Designs of water distribution systems and water resources planning and management can be obtained from a comprehensive investigation and analysis of water consumption data in real life systems. Water consumption patterns for domestic purposes were monitored at 145 households over a three-year period. Electric flow meters were installed at the ends of all of the household water taps. Water consumption patterns were analyzed to configure the water demand trends for social and cultural factors. Economic factors such as monthly income and the area of the floor plan were investigated to determine the impact of resident wealth on the patterns of water consumption. Water use data collected by a public water resources management firm in Korea, Kwater, had been filtered using both physical and probabilistic criteria to improve the credibility of the analysis. Both the Mann-Kendall and Spearman's Rho tests were used to perform the trend analysis. Distinct factors in the patterns of water consumption can be determined to cause both increasing and decreasing trends in water use. Analysis of this data provides the basis of parameter configuration for a reasonable design of a domestic water-demand prediction model.

An x-ray radiographic system consisting of two detectors in tandem, or a sandwich detector, can produce dual-energy image from a single-shot exposure. Subtraction of two images obtained from the two detectors can produce a sharper image through an unsharp masking effect if the two images are formed at different spatial resolutions. This is indeed possible by incorporating different thicknesses of x-ray conversion layers in the detectors. In this study, we have developed a microtomography system with a sandwich detector in pursuit of high-resolution bone-enhanced small-animal imaging. The results show that the bone-enhanced images reconstructed from the dualenergy projection data provide higher visibility of bone details than the conventionally reconstructed images. The microtomography with the single-shot dual-energy sandwich detector will be useful for the high-resolution bone-enhanced small-animal imaging. K : Computerized Tomography (CT) and Computed Radiography (CR); Medical-image reconstruction methods and algorithms, computer-aided diagnosis 1Corresponding author.

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For a dedicated x-ray inspection of printed-circuit boards (PCBs), a bench-top planar cone-beam computed tomography (pCT) system with a flat-panel detector has been built in the laboratory. The system adopts the tomosynthesis technique that can produce cross-sectional images parallel to the axis of rotation for a limited angular range. For the optimal operation of the system and further improvement in the next design, we have evaluated imaging performances, such as modulation-transfer function, noise-power spectrum, and noise-equivalent number of quanta. The performances are comparatively evaluated with the coventional cone-beam CT (CBCT) acquisition for various scanning angular ranges, applied tube voltages, and geometrical magnification factors. The pCT scan shows a poorer noise performance than the conventional CBCT scan because of less number of projection views used for reconstruction. However, the pCT shows a better spatialresolution performance than the CBCT. Because the image noise can be compensated by an elevated exposure level during scanning, the pCT can be a useful modality for the PCB inspection that requires higher spatial-resolution performance. K : Computerized Tomography (CT) and Computed Radiography (CR); Inspection with x-rays 1Corresponding author.

The information on the incoming load to wastewater treatment plants is not often available to apply modelling for evaluating the effect of control actions on a full-scale plant. In this paper, a time series model was developed to forecast flow rate, COD, NH4(+)-N and PO4(3-)-P in influent by using 250 days data of field plant operation data. The data for 150 days and 100 days were used for model development and model validation, respectively. The missing data were interpolated by the spline method and the time series model. Three different methods were proposed for model development: one model and one-step to seven-step ahead forecasting (Method 1); seven models and one-step-ahead forecasting (Method 2); and one model and one-step-ahead forecasting (Method 3). Method 3 featured only one-step-ahead forecasting that could avoid the accumulated error and give simple estimation of coefficients. Therefore, Method 3 was the reliable approach to developing the time series model for the purpose of this research.