The response time distribution in a multi-processor database with single queue static locking

The Stroop interference effect—slower responses to the color of an incongruent color-word stimulus (e.g., GREEN in red ink) compared to a neutral stimulus (e.g., XXXX in red ink)—is one of the most robust findings in cognitive psychology. This thesis investigated why the effect is so robust, focusing on the unique perceptual architecture of the Stroop stimulus. Specifically, in a Stroop stimulus, the visual word form and color are integrated into a visual object, and hence attending to the color inevitably results in the word receiving attention as well. Across four empirical chapters, I demonstrated that presenting the distractor word in advance of a Stroop stimulus (a manipulation termed <i>distractor priming</i>—e.g., presenting the word GREEN in white ink followed by the same word GREEN in red ink) significantly reduced—and in some cases eliminated—the Stroop interference effect. I argued that this occurred because the distractor prime broke the integration of the visual word form and color in the Stroop stimulus, allowing rapid disengagement of attention from the word. Crucially, I examined response time (RT) distributions. In standard Stroop stimuli, the interference effect increased with slower responses, yielding a positively sloped delta plot. When the integration was disrupted by distractor priming, the delta slope flattened—that is, the interference effect remained constant across the RT distribution. Chapter 2 introduced the distractor priming paradigm. Consistent with prior studies of distractor priming that used oral color-naming responses, distractor priming in a manual Stroop task sped up responses to the color. Importantly, it eliminated the Stroop interference effect across the entire RT distribution (i.e., it removed the positively sloped delta). Chapter 3 demonstrated that this reduction in Stroop interference and removal of the positively sloped delta occurred only with a prime visually identical to the distractor. Stroop interference remained large, and the positively sloped delta persisted when the prime was conceptually related but not visually identical to the distractor word (e.g., LEAF - GREENred) or an auditory word (e.g., hearing “green”). Chapter 4 explored the relative “automaticity” of the distractor priming benefit and demonstrated that even when the word precue was only 50% predictive of the upcoming distractor word (unlike 100% as in the previous studies), Stroop interference was reduced and the positively sloped delta removed. Additionally, this experiment showed that the delta slope pattern of the Stroop interference effect found in the distractor-primed (identity precue) condition differed from that in the response-precue condition (e.g., the word RED followed by the word GREEN in red ink). Chapter 5 tested the assumption underlying the distractor priming benefit—that the positively sloped delta was removed when the integration between the word and color was disrupted—using the primed Stroop task. This paradigm differed from the standard Stroop task in that the word and color were not integrated into a single visual object; instead, the distractor word was presented ahead of a row of colored Xs. Across two experiments, RT distributions in the primed Stroop task mirrored those in distractor priming, in that Stroop interference was small and the positively sloped delta was eliminated. Together, these findings indicate that the robustness of the Stroop interference effect stems from the perceptual integration of the distractor word and color into a single visual object. Chapter 6 provides a discussion of the implication of our interpretation of Stroop interference on how the Stroop task is used as a tool to study selective attention.

Although response times (RTs) are the dependent measure of choice in the majority of studies of visual attention, changes in RTs can be hard to interpret. First, they are inherently ambiguous, since they may reflect a change in the central tendency or skew (or both) of a distribution. Second, RT measures may lack sensitivity, since meaningful changes in RT patterns may not be picked up if they reflect two or more processes having opposing influences on mean RTs. Here we describe RT distributions for repetition priming in visual search, fitting ex-Gaussian functions to RT distributions. We focus here on feature and conjunction search tasks, since priming effects in these tasks are often thought to reflect similar mechanisms. As expected, both tasks resulted in strong priming effects when target and distractor identities repeated, but a large difference between feature and conjunction search was also seen, in that the σ parameter (reflecting the standard deviation of the Gaussian component) was far more affected by search repetition in conjunction than in feature search. Although caution should clearly be used when particular parameter estimates are matched to specific functions or processes, our results suggest that analyses of RT distributions can inform theoretical accounts of priming in visual search tasks, in this case showing quite different repetition effects for the two differing search types, suggesting that priming in the two paradigms partly reflects different mechanisms.

Cloud-native performance testing has emerged as a critical discipline for ensuring application reliability and user experience in modern distributed systems. Unlike traditional testing methods designed for monolithic architectures, cloud-native approaches leverage distributed load generation, chaos engineering principles, and infrastructure-as-code frameworks to evaluate application behavior across dynamic, auto-scaling environments. By integrating comprehensive observability with performance testing, organizations can identify complex inter-service dependencies, container orchestration impacts, and resource contention issues that would otherwise remain undetected until production. The evolution from periodic testing events to continuous performance validation within CI/CD pipelines enables earlier detection of potential issues, substantially reducing customer impact and operational costs. Case studies across e-commerce, financial services, and media streaming sectors demonstrate how these advanced testing methodologies deliver significant improvements in transaction success rates, response times, and system availability while simultaneously reducing infrastructure costs.

In response time (RT) research, RT outliers are typically excluded from statistical analysis to improve the signal-to-noise ratio. Nevertheless, there exist several methods for outlier exclusion. This poses the question, how these methods differ with respect to recovering the uncontaminated RT distribution. In the present simulation study, two RT distributions with a given population difference were simulated in each iteration. RTs were replaced by outliers following two different approaches. The first approach generated outliers at the tails of the distribution, the second one inserted outliers overlapping with the genuine RT distribution. We applied ten different outlier exclusion methods and tested, how many pairs of distributions significantly differed. Outlier exclusion methods were compared in terms of bias. Bias was defined as the deviation of the proportion of significant differences after outlier exclusion from the proportion of significant differences in the uncontaminated samples (before introducing outliers). Our results showed large differences in bias between the exclusion methods. Some methods showed a high rate of Type-I errors and should therefore clearly not be used. Overall, our results showed that applying an exclusion method based on z-scores / standard deviations introduced only small biases, while the absence of outlier exclusion showed the largest absolute bias.

Previous analyses of response time distributions have shown that the Stroop effect is observed in the mode (μ) and standard deviation (σ) of the normal part of the distribution, as well as its tail (τ). Specifically, interference related to semantic and response processes has been suggested to specifically affect the mode and tail, respectively. However, only one study in the literature has directly manipulated semantic interference, and none manipulating response interference. The present research aims to address this gap by manipulating both semantic and response interference in a manual response Stroop task, and examining how these components of Stroop interference affect the response time distribution. Ex-Gaussian analysis showed both semantic and response conflict to only affect τ. Analyzing the distribution by rank-ordered response times (Vincentizing) showed converging results as the magnitude of both semantic and response conflict increased with slower response times. Additionally, response conflict appeared earlier on the distribution compared to semantic conflict. These findings further highlight the difficulty in attributing specific psychological processes to different parameters (i.e., μ, σ, and τ). The effect of different response modalities on the makeup of Stroop interference is also discussed.

The response time distributions of the frames sent on a Controller Area Network (CAN) bus are of prime interest to dimension and validate automotive electronic architectures. However, the existing work on the timing behaviour of the CAN network does not take into account that all the data exchanges between the Electronic Control Units (ECUs) are driven by different and independent clocks which are subject to clock drifts. This paper proposes a model for clock drifts and describes their impact on the CAN frame response time distributions. By implementing the clock drifts in a CAN simulation tool, we show experimentally that the response time distributions converge, for drift values chosen randomly within the same range on all ECUs, whatever the initial phasings between the sending nodes. Furthermore, we show that, as a result of the clock drifts, the situations leading to the worst case response times are transient.

In this work, a preliminary conceptual model of the hydrogeological functioning of a binary karst aquifer located in southern Spain is presented, based on the natural responses of the springs and the dye tracer tests. Results derived from the long-term analysis of cross-correlation function (CCF) (global average time of recharge input) have been validated with those obtained from a dye tracer test, performed during a specific recharge event. The overall response times (CCF results) obtained for the three springs studied were 58 (SP-1), 72 (SP-3), and 81 h (SP-2). This pattern in response times was contrasted with the first detection times of the BTC-Tracer Breakthrough Curve—at the same three springs (30.9, 35.3, and 47 h) and their respective recovery rates (2.03, 21.9, and 78.4% for S1, S2, and S3, respectively). The distribution of response times, both those determined by long-term statistical analysis and the ones derived from the use of dye tracer test, is directly related to the karst network development in each of the drainage routes. Additionally, the rate of tracer recovery at each of the springs is linked to the hierarchy of flow paths from the selected injection point toward each spring, within the overall drainage network scheme. An accurate knowledge of all factors affecting the hydrogeological behavior as well as groundwater flow paths (from swallow holes to the springs) is crucial for suitable management of the resource and to mitigate the pollution risks derived from fast infiltration of surface water.KeywordsCross-correlationDye tracer testKarst aquiferTime lagAquifer functioning

In a Fork-Join (FJ) queueing system an upstream fork station splits incoming jobs into N tasks to be further processed by N parallel servers, each with its own queue; the response time of one job is determined, at a downstream join station, by the maximum of the corresponding tasks' response times. This queueing system is useful to the modelling of multi-service systems subject to synchronization constraints, such as MapReduce clusters or multipath routing. Despite their apparent simplicity, FJ systems are hard to analyze. This paper provides the first computable stochastic bounds on the waiting and response time distributions in FJ systems. We consider four practical scenarios by combining 1a) renewal and 1b) non-renewal arrivals, and 2a) non-blocking and 2b) blocking servers. In the case of non blocking servers we prove that delays scale as O(logN), a law which is known for first moments under renewal input only. In the case of blocking servers, we prove that the same factor of log N dictates the stability region of the system. Simulation results indicate that our bounds are tight, especially at high utilizations, in all four scenarios. A remarkable insight gained from our results is that, at moderate to high utilizations, multipath routing 'makes sense' from a queueing perspective for two paths only, i.e., response times drop the most when N = 2; the technical explanation is that the resequencing (delay) price starts to quickly dominate the tempting gain due to multipath transmissions.

The current study examined the effects of responses on error-adjacent trials (i.e., those immediately preceding or following errors) on age differences in measures of intraindividual variability and the shape of response time (RT) distributions on a two-back task. Removing error-adjacent responses reduced variability as measured by the coefficient of variation, but did so similarly for younger and older adults. However, older adults’ standard deviations (SDs) were less than those of younger adults with comparable RTs, raising questions regarding the validity of the coefficient of variation. An ex-Gaussian analysis revealed that removing the RTs on error-adjacent trials reduced the length of the tails of distributions and the skewness of the distributions. These properties were reduced more for older adults than for younger adults. These results indicate that the influence of error-adjacent trials should be considered when analyzing intraindividual variability and the shape of RT distributions to test theories of cognitive aging.

Due to the effectiveness, simple deployment and low cost, radio frequency identification (RFID) systems are used in a variety of applications to uniquely identify physical objects. The operation of RFID systems often involves a situation in which multiple readers physically located near one another may interfere with one another’s operation. Such reader collision must be minimized to avoid the faulty or miss reads. Specifically, scheduling the colliding RFID readers to reduce the total system transaction time or response time is the challenging problem for large-scale RFID network deployment. Therefore, the aim of this work is to use a successful multi-swarm cooperative optimizer called PS2O to minimize both the reader-to-reader interference and total system transaction time in RFID reader networks. The main idea of PS2O is to extend the single population PSO to the interacting multi-swarm model by constructing hierarchical interaction topology and enhanced dynamical update equations. As the RFID network scheduling model formulated in this work is a discrete problem, a binary version of PS2O algorithm is proposed. With seven discrete benchmark functions, PS2O is proved to have significantly better performance than the original PSO and a binary genetic algorithm. PS2O is then used for solving the real-world RFID network scheduling problem. Numerical results for four test cases with different scales, ranging from 30 to 200 readers, demonstrate the performance of the proposed methodology.

The use of intra-transaction parallelism within a multi-processor database system is well suited to meet the special requirements of complex transactions as known of the so-called non-standard database applications. This paper describes a mechanism for easily implementing and evaluating different parallel execution schemes for any given complex transaction. The key idea is to separate the algorithmic aspects of the computation from the description of the parallel execution plan. This approach supports in particular massive parallel database applications, which show a number of very favorable properties in regard to resource consumption in a multiprocessor database system (linear speedup and scaleup).KeywordsDatabase SystemParallel ExecutionComplex QueryMultiprocessor SystemDatabase ApplicationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Application of SLAM in the design and performance analysis of a multi-processor database system

The mental experience of attention capture has attracted a great deal of intrigue among researchers seeking to explain the interactions between stimulus-driven and goal-driven attentional control. In recent years, researchers have increasingly begun to analyze cumulative response time (RT) distributions to test modern accounts of the capture phenomenon, particularly accounts claiming that there are changes in susceptibility to distraction as a function of time. In this paper, we raise a criticism of this approach, which centers on a problematic assumption. The assumption is that variability in these distributions is primarily determined by fluctuations in the observer's internal control state (e.g., readiness for the trial). However, it is also the case that faster segments of the distributions are overrepresented by trials that are objectively easy, while slower segments are overrepresented by trials that are objectively difficult. That is, incidental aspects of the trial stimuli influence task performance independently of the observer's internal control state. Here, we demonstrate empirically that contributions of incidental stimulus factors distort cumulative RT distributions in such a way that confounds proper interpretation of experimental data. The results have implications for theoretical accounts of attentional control, and they also raise caution about the assumptions that are sometimes made when analyzing cumulative RT distributions.

SNA is both an architecture and a set of products built in conformance with the architecture (1,2,3). The architecture is layered and precisely defined; it is both evolutionary and cost effective for implementing products. Perhaps the largest component of cost effectiveness is performance : transaction throughput and response times. For SNA, this involves data link control protocols (for SDLC and S/370 channel DLC's), routing algorithms, protocols used on the sessions that connect logical units (LU-LU session protocols), and interactions among them. SNA's DLC and routing protocols have been discussed elsewhere (4,5,6); this talk examines protocols on sessions between logical units (LU-LU session protocols) and illustrates the results of design choices by comparing the performance of various configurations.

Optimistic concurrency control technique is widely used as non-locking scheme to control concurrent access in mobile database environment. One of the key parameter that dictates the performance of optimistic scheme is the transaction start time interval. However, most of the existing work uses different values of this key parameter with no justification on its performance implications on the overall scheme. This paper evaluates the effect of different transaction start time intervals on the performance of optimistic strategy in terms of aborted transaction rate and response time. Simulation results shows that transaction start time interval of 300 milliseconds incurred less number of aborted transactions without sacrificing response time.