Estimation of a disease model based on a discrete time Markov model using secondary data with transitions based on multi-dimensional tablesBarhak, Jacob
doi: 10.1177/0037549716673729pmid: N/A
The progression of a disease may be affected by many risk factors, such as gender, age, and current disease state. Such information is collected and made publically available by published clinical studies, yet combining this information into a disease model remains a challenge. This paper extends the previously published maximum likelihood estimation technique to estimate model parameters from indirect secondary data. Such information is available in the scientific literature so the modeler can access more data when estimating model parameters. The extension to the estimation procedure allows model transitions that depend on different sets of covariates for which secondary data are available. This extension uses a Markov model with transition probabilities stored in multi-dimensional tables accessed by covariate values. The paper uses a set of cases, including a case of cardiovascular disease in diabetes. The cases demonstrate the proposed method with various model variations. To help cope with model multiplicity, a selection method is demonstrated for picking a preferred model according to likelihood and structure criteria.
Geometrical and mechanical characteristics of deformed balance spring obtained by simulation studyPopkonstantinovic, Branislav; Obradovic, Ratko; Obradovic, Marija; Jeli, Zorana; Stojicevic, Miša
doi: 10.1177/0037549716673453pmid: N/A
This paper analyzes the geometrical and mechanical characteristics of balance springs, which have the most important influence on the oscillation rate of the balance wheel and, consequently, the most decisive effects on the timekeeper’s accuracy. These characteristics are obtained by a set of SolidWorks simulations of static structural studies based on the finite element model, which are performed and accomplished in a specific and original way. Our study demonstrates that the position of the balance spring center of mass and its momentum of inertia are not constant but depend on the angular displacement of the spring collet end. It also shows that the torque spring rate (the spring stiffness) varies as a function of angular displacement during the balanced spring twist. All results are presented numerically and graphically by a set of diagrams and can contribute to the better understanding of the balance spring geometrical and mechanical features and, therefore, be applied for improving a timepiece’s accuracy. Moreover, the method of simulation study disclosed and explained in this paper provides general suggestions and guidance for similar studies. The accuracy of the presented results, as well as the validity of the complete simulation-based method, is proven by the experimentally determined relationship between balance spring restoring torque, stiffness, and spring angular displacement.
An agent-based model for simulation of traffic network status: Applied to Hanoi cityNguyen, Manh Hung; Ho, Tuong Vinh
doi: 10.1177/0037549716668259pmid: N/A
In recent times there have been many agent-based simulation models proposed for transportation network simulation. Intuitively, these models are applicable for the transportation simulation of modern cities in developed countries where the transportation network is very well organized: Roads are separated into lanes; most transportation occurs using vehicles; and almost all drivers respect the circulation rule. However, these models are not suitable for developing countries where the transportation network is unorganized. The reasons for this are as follows: (1) there is no lane on the road; (2) most vehicles are motorbikes; and (3) not many drivers respect the circulation rule. This paper introduces an agent-based model for transportation network simulation in which each form of transport is modeled as an agent exhibiting full features of unorganized circulation behavior. The model is designed for a large scale and instead of displaying the circulation for all individual modes of transport, the model displays only the status of the traffic network. The simulation of circulation is therefore considered as a background process. The simulation is launched and the results are obtained before being displayed. This model is applied to the traffic network of Hanoi to analyze the hot or bottle neck points on the transportation network during rush hours in the city.
Optimizing a fuzzy logic traffic signal controller via the differential evolution algorithm under different traffic scenariosDoğan, Erdem; Akgüngör, Ali P
doi: 10.1177/0037549716673217pmid: N/A
This study aims at optimizing fuzzy logic controller (FLC) triangle membership functions (MFs) for different traffic volumes via differential evolution (DE). To achieve this goal, a new FLC with a red time limiter, which actually calculates green time and the extension time of traffic movement phase, is developed to control an intersection. Subsequently, this FLC is optimized with two levels, namely Level-1 and Level-2. Level-1 searches each fuzzy class’s minimum and maximum values (α and β) that generate the lowest average delay per vehicle with DE. Using DE Level-2 inherits Level-1 ranges and reshapes the MFs to explore lower delay values computed by Level-1. The proposed method is tested with nine different traffic scenarios. For each scenario, 15 different headways are applied for a four-leg isolated intersection. The results indicate that the intersection average performance is increased up to 52%, 48%, and 14% at 800, 1600, and 2400 veh/h total intersection volumes, respectively, after Level-1 optimizations. They also reveal that intersection control produces higher delay values in only four scenarios after Level-2 procedures. Consequently, it is shown that the DE has significant potential to optimize FLCs at the intersection signal control. In addition, tuning fuzzy class ranges is found to be more critical than the MF reshaping process in traffic control via FLCs.
An efficient Model Predictive Control-based motion cueing algorithm for the driving simulatorFang, Zhou; Kemeny, Andras
doi: 10.1177/0037549716667835pmid: N/A
Recently, a new technique using a MPC (Model Predictive Control)-based motion cueing algorithm has been successfully applied in driving simulation. However, the feasibility and the stability condition of MPC, a crucial criterion for high-performance simulators, has barely been addressed except in our previous works and in Dagdelen et al. (Model-based predictive motion cueing strategy for vehicle driving simulators. Contr Eng Pract 2009; 17: 995–1003). In this paper, it is shown that based on an implicit MPC algorithm using qpOASES, the authors’ proposed feasibility and stability condition not only guarantees the feasibility and stability of the MPC-based motion cueing algorithm, but also controls washout motion, taking into account the driver’s perception threshold, thus resulting in a more robust and flexible motion cueing algorithm and a better motion feeling than that for the conventional motion cueing algorithms.