This paper presents a recognition system for handwritten Pashto letters. However, handwritten character recognition is a challenging task. These letters not only differ in shape and style but also vary among individuals. The recognition becomes further daunting due to the lack of standard datasets for inscribed Pashto letters. In this work, we have designed a database of moderate size, which encompasses a total of 4488 images, stemming from 102 distinguishing samples for each of the 44 letters in Pashto. The recognition framework uses zoning feature extractor followed by K-Nearest Neighbour (KNN) and Neural Network (NN) classifiers for classifying individual letter. Based on the evaluation of the proposed system, an overall classification accuracy of approximately 70.05% is achieved by using KNN while 72% is achieved by using NN.
It is widely known that resonance can quickly lead to failure in vibrating bolted flanged pipe joints. Condition monitoring is performed time to time in some industries for smooth operation of a system, whereas mostly trial-and-error tests are performed to control vibration. During all this process, the inherent design problems are not considered. A bolted flange joint in piping system is not a simple problem, being the combination of flange, gasket, bolts, and washers. The success of a bolted flanged pipe joint is defined by the “static mode of load” in the joint. However, it has been recognized that a “dynamic mode of load” governs in a gasketed bolted flanged pipe joint, which leads to its failure due to flange rotation, providing flange yielding, fatigue of bolts, and gasket crushing. This paper presents results of detailed 3D finite element and mathematical modal analysis under bolt up to determine natural frequencies and mode shapes of gasketed flanged joints with and without raised face in comparison to the nongasketed flange joint.
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