scholarly journals Monitoring of Stiffness Estimation for Tomato During Storage Period

2021 ◽  
Vol 2129 (1) ◽  
pp. 012104
Author(s):  
M K R Hashim ◽  
M N A Uda ◽  
Muhammad Adi Yusri Mohd Sabri ◽  
U Hashim ◽  
M N Afnan Uda
Keyword(s):  
Quality Assessment ◽  
Sound Wave ◽  
Fruits And Vegetables ◽  
Storage Period ◽  
Cost Effective ◽  
Assessment Method

Abstract The quality assessment through stiffness or firmness is widely used to identify the maturity of fruits and vegetables. Most of assessment method are destructive and no cost effective. This study was done to develop a stiffness estimation for tomato during storage period by using acoustics method. This project involved the usage of modern tools such as Arduino and LabVIEW where both of them were used to controls and regulate the data collected from a buzzer that produced sinusoidal sound wave. The time taken for the sound wave to reach the microphone were recorded as it was considered as the important factor in determining the stiffness factor, S, alongside the changing mass and diameter of the tomato during its storage period. At the end of the project, it was shown that the stiffness value of the tomato decreases in hand as the day progress. Furthermore, the correlation of the parameters was also calculated in which R2 value between stiffness and weight was finalized at 0.8993, with equation of y = 379.45 × – 40.321. The findings had successfully proved that the parameters involved in the research are greatly related.

No-Reference Image Quality Assessment Based on Multi-Order Gradients Statistics

2020 ◽  
Vol 64 (1) ◽  
pp. 10505-1-10505-16
Author(s):  
Yin Zhang ◽  
Xuehan Bai ◽  
Junhua Yan ◽  
Yongqi Xiao ◽  
C. R. Chatwin ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Assessment Method ◽  
Image Distortion ◽  
Image Feature ◽  
Reference Image ◽  
Gradient Magnitude ◽  
Distortion Type

Abstract A new blind image quality assessment method called No-Reference Image Quality Assessment Based on Multi-Order Gradients Statistics is proposed, which is aimed at solving the problem that the existing no-reference image quality assessment methods cannot determine the type of image distortion and that the quality evaluation has poor robustness for different types of distortion. In this article, an 18-dimensional image feature vector is constructed from gradient magnitude features, relative gradient orientation features, and relative gradient magnitude features over two scales and three orders on the basis of the relationship between multi-order gradient statistics and the type and degree of image distortion. The feature matrix and distortion types of known distorted images are used to train an AdaBoost_BP neural network to determine the image distortion type; the feature matrix and subjective scores of known distorted images are used to train an AdaBoost_BP neural network to determine the image distortion degree. A series of comparative experiments were carried out using Laboratory of Image and Video Engineering (LIVE), LIVE Multiply Distorted Image Quality, Tampere Image, and Optics Remote Sensing Image databases. Experimental results show that the proposed method has high distortion type judgment accuracy and that the quality score shows good subjective consistency and robustness for all types of distortion. The performance of the proposed method is not constricted to a particular database, and the proposed method has high operational efficiency.

scholarly journals Reproducibility and relative validity of a semi-quantitative food frequency questionnaire for the Chinese lactating mothers

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Ye Ding ◽  
Fang Li ◽  
Ping Hu ◽  
Mei Ye ◽  
Fangping Xu ◽  
...  
Keyword(s):  
Food Frequency Questionnaire ◽  
Dietary Assessment ◽  
Correlation Coefficients ◽  
Cost Effective ◽  
Assessment Method ◽  
Food Frequency ◽  
Relative Validity ◽  
Lactating Mothers ◽  
Dietary Record ◽  
Spearman’S Correlation

Abstract Background The dietary nutritional status of the lactating mothers is related to maternal health and has a significant impact on the growth and development of infants through the secretion of breast milk. The food frequency questionnaire (FFQ) is the most cost-effective dietary assessment method that can help obtain information on the usual dietary pattern of participants. Until now, the FFQs have been used for different populations in China, but there are few FFQs available for the lactating mothers. We aimed to develop a semi-quantitative, 156-item FFQ for the Chinese lactating mothers, and evaluate its reproducibility and relative validity. Methods A total of 112 lactating mothers completed two FFQs and one 3-d dietary record (3DR). The first FFQ (FFQ1) was conducted during postpartum at 60–65 days and the second FFQ (FFQ2) during subsequent follow-up at 5 weeks. The 3DR was completed with portion sizes assessed using photographs taken by the respondent before and after eating (instant photography) 1 week after FFQ1. Results For reproducibility, the Spearman’s correlation coefficients for food ranged from 0.34 to 0.68, and for nutrients from 0.25 to 0.61. Meanwhile, the intra-class correlation coefficients for food ranged from 0.48 to 0.87, and for nutrients from 0.27 to 0.70. For relative validity, the Spearman’s correlation coefficients for food ranged from 0.32 to 0.56, and for nutrients from 0.23 to 0.72. The energy-adjusted coefficients for food ranged from 0.26 to 0.55, and for nutrients from 0.22 to 0.47. Moreover, the de-attenuation coefficients for food ranged from 0.34 to 0.67, and for nutrients from 0.28 to 0.77. The Bland-Altman plots also showed reasonably acceptable agreement between the two methods. Conclusions This FFQ is a reasonably reproducible and a relative valid tool for assessing dietary intake of the Chinese lactating mothers.

A Video Quality Assessment Method for VoIP Applications Based on User Experience

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Zedong Wang ◽  
Jing Wang ◽  
Fei Wang ◽  
Chengcai Li ◽  
Zesong Fei ◽  
...  
Keyword(s):  
Quality Assessment ◽  
User Experience ◽  
Video Quality ◽  
Assessment Method ◽  
Video Quality Assessment ◽  
Quality Assessment Method
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