scholarly journals Feasibility Study of an Automated Carbohydrate Estimation System Using Thai Food Images in Comparison With Estimation by Dietitians

2021 ◽  
Vol 8 ◽  
Author(s):  
Phawinpon Chotwanvirat ◽  
Narit Hnoohom ◽  
Nipa Rojroongwasinkul ◽  
Wantanee Kriengsinyos
Keyword(s):  
Estimation Error ◽  
Weight System ◽  
Registered Dietitians ◽  
Estimation Errors ◽  
Carbohydrate Counting ◽  
Measured Weight ◽  
Food Image ◽  
Food Images ◽  
Estimation System

Carbohydrate counting is essential for well-controlled blood glucose in people with type 1 diabetes, but to perform it precisely is challenging, especially for Thai foods. Consequently, we developed a deep learning-based system for automatic carbohydrate counting using Thai food images taken from smartphones. The newly constructed Thai food image dataset contained 256,178 ingredient objects with measured weight for 175 food categories among 75,232 images. These were used to train object detector and weight estimator algorithms. After training, the system had a Top-1 accuracy of 80.9% and a root mean square error (RMSE) for carbohydrate estimation of <10 g in the test dataset. Another set of 20 images, which contained 48 food items in total, was used to compare the accuracy of carbohydrate estimations between measured weight, system estimation, and eight experienced registered dietitians (RDs). System estimation error was 4%, while estimation errors from nearest, lowest, and highest carbohydrate among RDs were 0.7, 25.5, and 7.6%, respectively. The RMSE for carbohydrate estimations of the system and the lowest RD were 9.4 and 10.2, respectively. The system could perform with an estimation error of <10 g for 13/20 images, which placed it third behind only two of the best performing RDs: RD1 (15/20 images) and RD5 (14/20 images). Hence, the system was satisfactory in terms of accurately estimating carbohydrate content, with results being comparable with those of experienced dietitians.

Food exchange estimation by children with type 1 diabetes at summer camp

2017 ◽  
Vol 30 (1) ◽  
Author(s):  
Wojciech Szypowski ◽  
Karolina Kunecka ◽  
Beata Zduńczyk ◽  
Katarzyna Piechowiak ◽  
Maria Dyczek ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Mobile Applications ◽  
Summer Camp ◽  
Estimation Error ◽  
Carbohydrate Counting ◽  
Food Exchange ◽  
Younger Age ◽  
True Values ◽  
Main Meals

AbstractBackground:As exchange counting poses difficulty for children with type 1 diabetes (T1D) attending diabetes camps, they often guesstimate food amount without performing an exchange calculation. The aim of the study was to compare the accuracy of estimation with exchange counting using the mobile food exchange calculator (MFEC).Methods:During a summer camp, 25 children with T1D on pumps estimated the number of carbohydrate (CE) and fat/protein exchanges (FPE) appropriate for main meals. Afterwards, the number of exchanges was counted with MFEC and electronic scales.Results:There was a difference between CE (p<0.0001) and FPE (p<0.0001) estimations and counting using MFEC. The youth miscalculated the true values of ≥1 CE and ≥1 FPE by 31% and 23%, respectively. They more often underestimated than overestimated CE and FPE (p<0.0001). The estimation error increased with younger age.Conclusions:Carbohydrate counting caused significant error in the exchange number. The use of MFEC facilitates correct exchange calculation. Patients should weigh food and calculate exchanges themselves using mobile applications.

scholarly journals Regional robust secure precise wireless transmission design for multi-user UAV broadcasting system

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Tong Shen ◽  
Tingting Liu ◽  
Yan Lin ◽  
Yongpeng Wu ◽  
Feng Shu ◽  
...  
Keyword(s):  
Estimation Error ◽  
Wireless Transmission ◽  
Artificial Noise ◽  
Target Area ◽  
Secrecy Rate ◽  
Estimation Errors ◽  
Transmission Design ◽  
Broadcasting System ◽  
Aerial Vehicle ◽  
Noise Ratio

Abstract In this paper, two regional robust secure precise wireless transmission (SPWT) schemes for multi-user unmanned aerial vehicle (UAV), (1)regional signal-to-leakage-and-noise ratio (SLNR) and artificial-noise-to-leakage-and-noise ratio (ANLNR) (R-SLNR-ANLNR) maximization and (2) point SLNR and ANLNR (P-SLNR-ANLNR) maximization, are proposed to tackle with the estimation errors of the target users’ location. In the SPWT system, the estimation error for SPWT cannot be ignored. However, the conventional robust methods in secure wireless communications optimize the beamforming vector in the desired positions only in statistical means and cannot guarantee the security for each symbol. The proposed regional robust schemes are designed for optimizing the secrecy performance in the whole error region around the estimated location. Specifically, with the known maximal estimation error, we define the target region and wiretap region. Then, we design an optimal beamforming vector and an artificial noise projection matrix, which achieve the confidential signal in the target area having the maximal power while only few signal power is conserved in the potential wiretap region. Instead of considering the statistical distributions of the estimated errors into optimization, we optimize the SLNR and ANLNR of the whole target area, which significantly decreases the complexity. Moreover, the proposed schemes can ensure that the desired users are located in the optimized region, which are more practical than the conventional methods. Simulation results show that our proposed regional robust SPWT design is capable of substantially improving the secrecy rate compared to the conventional non-robust method. The P-SLNR-ANLNR maximization-based method has the comparable secrecy performance with lower complexity than that of the R-SLNR-ANLNR maximization-based method.

Improved estimation is a prerequisite for successful terminal guidance

2005 ◽  
Vol 219 (2) ◽  
pp. 145-156 ◽  
Author(s):  
J Shinar ◽  
V Turetsky
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Estimation Errors ◽  
New Approach ◽  
Target Acceleration ◽  
The Future ◽  
New Ideas ◽  
Estimation System ◽  
Terminal Guidance

Successful interception of manoeuvring anti-surface missiles that are expected in the future can be achieved only if the estimation errors against manoeuvring targets can be minimized. The paper raises new ideas for an improved estimation concept by separating the tasks of the estimation system and by explicit use of the time-to-go in the process. The outcome of the new approach is illustrated by results of Monte Carlo simulations in generic interception scenarios. The results indicate that if an eventual ‘jump’ in the commanded target acceleration is detected sufficiently rapidly, small estimation errors and consequently precise guidance can be obtained.

Effects of advanced carbohydrate counting in patients with Type 1 diabetes: a systematic review

2014 ◽  
Vol 31 (8) ◽  
pp. 886-896 ◽  
Author(s):  
S. Schmidt ◽  
B. Schelde ◽  
K. Nørgaard
Keyword(s):  
Systematic Review ◽  
Type 1 Diabetes ◽  
Carbohydrate Counting

scholarly journals Application of Attenuation Correction to Quantitative Precipitation Estimation on C-Band Weather Radar in Bengkulu

2021 ◽  
Vol 893 (1) ◽  
pp. 012054
Author(s):  
M F Handoyo ◽  
M P Hadi ◽  
S Suprayogi
Keyword(s):  
Attenuation Correction ◽  
Estimation Error ◽  
Weather Radar ◽  
Radar Data ◽  
Signal Interference ◽  
Active System ◽  
Estimation Errors ◽  
Rain Gauges ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation

Abstract A weather radar is an active system remote sensing tool that observes precipitation indirectly. Weather radar has an advantage in estimating precipitation because it has a high spatial resolution (up to 0.5 km). Reflectivity generated by weather radar still has signal interference caused by attenuation factors. Attenuation causes the Quantitative Precipitation Estimation (QPE) by the C-band weather radar to underestimate. Therefore attenuation correction on C-band weather radar is needed to eliminate precipitation estimation errors. This study aims to apply attenuation correction to determine Quantitative Precipitation Estimation (QPE) on the c-band weather radar in Bengkulu in December 2018. Gate-by-gate method attenuation correction with Kraemer approach has applied to c-band weather radar data from the Indonesian Agency for Meteorology and Geophysics (BMKG) weather radar network Bengkulu. This method uses reflectivity as the only input. Quantitative Precipitation Estimation (QPE) has obtained by comparing weather radar-based rain estimates to 10 observation rain gauges over a month with the Z-R relation equation. Root Mean Square Error (RMSE) is used to calculate the estimation error. Weather radar data are processed using Python-based libraries Wradlib and ArcGIS 10.5. As a result, the calculation between the weather radar estimate precipitation and the observed rainfall obtained equation Z=2,65R1,3. The attenuation correction process with Kreamer's approach on the c-band weather radar has reduced error in the Qualitative Precipitation Estimation (QPE). Corrected precipitation has a smaller error value (r = 0.88; RMSE = 8.38) than the uncorrected precipitation (r = 0.83; RMSE = 11.70).

Carbohydrate counting in type 1 diabetes: time to REACCT

2007 ◽  
Vol 24 (3) ◽  
pp. 134-136 ◽  
Author(s):  
TJ Ulahannan ◽  
W Ross ◽  
FC Davies
Keyword(s):  
Type 1 Diabetes ◽  
Carbohydrate Counting

scholarly journals The Quality of Accruals and Earnings: The Role of Accrual Estimation Errors

2002 ◽  
Vol 77 (s-1) ◽  
pp. 35-59 ◽  
Author(s):  
Patricia M. Dechow ◽  
Ilia D. Dichev
Keyword(s):  
Estimation Error ◽  
Cash Flows ◽  
Empirical Measure ◽  
Earnings Persistence ◽  
Working Capital ◽  
Estimation Errors ◽  
Accrual Quality ◽  
Flows Over Time

This paper suggests a new measure of one aspect of the quality of working capital accruals and earnings. One role of accruals is to shift or adjust the recognition of cash flows over time so that the adjusted numbers (earnings) better measure firm performance. However, accruals require assumptions and estimates of future cash flows. We argue that the quality of accruals and earnings is decreasing in the magnitude of estimation error in accruals. We derive an empirical measure of accrual quality as the residuals from firm-specific regressions of changes in working capital on past, present, and future operating cash flows. We document that observable firm characteristics can be used as instruments for accrual quality (e.g., volatility of accruals and volatility of earnings). Finally, we show that our measure of accrual quality is positively related to earnings persistence.

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