Optimal Resource Allocation and Task Segmentation in IoT Enabled Mobile Edge Cloud

<div>This work examines the convex optimization problem. The objective is to minimize the task duration by optimal allocation of the resources like local and edge computational capabilities, transmission power, and optimal task segmentation. For optimal allocation of resources, an algorithm name Estimation of Optimal Resource Allocator (EORA) is designed to optimize the function by keeping track of statistics of each candidate of the population. </div>

Optimal Resource Allocation and Task Segmentation in IoT Enabled Mobile Edge Cloud

<div>This work examines the convex optimization problem. The objective is to minimize the task duration by optimal allocation of the resources like local and edge computational capabilities, transmission power, and optimal task segmentation. For optimal allocation of resources, an algorithm name Estimation of Optimal Resource Allocator (EORA) is designed to optimize the function by keeping track of statistics of each candidate of the population. </div>

Temporally Dynamic Interaction between Drug Cue Reactivity and Response Inhibition: An fMRI Study among People with Methamphetamine Use Disorder

Cue-induced drug craving and disinhibition are two essential components of continued drug use and relapse in substance use disorders. While these two phenomena develop and interact across time, the temporal dynamics of their underlying neural activity and their interaction remain under-investigated. To explore these dynamics, an analysis of time-varying activation was applied to fMRI data from 62 men with methamphetamine use disorder in their first weeks of recovery in abstinence-based treatment program. Using a mixed block-event, factorial cue-reactivity/Go-NoGo task, and a sliding window across the task duration, dynamically-activated regions were identified in linear mixed effects models (LMEs). Habituation to drug cues across time was observed in the superior temporal gyri, amygdalae, left hippocampus, and right precuneus, while response-inhibition was associated with the sensitization of temporally-dynamic activations across many regions of the inhibitory frontoparietal network. Cue-reactivity and response-inhibition dynamically interact in the parahippocampal gyri and right precuneus (corrected p-value < 0.001) regions, which show a declining cue-reactivity contrast and an increasing response-inhibition contrast. Overall, the declining craving-related activations (habituation) and increasing inhibition-associated activations (sensitization) along the task duration suggest the gradual recruitment of response-inhibition process and the concurrent habituation to drug cues in areas with significant dynamic interaction. This exploratory study demonstrates the time-variance of the neural activations undergirding cue-reactivity, response-inhibition, and their interaction, and suggests potentials to assess this dynamic interaction. This preliminary evidence provides justifications for new avenues in biomarker development and interventions using cue exposure paradigms, which could promote habituation to drug cues and sensitization in inhibitory control regions.

The performance costs of interruption during visual search are determined by the type of search task

Prior research has shown that interruptions lead to a variety of performance costs. However, these costs are heterogenous and poorly understood. Under some circumstances, interruptions lead to large decreases in accuracy on the primary task, whereas in others task duration increases, but task accuracy is unaffected. Presently, the underlying cause of these costs is unclear. The Memory for Goals model suggests that interruptions interfere with the ability to represent the current goal of the primary task. Here, we test the idea that working memory (WM) may play a critical role in representing the current goal and thus may underlie the observed costs associated with interruption. In two experiments, we utilized laboratory-based visual search tasks, which differed in their WM demands, in order to assess how this difference influenced the observed interruption costs. Interruptions led to more severe performance costs when the target of the search changed on each trial. When the search target was consistent across trials, the cost of interruption was greatly reduced. This suggests that the WM demands associated with the primary task play an important role in determining the performance costs of interruption. Our findings suggest that it is important for research to consider the cognitive processes a task engages in order to predict the nature of the adverse effects of interruption in applied settings such as radiology.

Assessing the difficulty of annotating medical data in crowdworking with help of experiments

Background As healthcare-related data proliferate, there is need to annotate them expertly for the purposes of personalized medicine. Crowdworking is an alternative to expensive expert labour. Annotation corresponds to diagnosis, so comparing unlabeled records to labeled ones seems more appropriate for crowdworkers without medical expertise. We modeled the comparison of a record to two other records as a triplet annotation task, and we conducted an experiment to investigate to what extend sensor-measured stress, task duration, uncertainty of the annotators and agreement among the annotators could predict annotation correctness. Materials and methods We conducted an annotation experiment on health data from a population-based study. The triplet annotation task was to decide whether an individual was more similar to a healthy one or to one with a given disorder. We used hepatic steatosis as example disorder, and described the individuals with 10 pre-selected characteristics related to this disorder. We recorded task duration, electro-dermal activity as stress indicator, and uncertainty as stated by the experiment participants (n = 29 non-experts and three experts) for 30 triplets. We built an Artificial Similarity-Based Annotator (ASBA) and compared its correctness and uncertainty to that of the experiment participants. Results We found no correlation between correctness and either of stated uncertainty, stress and task duration. Annotator agreement has not been predictive either. Notably, for some tasks, annotators agreed unanimously on an incorrect annotation. When controlling for Triplet ID, we identified significant correlations, indicating that correctness, stress levels and annotation duration depend on the task itself. Average correctness among the experiment participants was slightly lower than achieved by ASBA. Triplet annotation turned to be similarly difficult for experts as for non-experts. Conclusion Our lab experiment indicates that the task of triplet annotation must be prepared cautiously if delegated to crowdworkers. Neither certainty nor agreement among annotators should be assumed to imply correct annotation, because annotators may misjudge difficult tasks as easy and agree on incorrect annotations. Further research is needed to improve visualizations for complex tasks, to judiciously decide how much information to provide, Out-of-the-lab experiments in crowdworker setting are needed to identify appropriate designs of a human-annotation task, and to assess under what circumstances non-human annotation should be preferred.

Study of EHR-mediated workflows using ethnography and process mining methods

Rapid ethnography and data mining approaches have been used individually to study clinical workflows, but have seldom been used together to overcome the limitations inherent in either type of method. For rapid ethnography, how reliable are the findings drawn from small samples? For data mining, how accurate are the discoveries drawn from automatic analysis of big data, when compared with observable data? This paper explores the combined use of rapid ethnography and process mining, aka ethno-mining, to study and compare metrics of a typical clinical documentation task, vital signs charting. The task was performed with different electronic health records (EHRs) used in three different hospital sites. The individual methods revealed substantial discrepancies in task duration between sites. Specifically, means of 159.6(78.55), 38.2(34.9), and 431.3(283.04) seconds were captured with rapid ethnography. When process mining was used, means of 518.6(3,808), 345.5(660.6), and 119.74(210.3) seconds were found. When ethno-mining was applied instead, outliers could be identified, explained and removed. Without outliers, mean task duration was similar between sites (78.1(66.7), 72.5(78.5), and 71.7(75) seconds). Results from this work suggest that integrating rapid ethnography and data mining into a single process may provide more meaningful results than a siloed approach when studying of workflow.