Normative study of 500 general-knowledge for true-false questions in Russian

In this report we present Russian norms for 500 general knowledge questions in True-False format. The questions cover the topics of Natural Sciences, Social Sciences, Culture and Sports. For each of the questions we report accuracy and confidence.

Laterality Differences in Perception

<p>The subject of this thesis is laterality differences in perception. The term "laterality difference" refers to an asymmetry in report accuracy for stimuli presented about the center of a person's visual field. A discussion of the literature and experimental findings relevant to this topic is first given. This is followed by a detailed analysis of eight experiments which examine the effects of a number of variables on laterality differences. The main conclusion drawn from these experiments is that perceptual laterality differences are a function of acquired. Reading habits, the structural characteristics of the stimuli, and the order in which the stimuli are reported. To a lesser extent, they are also related to certain other factors such as differential eye sensitivity and handedness. An interpretation in terms of a "post-exposure trace-scanning" hypothesis is given to account for the experimental findings.</p>

Laterality Differences in Perception

<p>The subject of this thesis is laterality differences in perception. The term "laterality difference" refers to an asymmetry in report accuracy for stimuli presented about the center of a person's visual field. A discussion of the literature and experimental findings relevant to this topic is first given. This is followed by a detailed analysis of eight experiments which examine the effects of a number of variables on laterality differences. The main conclusion drawn from these experiments is that perceptual laterality differences are a function of acquired. Reading habits, the structural characteristics of the stimuli, and the order in which the stimuli are reported. To a lesser extent, they are also related to certain other factors such as differential eye sensitivity and handedness. An interpretation in terms of a "post-exposure trace-scanning" hypothesis is given to account for the experimental findings.</p>

Sensitivity of deep learning applied to spatial image steganalysis

In recent years, the traditional approach to spatial image steganalysis has shifted to deep learning (DL) techniques, which have improved the detection accuracy while combining feature extraction and classification in a single model, usually a convolutional neural network (CNN). The main contribution from researchers in this area is new architectures that further improve detection accuracy. Nevertheless, the preprocessing and partition of the database influence the overall performance of the CNN. This paper presents the results achieved by novel steganalysis networks (Xu-Net, Ye-Net, Yedroudj-Net, SR-Net, Zhu-Net, and GBRAS-Net) using different combinations of image and filter normalization ranges, various database splits, different activation functions for the preprocessing stage, as well as an analysis on the activation maps and how to report accuracy. These results demonstrate how sensible steganalysis systems are to changes in any stage of the process, and how important it is for researchers in this field to register and report their work thoroughly. We also propose a set of recommendations for the design of experiments in steganalysis with DL.

Target-Target Perceptual Similarity Within the Attentional Blink

Three experiments investigated the role of target-target perceptual similarity within the attentional blink (AB). Various geometric shapes were presented in a rapid serial visual presentation task. Targets could have 2, 1, or 0 shared features. Features included shape and size. The second target was presented after five or six different lags after the first target. The task was to detect both targets on each trial. Second-target report accuracy was increased by target-target similarity. This modulation was observed more for mixed-trial design as compared with blocked design. Results are discussed in terms of increased stability of working memory representations and reduced interference for second-target processing.

Resident-faculty overnight discrepancy rates as a function of number of consecutive nights during a week of night float

ObjectivesIn 2018, the ACGME (Accreditation Council for Graduate Medical Education) made a change to the maximum permissible number of consecutive nights a resident trainee can be on “night float,” from six to seven nights. To our knowledge, although investigators have studied overall discrepancy rates and discrepancy rates as a function of shift length or perceived workload of a particular shift, no study has been performed to evaluate resident-faculty discrepancy rates as a quality/performance proxy, to see whether resident performance declines as a function of the number of consecutive nights. Our hypothesis is that we would observe a progressive increase in significant overnight resident – attending discrepancies over the 7 days’ time.MethodsA total of 8,488 reports were extracted between 4/26/2019 to 8/22/2019 retrospectively. Data was obtained from the voice dictation system report server. Exported query was saved as a .csv file format and analyzed using Python packages. A “discrepancy checker” was created to search all finalized reports for the departmental standard heading of “Final Attending Report,” used to specify any significant changes from the preliminary interpretation.ResultsModel estimates varied on different days however there were no trends or patterns to indicate a deterioration in resident performance throughout the week. There were comparable probabilities throughout the week, with 2.17% on Monday, 2.35% on Thursday and 2.05% on Friday.ConclusionsOur results reveal no convincing trend in terms of overnight report discrepancies between the preliminary report generated by the night float resident and the final report issued by a faculty the following morning. These results are in support of the ACGME’s recent change in the permissible number of consecutive nights on night float. We did not prove our hypothesis that resident performance on-call in the domain of report accuracy would diminish over seven consecutive nights while on the night float rotation. Our results found that performance remained fairly uniform over the course of the week.

Machine-Scored Syntax: Comparison of the CLAN Automatic Scoring Program to Manual Scoring

Purpose The results of automatic machine scoring of the Index of Productive Syntax from the Computerized Language ANalysis (CLAN) tools of the Child Language Data Exchange System of TalkBank (MacWhinney, 2000) were compared to manual scoring to determine the accuracy of the machine-scored method. Method Twenty transcripts of 10 children from archival data of the Weismer Corpus from the Child Language Data Exchange System at 30 and 42 months were examined. Measures of absolute point difference and point-to-point accuracy were compared, as well as points erroneously given and missed. Two new measures for evaluating automatic scoring of the Index of Productive Syntax were introduced: Machine Item Accuracy (MIA) and Cascade Failure Rate— these measures further analyze points erroneously given and missed. Differences in total scores, subscale scores, and individual structures were also reported. Results Mean absolute point difference between machine and hand scoring was 3.65, point-to-point agreement was 72.6%, and MIA was 74.9%. There were large differences in subscales, with Noun Phrase and Verb Phrase subscales generally providing greater accuracy and agreement than Question/Negation and Sentence Structures subscales. There were significantly more erroneous than missed items in machine scoring, attributed to problems of mistagging of elements, imprecise search patterns, and other errors. Cascade failure resulted in an average of 4.65 points lost per transcript. Conclusions The CLAN program showed relatively inaccurate outcomes in comparison to manual scoring on both traditional and new measures of accuracy. Recommendations for improvement of the program include accounting for second exemplar violations and applying cascaded credit, among other suggestions. It was proposed that research on machine-scored syntax routinely report accuracy measures detailing erroneous and missed scores, including MIA, so that researchers and clinicians are aware of the limitations of a machine-scoring program. Supplemental Material https://doi.org/10.23641/asha.11984364

Learning how to exploit sources of information

How is our strategy for forming memories shaped by experience with a task? Previous work using surprise questions (i.e. unexpected by the participant) has shown a remarkable inability to report attributes of an attended target in a search display. This representational poverty presumably reflects a form of information exploitation, in which control processes specialize the conversion of available information into memory representations. We hypothesize that such control is refined by repeated experience with a task, and as a result, memory representations will specialize as task experience accrues, such that report accuracy for an unexpected question will progressively worsen as the number of preceding trials increases. To test this, subjects were asked to report the location of a letter among three digits. The ability to respond correctly to a surprise question about the identity of that letter became worse as the experiment progressed. A followup study evaluated whether this incremental worsening of report accuracy could be explained as a buildup of proactive interference by varying the set of letters for the surprise test. The results were unchanged relative to the original experiment, which argues against a primary contribution of proactive interference in the worsening performance. The effect was replicated in a similar paradigm using color disks. These findings illustrate that repeated performance of a prescriptive task engages an adaptive modification of control processes that focus information processing on specific attributes of a stimulus that are expected to be necessary in the future, regardless of their immediate task relevance.