Improving hemoglobin estimation accuracy through standardizing of light-emitting diode power

Nowadays, hemoglobin monitoring is essential during surgeries, blood donations, and dialysis. Which are normally done using invasive methods. To monitor hemoglobin, a non-invasive hemoglobin meter was developed with five fixed light-emitting diode (LED) wavelengths at 670 nm, 770 nm, 810 nm, 850 nm, 950 nm and controlled using an Arduino Uno embedded development board. A photodetector with an on-chip trans-impedance amplifier was utilized to acquire the transmitted signal through the finger using the photoplethysmography (PPG) principle. Before the standardization of LED power, we had tested the designed system on fifteen subjects for the five wavelengths and estimated the hemoglobin with an accuracy of 96.51% and root mean square error (RMSE) of 0.57 gm/dL. To further improve the accuracy, the LED power was standardized and the PPG signal was reacquired on the same subjects. With this, the accuracy improved to 98.29% and also reduced the RMSE to 0.36 gm/dL. The designed system with LED power standardization showed a good agreement with pathology results with the coefficient of determination R²=0.981. Also, Bland–Altman analysis was used to evaluate the designed system and it showed good agreement between the two measurements.

Pengaruh Budaya Organisasi dan Motivasi Intrinsik terhadap Komitmen Afektif dengan Kepuasan Kerja sebagai Variabel Pemediasi pada Karyawan Dinas Koperasi dan UKM Kabupaten Sleman

This study aims to examine the effect of organizational culture and intrinsic motivation on affective commitment. This study also aims to examine whether job satisfaction acts as a mediating variable on the influence of organizational culture and intrinsic motivation on affective commitment to the employees of the Cooperatives and SMEs Service Office of Sleman Regency. This study uses the Associative method with a quantitative approach. The population in this study were all employees of the Department of Cooperatives and SMEs in Sleman Regency, with a sample of 45 employees. The sampling technique used saturated sampling with data collection using a questionnaire. The data analysis technique in this study used multiple linear regression, Sobel test, coefficient of determination, and standard beta. This study resulted in the findings that organizational culture has an effect on job satisfaction, and intrinsic motivation has an effect on job satisfaction. Likewise, organizational culture influences affective commitment. However, intrinsic motivation has no effect on affective commitment. Other findings show that job satisfaction has an effect on affective commitment. This study also produces findings that job satisfaction mediates the effect of organizational culture on affective commitment, and job satisfaction also mediates the effect of intrinsic motivation on affective commitment. Keywords: organizational culture, intrinsic motivation, job satisfaction, affective commitment.

Modeling Carbon Release of Brazilian Highest Economic Pole and Major Urban Emitter: Comparing Classical Methods and Artificial Neural Networks

Despite the concern about climate change and the associated negative impacts, fossil fuels continue to prevail in the global energy consumption. This paper aimed to propose the first model that relates CO2 emissions of Sao Paulo, the main urban center emitter in Brazil, with gross national product and energy consumption. Thus, we investigated the accuracy of three different methods: multivariate linear regression, elastic-net regression, and multilayer perceptron artificial neural networks. Comparing the results, we clearly demonstrated the superiority of artificial neural networks when compared with the other models. They presented better results of mean absolute percentage error (MAPE = 0.76%) and the highest possible coefficient of determination (R2 = 1.00). This investigation provides an innovative integrated climate-economic approach for the accurate prediction of carbon emissions. Therefore, it can be considered as a potential valuable decision-support tool for policymakers to design and implement effective environmental policies.

Pengaruh Profitabilitas, Likuiditas, Leverage, dan Ukuran Perusahaan terhadap Kebijakan Dividen

This study is intended to determine the effect of the independent variable (X), namely: Profitability, Liquidity, Leverage, and Company Size on Dividend Policy in the study of companies in the Consumer Goods Industry sector. The research method in this test uses quantitative descriptive and the data used is secondary data from official sources. The population in this study were all companies in the Consumer Goods Industry sector, totaling 60 companies. The sampling technique in this study was using purposive sampling by taking into account certain conditions that had been agreed upon so that the authors decided to use 10 companies as samples in this test. The data obtained with the observation time of 5 years is 50 data. The source of data in this study is secondary data. Test the quality of the data using Descriptive Analysis Techniques, Classical Assumption Test, and Multiple Linear Analysis. The data analysis technique in this test uses the t statistic test, f statistic test, and the coefficient of determination (Adjust R2). The partial test results in this test show that profitability and liquidity have a positive effect on Dividend Policy, while Leverage and Firm Size have a negative effect on Dividend Policy. Simultaneous test results show that the free factors of Profitability, Liquidity, Leverage, and Company Size also have a positive and significant effect on Dividend Policy in the Consumer Goods Industry sector on the IDX for the 2016-2020 period. Keywords: Profitability, Liquidity, Leverage, Firm Size, Dividend Policy

Quantitative Literacy and Reasoning of Freshman Students with Different Senior High School Academic Background Pursuing STEM-Related Programs

<p style="text-align: justify;">This paper investigates the quantitative literacy and reasoning (QLR) of freshmen students pursuing a Science, Technology, Engineering, and Mathematics (STEM)–related degree but do not necessarily have a Senior High School (SHS) STEM background. QLR is described as a multi-faceted skill focused on the application of Mathematics and Statistics rather than just a mere mastery of the content domains of these fields. This article compares the QLR performance between STEM and non-STEM SHS graduates. Further, this quantitative-correlational study involves 255 freshman students, of which 115 have non-STEM academic background from the SHS. Results reveal that students with a SHS STEM background had significantly higher QLR performance. Nevertheless, this difference does not cloud the fact that their overall QLR performance marks the lowest when compared to results of similar studies. This paper also shows whether achievement in SHS courses such as General Mathematics, and Statistics and Probability are significant predictors of QLR. Multivariate regression analysis discloses that achievement in the latter significantly relates to QLR. However, the low coefficient of determination (10.30%) suggests that achievement in these courses alone does not account to the students’ QLR. As supported by a deeper investigation of the students’ answers, it is concluded that QLR indeed involves complex processes and is more than just being proficient in Mathematics and Statistics.</p>

Self Awareness and Mitigation of Learning Loss on Students' Science Learning Outcomes During the Covid 19 Pandemic

This study aimed to analyze the correlation between self-awareness, mitigating learning loss, and student science learning outcomes during the COVID-19 pandemic. Data was collected using a correlational study, a questionnaire, and data analysis using linear regression using the SPSS 16.00 application. The analysis results found that the correlation value or R correlation between self-awareness and learning outcomes was 0.020. The coefficient of determination (R2) was 0.000. In contrast, the regression between learning loss and learning outcomes was R, which was -0.073, the coefficient of determination (R2) was 0.005. The self-awareness regression coefficient on the correlation between self-awareness and learning outcomes is 0.018 or only 0.02%, so the equation becomes Y = 83,287 + 0.018X. In the correlation between self-awareness and learning outcomes, the regression coefficient of learning loss is -.119 or only <0, so the regression equation formed is Y = 94.480 -.199X. Therefore, it can be concluded that self-awareness has no correlation with students' cognitive learning outcomes, and there is no correlation between learning loss mitigation and student learning outcomes during the COVID-19 pandemic

Correlation Self-Efficacy and Adversity Quotient of Students at SMK Muhammadiyah 2 Wedi Klaten

This study aims to determine whether there is a correlation between self-efficacy and adversity quotient for students of SMK Muhammadiyah 2 Wedi Klaten. This type of research uses quantitative research methods with a correlational approach. Sampling methods using simple random sampling with data collection techniques in the form of a scale. The research subjects were 70 students from class XI of SMK Muhammadiyah 2 Wedi, Klaten. The results obtained correlation analysis (rxy) of 0.708 with a p-value 0.000 that is lower than 0.05, meaning that there is a significant positive correlation between self-efficacy and the student's adversity quotient. This can indicate that the higher the student's self-efficacy, higher the adversity quotient of the student, then Ho is rejected and Ha is accepted. Self efficacy and adversity quotient in students of SMK Muhammadiyah 2 Wedi, Klaten are classified as moderate. The coefficient of determination (R2) of the correlation is 0.724, meaning that self-efficacy contributes effectively to the adversity quotient by 72%, which means there are 28% of the other factors that affect students adversity quotient

The Effect of Price, Land Area and Production Costs on Rice Farmer’s Income: Case in Bone Bolango Regency

This study aims to determine the effect of price, land area and production costs on the income of rice farmers in North Toto Village, Tilongkabila District, Bone Bolango Regency. Data collection techniques used in this study were observation, interviews, questionnaires, and documentation. With a total sample of 44 farmers in North Toto Village. This research method uses a quantitative approach with multiple linear regression model analysis. The results showed that the price had a negative and insignificant effect on the income of rice farmers in North Toto Village. This means that every 1% increase in price can reduce income by 0.237. Land area has a positive and significant effect on the income of rice farmers in North Toto Village. This means that every 1% increase in land area can increase income by 0.682. Production costs have a negative and significant effect on the income of rice farmers in North Toto Village. This means that every 1% increase can reduce income by -0.254. The coefficient of determination (R Square) is 0.596, this shows that the percentage of rice farmers' income variation which is explained by the variation of the independent variables, namely price, land area and production costs is 59.6% for the remaining 40.4% influenced by other variables.

Uncertainty Analysis and Experimental Validation of Identifying the Governing Equation of an Oscillator Using Sparse Regression

In recent years, the rapid growth of computing technology has enabled identifying mathematical models for vibration systems using measurement data instead of domain knowledge. Within this category, the method Sparse Identification of Nonlinear Dynamical Systems (SINDy) shows potential for interpretable identification. Therefore, in this work, a procedure of system identification based on the SINDy framework is developed and validated on a single-mass oscillator. To estimate the parameters in the SINDy model, two sparse regression methods are discussed. Compared with the Least Squares method with Sequential Threshold (LSST), which is the original estimation method from SINDy, the Least Squares method Post-LASSO (LSPL) shows better performance in numerical Monte Carlo Simulations (MCSs) of a single-mass oscillator in terms of sparseness, convergence, identified eigenfrequency, and coefficient of determination. Furthermore, the developed method SINDy-LSPL was successfully implemented with real measurement data of a single-mass oscillator with known theoretical parameters. The identified parameters using a sweep signal as excitation are more consistent and accurate than those identified using impulse excitation. In both cases, there exists a dependency of the identified parameter on the excitation amplitude that should be investigated in further research.

Technological Potential of Saratov Spring Durum Wheat Grain

Introduction. Durum wheat is vital for high-quality pasta production. The present research tested the high technological potential of durum wheat varieties developed in the Saratov region. The research objective was to study the effect of the quality of durum wheat on the quality of pasta. Study objects and methods. The study featured durum wheat of the following varieties: Saratovskaya Zolotistaya, Valentina, Nik, Krasnokutka 13, Luch 25, Pamyati Vasilchuka, Bezenchukskaya 182 and Annushka. The experiment involved an original PSL-13 press for standard spaghetti with a diameter of 1.8 mm. The content of protein, raw gluten, and their quality were determined by standard methods. The cooking properties of the pasta were evaluated according to the method developed in the South-Eastern Federal Agricultural Research Center. Results and discussion. The indicators of raw gluten and protein are known to correlate. The samples of Saratovskaya Zolotistaya and Luch 25 had a high protein content of 15.3 and 15.6%, respectively, as well as a high content of raw gluten (33.2 and 35.1%, respectively). The raw gluten of Saratov varieties proved to be much better than in the control samples. The indicator of microSDs sedimentation was 30–36 mm. The strength of spaghetti followed the increase in crude gluten (33–35%) and protein (15.3–15.6%), which is typical of this type of pasta. The strength, coefficient of determination (R2 = 0.98), and sharing force (R2 = 0.92) depended on the protein content. Conclusion. The study established the following optimal selection criteria for durum wheat varieties to be used in strong spaghetti production: virtuosity – 80%, raw gluten – 33–35%, protein content – 5–7% higher than normal, raw gluten – 72–80 units.