Modulation of saliva pattern and accurate detection of ovulation using an electrolyte pre-deposition-based method: a pilot study

The Analyst ◽  
2020 ◽  
Vol 145 (5) ◽  
pp. 1716-1723
Author(s):  
Eunji Lee ◽  
Iljeok Kim ◽  
Hyoryung Nam ◽  
Hyungkook Jeon ◽  
Geunbae Lim
Keyword(s):  
Pilot Study ◽  
Modulation Method ◽  
Detection Accuracy ◽  
Ovulation Detection ◽  
Accurate Detection ◽  
Pattern Modulation

A new saliva pattern modulation method was developed, which can improve ovulation detection accuracy based on electrolyte pre-deposition.

scholarly journals Detection of Breaking Waves in Single Wave Gauge Records of Surface Elevation Fluctuations

2019 ◽  
Vol 36 (9) ◽  
pp. 1863-1879 ◽  
Author(s):  
Dan Liberzon ◽  
Alexandru Vreme ◽  
Sagi Knobler ◽  
Itamar Bentwich
Keyword(s):  
Water Waves ◽  
Cost Effective ◽  
Breaking Waves ◽  
Recognition Algorithm ◽  
New Method ◽  
Surface Elevation ◽  
Detection Accuracy ◽  
Single Wave ◽  
Accurate Detection ◽  
Forced Waves

We report the development of a new method for accurate detection of breaking water waves that addresses the need for an accurate and cost-effective method that is independent of human decisions. The new detection method, which enables the detection of breakers using only surface elevation fluctuation measurements from a single wave gauge, supports the development of a new method for research relating to water waves and wind–wave interactions. According to the proposed method, detection is based on the use of the phase-time method to identify breaking-associated patterns in the instantaneous frequency variations of surface elevation fluctuations. A wavelet-based pattern recognition algorithm is devised to detect such patterns and provide accurate detection of breakers in the examined records. Validation and performance tests, conducted using both laboratory and open-sea data, including mechanically generated and wind-forced waves, are reported as well. These tests allow us to derive a set of parameters that assure high detection accuracy rates. The method is shown to be capable to achieve a positive detection rate exceeding 90%.

System of Weak Signal Detection Based on TD-SCDMA Dual Polarized Antenna

2014 ◽  
Vol 8 (1) ◽  
pp. 710-716
Author(s):  
Weiping Mao
Keyword(s):  
Frequency Control ◽  
Detection Accuracy ◽  
Testing Time ◽  
Weak Signal ◽  
Signal Loss ◽  
Traditional System ◽  
Accurate Detection ◽  
Signal Measurement ◽  
Dual Polarized ◽  
Dual Polarized Antenna

In the current signal measuring equipment in measurable characteristics under the condition of weak signal, the signal measurement accuracy is not high. Therefore, this study designs and realizes a kind of equipment based on TD - SCDMA dual polarized antenna for weak signal measurement system. System uses the 2.4 GHz ISM A7105 RF transmitter sent via baud generator clock for electromagnetic wave frequency control forming the local magnetic fields, the system design includes ICL7650 AD620 chip signal amplification module, combined with a module combination based on isolation MAX275 chips, by adjusting the built-in six resistance to noise filtering, in the design of TD -SCDMA dual polarization antenna, through multiple columns of smart antenna radiation, to form the sensitivity of the dynamic contact, to strengthen the weak signal loss repair characteristic, for the synchronization of GPRS communication and AT89C51 MCU for weak signal processing; finally it realizes the weak signal accurate detection. Through the experiment testing, the system can, in complex environment, able for the accurate detection of weak signal. Compared with the traditional system, its detection accuracy by about 49%, reduced testing time by 5 seconds, has a strong practical application value.

scholarly journals The Automatic Detection of Caries in Third Molars on Panoramic Radiographs Using Deep Learning: A Pilot Study

2021 ◽  
Author(s):  
Shankeeth Vinayahalingam ◽  
Steven Kempers ◽  
Lorenzo Limon ◽  
Dionne Deibel ◽  
Thomas Maal ◽  
...  
Keyword(s):  
Deep Learning ◽  
Pilot Study ◽  
Diagnostic Accuracy ◽  
Third Molar ◽  
Caries Detection ◽  
Detection Accuracy ◽  
Third Molars ◽  
Data Set ◽  
Panoramic Radiographs ◽  
Carious Lesions

Abstract The objective of this study is to assess the diagnostic accuracy of dental caries on panoramic radiographs using deep-learning algorithms. A convolutional neural network (CNN) was trained on a reference data set consisted of 400 cropped panoramic images in the detection of carious lesions in mandibular and maxillary third molars, based on the CNN MobileNet V2. For this pilot study, the trained MobileNet V2 was applied on a test set consisting of 100 cropped OPG(s). The detection accuracy and the area-under-the-curve (AUC) were calculated. The proposed method achieved an accuracy of 0.87, a sensitivity of 0.87, a specificity of 0.86 and an AUC of 0.90 for the detection of carious lesions of third molars on OPG(s). A high diagnostic accuracy was achieved in caries detection in third molars based on the MobileNet V2 algorithm as presented. This is beneficial for the further development of a deep-learning based automated third molar removal assessment in future.

scholarly journals NGS4THAL, a one-stop molecular diagnosis and carrier screening tool for thalassemia and other hemoglobinopathies by next-generation sequencing

2021 ◽  
Author(s):  
Yujie Cao ◽  
Shau Yin Ha ◽  
Chi-Chiu So ◽  
Tong Ming For ◽  
Clara Sze-Man Tang ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Molecular Diagnosis ◽  
Carrier Screening ◽  
Detection Accuracy ◽  
Next Generation ◽  
Sequencing Data ◽  
Pathogenic Variants ◽  
Accurate Detection ◽  
Ngs Data ◽  
Generation Sequencing

Abstract Background Thalassemia is one of the most common genetic diseases and a major health threat worldwide. Accurate, efficient and scalable genetic testing methodology is much needed for its molecular diagnosis and carrier screening.Results We developed NGS4THAL, a bioinformatics analysis pipeline analyzing next generation sequencing (NGS) data to detect pathogenic variants for thalassemia and other hemoglobinopathies. NGS4THAL recovers and realigns ambiguously mapped NGS reads derived from the homologous hemoglobin gene clusters to achieve accurate detection of point mutations and small insertion/deletions (InDels). And it uses several structural variant (SV) detection tools with complementary algorithms, and an inhouse database with control data on a number of known SVs to achieve accurate detection of hemoglobin SVs. Detected variants are matched with those in HbVar, allowing recognition of known pathogenic variants, including disease modifiers. Tested on simulation data, NGS4THAL achieved high sensitivity and specificity. For targeted NGS sequencing data from samples with laboratory-confirmed pathogenic hemoglobin variants, it achieved 100% detection accuracy. Application of NGS4THAL on whole genome sequencing data from unrelated studies detected thalassemia mutation carrier rates for Hong Kong Chinese and Northern Vietnamese that were consistent with those from epidemiological studies.Conclusions NGS4THAL is a highly accurate and efficient molecular diagnosis tool for thalassemia and other hemoglobinopathies based on tailored analysis of NGS data, and is potentially scalable for carrier screening purposes.

scholarly journals An Improved Character Recognition Framework for Containers Based on DETR Algorithm

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4612
Author(s):  
Xiaofang Zhao ◽  
Peng Zhou ◽  
Ke Xu ◽  
Liyun Xiao
Keyword(s):  
Character Recognition ◽  
Detection Accuracy ◽  
Position Information ◽  
Multi Scale ◽  
Accurate Detection ◽  
Shipping Containers ◽  
Different Dimensions ◽  
Feature Acquisition ◽  
Input Position ◽  
Detection And Recognition

An improved DETR (detection with transformers) object detection framework is proposed to realize accurate detection and recognition of characters on shipping containers. ResneSt is used as a backbone network with split attention to extract features of different dimensions by multi-channel weight convolution operation, thus increasing the overall feature acquisition ability of the backbone. In addition, multi-scale location encoding is introduced on the basis of the original sinusoidal position encoding model, improving the sensitivity of input position information for the transformer structure. Compared with the original DETR framework, our model has higher confidence regarding accurate detection, with detection accuracy being improved by 2.6%. In a test of character detection and recognition with a self-built dataset, the overall accuracy can reach 98.6%, which meets the requirements of logistics information identification acquisition.

scholarly journals Artificial Intelligence Analysis of Mandibular Movements Enables Accurate Detection of Phasic Sleep Bruxism in OSA Patients: A Pilot Study

2021 ◽  
Vol Volume 13 ◽  
pp. 1449-1459
Author(s):  
Jean-Benoit Martinot ◽  
Nhat-Nam Le-Dong ◽  
Valérie Cuthbert ◽  
Stéphane Denison ◽  
David Gozal ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Pilot Study ◽  
Sleep Bruxism ◽  
Intelligence Analysis ◽  
Accurate Detection ◽  
Mandibular Movements

Pilot study on criteria in cavity preparation-facts or artifacts?

1973 ◽  
Vol 37 (11) ◽  
pp. 27-31 ◽  
Author(s):  
G Salvendy ◽  
WM Hinton ◽  
GW Ferguson ◽  
PR Cunningham
Keyword(s):  
Pilot Study ◽  
Cavity Preparation

A Pilot Study of Early Storybook Reading With Babies With Hearing Loss

2019 ◽  
Vol 62 (9) ◽  
pp. 3397-3412
Author(s):  
Michelle I. Brown ◽  
David Trembath ◽  
Marleen F. Westerveld ◽  
Gail T. Gillon
Keyword(s):  
Hearing Loss ◽  
Pilot Study ◽  
Visual Analysis ◽  
Single Case ◽  
Eye Contact ◽  
Preliminary Evidence ◽  
Storybook Reading ◽  
Book Selection ◽  
Turn Taking ◽  
Parent Child

Purpose This pilot study explored the effectiveness of an early storybook reading (ESR) intervention for parents with babies with hearing loss (HL) for improving (a) parents' book selection skills, (b) parent–child eye contact, and (c) parent–child turn-taking. Advancing research into ESR, this study examined whether the benefits from an ESR intervention reported for babies without HL were also observed in babies with HL. Method Four mother–baby dyads participated in a multiple baseline single-case experimental design across behaviors. Treatment effects for parents' book selection skills, parent–child eye contact, and parent–child turn-taking were examined using visual analysis and Tau-U analysis. Results Statistically significant increases, with large to very large effect sizes, were observed for all 4 participants for parent–child eye contact and parent–child turn-taking. Limited improvements with ceiling effects were observed for parents' book selection skills. Conclusion The findings provide preliminary evidence for the effectiveness of an ESR intervention for babies with HL for promoting parent–child interactions through eye contact and turn-taking.

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