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Yoga Devaera,Danny Maesadatu Syaharutsa,Herwasto Kuncoroyakti Jatmiko,Damayanti Rusli Sjarif 대한소아소화기영양학회 2018 Pediatric gastroenterology, hepatology & nutrition Vol.21 No.4
Purpose: This study set out to evaluate the compliance to, and efficacy of oral supplementation, using a 1.5 kcal/mL or 1 kcal/mL sip feed, in children with mild to moderate malnutrition. Methods: This was a parallel, randomized, controlled open-label trial in children aged 3 to 6 years with a weight for height Z (WHZ) score <−1 and ≥−3, who were randomized to receive a total of 600 kcal/day from either a 1.5 kcal/mL or a 1.0 kcal/mL pediatric sip feed for 28 days. Assessments included daily study product intake, body weight, tolerance and dietary intake from solid food.Results: Of 110 children recruited, 98 (mean±standard deviation of age 49±7 months) completed the study. Both sip feeds were well tolerated, with high compliance (80±24% and 81±22% of prescribed volume in 1.5 kcal/mL and 1.0 kcal/mL groups respectively, p=0.79). Both study groups gained similar weight during the 28 days intervention period (0.42±0.40 kg in 1.5 kcal/mL group vs. 0.49±0.49 kg in 1.0 kcal/mL group, p=0.43). There were no significant differences between the groups in weight gain and in the change in WHZ score over the intervention period. Dietary analysis at the end of the study did not show replacement of solid food by the oral nutritional supplements.Conclusion: In children with mild to moderate malnutrition, both 1.5 kcal/mL and 1 kcal/mL pediatric sip feeds had high compliance and were well tolerated, and were equally effective in promoting weight gain in the 28 days study period.
Devaera, Yoga,Syaharutsa, Danny Maesadatu,Jatmiko, Herwasto Kuncoroyakti,Sjarif, Damayanti Rusli The Korean Society of Pediatric Gastroenterology 2018 Pediatric gastroenterology, hepatology & nutrition Vol.21 No.4
Purpose: This study set out to evaluate the compliance to, and efficacy of oral supplementation, using a 1.5 kcal/mL or 1 kcal/mL sip feed, in children with mild to moderate malnutrition. Methods: This was a parallel, randomized, controlled open-label trial in children aged 3 to 6 years with a weight for height Z (WHZ) score <-1 and ${\geq}-3$, who were randomized to receive a total of 600 kcal/day from either a 1.5 kcal/mL or a 1.0 kcal/mL pediatric sip feed for 28 days. Assessments included daily study product intake, body weight, tolerance and dietary intake from solid food. Results: Of 110 children recruited, 98 ($mean{\pm}standard$ deviation of age $49{\pm}7months$) completed the study. Both sip feeds were well tolerated, with high compliance ($80{\pm}24%$ and $81{\pm}22%$ of prescribed volume in 1.5 kcal/mL and 1.0 kcal/mL groups respectively, p=0.79). Both study groups gained similar weight during the 28 days intervention period ($0.42{\pm}0.40kg$ in 1.5 kcal/mL group vs. $0.49{\pm}0.49kg$ in 1.0 kcal/mL group, p=0.43). There were no significant differences between the groups in weight gain and in the change in WHZ score over the intervention period. Dietary analysis at the end of the study did not show replacement of solid food by the oral nutritional supplements. Conclusion: In children with mild to moderate malnutrition, both 1.5 kcal/mL and 1 kcal/mL pediatric sip feeds had high compliance and were well tolerated, and were equally effective in promoting weight gain in the 28 days study period.
Tax Avoidance and the Readability of Financial Statements: Empirical Evidence from Indonesiaf
Bima Yoga PRATAMA,Niluh Putu Dian Rosalina Handayani NARSA,Kadek Pranetha PRANANJAYA 한국유통과학회 2022 The Journal of Asian Finance, Economics and Busine Vol.9 No.2
This study aims to obtain empirical evidence regarding the link between tax avoidance (TA) and the readability of financial statements. This is a quantitative research using Ordinary Least Squares regression analysis which is then processed using STATA 14.0. A total of 278 companies listed on the Indonesia Stock Exchange during the period 2017–2019 is the data of this study. In detecting TA in a company, this study uses the ETR and CashETR and for the measurement of financial statement readability, this study uses gunning fog index and length of the document. The findings of this study suggest that tax avoidance and clear financial statements are mutually exclusive in the sense that when tax avoidance is practiced, companies will tend to conceal the information conveyed by financial statements. In other words, it is concluded that the more a company engages in tax avoidance, the lower the readability of the company’s financial statements. This study provides in-depth evidence that tax avoidance is indirectly related to the disclosure of information by the company. Users of financial statements will realize that the company seeks to make disclosures that are in their best interests to avoid their tax avoidance strategy being detected.
Ridho Hendra Yoga Perdana(리드호 헨드라 요가 페르다나),Beongku An(안병구) 한국통신학회 2022 한국통신학회 학술대회논문집 Vol.2022 No.2
This paper studies the deep learning-based joint power allocation and phase shift in multiuser multi-intelligent reflecting surface (IRS)-aided massive MIMO systems. The signal-to-noise-plus noise ratio is formulated to determine the spectral efficiency problem. Particularly, we design a deep neural network (DNN) to learn the relation between the position of every user within cell with the optimal power allocation and phase shift policies. The simulation results show that the suggested idea achieves good performance in predict the power allocation and phase shift with accuracy 97% compared to the conventional method while it reduces the computation complexity.
Ridho Hendra Yoga Perdana,Toan-Van Nguyen,Beongku An 한국통신학회 2023 ICT Express Vol.9 No.2
In this paper, we propose a deep learning approach for solving power allocation problems in massive MIMO networks. We use signal-to-interference-plus-noise-ratio (SINR) and signal-to-leak-plus-noise ratio (SLNR) criteria for linear precoder design to define the max–min and max-prod power allocation challenges. The power allocation process to each user equipment in the base station coverage takes a long time and is inefficient, hence numerous base stations are deployed to serve multiple user equipments. As a result, we develop a deep neural network (DNN) framework in which the user’s equipment position is utilized to train the deep model, which is then used to forecast the ideal power distribution depending on the user’s location. Compared to the traditional optimization approach, the DNN design helps to obtain the optimal solution of the power allocation problem within a short time via a quick-inference process. Simulation results show that the SINR criterion outperforms the SLNR one. Meanwhile, deep learning achieves excellent results in forecasting power allocation with an accuracy of 85% for the max–min strategy and 99% for the max-product approach.
Convolutional Neural Network-Based Metal Surface Defect Detection
Ida Bagus Krishna Yoga Utama,Yeong Min Jang 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.6
The visual inspection using computer vision technology is growing rapidly nowadays. The number of industries that relies on automatic defect detection is rising due to some limitations when doing defect detection manually by a worker. The automatic defect detection also benefits the industry because it will help increase the quality control of production line and in the end it helps to maintain the product quality. A convolutional neural network is developed in order to classify six types of defect on metal surface. The result is promising, the developed model able to recognize 95.8% of testing data correctly.