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This paper presents a novel methodology for urban growth prediction using a machine learning approach. The methodology treats successive historical satellite images of an urban area as a video for which future frames are predicted. It adopts a time‐dependent convolutional encoder–decoder architecture. The methodology's input includes a satellite image for the base year and the prediction horizon. It constructs an image that predicts the growth of the urban area for any given target year within the specified horizon. A sensitivity analysis is performed to determine the best combination of parameters to achieve the highest prediction performance. As a case study, the methodology is applied to predict the urban growth pattern for the Dallas–Fort Worth area in Texas, with focus on two of its counties that observed significant growth over the past decade. The methodology is shown to produce results that are consistent with other growth prediction studies conducted for the areas. [ABSTRACT FROM AUTHOR]

Many of the older bridges in the United States have no original contract documents available, and about 26,000 bridges that are rated as scour critical have unknown foundation conditions. Thus, no information is available regarding the type, depth, geometry, or material of these scour critical bridge foundations. The unknown bridge foundations pose a significant problem to bridge owners because of safety concerns. This paper presents the determination of an unknown bridge foundation depth at Forth Worth, Texas. The bridge was supported by driven steel H-piles. Three nondestructive testing (NDT) techniques were utilized: (1) the parallel seismic (PS) method, (2) the sonic echo (SE) method, and (3) resistivity imaging (RI). The main objective of this present study was to compare the suitability of NDT techniques to determine the unknown bridge foundation depth. Based on the field test results, both PS and RI methods provided foundation depth close to actual foundation depth. However, the SE method was determined to be unsuitable for determining the unknown steel H-pile depth. [ABSTRACT FROM AUTHOR]

This article focuses on the 2004 IEEE Microwave Theory and Techniques Society (IEEE MTT-S) International Microwave Symposium (IMS), which was held during 6-11 June 2004, in Fort Worth, Texas. 970 papers were originally submitted to the IEEE MTT-S IMS Technical Program Committee in December 2003 for possible presentation at the symposium in June 2004. Of those papers, 488 were accepted at the IEEE MTT-S IMS. Each of authors was then invited to expand their papers. 126 expanded papers were submitted and of these 65 papers have been accepted for publication. Of these, 22 were published in the November 2004 issue of the journal "IEEE Transactions on Microwave Theory and Techniques."