the preparation of subject material and for teaching, whereas gender influences their willingness to spend time working on ICT.

While researchers have examined the effectiveness of various online gloss types on incidental L2 vocabulary learning, little research on online gloss languages has been conducted. Previous attempts which compared the effects of L1 and L2 glosses have reported mixed results. To fill the gaps, this study examined the effectiveness of Chinese and English e-glosses on incidental English vocabulary learning on a less-researched student group in CALL – junior high-school English-as-a-foreign-language (EFL) students. Seventy-eight students with Chinese as their first language read two online passages with either Chinese (L1) or English (L2) glosses. They were divided into four treatment groups: (1) high-proficiency students receiving L1 gloss before L2 gloss (n = 19), (2) high-proficiency students receiving L2 gloss before L1 gloss (n = 19), (3) low-proficiency students receiving L1 gloss before L2 gloss (n = 20), and (4) low-proficiency students receiving L2 gloss before L1 gloss (n = 20). After reading, the students were assessed with a vocabulary test which contained a definition-supply part and a cloze part serving as both post-tests and delayed post-tests. Repeated-measures analyses of variance were utilized to analyze the score data. Significant differences were found not only among the four groups but also between the two post-tests. Overall the high proficiency groups performed better in the post-tests, but the high proficiency group who received English glosses remembered more words in the delayed post-test than the high proficiency group who received Chinese glosses. The results show that as learners’ proficiency increases, they may be able to make better use of the L2 conceptual links for word retention and learning. The conclusions support the usefulness of both Chinese and English e-glosses which should be selected based on learners’ proficiency level.

This study presents novel robotic therapy control algorithms for upper-limb rehabilitation, using newly developed passive and progressive resistance therapy modes. A fuzzy-logic based proportional-integral-derivative (PID) position control strategy, integrating a patient's biomechanical feedback into the control loop, is proposed for passive movements. This allows the robot to smoothly stretch the impaired limb through increasingly rigorous training trajectories. A fuzzy adaptive impedance force controller is addressed in the progressive resistance muscle strength training and the adaptive resistive force is generated according to the impaired limb's muscle strength recovery level, characterized by the online estimated impaired limb's bio-damping and bio-stiffness. The proposed methods are verified with a custom constructed therapeutic robot system featuring a Barrett WAM™ compliant manipulator. Twenty-four recruited stroke subjects were randomly allocated in experimental and control groups and enrolled in a 20-week rehabilitation training program. Preliminary results show that the proposed therapy control strategies can not only improve the impaired limb's joint range of motion but also enhance its muscle strength.

We present a control method for a simple limit-cycle bipedal walker that uses adaptive frequency oscillators (AFOs) to generate stable gaits. Existence of stable limit cycles is demonstrated with an inverted-pendulum model. This model predicts a proportional relationship between hip torque amplitude and stride frequency. The closed-loop walking control incorporates adaptive Fourier analysis to generate a uniform oscillator phase. Gait solutions (fixed points) are predicted via linearization of the walker model, and employed as initial conditions to generate exact solutions via simulation. Global stability is determined via a recursive algorithm that generates the approximate basin of attraction of a fixed point. We also present an initial study on the implementation of AFO-based control on a bipedal walker with realistic mass distribution and articulated knee joints.

Learning probabilistic logic programming languages is receiving an increasing attention, and systems are available for learning the parameters (PRISM, LeProbLog, LFI-ProbLog and EMBLEM) or both structure and parameters (SEM-CP-logic and SLIPCASE) of these languages. In this paper we present the algorithm SLIPCOVER for “Structure LearnIng of Probabilistic logic programs by searChing OVER the clause space.” It performs a beam search in the space of probabilistic clauses and a greedy search in the space of theories using the log likelihood of the data as the guiding heuristics. To estimate the log likelihood, SLIPCOVER performs Expectation Maximization with EMBLEM. The algorithm has been tested on five real world datasets and compared with SLIPCASE, SEM-CP-logic, Aleph and two algorithms for learning Markov Logic Networks (Learning using Structural Motifs (LSM) and ALEPH++ExactL1). SLIPCOVER achieves higher areas under the precision-recall and receiver operating characteristic curves in most cases.

Mobile Ad hoc Networks have attracted much attention in the last years, since they allow the coordination and cooperation between agents belonging to a multi-robot system. However, initially deploying autonomously a wireless sensor robot network in a real environment has not taken the proper attention. Moreover, maintaining the connectivity between agents in real and complex environments is an arduous task since the strength of the connection between two nodes (i.e., robots) can change rapidly in time or even disappear. This paper compares two autonomous and realistic marsupial strategies for initial deployment in unknown scenarios, in the context of swarm exploration: Random and Extended Spiral of Theodorus. These are based on a hierarchical approach, in which exploring agents, named scouts, are autonomously deployed through explicit cooperation with supporting agents, denoted as rangers. Experimental results with a team of heterogeneous robots are conducted using both real and virtual robots. Results show the effectiveness of the methods, using a performance metric based on dispersion. Conclusions drawn in this work pave the way for a whole series of possible new approaches.

This paper presents findings from a study investigating young English language learners (YELLs) in Sweden in 4th grade (N = 76, aged 10–11). Data were collected with the help of a questionnaire and a one-week language diary. The main purpose was to examine the learners’ L2 English language-related activities outside of school in general, and their use of computers and engagement in playing digital games in particular. A comparison is made between language-related activities in English, Swedish, and other languages. Another purpose was to see whether there is a relationship between playing digital games and (a) gender, (b) L1, (c) motivation for learning English, (d) self-assessed English ability, and (e) self-reported strategies for speaking English. In order to do so, the sample was divided into three digital game groups, (1) non-gamers, (2) moderate, and (3) frequent gamers (≥4 hours/week), based on diary data (using self-reported times for playing digital games in English). Results showed that YELLs are extensively involved in extramural English (EE) activities (M = 7.2 hrs/w). There are statistically significant gender differences, boys (11.5 hrs/w) and girls (5.1 hrs/w; p < .01), the reason being boys’ greater time investment in digital gaming and watching films. The girls, on the other hand, spent significantly more time on pastime language-related activities in Swedish (11.5 hrs/w) than the boys (8.0 hrs/w; p < .05), the reason being girls’ greater time investment in facebooking. Investigation of the digital game groups revealed that group (1) was predominantly female, (2) a mix, and (3) predominantly male. YELLs with an L1 other than Swedish were overrepresented in group (3). Motivation and self-assessed English ability were high across all groups. Finally, regarding the self-reported strategies, code-switching to one's L1 was more commonly reported by non- and moderate gamers than frequent gamers.

In this paper, a new sensor-based approach called nonholonomic random replanner (NRR) is presented for motion planning of car-like mobile robots. The robot is incrementally directed toward its destination using a nonholonomic rapidly exploring random tree (RRT) algorithm. At each iteration, the robot's perceived map of the environment is updated using sensor readings and is used for local motion planning. If the goal was not visible to the robot, an approximate path toward the goal is calculated and the robot traces it to an extent within its sensor range. The robot updates its motion to goal through replanning. This procedure is repeated until the goal lies within the scope of the robot, after which it finds a more precise path by sampling in a tighter Goal Region for the nonholonomic RRT. Three main replanning strategies are proposed to decide when to perform a visibility scan and when to replan a new path. Those are named Basic, Deliberative and Greedy strategies, which yield different paths. The NRR was also modified for motion planning of Dubin's car-like robots. The proposed algorithm is probabilistically complete and its effectiveness and efficiency were tested by running several simulations and the resulting runtimes and path lengths were compared to the basic RRT method.