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Abstract.Parkinson's disease is one of the most painful, dangerous and non curable diseases which occurs at older ages (mostly above 50 years) in humans. The data-set for the disease is retrieved from UCI repository. A relative study on feature relevance analysis and the accuracy using different classification methods was carried out on Parkinson data-set. Sieve multigram data and Survey graph provide the statistical analysis on the voice data so that the healthy and Parkinson patients would be correctly classified. KStar and NNge present good accuracy based classification methods. Sieve multigram shows the edges between the nodes such as Fhi, Flo, Jitter, JitterAb, RAP and PPQ. KStar and NNge have connections with Shimmer and ShimmerDB . ADTree shows 21 leaves with 31 leaves and SimpleCART shows 13 leaves and 7 leaves. Most of the clusters vary with DBScan and SimpleKMeans with 25% and 38% towards Parkinson disease.

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This article explores the design and analysis of a novel ultra‐wideband (UWB) antenna for body‐centric applications. The designed antenna consists of circular ring structured radiating element with 24 spokes, which resembles the shape of Ashoka chakra (Indian National flag emblem). The antenna placed on the semi flexible RT/Duroid 5880 with dielectric constant of 2.2 and occupying the dimension of 30 × 25 × 0.8 mm3. The present design aims at optimizing the antenna structure to cater UWB operating spectrum (3.1‐10.6 GHz) with a novel patch shape, which looks like the Ashoka chakra. The proposed antenna is analyzed by placing on three‐layered human phantom model and examined on head, arm at three of its operating frequencies. The maximum specific absorption rate (SAR) is found to be 1.23 W/kg and 1.29 W/kg when computed at arm and head of the human body respectively. The SAR values are observed under those conditions are satisfying the international safety standards such as FCC & IEEE C95.1:2005 & ICNIPR. Analysis of system savant (ANSYS Savant) radiation performance characteristics are also studied by placing the proposed antenna on virtual human body environment.

In this paper we deal with the design and development of a Four Fingered

In this paper a technique is proposed to estimate the bearing faults of induction motor using sensor less monitoring. Sensor less monitoring is more suitable than conventional vibrating meters. It is very difficult to distinguish the bearing component from its current signature in nascent stage. Therefore in this work bearing fault components are estimated by cancelling the nonbearing fault components in a stator current signature. All the stator current components are treated as noise and cancelled by a wiener filter in real time fashion. Bearing faults with wide range of fault frequencies are estimated using noise cancellation. The results of different bearing faults have been affirmed by this method. Finally a threshold limit is given to intimate the severity of the faults.