Mathematical Modeling of the Human Cognitive System in Two Serial Processing Stages With Its Applications in Adaptive Workload-Management Systems

This paper presents a driving simulation platform for the development of Driver Assistance Systems (DAS) with the main purpose of promoting the testing of DAS hardware and advancing the verification of DAS performance. The platform uses a combination of two simulation loops, Hardware-In-the-Loop (HIL) and Driver-In-the-Loop (DIL). Its hardware consists of a simulation computer, a monitor computer, a vision computer, DAS actuators as well as a dummy car. Its software components include several specific ones. When designing its monitor software, a GUI-Driven-by-S-Function (GUIDSF) method is proposed to eliminate the delay in the displaying of the simulation data. The vision rendering software uses adjustment based on the principle of optical projection, considerably improving the driver's perception of being immersed in the virtual traffic scene. The success of the developed platform is demonstrated by HIL experiments of actuators and DIL experiments of ACC. They demonstrate that the proposed actuator control algorithm possesses good tracking capability and ACC is capable of improving ride comfort and reducing driver workload, and consequently, the platform is capable of speeding up DAS development.

AnnotationThis article analyzes the operation numerical simulation for serial and multiphase stages of various manufacturers on water and gas-liquid mixtures (GLM). Are identified the local gas separation areas in serial stages, which can lead to the formation of gas plugs and disruption of the pump supply.These factors include: the creation of a finely dispersed flow structure at the entrance of the stage, the preservation along the flow with small free gas bubbles diameters, the sustenance of the value for the allowed free gas content by circulation means of fluid part in the impeller, a defined relationship between the pressure gradient and the GLM flow rate. A mathematical model is selected, hydrodynamic calculations of structural options, optimization are carried out, a conceptual option is selected. Bench tests were carried out, confirming the high parameters of the product when working on GLM.

Driving is a complex psychomotor task often interrupted by secondary activities that increase cognitive workload and divert attention away from the roadway. The risk of inattentive driving is known to vary with age. To assess the characteristics of advancing age on driver's cognitive workload under dual task condition, we evaluate the performance of 96 drivers divided into three age groups: 20's, 40's, and 60's. This study considers driver's cognitive workload in the context of urban and highway driving. Error rate & Dual task cost are used to measure driver's cognitive workload. Results indicate that age impacts cognitive workload during dual task driving conditions.

Shared steering control has been developed to reduce driver workload while keeping the driver in the control loop. A driver could integrate visual sensory information from the road ahead and haptic sensory information from the steering wheel to achieve better driving performance. Previous studies suggest that, compared with adaptive automation authority, fixed automation authority is not always appropriate with respect to human factors. This paper focuses on designing an adaptive shared steering control system via sEMG (surface electromyography) measurement from the forearm of the driver, and evaluates the effect of the system on driver behavior during a double lane change task. The shared steering control was achieved through a haptic guidance system which provided active assistance torque on the steering wheel. Ten subjects participated in a high-fidelity driving simulator experiment. Two types of adaptive algorithms were investigated: haptic guidance decreases when driver grip strength increases (HG-Decrease), and haptic guidance increases when driver grip strength increases (HG-Increase). These two algorithms were compared to manual driving and two levels of fixed authority haptic guidance, for a total of five experimental conditions. Evaluation of the driving systems was based on two sets of dependent variables: objective measures of driver behavior and subjective measures of driver workload. The results indicate that the adaptive authority of HG-Decrease yielded lower driver workload and reduced the lane departure risk compared to manual driving and fixed authority haptic guidance.

An improved de-embedding method is used to measure the intrinsic HBT S parameters to millimetre wave frequencies. Standard twelve-error element models and dummy pads with resistors as calibration standards are used. This new method correctly reveals the effect from the extra delay time, parasitic capacitance, and parasitic inductance introduced by the layout and enables the performance at millimetre-wave frequencies to be accurately predicted.

Modern driver assistance systems make increasing use of auditory and tactile signals in order to reduce the driver's visual information load. This entails potential crossmodal interaction effects that need to be taken into account in designing an optimal system. Here we show that saccadic reaction times to visual targets (cockpit or outside mirror), presented in a driving simulator environment and accompanied by auditory or tactile accessories, follow some well-known spatiotemporal rules of multisensory integration, usually found under confined laboratory conditions. Auditory nontargets speed up reaction time by about 80 ms. The effect tends to be maximal when the nontarget is presented 50 ms before the target and when target and nontarget are spatially coincident. The effect of a tactile nontarget (vibrating steering wheel) was less pronounced and not spatially specific. It is shown that the average reaction times are well-described by the stochastic “time window of integration” model for multisensory integration developed by the authors. This two-stage model postulates that crossmodal interaction occurs only if the peripheral processes from the different sensory modalities terminate within a fixed temporal interval, and that the amount of crossmodal interaction manifests itself in an increase or decrease of second stage processing time. A qualitative test is consistent with the model prediction that the probability of interaction, but not the amount of crossmodal interaction, depends on target–nontarget onset asynchrony. A quantitative model fit yields estimates of individual participants' parameters, including the size of the time window. Some consequences for the design of driver assistance systems are discussed.

Estimating of radiation output of X-RAY tube using mathematical model: Case of high-frequency machines

Mathematical modelling is a powerful tool that bridges the gap between theoretical concepts and real-world phenomena. It involves the development of mathematical equations, algorithms, and computational techniques to describe, analyse, and predict complex systems across various disciplines. Researchers are creating mathematical models based on actual events to meet the demands of this scientific era. The main aim of mathematical modelling is to gain understanding into complex systems, make predictions, and optimize processes. By using mathematical equations, scientists and researchers can simulate and analyse various scenarios, explore the effects of different parameters, and make informed decisions. Mathematical models can provide a better understanding of the given mechanisms governing the system and help uncover relationships and patterns that may not be immediately apparent. Policymakers use mathematical models to inform their choices when deciding on public health interventions like lockdowns, social isolation tactics, and vaccination rollout plans.

We describe a model and report a new method to extract quantified data from the simple analysis of whole uroflow curves in healthy and symptomatic individuals. Recorded flow curves were compared with the curves theoretically predicted from a mathematical micturition model. This model was developed by relating each physiological event occurring during micturition to a set of mathematical equations. Due to improvements in speed of computer calculations, a very fast and adaptable mathematical micturition model became available. A total of 302 uroflow curves from 142 patients (61 men and 81 women) were studied. The control group consisted of seven men and 25 women; the symptomatic groups comprised 54 men and 56 women. The mathematical model was applied to analyze all the recorded curves. For patients with lower urinary tract symptoms, specific modelization parameters were introduced according to the clinical condition to be tested. Using two compulsory (patient sex and voided volume) and two optional parameters (clinical condition and urethral catheter size), our mathematical model was able to produce uroflow calculated curves similar to observed curves. In the control group, the calculated and recorded uroflow curves were found to superimpose with an impressive accuracy, i.e., a quadratic error <1%. Test-re-test studies gave the same determination of the specific parameters. In benign prostatic hyperplasia patients, the compressive effect on both prostatic urethra and bladder neck was separately identified. The same intra-individual values were found at 2-week intervals in the group with no treatment (P = no significance), whereas after 3 months of treatment with an alpha-blocker, a decrease in values was noted in responder patients (P < 0.001). In women with various degrees of cystocele, a constrictive effect was identified and found to be identical for successive flows during the same urodynamic testing. This large prospective study demonstrated the relevance of a sophisticated, heavily computerized micturition model, taking into account physiological voiding parameters, to the study of flow in healthy individuals and patients with benign prostatic hyperplasia or cystocele. Curve-fitting led to the determination of critical events during flow such as break point and plateau phase. Determination of these events may enhance uroflow interpretation by providing additional information on the detrusor function. Neurourol. Urodynam. 19:153-176, 2000.

Relationship between braking intensity and driver heart rate as a function of the size of the measurement window and its position

Differential speedometers are gauges that continually display real-time over/under vehicle speed relative to the current speed limit. Use of these gauges may increase situation awareness and reduce driver workload. The design of such a gauge, however, is critical to its usability and its effect on driver performance. Thirty differential speedometer designs were brainstormed and subsequently down-selected to nine gauges using a heuristic assessment. The selected gauges were then tested for usability in a desktop study. Participants answered questions regarding vehicle speed with respect to the current speed limit using information presented on the gauges. Understanding was assessed by measuring the response time and accuracy of the participants’ response. Subjective ratings of usability and overall gauge preference were also obtained. Results were used to select three gauge designs for future study in a vehicle simulator for the purpose of selecting an optimal design of a differential speedometer.

User trust and acceptance are critical for the success of Automated Vehicles (AVs) in enhancing road safety and reducing driver workload. This study aims to investigate the influence of AV style (careful or aggressive) and driver style (careful or aggressive) on trust in AVs, while considering the role of initial trust level. A questionnaire-based survey was conducted with 204 participants, and responses were analyzed utilizing a Linear Mixed Model (LMM) with AV style, driver style and initial level as fixed effects. Two significant two-way interactions were observed: between driver style and AV style, and another between initial trust and AV style on trust. Specifically, careful AVs were rated with a higher trust than aggressive AVs by both driver groups. Additionally, aggressive drivers trusted aggressive AVs more than careful drivers, but careful AVs gain the same trust. Interestingly, participants with medium initial trust exhibited a less divergence in trust between different AV styles, yet the trust gaps between different trust groups consistently existed. These findings underscore the importance of aligning driver style, AV style, and initial trust levels to cultivate heightened trust in AVs.

Human Requirements Validation for Complex Systems Design

Mathematical modeling and its potential applications in pharmacy are discussed. A model is a simplified representation of the real world. As an experimental approach, modeling minimizes expense, risk, and disruption, but its validity can be hard to ascertain. Mathematical models describe numerically the relationships among elements of a system and are a powerful tool in making decisions affecting that system. There are two types of mathematical models: analytical models, which directly describe the relationships between system inputs and outputs using mathematical equations (such as pharmacokinetic models), and simulation models, which involve the replication, usually with a computer, of events as they occur in the real world. Analytical models are easier to develop but are not appropriate for describing highly complex systems. In continuous-time simulation, the system is represented as an uninterrupted flow of material; in discrete-event simulation, it is assumed that events occur only at distinct times. Various simulation programs are commercially available. The stages of a mathematical modeling study are (1) formulate the problem, (2) determine the model's structure, (3) collect and analyze initial data, (4) develop the model further, (5) validate the model, (6) experiment using the model, and (7) use the results. There have been many applications of modeling in health care, but relatively few have involved the study of pharmacy systems. Mathematical modeling offers pharmacists a low-risk, low-cost tool for aiding decisions about pharmacy systems by predicting alternative futures.

The term “hydraulics” is concerned with the conveyance of water that can consist of very simple processes to complex physical processes, such as flow in open rivers, flow in pipes, the flow of nutrients/sediments, the flow of groundwater to sea waves. The study of hydraulics is primarily a mixture of theory and experiments. Computational hydraulics is very helpful to quantify and predict flow nature and behavior. The mathematical model is the backbone of the computational hydraulics that consists of simple to complex mathematical equations with linear and/or non-linear terms and ordinary or partial differential equations. Analytical solution to these mathematical equations is not feasible in the majority of cases. In these consequences, mathematical models are solved using different numerical techniques and associated schemes. In this manuscript, we aim to review hydraulic principles along with their mathematical equations. Then we aim to learn some commonly used numerical techniques to solve different types of differential equations related to hydraulics. Among them, the Finite Difference Method (FDM), Finite Element Method (FEM) and Finite Volume Method (FVM) have been discussed along with their use in real-life applications in the context of water resources engineering.