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The Real-time system estimates the worst-case execution time (WCET) of the program to ensure the real-time requirements of the system. In this paper, a test method based on Associative Process Communication (APC) is put forward. First it tests the WCET value of basic blocks of ICFG through the use of APC algorithm, and then estimates the WCET by analyzing the worst execution path of the basic block. APC test method tests all benchmarks of Mälardalen. And the test results show that the proposed test method is precise and effective, and the test error is within the theoretical analysis.

this study presents an eight array ultrasonic signal phased array sparse sampling experiment system based ultrasonic phased array technology and Compressed Sensing (CS). Proposed system considers recovery ultrasonic beam signal received eight phased array elements with sparse samples captured using sub-Nyquist model in CS recovery algorithm. We have the block defect detection test in the system. The test result approximated the actual block defect position. Based on block defect detection test, We compared sparse sampling value using spectrum estimation to Compressed Sensing recovery algorithm imaging, and no focus and focus detection effect, proved the phased array experiment system based on Compressed Sensing .it can greatly improve the detection signal to noise ratio (SNR) and sensitivity. So we verify the phased array focus can improve the detection ability.

This paper discusses the implementation of a new travel time estimation method in a regional demand forecasting model. The developed model considers implicitly the influence of signal timing as a function of main street and cross street traffic demands, although signal timing setting is not required as input. The application presented in this paper demonstrates that the developed model is applicable to a large network without the burden of signal timing input requirement. The results indicate that the application of the model can improve the performance of traffic assignment as part of the demand forecasting process. The model is promising to support dynamic traffic assignment (DTA) model applications in the future.