Analysis of an extended pressure finite element space for two-phase incompressible flows

We consider a standard model for incompressible two-phase flows in which a localized force at the interface describes the effect of surface tension. If a level set (or VOF) method is applied then the interface, which is implicitly given by the zero level of the level set function, is in general not aligned with the triangulation that is used in the discretization of the flow problem. This non-alignment causes severe difficulties w.r.t. the discretization of the localized surface tension force and the discretization of the flow variables. In cases with large surface tension forces the pressure has a large jump across the interface. In standard finite element spaces, due to the non-alignment, the functions are continuous across the interface and thus not appropriate for the approximation of the discontinuous pressure. In many simulations these effects cause large oscillations of the velocity close to the interface, so-called spurious velocities. In [6] it is shown that an extended finite element space (XFEM) is much better suited for the discretization of the pressure variable. In this paper we derive important properties of the XFEM space. We present (optimal) approximation error bounds and prove that the diagonally scaled mass matrix has a uniformly bounded spectral condition number. Results of numerical experiments are presented that illustrate properties of the XFEM space.     

Motivating agents in software tutorials

Pedagogical agents can provide important support for the user in human–computer interaction systems. This paper examines whether a supplementary, motivating agent in a print tutorial can enhance student motivation and learning in software training. The agent served the role of motivator, attending the students to issues of task relevance and self-efficacy. The agent was presented in the tutorial by means of images and written messages. An experiment compared the agent condition with a no-agent (control) condition. Participants were 49 students (mean age 11.3 years) from the upper grades of elementary school. Data on motivation and learning were gathered before, during and after training. The findings revealed that students in the agent condition did significantly better on skills measures during and after training (i.e., performance indicators, posttest, and retention test). In addition, marginally significant differences favoring these students were found for flow experience during training and for motivational gains on task relevance and self-efficacy after training. The design strategies of the motivating agent are considered relevant for the creation of Animated Pedagogical Agents.     

The effects of reviews in video tutorials

This study investigates how well a video tutorial for software training that is based on Demonstration‐Based Teaching supports user motivation and performance. In addition, it is studied whether reviews significantly contribute to these measures. The Control condition employs a tutorial with instructional features added to a dynamic task demonstration. The Review condition additionally includes video reviews. Participants were 55 seventh graders who viewed task demonstrations (and reviews) followed by practice. Both tutorials increased motivation (i.e., task relevance and self‐efficacy) and performance. In addition, the Review condition had significantly better results for training time, self‐efficacy and scores on an immediate post‐test. Reviews have rarely been studied in dynamic visualizations. The present study suggests that there may be important advantages to be gained from concluding a demonstration video with a summary of the main points.     

Computer diagnosis of primary headaches in children

In the area of primary headaches in children several diagnostic classes (migraine, psychogenic) and other nondefined headaches are recognized. Their clinical diagnosis is complex and still not standardized. We present a Personal Computer program for diagnosing types of primary headaches in children. The program calls for the input of each patient's score on five clinical variables chosen by means of discriminant analysis, and the output gives a clinical diagnosis along with its posterior probability. The program was used on an initial group of 223 pediatric patients and was cross-validated at a first level on a second group of 90 patients and at a second level on a third group of 70 patients. The total correct classification figures were 85.2, 90, and 87.1%, respectively.     

Mobile‐Based micro‐Learning and Assessment: Impact on learning performance and motivation of high school students

Mobile‐based micro‐learning has gained a lot of attention lately, especially for work‐based and corporate training. It combines features of mobile learning and micro‐learning to deliver small learning units and short‐term learning activities. The current study uses the lens of the Self‐Determination Theory of motivation and proposes a series of Mobile‐Based micro‐Learning and Assessment (MBmLA) homework activities to improve high school students' motivation and learning performance in science. An experiment was conducted to evaluate the effectiveness of the proposed approach. One hundred and eight students of a senior‐level high school in Europe were randomly assigned into either a control condition (conventional paper‐based homework approach) or an experimental (MBmLA approach) condition. The study carried out for a period of 5 weeks. From the experimental results, it was found that, in comparison to the conventional paper‐based approach, the proposed MBmLA approach enhanced students' basic psychological needs of self‐perceived autonomy, competence, and relatedness and improved students' exam performance in terms of factual knowledge. Moreover, students self‐reported greater learning satisfaction with the mobile‐based microassessment and micro‐learning homework tasks. Implications on educational practices as well as future research are discussed.     

Effect of reduction of slider pitch-mode vibration on magnetic-recording performance at low-clearance head–disk interface

Aiming at improvements of both stability of slider flying and magnetic-recording performance under a low-clearance condition, a “narrow-grooved slider” was constructed and demonstrated at drive level. The proposed slider has narrow grooves on its center pad of an air-bearing surface for attaining a high-damping effect on pitch-mode resonant vibration of the air bearing. The relationship between the high-damping effect and the pitch-mode resonant vibration was studied, and the magnetic-recording performance at the lube/slider interaction regime was improved. In this study, first, flying-height modulation (FHM) of the slider was analyzed in the frequency domain by using a fast Fourier transform. Compared with the narrow-grooved slider, a non-grooved slider showed a larger increase in high-frequency modulation of gap flying height when the clearance was reduced to near “zero” at which the slider is starting to interact with lube. Furthermore, by means of drive-level experiments, sector error rate (SER) as a function of flying clearance was investigated. Under a low gap flying height condition, HDDs with the non-grooved slider showed slight SER degradation during slider/lube interaction. However, the narrow-grooved slider did not show any SER degradation at the same gap flying height; the damping effect of the narrow-grooved slider suppressed high-frequency FHM, thereby preventing SER degradation in the slider/lube interaction region.     

Min-Max MPC based on an upper bound of the worst case cost with guaranteed stability. Application to a pilot plant

Min-Max MPC (MMMPC) offers the possibility to consider disturbances and uncertainties in the mathematical model used to predict the future trajectory of the system. The explicit consideration of disturbances and uncertainties in order to obtain a more robust control performance complicates the practical implementation of MMMPC due to the high computational burden required to compute the control law. The computational complexity of the optimization problem can be reduced by using approximate solutions or upper bounds of the worst case cost of the objective function. A computationally efficient MMMPC strategy based on such an upper bound was presented in a previous work also published in this journal (see Section 1). One of the main drawbacks of that strategy is the lack of a stability guarantee. In this paper it is shown that input-to-state practical stability of the MMMPC strategy can be guaranteed if a certain initial condition and a semi-feedback approach are used. Furthermore, the MMMPC strategy is validated in experiments with a continuous stirred tank reactor in which the temperature of the reactor is controlled. The behavior of the system and the controller are illustrated by means of experimental results.     

Biotechnical measurement and software system controlled features for determining the level of psycho-emotional tension on man-machine systems by fuzzy measures

A new software technique for determining emotional tension on humans is developed by means of psychological tests connected with the psycho-emotional sphere and on indicators characterizing the state of a subject’s visual attention. Each of these two areas determines several factors for psycho-emotional tension. The level of tension is determined as an aggregate of these two components with the rules of fuzzy logic. The membership functions and solving rules for the psychological tests, and for the state of visual attention, are constructed using fuzzy logic theory. It is shown that the resulting method can be used as an informative feature for prediction of many properties, such as the situational awareness (training and experience) of an operator and the operator’s individual capacity to function (mental-physiological limits). The second group of indicators characterize properties such as switchable attention (the ability to switch attention) (SWA), concentration (ability to concentrate) (CNA), stability of visual attention (STA) and parameters determining the state of memory. One of the most important issues for man-machine systems is to evaluate the performance of operators under abnormal conditions such as stress or tension.     

A sensor fusion and support vector machine based approach for recognition of complex machining conditions

During the machining process of thin-walled parts, machine tool wear and work-piece deformation always co-exist, which make the recognition of machining conditions very difficult. Existing machining condition monitoring approaches usually consider only one single condition, i.e., either tool wear or work-piece deformation. In order to close this gap, a machining condition recognition approach based on multi-sensor fusion and support vector machine (SVM) is proposed. A dynamometer sensor and an acceleration sensor are used to collect cutting force signals and vibration signals respectively. Wavelet decomposition is utilized as a signal processing method for the extraction of signal characteristics including means and variances of a certain degree of the decomposed signals. SVM is used as a condition recognition method by using the means and variances of signals as well as cutting parameters as the input vector. Information fusion theory at the feature level is adopted to assist the machining condition recognition. Experiments are designed to demonstrate and validate the feasibility of the proposed approach. A condition recognition accuracy of about 90 % has been achieved during the experiments.     

Person- versus computer-mediated feedback

The effects of feedback provided by a person versus that provided by a computer on performance, motivation, and feedback seeking were studied. Employing a 2 × 3 experimental design, subjects were assigned to one of three feedback conditions: (a) no feedback, (b) feedback only upon request, and (c) automatic feedback with feedback provided either by a person or a computer. The results indicate that (a) subjects are more likely to seek feedback from a computer than from another person; (b) feedback from a person causes a decline in performance relative to a condition where a person is present but does not deliver feedback; (c) both human- and computer-mediated feedback reduce motivation in comparison to a control group that receives no feedback; and (d) personality — in this case, self-esteem and public and private self-consciousness — interacts with the receipt of person-mediated feedback to negatively affect performance.     

The roles of task difficulty and prior videogame experience on performance and motivation in instructional videogames

Videogames are an increasingly popular instructional tool. This research investigated how various strategies for modifying task difficulty in instructional videogames impact learner performance and motivation. Further, the influence of prior videogame experience on these learning outcomes was examined, as well as the role prior experience played in determining the optimal approach for adjusting task difficulty. Participants completed a game-based training task under one of four task difficulty conditions: static, increasing, adaptive-low and adaptive-high. All participants completed an identical pre-training trial, 10 practice trials varying in difficulty level according to condition, and a final performance trial. Results demonstrate that learner performance and motivation significantly improved in all difficulty conditions. Further, prior videogame experience was found to significantly influence these learning outcomes and a three-way interaction was detected between performance, task difficulty condition, and experience. The results of this research provide information useful to instructional videogame developers and instructors utilizing videogames as instructional tools.     

Stability and performance of distributed production control methodsbased on continuous-flow models

Investigates the stability and performance of a two-level production control method for part release, routing, and machine scheduling in manufacturing systems. At the first level (off line), a continuous-flow (fluid) approximation of the production control problem is formulated and solved as a linear program. At the second level (on line), simple distributed control policies are used to track the solution of the continuous-flow model of level one. A major research issue concerns the potential instability of decentralized tracking policies due to the discreteness of the decision space (caused by the sequential nature of operations and their discrete processing times). The author considers a broad class of distributed tracking policies, which is called nonidling-nonexceeding (NINE) and finds a sufficient condition for their stability. The results show the NINE policies potential instability for nonacyclic systems due to machine starvation, which is caused by tracking delays induced by the discrete nature of operations. The sufficient stability condition takes a familiar form, namely that, the largest eigenvalue of a matrix-which captures the dynamics of tracking delays in the system-must be less than one. It ensures the contraction of tracking delays in the feedback loops of material flow in the system. When this condition is met, an upper bound on the performance of the policy is readily obtained. It is further shown that any nonidling dispatching policy can be considered as a special NINE policy, and thus the same stability and performance results apply to the class of all nonidling policies. The author also investigates NINE policies with buffer priorities and shows that a NINE policy with certain buffer priority ordering is always stable. Simulation experiments show that near-zero work-in-process and finished-parts' inventory can be achieved with the method even for demands that are very close to the production capacity of the system     

A Human–Computer Cooperation Fuzzy c‐Means Clustering with Interval‐Valued Weights

In this paper, a fuzzy c‐means clustering algorithm based on interval‐valued weights is proposed for improving clustering performance. In the proposed algorithm, the interval‐valued weights are first constructed by synergy of the ReliefF algorithm and the analytic hierarchy process (AHP) method, and then they are transformed into a constraint condition associating with each weight variable in the weighted clustering objective function. In the sequence, the weighted clustering objective function is solved by combining the Lagrange multiplier method with the gradient‐based iteration computation. In the whole process of algorithm iteration, a compulsion strategy with human–computer cooperation is adopted to ensure each weight variable satisfies interval constraint itself. Three well‐known data set are used to perform profound experiments. Experimental results clearly show that the proposed algorithm has better clustering performance than other the weighted fuzzy c‐means clustering algorithm.     

Performance variability in software product lines: proposing theories from a case study

In the software product line research, product variants typically differ by their functionality and quality attributes are not purposefully varied. The goal is to study purposeful performance variability in software product lines, in particular, the motivation to vary performance, and the strategy for realizing performance variability in the product line architecture. The research method was a theory-building case study that was augmented with a systematic literature review. The case was a mobile network base station product line with capacity variability. The data collection, analysis and theorizing were conducted in several stages: the initial case study results were augmented with accounts from the literature. We constructed three theoretical models to explain and characterize performance variability in software product lines: the models aim to be generalizable beyond the single case. The results describe capacity variability in a base station product line. Thereafter, theoretical models of performance variability in software product lines in general are proposed. Performance variability is motivated by customer needs and characteristics, by trade-offs and by varying operating environment constraints. Performance variability can be realized by hardware or software means; moreover, the software can either realize performance differences in an emergent way through impacts from other variability or by utilizing purposeful varying design tactics. The results point out two differences compared with the prevailing literature. Firstly, when the customer needs and characteristics enable price differentiation, performance may be varied even with no trade-offs or production cost differences involved. Secondly, due to the dominance of feature modeling, the literature focuses on the impact management realization. However, performance variability can be realized through purposeful design tactics to downgrade the available software resources and by having more efficient hardware.     

Motivation,engagement, and performance across multiple virtual reality sessions and levels of immersion

This study investigated changes in learners' motivation, engagement, performance, and spatial reasoning over time and across different levels of virtual reality (VR) immersion. Undergraduate participants explored a virtual solar system via a moderately immersive or highly immersive VR platform over three sessions. In a third condition, participants initially learned with moderate immersion and transitioned to higher immersion after the second session. Following research on novelty effects, we explored whether subjective experiences and performance would decline over time (e.g., decreasing motivation or performance) as participants became familiar with the virtual environment and tools. However, we hypothesized that transitional immersion (i.e., switching from moderate to higher immersion) might lead to a renewed sense of novelty. Results suggested that both moderate and higher levels of immersion were motivating, engaging, and supportive of learning. In contrast to predictions based on novelty effects, these outcomes did not decline overall as learners gained familiarity with the systems. However, transitional immersion emerged as a promising and testable pedagogical approach for future VR education. All participants also showed gains in spatial reasoning.     

Working in a moving environment

The present paper provides a review of research and theories concerning the question of how and why working in a moving environment may affect performance. It is argued that performance decrements can be expected to occur as a result of general factors or as a result of specific impairments of particular human skills. General effects happen when environmental motion, simulated or real, reduces motivation (due to motion sickness), increases fatigue (due to increased energy requirements), or creates balance problems. Specific effects of moving environments on task performance may only be expected through biomechanical influences on particular skills such as perception (interference with oculomotor control) or motor skills (such as manual tracking). There is no evidence for direct effects of motion on performance in purely cognitive tasks.     

Evaluating the benefits of introducing “BIM” based on Revit in construction courses,without changing the course schedule

Recently, the building industry has shown great interest in building information modeling (BIM) due to the many benefits BIM provides. During the last decade, the government of Dubai has been working toward a BIM environment, where any new building project that is ten floors or higher shall be submitted in BIM format. The need for BIM creates more job opportunities for technicians with BIM skills. This inflates the need to prepare related field engineers with BIM background before graduation. This report analyzes the implementation of BIM in a construction course, which is currently using AutoCAD, by splitting the laboratory skills. Through this implementation, we will test whether adding BIM based on Revit to a currently existent course will improve the students’ motivation, performance and satisfaction. The authors use the results of the Architectural Engineering (AE) students at the United Arab Emirates University (UAEU) in construction courses to study the performance before and after implementing BIM. The authors found some issues, which can decrease the students’ performance with a 97% certainty. The students’ motivation and satisfaction was tested using a pre-test/post-test quasi-experiment design. The tests showed that BIM based on Revit reduces student performance time while increasing student motivation and satisfaction. The causes behind the last statement were analyzed with the use of interviews with related students.     

The impact of background speech varying in intelligibility: effects on cognitive performance and perceived disturbance

Noise abatement in office environments often focuses on the reduction of background speech intelligibility and noise level, as attainable with frequency-specific insulation. However, only limited empirical evidence exists regarding the effects of reducing speech intelligibility on cognitive performance and subjectively perceived disturbance. Three experiments tested the impact of low background speech (35 dB(A)) of both good and poor intelligibility, in comparison to silence and highly intelligible speech not lowered in level (55 dB(A)). The disturbance impact of the latter speech condition on verbal short-term memory (n=20) and mental arithmetic (n=24) was significantly reduced during soft and poorly intelligible speech, but not during soft and highly intelligible speech. No effect of background speech on verbal-logical reasoning performance (n=28) was found. Subjective disturbance ratings, however, were consistent over all three experiments with, for example, soft and poorly intelligible speech rated as the least disturbing speech condition but still disturbing in comparison to silence. It is concluded, therefore, that a combination of objective performance tests and subjective ratings is desirable for the comprehensive evaluation of acoustic office environments and their alterations.     

Digital game-based learning: Impact of instructions and feedback on motivation and learning effectiveness

Although many studies have investigated the effects of digital game-based learning (DGBL) on learning and motivation, its benefits have never been systematically demonstrated. In our first experiment, we sought to identify the conditions under which DGBL is most effective, by analyzing the effects of two different types of instructions (learning instruction vs. entertainment instruction). Results showed that the learning instruction elicited deeper learning than the entertainment one, without impacting negatively on motivation. In our second experiment, we showed that if learners are given regular feedback about their performance, the entertainment instruction results in deep learning. These two experiments demonstrate that a serious game environment can promote learning and motivation, providing it includes features that prompt learners to actively process the educational content.     

Increasing social presence of social actors in e-learning environments: Effects of dynamic and static emoticons on children

The present research aimed to employ dynamic and static emotions as social cues in e-learning environments for computers to be able to convey social presence and increase children’s motivation with learning. To understand how children of different gender react to the two types of emoticon in e-learning environment, a math problem-solving practice program was designed to test their reactions. The program features two treatments, dynamic emoticons and static emoticons. A 2 × 2 (emoticon style × gender) between-subjects factorial design was adopted for this study. One hundred seventy-three sixth graders participated in this study. Data were collected via questionnaire regarding the perceived social presence and children’s intrinsic motivation, and then analyzed by means of two-way ANOVA. The results show that the children in dynamic-emoticon condition perceived a higher degree of social presence and reported greater intrinsic motivation than those in static-emoticon condition. The feelings of social presence created by the computer itself can mediate children’s intrinsic motivation. Besides, no gender differences in children’s attitudes toward computers were observed. It suggests that the use of dynamic emoticons as social cues incorporating in e-learning environments can enable children to perceive computers on social dimension and lead to increase their motivation with learning.