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Structural Health Monitoring is an emerging field of science and technology. The process of implementing a damage detection and characterization strategy for engineering structures is referred to as Structural Health Monitoring (SHM). The SHM process involves the observation of a system over time using periodically sampled dynamic response measurements from an array of sensors, the extraction of damage sensitive features from these measurements, and the statistical analysis of these features to determine the current state of system health. The research paper describes the piezo-vibrational sensor and accelerometer sensors to monitor the prototype of bridge.

The present study was carried out during year 2015 and 2016 at ICAR-Central Institute of Temperate Horticulture (CITH), Srinagar, India with the objective of trait specific characterization of walnut accessions with specific emphasis on lateral bearing trait. The study was initiated on pre-selected indigenous accessions collected from various pockets of North Western Himalaya and maintained at field gene bank of the institute. The most widely grown varieties 'Sulaiman' and 'Hamdan' were used as local check. All the accessions were monitored to identify the bearing habit. Only one accession CITH-W-121 (IC-0622836) was found with lateral bearing trait, which had fruit bearing on leafy shoots emerging from terminal, sub terminal as well as from lateral buds of 1-year-old shoot. Bearing on lateral leafy shoots developing from lateral buds of 1-year-old shoot is being reported for the first time in indigenous genetic resources of walnut which is an important trait to improve productivity. Lateral leafy shoots emerged all along 1-year old shoot, in which about 50% lateral leafy shoots bearing 1−3 fruits panicle-1. Overall 40−60% lateral leafy shoots in a tree were bearing fruits in this accession. In term of yield, CITH-W-121 (11.07 kg tree-1) was found significantly superior to Sulaiman (5.85 kg tree-1) and Hamdan (5.48 kg tree-1). Yield efficiency was recorded significantly higher in CITH-W-121 (26.37 g cm-2 tcsa) over the two ruling check varieties i.e, Hamdan (13.99 g cm-2 tcsa) and Sulaiman (9.65 g cm-2 tcsa). In accession CITH-W-121, nut weight and kernel weight was recorded on par with Hamdan, while kernel recovery was on par with Sulaiman. This accession has desirable traits like well filled, plump and light coloured kernel with moderately easy removal of kernel halves and is having a good balance between vegetative growth and fruit bearing.

Human gesture recognition is defined as a necessity to determine what human body actions occur in videos. Gestures can originate from body motion like walking, bending, jumping, and hand waving. When a video is playing the human action detection is a difficult point of detection. This problem is peculiarly hard due to extensive variations in motion appearance of actions, camera angles with respect to the human body, motion in the background, noise and large amount of video data. Main aim is to detect various gestures in a multimedia clip by preprocessing the video and then applying algorithm for identifying various actions. The important role is to determine behavior of humans based on based on their actions. The moving objects are determined from a video stream. The database used includes CASIA database and WEIZ MANS ACTION database to test the proposed system. Those can be applied to Surveillance Systems.