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1
Pujol, Oriol, Debora Gil, and Petia Radeva. "Fundamentals of Stop and Go active models." Image and Vision Computing 23, no. 8 (2005): 681–91. http://dx.doi.org/10.1016/j.imavis.2005.03.007.
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Schall, Jeffrey D., Thomas J. Palmeri, and Gordon D. Logan. "Models of inhibitory control." Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1718 (2017): 20160193. http://dx.doi.org/10.1098/rstb.2016.0193.
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We survey models of response inhibition having different degrees of mathematical, computational and neurobiological specificity and generality. The independent race model accounts for performance of the stop-signal or countermanding task in terms of a race between GO and STOP processes with stochastic finishing times. This model affords insights into neurophysiological mechanisms that are reviewed by other authors in this volume. The formal link between the abstract GO and STOP processes and instantiating neural processes is articulated through interactive race models consisting of stochastic accumulator GO and STOP units. This class of model provides quantitative accounts of countermanding performance and replicates the dynamics of neural activity producing that performance. The interactive race can be instantiated in a network of biophysically plausible spiking excitatory and inhibitory units. Other models seek to account for interactions between units in frontal cortex, basal ganglia and superior colliculus. The strengths, weaknesses and relationships of the different models will be considered. We will conclude with a brief survey of alternative modelling approaches and a summary of problems to be addressed including accounting for differences across effectors, species, individuals, task conditions and clinical deficits. This article is part of the themed issue ‘Movement suppression: brain mechanisms for stopping and stillness’.
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Pamanikabud, Pichai, and Chaisri Tharasawatpipat. "Stop-and-Go Urban Traffic Noise Simulation and Prediction." Noise & Vibration Worldwide 33, no. 4 (2002): 17–24. http://dx.doi.org/10.1260/095745602320753156.
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This paper presents techniques for simulating of urban traffic noise along with a mathematical model of stop-and-go traffic noise for the road network in the city center. The road network in the central part of Bangkok surrounded by the cordon line of Rajchadapisek Ring Road was used as the study area. The analysed data consisted of traffic characteristics and its noise levels which were collected from the study area together with the geometrical dimensions of road sections at each data collection locations. Finally, the stop-and-go traffic noise models generated by this study in the form of acceleration and deceleration lane models, and their statistical goodness of fit tests are presented.
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Penadés, R., R. Catalán, K. Rubia, S. Andrés, M. Salamero, and C. Gastó. "Impaired response inhibition in obsessive compulsive disorder." European Psychiatry 22, no. 6 (2006): 404–10. http://dx.doi.org/10.1016/j.eurpsy.2006.05.001.
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AbstractObjectiveThe present study investigates different three inhibitory control functions in patients with obsessive-compulsive disorder (OCD). Selective motor response inhibition was tested in a GO/NO-GO paradigm, the inhibition of a triggered motor response in a STOP paradigm and the ability to inhibit cognitive interference in a motor STROOP paradigm.Methods27 patients who met DSM-IV criteria for OCD and 25 age, handedness and IQ-matched healthy control subjects were tested in the GO/NO-GO, STOP and motor STROOP tasks.ResultsOCD patients performed significantly worse than controls in the selective inhibition of their motor responses (GO/NO-GO) and in the inhibition of cognitive interference (STROOP), and also showed worse performance in suppressing previously triggered motor responses (STOP).ConclusionPatients with OCD are impaired in motor and cognitive inhibitory mechanisms. The findings are consistent with psychobiological and neuropsychological models of OCD suggesting impairment of frontostriatal circuitries that mediate functions of inhibitory control.
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Farah, Ashraf, Ashraf Talaat, and Farrag Farrag. "Accuracy Assessment of Digital Elevation Models Using GPS." Artificial Satellites 43, no. 4 (2008): 151–61. http://dx.doi.org/10.2478/v10018-009-0014-7.
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Accuracy Assessment of Digital Elevation Models Using GPSA Digital Elevation Model (DEM) is a digital representation of ground surface topography or terrain with different accuracies for different application fields. DEM have been applied to a wide range of civil engineering and military planning tasks. DEM is obtained using a number of techniques such as photogrammetry, digitizing, laser scanning, radar interferometry, classical survey and GPS techniques. This paper presents an assessment study of DEM using GPS (Stop&Go) and kinematic techniques comparing with classical survey. The results show that a DEM generated from (Stop&Go) GPS technique has the highest accuracy with a RMS error of 9.70 cm. The RMS error of DEM derived by kinematic GPS is 12.00 cm.
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Soltanifar, Mohsen, Michael Escobar, Annie Dupuis, Andre Chevrier, and Russell Schachar. "The Asymmetric Laplace Gaussian (ALG) Distribution as the Descriptive Model for the Internal Proactive Inhibition in the Standard Stop Signal Task." Brain Sciences 12, no. 6 (2022): 730. http://dx.doi.org/10.3390/brainsci12060730.
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Measurements of response inhibition components of reactive inhibition and proactive inhibition within the stop-signal paradigm have been of particular interest to researchers since the 1980s. While frequentist nonparametric and Bayesian parametric methods have been proposed to precisely estimate the entire distribution of reactive inhibition, quantified by stop signal reaction times (SSRT), there is no method yet in the stop signal task literature to precisely estimate the entire distribution of proactive inhibition. We identify the proactive inhibition as the difference of go reaction times for go trials following stop trials versus those following go trials and introduce an Asymmetric Laplace Gaussian (ALG) model to describe its distribution. The proposed method is based on two assumptions of independent trial type (go/stop) reaction times and Ex-Gaussian (ExG) models. Results indicated that the four parametric ALG model uniquely describes the proactive inhibition distribution and its key shape features, and its hazard function is monotonically increasing, as are its three parametric ExG components. In conclusion, the four parametric ALG model can be used for both response inhibition components and its parameters and descriptive and shape statistics can be used to classify both components in a spectrum of clinical conditions.
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Czapla, Marta, Sabine Vollstädt-Klein, Mira Fauth-Bühler, et al. "Response inhibition deficits: Reliability of alcohol-related assessment tasks." SUCHT 62, no. 4 (2016): 203–15. http://dx.doi.org/10.1024/0939-5911/a000431.
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Abstract. Background: While models of addictive behaviour stress the role of an impairment of response inhibition when drug-dependent individuals are confronted with drug-associated stimuli, results from different studies are conflicting. However, there is a considerable lack of studies that assess the reliability of tasks to assess deficits of response inhibition when drug-associated stimuli are presented. Methods: In the present paper we present results from four different studies in which either a stop-signal task (study 1), a go/no-go task (study 2/3) or a go/no-go shifting task (study 4) with alcohol-related stimuli was administered to alcohol-dependent patients or control participants and split-half and/or test-retest reliability of the different outcome measures calculated. Results: Our results suggest that the go/no-go task and the go/no-go shifting task are more reliable tasks to assess impairment of inhibition in response to alcohol-associated stimuli than to the stop-signal task. Especially the go/no-go shifting task achieves at least acceptable split-half as well as test-retest reliability indices for outcome measure related to the presentation of alcohol-associated stimuli. Nevertheless, for alcohol-dependent patients reliability indices are generally considerably lower than for control participants and thus care should be taken when these tasks are administered to alcohol-dependent patients. Conclusion: Future studies are warranted to enhance our understanding of true effects and random error
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Wilson, R. Eddie. "Mechanisms for spatio-temporal pattern formation in highway traffic models." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 366, no. 1872 (2008): 2017–32. http://dx.doi.org/10.1098/rsta.2008.0018.
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A key qualitative requirement for highway traffic models is the ability to replicate a type of traffic jam popularly referred to as a phantom jam , shock wave or stop-and-go wave . Despite over 50 years of modelling, the precise mechanisms for the generation and propagation of stop-and-go waves and the associated spatio-temporal patterns are in dispute. However, the increasing availability of empirical datasets, such as those collected from motorway incident detection and automatic signalling system (MIDAS) inductance loops in the UK or the next-generation simulation trajectory data (NGSIM) project in the USA, means that we can expect to resolve these questions definitively in the next few years. This paper will survey the essence of the competing explanations of highway traffic pattern formation and introduce and analyse a new mechanism, based on dynamical systems theory and bistability, which can help resolve the conflict.
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Dong, Sheng, and Jibiao Zhou. "A Comparative Study on Drivers’ Stop/Go Behavior at Signalized Intersections Based on Decision Tree Classification Model." Journal of Advanced Transportation 2020 (May 29, 2020): 1–13. http://dx.doi.org/10.1155/2020/1250827.
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The stop/go decisions at signalized intersections are closely related to driving speed during signal change intervals. The speed during stop/go decision-making has a significant influence on the dilemma area, resulting in changes of stop/go decisions and high complexity of the decision-making process. Considering that traffic delays and vehicle exhaust pollution are mainly caused by queuing at intersections, the stop-line passing speed during the signal change interval will affect both vehicle operation safety and the atmospheric environment. This paper presents a comparative study on drivers’ stop/go behaviors when facing a transition signal period consisting of 3 s green flashing light (FG) and 3 s yellow light (Y) at rural high-speed intersections and urban intersections. For this study, 1,459 high-quality vehicle trajectories of five intersections in Shanghai during the transition signal period were collected. Of these five intersections, three are high-speed intersections with a speed limit of 80 km/h, and the other two are urban intersections with a speed limit of 50 km/h. Trajectory data of these vehicle samples were statistically analyzed to investigate the general characteristics of potential influencing factors, including the instantaneous speed and the distance to the intersection at the start of FG, the vehicle type, and so on. Decision Tree Classification (DTC) models are developed to reveal the relationship between the drivers’ stop/go decisions and these possible influencing factors. The results indicate that the instantaneous speed of FG onset, the distance to the intersection at the start of FG, and the vehicle type are the most important predictors for both types of intersections. Besides, a DTC model can offer a simple way of modeling drivers’ stopping decision behavior and produce good results for urban intersections.
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Tordeux, Antoine, Andreas Schadschneider, and Sylvain Lassarre. "Stop-and-go waves induced by correlated noise in pedestrian models without inertia." Journal of Traffic and Transportation Engineering (English Edition) 7, no. 1 (2020): 52–60. http://dx.doi.org/10.1016/j.jtte.2019.01.006.
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Saxena, Neeraj, Ruiyang Wang, Vinayak V. Dixit, and S. Travis Waller. "Frequentist and Bayesian Approaches for Understanding Route Choice of Drivers under Stop-and-Go Traffic." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 9 (2020): 371–82. http://dx.doi.org/10.1177/0361198120929332.
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Driving in congested traffic is a nuisance that not only results in longer travel times, but also triggers frustration and impatience among drivers. A few studies have modeled the effects of congested traffic in the resulting route choice behavior of car drivers. The studies used frequentist models such as discrete choice models to analyze large samples. However, these studies did not compare the inferences obtained from the frequentist and Bayesian approaches, particularly for datasets which are not sufficiently large. It has been shown by researchers that Bayesian models perform well, especially when the sample size is small. Thus, this paper develops and compares a multinomial logit (frequentist) and a Naïve Bayes (Bayesian) model on a mid-sized dataset of size around 100 participants which was obtained from a driving simulator experiment to understand driver’s route choice under stop-and-go traffic. The results show that the prediction power of the Naïve Bayes model is much higher than the multinomial logit model (MNL). The Naïve Bayes model is also found to perform better than machine learning algorithms like the decision tree model. The findings from this study will be useful to researchers and practitioners as they should test both the approaches and select the appropriate model, particularly in the case of seemingly large datasets.
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Molloy, M. Fiona, Giwon Bahg, Zhong-Lin Lu, and Brandon M. Turner. "Individual Differences in the Neural Dynamics of Response Inhibition." Journal of Cognitive Neuroscience 31, no. 12 (2019): 1976–96. http://dx.doi.org/10.1162/jocn_a_01458.
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Response inhibition is a widely studied aspect of cognitive control that is particularly interesting because of its applications to clinical populations. Although individual differences are integral to cognitive control, so too is our ability to aggregate information across a group of individuals, so that we can powerfully generalize and characterize the group's behavior. Hence, an examination of response inhibition would ideally involve an accurate estimation of both group- and individual-level effects. Hierarchical Bayesian analyses account for individual differences by simultaneously estimating group and individual factors and compensate for sparse data by pooling information across participants. Hierarchical Bayesian models are thus an ideal tool for studying response inhibition, especially when analyzing neural data. We construct hierarchical Bayesian models of the fMRI neural time series, models assuming hierarchies across conditions, participants, and ROIs. Here, we demonstrate the advantages of our models over a conventional generalized linear model in accurately separating signal from noise. We then apply our models to go/no-go and stop signal data from 11 participants. We find strong evidence for individual differences in neural responses to going, not going, and stopping and in functional connectivity across the two tasks and demonstrate how hierarchical Bayesian models can effectively compensate for these individual differences while providing group-level summarizations. Finally, we validated the reliability of our findings using a larger go/no-go data set consisting of 179 participants. In conclusion, hierarchical Bayesian models not only account for individual differences but allow us to better understand the cognitive dynamics of response inhibition.
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Tordeux, Antoine, and Andreas Schadschneider. "White and relaxed noises in optimal velocity models for pedestrian flow with stop-and-go waves." Journal of Physics A: Mathematical and Theoretical 49, no. 18 (2016): 185101. http://dx.doi.org/10.1088/1751-8113/49/18/185101.
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Mahona, John N. P., Cuthbert F. Mhilu, Joseph Kihedu, and Hannibal Bwire. "Effects of static bottlenecks on traffic flow in urban road network." International Journal of Engineering, Science and Technology 12, no. 3 (2020): 1–15. http://dx.doi.org/10.4314/ijest.v12i3.1.
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Existing traffic flow models do not consider the effects of road static bottlenecks on traffic flow. In this paper, a modified macroscopic continuum model for traffic flow on urban road network with static bottlenecks is presented. The model takes into account the fluctuations of traffic flow considering static bottlenecks during the morning peak period. The model results show that existence of static road bottlenecks with various configurations cause traffic flow instabilities. This phenomenon lead into stop-and-go traffic flow conditions under the moderate density and reduction of the traffic system’s efficiency. Furthermore, results show that an increase in traffic density is accompanied by a significant decrease of speed which adversely influences performance of roadway and decrease the traffic system’s efficiency and thus resulting to the occurrence of congestions. The methodological aspects of the study and results will enable traffic engineers and planners to assess and improve existing urbanroad networks.
 Keywords: Traffic flow, Bottlenecks, stability, Stop-and-go traffic, System’s efficiency, Congestion.
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Cai, Jing, Jianyou Zhao, Yusheng Xiang, et al. "Can I Trust You? Estimation Models for e-Bikers Stop-Go Decision before Amber Light at Urban Intersection." Journal of Advanced Transportation 2020 (December 23, 2020): 1–17. http://dx.doi.org/10.1155/2020/6678996.
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Electric bike (e-bike) riders’ inappropriate go-decision, yellow-light running (YLR), could lead to accidents at intersection during the signal change interval. Given the high YLR rate and casualties in accidents, this paper aims to investigate the factors influencing the e-bikers’ go-decision of running against the amber signal. Based on 297 cases who made stop-go decisions in the signal change interval, two analytical models, namely, a base logit model and a random parameter logit model, were established to estimate the effects of contributing factors associated with e-bikers’ YLR behaviours. Besides the well-known factors, we recommend adding approaching speed, critical crossing distance, and the number of acceleration rate changes as predictor factors for e-bikers’ YLR behaviours. The results illustrate that the e-bikers’ operational characteristics (i.e., approaching speed, critical crossing distance, and the number of acceleration rate change) and individuals’ characteristics (i.e., gender and age) are significant predictors for their YLR behaviours. Moreover, taking effects of unobserved heterogeneities associated with e-bikers into consideration, the proposed random parameter logit model outperforms the base logit model to predict e-bikers’ YLR behaviours. Providing remarkable perspectives on understanding e-bikers’ YLR behaviours, the predicting probability of e-bikers’ YLR violation could improve traffic safety under mixed traffic and fully autonomous driving condition in the future.
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Knechtel, J., L. Klingbeil, J. H. Haunert, and Y. Dehbi. "OPTIMAL POSITION AND PATH PLANNING FOR STOP-AND-GO LASERSCANNING FOR THE ACQUISITION OF 3D BUILDING MODELS." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-4-2022 (May 18, 2022): 129–36. http://dx.doi.org/10.5194/isprs-annals-v-4-2022-129-2022.
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Abstract. Terrestrial laser scanning has become more and more popular in recent years. The according planning of the standpoint network is a crucial issue influencing the overhead and the resulting point cloud. Fully static approaches are both cost and time extensive, whereas fully kinematic approaches cannot produce the same data quality. Stop-and-go scanning, which combines the strengths of both strategies, represents a good alternative solution. In the scanning process, the standpoint planning is by now mostly a manual process based on expert knowledge and relying on the surveyor’s experience. This paper provides a method based on Mixed Integer Linear Programming (MILP) ensuring an optimal placement of scanner standpoints considering all scanner-related constraints (e.g. incidence angle), a full coverage of the scenery, a sufficient overlap for the subsequent registration and an optimal route planning solving a Traveling Salesperson Problem (TSP). This enables the fully automatic application of autonomous systems for providing a complete model while performing a stop-and-go laser scanning, e.g. with the Spot robot from Boston Dynamics. Our pre-computed solution, i.e. standpoints and trajectory, has been evaluated surveying a real-world environment using a 360° panoramic laser scanner and successfully compared with a precise LoD2 building model of the underlying scene. The performed ICP-based registration issued from our fully automatic pipeline turns out to be a very good and safe alternative of the otherwise laborious target-based registration.
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van den Wildenberg, Wery P. M., Geert J. M. van Boxtel, Maurits W. van der Molen, D. Andries Bosch, Johannes D. Speelman, and Cornelis H. M. Brunia. "Stimulation of the Subthalamic Region Facilitates the Selection and Inhibition of Motor Responses in Parkinson's Disease." Journal of Cognitive Neuroscience 18, no. 4 (2006): 626–36. http://dx.doi.org/10.1162/jocn.2006.18.4.626.
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The aim of the present study was to specify the involvement of the basal ganglia in motor response selection and response inhibition. Two samples were studied. The first sample consisted of patients diagnosed with Parkinson's disease (PD) who received deep-brain stimulation (DBS) of the subthalamic nucleus (STN). The second sample consisted of patients who received DBS for the treatment of PD or essential tremor (ET) in the ventral intermediate nucleus of the thalamus (Vim). Stop-signal task and go/no-go task performances were studied in both groups. Both groups performed these tasks with (on stimulation) and without (off stimulation) DBS to address the question of whether stimulation is effective in improving choice reaction time (RT) and stop-signal RT. The results show that DBS of the STN was associated with significantly enhanced inhibitory control, as indicated by shorter stop-signal RTs. An additional finding is that DBS of the STN led to significantly shorter choice RT. The effects of DBS on responding and response inhibition were functionally independent. Although DBS of the Vim did not systematically affect task performance in patients with ET, a subgroup of Vim-stimulated PD patients showed enhanced stop-signal RTs in on stimulation versus off stimulation. This result suggests that the change in performance to stop signals may not be directly related to STN function, but rather results from a change in PD function due to DBS in general. The findings are discussed in terms of current functional and neurobiological models that relate basal ganglia function to the selection and inhibition of motor responses.
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Can, A., and D. Botteldooren. "Towards Traffic Situation Noise Emission Models." Acta Acustica united with Acustica 97, no. 5 (2011): 900–903. http://dx.doi.org/10.3813/aaa.918469.
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This article proposes a methodology to account for vehicle kinematics in a fast and efficient way when using single vehicle noise emission models such as the Harmonoise/Imagine, Nord2000 or NMPB. A model is built, which mimics the traffic situation emission models developed in the field of airborne pollutants research. The model aggregates the sound power emitted over driving cycles which are statistically representative of real-world driving conditions. Four different driving conditions are included in the cycles, ranging from free-flowing to stop-and-go traffic conditions. The sound power levels estimated with this new approach are significantly different from the ones estimated with the mean speed approach recommended by the noise mapping guidelines, especially when traffic is congested, suggesting that the method could prove relevant for improving noise map accuracy, in particular in urban context.
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Li, Haisheng, Junshe An, Xiujie Jiang, and Meiyan Lin. "Raw Data Simulation of Spaceborne Synthetic Aperture Radar with Accurate Range Model." Remote Sensing 15, no. 11 (2023): 2705. http://dx.doi.org/10.3390/rs15112705.
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Simulated raw data have become an essential tool for testing and assessing system parameters and imaging performance due to the high cost and limited availability of real raw data from spaceborne synthetic aperture radar (SAR). However, with increasing resolution and higher orbit altitudes, existing simulation methods fail to generate SAR simulated raw data that closely resemble real raw data. This is due to approximations such as curved orbits, “stop-and-go” assumption, and Earth’s rotation, among other factors. To overcome these challenges, this paper presents an accurate range model with a “nonstop-and-go” configuration for raw data simulation based on existing time-domain simulation methods. We model the SAR echo signal and establish a precise space geometry for spaceborne SAR. Additionally, we precisely identify the target illumination area based on elliptical beams through space coordinate transformation. Finally, the SAR raw data were accurately simulated using high-precision time-domain simulation methods. The accuracy of the proposed model was validated by comparing it with the traditional hyperbolic model and the curved orbit model with “stop-and-go” assumption through image processing of the generated raw data. Through the analysis of point target quality parameters, the errors of various parameters in our distance model compared with the other two models are within 1%. Furthermore, this simulation method can be adapted to simulate raw data of other modes and satellite orbits by adjusting beam control and satellite orbit parameters, respectively. The proposed simulation method demonstrated high accuracy and versatility, thereby providing a valuable contribution to the development of remote sensing technology.
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Jefferies-Sewell, Kiri, Samuel R. Chamberlain, Naomi A. Fineberg, and Keith R. Laws. "Cognitive dysfunction in body dysmorphic disorder: new implications for nosological systems and neurobiological models." CNS Spectrums 22, no. 1 (2016): 51–60. http://dx.doi.org/10.1017/s1092852916000468.
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IntroductionBody dysmorphic disorder (BDD) is a debilitating disorder, characterized by obsessions and compulsions relating specifically to perceived appearance, and which has been newly classified within the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) Obsessive-Compulsive and Related Disorders grouping. Until now, little research has been conducted into the cognitive profile of this disorder.MethodsParticipants with BDD (n=12) and participants without BDD (n=16) were tested using a computerized neurocognitive battery investigating attentional set-shifting (Intra/Extra Dimensional Set Shift Task), decision-making (Cambridge Gamble Task), motor response-inhibition (Stop-Signal Reaction Time Task), and affective processing (Affective Go-No Go Task). The groups were matched for age, IQ, and education.ResultsIn comparison to controls, patients with BDD showed significantly impaired attentional set-shifting, abnormal decision-making, impaired response inhibition, and greater omission and commission errors on the emotional processing task.ConclusionDespite the modest sample size, our results showed that individuals with BDD performed poorly compared to healthy controls on tests of cognitive flexibility, reward and motor impulsivity, and affective processing. Results from separate studies in OCD patients suggest similar cognitive dysfunction. Therefore, these findings are consistent with the reclassification of BDD alongside OCD. These data also hint at additional areas of decision-making abnormalities that might contribute specifically to the psychopathology of BDD.
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Chou, Fang-Chieh, Alben Rome Bagabaldo, and Alexandre M. Bayen. "The Lord of the Ring Road: A Review and Evaluation of Autonomous Control Policies for Traffic in a Ring Road." ACM Transactions on Cyber-Physical Systems 6, no. 1 (2022): 1–25. http://dx.doi.org/10.1145/3494577.
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This study focuses on the comprehensive investigation of stop-and-go waves appearing in closed-circuit ring road traffic wherein we evaluate various longitudinal dynamical models for vehicles. It is known that the behavior of human-driven vehicles, with other traffic elements such as density held constant, could stimulate stop-and-go waves, which do not dissipate on the circuit ring road. Stop-and-go waves can be dissipated by adding automated vehicles (AVs) to the ring. Thorough investigations of the performance of AV longitudinal control algorithms were carried out in Flow, which is an integrated platform for reinforcement learning on traffic control. Ten AV algorithms presented in the literature are evaluated. For each AV algorithm, experiments are carried out by varying distributions and penetration rates of AVs. Two different distributions of AVs are studied. For the first distribution scenario, AVs are placed consecutively. Penetration rates are varied from 1 AV (5%) to all AVs (100%). For the second distribution scenario, AVs are placed with even distribution of human-driven vehicles in between any two AVs. In this scenario, penetration rates are varied from 2 AVs (10%) to 11 AVs (50%). Multiple runs (10 runs) are simulated to average out the randomness in the results. From more than 3,000 simulation experiments, we investigated how AV algorithms perform differently with varying distributions and penetration rates while all AV algorithms remained fixed under all distributions and penetration rates. Time to stabilize, maximum headway, vehicle miles traveled, and fuel economy are used to evaluate their performance. Using these metrics, we find that the traffic condition improvement is not necessarily dependent on the distribution for most of the AV controllers, particularly when no cooperation among AVs is considered. Traffic condition is generally improved with a higher AV penetration rate with only one of the AV algorithms showing a contrary trend. Among all AV algorithms in this study, the reinforcement learning controller shows the most consistent improvement under all distributions and penetration rates.
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Cilliers, Jeanne, and Martine Mariotti. "Stop! Go! What Can We Learn About Family Planning From Birth Timing in Settler South Africa, 1835–1950?" Demography 58, no. 3 (2021): 901–25. http://dx.doi.org/10.1215/00703370-9164749.
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Abstract We revisit the discussion on family limitation through stopping and spacing behavior before and during the fertility transition with a sample of 12,800 settler women's birth histories in nineteenth- and twentieth-century South Africa. Using cure models that allow us to separate those who stop childbearing from those who continue, we find no evidence of parity-specific spacing before the transition. We do find evidence of non-parity-based birth postponement before the transition. Increased stopping and parity-independent postponement characterized the beginning of the fertility transition, with increased parity-specific spacing following later in the transition phase.
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Lu, Chaoru, Jing Dong, Anuj Sharma, Tingting Huang, and Skylar Knickerbocker. "Predicting Freeway Work Zone Capacity Distribution Based on Logistic Speed-Density Models." Journal of Advanced Transportation 2018 (November 1, 2018): 1–15. http://dx.doi.org/10.1155/2018/9614501.
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Speed-volume-density relationship and capacity are key elements in modelling traffic operations, designing roadways, and evaluating facility performance. This paper uses a modified five-parameter logistic model to describe the speed-density relationship. The calibrated speed-density models show that the stop-and-go speed (Vb) and shape parameters (θ1 and θ2) are similar for work zones and the nonwork zone site. Accordingly, an operational capacity prediction method is proposed. To demonstrate the effectiveness of the proposed method, the predicted operational capacities are compared with the field data, Highway Capacity Manual method, the output of WorkZoneQ software, and the ensemble tree approach under different work zone scenarios. Furthermore, a lifetime distribution prediction framework for stochastic capacity of work zones is proposed. The predicted lifetime distribution can well capture the tendency of the observed work zone capacities.
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Cao, Qianxia, Zhongxing Zhao, Qiaoqiong Zeng, Zhengwu Wang, and Kejun Long. "Real-Time Vehicle Trajectory Prediction for Traffic Conflict Detection at Unsignalized Intersections." Journal of Advanced Transportation 2021 (December 20, 2021): 1–15. http://dx.doi.org/10.1155/2021/8453726.
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Real-time prediction of vehicle trajectory at unsignalized intersections is important for real-time traffic conflict detection and early warning to improve traffic safety at unsignalized intersections. In this study, we propose a robust real-time prediction method for turning movements and vehicle trajectories using deep neural networks. Firstly, a vision-based vehicle trajectory extraction system is developed to collect vehicle trajectories and their left-turn, go straight, and right-turn labels to train turning recognition models and multilayer LSTM deep neural networks for the prediction task. Then, when performing vehicle trajectory prediction, we propose the vehicle heading angle change trend method to recognize the future move of the target vehicle to turn left, go straight, and turn right based on the trajectory data characteristics of the target vehicle before passing the stop line. Finally, we use the trained multilayer LSTM models of turning left, going straight, and turning right to predict the trajectory of the target vehicle through the intersection. Based on the TensorFlow-GPU platform, we use Yolov5-DeepSort to automatically extract vehicle trajectory data at unsignalized intersections. The experimental results show that the proposed method performs well and has a good performance in both speed and accuracy evaluation.
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Maia, Mateus, Jonatha S. Pimentel, Ivalbert S. Pereira, João Gondim, Marcos E. Barreto, and Anderson Ara. "Convolutional Support Vector Models: Prediction of Coronavirus Disease Using Chest X-rays." Information 11, no. 12 (2020): 548. http://dx.doi.org/10.3390/info11120548.
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The disease caused by the new coronavirus (COVID-19) has been plaguing the world for months and the number of cases are growing more rapidly as the days go by. Therefore, finding a way to identify who has the causative virus is impressive, in order to find a way to stop its proliferation. In this paper, a complete and applied study of convolutional support machines will be presented to classify patients infected with COVID-19 using X-ray data and comparing them with traditional convolutional neural network (CNN). Based on the fitted models, it was possible to observe that the convolutional support vector machine with the polynomial kernel (CSVMPol) has a better predictive performance. In addition to the results obtained based on real images, the behavior of the models studied was observed through simulated images, where it was possible to observe the advantages of support vector machine (SVM) models.
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Nakai, Teruhisa. "An optimal stopping problem in the excavation of archaeological remains." Journal of Applied Probability 28, no. 4 (1991): 924–29. http://dx.doi.org/10.2307/3214698.
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In the excavation of archaeological remains of high value, a search tool with low cost can be used at first, but if we reach a stratum which is very likely to contain valuable material we must use a search tool with high efficiency to reduce the risk of destruction of the remains even if this is more expensive. Which tool should we use at each time? Furthermore, if the search costs too much in comparison with the reward of detection, it is not profitable to go on searching for ever. When should we stop the search? We answer these questions for continuous and discrete models.
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Nakai, Teruhisa. "An optimal stopping problem in the excavation of archaeological remains." Journal of Applied Probability 28, no. 04 (1991): 924–29. http://dx.doi.org/10.1017/s0021900200042868.
Full textAbstract:
In the excavation of archaeological remains of high value, a search tool with low cost can be used at first, but if we reach a stratum which is very likely to contain valuable material we must use a search tool with high efficiency to reduce the risk of destruction of the remains even if this is more expensive. Which tool should we use at each time? Furthermore, if the search costs too much in comparison with the reward of detection, it is not profitable to go on searching for ever. When should we stop the search? We answer these questions for continuous and discrete models.
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KUMAR, Kranti, Manoranjan PARIDA, and Vinod Kumar KATIYAR. "Road Traffic Noise Prediction with Neural Networks - A Review." An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 2, no. 1 (2011): 29–37. http://dx.doi.org/10.11121/ijocta.01.2012.0059.
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This paper aims to summarize the findings of research concerning the application of neural networks in traffic noise prediction. Noise is an environmental agent, regarded as a stressful stimulus. Noise exposure causes changes at different levels in living beings, such as the cardiovascular, endocrine and nervous system. Study of traffic noise prediction models began in 1950s to predict a single vehicle sound pressure level at the road side. After that, several traffic noise prediction models such as FHWA, CORTN, STOP and GO, MITHRA, ASJ etc. were developed depending upon various parameters and conditions. Complexity of error identification by means of classical approaches has led to researchers and designers to explore the possibility of neural solution to the problem of traffic noise prediction. Present study is focused on review of various neural network models developed for road traffic noise prediction.
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Briani, Maya, Emiliano Cristiani, and Paolo Ranut. "Macroscopic and Multi-Scale Models for Multi-Class Vehicular Dynamics with Uneven Space Occupancy: A Case Study." Axioms 10, no. 2 (2021): 102. http://dx.doi.org/10.3390/axioms10020102.
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In this paper, we propose two models describing the dynamics of heavy and light vehicles on a road network, taking into account the interactions between the two classes. The models are tailored for two-lane highways where heavy vehicles cannot overtake. This means that heavy vehicles cannot saturate the whole road space, while light vehicles can. In these conditions, the creeping phenomenon can appear, i.e., one class of vehicles can proceed even if the other class has reached the maximal density. The first model we propose couples two first-order macroscopic LWR models, while the second model couples a second-order microscopic follow-the-leader model with a first-order macroscopic LWR model. Numerical results show that both models are able to catch some second-order (inertial) phenomena such as stop and go waves. Models are calibrated by means of real data measured by fixed sensors placed along the A4 Italian highway Trieste–Venice and its branches, provided by Autovie Venete S.p.A.
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Zhu, Kangli, Jiantao Bi, Jianjun Wu, and Shubin Li. "Effects of speed bottleneck on traffic flow with feedback control signal." Modern Physics Letters B 30, no. 25 (2016): 1650323. http://dx.doi.org/10.1142/s0217984916503231.
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Various car-following models (CMs) have been developed to capture the complex characteristics of microscopic traffic flow, among which the coupled map CM can better reveal and reflect various phenomena of practical traffic flow. Capacity change at bottleneck contributes to high-density traffic flow upstream the bottleneck and contains very complex dynamic behavior. In this paper, we analyze the effect of speed bottleneck on the spatial-temporal evolution characteristics of traffic flow, and propose a method to reduce traffic congestion with the feedback control signal based on CM. Simulation results highlight the potential of using the feedback signal to control the stop-and-go wave and furthermore to alleviate the traffic congestion effectively.
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Huma Rauf, Huma Sikandar, and Muhammad Umar. "Transport emission models: A bibliometric and content analysis." Journal of Public Value and Administrative Insight 5, no. 2 (2022): 395–423. http://dx.doi.org/10.31580/jpvai.v5i2.2530.
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Environment deterioration and subsequent climate change require the accountability of each contributor. Pollutants produced from fossil fuel in the transport sector is measured using emission models and this paper offers a Bibliometric analysis of these models from 1990-2020 of previous literature supported with the content analysis done in two tiers; review of the most cited research work of last ten years and the evolving research themes from recently published articles of last five years. From Bibliometric analysis, we identified top authors, institutions and journals, co-occurrence analysis of keywords, and co-authorship countries. Content analysis revealed that emission models have evolved globally with modifications and integrations of new techniques, multi disciplinary variables combining emission, transport, air quality, dispersion, and environment models. The technological adaptations in models have also been carried out locally by some countries bringing transport emissions to inventory counting for global warming potential. Research trends for future emission reduction suggest that besides the warming potential of fossil fuel from the transport sector, parallel reductions can be achieved through efficient traffic planning, road designs, driving patterns, stop and go cycles, traffic calming techniques impacting spatial and temporal goals through reduced clustering and hot spots.
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Ray, Supriya, Pierre Pouget, and Jeffrey D. Schall. "Functional Distinction Between Visuomovement and Movement Neurons in Macaque Frontal Eye Field During Saccade Countermanding." Journal of Neurophysiology 102, no. 6 (2009): 3091–100. http://dx.doi.org/10.1152/jn.00270.2009.
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In the previous studies on the neural control of saccade initiation using the countermanding paradigm, movement and visuomovement neurons in the frontal eye field were grouped as movement-related neurons. The activity of both types of neurons was modulated when a saccade was inhibited in response to a stop signal, and this modulation occurred early enough to contribute to the control of the saccade initiation. We now report a functional difference between these two classes of neurons when saccades are produced. Movement neurons exhibited a progressive accumulation of discharge rate following target presentation that triggered a saccade when it reached a threshold. When saccades were inhibited with lower probability in response to a stop signal appearing at longer delays, this accumulating activity was interrupted at levels progressively closer to the threshold. In contrast, visuomovement neurons exhibited a maintained elevated discharge rate following target presentation that was followed by a further enhancement immediately before the saccade initiation. When saccades were inhibited in response to a stop signal, the late enhancement was absent and the maintained activity decayed regardless of stop-signal delay. These results demonstrate that the activity of movement neurons realizes the progressive commitment to the saccade initiation modeled by the activation of the go unit in computational models of countermanding performance. The lack of correspondence of the activity of visuomovement neurons with any elements of these models indicates that visuomovement neurons perform a function other than the saccade preparation such as a corollary discharge to update visual processing.
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Yin, Derek, and Tony Z. Qiu. "Compatibility analysis of macroscopic and microscopic traffic simulation modeling." Canadian Journal of Civil Engineering 40, no. 7 (2013): 613–22. http://dx.doi.org/10.1139/cjce-2012-0104.
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To implement model predictive traffic control to reduce congestion, traffic state variables such as flow, speed, and density need to be accurately predicted with real-time measurements. To evaluate the accuracy of online prediction of a macroscopic traffic model, this paper compares the predicted flow, density, and speed from a macroscopic simulation model with those from a microscopic simulation model, using METANET and VISSIM respectively, on a section of urban freeway. Three levels of traffic demands and seven different time step lengths in macroscopic simulation were applied to evaluate the compatibility of the two models. It was concluded that in the macroscopic simulation model there exists an optimum time step length, under moderate to heavy traffic demands the predicted traffic states from the macroscopic simulation are consistent with the outputs from the microscopic simulation, and under stop-and-go traffic states significant difference exists between the two models.
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Kang, Min-Wook, Moynur Rahman, and Joyoung Lee. "Determination and Utilization of Dilemma Zone Length and Location for Safety Assessment of Rural High-Speed Signalized Intersections." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 4 (2020): 272–80. http://dx.doi.org/10.1177/0361198120911929.
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The objective of the present study is to see how the dilemma zone length and location are related to intersection safety at rural high-speed signalized intersections. For that, dilemma zones at 30 rural signalized intersection approaches where similar traffic operations and land-use conditions are present were identified, and traffic conflicts associated with the dilemma zones were investigated. Drivers’ stop or go behaviors as well as vehicle dynamics (e.g., vehicle speeds and locations) during the yellow and red clearance intervals were collected and analyzed to determine the dilemma zone length and location of each site. Red-light running violations and vehicles’ abrupt stops were also collected to investigate the relationship between such conflicts and dilemma zone length and location. As a result, two dilemma zone conflict models were developed. The analysis results show that the conflict models are accurate enough to predict the safety level of high-speed signalized intersections using the two dilemma zone variables. Results show that the chance of intersection angle conflicts increases if the dilemma zone is located farther from the intersection stop bar. Results also show that there would be a high chance of rear-end conflicts if the dilemma zone length is longer. The models were validated with additional datasets, and acceptable root means square error and mean absolute percentage error values were obtained as a result.
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Shi, Zhongke, Wenhuan Ai, and Dawei Liu. "An Improved Macro Model of Traffic Flow with the Consideration of Ramps and Numerical Tests." Mathematical Problems in Engineering 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/136451.
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We present an improved macro model for traffic flow based on the existing models. The equilibrium point equation of the model is obtained. The stop-and-go traffic phenomenon is described in phase plane and the relationship between traffic jams and system instability is clearly shown in the phase plane diagrams. Using the improved model, some traffic phenomena on a highway with ramps are found in this paper. The numerical simulation is carried out to investigate various nonlinear traffic phenomena with a single ramp generated by different initial densities and vehicle generation rates. According to the actual road sections of Xi’an-Baoji highways, the situations of morning peak with several ramps are also analyzed. All these results are consistent with real traffic, which shows that the improved model is reasonable.
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Jamieson, R. A., C. Beaumont, C. J. Warren, and M. H. Nguyen. "The Grenville Orogen explained? Applications and limitations of integrating numerical models with geological and geophysical dataThis article is one of a series of papers published in this Special Issue on the theme Lithoprobe — parameters, processes, and the evolution of a continent." Canadian Journal of Earth Sciences 47, no. 4 (2010): 517–39. http://dx.doi.org/10.1139/e09-070.
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Numerical models offer powerful insights into tectonic processes, especially when their validity can be tested against geological and geophysical observations from natural orogenic belts. Here we explain some of the criteria for success in integrating orogenic models with data, using examples from the Grenville Orogen. Model designs must be simplified by comparison with nature to illuminate the first-order processes that control orogenic evolution, which limits the extent to which model results can reproduce geological observations. For the western Grenville Orogen, observed variations in geological properties are represented by lower crustal blocks with strength decreasing from the exterior to the interior of the model. GO-series models with this design reproduce the first-order crustal architecture of the Georgian Bay and Montréal – Val d’Or Lithoprobe transects. Both constant-convergence and stop-convergence models produce similar geometries, but only stop-convergence models produce normal-sense shear zones like those observed. EGO-series models, incorporating an initial weak zone bounded by stronger lower crustal blocks, predict exhumation of high-pressure rocks as observed in the eastern Grenville Orogen, although other aspects of these model results are not as successful. The single most important test of a geodynamic model is its ability to integrate diverse and independent observations in a self-consistent manner. Other criteria include consistency with crustal-scale geometry and structural and metamorphic histories. By these criteria, the present models account reasonably well for the syn- and post-convergent evolution of the western Grenville Orogen, but further work is required to produce a fully satisfactory model for the eastern end of the system.
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Gusak, Andriy, A. O. Kovalchuk, and King Ning Tu. "Diffusion in Point Contact Reaction." Defect and Diffusion Forum 309-310 (March 2011): 143–48. http://dx.doi.org/10.4028/www.scientific.net/ddf.309-310.143.
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Recently) the point contact reactions between silicon nanowires (covered by natural oxide) and nanowires or nanodots of metals (nickel, cobalt, platinum) were discovered and studied. These reactions have at least three remarkable characteristics: (1) the reaction product phase is quite different from thin film or bulk reactions (for example, in Ni-Si reaction the appearing phase is Ni1Si1 or Ni1Si2, depending on the orientation of Si, instead of common Ni2Si phase); (2) Phase is formed not in the contact zone but, instead, near the wire tip or between two point contacts; (3) Subsequent phase growth of silicide inside silicon nanowire is a “stop-and-go” process consisting of waiting time before formation of critical island of each new atomic layer and then the fast filling of this new layer (mechanism suggested in 30-s for ideal crystals) Models of surface diffusion along and penetration through silicon oxide are presented. Nucleation models need more place and will be discussed in subsequent parts
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Salwa, Athiyah S. S., and Sry Ratna Dewi. "Strengthening Students’ Motivation and Confidence to Achieve Learning Goals in Blended Learning Method." IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature 9, no. 2 (2021): 296–309. http://dx.doi.org/10.24256/ideas.v9i2.2288.
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Pandemic outbreak today has changed any sectors including education, from their normal state into the condition we never expected before. From primary to higher education, the institutions are forced to change teaching and learning models into virtual since the Government tries to stop the spread of the virus by prohibiting face-to-face classes. Online learning has come like tsunami trends as the outbreak rose. It also happened in some vocational schools where students live in the dormitory. Initially, they conducted offline classes, but they were transferred to go home as the virus spread. In one semester, they faced two models of learning, online and offline. Based on this situation, this article aims to disseminate the effectiveness of blended-learning models to improve students' motivation and confidence in speaking class by using the material to build their high-order thinking skills. The method of this study is combined between experimental and descriptive qualitative, by which the result of the study and analysis will be described in numbers and words.
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Jin, Wen-Long, and Yu Zhang. "Paramics Simulation of Periodic Oscillations Caused by Network Geometry." Transportation Research Record: Journal of the Transportation Research Board 1934, no. 1 (2005): 188–96. http://dx.doi.org/10.1177/0361198105193400120.
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Traffic oscillations such as stop-and-go waves in a traffic system can occur for a variety of reasons, such as instabilities. This paper describes a study of a type of periodic oscillations caused by network geometry with a microscopic simulation model, Paramics. With careful tuning in Paramics, periodic oscillations in which traffic states change periodically between a diverging junction and a merging junction are successfully simulated. The formation process is discussed in detail. The study suggests that, given an appropriate network structure and traffic conditions, the local oscillations caused by randomness in car-following and lane-changing models in Paramics can be maintained and can become periodic and global. Finally, the consistencies between a macroscopic kinematic wave model and Paramics are discussed, and future research topics and the implications of the findings of the study are presented.
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Markovskaya, Elizaveta, Elena Smolina, Kolawole Shola Ojo, Igor Merzlikin, and Igor Pryadko. "Risk modeling in the aviation industry as a factor of sustainable development." E3S Web of Conferences 381 (2023): 02008. http://dx.doi.org/10.1051/e3sconf/202338102008.
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Research by leading economists has revealed that risks in the aviation industry affect the forecasting models of regional sustainable development. The current study is devoted to the development of approaches to risk assessment on the example of European airlines. This problem has become very problematic after several recent financial crises, when airlines around the world were going through difficult times, and dozens of them had to go bankrupt, receive financial assistance from governments or find their salvation in mergers or acquisitions with larger players in the market with the support of governments. Since the beginning of the pandemic, airlines around the world have faced many more serious problems that have forced them to stop most of their passenger flights due to restrictions aimed at reducing the incidence. Unlike other financial crises, the pandemic faces the most serious problem of uncertainty, since it is difficult to predict how the virus will behave and when it will stop. This study is aimed at developing approaches that can help identify and predict possible airline risks and establish regulatory values of significant indicators for this industry in Europe.
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Ali, Akbar, Nasir Ayub, Muhammad Shiraz, Niamat Ullah, Abdullah Gani, and Muhammad Ahsan Qureshi. "Traffic Efficiency Models for Urban Traffic Management Using Mobile Crowd Sensing: A Survey." Sustainability 13, no. 23 (2021): 13068. http://dx.doi.org/10.3390/su132313068.
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The population is increasing rapidly, due to which the number of vehicles has increased, but the transportation system has not yet developed as development occurred in technologies. Currently, the lowest capacity and old infrastructure of roads do not support the amount of vehicles flow which cause traffic congestion. The purpose of this survey is to present the literature and propose such a realistic traffic efficiency model to collect vehicular traffic data without roadside sensor deployment and manage traffic dynamically. Today’s urban traffic congestion is one of the core problems to be solved by such a traffic management scheme. Due to traffic congestion, static control systems may stop emergency vehicles during congestion. In daily routine, there are two-time slots in which the traffic is at peak level, which causes traffic congestion to occur in an urban transportation environment. Traffic congestion mostly occurs in peak hours from 8 a.m. to 10 a.m. when people go to offices and students go to educational institutes and when they come back home from 4 p.m. to 8 p.m. The main purpose of this survey is to provide a taxonomy of different traffic management schemes for avoiding traffic congestion. The available literature categorized and classified traffic congestion in urban areas by devising a taxonomy based on the model type, sensor technology, data gathering techniques, selected road infrastructure, traffic flow model, and result verification approaches. Consider the existing urban traffic management schemes to avoid congestion and to provide an alternate path, and lay the foundation for further research based on the IoT using a Mobile crowd sensing-based traffic congestion control model. Mobile crowdsensing has attracted increasing attention in traffic prediction. In mobile crowdsensing, the vehicular traffic data are collected at a very low cost without any special sensor network infrastructure deployment. Mobile crowdsensing is very popular because it can transmit information faster, collect vehicle traffic data at a very low cost by using motorists’ smartphone or GPS vehicular embedded sensor, and it is easy to install, requires no special network deployment, has less maintenance, is compact, and is cheaper compared to other network options.
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Rábová, Ivana. "Using UML and Petri nets for visualization of business document flow." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 60, no. 2 (2012): 299–306. http://dx.doi.org/10.11118/actaun201260020299.
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The article deals with two principles of business workflow modeling, Petri nets and UML notation, that are the acceptable approaches to business modeling and can be used also for business documents workflow. The special type of Petri nets, WF-nets and UML activity diagrams are used in this article and both modeling ways are presented on the concrete business workflow and then there are presented and specified their advantage and disadvantage for business documents flows. At beginning it is explained the word workflow in context business documents, its features, principles and using in business environment. After that it is clarified that the UML is OMG’s most-used specification, and the way the world models not only application structure, behavior, and architecture, but also business process, workflows and data structure. Activity diagram UML is good way to show how different workflows in the business are managed, how they start, go and stop. Diagrams also show many different decision paths that can be taken from start to finish. State charts can be used as a detail the transitions or changes of states when documents can go through in the business. They show how a documents moves from one state to another and the rules that govern that change. Petri-nets offer a graphical notation for stepwise processes that include choice, iteration, and concurrent execution. Unlike UML Petri nets have an exact mathematical definition of their execution semantics, with a well-developed mathematical theory for process analysis. In the article there are modeled a special type of Petri nets, the WF-nets. The practical part of article incorporates two models of concrete business documents workflows presented in these notations, their comparison and recommendation for using these diagrams in business process management.
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Li, Jia, Gui Yu Lin, and Qiu Fang Xia. "Research on the Establishing Model Method of Engine Eternal Characteristic Curve Based on F Distribution." Advanced Materials Research 971-973 (June 2014): 684–87. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.684.
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The external characteristic curve of engine is the basis of choosing engine, matching and optimizing dynamic performance correctly. At present, most models of the external characteristic curve of engine are carried out by using polynomial regression equation for fitting the external characteristic curve of engine. In this paper, an establishing model method of the external characteristic curve of engine based on F distribution testing is proposed. F test with variance analysis is implemented for obtaining the difference of square sum of return difference between the former equation and the latter equation. If the test doesn’t go through, it can rise one level automatically, until the difference about square sum of return difference of the before-after fitting equation is no significant can it stop. This method provides a theoretical criterion for establishing model of the external characteristic curve of engine. When it is applied to the engineering case, the model will have a higher fitting precision.
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Ningbo, Cao, Wei Wei, Qu Zhaowei, Zhao Liying, and Bai Qiaowen. "Simulation of Pedestrian Crossing Behaviors at Unmarked Roadways Based on Social Force Model." Discrete Dynamics in Nature and Society 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/8741534.
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Limited pedestrian microcosmic simulation models focus on the interactions between pedestrians and vehicles at unmarked roadways. Pedestrians tend to head to the destinations directly through the shortest path. So, pedestrians have inclined trajectories pointing destinations. Few simulation models have been established to describe the mechanisms underlying the inclined trajectories when pedestrians cross unmarked roadways. To overcome these shortcomings, achieve solutions for optimal design features before implementation, and help to make the design more rational, the paper establishes a modified social force model for interactions between pedestrians and vehicles at unmarked roadways. To achieve this goal, stop/go decision-making model based on gap acceptance theory and conflict avoidance models were developed to make social force model more appropriate in simulating pedestrian crossing behaviors at unmarked roadways. The extended model enables the understanding and judgment ability of pedestrians about the traffic environment and guides pedestrians to take the best behavior to avoid conflict and keep themselves safe. The comparison results of observed pedestrians’ trajectories and simulated pedestrians’ trajectories at one unmarked roadway indicate that the proposed model can be used to simulate pedestrian crossing behaviors at unmarked roadways effectively. The proposed model can be used to explore pedestrians’ trajectories variation at unmarked roadways and improve pedestrian safety facilities.
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Al-Jameel, Hamid Athab. "DEVELOPING A NEW HYBRID SAFETY CAR-FOLLOWING MODEL." Kufa Journal of Engineering 5, no. 2 (2014): 47–60. http://dx.doi.org/10.30572/2018/kje/521327.
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For more than five decades, car-following models have been developed based on different theoretical backgrounds and conditions. The importance of these models belongs to their representation of longitudinal movement for any simulation model. Therefore, the accuracy of the car-following model is still the core of strength of any simulation model. For the purpose of this study, a hybrid car-following model has been developed to represent “go and stop” conditions. These conditions mostly occur in a weaving section. This model has been developed as a corner stone for a microscopic simulation model of representation of driver behaviour at a weaving section. A new condition that improves a driver behaviour in a situation at which the driver should not accelerate under specific condition as approaching from decelerated leading vehicle. Some assumptions of this model have been adopted from the CARSIMmodel. After developing this model using Visual Compact Fortran (version 6.5), the developed model has been calibrated with a set of field data from Germany. The results show that this model is more reasonable than other models such as Paramics, VISSIM, AIMSUNand CARSIMusing the same set of data. This model show significantly improvement in representing the reality than the others.
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Tan, Chunxi, Ruijian Han, Rougang Ye, and Kani Chen. "Adaptive Learning Recommendation Strategy Based on Deep Q-learning." Applied Psychological Measurement 44, no. 4 (2019): 251–66. http://dx.doi.org/10.1177/0146621619858674.
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Personalized recommendation system has been widely adopted in E-learning field that is adaptive to each learner’s own learning pace. With full utilization of learning behavior data, psychometric assessment models keep track of the learner’s proficiency on knowledge points, and then, the well-designed recommendation strategy selects a sequence of actions to meet the objective of maximizing learner’s learning efficiency. This article proposes a novel adaptive recommendation strategy under the framework of reinforcement learning. The proposed strategy is realized by the deep Q-learning algorithms, which are the techniques that contributed to the success of AlphaGo Zero to achieve the super-human level in playing the game of go. The proposed algorithm incorporates an early stopping to account for the possibility that learners may choose to stop learning. It can properly deal with missing data and can handle more individual-specific features for better recommendations. The recommendation strategy guides individual learners with efficient learning paths that vary from person to person. The authors showcase concrete examples with numeric analysis of substantive learning scenarios to further demonstrate the power of the proposed method.
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Przespolewski, Amanda, Elizabeth A. Griffiths, James E. Thompson, et al. "Phase 1/1b Trial of Talazoparib and Gemtuzumab Ozogamicin in Adult Patients with Relapsed or Refractory Acute Myeloid Leukemia." Blood 136, Supplement 1 (2020): 20–21. http://dx.doi.org/10.1182/blood-2020-141736.
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Background: Poly (ADP-ribose) polymerase (PARP) enzymes are involved in repair of single-strand DNA breaks through base excision repair pathways. Inhibitors of PARP are approved for the treatment of BRCA1/2-mutant malignancies where they result in compromise of dual DNA damage repair pathways, leading to induction of double-strand DNA breaks during replication and ultimately cell death. We have previously demonstrated (Portwood et al, ASH 2019 abstract) that PARP inhibitors can reduce in vitro acute myeloid leukemia (AML) growth and can synergistically enhance the anti-leukemic activity of antibody-drug conjugates containing DNA-damaging cytotoxic agents in preclinical human AML models. Talazoparib (Tala) is a novel selective PARP inhibitor which has been shown to exert more potent growth inhibitory effects across a panel of human AML cell lines than four other PARP inhibitors (veliparib, olaparib, rucaparib, niraparib). Gemtuzumab ozogamicin (GO) is an approved drug consisting of an antibody against human CD33 (gemtuzumab) linked to a cytotoxic component (calicheamicin). Hypothesis: We hypothesize that the combination of Tala + GO will be well tolerated and will result in improved clinical efficacy as compared with historical outcomes of GO monotherapy in patients with relapsed or refractory (R/R) AML. Objectives: The primary objectives of this study are (a) to determine the safety and tolerability of Tala + GO therapy in R/R AML; (b) to determine the overall response rate (ORR = complete remission (CR) + complete remission with incomplete hematologic recovery (CRi)) of combination therapy in patients with R/R AML. Additional anti-leukemic effects will be reported including complete remission rate, best response rate, duration of remission, leukemia-free survival, transfusion independence, and overall survival. Exploratory aims include measurable residual disease, evidence of PARP inhibition and DNA damage, feasibility of subsequent allogeneic stem cell transplant, and quality of life. Study Design: This open-label multi-center, Phase 1/1b trial is designed to determine whether the combination of Tala and GO represents a safe and effective approach for R/R AML. Eligible patients are adults aged ≥18 years with CD33-positive AML whose disease has failed to respond to and/or has recurred following at least one prior line of chemotherapy. There are two parts of the study: dose escalation and dose expansion. The dose escalation portion will establish the recommended Phase 2 dose (RP2D) of Tala in combination with GO. Cohorts of 3 subjects will be treated at one of three dose levels of Tala (0.5 mg, 0.75 mg, and 1 mg orally daily) in combination with fixed doses of GO (3 mg/m2/day on days 1,4, and 7, capped to one 4.5 mg vial) using a standard 3+3 subject cohort dose evaluation. Treatment will be given in 28-day cycles. The dose limiting toxicity (DLT) window will be Cycle 1 Day 1 to 28. Therapy may be given in the outpatient setting. Following determination of the RP2D, an expansion cohort of patients will be treated with the combination of Tala + GO for preliminary assessment of toxicities and anti-leukemic efficacy. Bone marrow assessment will be performed on Day 28 of Cycles 1 and 2. Safety and activity will be assessed using descriptive statistical analysis. If a patient achieves CR/CRi after cycles 1-2, the GO dose will be reduced to a maintenance dose of 2 mg/m2 on day 1 only of every subsequent cycle until disease progression or for a maximum of 6 total cycles of therapy. Patients not achieving a clinical response after 2 cycles will stop treatment. Treatment duration will be up to six months. This trial was activated in July 2020 and is registered at ClinicalTrials.gov (NCT04207190). Accrual is ongoing. Disclosures Griffiths: Novartis: Honoraria, Research Funding; Celgene/BMS: Honoraria, Research Funding; Boston Biomedical: Honoraria; Persimmune: Research Funding; AbbVie Inc: Honoraria; Genentech Inc: Research Funding; Astex Pharmceuticals: Research Funding; Alexion Pharmaceuticals: Honoraria, Research Funding. Emadi:Jazz Pharmaceuticals: Research Funding; NewLink Genetics: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Genentech: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees; KinaRx: Other: co-founder and scientific advisor. Baer:AbbVie: Other: Institutional research funding; Astellas: Other: Institutional research funding; Forma: Other: Institutional research funding; Incyte: Other: Institutional research funding; Kite: Other: Institutional research funding; Oscotec: Other: Institutional research funding; Takeda: Other: Institutional research funding. Wang:Stemline: Speakers Bureau; Astellas: Consultancy; PTC Therapeutics: Consultancy; Macrogenics: Consultancy; Jazz Pharmaceuticals: Consultancy; Bristol Meyers Squibb (Celgene): Consultancy; Abbvie: Consultancy; Genentech: Consultancy; Pfizer: Speakers Bureau.
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Skandali, N., BJ Sahakian, TWR Robbins, and V. Voon. "#3071 Acute escitalopram administration increases premature responding as a function of reward magnitude in healthy male volunteers." Journal of Neurology, Neurosurgery & Psychiatry 92, no. 8 (2021): A8. http://dx.doi.org/10.1136/jnnp-2021-bnpa.20.
Full textAbstract:
ObjectivesImpulsivity is a multifaceted construct that involves a tendency to act prematurely with little foresight, reflection or control. Waiting impulsivity is one aspect of action impulsivity and is commonly studied in animals using tasks such as the 5-choice serial reaction time task (5CSRTT).1 It is neurochemically distinct from motor response inhibition defined as the ability to restrain or cancel a pre-potent motor response and measured with no-go and stop-signal tasks respectively.1 Serotonin modulates waiting impulsivity as decreased serotonergic transmission promotes premature responding in the rodent 5CSRT and the human analogue 4CSRT task.2 Potential mechanisms contributing to waiting impulsivity include proactive or tonic inhibition, motivational processes and sensitivity to feedback and delay.3 Higher waiting impulsivity in response to high reward cues was previously associated with greater subthalamic nucleus connectivity with orbitofrontal cortex and greater subgenual cingulate connectivity with anterior insula.4MethodsWe administered a clinically relevant dose of escitalopram (20mg) in healthy subjects in a double-blind, placebo-controlled, parallel-groups design study and assessed its effect on waiting impulsivity using the well-validated 4CSRT task. Compared to previous studies,2 4 we added another test block with increased potential gain to assess the interaction between premature responding and reward processing. We recruited sixty-six healthy participants who completed an extensive neuropsychological test battery assessing probabilistic reversal learning, set-shifting, response inhibition, emotional processing and waiting impulsivity. Sixty participants (N=60, 26 females, 34 males) completed the 4CSRT task with N=30 in the escitalopram and N=30 in the placebo group, due to technical errors and experienced side-effects for the remaining six participants. The results of the other cognitive tasks are reported separately.5ResultsEscitalopram increased premature responding in the high incentive condition of the 4CSRT task, p=.028, t= 2.275, this effect being driven by male participants, p=.019, t=2.532 (for females, p>.05). We further show that escitalopram increased premature responses after a premature response in the same block again in male participants only, p=.034, Mann-Whitney U= 61.500. We found no correlation between premature responding in the 4CSRT task, in any test block, and the Stop-signal reaction time, the primary measure of the stop-signal task completed by the same participants (reported in [5]).ConclusionsWe show that acute escitalopram increased premature responding in healthy male participants only in high incentive conditions potentially mediated potentially through an effect on increased incentive salience. We also show that acute escitalopram increased perseverative responding thus producing a maladaptive response strategy. We show no correlation between SSRT and premature responding in the same participants consistent with these two forms of impulsivity being neurochemically and anatomically distinct. We interpret our findings in the context of acute escitalopram decreasing serotonergic transmission in some brain areas through inhibitory actions on terminal 5-HT release mediated by auto-receptors on raphe 5-HT neurons analogous to the presumed transient reduction in 5-HT activity caused by ATD.5Our findings provide further insights in the relationship of premature responding and reward processing and our understanding of pathological impulse control behaviours.References Eagle DM, Bari A, Robbins TW. The neuropsychopharmacology of action inhibition: cross-species translation of the stop-signal and go/no-go tasks. Psychopharmacology 2008;199(3):439456. Worbe Y, Savulich G, Voon V, Fernandez-Egea E, Robbins TW. Serotonin depletion induces waiting impulsivityon the human four-choice serial reaction time task: cross-species translational significance. Neuropsychopharmacology 2014;39(6):15191526. Voon V. Models of impulsivity with a focus on waiting impulsivity: translational potential for neuropsychiatric disorders. Current Addiction Reports 2014;1(4):281288. Mechelmans DJ, Strelchuk D, Doamayor N, Banca P, Robbins TW, Baek K, et al. Reward sensitivity and waiting impulsivity: shift towards reward valuation away from action control. International Journal of Neuropsychopharmacology 2017;20(12):971978. Skandali N, Rowe JB, Voon V, Deakin JB, Cardinal RN, Cormack F, et al. Dissociable effects of acute SSRI (escitalopram) on executive, learning and emotional functions in healthy humans. Neuropsychopharmacology 2018;43(13):26452651.
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Xiao, Lin, Meng Wang, and Bart van Arem. "Realistic Car-Following Models for Microscopic Simulation of Adaptive and Cooperative Adaptive Cruise Control Vehicles." Transportation Research Record: Journal of the Transportation Research Board 2623, no. 1 (2017): 1–9. http://dx.doi.org/10.3141/2623-01.
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Adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) are important technologies for the achievement of vehicle automation, and their effect on traffic systems generally is evaluated with microscopic traffic simulations. A successful simulation requires realistic vehicle behavior and minimal vehicle collisions. However, most existing ACC-CACC simulation studies used simplified models that were not based on real vehicle response. The studies rarely addressed collision avoidance in the simulation. The study presented in this paper developed a realistic and collision-free car-following model for ACC-CACC vehicles. A multiregime model combining a realistic ACC-CACC system with driver intervention for vehicle longitudinal motions is proposed. This model assumes that a human driver resumes vehicle control either according to his or her assessment or after a collision warning asks the driver to take over. The proposed model was tested in a wide range of scenarios to explore model performance and collision possibilities. The testing scenarios included three regular scenarios of stop-and-go, approaching, and cut-out maneuvers, as well as two extreme safety-concerned maneuvers of hard brake and cut-in. The simulation results show that the proposed model is collision free in the full-speed-range operation with leader accelerations within −1 to 1 m/s2 and in approaching and cut-out scenarios. Those results indicate that the proposed ACC-CACC car-following model can produce realistic vehicle response without causing vehicle collisions in regular scenarios for vehicle string operations.
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Song, Zhijin, Huizi Wang, Jian Sun, and Ye Tian. "Experimental Findings with VISSIM and TransModeler for Evaluating Environmental and Safety Impacts using Micro-Simulations." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 8 (2020): 566–80. http://dx.doi.org/10.1177/0361198120925077.
Full textAbstract:
Micro-simulation packages provide an efficient and systematic approach to depicting traffic dynamics. Nonetheless, many of these models used by the micro-simulation packages are only calibrated with respect to observed traffic indicators such as average speed, traffic count, and so forth, while omitting non-traffic indicators. This paper aims to investigate the performance of VISSIM and TransModeler when depicting non-traffic indicators such as fuel consumption, emissions, and safety. A model was first calibrated for traffic indicators based on Next Generation SIMulation (NGSIM) trajectories. Results indicated that after calibration, simulation accuracy was still unsatisfactory with regard to energy consumption and emission measurements, with errors of up to 38.23% in VISSIM. In assessing safety, the relative error of VISSIM increased from 12.36% to 59.92% after calibration. The error in TransModeler increased to almost 100%. Furthermore, this study explored the simulation accuracy of VISSIM and TransModeler under different traffic conditions and discovered that the models’ accuracies were relatively high when simulating stop-and-go traffic. We also explored the causes of these observed differences through a regression model. This study presents practical insight into the deficiencies of micro-simulation related research, and based on error analysis, provides a theoretical reference for optimizing simulation accuracy from a novel perspective.