scholarly journals Hadronic tau reconstruction and identification performance in ATLAS and CMS

2018 ◽  
Author(s):  
Camilla Galloni ◽  
Keyword(s):  
Identification Performance ◽  
Hadronic Tau

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

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.

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.

scholarly journals The Indices of Cardiovascular Magnetic Resonance Derived Atrial Dynamics May Improve the Contemporary Risk Stratification Algorithms in Children with Hypertrophic Cardiomyopathy

2021 ◽  
Vol 10 (4) ◽  
pp. 650
Author(s):  
Lidia Ziółkowska ◽  
Łukasz Mazurkiewicz ◽  
Joanna Petryka ◽  
Monika Kowalczyk-Domagała ◽  
Agnieszka Boruc ◽  
...  
Keyword(s):  
Hypertrophic Cardiomyopathy ◽  
High Risk ◽  
Risk Stratification ◽  
Heart Association ◽  
The Novel ◽  
Identification Performance ◽  
Strong Trend ◽  
Prognostic Utility ◽  
Conduit Function ◽  
High Risk Children

Introduction: The most efficient risk stratification algorithms are expected to deliver robust and indefectible identification of high-risk children with hypertrophic cardiomyopathy (HCM). Here we compare algorithms for risk stratification in primary prevention in HCM children and investigate whether novel indices of biatrial performance improve these algorithms. Methods and Results: The endpoints were defined as sudden cardiac death, resuscitated cardiac arrest, or appropriate implantable cardioverter-defibrillator discharge. We examined the prognostic utility of classic American College of Cardiology/American Heart Association (ACC/AHA) risk factors, the novel HCM Risk-Kids score and the combination of these with indices of biatrial dynamics. The study consisted of 55 HCM children (mean age 12.5 ± 4.6 years, 69.1% males); seven had endpoints (four deaths, three appropriate ICD discharges). A strong trend (DeLong p = 0.08) was observed towards better endpoint identification performance of the HCM Risk-Kids Model compared to the ACC/AHA strategy. Adding the atrial conduit function component significantly improved the prediction capabilities of the AHA/ACC Model (DeLong p = 0.01) and HCM Risk-Kids algorithm (DeLong p = 0.04). Conclusions: The new HCM Risk-Kids individualised algorithm and score was capable of identifying high-risk children with very good accuracy. The inclusion of one of the atrial dynamic indices improved both risk stratification strategies.

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