Sewer condition assessment involves the determination of defective points and status of aged sewers by a CCTV inspection according to the standard manual. Therefore, it is important to establish a reliable and effective standard manual for identifying the sewer defect. In this study, analytic reviews of the CCTV inspection manuals of the UK, New Zealand, Canada and South Korea were performed in order to compare the defect codes and the protocols of condition assessment. Through this, we also established the standardized method for defect code and revised the calculation method of assigning the condition grade. Analyses of the types and frequencies of sewer defects that obtained by CCTV inspection of 7000 case results, showed that the joint defect and lateral defect were the most frequent defects that occurred in Korea. Some defect codes are found to be modified because those did not occur at all. This study includes a proposed new sewer defect codes based on sewer characteristics.

To perform long-term sewer monitoring, It is important to understand the nature of the wastewater flow that occurs at the point on early stage of the monitor and to prevent in advance a problem which may caused. We can infer the flow properties and external factors by analyzing the scatter graph obtained from the measured data flow rate monitoring data since an field external factor affecting the sewage flow is reflected in the flow rate monitoring data. In this study, Selecting the three points having various external factors, and we Inferred the sewer flow characteristics from depth-velocity scatter graph and determined the analysis equation for the dry-weather flow rate data. At the‘point 1’expected non-pressure flow, we were able to see the drawdown effect caused by the free fall in the manhole section. At the‘point 2’, existed weir and sediments, there was backwater effect caused by them, and each of size calculated from the scatter graph analysis were 400 mm and 130 mm. At the‘Point 3’, there is specific flow pattern that is coming from flood wave propagation generated by the pump station at upstream. In common, adequate equations to explain the dry weather flow data are flume equation and modified manning equation(SS method), and the equations had compatibility for explaining the data because all of R2 values are over 0.95.

The widespread occurrence of dissolved endocrine disrupting compounds(EDCs) and pharmaceutical active compounds(PhACs) in water sources is of concern due to their adverse effects. To remove these chemicals, adsorption of EDCs/PhACs on granular activated carbon(GAC) was investigated, and bisphenol A, carbamazepine, diclofenac, ibuprofen, and sulfamethoxazole were selected as commonly occurring EDCs/PhACs in the aquatic environment. Various adsorption isotherms were applied to evaluate compatability with each adsorption in the condition of single-solute. Removal difference between individual and competitive adsorption were investigated from the physicochemical properties of each adsorbate. Hydrophobicity interaction was the main adsorption mechanism in the single-solute adsorption with order of maximum adsorption capacity as bisphenol A ≻ carbamazepine ≻ sulfamethoxazole ≻ diclofenac ≻ ibuprofen, while both hydrophobicity and molecular size play significant roles in competitive adsorption. Adsorption kinetic was also controled by hydrophobicity of each adsorbate resulting in higher hydrophobicity allowed faster adsorption on available adsorption site on GAC. EDCs/PhACs adsorption on GAC was determined as an endothermic reaction resulting in better adsorption at higher temperature (40 ◦C) than lower temperature (10 ◦C#x25E6;C).

Every port is competing for attracting loyal customers from other ports to achieve more profits stably. This paper proposes a data-mining scheme to facilitate this process. For resolving the problem, the OD (Origination-Destination) data are gathered from the AIS (Automatic Identification System) data. The OD data are clustered according to the arrival dates and ports. The FP-growth algorithm is applied to mine the frequent patterns of ships arriving at ports. Maintaining a loyal customer list for port updates and accuracy is critical in establishing its usefulness. These lists are critical as they can be used to provide suggestions for new products and services to loyal customers. Finally, based on the frequent patterns of the ships and the mode of arrival times, a formula proposed in this paper to derive shipping companies’ loyalty to ports was applied. The case of Kaohsiung port was shown as an example of our algorithm, and the OD data of ships in 2017-2018 were processed. Using the results of our algorithm, other rival ports, such as Shanghai or Busan, may attract customers no longer loyal to Kaohsiung ports in the last two years and attract them as new loyal customers.