• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4664-4681
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• 2020

Modulation recognition (MR) plays a key role in cognitive radar, cognitive radio, and some other civilian and military fields. While existing methods can identify the signal modulation type by extracting the signal characteristics, the quality of feature extraction has a serious impact on the recognition results. In this paper, an end-to-end MR method based on long short-term memory (LSTM) and the gated recurrent unit (GRU) is put forward, which can directly predict the modulation type from a sampled signal. Additionally, the sliding window method is applied to fast-changing mixed-modulation signals for which the signal modulation type changes over time. The recognition accuracy on training datasets in different SNR ranges and the proportion of each modulation method in misclassified samples are analyzed, and it is found to be reasonable to select the evenly-distributed and full range of SNR data as the training data. With the improvement of the SNR, the recognition accuracy increases rapidly. When the length of the training dataset increases, the neural network recognition effect is better. The loss function value of the neural network decreases with the increase of the training dataset length, and then tends to be stable. Moreover, when the fast-changing period is less than 20ms, the error rate is as high as 50%. As the fast-changing period is increased to 30ms, the error rates of the GRU and LSTM neural networks are less than 5%.

• The Journal of the Korean dental association
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• v.9 no.4
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• pp.157-160
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• 1971

To compare the effects of various pulp capping agents that are usually applied to human pulp tissue, adult dogs were bred for a certain period and each capping agent was applied experimentally to pulp tissue after vital pulpotomy. Histological observations are as follows. 1) In comparison between methods of vital pulpotomy, one and two appointment method, different courses of healing were observed. In one appointment method, the granulation tissue formation at the amputation sur face of pulp tissue had a tendency to be transformed to scar tissue formation. In two appointment method, more transformation than that of one appointment method from scar tissue to dentin matrix formation were observed. 2) Histologic changes that have appeared in pulp tissue are a) fixation at outer layer b) degeneration at middle layer c) hyperemia and round cell infiltration at inner layer 3) With use of formocresol mixed zinc oxide powder in two appointment method complete formation of dentin matrix were observed. 4) Among the methods and aagents described above formocresol mixed zinc oxide powder in two appointment method appeared to be relatively effective.

• Journal of Distribution Science
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• v.18 no.9
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• pp.19-30
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• 2020

Purpose: As an environmental concern increases, customers pay more attention to purchase organic food. While customers' purchase intention of organic food has been widely studied, there are lacks of researches regarding the moderation effect of environmental concern and the interactive effect of level of education based on the Theory of Planned Behavior (TPB). This study examines the influence of level of education and environmental concern on purchase intention based on the Theory of Planned Behavior and organic food in Vietnam. Research design, data and methodology: The methodology of mixed methods of qualitative and quantitative is applied with a survey of 420 customers being conducted to collect data from three biggest cities in Vietnam: Ho Chi Minh, DaNang and Hanoi. SPSS 23 and SMART-PLS 3.2 are used for data analysis. Results: The result shows that the customers have more environmental concern which increases their attitude to the intention of purchasing organic food. Moreover, there has not the three-way interactive effect of level of education, environmental concern and attitude on purchase intention toward organic food. Conclusions: This enriches the existing literature with the moderation of environmental concern to the relationship between attitude and purchase intention toward organic food in Vietnam based on the Theory of Planned Behavior.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.111-128
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• 2018

About 3.9 million apps and 24 primary categories can be approved on Apple iTunes Store. Making accurate categorization can potentially receive many benefits for developers, app stores, and users, such as improving discoverability and receiving long-term revenue. However, current categorization problems may cause usage inefficiency and confusion, especially for cross-attribution, etc. This study focused on evaluating the reliability of app categorization on Apple iTunes Store by using several rounds of inter-rater reliability statistics, locating categorization problems based on Machine Learning, and making more accurate suggestions about representative functionality stems for each primary category. A mixed methods research was performed and total 4905 popular apps were observed. The original categorization was proved to be substantial reliable but need further improvement. The representative functionality stems for each category were identified. This paper may provide some fusion research experience and methodological suggestions in categorization research field and improve app store's categorization in discoverability.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.3887-3895
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• 2016

Background: In order to increase breast and cervical cancer screening uptake in Singapore, women's perceived barriers to screening need to be identified and overcome. Using data from both focus groups and surveys, we aimed to assess perceived barriers and motivations for breast and cervical cancer screening. Materials and Methods: We conducted 8 focus groups with 64 women, using thematic analysis to identify overarching themes related to women's attitudes towards screening. Based on recurring themes from focus groups, several hypotheses regarding potential barriers and motivations to screen were generated and tested through a national survey of 801 women aged 25-64. Results: Focus group participants had misconceptions related to screening, believing that the procedures were painful. Cost was an issue, as well as efficacy and fatalism. Conclusions: By identifying barriers to and motivators for screening through a mixed-method design that has both nuance and external validity, this study offers valuable suggestions to policymakers to improve breast and cervical cancer screening uptake in Singapore.

• Child Health Nursing Research
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• v.22 no.2
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• pp.79-86
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• 2016

Purpose: The purpose of this study was to identify breastfeeding practice with late preterm infants (LPIs), and to determine predictors of exclusive breastfeeding at the 12th week after discharge. Methods: The participants were 106 mothers of LPIs hospitalized in neonatal intensive care units at two university hospitals. Data were collected between February and October, 2013. Questionnaires included characteristics of LPIs, their mothers, and feeding-related characteristics. Feeding methods were exclusive breastfeeding, mixed feeding, and formula feeding. Results: Exclusive breastfeeding steadily increased from 5.7% at the 1st week to 19.8% at the 12th week, as did formula feeding from 27.3% to 67.9%. Contrarily, mixed feeding decreased from 67.0% at the 1st week to 12.3% at the 12th week. The ratio of formula feeding was higher than that of exclusive breastfeeding over time. Predictors for exclusive breastfeeding were the following: type of delivery (OR=2.96, 95%CI=1.07-8.14), feeding intolerance (OR=3.03, 95%CI=1.26-7.25) and feeding method during hospitalization (OR=7.84, 95%CI=3.15-19.53). Conclusion: In order to increase breastfeeding opportunities for LPIs, educational programs for gestational age-appropriate breastfeeding should be developed. The focus of breastfeeding education needs to be on mothers who delivered their LPIs through Cesarean-section and LPIs who had feeding intolerance or were fed only formula during hospitalization.

• Journal of Biosystems Engineering
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• v.42 no.3
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• pp.155-162
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• 2017

Purpose: The objective of this study was to evaluate the biogas productivity of agricultural by-products (ABPs) based on their proximate composition. Specifically, the effects of proximate composition were investigated, and a new mixing method was developed using various ABPs that are difficult to digest for biogas production. Methods: Experiments were conducted to compare the biogas productivity between a single ABP and a mixture of ABPs that had the same proximate composition as the single ABP. To match the proximate compositions of radish waste and corn distiller's dried grains with solubles (DDGS), mixed ABPs were made from various ABPs. Biogas potential tests (BMP tests) were performed at an organic loading rate (OLR) of 2.5 g VS/L and a feed to microorganism ratio (F/M) of 0.5 under the mesophilic condition. Results: The individual ABPs (radish and corn DDGS) and the mixed ABPs (cabbage waste with skim milk waste, bean-curd waste with skim milk waste, and some others) produced similar amounts of biogas. Conclusions: The new mixing method based on proximate composition can be applied to other ABPs and organic wastes from factories and municipal waste treatment plants to develop renewable energy and effective waste treatment methods.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.1-15
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• 2022

Combining the strength of both Mixed Data Sampling (MIDAS) Regression and realized variance measures, this paper seeks to investigate two objectives: (1) evaluate the post-sample performance of the proposed weekly Realized Variance-MIDAS (RVar-MIDAS) in one-week ahead volatility forecasting against the established Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and the less explored but robust STES (Smooth Transition Exponential Smoothing) methods. (2) comparing forecast error performance between realized variance and squared residuals measures as a proxy for actual volatility. Data of seven private equity mutual fund indices (generated from 57 individual funds) from two different time periods (with and without financial crisis) are applied to 21 models. Robustness of the post-sample volatility forecasting of all models is validated by the Model Confidence Set (MCS) Procedures and revealed: (1) The weekly RVar-MIDAS model emerged as the best model, outperformed the robust DAILY-STES methods, and the weekly DAILY-GARCH models, particularly during a volatile period. (2) models with realized variance measured in estimation and as a proxy for actual volatility outperformed those using squared residual. This study contributes an empirical approach to one-week ahead volatility forecasting of mutual funds return, which is less explored in past literature on financial volatility forecasting compared to stocks volatility.

• Communications for Statistical Applications and Methods
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• v.31 no.5
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• pp.535-556
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• 2024

Measuring stock market volatility and its determinants is critical for stock market participants, as volatility spillover effects affect corporate performance. This study adopted a novel approach to analysing and implementing GARCH-MIDAS modelling methods. The classical GARCH as a benchmark and the univariate GARCH-MIDAS framework are the GARCH family models whose forecasting outcomes are examined. The outcome of GARCH-MIDAS analyses suggests that inflation, interest rate, exchange rate, and oil price are significant determinants of the volatility of the Johannesburg Stock Market All Share Index. While for Nigeria, the volatility reacts significantly to the exchange rate and oil price. Furthermore, inflation, exchange rate, interest rate, and oil price significantly influence Ghanaian equity volatility, especially for the long-term volatility component. The significant shock of the oil price and exchange rate to volatility is present in all three markets using the generalized autoregressive conditional heteroscedastic-mixed data sampling (GARCH-MIDAS) framework. The GARCH-MIDAS, with a powerful fusion of the GARCH model's volatility-capturing capabilities and the MIDAS approach's ability to handle mixed-frequency data, predicts the volatility for all variables better than the traditional GARCH framework. Incorporating these two techniques provides an innovative and comprehensive approach to modelling stock returns, making it an extremely useful tool for researchers, financial analysts, and investors.

• Journal of Information Science Theory and Practice
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• v.11 no.3
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• pp.79-91
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• 2023

The storage of data documentation for Myanmar pagodas has various issues, and its retrieval method causes problems for users and libraries. This study utilized a mixed-methods approach, combining qualitative and quantitative methods to investigate pagoda data management in Myanmar libraries. The study aims to achieve the following objectives: to study the library collection management of pagodas in Myanmar, to investigate the management of pagoda data in Myanmar libraries, and to identify the pagoda data requirements for metadata development from the library professional perspective. The study findings revealed several challenges facing librarians and library users in accessing and managing Myanmar pagoda data, including limited stocks and retrieval tools, difficulty in accessing all available data online, and a lack of a centralized database or repository for storing and retrieving pagoda data. The study recommends the establishment of metadata criteria for managing a set of pagoda data and improving access to technology to address these challenges.