Recent advances in smart devices have sustained them as a better alternative for the design of human-machine interaction because they are equipped with accelerometer sensor, gyroscope sensor, and an advanced operating system. This paper presents a continuous hand gestures recognition technique that is capable of continuous recognition of hand gestures using threeaxis accelerometer and gyroscope sensors in a smart device. To reduce the influence of unstableness of a hand making the gesture and compress the data, a gesture coding algorithm is developed. An automatic gesture spotting algorithm is developed to detect the start and end points of meaningful gesture segments. Finally, a gesture is recognized by comparing the gesture code with gesture database using dynamic time warping algorithm. In addition, a prototype system is developed to recognize the continuous hand gestures based human-machine interaction. With the smartphone, the user is able to perform the predefined gestures and control smart appliances using the Samsung AllShare protocol.

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Humans are recognized as having a major role in influencing environmental variability and change, including their influence on the climate system. To advance scientists' understanding of the role of humans within the climate system, there remains a need to resolve which of the following three hypotheses is correct: Hypothesis 1: Human influence on climate variability and change is of minimal importance, and natural causes dominate climate variations and changes on all time scales. In coming decades, the human influence will continue to be minimal.

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Digital watermarking has received much attention in recent years as a promising solution to copyright protection. Video watermarking in compressed domain has gained importance since videos are stored and transmitted in a compressed format. This decreases the overhead to fully decode and re-encode the video for embedding and extraction of the watermark. High Efficiency Video Coding (HEVC/H.265) is the latest and most efficient video compression standard and a successor to H.264 Advanced Video Coding. In this article, we propose a robust watermarking framework for HEVC-encoded video using informed detector. A readable watermark is embedded invisibly in P frames for better perceptual quality. Our framework imposes security and robustness by selecting appropriate blocks using a random key and the spatio-temporal characteristics of the compressed video. A detail analysis of the strengths of different compressed domain features is performed for implementing the watermarking framework. We experimentally demonstrate the utility of the proposed work. The results show that the proposed work effectively limits the increase in video bitrate and degradation in perceptual quality. The proposed framework is robust against re-encoding and image processing attacks.

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