• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.205-214
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• 2019

This paper aims to discover factors and their influences degree to repurchase organic cosmetic in Vietnam. In addition, this research also discloses the main segments that have high demand re-buying intention based on demographic groups of gender, age, income, educational level, job, type of products, and place of production. Twenty-eight scale was designed based on previous studies and adjusted to match the 5-point Likert scale to conduct measurement. By using survey method to test hypotheses and set up conceptual models to collect 295 Vietnamese consumers who have experience in consuming organic cosmetic by explain the results through Smart PLS software. The findings show that there is positive attitude of customers to the intention of acquiring organic cosmetics, green perceived and customer satisfaction. In addition, customer satisfaction, knowledge of products, safety values, and environmental protection consciousness also play important roles to form a positive attitude of customers for products. Moreover, the consciousness of green living of consumers accounts for a high proportion in creating customer satisfaction for organic products. The results show useful information for current premises to determine the factors that influence the decision to repurchase organic cosmetic product, that provide business strategies.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.1025-1034
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• 2020

This paper aims to develop a conceptual framework for Green Supply Chain Management (GSCM) that takes into account the effect of GSCM drivers on implementing GSCM practices in Vietnam FDI companies. This study has considered organizational commitment, social network, and government support as GSCM driver factors and proposed a structural model of the relationships between GSCM drivers and GSCM practices in Vietnam FDI companies. The empirical analysis used data from 192 questionnaires which used a comprehensive, valid, and reliable tool (SPSS 26 and SmartPLS 3.0 software) to evaluate rigorous statistical tests including convergence validity, discriminatory validity, reliability, and Average Variance Extracted (AVE) to analyze and verify the gathered data and develop the hypothesis. The result of path analysis shows that GSCM driver factors constitute a structured system with different degrees of influence on GSCM drivers and GSCM practices. Organizational commitment and government support has a positive relationship with both GSCM drivers and GSCM practices, while social network only has a positive relationship on GSCM drivers. As a result, the testing of the relationship between GSCM drivers and GSCM practices has been verified and supported. The findings of this study can help managers and decision-makers to push the implementation of GSCM practices in FDI companies.

• Journal of Energy Engineering
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• v.26 no.1
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• pp.54-61
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• 2017

In general, solid waste arises from lots of human activities such as domestic, agricultural, industrial, commercial, waste water treatment, construction, and mining activities etc. If the waste is not properly disposal and treated, it will have a negative impact to the environment, and hygienic conditions in urban areas and pollute the air with greenhouse gases (GHG), ground water, as well as the soil and crops. In this paper, the Carbon Resources Recycling Appropriate Technology Center feasibility studies are reported at Bantayan Island, Philippines on the municipal solid waste management. The present objective of our study is to characterize the municipal solid waste incineration (MSWI) bottom ash and case study of MSWI production status in Bantayan, Philippines. Currently, wide variety of smart technologies available for MSWI management in developed countries. Recycling is the other major alternative process for MSWI landfill issues. In this paper, the feasibility studies of applied appropriate technologies for the municipal solid waste generation in Bantayan Island, Philippines are reported.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.41-50
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• 2021

The purpose of this study is to analyze various energy platforms using data in the US and to suggest directions and implications. Some of the leading energy platforms are selected and analyzed based on the opening platform model. We focus on the case analysis of the US utility companies. In case of the horizontal open platform, Green Button sponsor's 'Connect My Data (CMD)' driven by the government invites the utility companies to jointly develop the sponsor's data solution. In case of the vertical open platform, the certification program 'Share My Data (SMD)' allows backward compatibility, because the technical improvement is minimal. The utility companies benchmark Amazon's three-sided market mediation and prefer platform and category exclusivity. For the former, they have data analytics companies like Enervee, Opower and for the latter, they have electronics manufactures and energy service providers (ESPs) like Distributed Energy Resources (DERs). Based on this US case study, we suggest the energy platforms to open their platform for renewable energy supply, energy conservation, high-efficiency products, and residential DER dissemination. To successfully implement the government's energy transition policy, the US platforms should be benchmarked as a business model. Especially, it is needed for them to coordinate a platform ecosystem. To ensure trust in the products and services offered on the marketplace platform, platform's certification program is helpful.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.59-67
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• 2020

In this study, a suitable algorithm for each BRT stop type is presented through the network construction and algorithm design effect analysis through the LISA, a traffic signal program, for the BRT stop type in the BRT Design Guidelines, Ministry of Land, Transport and Maritime Affairs, 2010.6. It was. The phase insert technique is the most effective method for the stop before passing the intersection, the early green technique for the stop after the intersection, and the extend green technique for the mid-block type stop. The extension green technique is used only because it consists of BRT vehicles, general vehicles and pedestrians. Analyzed. After passing through the intersection, the stop was analyzed as 56.4 seconds for the total crossing time and 29.8 seconds for the delay time. In the mid-block type stop, the total travel time of the intersection was 40.5 seconds, the delay time was 9.6 seconds, the average travel time of up and down BRT was 70.2 seconds, the delay time was 14.0 seconds, and the number of passages was 29.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.4
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• pp.15-31
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• 2022

The Green Purification Unit System (GPUS) is a green infrastructure facility applicable to the roadside to reduce particulate matter from road traffic. This study introduces two types of GPUS (type1 and type2) and assesses the performance and maintenance costs of each of them. The GPUS's performance analysis used the data collected in November 2021 after the installation of the GPUS type1 and type2 at the study site in Suwon. The changes in the particulate matter concentration near the GPUS were measured. The maintenance cost of GPUS type1 and type2 was assessed by calculating the initial installation cost and the management and repair cost after installation. The results of the performance analysis showed that the GPUS type1, which was manufactured by combining plants and electric dust collectors, had a superior particulate matter reduction performance. In particular, type1 produced a greater effect of particulate matter reduction in the time with a high concentration (50㎍/m³ or higher) of particulate matter due to the operation of electric dust collectors. GPUS type2, which was designed in the form of a plant wall without applying an electric dust collector, showed lower reduction performance than type1 but showed sufficiently improved performance compared to the existing band green area. Meanwhile, the GPUS type1 had three times higher costs for the initial installation than GPUS type2. In terms of costs for managing and repairing, it was evaluated that type1 would be slightly more costly than type2. Finally, this study discussed the applicability of two types of GPUS based on the result of the analysis of their particulate matter performance and maintenance cost at the same time. Since GPUS type2 has a cheaper cost than type1, it could be more economical. However, in the area suffering a high concentration of particulate matter, GPUS type1 would be more effective than type2. Therefore, the choice of GPUS types should rely on the status of particulate matter concentration in the area where GPUS is being installed.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.4
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• pp.87-96
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• 2021

Determining design rainfall is the first step to plan an agricultural drainage facility. The objective of this study is to evaluate whether the current method for parameter estimation is reasonable for computing the design rainfall. The current Gumbel-Kendall (G-K) method was compared with two other methods which are Gumbel-Chow (G-C) method and Probability weighted moment (PWM). Hourly rainfall data were acquired from the 60 ASOS (Automated Synoptic Observing System) stations across the nation. For the goodness-of-fit test, this study used chi-squared (𝛘²) and Kolmogorov-Smirnov (K-S) test. When using G-K method, 𝛘² statistics of 18 stations exceeded the critical value (𝑥²_a=0.05,df=4=9.4877) and 10, 3 stations for G-C method, PWM method respectively. For K-S test, none of the stations exceeded the critical value (D^a=0.05_n=0.19838). However, G-K method showed the worst performances in both tests compared to other methods. Subsequently, this study computed design rainfall of 48-hour duration in 60 ASOS stations. G-K method showed 5.6 and 6.4% higher average design rainfall and 15.2 and 24.6% higher variance compared to G-C and PWM methods. In short, G-K showed the worst performance in goodness-of-fit tests and showed higher design rainfall with the least robustness. Likewise, considering the basic assumptions of the design rainfall estimation, G-K is not an appropriate method for the practical use. This study can be referenced and helpful when revising the agricultural drainage standards.

• Tribology and Lubricants
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• v.24 no.3
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• pp.111-121
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• 2008

An integrated in-line oil monitoring detector assigned for continuous in situ monitoring multiple parameters of oil performance for predicting economically optimal oil change intervals and equipment condition control is presented in this study. The detector estimates oil deterioration based on the information about chemical degradation, total contamination, water content of oil and oil temperature. The oil oxidation is estimated by "chromatic ratio", total contamination is measured by the changes in optical intensity of oil in three optical wavebands ("Red", "Green" and "Blue") and water content is evaluated as Relative Saturation of oil by water. The detector is able to monitor oils with low light absorption (hydraulic, transformer, turbine, compressor and etc. oils) as well as oils with rather high light absorption in visible waveband (diesel and etc. oils). In a case study that the detector is applied to a diesel engine oil, it is found that the detector provides good results on oil chemical degradation as well as soot concentration.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.1964-1970
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• 2010

A new intelligent power network (Smart Grid) that grafts some new technologies, such as the extension of the new and reproducible energy, electric motors, and electric storages, onto the regulation of green house gases according to the recent convention on climate changes has been actively promoted. As establishing such an intelligent power network, it is possible to implement a real-time rate system according to the change from the conventional single directional information transmission to the bidirectional information transmission. Such a real-time rate system can provide power during the chip rate hour by avoiding the high rate hour although customers use the same level of power through providing such real-time rate information including power generation costs. In this study, the establishment of an operating system that makes an effective use of the real-time rate system and its operation method are to be proposed.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1874-1885
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• 2018

The customer side operation is getting more complex in a smart grid environment because of the adoption of renewable resources. In performing energy management planning or scheduling, it is essential to forecast non-controllable resources accurately and robustly. The PV system is one of the common renewable energy resources in customer side. Its output depends on weather and physical characteristics of the PV system. Thus, weather information is essential to predict the amount of PV system output. However, weather forecast usually does not include enough solar irradiation information. In this study, a PV system power output prediction model (PPM) under limited weather information is proposed. In the proposed model, meteorological radiation model (MRM) is used to improve cloud cover radiation model (CRM) to consider the seasonal effect of the target region. The results of the proposed model are compared to the result of the conventional CRM prediction method on the PV generation obtained from a field test site. With the PPM, root mean square error (RMSE), and mean absolute error (MAE) are improved by 23.43% and 33.76%, respectively, compared to CRM for all days; while in clear days, they are improved by 53.36% and 62.90%, respectively.