Standard Deviation Of Response Time Research Articles

Design and experimentation of soil organic matter content detection system based on high-temperature excitation principle

With the continuous development of precision agriculture, the integration of sensor technology, control technology, and agricultural production activities has become increasingly tight. Soil organic matter (SOM) content is an important parameter in precision agriculture, closely related to the growth status of crops. Therefore, in-situ detection of SOM is an important part of variable seeding. Currently, most researchers use spectroscopy to detect SOM. However, the accuracy of spectroscopy is affected by factors such as soil texture, soil moisture content, soil iron oxide content, and soil particle size. Additionally, spectroscopic instruments are expensive and complex. To address these issues, this study designed and developed a real-time detection system for soil organic matter content based on the high-temperature excitation principle. The SOM detection system includes the selection and application of carbon dioxide sensor, the design of detection devices, the design of control systems, and the design of human–machine interface. Benchtop tests showed that the system's response time standard deviation was 0.252 s, indicating good stability. The filtering and cooling effects of the system met the requirements of the detection system. Five different natural soils were collected, and two of them, along with organic soil, were used to create artificially graded soil samples. Multiple linear regression was used for modeling, selecting six models with an R2 greater than 0.8 for accurate prediction of the remaining three different soil textures. The modeling results showed that a heating depth of 10 mm was susceptible to external interference, and the accuracy of the model with a heating depth of 15 mm was similar to that of the model with a heating depth of 20 mm. When the heating time exceeded 10 s, both models with different heating depths had an R2 greater than 0.8. The accuracy of the models increased with increasing heating time. Among them, the 15 mm-20 s model had the highest accuracy, with an average prediction accuracy of 91.4 %, a maximum accuracy of 94.1 %, and a minimum accuracy of 86.7 %. The experimental results showed that the SOM detection system designed in this study had good predictive capabilities for SOM in different soil textures and could achieve in-situ detection of SOM.

The interplay of hedonic appetite and attentional abilities is linked to poorer dietary self-control: Two studies on young adults living in cities

Voluntary attention supports dietary self-control, while hedonic appetite impairs it. However, hedonic processing of foods consumes voluntary attention. We therefore checked whether the interaction between hedonic appetite and attentional abilities is associated with poorer dietary self-control. Using the Power of Food Scale (PFS) we measured hedonic appetite in two samples of young adults living in cities. In Study 1 (380 participants) poor dietary self-control and attentional abilities were measured by the Uncontrolled Eating subscale of Three-Factor Eating Questionnaire and the Attentional Control Scale, respectively. In Study 2, 49 participants rated the healthiness and tastiness of foods. In the incentivized series of computerized trials, dietary self-control was defined as choosing a healthier over a tastier food item. Attentional abilities were computed as the ratio of mean to standard deviation of response time in a memory task check (a presented digit was checked against a memorized digit). The interaction between the PFS and attentional abilities was associated with poorer dietary self-control (Studies 1–2). The strength of the positive association between attentional abilities and self-control decreased with a PFS score, with no association (Study 1) and the negative association (Study 2) for high-PFS individuals. The strength of the negative association between the PFS and dietary self-control increased with attentional abilities, with no association for individuals with low attentional abilities in Study 2. The interplay between attentional skills and hedonic appetite can be harmful for dietary self-control in young adults. If hedonic appetite is strong enough, attentional abilities may be unfavorable for dietary self-control.

Which Measures From a Sustained Attention Task Best Predict ADHD Group Membership?

Difficulty with sustaining attention to a task is a hallmark of ADHD. It would be useful to know which measures of sustained attention best predict a diagnosis of ADHD. Participants were 129 children with a diagnosis of ADHD and 129 matched controls who completed the fixed Sustained Attention to Response Task (SART). The number of commission and omission errors, standard deviation of response time (SDRT), tau, fast and slow frequency variability, d-prime, and mu were able to successfully classify children with and without ADHD. The mean response time, criterion, and sigma were not able to classify participants. The best classifiers were d-prime (0.75 Area Under the Receiver Operated Characteristic), tau (.74), SDRT (0.74), omission errors (0.72), commission errors (0.71), and SFAUS (0.70). This list of the best classifier measures derived from the SART may prove useful for the planning of future studies.

Default mode network connections supporting intra-individual variability in typically developing primary school children: An EEG study.

Objective: Intraindividual variability in response time (RT) provides information about attention abilities beyond accuracy and mean RT. It could be an endophenotype for a wide range of clinical disorders and a general marker of neurological health or maladaptation. The default mode network (DMN) and the central executive and the salience networks (CEN + SN) support response stability in adults. The aim of this study was to explore the associations of resting-state connectivity of the DMN and the CEN + SN with lapses of attention in typically developing primary schoolchildren. Method: RT variability was measured by RT standard deviation in the self-paced Stroop-like Animal Size Test in 137 children aged 6-11 years. Electrophysiological signatures of the DMN and the CEN + SN were obtained using a seed-based oscillatory power envelope correlation in conjunction with beamformer spatial filtering. Results: Statistical nonparametric mapping showed that RT variability was positively associated with connectivity between the DMN and the posterior insula and the right temporal cortex (PFWE-corr < .006), suggesting that a greater focus of self-reflective internal attention may be associated with obstructed transition to an active processing mode. RT variability was negatively associated with connectivity between the DMN and the anterior cingulate and the anterior insula (PFWE-corr = .001) overlapping with the SN, which handles top-down cognitive regulation. These associations were specifically found for the anterior DMN seed in the medial prefrontal cortex, which is involved in emotion and motivational circuits. Conclusions: Default network connectivity supporting RT variability may be involved in the development of internalizing and externalizing problems in childhood. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Longitudinal Trajectories of Sustained Attention Development in Children and Adolescents with ADHD.

The present study characterizes changes in sustained attention ability over ages 9-14, and whether longitudinal trajectories of attention development differ between persistent ADHD, remitted ADHD and control groups. The Sustained Attention to Response Task (SART) was administered to 120 children with ADHD and 123 controls on three occasions between ages 9 and 14. Trajectories of sustained attention development, indicated by changes in SART performance (standard deviation of response time [SDRT], omission errors, and ex-Gaussian parameters sigma and tau), were examined using generalized additive mixed models. For all measures there was a significant main effect of age; response time variability and number of omission errors improved linearly as children aged. However, children with ADHD had significantly greater SDRT, tau and omission errors than controls across waves. There were no significant group differences in sigma, indicating that the greater overall response time variability (SDRT) observed in ADHD was likely driven by more intermittent long responses (larger tau). Trajectories of sustained attention performance did not differ between children with persistent ADHD or ADHD in remission. Longitudinal trajectories of sustained attention development are comparable between ADHD and controls, however children with ADHD (regardless of remission status) display a performance deficit equivalent to typical controls 1-3years younger. Findings highlight the need for continued clinical support for children in remission from ADHD and provide support for tau as an endophenotype of ADHD.

Acute effects of aerobic exercise on response variability and neuroelectric indices during a serial n-back task

To determine the neuroelectric underpinnings of exercise-induced changes in working memory, this study investigated the acute effects ofaerobic exercise (AE) on the P3 component of an event-related potential and brain oscillations during a serial n-back task. Task-related electroencephalography was collected in 23 young adults following 20 min of rest and AE on separate, counterbalanced days. The results revealed reductions in standard deviation of response time and coefficient of variation of response time following AE compared to rest. Neuroelectric analyses showed increased P3 amplitude following AE compared to rest. Task-related frontal alpha desynchronization was stronger in the 2-back compared with the 1-back task following AE, while no such modulation was observed following rest. These findings suggest AE may temporarily enhance working memory, as reflected by decreases in response variability, which are accompanied by neuroelectric indices reflecting greater upregulation of attentional processes.

Effects of methylphenidate on the ERP amplitude in youth with ADHD: A double-blind placebo-controlled cross-over EEG study.

Methylphenidate (MPH) is a first line drug for attention-deficit/hyperactivity disorder (ADHD), yet the neuronal mechanisms underlying the condition and the treatment are still not fully understood. Previous EEG studies on the effect of MPH in ADHD found changes in evoked response potential (ERP) components that were inconsistent between studies. These inconsistencies highlight the need for a well-designed study which includes multiple baseline sessions and controls for possible fatigue, learning effects and between-days variability. To this end, we employ a double-blind placebo-controlled cross-over study and explore the effect of MPH on the ERP response of subjects with ADHD during a Go/No-Go cognitive task. Our ERP analysis revealed significant differences in ADHD subjects between the placebo and MPH conditions in the frontal-parietal region at 250ms-400ms post stimulus (P3). Additionally, a decrease in the late 650ms-800ms ERP component (LC) is observed in frontal electrodes of ADHD subjects compared to controls. The standard deviation of response time of ADHD subjects was significantly smaller in the MPH condition compared to placebo and correlated with the increased P3 ERP response in the frontoparietal electrodes. We suggest that mental fatigue plays a role in the decrease of the P3 response in the placebo condition compared to pre-placebo, a phenomenon that is significant in ADHD subjects but not in controls, and which is interestingly rectified by MPH.

Reducing Write Amplification of Flash Storage through Cooperative Data Management with NVM

Write amplification is a critical factor that limits the stable performance of flash-based storage systems. To reduce write amplification, this article presents a new technique that cooperatively manages data in flash storage and nonvolatile memory (NVM). Our scheme basically considers NVM as the cache of flash storage, but allows the original data in flash storage to be invalidated if there is a cached copy in NVM, which can temporarily serve as the original data. This scheme eliminates the copy-out operation for a substantial number of cached data, thereby enhancing garbage collection efficiency. Simulated results show that the proposed scheme reduces the copy-out overhead of garbage collection by 51.4% and decreases the standard deviation of response time by 35.4% on average. Measurement results obtained by implementing the proposed scheme in BlueDBM, 1 an open-source flash development platform developed by MIT, show that the proposed scheme reduces the execution time and increases IOPS by 2--21% and 3--18%, respectively, for the workloads that we considered. This article is an extended version of Lee et al. [2016], which was presented at the 32nd International Conference on Massive Data Storage Systems and Technology in 2016.

Capturing Dynamics of Biased Attention: Are New Attention Variability Measures the Way Forward?

BackgroundNew indices, calculated on data from the widely used Dot Probe Task, were recently proposed to capture variability in biased attention allocation. We observed that it remains unclear which data pattern is meant to be indicative of dynamic bias and thus to be captured by these indices. Moreover, we hypothesized that the new indices are sensitive to SD differences at the response time (RT) level in the absence of bias.MethodRandomly generated datasets were analyzed to assess properties of the Attention Bias Variability (ABV) and Trial Level Bias Score (TL-BS) indices. Sensitivity to creating differences in 1) RT standard deviation, 2) mean RT, and 3) bias magnitude were assessed. In addition, two possible definitions of dynamic attention bias were explored by creating differences in 4) frequency of bias switching, and 5) bias magnitude in the presence of constant switching.ResultsABV and TL-BS indices were found highly sensitive to increasing SD at the response time level, insensitive to increasing bias, linearly sensitive to increasing bias magnitude in the presence of bias switches, and non-linearly sensitive to increasing the frequency of bias switches. The ABV index was also found responsive to increasing mean response times in the absence of bias.ConclusionRecently proposed DPT derived variability indices cannot uncouple measurement error from bias variability. Significant group differences may be observed even if there is no bias present in any individual dataset. This renders the new indices in their current form unfit for empirical purposes. Our discussion focuses on fostering debate and ideas for new research to validate the potentially very important notion of biased attention being dynamic.

Effect of Psychomotor Program on Inattetion and Impulsivity of Chilren with Attention Deficit Hyperactivity Disorder ADHD)

Background/Objectives: The purpose of this study was to verify the effect of a psychomotor program to improve inattention and to control impulsivity of children with Attention Deficit Hyperactivity Disorder (ADHD). Methods/Statistical Analysis: For this purpose, 12 children with 100 or more ADHD index were selected among a group of children referred by elementary school teachers as a result of the Advanced Test of Attention and 20 sessions of psychomotor program was applied, 90 minutes per week. The data was comparatively analyzed by processing the pre- and post-test means of sub factors of the Advanced Test of Attention's visual and auditory tests through a t-test. Findings: The following are the findings of the analysis of results on how the psychomotor program affects ADHD children's attentiveness: first, the psychomotor program improved the inattention of children with ADHD. It is the means inattention index of children with ADHD who participated in the psychomotor program showed a significant change. There was a meaningful improvement in their visual attention. Second, the impulsivity control ability of the children who participated in the psychomotor program improved statistically significantly in both the visual and the auditory areas the psychomotor program was found to affect the impulsivity control of children with ADHD. Third, the mean response time of children who participated in the psychomotor program did not show a significant change. Fourth, the standard deviation of response time of children who participated in the psychomotor program did not show a statistically significant difference. Application/Improvements: The following suggestions are made for follow-up studies based on the findings of this study. Although generalization was limited due to the limited number of subjects, constant case study would contribute to resolving the problems related to the inattention and impulsivity of children with ADHD.

A hybrid cloud controller for vertical memory elasticity: A control-theoretic approach

Web-facing applications are expected to provide certain performance guarantees despite dynamic and continuous workload changes. As a result, application owners are using cloud computing as it offers the ability to dynamically provision computing resources (e.g., memory, CPU) in response to changes in workload demands to meet performance targets and eliminates upfront costs. Horizontal, vertical, and the combination of the two are the possible dimensions that cloud application can be scaled in terms of the allocated resources. In vertical elasticity as the focus of this work, the size of virtual machines (VMs) can be adjusted in terms of allocated computing resources according to the runtime workload. A commonly used vertical resource elasticity approach is realized by deciding based on resource utilization, named capacity-based. While a new trend is to use the application performance as a decision making criterion, and such an approach is named performance-based. This paper discusses these two approaches and proposes a novel hybrid elasticity approach that takes into account both the application performance and the resource utilization to leverage the benefits of both approaches. The proposed approach is used in realizing vertical elasticity of memory (named as vertical memory elasticity), where the allocated memory of the VM is auto-scaled at runtime. To this aim, we use control theory to synthesize a feedback controller that meets the application performance constraints by auto-scaling the allocated memory, i.e., applying vertical memory elasticity. Different from the existing vertical resource elasticity approaches, the novelty of our work lies in utilizing both the memory utilization and application response time as decision making criteria. To verify the resource efficiency and the ability of the controller in handling unexpected workloads, we have implemented the controller on top of the Xen hypervisor and performed a series of experiments using the RUBBoS interactive benchmark application, under synthetic and real workloads including Wikipedia and FIFA. The results reveal that the hybrid controller meets the application performance target with better performance stability (i.e., lower standard deviation of response time), while achieving a high memory utilization (close to 83%), and allocating less memory compared to all other baseline controllers.

Treating attention deficit hyperactivity disorder with acupuncture: A randomized controlled trial

IntroductionAttention deficit hyperactivity disorder (ADHD) is the most common childhood behavioral problem. The purpose of this study was to evaluate the effectiveness and safety of acupuncture in patients with ADHD. MethodsThe study was randomized, waitlist-controlled, and unblinded. A total of 93 participants with ADHD were enrolled. The acupuncture group received acupuncture treatment twice per week for 6 weeks. The waitlist group did not receive acupuncture during the first six weeks, and then underwent acupuncture treatment during the next six weeks. The primary outcome measure was the ADHD-rating scale. The computerized neurocognitive function tests (CNTs) was conducted as an objective measurement. ResultsThe results of the primary analyses were equivocal. Additional analyses were conducted after data were stratified according to ADHD medication. The acupuncture group not taking ADHD medications demonstrated significantly better performance in the CNTs compared to the waitlist group: the backward digit span test (p=0.026), backward visual span test (p=0.044), correct hit/omission error of auditory continuous performance test (CPT) (p=0.021), standard deviation of response time of visual CPT (p=0.048). The clinical global impression-severity score decreased significantly in the acupuncture group after treatment compared to that in the waitlist group (p=0.000). There was no statistically significant difference between both groups taking ADHD medications, except for verbal learning test in which waitlist group experienced a higher increase than acupuncture group. No adverse effect was reported. ConclusionsAcupuncture positively influences cognitive function in patients who are not on ADHD medication.

A new approach to active rule scheduling

Active database systems (ADSs) react automatically to the occurrence of predefined events by defining a set of active rules. One of the main modules of an ADS is the rule scheduler, which has a significant impact on the effectiveness and efficiency of ADSs. During the rule scheduling process, the rule scheduler is responsible for choosing one of the activated or ready-to-be-executed rules to evaluate its condition section or execute its action section, respectively. This process continues until there is no rule to be evaluated or executed. In this research, we evaluate and compare existing rule scheduling approaches in a laboratory environment based on a three-tier architecture. There are criteria used for the evaluation and comparison of rule scheduling approaches: Average Response Time, Throughput, Response Time Standard Deviation, Time Overhead per Transaction, and CPU Utilization. The three first criteria are used to evaluate the effectiveness, and the latter two criteria are used to evaluate the efficiency of rule scheduling approaches. In this paper, a new approach, referred to as EX-SJFEsTLA, is proposed to improve the rule scheduling process, using a learning automaton. In our laboratory environment, EX-SJFEsTLA is compared with those rule scheduling approaches that are unconstrained as EX-SJFEsTLA is. Unconstrained scheduling approaches serially schedule the rules that do not have any priorities or deadlines. The results of experiments revealed that the proposed approach improved the rule scheduling process according to the evaluation criteria.

Conflict tasks and the diffusion framework: Insight in model constraints based on psychological laws

Formal models of decision-making have traditionally focused on simple, two-choice perceptual decisions. To date, one of the most influential account of this process is Ratcliff’s drift diffusion model (DDM). However, the extension of the model to more complex decisions is not straightforward. In particular, conflicting situations, such as the Eriksen, Stroop, or Simon tasks, require control mechanisms that shield the cognitive system against distracting information. We adopted a novel strategy to constrain response time (RT) models by concurrently investigating two well-known empirical laws in conflict tasks, both at experimental and modeling levels. The two laws, predicted by the DDM, describe the relationship between mean RT and (i) target intensity (Piéron’s law), (ii) standard deviation of RT (Wagenmakers–Brown’s law). Pioneering work has shown that Piéron’s law holds in the Stroop task, and has highlighted an additive relationship between target intensity and compatibility. We found similar results in both Eriksen and Simon tasks. Compatibility also violated Wagenmakers–Brown’s law in a very similar and particular fashion in the two tasks, suggesting a common model framework. To investigate the nature of this commonality, predictions of two recent extensions of the DDM that incorporate selective attention mechanisms were simulated and compared to the experimental results. Both models predict Piéron’s law and the violation of Wagenmakers–Brown’s law by compatibility. Fits of the models to the RT distributions and accuracy data allowed us to further reveal their relative strengths and deficiencies. Combining experimental and computational results, this study sets the groundwork for a unified model of decision-making in conflicting environments.

A Study of the Attention Measurement Variables of a Serious Game as a Treatment for ADHD

The number of young children classified as being affected with attention deficit/hyperactivity disorder (ADHD) is reaching a very serious level. A method to help children with attention-related conditions such as ADHD without depending on drugs is required. In this context, the necessity for research on means of improving attention through the use of computer games, loved by children, has recently been highlighted. Therefore, in this study, research on variables that enable the measurement of attention leading to the development of tangible games to improve attention while children are playing these types of games by moving their bodies is done. First, measurement variables are selected based on a survey of existing attention measurement methods in a computer environment. Experimental research is then conducted to find if children with attention deficits and normal children can be distinguished in terms of the selected measurement variables in the tangible game environment. Those variables are omission error, commission error, average response time, and standard deviation of response time. According to the results, four variables are confirmed to be usable to measure and assess attention in the tangible game to be developed through this study. With these experimental results, a 3D tangible game that improves children's attention level can be developed.

Study on Measurement Variables for Visual Attention Improvement in a Serious Game

Recently attention deficit of children has caused various social problems. Those children who has symptoms like ADHD (Attention Deficit/Hyperactivity Disorder) has to be provided with methods which can enhance their attention level in a child-friendly way such as 3D games. This paper shows a research on how to measure the level of attention for attention deficit children using their favorite 3D games. Firstly, we speculated on the methods about attention measurement used in the medical area. And then we searched measurement variables which can effectively evaluate the level of attention during a game play time. Secondly, we have conducted experiment whether there exists difference about the value of the measurement variables between the two groups, normal children group and attention deficit children group. Those variables are omission error, commission error, average response time, and standard deviation of response time. Though our experiment has only been limited to visual attention level, four measurement variables revealed mutual differences.

On the linear relation between the mean and the standard deviation of a response time distribution.

Although it is generally accepted that the spread of a response time (RT) distribution increases with the mean, the precise nature of this relation remains relatively unexplored. The authors show that in several descriptive RT distributions, the standard deviation increases linearly with the mean. Results from a wide range of tasks from different experimental paradigms support a linear relation between RT mean and RT standard deviation. Both R. Ratcliff's (1978) diffusion model and G. D. Logan's (1988) instance theory of automatization provide explanations for this linear relation. The authors identify and discuss 3 specific boundary conditions for the linear law to hold. The law constrains RT models and supports the use of the coefficient of variation to (a) compare variability while controlling for differences in baseline speed of processing and (b) assess whether changes in performance with practice are due to quantitative speedup or qualitative reorganization.

On the relation between the mean and the variance of a diffusion model response time distribution

Almost every empirical psychological study finds that the variance of a response time (RT) distribution increases with the mean. Here we present a theoretical analysis of the nature of the relationship between RT mean and RT variance, based on the assumption that a diffusion model (e.g., Ratcliff (1978) Psychological Review, 85, 59–108; Ratcliff (2002). Psychonomic Bulletin & Review, 9, 278–291), adequately captures the shape of empirical RT distributions. We first derive closed-form analytic solutions for the mean and variance of a diffusion model RT distribution. Next, we study how systematic differences in two important diffusion model parameters simultaneously affect the mean and the variance of the diffusion model RT distribution. Within the range of plausible values for the drift rate parameter, the relation between RT mean and RT standard deviation is approximately linear. Manipulation of the boundary separation parameter also leads to an approximately linear relation between RT mean and RT standard deviation, but only for low values of the drift rate parameter.

Testing instance models of face repetition priming.

Two experiments examining repetition priming in face recognition are reported. They employed eight rather than the more usual two presentation trials so that the prediction made by Logan's (1988) instance model of power function speedup of response time (RT) distributions could be examined. In Experiment 1, we presented the same photograph on each trial; in Experiment 2, we presented photographs of varying poses. Both experiments showed repetition priming effects for familiar and unfamiliar faces, power function speedup for both the mean and the standard deviation of RT and the power function speedup of the quanties of the RT distributions. We argue that our findings are consistent with the predictions made by the instance model and provide an explanatory challenge for alternative theoretical approaches.

Linking visual and kinesthetic imagery in lipreading instruction.

The purpose of this study was to replicate van Uden's (1983) finding that watching oneself speak improves lipreading of visually confusable nonsense words. Specifically, this replication focused on an older group of subjects whose educational experience varied widely in the emphasis given to spoken communication. Four groups of 12 young-adult subjects who are deaf participated in evaluating two aspects of training: (a) source of video feedback (self or trainer), and (b) timing of feedback (during speech production or after speech production). Mean posttest results indicated significantly increased accuracy in identifying items that had been trained. The group that viewed self-speech after speech-production practice also demonstrated generalization to test items that were not trained. On the combined list of both trained and untrained items, both groups that viewed their own speech achieved significant gains compared to pretest scores, but those that viewed the trainer's speech did not. Response time (RT) during pre- and posttesting was measured using a computer-generated waveform display to calculate the interval between stimulus offset and response onset. Results are reported for 13 subjects with > or = 50% speech intelligibility for words in sentences. Although there were no differences attributable to training conditions, there was an overall increase in the regularity of the identification responses after training (measured by the standard deviation of RTs) and a generalization of the improvement to the untrained items. The results of this study substantiate the beneficial effects of multisensory feedback by practicing lipreading of one's own speech production. This finding appears to apply even to young-adult subjects who are deaf and whose habituated speech patterns may be quite distinct from those of talkers with normal hearing.