Commonly, low completion rates in massive open online courses have called into question the quality of their learning materials and instruction. This paper attempts to identify crucial factors of engagement and retention in language massive open online courses (LMOOCs) in the context of the open online program of Icelandic Online, a self-guided course for second language learners of Icelandic. The study seeks to explore the impact of factors associated with the course’s instructional design on engagement and retention and reveal crucial determinants of attrition. The study depends on survey and tracking data from 400 learners and qualitative data from 62 informants in one course. It builds on previous studies on student engagement and retention in LMOOCs (Friðriksdóttir, 2018, 2019). The present study identified six content-specific factors that the majority of participants considered to be important for their motivation. Some factors, such as gradual and scaffolded presentation of input, had a positive impact on retention. Furthermore, statements from learners in the study who disengaged before completing show that non-course-related factors, such as time constraints, affect LMOOC retention. The study provides a new framework for how to promote student engagement and suggests specific strategies for other LMOOC developers.

COVID-19 is causing a significant burden on medical and healthcare resources globally due to high numbers of hospitalisations and deaths recorded as the pandemic continues. This research aims to assess the effects of climate factors (i.e., daily average temperature and average relative humidity) on effective reproductive number of COVID-19 outbreak in Wuhan, China during the early stage of the outbreak. Our research showed that effective reproductive number of COVID-19 will increase by 7.6% (95% Confidence Interval: 5.4% ~ 9.8%) per 1°C drop in mean temperature at prior moving average of 0–8 days lag in Wuhan, China. Our results indicate temperature was negatively associated with COVID-19 transmissibility during early stages of the outbreak in Wuhan, suggesting temperature is likely to effect COVID-19 transmission. These results suggest increased precautions should be taken in the colder seasons to reduce COVID-19 transmission in the future, based on past success in controlling the pandemic in Wuhan, China.

This paper introduces techniques to integrate WordNet into a Fuzzy Logic Programming system. Since WordNet relates words but does not give graded information on the relation between them, we have implemented standard similarity measures and new directives allowing the proximity equations linking two words to be generated with an approximation degree. Proximity equations are the key syntactic structures which, in addition to a weak unification algorithm, make a flexible query-answering process possible in this kind of programming language. This addition widens the scope of Fuzzy Logic Programming, allowing certain forms of lexical reasoning, and reinforcing Natural Language Processing (NLP) applications.

New computing and communications paradigms will result in traffic loads in information server systems that fluctuate over much broader ranges of time scales than current systems. In addition, these fluctuation time scales may only be indirectly known or even be unknown. However, we should still be able to accurately design and manage such systems. This paper addresses this issue: we consider an M/M/1 queueing system operating in a random environment (denoted M/M/1(R)) that alternates between HIGH and LOW phases, where the load in the HIGH phase is higher than in the LOW phase. Previous work on the performance characteristics of M/M/1(R) systems established fundamental properties of the shape of performance curves. In this paper, we extend monotonicity results to include convexity and concavity properties, provide a partial answer to an open problem on stochastic ordering, develop new computational techniques, and include boundary cases and various degenerate M/M/1(R) systems. The basis of our results are novel representations for the mean number in system and the probability of the system being empty. We then apply these results to analyze practical aspects of system operation and design; in particular, we derive the optimal service rate to minimize mean system cost and provide a bias analysis of the use of customer-level sampling to estimate time-stationary quantities.

There are growing efforts to mine public and common-sense semantic network databases for engineering design ideation stimuli. However, there is still a lack of design ideation aids based on semantic network databases that are specialized in engineering or technology-based knowledge. In this study, we present a new methodology of using the Technology Semantic Network (TechNet) to stimulate idea generation in engineering design. The core of the methodology is to guide the inference of new technical concepts in the white space surrounding a focal design domain according to their semantic distance in the large TechNet, for potential syntheses into new design ideas. We demonstrate the effectiveness in general, and use strategies and ideation outcome implications of the methodology via a case study of flying car design idea generation.

This paper proposes and evaluates swarming mechanisms of patrolling unmanned aerial vehicles (UAVs) that can collectively search a region for intruding UAVs. The main contributions include the development of multi-objective searching strategies and investigation of the required sensor configurations for the patrolling UAVs. Numerical results reveal that it is sometimes better to search through a region with a single swarm rather than multiple swarms deployed over sub-regions. Moreover, a large communication range does not necessarily improve search performances, and the patrolling swarm must have a speed close to the speed of the intruding UAVs to maximize the search performances.

A new approach to the design of a polytopic gain scheduled H∞ controller with pole placement for n-joint rigid robotic manipulators is presented. With linearization around the equilibrium manifold, the robotic system is transformed into a continuous linear parameter-varying (LPV) system with respect to the equilibrium manifold. A filter is introduced to obtain an augmented system, which is apt to have the polytopic gain scheduled controller designed. This system is put into a polytopic expression by a convex decomposition. Based on the concepts of quadratic D-stability and quadratic H∞ performance, the polytopic features are used to simplify the controller design to be a vertices’ controller design for the polytope. A state feedback gain, which satisfies H∞ performance and dynamic characteristics for each vertex of the polytope, is designed with a Linear Matrix Inequality (LMI) approach. A global continuous gain scheduled controller is then obtained by a synthesis of the vertex gains. Experiments demonstrate the feasibility of the designed controller.

A novel hyper-redundant manipulator named RT1 is presented in this paper. The key feature of RT1 is that all degrees of freedom (DOF) are actuated with only one motor, via specially designed hinge bar universal joints. The mechanism of RT1 which includes a special hinge bar universal joint, bend structure and motion diversion structure is described. RT1 is a discrete manipulator; the discrete working space is described, and the parameter optimization for kinematical redundancy resolution is also studied. In selecting the unit increment of joints angles as an optimizing parameter, the criterion used is to alter the design parameter as little as possible during the manipulator’s motion from the initial to the expected position.

This paper proposes an effective top-down design approach for the mechanical design for assembly of a four degree-offreedom revolute jointed robotic arm. The design process begins by specifying top-level design criteria and passing down these criteria from the top level of the manipulator’s structure to all of the subsequent components. With this proposed approach, the sequential design intents are captured, organized and implemented based on the entire system’s objectives, as opposed to the conventional design process which aims at individual components’ optimization. By considering the mechanical arm’s performance objectives, the design starts with modeling the integration of all the individual links constituting the manipulator. During the design process, modifications are made based on the integrated information of kinematics, dynamics, and structural analyses of the desired robot configurations as a whole. An optimum assembly design is then achieved with workable subdesigns of the manipulator components. As a result, the proposed approach for manipulator design yields substantially less number of iterations, automatic propagation of design changes, and great saving of design efforts. Thus, it is suitable and can be used as a guideline for design automation purposes of complex systems such as robotic arms.