The Design and Implementation of a Bayesian CAD Modeler for Robotic Applications

We present a Bayesian CAD modeler for robotic applications. We address the problem of taking into account the propagation of geometric uncertainties when solving inverse geometric problems. The proposed method may be seen as a generalization of constraint-based approaches in which we explicitly model geometric uncertainties. Using our methodology, a geometric constraint is expressed as a probability distribution on the system parameters and the sensor measurements, instead of a simple equality or inequality. To solve geometric problems in this framework, we propose an original resolution method able to adapt to problem complexity. Using two examples, we show how to apply our approach by providing simulation results using our modeler

Improved Fair-Zone technique using Mobility Prediction in WSN

The self-organizational ability of ad-hoc Wireless Sensor Networks (WSNs) has led them to be the most popular choice in ubiquitous computing. Clustering sensor nodes organizing them hierarchically have proven to be an effective method to provide better data aggregation and scalability for the sensor network while conserving limited energy. It has some limitation in energy and mobility of nodes. In this paper we propose a mobility prediction technique which tries overcoming above mentioned problems and improves the life time of the network. The technique used here is Exponential Moving Average for online updates of nodal contact probability in cluster based network.Comment: 10 pages, 7 figures, Published in International Journal Of Advanced Smart Sensor Network Systems (IJASSN

A Giant Lipoma In The Hand - Report Of A Rare Case

A 38 years old male patient presented with a large painless swelling in the right palm with ultrasound examination suggestive of fatty nature of the swelling MRI showing a well-circumscribed soft tissue swelling in the deep palmar space. The giant tumor of 6.5 X 4 cm was excised and the patient was symptom free two years following the surgery

Axillary Arch (Of Langer): Incidence, Innervation, Importance

The present study was planned to find out the incidence of accessory muscle arches in the axilla of 68 upper limb (38 right and 30 left) dissections. Langer’s arch was observed in one right limb out of the 68 limbs, total incidence was 1.47%. The arch extended from the latissimus dorsi to the fascia covering the biceps brachii. The incidence is low in South Indian population (Dravidians) compared to the various other populations reported in literature. A branch from the lateral cord of brachial plexus supplied it in contrast with the previous reports. The surgical significance of this muscle is reviewe

Image Encryption Based on Diffusion and Multiple Chaotic Maps

In the recent world, security is a prime important issue, and encryption is one of the best alternative way to ensure security. More over, there are many image encryption schemes have been proposed, each one of them has its own strength and weakness. This paper presents a new algorithm for the image encryption/decryption scheme. This paper is devoted to provide a secured image encryption technique using multiple chaotic based circular mapping. In this paper, first, a pair of sub keys is given by using chaotic logistic maps. Second, the image is encrypted using logistic map sub key and in its transformation leads to diffusion process. Third, sub keys are generated by four different chaotic maps. Based on the initial conditions, each map may produce various random numbers from various orbits of the maps. Among those random numbers, a particular number and from a particular orbit are selected as a key for the encryption algorithm. Based on the key, a binary sequence is generated to control the encryption algorithm. The input image of 2-D is transformed into a 1- D array by using two different scanning pattern (raster and Zigzag) and then divided into various sub blocks. Then the position permutation and value permutation is applied to each binary matrix based on multiple chaos maps. Finally the receiver uses the same sub keys to decrypt the encrypted images. The salient features of the proposed image encryption method are loss-less, good peak signal-to-noise ratio (PSNR), Symmetric key encryption, less cross correlation, very large number of secret keys, and key-dependent pixel value replacement.Comment: 14 pages,9 figures and 5 tables; http://airccse.org/journal/jnsa11_current.html, 201

A participatory methodology for large scale field trials in the UK

Farmer participation was essential in developing a uniquely useful set of wheat variety trials data on a wide range of organic farms over two years. Although the trials were successful, it became clear that some of the participating farmers felt there were some limitations in the process. These included a lack of ownership in the project and a concern for more researcher help. It was clear that a greater time in-vestment was needed at the start of the project to help with farmer understanding and ownership. De-spite the negative comments, farmers appreciated their involvement, particularly in contrasting their own views and information with that from the wider scene. Farmer participation is essential for systems-level research and this project helped to develop a small core of trained farmers and researchers

fMRI Investigation of Cortical and Subcortical Networks in the Learning of Abstract and Effector-Specific Representations of Motor Sequences

A visuomotor sequence can be learned as a series of visuo-spatial cues or as a sequence of effector movements. Earlier imaging studies have revealed that a network of brain areas is activated in the course of motor sequence learning. However these studies do not address the question of the type of representation being established at various stages of visuomotor sequence learning. In an earlier behavioral study, we demonstrated that acquisition of visuo-spatial sequence representation enables rapid learning in the early stage and progressive establishment of somato-motor representation helps speedier execution by the late stage. We conducted functional magnetic resonance imaging (fMRI) experiments wherein subjects learned and practiced the same sequence alternately in normal and rotated settings. In one rotated setting (visual), subjects learned a new motor sequence in response to an identical sequence of visual cues as in normal. In another rotated setting (motor), the display sequence was altered as compared to normal, but the same sequence of effector movements were used to perform the sequence. Comparison of different rotated settings revealed analogous transitions both in the cortical and subcortical sites during visuomotor sequence learning  a transition of activity from parietal to parietal-premotor and then to premotor cortex and a concomitant shift was observed from anterior putamen to a combined activity in both anterior and posterior putamen and finally to posterior putamen. These results suggest a putative role for engagement of different cortical and subcortical networks at various stages of learning in supporting distinct sequence representations