• Analytical Science and Technology
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• v.34 no.6
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• pp.241-250
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• 2021

Calibration curves are essential in quantitative methods and for improving the accuracy of analyte measurements in biological samples. In this study, a statistical analysis model built in the R language (The R Foundation for Statistical Computing) was used to identify a set of weighting factors and regression models based on a stepwise selection criteria. An LC-MS/MS method was used to detect the presence of urinary methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹ -tetrahydrocannabinol in a sample set. Weighting factors for the calibration curves were derived by calculating the heteroscedasticity of the measurements, where the presence of heteroscedasticity was determined via variance tests. The optimal regression model and weighting factor were chosen according to the sum of the absolute percentage relative error. Subsequently, the order of the regression model was calculated using a partial variance test. The proposed statistical analysis tool facilitated selection of the optimal calibration model and detection of methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol in urine. Thus, this study for the selection of weighting and the use of a complex regression equation may provide insights for linear and quadratic regressions in analytical and bioanalytical measurements.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.187-196
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• 2021

The mobility handicapped are representative socially vulnerable people who account for a high percentage of our society. Due to the recent development of technology, personalized welfare technologies for the socially vulnerable are being studied, but it is relatively insufficient compared to the general people. In this study, we intend to implement a personalized restaurant recommendation system for the mobility handicapped. To this end, a hybrid recommendation system was implemented by combining the data of special transportation boarding and alighting history (7,153 cases) and information of Daegu Food restaurants (955 cases). In order to evaluate the effectiveness of the implemented recommendation system, we conducted performance comparisons with existing recommendation systems by prediction error rate and recommendation coverage. As a result of the analysis, the performance was higher than that of the existing recommendation system, and the possibility of a personalized restaurant recommendation system for the mobility handicapped was confirmed. In addition, we also confirmed the correlation in which similar restaurants are recommended in some types of the mobility handicapped. As a result of this study, it is judged that it will contribute to the use of restaurants with high satisfaction for the mobility handicapped, and the limitations of the study are also presented.

• Animal Bioscience
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• v.35 no.5
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• pp.648-658
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• 2022

Objective: The identification of nonlinear mixed models that describe the growth trajectory of New Zealand rabbits was performed based on weight records and carcass measures obtained using ultrasonography. Methods: Phenotypic records of body weight (BW) and loin eye area (LEA) were collected from 66 animals raised in a didactic-productive module of cuniculture located in the southern Piaui state, Brazil. The following nonlinear models were tested considering fixed parameters: Brody, Gompertz, Logistic, Richards, Meloun 1, modified Michaelis-Menten, Santana, and von Bertalanffy. The coefficient of determination (R²), mean squared error, percentage of convergence of each model (%C), mean absolute deviation of residuals, Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to determine the best model. The model that best described the growth trajectory for each trait was also used under the context of mixed models, considering two parameters that admit biological interpretation (A and k) with random effects. Results: The von Bertalanffy model was the best fitting model for BW according to the highest value of R² (0.98) and lowest values of AIC (6,675.30) and BIC (6,691.90). For LEA, the Logistic model was the most appropriate due to the results of R² (0.52), AIC (783.90), and BIC (798.40) obtained using this model. The absolute growth rates estimated using the von Bertalanffy and Logistic models for BW and LEA were 21.51g/d and 3.16 cm², respectively. The relative growth rates at the inflection point were 0.028 for BW (von Bertalanffy) and 0.014 for LEA (Logistic). Conclusion: The von Bertalanffy and Logistic models with random effect at the asymptotic weight are recommended for analysis of ponderal and carcass growth trajectories in New Zealand rabbits. The inclusion of random effects in the asymptotic weight and maturity rate improves the quality of fit in comparison to fixed models.

• Nutrition Research and Practice
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• v.16 no.5
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• pp.646-657
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• 2022

BACKGROUND/OBJECTIVES: The doubly labeled water (DLW) method is the gold standard for estimating total energy expenditure (TEE) and is also useful for verifying the validities of dietary evaluation tools. In this study, we compared the accuracy of total energy intakes (TEI) estimated by the 24-h diet recall method with TEE obtained using the doubly labeled water method. SUBJECTS/METHODS: This study involved 71 subjects aged 20-49 yrs. Over a 14-day period, three 24-h diet recalls per subject (2 weekdays and 1 weekend day) were used to estimate energy intakes, while TEE was measured using the DLW method. The paired t-test was used to determine the significance of differences between TEI and TEE results, and the accuracy of the 24-h recall method was determined by accuracy predictions percentage, root mean square error, and bias. RESULTS: Average study subject age was 33.4 ± 8.6 yrs. The association between TEI and TEE was positive and significant (r = 0.463, P < 0.001), and the difference between TEI (2,084.3 ± 684.2 kcal/day) and TEE (2,401.7 ± 480.3 kcal/day) was also significant (P < 0.001). In all study subjects, mean TEI was 12.0% (307.5 ± 629.3 kcal/day) less than mean TEE, and 12.2% (349.4 ± 632.5 kcal/day) less in men and 11.8% (266.7 ± 632.5 kcal/day) less in women. Rates of TEI underprediction for all study subjects, men, and women, were 60.5%, 51.4%, and 66.7%, respectively. CONCLUSIONS: This study shows that 24-h diet recall underreports energy intakes. More research is needed to corroborate our findings and evaluate the accuracy of 24-h recall with respect to additional demographics.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.363-370
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• 2022

In this paper, an estimation algorithm for state of charge (SOC) was applied using an equivalent circuit model (ECM) and an Extended Kalman Filter (EKF) to improve the estimation accuracy of the battery system states. In particular, an observer was designed to estimate SOC along with the aged capacity. In the case of the fresh battery, when SOC was estimated by Kalman Filter (KF), the mean absolute percentage error (MAPE) was 0.27% which was smaller than MAPE of 1.43% when the SOC was calculated by the model without the observer. In the driving mode of the vehicle, the general KF or EKF algorithm cannot be used to estimate both SOC and capacity. Considering that the battery aging does not occur in a short period of time, a strategy of periodically estimating the battery capacity during charging was proposed. In the charging mode, since the current is fixed at some intervals, a strategy for estimating the capacity along with the SOC in this situation was suggested. When the current was fixed, MAPE of SOC estimation was 0.54%, and the MAPE of capacity estimation was 2.24%. Since the current is fixed when charging, it is feasible to estimate the battery capacity and SOC simultaneously using the general EKF. This method can be used to periodically perform battery capacity correction when charging the battery. When driving, the SOC can be estimated using EKF with the corrected capacity.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• Education of Primary School Mathematics
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• v.27 no.3
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• pp.303-320
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• 2024

This study presents the development and performance evaluation of a custom GPT-based chatbot tailored to provide solutions following Polya's problem-solving stages. A beta version of the chatbot was initially deployed to assess its mathematical capabilities, followed by iterative error identification and correction, leading to the final version. The completed chatbot demonstrated an accuracy rate of approximately 89.0%, correctly solving an average of 57.8 out of 65 image-based problems from a 6th-grade elementary mathematics textbook, reflecting a 4 percentage point improvement over the beta version. For a subset of 50 problems, where images were not critical for problem resolution, the chatbot achieved an accuracy rate of approximately 91.0%, solving an average of 45.5 problems correctly. Predominant errors included problem recognition issues, particularly with complex or poorly recognizable images, along with concept confusion and comprehension errors. The custom chatbot exhibited superior mathematical performance compared to the general-purpose ChatGPT. Additionally, its solution process can be adapted to various grade levels, facilitating personalized student instruction. The ease of chatbot creation and customization underscores its potential for diverse applications in mathematics education, such as individualized teacher support and personalized student guidance.

• Journal of Korean Society of Forest Science
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• v.13 no.1
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• pp.79-84
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• 1971

This study is, by correlation and regression analysis, on the correlation between culm height and other growth factors which are circle at eye height and length of internode. The samples were come by in Tamyang district, To sum up, the results are as follows; 1. Two growth factors are much more correlative to culm height; both simple correlation and multiple correlation between the former and the latter are significant. ($r_{yx}=0.91$, $r_{yz}=0.78$, $r_{yx{\cdot}z}=0.84$, $r_{yz{\cdot}x}=0.55$, $R_{y{\cdot}xz}=0.94$) Seeing above significance, circle at eye height is more highly correlative than length of internode. 2. The following regression equation was derived from regression analysis. y= -0.687+0.335x+0.206z. y ; culm height. x ; circle at eye height. z ; length of internode. 3. By testing of the equation, regression coefficients are as follows; ${\beta}{\neq}O$, ${\gamma}{\neq}O$, ${\beta}{\neq}O{\neq}{\gamma}$ 4. The results tested the precision of the empirical formula, standard error of standard error by percentage are as follows. $Sy{\cdot}xz=0.89$, $Sy{\cdot}xz(%)=8.14$.

• The korean journal of orthodontics
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• v.32 no.5 s.94
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• pp.313-325
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• 2002

Three-dimensional CT imaging is efficient in examining specific structures in the craniofacial area by reproducing actual measurements through minimization of errors from patient movement and image magnification. Due to the rapid development of digital image technology and the expansion of treatment range a need for developing three -dimensional analysis has become urgent. Therefore the purpose of this study was to evaluate the percentage of error and magnification of three-dimensional CT using a dried skull and Vworks $program^{TM}$ (Cybermed Inc., Seoul, Korea) and also to obtain landmarks that are easy to designate and reproduce in three-dimensional images using the Vmorph-proto $program^{TM}$ (Cybermed Inc., Seoul, Korea). The following conclusions were obtained, 1. In the comparison of actual measurements from the dried skull and the three-dimensional image obtained from the Vworks program, the mean error was 0.99mm and the magnification was 1.04%. 2. Clinically useful hard tissue landmarks from three-dimensional images were Supraorbitale, Lateral orbital margin, Infraorbitale, Nasion, ANS, A point, Zygomaticomaxilla, Upper incisor, Lower incisor, B point, pogonion, Menton, PNS, Condylar inner margin, Condylar outer margin, Porion, Condylion, Gonionl, Gonion2, Gonion3, Sigmoid notch and Basion. 3. Clinically useful soft tissue landmarks from three-dimensional images were Endocanthion, Exocanthion, Soft tissue Nasion, Pronasale, Alare lateralis, Upper nostril point, Lower nostril point, Subnasale, Upper lip point, Cheilion, Stomion, Lower lip center, Soft tissue B, Pogonion, Menton and Preaurale. The Vworks program can be considered a clinically efficient tool to produce and measure three-dimensional images. Most of the hard and soft tissue landmarks proposed above are anatomically important points which are also easily reproducible and designated. These landmarks can be beneficial in three-dimensional diagnosis and the prediction of changes before and after surgery.

• Journal of the Korean Applied Science and Technology
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• v.36 no.3
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• pp.995-1007
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• 2019

The purpose of this study was to investigate the effects of 12-week elastic band exercise on body composition, blood lipids and AMPK in 24 elderly female volunteers aged 65-75 years, and they were divided into the combined exercise group(n=12) and the control group(n=12). The elastic band exercise method was to do exercise 3 times a week for 60 minutes per session, 1-4 weeks for low intensity of OMNI-RES 3-4, 5-8 weeks for medium intensity of OMNI-RES 5-6, 9-12 weeks for OMNI-RES 7-8 of high intensity. In order to compare the differences in the groups before and after the elastic band exercise, two-way repeated measures ANOVA was used to verify the interaction between group and time. The difference in the groups of the measured data was paired t-test, the difference between the groups was paired independent t-test, and analysis of covariance ANCOVA was performed to minimize the inter-group error. The statistical significance level of each item was set to .05. As a result, body fat percentage of exercise group significantly decreased (p<.05), and skeletal muscle volume was significantly increased (p<.01). TC, TG and LDL-C were not significantly different between the exercise and control groups, and HDL-C was significantly decreased in the control group (p<.05). AMPK was significantly decreased in the exercise group (p<.001), but there was no significant difference in the control group. According to the covariance analysis to minimize the error of difference between the pre-exercise groups (p<.05), there was significant difference in AMPK of groups after exercise. These results suggest that the 12-week elastic band exercise has a positive effect on the body composition and AMPK of the elderly women.