Medical simulation-based education improves medicos' clinical skills

Clinical skill is an essential part of clinical medicine and plays quite an important role in bridging medicos and physicians. Due to the realities in China, traditional medical education is facing many challenges. There are few opportunities for students to practice their clinical skills and their dexterities are generally at a low level. Medical simulation-based education is a new teaching modality and helps to improve medicos＇ clinical skills to a large degree. Medical simulation-based education has many significant advantages and will be further developed and applied.

The Effects of Simulation-Based Learning Using Virtual Reality in Nursing Student:A Meta-Analysis

Purpose:This study is a meta-analysis to assess the effect of simulation-based learning using virtual reality(VR)on knowledge,affective,and performance domain outcomes of learning in nursing students.Methods:A literature search was conducted using Cochrane library,PubMed,EMBASE,Web of Science,ProQuest,ScienceDirect,Springer and Ovid eight electronic English databases,independently by 2 of the authors from January 2008 to December 2018.The RevMan 5.3 program of the Cochrane library was used to analyze the data with mean and standardized differences.Results:A total of 10 studies(5 randomized control trials(RCTs)and 5 non-RCTs)involved 630 nursing students.As a whole,simulation-based learning using VR appeared to have beneficial effects on the knowledge(I2=50%,95%CI 0.35[0.09,0.62],P=0.009),have no significant difference on the performance(I2=97%,95%CI 1.05[-0.54,2.63],P=0.19)and have a negative impact on the affective field(I2=0%,95%CI-0.43[-0.71,-0.15],P=0.003).Conclusion:The existing evidences imply that simulation-based learning using VR might have a positive trend that is beneficial to knowledge and clinical skill acquisition.However,the best way of integration still needs further research to be identified.

Simulation-based Optimal Design of α-β-γ-δ Filter

The existing third-order tracker known as α-β-γ-δ filter has been used for target tracking and predicting for years. The filter can track the target＇s position and velocity, but not the acceleration. To extend its capability, a new fourth-order target tracker called α-β-γ-δ filter is proposed. The main objective of this study was to find the optimal set of filter parameters that leads to minimum position tracking errors. The tracking errors between using the α-β-γ-δ filter and the α-β-γ-δ filter are compared. As a result, the new filter exhibits significant improvement in position tracking accuracy over the existing third-order filter, but at the expense of computational time in search of the optimal filter. To reduce the computational time, a simulation-based optimization technique via Taguchi method is introduced.

Understanding the effects of structured self-assessment in directed,self-regulated simulation-based training of mastoidectomy:A mixed methods study

Objective:Self-directed training represents a challenge in simulation-based training as low cognitive effort can occur when learners overrate their own level of performance.This study aims to explore the mechanisms underlying the positive effects of a structured self-assessment intervention during simulation-based training of mastoidectomy.Methods:A prospective,educational cohort study of a novice training program consisting of directed,self-regulated learning with distributed practice(5x3 procedures)in a virtual reality temporal bone simulator.The intervention consisted of structured self-assessment after each procedure using a rating form supported by small videos.Semi-structured telephone interviews upon completion of training were conducted with 13 out of 15 participants.Interviews were analysed using directed content analysis and triangulated with quantitative data on secondary task reaction time for cognitive load estimation and participants’self-assessment scores.Results:Six major themes were identified in the interviews:goal-directed behaviour,use of learning supports for scaffolding of the training,cognitive engagement,motivation from self-assessment,selfassessment bias,and feedback on self-assessment(validation).Participants seemed to self-regulate their learning by forming individual sub-goals and strategies within the overall goal of the procedure.They scaffolded their learning through the available learning supports.Finally,structured self-assessment was reported to increase the participants’cognitive engagement,which was further supported by a quantitative increase in cognitive load.Conclusions:Structured self-assessment in simulation-based surgical training of mastoidectomy seems to promote cognitive engagement and motivation in the learning task and to facilitate self-regulated learning.

Simulation-Based Optimization for the Fast Fashion Replenishment

Fast fashion is a commercial pattern which provides fashionable clothes at affordable price.This mode needs rapid response supply chain to respond to varying fashion trends.New styles are introduced in every sale period to cover fashion trends.In order to maximize profits,replenishment quantity of each style should be decided in every period.The purchasing and replenishing process over multiple periods based on uncertainty customer demand is modeled,which is formulated by a stochastic choice process.Heterogeneous consumers visit a store in a stochastic sequence and choosing dynamically from the available fashion styles(buy or not buy) according to a utility maximization criterion.The purchase process in a retail shop for multi-period is simulated.An algorithm which combines simulated anneal(SA) with gradient estimation is proposed to find the optimal replenishing strategy from the simulation program.

The Effect of Simulation-Based Training on Nursing Students’ Communication Skill, Self-Efficacy and Clinical Competence for Nursing Practice

Background: Simulation-based training is a new strategy in teaching that gives the students good opportunities to learn and apply what they learn in nursing care safely. Aim: This study conducted to evaluate the effects of simulation-based training on nursing students’ communication skill, self-efficacy and clinical competence in practice. Subjects and Methods: Quiz-experimental design was used in this study (pre-posttest intervention), it was carried out on 100 nursing students first semester in 2019 using low and high-fidelity simulators. This study was carried out at College of Applied Medical Sciences-Bshia University. Data Collection: demographic data, communication skill, self-efficacy and clinical competence questionnaires. Analysis is done by SPSS version 20 software. Results: Participants who received the simulation-based training, showed statistical significant improvement in communication skill, self-efficacy, and clinical competence scores after participation in the simulation program (t = −32.64, p = 0.001;t = −19.9, p = 0.001;16.4, p = 0.001). Also, there are significant relation between gender and clinical competency (t = 2.768, p Conclusion: Simulation-based training in medical courses is effective in enhancing communication skill, self-efficacy and clinical competence. Multiple-patient simulations as a teaching-learning strategy in the nursing curriculum are highly recommended.

Simulation-based optimization of control policy on multi-echelon inventory system for fresh agricultural products

As fresh agricultural products are perishable and vulnerable,reducing inventory cost is a strategic target for supply chain enterprises.How to design a reliable multi-echelon inventory control policy is still a great challenge.Therefore,the inventory cost of a three-level fresh agricultural products inventory system was firstly mathematically analyzed.Then,the simulation-based optimization model of the multi-echelon inventory system for fresh agricultural products was proposed by using the Flexsim simulation software and the improved particle swarm optimization algorithm.Finally,the multi-echelon inventory system is simulated based on a large number of survey data.Simulation results demonstrate that the proposed simulation-based optimization model of multi-echelon inventory system for fresh agricultural products can provide decision-making and technical support for the formulation of inventory control policy,and also it shows that the modeling of system simulation is an effective method to solve the problem of complex system.

Simulation-Based and Risk-Informed Assessment of the Effectiveness of Tsunami Evacuation Routes Using Agent-Based Modeling:A Case Study of Seaside,Oregon

Typically,tsunami evacuation routes are marked using signs in the transportation network and the evacuation map is made to educate people on how to follow the evacuation route.However,tsunami evacuation routes are usually identified without the support of evacuation simulation,and the route effectiveness in the reduction of evacuation risk is typically unknown quantitatively.This study proposes a simulation-based and risk-informed framework for quantitative evaluation of the effectiveness of evacuation routes in reducing evacuation risk.An agentbased model is used to simulate the tsunami evacuation,which is then used in a simulation-based risk assessment framework to evaluate the evacuation risk.The route effectiveness in reducing the evacuation risk is evaluated by investigating how the evacuation risk varies with the proportion of the evacuees that use the evacuation route.The impacts of critical risk factors such as evacuation mode(for example,on foot or by car)and population size and distribution on the route effectiveness are also investigated.The evacuation risks under different cases are efficiently calculated using the augmented sample-based approach.The proposed approach is applied to the riskinformed evaluation of the route effectiveness for tsunami evacuation in Seaside,Oregon.The evaluation results show that the route usage is overall effective in reducing the evacuation risk in the study area.The results can be used for evacuation preparedness education and hence effective evacuation.

Data fusion and simulation-based planning and control in cyber physical system for digital assembly of aeroplane

This paper introduces a CPS application for intelligent aeroplane assembly.At first,the CPS structure is presented,which acquires the characteristics of general CPS and enables“simulation-based planning and control”to achieve high level intelligent assembly.Then the paper puts forward data fusion estimation algorithm under synchronous and asynchronous sampling,respectively.The experiment shows that global optimal distributed fusion estimation under synchronized sampling proves to be closer to the actual value compared with ordinary weighted estimation,and multi-scale distributed fusion estimation algorithm of wavelet under asynchronous sampling does not need time registration,it can also directly link to data,and the error is smaller.This paper presents hybrid control strategy under the circumstance of joint action of the inner and outer loop to address the problems caused by the less controllable feature of the parallel mechanism when undertaking online process simulation and control.A robust adaptive sliding mode controller is designed based on disturbance observer to restrain inner interference and maintain robustness.At the same time,an outer collaborative trajectory planning is also designed.All the experiment results show the feasibility of above proposed methods.

Efficient functional encryption for inner product with simulation-based security

Functional encryption(FE)is a novel paradigm for encryption scheme which allows tremendous flexibility in accessing encrypted information.In FE,a user can learn specific function of encrypted messages by restricted functional key and reveal nothing else about the messages.Inner product encryption(IPE)is a special type of functional encryption where the decryption algorithm,given a ciphertext related to a vector x and a secret key related to a vector y,computes the inner product x·y.In this paper,we construct an efficient private-key functional encryption(FE)for inner product with simulation-based security,which is much stronger than indistinguishability-based security,under the External Decisional Linear assumption in the standard model.Compared with the existing schemes,our construction is faster in encryption and decryption,and the master secret key,secret keys and ciphertexts are shorter.

Efficient functional encryption for inner product with simulation-based security

Functional encryption(FE)is a novel paradigm for encryption scheme which allows tremendous flexibility in accessing encrypted information.In FE,a user can learn specific function of encrypted messages by restricted functional key and reveal nothing else about the messages.Inner product encryption(IPE)is a special type of functional encryption where the decryption algorithm,given a ciphertext related to a vector x and a secret key related to a vector y,computes the inner product x·y.In this paper,we construct an efficient private-key functional encryption(FE)for inner product with simulation-based security,which is much stronger than indistinguishability-based security,under the External Decisional Linear assumption in the standard model.Compared with the existing schemes,our construction is faster in encryption and decryption,and the master secret key,secret keys and ciphertexts are shorter.

Optimal synthesis of heat-integrated distillation configurations using the two-column superstructure

In the realm of the synthesis of heat-integrated distillation configurations,the conventional approach for exploring more heat integration possibilities typically entails the splitting of a single column into a twocolumn configuration.However,this approach frequently necessitates tedious enumeration procedures,resulting in a considerable computational burden.To surmount this formidable challenge,the present study introduces an innovative remedy:The proposition of a superstructure that encompasses both single-column and multiple two-column configurations.Additionally,a simultaneous optimization algorithm is applied to optimize both the process parameters and heat integration structures of the twocolumn configurations.The effectiveness of this approach is demonstrated through a case study focusing on industrial organosilicon separation.The results underscore that the superstructure methodology not only substantially mitigates computational time compared to exhaustive enumeration but also furnishes solutions that exhibit comparable performance.

A Holistic Approach to Enhance FRCS General Surgery Examination Training Using Adult Learning Model: A Non-Profit Initiative

Objectives: To evaluate the impact of adult learning and simulation-based learning (SBL) on surgical trainees’ learning experiences and Fellowship of the Royal College of Surgeons (FRCS) Section 2 General Surgery examination pass rate. Methods: This was a cross-sequential study involving 148 surgical candidates (72 UK trainees, 75 non-UK trainees) who had attended our revision course (Phoenix FRCS Course) from June 2017 until 2023. Each course comprised a two-day weekend preparation with dedicated sections for clinical, viva, and academic reading, incorporating SBL as its key learning style. We maintained a prospective database of candidate and course details, examination results, and feedback since the course inception. Results: We found that 97% of candidates passed the FRCS examination after their first attempt. The course was attended once by 89% of candidates, and only 3 of the 148 candidates exhausted all four attempts at the examination. Candidate feedback for the course and its style of learning was positive, with simulation-based table viva sessions and virtual clinical sessions proving the most popular learning sessions (95% and 80% of candidates attending courses run in December 2017, April 2018, and May 2021 rated them “Excellent” respectively). Conclusions: The course is centered around shared adult learning and mindfulness tools to encourage candidates to learn from each other and develop confidence and mastery in all domains of surgical practice. These methods have been shown to be effective in achieving high success rates in the Intercollegiate and International FRCS examinations for UK and overseas surgeons.

Simulation of Cyber-Physical Systems of Systems： Some Research Areas-Computational Understanding, Awareness, and Wisdom

After a brief emphasis about the interconnected world, including Cyber-Physical Systems of Systems, the increasing importance of the decision-making by autonomous, quasi-autonomous, and autonomic systems is emphasised. Promising roles of computational understanding, computational awareness, and computational wisdom for better autonomous decision-making are outlined. The contributions of simulation-based approaches are listed.

Is There an Improvement in Patient Survival/Code Blue Activation after Training Based on Simulation (Basic Life Support—BLS) Based Practice of Cardiopulmonary Resuscitation?

Background and Aim: The only way to survive a sudden cardiac arrest is when the CPR is performed immediately after the arrest. The focus of the present research study is to assess the effectiveness of a pre- and post-simulation-based BLS training (BLS) and the outcome was measured on the basis of patient survival after the cardiac arrest. Study Design: This pre- and post-training BLS/CPR training study enrolled all nursing staff, all hospital residents, internees, throughout the hospital in a simulation-based BLS training as per the standards of American Heart Association (AHA), to make them respond to immediate resuscitation and code blue activation during the cardiac arrest within the hospital premises including ED, wards, ICUs, MRI, CT and all miscellaneous areas. The providers completed self-efficacy questionnaires as per the AHA protocol before being certified and were evaluated during the emergency in hospital cardiopulmonary arrest. Results: 296 nursing staff, 206 non-healthcare professionals, 143 residents, 212 internees, and 98 medical staff grade doctors completed the BLS training (total 955 hospital staff—providers) were graded for the response by pre- and post-training testing. In the course of pre-BLS training period out of the 250 cardiac arrest patients, 68 patients (27.2%) had ROSC, while after instituting the BLS training period, 143 individuals (40.86%) of the 350 patients who had cardiac arrest had ROSC (p < 0.05). Conclusion: A simulation-based CPR and BLS training curriculum greatly improves patient outcome by reducing mortality and morbidity with improved subjectivity, self-efficiency along with the objective assessment of the performance scores during acute cardiac arrest in Emergency Cardiovascular Care (ECC).

The Relationship between Presence and Performance in Virtual Simulation Training

The use of virtual simulation-based training continues to expand, as organizations explore alternative methods to reduce the cost of training. While virtual simulation has been empirically validated to be effective in the transfer of skills to the live environment, what is still unknown is what effect, if any, that an individual’s sense of presence in the simulation has on their performance. In this paper, we examine the relationship between presence and performance while performing a psychomotor task in a virtual environment. The independent variables were visual display and expertise level. The dependent variables were presence and performance. We found evidence of a moderate relationship between the degree of presence experienced in the simulation and an individual’s performance over three training trials. Results of this study may inspire future research to investigate whether higher presence in virtual simulation results in higher performance.

Team effectiveness evaluation and virtual reality scenario mapping model for helicopter emergency rescue

The application of helicopter emergency rescue is becoming increasingly widespread,but the flight crew training in this area is still difficult due to high cost and risk.Nevertheless,with the development of Virtual Reality(VR)technology,virtual simulation has become a significant role in crew training of helicopter rescue.During the implementation of VR-based training,how to transform complex real tasks into VR scenarios and how to evaluate the performance of crew are of great importance.To address these issues,a novel VR-based R-E-A-D(Report,Evaluate,Agree,Do)evaluation model for training is proposed,which is suitable for complex missions with multiple tasks,multiple scenarios,and multiple people.Then,a mapping method of VR scenarios is put forward,which can transform the real tasks into virtual scenarios to serve the virtual simulation training.Finally,an experiment is carried out to verify the feasibility of the evaluation method and virtual scenario mapping method.

An integrated optimization design of a fishing ship hullform at different speeds

This paper shows how to improve the hydrodynamics performance of a ship by solving a shape optimization design problem at different speeds using the simulation-based design(SBD) technique. The SBD technique is implemented by integrating the advanced CFD codes, the global optimization algorithms and the geometry modification methods, which offers a new way for the hullform optimization design and the configuration innovation. The multiple speed integrated optimization for the hullform design is a challenge. In this paper, an example of the technique application for a fishing ship hullform optimization at different speeds is demonstrated. In this optimization process, the free-form deformation method is applied to automatically modify the geometry of the ship, and the multi-objective particle swarm optimization(MOPSO) algorithm is adopted for exploring the design space. Two objective functions, the total resistances at two different speeds(12 kn and 14 kn) are assessed by the RANS solvers. The optimization results show that the decrease of the total resistance is significant after the optimization at the two speeds, with a reduction of 5.0% and 11.2%, respectively. Finally, dedicated experimental validations for the design model and the optimized model are carried out for the computation and the optimization processes. At the two speeds, the reduction of the total resistance in the model scale is about 6.0% and 11.8% after the optimization. It is a valuable result in view of the small modifications allowed and the good initial performances of the original model. The given practical example demonstrates the feasibility and the superiority of the proposed SBD technique for the multiple speed integrated optimization.

Synergistic optimization framework for the process synthesis and design of biorefineries

The conceptual process design of novel bioprocesses in biorefinery setups is an important task,which remains yet challenging due to several limitations.We propose a novel framework incorporating superstructure optimization and simulation-based optimization synergistically.In this context,several approaches for superstructure optimization based on different surrogate models can be deployed.By means of a case study,the framework is introduced and validated,and the different superstructure optimization approaches are benchmarked.The results indicate that even though surrogate-based optimization approaches alleviate the underlying computational issues,there remains a potential issue regarding their validation.The development of appropriate surrogate models,comprising the selection of surrogate type,sampling type,and size for training and cross-validation sets,are essential factors.Regarding this aspect,satisfactory validation metrics do not ensure a successful outcome from its embedded use in an optimization problem.Furthermore,the framework’s synergistic effects by sequentially performing superstructure optimization to determine candidate process topologies and simulationbased optimization to consolidate the process design under uncertainty offer an alternative and promising approach.These findings invite for a critical assessment of surrogatebased optimization approaches and point out the necessity of benchmarking to ensure consistency and quality of optimized solutions.

Simulation modeling and optimization for ambulance allocation considering spatiotemporal stochastic demand

To ensure a timely response to emergencies,governments are obliged to implement effective ambulance allocation plans.In practice,an emergency medical service(EMS)system works in an uncertain environment,with stochastic demand,response-times,and travel-times.This uncertainty significantly affects ambulance allocation planning.How-ever,few studies in this field adequately consider the effect of spatiotemporal uncertainty in demand,because it is difficult to measure it quantitatively.As a result,few analytic models capture the dynamic nature of an EMS system and,thus,the allocation plans they generate are not efficient in practice.Therefore,this study proposes a simulation-based optimization method for ambulance allocation.A simulation model is constructed to mimic the operational processes of an EMS system,and to evaluate the performance of an ambulance allocation plan in an uncertain environment.Gaussian mixture model clus-tering is used to derive the uncertain spatial demand.Then,the simulation generates emergency demand based on the obtained spatial distribution.A Gaussian-process-based search algorithm is used together with the simulation model to identify optimal solutions.To validate the proposed method,a case study is conducted using data on emergency patients in the Shanghai Songjiang District.Compared with the current plan adopted in Songjiang,the experimental results demonstrate that the delay time and frequency of the EMS system can be reduced significantly by employing the proposed methods.Further-more,nearly 41%of the allocation cost can be saved.