Ambulance Locations in a Tiered Emergency Medical System in a City

This paper deals with optimizing the location of ambulance stations in a two-tiered emergency medical system in an urban environment. Several variants of station distribution are calculated by different mathematical programming models and are evaluated by a detailed computer simulation model. A new modification of the modular capacitated location model is proposed. Two ways of demand modelling are applied; namely, the aggregation of the ambient population and the aggregation of permanent residents at the street level. A case study of the city of Prešov, Slovakia is used to assess the models. The performance of the current and proposed sets of locations is evaluated using real historical data on ambulance trips. Computer simulation demonstrates that the modular capacitated location model, with the ambient population demand, significantly reduces the average response time to high-priority patients (by 79 s in the city and 62 s in the district) and increases the percentage of high-priority calls responded to within 8 min (by almost 4% in the city and 5% in the district). Our findings show that a significant improvement in the availability of the service can be achieved when ambulances are not accumulated at a few stations but rather spread over the city territory.

DESIGN AND DEVELOPMENT OF AN EFFICIENT COMPUTER SIMULATION MODEL FOR RESPONSE ANALYSIS OF A MOORED SEMI-SUBMERSIBLE

This paper presents the design and development of an efficient modular ‘Computer Simulation Model (CSM)’ for response analysis of a moored semi-submersible. The computer simulation model is designed in two split models (i.e. computational and experimental models) and each of these models consists of various modules. The modules are developed from basic governing equations related to motion and modules are integrated and we aim for a seamless integration. The moored semi-submersible is represented mathematically as six degrees of freedom dynamic system and the coupling effects between the structure and mooring lines are considered. The basic geometric configuration of semi- submersible is modelled and analyzed for stability computations in MS-Excel*TM and then the basic governing equations related to motion are modelled mathematically in a module and solved numerically with Ansys-AQWA**TM. The computational model is validated and verified with some available experimental results. The CSM is utilized to study the surge and sway responses with respect to the horizontal range of mooring lines and our results show good validation with the existing experimental results. Our presented results show that the fibre wires have minimum steady state response in surge and sway degrees of freedom as compared with the steel wires. However, they have large drift as compared with steel wires. Finally, we show that the computer simulation model can help in detailed analysis of responses and results can be utilized for design and development of new age semi-submersibles for optimum performances for a given set of parameters.

Watering of the river delta Volga and Western sub-steppe ilmens based on simulation hydrodynamic modeling

To ensure the flooding of the Volga river delta and the Western sub-basin Ilmen and meet the requirements of the fisheries and agriculture, the following tasks were set and completed: to describe the current state and the main environmental, fisheries, agricultural and transport problems of the functioning of the Volga Delta and the Western sub-basin Ilmen; to develop a computer simulation model in the software package MIKE 11 plot of the Volga river from Verkhneye Lebyazhye village before flowing into the Caspian sea, with the specification of cross-sections along the river bed and the floodplain of the Volga river and its branches, spawning grounds, and western sub-steppe ilmen; to perform computer hydrodynamic modeling of the studied section of the Volga river; to develop possible scenarios to solve the problems of flooding of the Volga river delta and the western sub-steppe ilmen, and to meet the requirements of fisheries and agriculture. As the result, the requirements of the main water users for the operating modes of the Volga hydroelectric power station were presented and a hydrodynamic model was described, which allows determining the measures for watering the territory and using simulation modeling to evaluate their effectiveness.

A MODEL OF THE WOVEN FABRIC ELONGATION AND BREAKING WITH INFLUENCE OF WARP AND WEFT THREADS UNEVENNESS AND INTERACTION

The article presents the results of development of the woven fabric rectangular sample stretching and tearing computer simulation model. The model allows to set the sample size, elastic modulus and tensile breaking strength of the threads, random variations of these indicators for the warp and weft threads along their length. The modelling algorithm provides for the breakage of the warp threads, the redistribution of stress and strain between the sections of the threads and allows to get a detailed picture of the fabric sample deformation dynamics before it breaks. Examples of modelling results, the influence of the interaction degree between two systems of threads on the features of the strain distribution over the sections of the warp threads are given. The similarity of the simulation results according to the developed algorithm and the finite element method is shown, and the advantages of the proposed algorithm are noted.

Optimising the balance of acute and intermediate care capacity for the complex discharge pathway: computer modelling study during COVID-19 recovery in England

Objectives: While there has been significant research on the pressures facing acute hospitals during the COVID-19 pandemic, there has been less interest in downstream community services which have also been challenged in meeting demand. This study aimed to estimate the theoretical cost-optimal capacity requirement for 'step down' intermediate care services within a major healthcare system in England, at a time when considerable uncertainty remained regarding vaccination uptake and the easing of societal restrictions. Methods: Demand for intermediate care was projected using an epidemiological model (for COVID-19 demand) and regressing upon public mobility (for non-COVID-19 demand). These were inputted to a computer simulation model of patient flow from acute discharge readiness to bedded and home-based Discharge to Assess (D2A) intermediate care services. Cost-optimal capacity was defined as that which yielded the lowest total cost of intermediate care provision and corresponding acute discharge delays. Results: Increased intermediate care capacity is likely to bring about lower system-level costs, with the additional D2A investment more than offset by substantial reductions in costly acute discharge delays (leading also to improved patient outcome and experience). Results suggest that completely eliminating acute 'bed blocking' is unlikely economical (requiring large amounts of downstream capacity), and that health systems should instead target an appropriate tolerance based upon the specific characteristics of the pathway. Conclusions: Computer modelling can be a valuable asset for determining optimal capacity allocation along the complex care pathway. With results supporting a Business Case for increased downstream capacity, this study demonstrates how modelling can be applied in practice and provides a blueprint for use alongside the freely-available model code.

A METHOD OF COMPUTER SIMULATION MODELING OF USER AND BOT BEHAVIOR IN A RECOMMENDATION SYSTEM USING THE GRAPH DATABASE NEO4J

The subject matter of the article is the process of computer simulation modeling of complex networks. The goal is to develop a method of computer simulation modeling of ordinary user and bot behavior in a recommendation system based on the theory of complex networks to test the accuracy and robustness of various algorithms for generating recommendations. The tasks to be solved are: to develop a computer simulation model of user and bot behavior in a recommendation system with the ability to generate datasets for testing recommendation generation algorithms. The methods used are: graph theory, theory of complex networks, statistics theory, probability theory, methods of object-oriented programming and methods of working with graph databases. Results. A method of computer simulation modeling of users and objects in a recommender system was proposed, which consists of generating the structure of the social graph of a recommender system and simulating user and bot behavior in it. A series of experiments to test the performance of the developed computer simulation model was carried out. During the experiments, working and testing datasets were generated. Based on the working datasets, the preferences of users by the method of collaborative filtering were predicted. Based on testing datasets, the accuracy of prediction predictions was checked. The results of the experiments showed that the jitter of the investigated values of the Precision, Recall and RMSE of prediction predictions in most practical cases confidently fits within the allowable fluctuation limits, and therefore the users' behavior in computer simulation model was not random and it real users' behavior with certain preferences was simulated. This confirms the reliability of the developed computer simulation model of a recommendation system. Conclusions. A method of computer simulation modeling of user and bot behavior in a recommendation system, which allows generating datasets for testing the algorithms for generating recommendations, was proposed. The developed method makes it possible to simulate the behavior of both ordinary users and bots, which makes it possible to create datasets for testing the robustness of recommender systems to information attacks, as well as for testing the effectiveness of methods for detecting and neutralizing botnets. The structure of relations between users and objects of the recommender system was modeled using the theory of complex networks. Information attacks of bots were modeled on the basis of known models of profile-injection attacks on recommender systems.

The Effect of OPV Module Size on Stability and Diurnal Performance: Outdoor Tests and Application of a Computer Model

The outdoor performance of large area Organic Photovoltaics (OPVs) is investigated in this work. Initially, the diurnal performance of the three modules is determined and found to be similar. Subsequently module degradation is monitored, and it is found that the larger area module displays a significantly greater stability as compared to the smallest area module; in fact the larger module displays a T50% (time to fall to 50% of its original value) of 191 days whilst the smallest module displays a T50% of 57 days. This is attributed to an increased level of water infiltration due to a larger perimeter-to-area ratio. These findings are then used to verify a computer simulation model which allows the model parameters, series and shunt resistances, to be calculated. It is determined that the series resistance is not an obvious obstruction at these module sizes. The findings of this work provide great promise for the application of OPV technology on a larger scale.

Prediction of Wave Energy Transformation Capability in Isolated Islands by Using the Monte Carlo Method

In this work, a mathematical computer simulation model is used to predict the possible energy generated from different Waves Energy Converters (WECs) in the Canary Islands. The Monte Carlo Method is the computer simulation model proposed to predict the generated energy. The Waves Energy Converter systems analyzed in the study were, the Aqua Buoy, Wave Dragon and Pelamis converters. The models were implemented and validated, with the dataset of Gran Canaria deep water buoy. This buoy belongs to a network of buoys belonging to Spain’s State Ports and they cover a dataset period of 22 years. The research has concluded that it is possible to affirm that the achieved model is a strong tool to compute the possible energy of any WECs, when the power matrix is known. The model based on the Monte Carlo simulation can be used in isolated islands of the Atlantic Ocean and can be extrapolated to other regions with the same characteristics.

Delay in the induction of labour process: a retrospective cohort study and computer simulation of maternity unit workload

ObjectivesDelay in the induction of labour (IOL) process is associated with poor patient experience and adverse perinatal outcome. Our objective was to identify factors associated with delay in the IOL process and develop interventions to reduce delay.Design and settingsWe performed a retrospective cohort study of maternity unit workload in a large UK district general hospital. Electronic hospital records were used to quantify delay in the IOL process and linear regression analysis was performed to assess significant associations between delay and potential causative factors. A novel computer maternity unit simulation model, MUMSIM (Maternity Unit Management SIMulation), was developed using real-world data and interventions were tested to identify those associated with a reduction in delay.ParticipantsAll women giving birth at Stoke Mandeville Hospital, Buckinghamshire National Health Service (NHS) Trust in 2018 (n=4932).Primary outcome measureDelay in the IOL process of more than 12 hours.ResultsThe retrospective analysis of real-world maternity unit workload showed 30% of women had IOL and of these, 33% were delayed >12 hours with 20% delayed >24 hours, 10% delayed >48 hours and 1.3% delayed >72 hours. Delay was significantly associated with the total number of labouring women (p=0.008) and the number of booked IOL (p=0.009) but not emergency IOL, spontaneously labouring women or staffing shortfall. The MUMSIM computer simulation predicted that changing from slow release 24-hour prostaglandin to 6-hour prostaglandin for primiparous women would reduce delay by 4% (p<0.0001) and that additional staffing interventions could significantly reduce delay up to 17.9% (p<0.0001).ConclusionsPlanned obstetric workload of booked IOL is associated with delay rather than the unpredictable workload of women in spontaneous labour or emergency IOL. We present a novel maternity unit computer simulation model, MUMSIM, which allows prediction of the impact of interventions to reduce delay.