Intensity perception. X. Effect of preceding stimulus on identification performance

1980 ◽  
Vol 67 (2) ◽  
pp. 634-637 ◽  
Author(s):  
S. R. Purks ◽  
D. J. Callahan ◽  
L. D. Braida ◽  
N. I. Durlach
Keyword(s):  
Identification Performance ◽  
Preceding Stimulus ◽  
Intensity Perception

Individual Differences Predict Eyewitness Identification Performance

2012 ◽  
Author(s):  
Shannon M. Andersen ◽  
Curt A. Carlson ◽  
Maria Carlson ◽  
Scott D. Gronlund
Keyword(s):  
Individual Differences ◽  
Eyewitness Identification ◽  
Identification Performance

Preceding Stimulus Frequency-Dependent Potentiation of the Postrest Shortening of the Action Potential Duration in Rabbits.

2000 ◽  
Vol 41 (4) ◽  
pp. 481-492
Author(s):  
Naohiko Takahashi ◽  
Morio Ito ◽  
Shuji Ishida ◽  
Takao Fujino ◽  
Mikiko Nakagawa ◽  
...  
Keyword(s):  
Action Potential ◽  
Action Potential Duration ◽  
Stimulus Frequency ◽  
Frequency Dependent ◽  
Preceding Stimulus

Improving person re-identification performance by customized dataset and person detection

2019 ◽  
Vol 2019 (11) ◽  
pp. 268-1-268-9
Author(s):  
Herman G.J Groot ◽  
Egor Bondarev ◽  
Peter H.N. de With
Keyword(s):  
Identification Performance ◽  
Person Detection

New Feature Vectors using GFCC for Speaker Identification

2018 ◽  
Vol 6 (8) ◽  
pp. 243
Author(s):  
A. Nagesh
Keyword(s):  
Speaker Recognition ◽  
Speaker Identification ◽  
Signal To Noise Ratio ◽  
Main Idea ◽  
Extraction Methods ◽  
Identification System ◽  
Identification Performance ◽  
Feature Vectors ◽  
Overall Performance ◽  
New Feature

The feature vectors of speaker identification system plays a crucial role in the overall performance of the system. There are many new feature vectors extraction methods based on MFCC, but ultimately we want to maximize the performance of SID system.  The objective of this paper to derive Gammatone Frequency Cepstral Coefficients (GFCC) based a new set of feature vectors using Gaussian Mixer model (GMM) for speaker identification. The MFCC are the default feature vectors for speaker recognition, but they are not very robust at the presence of additive noise. The GFCC features in recent studies have shown very good robustness against noise and acoustic change. The main idea is  GFCC features based on GMM feature extraction is to improve the overall speaker identification performance in low signal to noise ratio (SNR) conditions.

A Comparison of Odor Intensity Perception by Chinese and South Koreans

2019 ◽  
Vol 20 (5) ◽  
pp. 353-359
Author(s):  
Ik-Jun Yeon ◽  
Yi-Xuan Zhao ◽  
Ju-Yong Jung ◽  
Sung-Sik Park ◽  
Ji-Sun Jung
Keyword(s):  
Odor Intensity ◽  
Intensity Perception

scholarly journals Does Each Menstrual Cycle Elicit a Distinct Effect on Olfactory and Gustatory Perception?

Nutrients ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 2509
Author(s):  
Žana Stanić ◽  
Ajka Pribisalić ◽  
Maria Bošković ◽  
Jasna Bućan Cvitanić ◽  
Kristina Boban ◽  
...  
Keyword(s):  
Menstrual Cycle ◽  
Repeated Measurements ◽  
Intensity Perception ◽  
Anovulatory Cycle ◽  
Sweet Solution ◽  
Additional Control ◽  
Test Kit ◽  
Hormonal Milieu ◽  
Gustatory Perception ◽  
One Way Anova

The obesity pandemic has brought forth a scientific interest in food intake and sensory perception interactions. Olfactory perception and gustatory perception are very complex and under the influence of many factors, including the menstrual cycle. This study aims to clarify conflicting findings on the influence of the menstrual cycle on olfactory and gustatory perception. Women were assessed during four consecutive phases of one complete cycle (mid-follicular, ovulatory, mid-luteal, and late luteal phases (N = 21)), in contrast to women measured across the same phases belonging to two menstrual cycles (N = 29). Additional control groups were men (N = 17), postmenopausal women (N = 14), oral contraceptive users (N = 10), and women with an anovulatory cycle (N = 8). Olfactory threshold, odor discrimination, and identification were tested using the “Sniffin Sticks“ test kit. Suprathreshold intensity and hedonic ratings for sweet, salty, sour, and bitter solutions were assessed. One-way ANOVA and ANOVA for repeated measurements was applied in the analysis, along with linear and trigonometric data fitting and linear mixed models. Linear increases in olfactory discrimination, identification, and overall olfactory performance were observed only in women followed across a complete menstrual cycle. Compared to other groups, these women displayed a cyclic pattern characterized by a predilection for sweet solution; reduced distaste for salty and sour solutions; and increased intensity perception of salty, sour, and bitter solutions towards the end of the cycle. These results suggest that a distinct hormonal milieu of a complete menstrual cycle may be affecting both olfactory and gustatory perception.

scholarly journals Eyewitness identification performance is not affected by time-of-day optimality

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sergii Yaremenko ◽  
Melanie Sauerland ◽  
Lorraine Hope
Keyword(s):  
Eyewitness Identification ◽  
Time Of Day ◽  
Decision Time ◽  
Identification Accuracy ◽  
Optimal Time ◽  
Identification Performance ◽  
Accurate Identification ◽  
Facial Stimuli ◽  
Time Accuracy ◽  
Accuracy Relationship

AbstractThe circadian rhythm regulates arousal levels throughout the day and determines optimal periods for engaging in mental activities. Individuals differ in the time of day at which they reach their peak: Morning-type individuals are at their best in the morning and evening types perform better in the evening. Performance in recall and recognition of non-facial stimuli is generally superior at an individual’s circadian peak. In two studies (Ns = 103 and 324), we tested the effect of time-of-testing optimality on eyewitness identification performance. Morning- and evening-type participants viewed stimulus films depicting staged crimes and made identification decisions from target-present and target-absent lineups either at their optimal or non-optimal time-of-day. We expected that participants would make more accurate identification decisions and that the confidence-accuracy and decision time-accuracy relationships would be stronger at optimal compared to non-optimal time of day. In Experiment 1, identification accuracy was unexpectedly superior at non-optimal compared to optimal time of day in target-present lineups. In Experiment 2, identification accuracy did not differ between the optimal and non-optimal time of day. Contrary to our expectations, confidence-accuracy relationship was generally stronger at non-optimal compared to optimal time of day. In line with our predictions, non-optimal testing eliminated decision-time-accuracy relationship in Experiment 1.

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