Abstract Increase of science and technology lead to the development of variety of missiles. Generally, a missile consists of four system components targeting and/or missile guidance, flight system, engine and war head. In order to determine the effectiveness, yield and explosive capability of these components several tests had to be done. These tests can yield their information on how they work, as well as... Increase of science and technology lead to the development of variety of missiles. Generally, a missile consists of four system components targeting and/or missile guidance, flight system, engine and war head. In order to determine the effectiveness, yield and explosive capability of these components several tests had to be done. These tests can yield their information on how they work, as well as how missile behave under various conditions. Tests like Pressure Position Test (PPT), Null Position Test (NPT), and Vectoring Tests are carried on each flex nozzle system of a missile to verify the performance of flex seal using electro hydraulic actuators, mirror image sensor and electronic controller. These tests are done for acceptance of flex nozzle control system in the missile. During the test command, pitch, average, main voltages are recorded using DAC. The flex nozzle system is integrated to pressure chamber in horizontal condition and actuators. Then the PPT, NPT and Vectoring Tests are performed using electro hydraulic actuators. In the process mentioned above, it is evident that every missile and its subsystems should be tested in order to get approved. The testing part is done by measuring certain quantities such as stress, strain, pressure, load and temperature. These quantities are compared with the standard results. Measuring of any quantity requires the help of the instrumentation. So instrumentation plays a vital role in the testing of missile system. Without the helping of this, launching of the missile is next to impossible. Read More Read Less

Abstract In this paper, I design a new neural network for solving least absolute deviation problems with equality and box constraints. Compared with some existing models, the proposed neural network needs the fewest state variables and has only one-layer structure. By constructed a proper Lyapunov function, the following two results can be proved. First, it is stable in the sense of Lyapunov. Second, the... In this paper, I design a new neural network for solving least absolute deviation problems with equality and box constraints. Compared with some existing models, the proposed neural network needs the fewest state variables and has only one-layer structure. By constructed a proper Lyapunov function, the following two results can be proved. First, it is stable in the sense of Lyapunov. Second, the solution of the proposed model can converge to an exact optimal solution of the problem. Finally, its validity and transient behaviors are demonstrated by some simulation results. Read More Read Less

Abstract A video-input traffic sign recognition is an advanced application which is a part of Intelligent Transport System(ITS) that provides information to the vehicles in order to make them safe and coordinated on road. The approach is to take a video as an input, divide it into series of frames and implement detection and recognition under mobile conditions. There are three major components: 1)... A video-input traffic sign recognition is an advanced application which is a part of Intelligent Transport System(ITS) that provides information to the vehicles in order to make them safe and coordinated on road. The approach is to take a video as an input, divide it into series of frames and implement detection and recognition under mobile conditions. There are three major components: 1) detection; 2) recognition; 3) classification. We implement our technology on real data sets to obtain results in real-time manner. Read More Read Less