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This paper presents a prototype that can convert sign language into text. A Leap Motion controller was utilised as an interface for hand motion tracking without the need of wearing any external instruments. Three recognition techniques were employed to measure the performance of the prototype, namely the Geometric Template Matching, Artificial Neural Network and Cross Correlation. 26 alphabets from American Sign Language were chosen for training and testing the proposed prototype. The experimental results showed that Geometric Template Matching achieved the highest recognition accuracy compared to the other recognition techniques.

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A clinical staging for carcinoma of the lung utilizing conventional diagnostic procedures and mediastinoscopy for careful assessment of the upper mediastinum has been developed. In an analysis of 144 patients, one of 83 right‐sided tumors had contralateral spread compared to 7 of 61 for the left side. Bilateral spread was equal. Forty‐three of 52 patients with squamous cell carcinoma had negative upper mediastinal nodes, 6 had ipsilateral, and 3 contralateral node involvement. Forty of 64 poorly differentiated tumors had involved nodes, and 28 had either contralateral or bilateral spread. Twelve of the 16 oat‐cell cancers had involved nodes; 8 were bilateral. Eight of the 12 adenocarcinomas had involved nodes; 3 were bilateral. Seventy‐three percent of the well‐differentiated tumors fell into Stages 1 and 2; 83 percent of the anaplastic tumors in Stages 3 or 4.

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