Supporting New ODL Learners via Face-to-Face Academic Advising to Increase Retention: Sharing Open University Malaysia’s Experience

The last decade has witnessed an increased demand for tertiary education via Open and Distance Learning due to advance methods in technology for educators, administrators and learners that make a difference in effective instruction being delivered at a distance. More people too are beginning to embrace adult education and lifelong learning. Institutions that offer such mode of learning which include the Indira Gandhi National Open University, Islamic Azad University, Anadolu University and Allama Iqbal Open University, have all attained the ‘Mega’ university status with enrolment exceeding 1,000,000 learners. Attrition rate which can be based on completion or graduation rates of their learners is as low as 50 percent to as high as 80 percent. A high rate of attrition is always linked to the learners’ background, which includes their academic and social background, workplace settings, their ability to adapt to the new learning environment as well as their ability to finance their studies. As the cost of attracting learners to an ODL institution is higher than the cost of retaining them, thus the subject of retention has become a widely researched subject until today. At Open University Malaysia, the retention rate is within 69-79 percent among new learners and varies from one faculty to another and also varies for learners from different intakes. Data collected over the last five years revealed that attrition is highest for learners in their first semester as compared to later stages. Thus, several interventions were taken to reach out to new learners to provide support services to engage them actively in learning. Research conducted on 6,141 learners from all over Malaysia throughout a one-year period in 2011 found that early interventions that include face-toface meetings cum Academic Advising sessions conducted by Directors of Learning Centers, have successfully increased the retention rate of first semester learners to 80.1 percent in January 2012. This study is important as early intervention and engagement with new learners will help to improve retention rate and enable an ODL institution to remain sustainable. (abstract by authors

Variable Configuration Planner for Legged-Rolling Obstacle Negotiation Locomotion: Application on the CENTAURO Robot

Hybrid legged-wheeled robots are able to adapt their leg configuration and height to vary their footprint polygons and go over obstacles or traverse narrow spaces. In this paper, we present a variable configuration wheeled motion planner based on the A* algorithm. It takes advantage of the agility of hybrid wheeled-legged robots and plans paths over low-lying obstacles and in narrow spaces. By imposing a symmetry on the robot polygon, the computed plans lie in a low-dimensional search space that provides the robot with configurations to safely negotiate obstacles by expanding or shrinking its footprint polygon. The introduced autonomous planner is demonstrated using simulations and real-world experiments with the CENTAURO robot

Physiological Fluid Flow Moderates Fibroblast Responses to TGF-β1.

Fibroblasts are the major cellular component of connective tissue and experience mechanical perturbations due to matrix remodelling and interstitial fluid movement. Transforming growth factor β1 (TGF-β1) can promote differentiation of fibroblasts in vitro to a contractile myofibroblastic phenotype characterised by the presence of α-smooth muscle actin (α-SMA) rich stress fibres. To study the role of mechanical stimulation in this process, we examined the response of primary human fibroblasts to physiological levels of fluid movement and its influence on fibroblast differentiation and responses to TGF-β1. We report that in both oral and dermal fibroblasts, physiological levels of fluid flow induced widespread changes in gene expression compared to static cultures, including up-regulation of genes associated with TGFβ signalling and endocytosis. TGF-β1, activin A and markers of myofibroblast differentiation including α-SMA and collagen IA1 were also increased by flow but surprisingly the combination of flow and exogenous TGF-β1 resulted in reduced differentiation. Our findings suggest this may result from enhanced internalisation of caveolin and TGF-β receptor II. These findings suggest that a) low levels of fluid flow induce myofibroblast differentiation and b) fluid flow antagonises the fibroblast response to pro-differentiation signals such as TGF-β1. We propose that this may be a novel mechanism by which mechanical forces buffer responses to chemical signals in vivo, maintaining a context-specific fibroblast phenotype. This article is protected by copyright. All rights reserved

A Study on Low-Drift State Estimation for Humanoid Locomotion, Using LiDAR and Kinematic-Inertial Data Fusion

Several humanoid robots will require to navigate in unsafe and unstructured environments, such as those after a disaster, for human assistance and support. To achieve this, humanoids require to construct in real-time, accurate maps of the environment and localize in it by estimating their base/pelvis state without any drift, using computationally efficient mapping and state estimation algorithms. While a multitude of Simultaneous Localization and Mapping (SLAM) algorithms exist, their localization relies on the existence of repeatable landmarks, which might not always be available in unstructured environments. Several studies also use stop-and-map procedures to map the environment before traversal, but this is not ideal for scenarios where the robot needs to be continuously moving to keep for instance the task completion time short. In this paper, we present a novel combination of the state-of-the-art odometry and mapping based on LiDAR data and state estimation based on the kinematics-inertial data of the humanoid. We present experimental evaluation of the introduced state estimation on the full-size humanoid robot WALK-MAN while performing locomotion tasks. Through this combination, we prove that it is possible to obtain low-error, high frequency estimates of the state of the robot, while moving and mapping the environment on the go

Entangled quantum tunneling of two-component Bose-Einstein condensates

We examine the quantum tunneling process in Bose condensates of two interacting species trapped in a double well configuration. We discover the condition under which particles of different species can tunnel as pairs through the potential barrier between two wells in opposition directions. This novel form of tunneling is due to the interspecies interaction that eliminates the self- trapping effect. The correlated motion of tunneling atoms leads to the generation of quantum entanglement between two macroscopically coherent systems.Comment: 4 pages, 3 figure

A probabilistic approach for quantitative identification of multiple delaminations in laminated composite beams using guided waves

Available online 16 September 2016In this study a probabilistic approach is proposed to identify multiple delaminations in laminated composite beams using guided waves. The proposed method is a model-based approach, which provides a quantitative identification of the delaminations. This study puts forward a practical damage identification method, and hence, it can identify multiple delaminations using guided wave signal measured at a single measurement point on the laminated composite beams. The proposed method first determines the number of delaminations using Bayesian model class selection method. The Bayesian statistical framework is then employed to not only identify the delamination locations, lengths and through-thickness locations, but also quantify the associated uncertainties, which provides valuable information for engineers in making decision on necessary remedial work. In addition the proposed method employs the time-domain spectral finite element method and Bayesian updating with Subset simulation to further improve the computational efficiency. The proposed probabilistic approach is verified and demonstrated using data obtained from numerical simulations, which consider both measurement noise and modeling error, and experimental data. The results show that the proposed method can accurately determine the number of delaminations, and the identified delamination locations, lengths and through-thickness locations are closed to the true values.Shuai He, Ching-Tai N

Quasi-spin Model for Macroscopic Quantum Tunnelling between Two Coupled Bose-Einstein Condensates

The macroscopic quantum tunneling between two coupled Bose-Einstein condensates (BEC) (radio-frequency coupled two-component BECs or two BECs confined in a double-well potential) is mapped onto the tunneling of an uniaxial spin with an applied magnetic field. The tunneling exponent is calculated with an imaginary-time path-integral method. In the limit of low barrier, the dependence of tunneling exponent on the system parameters is obtained, and the crossover temperature from thermal regime to quantum regime is estimated. The detailed information about the tunnelling will give help to control population conversion between coupled BECs and realize quantum computation with coupled BECs.Comment: 20 pages, 4 figures, accepted by Phys.Rev.

Guided wave-based identification of multiple cracks in beams using a Bayesian approach

Available online 26 July 2016A guided wave damage identification method using a model-based approach is proposed to identify multiple cracks in beam-like structures. The guided wave propagation is simulated using spectral finite element method and a crack element is proposed to take into account the mode conversion effect. The Bayesian model class selection algorithm is employed to determine the crack number and then the Bayesian statistical framework is used to identify the crack parameters and the associated uncertainties. In order to improve the efficiency and ensure the reliability of identification, the Transitional Markov Chain Monte Carlo (TMCMC) method is implemented in the Bayesian approach. A series of numerical case studies are carried out to assess the performance of the proposed method, in which the sensitivity of different guided wave modes and effect of different levels of measurement noise in identifying different numbers of cracks is studied in detail. The proposed method is also experimentally verified using guided wave data obtained from laser vibrometer. The results show that the proposed method is able to accurately identify the number, locations and sizes of the cracks, and also quantify the associated uncertainties. In addition the proposed method is robust under measurement noise and different situations of the cracks.Shuai He, Ching-Tai N