Response Time Analysis Research Articles

Neural Substrates of the Drift-Diffusion Model in Brain Disorders.

Many studies on the drift-diffusion model (DDM) explain decision-making based on a unified analysis of both accuracy and response times. This review provides an in-depth account of the recent advances in DDM research which ground different DDM parameters on several brain areas, including the cortex and basal ganglia. Furthermore, we discuss the changes in DDM parameters due to structural and functional impairments in several clinical disorders, including Parkinson's disease, Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorders, Obsessive-Compulsive Disorder (OCD), and schizophrenia. This review thus uses DDM to provide a theoretical understanding of different brain disorders.

Interval-Valued Invehicular Latency Characterization for Risk/Fault Management Purposes

Guaranteeing the reliability of Intelligent Transportation Systems (ITSs) is an overlapping issue. Not only the in-road risks must be mastered, but also the internal threats that emerge from the ITS material aspects should be addressed carefully. Most of the safety verification solutions ignore the limitations issued from the ITS onboard embedded structure, such as the invehicular communication delays. In this work, a novel Response Time Analysis (RTA) method is introduced to bridge the gap between the risk/failure management issues and the material aspects (the invehicular communication delays in particular) for ITSs. Aside of its simplicity, the suggested RTA reveals all potential latency scenarios by returning an interval estimation of delays. The interval results enclose certainly the exact delay that may occur in runtime. As a proof of concept of the introduced RTA algorithm, the Hardware-in-the-Loop (HIL) validation technique is adopted. The HIL platform is realized thanks to a model of a modern industrial automotive system. The validation work proves the consistency and efficiency of the proposed RTA solution to ensure ITS safety assurance.

The impact of decoys on a genetic oscillator based on coupled positive-negative feedbacks

Within cells, transcription factors (TFs) bind to a wide range of nonspecific genomic sites in addition to their target sites. Binding to such high affinity “decoys” has been shown to qualitatively alter the dynamics of gene regulatory circuits. Analyzing simple gene expression models with decoy binding we derive formulas for the TF response time as a function of the number of decoys, binding affinity, and stability of the decoy-bound TF. Our results show that while on one hand, decoys make the response sluggish whenever decoy binding stabilizes the TF, on the other hand, decoys can accelerate responses by destabilizing the bound TF. We apply these results in the context of a genetic oscillator based on an activator-repressor motif, where sustained oscillations result from a rapid activator-mediated positive feedback working in conjunction with a slow repressor-mediated negative feedback. Consistent with our response time analysis, we find that activator binding to decoy sites can destroy oscillations in the case of a stable decoy-activator complex that functions to slow down the positive feedback. In contrast, an unstable decoy-activator complex can expand the oscillatory parameter regime. In conclusion, our response time analysis provides intuitive insights into the emergence of sustained oscillations.

Effects of color–emotion association on facial expression judgments

Color and emotion are metaphorically associated in the human mind. This color–emotion association affects perceptual judgment. For example, stimuli representing colors can affect judgment of facial expressions. The present study examined whether colors associated with happiness (e.g., yellow) and sadness (e.g., blue and gray) facilitate judgments of the associated emotions in facial expressions. We also examined whether temporal proximity between color and facial stimuli interacts with any of these effects. Participants were presented with pictures of a happy or sad face against a yellow-, blue-, or gray-colored background and asked to judge whether the face represented happiness or sadness as quickly as possible. The face stimulus was presented simultaneously (Experiment 1) or preceded for one second by the colored background (Experiment 2). The analysis of response time showed that yellow facilitated happiness judgment, while neither blue nor gray facilitated sadness judgment. Moreover, the effect was found only when the face and color stimuli were presented simultaneously. The results imply that the association of sadness with blue and gray is weak and, consequently, does not affect emotional judgment. Our results also suggest that temporal proximity is critical for the effect of the color–emotion association (e.g., yellow–happiness) on emotional judgment.

Worst-Case Response Time Analysis of Multitype DAG Tasks Based on Reconstruction

With the wide application of heterogeneous multi-core processor real-time systems, the existing analysis methods of worst-case response time (WCRT) overestimate the blocking information among tasks, resulting in a rather pessimistic estimation. To improve the accuracy of the WCRT, we propose a reconstruction-based WCRT analysis method for multi-type directed acyclic graph (DAG) tasks scheduling algorithm(RMDS). The RMDS algorithm comprises the following steps: First, we unitize all task nodes in the multi-type DAG task; Then, we use key factors as task priorities to schedule tasks and reconstruct the DAG task model into a parallel node segment model; Finally, we estimate the WCRT of multi-type DAG tasks according to the parallel node segment model to assess task schedulability. To verify the performance of our algorithm, we compared it with traditional algorithms. RDMS showed an acceptance rate 6.13% higher and its overall performance increased by 25.95% in comparison with traditional algorithms.

High-Capacity Real-Time Face Retrieval Recognition Algorithm Based on Task Scheduling Model for the Treatment Area of Hospital

This paper presents an in-depth study of face detection, face feature extraction, and face classification from three important components of a high-capacity face recognition system for the treatment area of hospital and a study of a high-capacity real-time face retrieval and recognition algorithm for the treatment area of hospital based on a task scheduling model. Considering the real-time nature of our system, our face feature extraction network is modeled by DeepID, and the network is slightly improved by introducing a central loss verification signal to train a DeepID-like network model using central loss and use it to extract face features. To further investigate and optimize the schedulability analysis problem of the directed graph real-time task model, this paper proposes a rigorous and approximate response time analysis method for the directed graph real-time task model with an arbitrary time frame. Based on the theoretical results of the greatly additive algebra, it is shown that the coherent qualifying function is linearly periodic, i.e., the function can be represented by a finite nonperiodic part and an infinitely repeated periodic part, thus calculating the coherent qualifying function independent of the magnitude of the interval time. The algorithm for high-capacity real-time face retrieval and recognition in the treatment area of hospital based on the task scheduling model is further investigated, and a face database is established by using the PCA dimensionality reduction technique. Based on the internal architecture of the processor, image preprocessing and IP core packaging are implemented, and the hardware engineering of the high-capacity real-time face recognition system for hospital visits is built using the IP-based design concept. The performance tests of the face detection model and feature extraction network show that the face detection model has a significant reduction in false-positive rate, better fitting of border regression, and improved time performance. The face feature extraction network has no overfitting, and the features are highly discriminative with small feature extraction time consumption. The high-capacity real-time face recognition system for the treatment area of hospital combined with the optimized directed graph task scheduling model can approach 25 fps, which meets the real-time requirements, and the face recognition rate surpasses that of real people. It realizes the intelligence, self-help, and autonomy of medical services and satisfies the medical needs of users in all aspects.

The influence of location, ownership, and the presence of a coactor on the processing of objects.

Humans operate in complex environments where social interactions require individuals to constantly attend to people and objects around them. Despite the complexity of these interactions from a visuomotor perspective, humans can engage and thrive in social settings. The purpose of the current study was to examine the simultaneous influence of multiple social cues (i.e., ownership and the presence of a coactor) on the processing of objects. Participants performed an object-based compatibility task in the presence and absence of a coacting confederate. Participants indicated whether pictures of mugs (that were either self-owned or unowned) were upright or inverted. The pictures appeared at one of 2 locations (a near or far location relative to the participant) on a computer screen laid flat on (parallel to) the tabletop. When present, the coactor stood on the opposite side of the screen/table. Analysis of response times (RTs) indicated that the processing of objects was influenced by the object's ownership status, the presence of the coactor, and where the object was located on the screen. Specifically, RTs for pictures of self-owned mugs were shorter than unowned mugs, but only when the pictures were located at the near location. Further, the presence of a confederate resulted in shorter RTs for pictures located at the near but not the far location. These findings suggest that when objects were placed at the far location, the additional social cues of ownership and social context did not influence visuomotor processing of the objects. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Neural response time analysis: Explainable artificial intelligence using only a stopwatch

AbstractHow would you describe the features that a deep learning model composes if you were restricted to measuring observable behaviours? Explainable artificial intelligence (XAI) methods rely on privileged access to model architecture and parameters that is not always feasible for most users, practitioners and regulators. Inspired by cognitive psychology research on humans, we present a case for measuring response times (RTs) of a forward pass using only the system clock as a technique for XAI. Our method applies to the growing class of models that use input‐adaptive dynamic inference and we also extend our approach to standard models that are converted to dynamic inference post hoc. The experimental logic is simple: If the researcher can contrive a stimulus set where variability among input features is tightly controlled, differences in RT for those inputs can be attributed to the way the model composes those features. First, we show that RT is sensitive to difficult, complex features by comparing RTs from ObjectNet and ImageNet. Next, we make specific a priori predictions about RT for abstract features present in the SCEGRAM data set, where object recognition in humans depends on complex intrascene object‐object relationships. Finally, we show that RT profiles bear specificity for class identity and therefore the features that define classes. These results cast light on the model's feature space without opening the black box.

Beyond the limitations of real-time scheduling theory: a unified scheduling theory for the analysis of real-time systems

We investigate the mathematical properties of event bound functions as they are used in the worst-case response time analysis and utilization tests. We figure out the differences and similarities between the two approaches. Based on this analysis, we derive a more general form do describe events and event bounds. This new unified approach gives clear new insights in the investigation of real-time systems, simplifies the models and will support algebraic proofs in future work. In the end, we present a unified analysis which allows the algebraic definition of any scheduler. Introducing such functions to the real-time scheduling theory will lead two a more systematic way to integrate new concepts and applications to the theory. Last but not least, we show how the response time analysis in dynamic scheduling can be improved.

Evaluation of Fire Disaster Emergency Response Capacity using Open-source Data and Response Time Analysis in Ilorin Metropolis

This study evaluates the response capacity to fire disaster emergency response system in Ilorin metropolis using Open-source data and response time analysis. Road and street information were obtained from Geofabrik. In addition, coordinates of fire service stations and fire disaster risk spots, specifically fuel and gas stations were acquired using Garmin 76X handheld GPS. Using the relationship of the length of road segments and speed, the travel time was computed in ArcGIS 10.4 environment. With the Network analyst tool, the response capability of the fire stations was evaluated at different response times (1, 2, and 3 minutes) based on service area coverage. The results showed that the fire stations could only cover 0.24%, 0.68%, and 1.22% of the service area within 1-, 2- and 3-minute response time, respectively, whereas 97.86% of the metropolis requires longer time (>3 minutes). Finding from this study has revealed the inadequacy of the existing fire disaster emergency response system to effectively cover the city. This will be useful for local and state governments in policy directives on strengthening fire disaster emergency response structure.

EFFECT OF DIFFERING EXERCISE INTENSITIES ON THE RESPONSE TIME OF GYMNASTS AND NON-GYMNASTS IN 3D CUBE MENTAL ROTATION TASK

The purpose of the present study was to examine the effect of different levels of exercise intensity on mental rotation performance in gymnasts vs. non-gymnasts'. Forty-one participants (18 females; mean age 20.94±0.89 years, height 1.65±0.03 m, body mass58.94±5.67 kg, and 23 males; mean age 21.26±0.99 years, height 1.70±0.05 m, body mass 66.87±4.52 kg) divided into two groups (i.e., gymnasts and non-gymnast) voluntarily took part in the present study. The two groups performed a 3D cube mental rotation task at rest, and then performed the same task preceded by short bouts of intense exercise at 60%, 80%, 100% and 120% of their maximum aerobic speed (MAS). The analyses of response times showed that gymnasts performed the mental rotation task faster following bouts of intense exercise than in rest condition, especially in 60% and 80% of MAS, whereas non-gymnasts increased their response times after moderate exercises (i.e., 60 et 80 % of MAS) and stabilized their performance (i.e., equally at the rest) after intense exercises. This finding highlights the specific physical expertise as a variable that can affect the influence of exercise on cognitive processing.

The influence of sociophonetic knowledge on lexical encoding across dialects

The goal of this study was to determine if the strength of lexical encoding differed between regional dialects as a function of the explicit social knowledge listeners held about the dialects or talkers. Participants heard lexical items produced in the Midland, Northern, and Southern dialects of American English in an explicit lexical recognition memory task. Some participants were told the regional backgrounds of the talkers while others were not. It was predicted that encoding would be most robust for tokens produced in the ideologically standard Midland dialect and would be more robust for the socially stereotyped Southern dialect compared with the non-stereotyped Northern dialect. Being told regional information about the talkers was predicted to increase the robustness of encoding. Analysis of response times provided some evidence of a standard dialect benefit across listeners from the three regions, though this effect varied depending on the vowel contained in the stimulus item. Interestingly, being given regional information about the talkers did not increase the robustness with which tokens were encoded; for some listeners, it hindered performance. These results indicate that social knowledge about linguistic varieties can be highly integrated with speech processing, but that it is not facilitative in all situations.

Excluding Parallel Execution to Improve Global Fixed Priority Response Time Analysis

Response Time Analysis (RTA) is an effective method for testing the schedulability of real-time tasks on multiprocessor platforms. Existing RTAs for global fixed priority scheduling calculate the upper bound of the worst case response time of each task. Given a target task, existing RTAs first calculate the workload upper bound of each higher priority task (than the target task), and then calculate the interference on the target task by each higher priority task according to the obtained workload upper bounds. The workload of a task consists of three parts: carry-in, body and carry-out. The interference from all these three parts may be overestimated in existing RTAs. However, although the overestimation of the interference from body is the major factor that causes the low accuracy of existing RTAs, all existing work only focuses on how to reduce the overestimation of the interference from carry-in, and there is no method to reduce the overestimation of the interference from body or carry-out. In this work, we propose a method to calculate the lower bound of the accumulative time in which the target task and higher priority tasks are executed in parallel. By excluding the parallel execution time from the interference, we derive a new RTA test that can reduce the overestimation of the interference from all three parts of the workload. Extensive experiments are conducted to verify the superior performance of the proposed RTA test.

An Efficient Execution Framework of Two-Part Execution Scenario Analysis

Response Time Analysis ( RTA ) is an important and promising technique for analyzing the schedulability of real-time tasks under both Global Fixed-Priority ( G-FP ) scheduling and Global Earliest Deadline First ( G-EDF ) scheduling. Most existing RTA methods for tasks under global scheduling are dominated by partitioned scheduling, due to the pessimism of the -based interference calculation where is the number of processors. Two-part execution scenario is an effective technique that addresses this pessimism at the cost of efficiency. The major idea of two-part execution scenario is to calculate a more accurate upper bound of the interference by dividing the execution of the target job into two parts and calculating the interference on the target job in each part. This article proposes a novel RTA execution framework that improves two-part execution scenario by reducing some unnecessary calculation, without sacrificing accuracy of the schedulability test. The key observation is that, after the division of the execution of the target job, two-part execution scenario enumerates all possible execution time of the target job in the first part for calculating the final Worst-Case Response Time ( WCRT ). However, only some special execution time can cause the final result. A set of experiments is conducted to test the performance of the proposed execution framework and the result shows that the proposed execution framework can improve the efficiency of two-part execution scenario analysis by up to in terms of the execution time.

Yes! I love my mother as much as myself: Self- and mother-association effects in an Indian sample.

Information associated with the self is preferentially processed compared to information associated with others. However, cultural differences appear to exist in the way information is processed about those close to us like our mothers. In Eastern compared with Western cultures, information about the mother seems to be processed as well as our self. However, it is not clear whether this lack of difference is due to familiarity or would extend to processing arbitrary perceptual information associated with different categorical labels. The current study employs a perceptual association paradigm in which category labels like self, mother, and none are associated with arbitrary shapes to study self versus mother processing in an Indian sample. We hypothesised that there would be no difference between self and mother processing given the familial and collectivistic tendencies in India. Participants in two experiments performed a matching task between a shape and a pre-assigned category label, with self, mother, and none as categories in Experiment 1A and self, friend, and none as categories in Experiment 1B. As expected, analysis of response times (RT), accuracies, and signal detection theoretic measures showed that information about mother is processed as well as self in Experiment 1A, but this effect is not present with friend in Experiment 1B. Moreover, participants' processing for the self-associated information gets attenuated depending upon the other close person category used in the task (friend vs. mother) indicating that self-information processing is dynamically dependent on the categorical contexts in which such processing takes place. Our findings have implications for understanding the processing of self-associated information across cultures and contexts.

Analysis of dynamic pull-in voltage and response time for a micro-electro-mechanical oscillator made of power-law materials

Analysis of dynamic pull-in voltage and response time for a micro-electro-mechanical oscillator made of power-law materials

Compact Steam Bottoming Cycles: Minimum Weight Design Optimization and Transient Response of Once-Through Steam Generators

Compactness and weight minimization are key aspects for successful and widespread implementation of waste heat recovery steam cycles in off-shore oil and gas platforms due to the site weight and volume footprint constraints. The power plant off-shore must be designed for flexibility in its operations to provide varying power demands across multiple time scales. Reliability of the heat and power production units is crucial. Within a case study in an off-shore platform in the Norwegian Continental Shelf, this article conducts design optimization of compact and low-weight steam cycles for power production from gas turbine exhaust and transient analysis of the core of heat recovery steam generators (HRSGs) via dynamic modeling and simulation, considering once-through steam generators (OTSGs) for the HRSGs. A method for simultaneous thermodynamic and heat exchanger geometry optimization design for bottoming cycles is applied, with the main objective being weight minimization and compactness of the cycle heat exchangers. Ten different optimal minimum weight bottoming cycle designs are provided by selecting ten different manufacturable tubes. The resulting bottoming cycle designs are compared in terms of weight, OTSG core weight distribution, heat transfer area, and footprint. The resulting bottoming cycle weight varies from 48.4 to ca. 87.10 ton for designs sensible for off-shore applications, and from 95.8 to 178.9 ton when selecting outer tube diameters typical of onshore applications. Smaller outer tube diameter selection in OTSG bundles is a key driver for low-weight and compact steam cycle designs. Three different designs representing light, normal, and heavy OTSG designs are compared by dynamic trajectory and response time analysis under transient scenarios by means of dynamic modeling and simulation. More compact and lighter designs respond faster to changes in the gas turbine (GT) operation upstream the OTSG. The results in this analysis indicate the need for feedforward control. Feedback control alone is probably not a good option due to the high OTSG open loop stabilization time and large sensitivity to GT exhaust gas variations. More compact and low-weight designs based on the OTSG can reduce potential challenges in controlling and stabilizing bottoming cycles for power production.

Analysis of Response Time and Quality of Professional Service Provider Care (PPA) with Patient Satisfaction in Hospital Poly Disease in Kartini Mojokerto

To create patient satisfaction, the hospital must create and manage a system to obtain more patients and the ability to retain patients. The process of patient care and care is dynamic and involves many Caregiver Professionals (PPA) and involves various service units. There are many problems regarding the lack of satisfaction from health care workers, one of which is due to the long response time. This study aims to analyze the relationship between response time and service quality of health workers with satisfaction of outpatients at Kartini Hospital, Mojokerto. This study used a quantitative analytic design with a cross sectional approach. The population was all unhospitalited patients who had received services the internal medicine poly at Kartini Hospital, Mojokerto with a total of 156 respondents. The sample used Simple Random Sampling totaling 112 respondents. Independent variables are response time and service quality. The dependent variable is outpatient satisfaction. Data analysis using Ordinal Regression. The time of the study was 18-23 March 2020. Based on the results of the Ordinal Regression Test analysis, it shows that the variable that most influences patient satisfaction is the variable service quality with a p-value of 0.013 <0.05, so H0 is rejected and H1 is accepted, so it can be concluded that there is a significant relationship between the quality of health care workers and satisfaction. On Outpatients at Kartini Hospital, Mojokerto Regency

Effects of phonological neighbourhood density and frequency in picture naming

• Phonological neighbourhood effects depend on target frequency in picture naming. • The frequency of phonological neighbours, less so their number, affects performance. • Phonological neighbours can both inhibit and facilitate picture naming. • An interactive activation model was used to simulate picture naming. • A slow rise in lexical activation is required to successfully simulate the effects. Speaking involves selecting a word among co-activated words in the lexicon. The factors determining which potentially co-activated words affect the production of spoken words remain underspecified. This research investigated the influence of words that sound similar to a target word (phonological neighbours) on the picture naming latency and accuracy of young English-speaking adults. Response time analyses showed a significant interaction between the frequency of the target and the frequency of those phonological neighbours that were higher in frequency than the target. Analysis of a published picture naming dataset gave similar results. The mechanisms underlying these results were explored using computational modelling. The critical interaction observed in the human data was successfully reproduced in analyses of the output of some versions of an interactive activation model. This model featured a relatively slow rise of activation in the phonological lexicon nodes, resulting in an increase in the effect of frequency. Overall, results show that phonological neighbourhood effects are tightly related to frequency effects.

Queue assignment for fixed-priority real-time flows in time-sensitive networks: Hardness and algorithm

Abstract Time sensitive networks (TSNs) enable deterministic real-time communication over Ethernet networks. According to IEEE 802.1Qbv standards, TSN switches use gates between queues and their corresponding egress ports to facilitate timing-deterministic communications. Management of switch resources, such as queues, has a significant impact on the schedulability of real-time flows. In this paper, we look into the theoretical foundation of queue management in TSN switches. We prove that the queue assignment problem for real-time flows on time sensitive networks under static priority scheduling is NP-hard in the strong sense, even if the number of queues per port is 3. Then we formulate the problem as a satisfiability modulo theories (SMT) specification. Besides, we propose a worst case response time analysis and a fast heuristic algorithms by eliminating scheduling conflicts. Experiments with randomly generated workload demonstrate the effectiveness of our algorithms for queue assignment of real-time flows.