<span>The critical activity of testing is the systematic selection of suitable test cases, which be able to reveal highly the faults. Therefore, mutation coverage is an effective criterion for generating test data. Since the test data generation process is very labor intensive, time-consuming and error-prone when done manually, the automation of this process is highly aspired. The researches about automatic test data generation contributed a set of tools, approaches, development and empirical results. In this paper, we will analyse and conduct a comprehensive survey on generating test data based on mutation. The paper also analyses the trends in this field.</span>
Airport runway and taxiway (airside) areas are highly complex environments, where safe-separation procedures must be maintained by Air Traffic Controllers (ATCs) under varying visibility and traffic conditions. In this paper, we propose a novel computer-vision based framework, namely Deep4Air, for automated visual monitoring of airside operations, providing real-time data including aircraft location, speed, and distance analytics. This framework includes an adaptive deep neural network that exploits a depth-wise convolutional operator for efficient detection and tracking of aircraft. The experimental results show an average precision of detection and tracking of up to 98.2% on simulated data with validation on surveillance videos from the digital tower at George Bush Intercontinental Airport. The results also demonstrate that Deep4Air can locate aircraft positions relative to the airport runway and taxiway infrastructure with high accuracy. Furthermore, aircraft speed and separation distance are monitored in real-time, providing enhanced safety management.
The research process has developed the criterion for test and assessment of academic results of high quality curriculum for students majoring in Basketball of Sport Training discipline in each module in accordance with the curriculum’s practical conditions aiming to accurately assess learners' competencies and ensure the enhanced quality of training for bachelors of Bac Ninh Sport University.
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