Occurrence of process environment changes, such as influent load variances and process condition changes, can reduce treatment efficiency, increasing effluent water quality. In order to prevent exceeding effluent standards, it is necessary to manage effluent water quality based on process operation data including influent and process condition before exceeding occur. Accordingly, the development of the effluent water quality prediction system and the application of technology to wastewater treatment processes are getting attention. Therefore, in this study, through the multi-channel measuring instruments in the bio-reactor and smart multi-item water quality sensors (location in bio-reactor influent/effluent) were installed in The Seonam water recycling center #2 treatment plant series 3, it was collected water quality data centering around COD, T-N. Using the collected data, the artificial intelligence-based effluent quality prediction model was developed, and relative errors were compared with effluent TMS measurement data. Through relative error comparison, the applicability of the artificial intelligence-based effluent water quality prediction model in wastewater treatment process was reviewed.

Since aged water treatment facilities could threaten the sustainable water supply, asset management system has been adopted for their systematic management. Level of Service(LoS) is one of critical components of asset management and could be quantified through benchmark index(BMI). Water supplier could estimate consumer’s satisfaction and their performance through BMI to improve the LoS. We developed BMI for water treatment facilities from customer’s satisfaction survey. BMI, represented with the Total Service Score(TSS), was assessed with water quality, water pressure, taste and odor, water rate, and service quality with weighing factors. BMI could, further, be used to assist the analysis of the life cycle cost to increase the unit of LoS.

This study was carried out to analyze water suspension in the water supply system through fault tree analysis. And quantitative factors was evaluated to minimize water suspension. Consequently the aim of this study is to build optimal planning by analyzing scenarios for water suspension.Accordingly the fault tree model makes it possible to estimate risks for water suspension, current risks is 92.23 m3/day. The result of scenario analysis by pipe replacement, risks for water suspension was reduced 7.02 m3/day when replacing WD4 pipe. As a result of scenario analysis by water district connections, the amount of risk reduction is maximized when it is connecting to network pipe of D Zone. Therefore, connecting to network pipe for D Zone would be optimal to reduce risk for water suspension.

Purpose - The IT convergence industry, which is the subject of this study, is the main strategy field during the 4th industrial revolution era. Against this background, it is urgent to establish policy measures to survive and spread export products in the global industries. Research, design, data and methodology - In order to achieve this goal, we conducted the Importance - Performance Analysis (IPA) and found that it is necessary to develop tailor - made marketing support for small and medium sized IT exporters and to develop export strategy products with competitive technologies. Results - Above all, customized marketing support for IT export-related SMEs was needed. Next, in the first quadrant, strategic products, qualitative level, global, value added, and information systems were included, and it was found that 'development of export strategic products with competitive technologies' was necessary. In the third quadrant, related variables calculated at present time are not urgent variables. Conclusions - In this study, it would be necessary to calculate the additional implications of the variables that are not considered in this study, including future studies, because the methods considered here as analysis variables are carried out in comparison with the previous studies.

Purpose - This study aims to clarify the impact of smart health gadgets (specfically, smart watches/sports wristbands) on promoting healthy behavior. It also aims to understand the use and characteristics of the devices, to explore the relationship between device factors and factors that affect healthy behavior, and to discuss the development of health promotion. Research, design, data, and methodology - Smart device users were investigated through a random sampling method of 185 respondents, including all ages and all levels of occupation, education, and income. The SmartPLS 3.0 software enabled the path analysis and the descriptive statistical analysis; the theoretical model was evaluated for the parameter analysis. Results - The size and path of each factor impacting health promoting behavior were ascertained. The objective factors that attract users to the smart wristband were investigated as well as the methods by which the device and the HPM are bound to each other and the correlation factors to seek out the closest relationship. Conclusions - According to the analysis, the real-time smart watch/sports wristband exerts a positive impact on one’s health promoting behavior. Health awareness is increasingly promoted in the process of using the device, and the impact of health awareness and self-efficacy effects on healthy behavior is considerable.

Global increase in the demand for the new Electrical and Electronic Equipment (EEE) results in the rapid increase of waste electrical and electronic equipment (WEEE) (or electronic waste). Significant efforts on developing diverse WEEE recycling policy and programs such as extended producer responsibility (EPR), WEEE directive, and the restriction of the use of hazardous substances (RoHS) directive are being made by many developed nations. This study focuses on determining priority among proposed WEEE recycling policy research projects by a number of experts from academia, institutions and recycling industry using quality function deployment (QFD) method to better manage and recycle WEEE in Korea. In order to develop effective WEEE recycling policy, a total of 12 different WEEE recycling policy research projects were proposed by a total of 11 experts related WEEE recycling. Reliability and validity evaluation of the proposed projects were conducted, along with SPSS statistical software. By using the QFD method, a survey regarding potential problems, suggestions, and difficulties at several WEEE recycling facilities were conducted and evaluated. Evaluation of the proposed projects was made by house of quality (HOQ). In this study, proposed research projects with higher importance index include WEEE collection system, development of WEEE recycling guideline, and establishment of WEEE generation/collection/recycling national database. The QFD method employed in this study can be effectively used as a decision-making process tool in WEEE recycling policy and road map.