scholarly journals The effect of stress on memory for temporal context: an exploratory study

2021 ◽  
Author(s):  
Nicole D. Montijn ◽  
Lotte Gerritsen ◽  
Iris. M. Engelhard
Keyword(s):  
Exploratory Study ◽  
Learning Strategy ◽  
Temporal Structure ◽  
Temporal Context ◽  
Event Sequence ◽  
Fine Grained ◽  
Strategy Shift ◽  
Virtual Time ◽  
Sequence Memory ◽  
Extreme Performance

ABSTRACTTrauma memories can appear dissociated from their original temporal context, and are often relived as they occur in the here-and-now. Potentially these temporal distortions already occur during encoding of the aversive experience as a consequence of stress. Here, 86 participants were subjected to either a stress or control induction, after which they learned the temporal structure of four virtual days. In these virtual days, time was scaled and participants could use clock cues to construe the passage of time within a day. We examined whether stress causes a shift in the learning strategy from one based on virtual time to one based on event sequence. Our results do not show a discernible impact of stress on memory for temporal context, in terms of both sequence memory and more fine-grained representations of time. The stress groups showed more extreme performance trajectories, either good or poor, across all measures. However, as time estimations were overall quite poor it is unclear to what extent this reflected a true strategy shift. Future avenues of research that can build on these findings are discussed.

An Exploratory Study on Learning Strategy Profiles of Middle School Freshmen in Korea

2017 ◽  
Vol 2 (1) ◽  
pp. 7-12
Author(s):  
Jong-Yoen Lee ◽  
◽  
Minjung Chei ◽  
Heejung Seo ◽  
◽  
...  
Keyword(s):  
Middle School ◽  
Exploratory Study ◽  
Learning Strategy

scholarly journals BeautyNet: Joint Multiscale CNN and Transfer Learning Method for Unconstrained Facial Beauty Prediction

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yikui Zhai ◽  
He Cao ◽  
Wenbo Deng ◽  
Junying Gan ◽  
Vincenzo Piuri ◽  
...  
Keyword(s):  
Transfer Learning ◽  
Classification Accuracy ◽  
Learning Strategy ◽  
State Of The Art ◽  
Activation Function ◽  
Training Data ◽  
Fine Grained ◽  
Pattern Recognition Problem ◽  
Face Features ◽  
Facial Beauty

Because of the lack of discriminative face representations and scarcity of labeled training data, facial beauty prediction (FBP), which aims at assessing facial attractiveness automatically, has become a challenging pattern recognition problem. Inspired by recent promising work on fine-grained image classification using the multiscale architecture to extend the diversity of deep features, BeautyNet for unconstrained facial beauty prediction is proposed in this paper. Firstly, a multiscale network is adopted to improve the discriminative of face features. Secondly, to alleviate the computational burden of the multiscale architecture, MFM (max-feature-map) is utilized as an activation function which can not only lighten the network and speed network convergence but also benefit the performance. Finally, transfer learning strategy is introduced here to mitigate the overfitting phenomenon which is caused by the scarcity of labeled facial beauty samples and improves the proposed BeautyNet’s performance. Extensive experiments performed on LSFBD demonstrate that the proposed scheme outperforms the state-of-the-art methods, which can achieve 67.48% classification accuracy.

scholarly journals The relationship between physiological arousal and multiple levels of temporal context in risky choice

2021 ◽  
Author(s):  
Hayley R. Brooks ◽  
Peter Sokol-Hessner
Keyword(s):  
Decision Making ◽  
Risk Taking ◽  
Context Effects ◽  
Temporal Structure ◽  
Physiological Arousal ◽  
Risky Choice ◽  
Context Dependency ◽  
Temporal Context ◽  
Multiple Levels ◽  
Task Level

Context-dependence is fundamental to risky monetary decision-making. A growing body of evidence suggests that temporal context, or recent events, alters risk-taking at a minimum of three timescales: immediate (e.g. trial-by-trial), neighborhood (e.g. a group of consecutive trials), and global (e.g. task-level). To examine context effects, we created a novel monetary choice set with intentional temporal structure in which option values shifted between multiple levels of value magnitude (“contexts”) several times over the course of the task. This structure allowed us to examine whether effects of each timescale were simultaneously present in risky choice behavior and the potential mechanistic role of arousal, an established correlate of risk-taking, in context-dependency. We found that risk-taking was sensitive to immediate, neighborhood, and global timescales, increasing following small (vs. large) outcome amounts, large positive (but not negative) shifts in context, and when cumulative earnings exceeded expectations. We quantified arousal with skin conductance responses, which were specifically related to the global timescale, increasing with cumulative earnings, suggesting that physiological arousal captures a task-level assessment of performance. We complimented this correlational analysis with a secondary reanalysis of risky monetary choices following the double-blind administration of propranolol and a placebo during a temporally unstructured choice task. We replicated our behavioral finding that risk-taking is context-sensitive at three timescales but found no change in temporal context-effects following propranolol administration. Our results demonstrate that risky decision-making is consistently dynamic at multiple timescales and that arousal is likely the consequence, rather than the cause, of temporal context in risky monetary decision-making.

scholarly journals Fine-Grained Mechanical Chinese Named Entity Recognition Based on ALBERT-AttBiLSTM-CRF and Transfer Learning

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1986
Author(s):  
Liguo Yao ◽  
Haisong Huang ◽  
Kuan-Wei Wang ◽  
Shih-Huan Chen ◽  
Qiaoqiao Xiong
Keyword(s):  
Active Learning ◽  
Manufacturing Industry ◽  
Learning Strategy ◽  
Named Entity Recognition ◽  
Entity Recognition ◽  
Utilization Rate ◽  
Data Types ◽  
Fine Grained ◽  
Named Entity ◽  
Model Transfer

Manufacturing text often exists as unlabeled data; the entity is fine-grained and the extraction is difficult. The above problems mean that the manufacturing industry knowledge utilization rate is low. This paper proposes a novel Chinese fine-grained NER (named entity recognition) method based on symmetry lightweight deep multinetwork collaboration (ALBERT-AttBiLSTM-CRF) and model transfer considering active learning (MTAL) to research fine-grained named entity recognition of a few labeled Chinese textual data types. The method is divided into two stages. In the first stage, the ALBERT-AttBiLSTM-CRF was applied for verification in the CLUENER2020 dataset (Public dataset) to get a pretrained model; the experiments show that the model obtains an F1 score of 0.8962, which is better than the best baseline algorithm, an improvement of 9.2%. In the second stage, the pretrained model was transferred into the Manufacturing-NER dataset (our dataset), and we used the active learning strategy to optimize the model effect. The final F1 result of Manufacturing-NER was 0.8931 after the model transfer (it was higher than 0.8576 before the model transfer); so, this method represents an improvement of 3.55%. Our method effectively transfers the existing knowledge from public source data to scientific target data, solving the problem of named entity recognition with scarce labeled domain data, and proves its effectiveness.

Ineffabilities of Making Music: An Exploratory Study

2006 ◽  
Vol 37 (1) ◽  
pp. 9-23 ◽  
Author(s):  
Daniel A. Schmicking
Keyword(s):  
Exploratory Study ◽  
Musical Instrument ◽  
Verbal Interaction ◽  
Embodied Perception ◽  
Fine Grained ◽  
Sensorimotor Knowledge ◽  
A Performance

Some facets of making music are explored by combining arguments of Raffman's cognitivist explanation of ineffability with Merleau-Ponty's view of embodied perception. Behnke's approach to a phenomenology of playing a musical instrument serves as a further source. Focusing on the skilled performer-listener, several types of ineffable knowledge of performing music are identified: gesture feeling ineffability—the performer's sensorimotor knowledge of the gestures necessary to produce instrumental sounds is not exhaustively communicable via language; gesture nuance ineffability—the performer is aware of nuances of instrumental gestures, e.g., micro-variations of intensity or duration of musical gestures, but cannot perceptually, and consequently conceptually, categorize those fine-grained variations; and ineffabilities of inter-subjectivity—the non-verbal interaction between performers that makes a performance a vibrant dialogue is similarly incommunicable. An attempt to identify some of the ineffable dimensions of this dialogue is proposed. Further ineffabilities relating the acoustical embedding of performing are identified.

scholarly journals Sexual networks: measuring sexual selection in structured, polyandrous populations

2013 ◽  
Vol 368 (1613) ◽  
pp. 20120356 ◽  
Author(s):  
Grant C. McDonald ◽  
Richard James ◽  
Jens Krause ◽  
Tommaso Pizzari
Keyword(s):  
Sexual Selection ◽  
Temporal Structure ◽  
Natural Populations ◽  
Population Level ◽  
Global Scale ◽  
Local Scale ◽  
Emergent Property ◽  
Sexual Competition ◽  
Fine Grained ◽  
Multi Level

Sexual selection is traditionally measured at the population level, assuming that populations lack structure. However, increasing evidence undermines this approach, indicating that intrasexual competition in natural populations often displays complex patterns of spatial and temporal structure. This complexity is due in part to the degree and mechanisms of polyandry within a population, which can influence the intensity and scale of both pre- and post-copulatory sexual competition. Attempts to measure selection at the local and global scale have been made through multi-level selection approaches. However, definitions of local scale are often based on physical proximity, providing a rather coarse measure of local competition, particularly in polyandrous populations where the local scale of pre- and post-copulatory competition may differ drastically from each other. These limitations can be solved by social network analysis, which allows us to define a unique sexual environment for each member of a population: ‘local scale’ competition, therefore, becomes an emergent property of a sexual network. Here, we first propose a novel quantitative approach to measure pre- and post-copulatory sexual selection, which integrates multi-level selection with information on local scale competition derived as an emergent property of networks of sexual interactions. We then use simple simulations to illustrate the ways in which polyandry can impact estimates of sexual selection. We show that for intermediate levels of polyandry, the proposed network-based approach provides substantially more accurate measures of sexual selection than the more traditional population-level approach. We argue that the increasing availability of fine-grained behavioural datasets provides exciting new opportunities to develop network approaches to study sexual selection in complex societies.

scholarly journals Complexity and learnability in the explanation of semantic universals of quantifiers

2019 ◽  
Author(s):  
Iris van de Pol ◽  
Shane Steinert-Threlkeld ◽  
Jakub Szymanik
Keyword(s):  
Exploratory Study ◽  
Kolmogorov Complexity ◽  
Natural Languages ◽  
Fine Grained ◽  
Important Challenge ◽  
Robust Result

Despite wide variation among natural languages, there are linguistic properties universal to all (or nearly all) languages. An important challenge is to explain why these linguistic universals hold. One explanation employs a learnability argument: semantic universals hold because expressions that satisfy them are easier to learn than those that do not. In an exploratory study we investigate the relation between learnability and complexity and whether the presence of semantic universals for quantifiers can also be explained by differences in complexity. We develop a novel application of (approximate) Kolmogorov complexity to measure fine-grained distinctions in complexity between different quantifiers. Our results indicate that the monotonicity universal can be explained by complexity while the conservativity universal cannot. For quantity we did not find a robust result. We also found that learnability and complexity pattern together in the monotonicity and conservativity cases that we consider, while that pattern is less robust in the quantity cases.

scholarly journals Spotting The Elusive Prospect Customer: Exploratory Study Of A Web-Powered Customer Relationship Management Framework

2015 ◽  
Vol 31 (5) ◽  
pp. 1935 ◽  
Author(s):  
Myriam Ertz ◽  
Raoul Graf
Keyword(s):  
Customer Relationship Management ◽  
Exploratory Study ◽  
Web Mining ◽  
Opinion Mining ◽  
Relationship Management ◽  
Online Marketing ◽  
Customer Relationship ◽  
Homogeneous Groups ◽  
Fine Grained ◽  
Managerial Implications

Research on how Web-Mining (WM) optimizes marketing, is sparse. Especially absent, is research on WM usefulness for Customer Relationship Management (CRM). The purpose of this research, is to propose a Web Mining-enabled knowledge acquisition framework for analytical CRM. An exploratory study consisting of eleven in-depth interviews with marketing scholars and practitioners revealed that, WM methods and techniques - currently available to practitioners - are well-suited for identifying the profile of web prospects according to their browsing behaviour and to classify them into homogeneous groups. Besides, the nascent technologies regarding opinion mining, sentiment analysis or natural language parsing, and which underlie WM, seem sufficient to acquire knowledge pertaining to attitudinal and other more psychometrically-based characteristics about web prospects. Such tools enable to better understand the so-often termed elusive prospects, by crafting fine-grained online marketing strategies to acquire those would-be customers. The authors discuss the managerial implications that derive from these findings.

Sign in / Sign up

Export Citation Format

Share Document