Bridge monitoring and maintenance is an expensive yet essential task in maintaining a safe national transportation infrastructure. Traditional monitoring methods use visual inspection of bridges on a regular basis and often require inspectors to travel to the bridge of concern and determine the deterioration level of the bridge. Automation of this process may result in great monetary savings and can lead to more frequent inspection cycles. One aspect of this automation is the detection of cracks and deterioration of a bridge. This paper provides a comparison of the effectiveness of four crack-detection techniques: fast Haar transform ͑FHT͒, fast Fourier transform, Sobel, and Canny. These imaging edge-detection algorithms were implemented in MatLab and simulated using a sample of 50 concrete bridge images ͑25 with cracks and 25 without͒. The results show that the FHT was significantly more reliable than the other three edge-detection techniques in identifying cracks.

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Cost control and schedule control are two of the most important management functions in the construction industry. Major research efforts are focused on developing procedures for improving the effectiveness of cost and schedule control. As a result, researchers are concerned with the quality, integrity, and timeliness of data that flow through such control systems. A number of data models have been proposed to integrate cost-and schedule-control functions, because such integration is viewed as the, solution to the many problems facing construction projects today. This paper provides an overview of cost-and schedule-control functions, defines the desired control cycle, and discusses the problems and needs of cost-and schedule-control functions. A number of integrated cost-and schedulecontrol data models, which represent the state of construction research in this area, are discussed. The work-packaging model is briefly described and is suggested as the most likely existing model to achieve the desired cost and schedule integration. Finally, the conceptual design of a foundational data model for control, based on relational concepts, is provided. The recommended design adopts the conceptual structures of the work-packaging model. 2Res. Asst.,

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