Online Simulation Research Articles

How simulated learning can support a more diverse inclusive society

Combinations of simulations and games provide learners with a virtual environment where they can immerse themselves in highly contextualised, work-related scenarios, encouraging experimentation and learning from mistakes without compromising the safety of real patients. This pilot study investigated how interactive online simulations supported students’ disciplinary knowledge, care of diverse patients, and the development of students’ professional attitudes and beliefs. Four urinary tract infection (UTI) scenarios (two involving Transgender patients) were delivered to medical and pharmacy students through an interprofessional-education (IPE) activity. Evaluation involved pre- and post-activity questionnaires. There were 26 participants (18 females/ 8 males; range: 18 – 36 years]), including 11 medical and 15 pharmacy students. We found statistically significant changes in self-reported knowledge, skills and confidence to manage UTI (all p<0.001); competence to care for Transgender patients (2.21 vs. 2.74; p=0.001) and awareness of specific health needs of Transgender people (3.74 vs. 4.42; p=0.028). This pilot study demonstrated the potential of simulation-gaming platforms in evaluating and enhancing students' learning, offering a novel and sustainable approach to IPE. Simulations are a versatile teaching approach that can be adapted to promote cultural awareness and inclusivity across various fields in higher education.

Building Narratives Through Empathy: The Role of Empathy Mechanisms and Associative Thinking in Creative Writing

ABSTRACTEmpathy emerges as a pivotal skill in creative writing, yet previous studies lack an understanding of empathy's multidimensionality and specific impact of its facets on the capacity to generate narrative stories. This cross‐sectional study delved into the various cognitive and affective empathy facets—that is, perspective‐taking, online simulation, emotion contagion, proximal responsivity, and peripheral responsivity—and their contributions to creative writing. Further, it examined the mediating effects of associative thinking—conceptualized as a common empathy‐creativity resource—on the relationship between empathy facets and creative writing. Two‐hundred twenty participants (university students) completed performance‐based tasks and self‐report measures of creative writing, associative thinking, and empathy. A latent mediation model implemented in Structural Equation Modeling indicated two effects of empathy facets on creative writing, with perspective‐taking emerging as a positive predictor. Additionally, peripheral responsivity (i.e., affect sharing in indirect contexts) exhibited an indirect positive influence on creative writing, mediated by associative thinking. In summary, associative thinking appears to be an important ingredient in both empathy and creative writing, while cognitive empathy, specifically intuitive perspective‐taking, contributes significantly to creative writing skills. Future studies should further explore these connections and their causalities, possibly using experimental or longitudinal approaches.

Design and optimization of PD control system based on saturation

Abstract. Designing PI, PD, and PID controllers is challenging, but it is an inevitable step if engineers want their systems to perform well. Consequently, control theory was purposed and the system became more complicated. Unfortunately, saturation is hard to prevent. The degree of saturation is an important aspect of the electrical signal process. This paper investigates the concepts of saturation for PD,PI, and PID control. It involves the discussion of properties of passive components, excessive input/output concerning the design maximum or minimum, and the saturation function. The main purpose of the paper is to give an insight into how to prevent control saturation. The investigation will be mainly based on current control theory, research processes from other papers, and the online simulations. To avoid saturation, applying analysis on the gain of all controllers and saturation function is crucial.

On Elastic Language Models

Large-scale pretrained language models have achieved compelling performance in a wide range of language understanding and information retrieval tasks. While their large scales ensure capacity, they also hinder deployment. Knowledge distillation offers an opportunity to compress a large language model to a small one, in order to reach a reasonable latency-performance tradeoff. However, for scenarios where the number of requests (e.g., queries submitted to a search engine) is highly variant, the static tradeoff attained by the compressed language model might not always fit. Once a model is assigned with a static tradeoff, it could be inadequate in that the latency is too high when the number of requests is large, or the performance is too low when the number of requests is small. To this end, we propose an elastic language model ( ElasticLM ) that elastically adjusts the tradeoff according to the request stream. The basic idea is to introduce a compute elasticity to the compressed language model, so that the tradeoff could vary on-the-fly along a scalable and controllable compute. Specifically, we impose an elastic structure to equip ElasticLM with compute elasticity and design an elastic optimization method to learn ElasticLM under compute elasticity. To serve ElasticLM , we apply an elastic schedule. Considering the specificity of information retrieval, we adapt ElasticLM to dense retrieval and reranking, and present an ElasticDenser and an ElasticRanker, respectively. Offline evaluation is conducted on a language understanding benchmark GLUE, and several information retrieval tasks including Natural Question, Trivia QA and MS MARCO. The results show that ElasticLM along with ElasticDenser and ElasticRanker can perform correctly and competitively compared with an array of static baselines. Furthermore, an online simulation with concurrency is also carried out. The results demonstrate that ElasticLM can provide elastic tradeoffs with respect to varying request stream.

A Non‐Iterative Wheel‐Rail Contact Geometry Determination Algorithm and Its Application

AbstractTo ensure a more accurate simulation of the wheel‐rail contact state in vehicle‐track interaction, a non‐iterative contact geometry determination algorithm is proposed. This algorithm decouples lateral movement and roll, independently calculates the minimum wheel‐rail gap on both sides, and overcomes the limitation of simultaneous wheel‐rail contact on both sides. It can be applied to single‐side and two‐side wheel‐rail separation problems. Additionally, by converting track irregularity and rail deformation into the reverse displacement of the wheel, it avoids real‐time calculation of the wheel‐rail spatial position, thereby improving calculation efficiency. The effectiveness of the algorithm is verified through Universal Mechanism software and field measurements. Subsequently, the influence of the measured wheel‐rail profile, rail cant, and rail gauge on the wheel‐rail contact characteristics is analyzed. Finally, vehicle shaking caused by track irregularity and wheel‐rail contact is examined from the perspective of wheel‐rail matching. The study demonstrates that the non‐iterative algorithm is suitable for online simulation by pre‐processing the contact geometry parameters. When the track gauge and rail cant increase, the distribution of wheel‐rail contact points becomes more concentrated. Furthermore, when the excitation frequency of wheel‐rail matching is close to the track irregularity excitation frequency, it causes vibration amplification, resulting in lateral vehicle shaking.

Gamification Technology as a Tool for Improving Students’ Understanding of Text-Based Problem-Solving Techniques

Solving text problems to a greater extent than other mathematical topics in Grades 5–6 contributes to the development of erudition, thinking abilities, analytical reasoning skills, and the formation of mathematical knowledge. Problem-solving skills bring students closer to real-life situations that require them to develop strategies and search for optimal solutions. The article considers the necessity of using gamification technology to effectively achieve the main goal of the research – to improve students’ understanding of text problem solving methods. In order to achieve the goal, the authors have developed methodological recommendations to improve students’ understanding of the condition and solution of text problems. The authors note that the use of interactive tools, innovative teaching methods, such as online simulators and gamification, contributes to the attractiveness of the learning process. This helps to increase students’ activity, formation of motivation for understanding the conditions of the textual task, as well as stimulates their cognitive activity. The methods of analysis, synthesis, generalization, study of pedagogical experience, observation and survey have been used to conduct the research. The analysis of the research results showed that the novelty of using gamification technology will help, on the one hand, the teacher to adapt teaching methods depending on the level of understanding and the pace of learning of students and to present them with new material in an interactive form, and on the other hand - students to develop self-education, improve communication skills, learn to discuss the solution and work in a team. The author’s development of methodological recommendations in combination with game technologies will help teachers to apply gamification in the practice of solving text problems with schoolchildren. Keywords: text problem, formation of mathematical knowledge, gamification technology, motivation, game technology

Development and application of a population pharmacokinetic model repository for caffeine dose tailoring in preterm infants

ABSTRACT Background Considerable interindividual variability for the pharmacokinetics of caffeine in preterm infants has been demonstrated, emphasizing the importance of personalized dosing. This study aimed to develop and apply a repository of currently published population pharmacokinetic (PopPK) models of caffeine in preterm infants to facilitate model-informed precision dosing (MIPD). Research design and methods Literature search was conducted using PubMed, Embase, Scopus, and Web of Science databases. Relevant publications were screened, and their quality was assessed. PopPK models were reestablished to develop the model repository. Covariate effects were evaluated and the concentration–time profiles were simulated. An online simulation and calculation tool was developed as an instance. Results Twelve PopPK models were finally included in the repository. Preterm infants’ age and body size, especially the postnatal age and current weight, were identified as the most clinically critical covariates. Simulated blood concentration–time profiles across these models were comparable. Caffeine citrate-dose regimen should be adjusted according to the age and body size of preterm infants. The developed online tool can be used to facilitate clinical decision-making. Conclusions The first developed repository of PopPK models for caffeine in preterm infants has a wide range of potential applications in the MIPD of caffeine.

ACWA Power’s CSP Performance Assessment

A CSP Plant and in particular the solar field has hundreds of thousands of components and the corresponding process parameters. This needs to be monitored and evaluated every day to make sure that the plant is working efficiently. A performance assessment with a production simulation is done daily where the expected and actual power production are compared. Such evaluation is usually done with the plant performance model and the necessary data is compiled in calculation programs like Excel. The work is repetitive, time consuming and human errors may easily occur. Typically, the evaluations are done from different parties with deviating results and conclusions. ACWA Power has developed an online simulation platform to automatize the data processing to increase the data reliability and reduce the time effort. The application has been implemented in the Noor Energy 1 hybrid solar plant in Dubai and shall be presented in this paper.

A visual digital twin framework based on residual-based fourier neural operator online simulation method

ABSTRACT To enjoy a wonderful cooking experience in a smart kitchen, users and designers need a visual interaction platform. This paper proposes a DT framework incorporating data processing, flow field online simulation, equipment monitoring, interaction and visualization. Specifically, the DT online simulation and visualization of the kitchen fume flow field serve as the foundation for appliance design and control. Additionally, users can gain deeper insight into the state and change trends of the kitchen. To address the online simulation of the flow field, a RFNO online simulation method is proposed. In addition, this paper proposes an Echarts-based 2D and UE5-based 3D flow field visualization method to enable dynamic visualization and interaction of the flow field. The proposed DT framework was successfully verified in the case of the smart kitchen, demonstrating its efficiency and effectiveness.

Cloud-based STEM learning: Using an online simulation to teach renewable resources management in a remote learning classroom during the COVID-19 pandemic

Cloud-based STEM learning: Using an online simulation to teach renewable resources management in a remote learning classroom during the COVID-19 pandemic

Student informed development of virtual reality simulations for teaching and learning in the molecular sciences

ABSTRACT The development of accurate spatial conceptualisations of molecular biology structures, processes and interactions represents a critical learning outcome for a wide array of life sciences students. In this study, we investigated student learning through a bespoke virtual reality (VR) simulation focused on interactive assembly of an expression vector and visualisation of the recombinant protein expression process, encompassing constructivist pedagogical principles. A mixed methods approach was pursued involving surveys, assessments, and online simulation data capture to facilitate student partnered inputs into virtual simulation design and implementation in the teaching of molecular and cellular biology. The scope of student learning modalities, effective teaching practices and perspectives on challenging curriculum were also captured to position VR implementation within a wider learning framework. Students expressed a consensus view towards the application of this innovative teaching modality and appear well equipped to adapt to this new teaching and learning approach. The visual and kinaesthetic elements of the simulations were found to offer a unique entry point to challenging and abstract molecular concepts that has the potential to transform life science education for students, where a partnership approach can best deliver a roadmap for effective integration into the curriculum.

Effectiveness of a new 3D printed simulator for mitral transcatheter edge-to-edge repair in enhancing the confidence and procedural skills of the operator

Background. Mitral transcatheter edge-to-edge repair (m-TEER) is a minimally invasive procedure for treating mitral regurgitation (MR). m-TEER is a highly technical procedure, and a steep learning curve needs to be overcome for operators to ensure optimal patient outcomes and minimise procedural complications. Training via online simulation and observation of procedures is not sufficient to establish operator confidence; thus, advanced hands-on training modalities need to be explored and developed.Methods. In this study, a novel anatomical simulator for m-TEER training was evaluated in comparison to a standard model. The proposed simulator resembled the anatomical features of the right and left atrium, left ventricle and mitral valve apparatus. Participants in the questionnaire (n = 18) were recruited across 4 centres in London with (n = 8) and without (n = 10) prior experience in m-TEER. Participants were asked to simulate procedures on both an idealised, routinely used simulator and the newly proposed anatomical model. The questionnaire was designed to assess (i) participants’ confidence before and after training and (ii) the realism of the model in the context of the m-TEER procedure. The results of the questionnaires were collected, and statistical analysis (t-test) was performed.Results. Both models were equally beneficial in increasing operator confidence before and after the simulation of the intervention (P = 0.43). However, increased confidence after training with the anatomical model was recorded (P = 0.02). Participants with prior experience with m-TEER therapy were significantly more confident about the procedure after training with the anatomical model than participants who had no prior experience (P = 0.002). On average, all participants thought that the anatomical model was effective as a training simulator (P = 0.013) and should be integrated into routine training (P = 0.015)). Participants with experience thought that the anatomical model was more effective at reproducing the m-TEER procedure than the idealised model (P = 0.03).Conclusions. This study showed how a more realistic simulator can be used to improve the effectiveness of m-TEER procedural training. Such pilot results suggest planning future and large investigations to evaluate improvements in clinical practice.

Design and Development of a Teaching–Learning Sequence about Deterministic Chaos Using Tracker Software

In this paper, we present the design, development, and pilot implementation of a Teaching–Learning Sequence (TLS) about the physics of deterministic chaos. The main aim of the activities is to let students become aware of two key ideas about deterministic chaos: (1) the role of initial conditions and (2) the graphical representation in a momentum–position graph. To do so, the TLS is based on the observation and analysis of the trajectory of the free end of a double pendulum through the modeling software Tracker. In particular, the Tracker-based activities help students understand that, by modifying the well-known simple pendulum dynamic system into a double pendulum, long-time-scale predictability is lost, and a completely new behavior appears. The TLS was pilot tested in a remote teaching setting with about 70 Italian high school students (16–17 years old). The pretest analysis shows that before participating in the activities, students held typical misconceptions about chaotic behavior. Analysis of the written responses collected during and after implementation shows that the proposed activities allowed students to grasp the two key ideas about nondeterministic chaos. A possible integration of the TLS with an online simulation is finally discussed.

Evaluation of Online Virtual Patient Simulation Training for Managing Acute Patients with an Emphasis on Meaningful Learning

Objective: To evaluate the meaningful learning aspect of emergency patient management training conducted using an on-line virtual patient simulator. Methods: Case-based trainings which is a part of curriculum were conducted on-line using a Virtual Patient Simulator (VP) under the guidance of an educator in the years 2019-2020.The course was designed according to FTL(Fascilitation,training,learning) Model. The data in this study consisted of the survey results completed by 2nd year Emergency and First Aid Department students of Acibadem University (n:38/54) before and after the training sessions. The survey used was Keskitalo’s survey .The data were analyzed by using descriptive statistics. The paired-samples t-test was used to compare the differences between the students’ expectations and their experiences. Results: The results obtained indicate that meaningful learning expectations, including concrete, metacognitive, individual and competency-based, characteristics were exceeded by the experiences (p

A combined interactive online simulation and face-to-face laboratory enable undergraduate student proficiency in hemocytometer use, cell density and viability calculations.

A hemocytometer is a key piece of laboratory equipment typically used in diagnostic and immunology research laboratories to enumerate white blood cells. The accurate quantification of cell density is essential to ensure accurate numbers of cells are added to assays to generate valid data. Hence, learning to correctly use a hemocytometer is a critical skill for all undergraduate immunology students. However, this skill can be challenging to learn because of students' unfamiliarity with correct cell identification, differentiating viable versus dead cells and mathematical proficiency in calculating cell density and viability. To address these issues, we developed an interactive computer simulation that replicated all aspects of a Neubauer-style hemocytometer. This simulation was used to teach second-year undergraduate immunology students before a face-to-face (F-2-F) laboratory exercise where these skills were applied. Using a mixed methods approach, student performance and feedback were collected on broad aspects of the intervention and its benefits to the F-2-F setting. The approach was found to be extremely successful with all measures indicating a significant impact of the virtual hemocytometer on student learning, understanding and confidence. We suggest that integrating an online simulation to teach students the fundamentals of hemocytometer use and calculations is a valuable educational aid for learning this important skill.

A discontinuous Galerkin based multiscale method for heterogeneous elastic wave equations

In this paper, we develop a local multiscale model reduction strategy for the elastic wave equation in strongly heterogeneous media, which is achieved by solving the problem in a coarse mesh with multiscale basis functions. We use the interior penalty discontinuous Galerkin (IPDG) to couple the multiscale basis functions that contain important heterogeneous media information. The construction of efficient multiscale basis functions starts with extracting dominant modes of carefully defined spectral problems to represent important media feature, which is followed by solving a constraint energy minimization problem. Then a Petrov-Galerkin projection and systematization onto the coarse grid are applied. As a result, an explicit and energy-conserving scheme is obtained for fast online simulation. The method exhibits both coarse-mesh and spectral convergence as long as one appropriately chooses the oversampling size. We rigorously analyze the stability and convergence of the proposed method. Numerical results are provided to show the performance of the multiscale method and confirm the theoretical results.

Research on the Design of Blended Teaching of "Food Physical and Chemical Inspection" Course

The blended teaching mode is a cutting-edge teaching approach in current higher vocational education. Compared with traditional teaching methods, it has advantages such as rich teaching resources, intuitive teaching methods, no time and space constraints, and strong student classroom participation. These advantages effectively stimulate students' enthusiasm for learning and improve classroom teaching effectiveness. This paper takes the core course "Food Physical and Chemical Inspection" of the higher vocational food inspection and testing technology major as an example. Based on online classrooms and simulation training platforms, a complete blended teaching design case is designed, covering pre-class preparation, in-class tutoring, post-class summarization, and reflection evaluation. Practice has proven that the blended teaching mode of online and offline fully utilizes teaching time inside and outside the classroom, mobilizes students' enthusiasm and initiative, and achieves the expected teaching objectives.

In-Person Versus Online Training in Simulations of Helping Babies Breathe: A Randomized Controlled Trial.

Birth asphyxia is a leading cause of neonatal deaths, but simple interventions may prevent it. The Helping Babies Breathe (HBB) course has significantly reduced neonatal mortality ratesin lower and middle-income countries (LMICs) by training healthcare providers (i.e. midwives and nurses) on the essential skills of bag-and-mask ventilation and postnatal care. Although several studies have supported the efficacy of virtual learning in other medical education programs, there is still a lack of knowledge regarding a virtual approach to HBB. This study aims to compare the effectiveness of online versus in-person learning of the HBB course among medical and nursing students. The study is a two-arm parallel randomized non-inferiority controlled trial, that includes medical and nursing students. Participants were randomly assigned to either online or in-person debriefing during the hands-on simulations of HBB. They attended a pre-recorded lecture before being assigned to one of three instructors for the simulation lab. Participants completed a seven-point anonymous Likert-based questionnaire and a standardized Debriefing Assessment for Simulation in Healthcare Student Version (DASH-SV) Short Form. The primary outcome was the Objective Structured Clinical Exam (OSCE) grade. The trial is listed on ClinicalTrials.gov with the registration number NCT05257499. 47 participants completed the study, with similar baseline characteristics in each arm (gender, age, and class). The participants in both arms reported high levels of satisfaction and confidence, with no significant difference between the two arms. The DASH score over 7 was also similar in the online arm(6.27±0.26) compared to the in-person arm (6.55±0.13) (p=0.07). The mean OSCE scorein the online arm (45.8±5.2) was comparable to the mean OSCE score in the in-person arm (41.3±5.0) (p=0.22). Both online and in-person participants failed the OSCE. The survey responses conveyed that online simulation training is comparable to in-person simulation for the HBB course. Both online and in-person participants failed the OSCE most likely because they needed more training on HBB. This could be due to the fact that the material is too new to the students who needed more practice to pass the OSCE. Further research is needed to confirm these results and explore the long-term impact of online neonatal resuscitation training.

Evaluation of Thermal Comfort Online Simulation Tools Usage Through Distance Education Process in an Applied Graduate Course

Through Covid 19 pandemic, education field has experienced mandatory transition to distant education. The case study held in Indoor Comfort Management postgraduate course. In order to examine how direct sunlight affects the adaptive thermal comfort of the user, simulations were made with online tools to evaluate thermal comfort within the scope this course at Yaşar University. The SolarCal and ComfTool of CBE online tools are used. This article aims to question the contribution of online simulation tools to education via a questionnaire given to students to grasp aspects of adaptive thermal comfort. The use of these aforementioned online tools and formulas can enrich studies and draw conclusions in limited facilities for professionals especially for architectural and engineering industries. The results of the survey will be analyzed to ensure the applicability of such a methodology in similar learning environments for easy understanding of the various adaptive thermal comfort indices at once.

An exploration of online-simulation-driven portfolio scheduling in Workflow Management Systems

Workflow Management Systems used to automate the execution of scientific workflow applications on parallel and distributed computing platforms must make scheduling decisions at runtime. A large number of workflow scheduling algorithms have been proposed in the literature, but often these algorithms are evaluated based on simplifying assumptions that may not hold in practice. Furthermore, published algorithm evaluation and/or comparison results are necessarily only for a subset of all possible scenarios, and thus may not include scenarios relevant to particular use-cases. Consequently, it is difficult for Workflow Management Systems (WMSs) developers to decide which scheduling algorithm should be implemented. To obviate this difficulty, one possible approach is to implement a portfolio of scheduling algorithms and select the most effective algorithm at runtime. One method for performing this selection is to run an online simulation for each algorithm in the portfolio. The algorithm that leads to the best performance, in simulation, is selected for future use.The above simulation-driven portfolio scheduling (SDPS) approach has been proposed in a few parallel and distributed computing contexts. The main objective of this work is to evaluate the feasibility and potential merit of SDPS if implemented in WMSs. We perform this evaluation using simulated WMS executions, where the simulations are instantiated from real-world platform and workflow configurations. Our main finding is that SDPS is on par with or outperforms an approach in which a single algorithm is used, where this algorithm is the one that performs best on average across all our experimental scenarios. Furthermore, we find that SDPS remains an attractive proposition even in the presence of high levels of simulation error and for simulators with relatively low levels of sophistication. In many of our experimental scenarios we find that mitigating simulation error at runtime can further improve performance. Finally, we show that simulation overhead can be made sufficiently low for SDPS to be feasible in practice.