Increasing the Accuracy of Cooperative Localization by Controlling the Sensor Graph

We characterize the accuracy of a cooperative localization algorithm based on Kalman Filtering, as expressed by the trace of the covariance matrix, in terms of the algebraic graph theoretic properties of the sensing graph. In particular, we discover a weighted Laplacian in the expression that yields the constant, steady state value of the covariance matrix. We show how one can reduce the localization uncertainty by manipulating the eigenvalues of the weighted Laplacian. We thus provide insight to recent optimization results which indicate that increased connectivity implies higher accuracy and we offer an analysis method that could lead to more efficient ways of achieving the desired accuracy by controlling the sensing network

STUDY ON FRICTION STIR WELDING OF ALUMINIUM PLATES USING AN ARTIFICIAL NEURAL NETWORK

For attaching solid materials, friction stir welding (FSW) is a relatively novelmethod recently developed. Compared to fusion welding processes, it has many benefits,such as reduced distortion, porosity, shrinkage, and cracking. FSW was first used to linkaluminum alloys with limited weldability, but it has since been used to join other metallicalloys and other dissimilar alloys. It is possible to fuse two plates using FSW by inserting anon-consumable rotating tool with a specifically designed pin between them and moving italong the welding line. Multiple applications in the aerospace and shipbuilding industries andthe automobile sector have seen success with this approach owing to its many benefits.Computer-aided artificial neural network (ANN) modelling may be used in material scienceand engineering to improve the FSW process. In the same manner, as the brain processesinformation, ANN is a computer processing paradigm inspired by the brain's workings. Thereare many nerve cells in the system. ANNs, like humans, are taught by examples and maybeboth a teaching and a forecasting tool. Well-trained neural networks are excellent predictiontools and can predict results for inputs it has never seen. It may therefore be considered as anapproach to automating FSW.A wide range of variables influences the FSW process. To better understand the relationshipbetween welded material's mechanical characteristics, such as ultimate tensile strength (UTS)and hardness, this study considers three parameters: tool rotation speed, welding speed, andaxial force. An artificial neural network (ANN) is developed and then evaluated to determinethe mechanical characteristics of welded materials

Filogenetska analiza izolata pasjeg parvovirusa izdvojenih u Mathuri u Indiji.

Canine parvovirus (CPV) is an important pathogen causing acute hemorrhagic gastroenteritis in dogs and myocarditis in pups. The present study deals with an analysis of partial nucleotide sequences of the VP1/VP2 gene of CPV isolates from Mathura, India to establish their phylogenetic relationship with other CPV isolates. Out of 100 samples from dogs showing the clinical signs of gastroenteritis viz., vomiting, diarrhea and dysentery, 63 were found positive for CPV-2 by polymerase chain reaction (PCR). Among the 63 positive samples, eight samples were processed further for nucleotide sequencing. Phylogenetic analysis revealed that the CPV variants were not only closely related among themselves but also showed minimum divergence from their ancestors, such as MEV, indicating very little divergence since their origin. From the study, it may be concluded that canine parvovirus-2 variants may represent a potential threat to canine populations. Thus more efforts is required to increase epidemiological monitoring and surveillance, along with the measures necessary to control this disease in the canine population, and to assess the efficacy of the current vaccines.Pasji parvovirus važan je uzročnik hemoragijskog gastroenteritisa u odraslih pasa i miokarditisa u štenadi. U ovom su istraživanju djelomično analizirane nukleotidne sekvencije gena VP1/VP2 izolata pasjeg parvovirusa iz Mathure u Indiji sa svrhom da se njihova filogenetska svojstva usporede s drugim izolatima toga virusa. Od 100 uzoraka izdvojenih iz pasa s gastroenteritisom odnosno s povraćanjem i proljevom, 63 su bila pozitivna na pasji parvovirus 2 upotrebom lančane reakcije polimerazom. Od toga je osam uzoraka uzeto za određivanje njihova nukleotidnog slijeda. Filogenetska analiza je pokazala da varijante pasjeg parvovirusa nisu bile samo međusobno usko srodne, već su s neznatnim skretanjem bile srodne i sa svojim predcima, kao što je virus enteritisa američke vidrice, što upućuje na njihove neznatne razlike od njihova nastanka. Može se zaključiti da varijante pasjeg parvovirusa 2 predstavljaju moguću prijetnju za populaciju pasa. Potrebno je uložiti više napora u smjeru epizootioloških istraživanja i donošenja mjera nadzora te kontrole ove zarazne bolesti zajedno s naporima za procjenu učinkovitosti postojećih cjepiva

PREDICTION OF WELD SHAPE FACTOR IN FLUX BONDED GAS TUNGSTEN ARC WELDING FOR AISI 1020 STEEL

GTAW welding has a number of drawbacks, the most significant of which is the limitedthickness of material that can be welded in a single pass, resulting in a decreased productionrate. Thus, a new welding technique Flux Bonded Gas Tungsten Arc Welding used whichlimits the drawbacks of the GTAW process. In the present work, GTAW process is carriedout on AISI 1020 carbon steel plates of 10mm thickness. The specimens were welded as beadon plate. Shape factor is calculated for FB-GTAW and compared with GTAW process. Themicrostructures and micro hardness are compared with flux and without flux at different heatinputs. The simulation of FB-GTAW process was done by NASTRAN® software. The shapefactor predicted by simulation and compared with experimental shape factor at different heatinputs. Time temperature data was measured by NASTRAN® software and compared withexperimental time temperature data. The shape factor decreases by FB-GTAW as comparedwith GTAW process. The shape factor by FB-GTAW decrease by 29.22%, 19.59% and31.13% at 120, 140 and 160 A respectively. The Micro-hardness of more than 300HV wasmeasured in FB-GTAW process. The Micro-hardness measured was about 200HV. TheMicro-hardness measured with FB-GTAW is more than normal GTAW process. This isbecause due to high cooling rate the martensite formation takes place in the weld pool by FBGTAWprocess. While with normal GTAW process acicular ferrite and pearlite are observedin the weld metal. The FB-GTAW process shows that there was maximum error of 0.395%calculated after comparing simulation and experimental shape factor. The simulation peaktemperature was 1387°C, 1300°C and 1250°C at 160 A, 140 A and 120 A respectively.Experimental results were 1350°C, 1280°C and 1235°C at above respective currents

Effect of Machining Parameters on Surface Finish and Noise Patterns for Machining EN-19 Steel with PVD-TiN Coated Mixed Ceramic Inserts in CNC Turning Operation

235-240This paper presents a relationship between the surface finish, machining conditions and the noise level generated by the turning operation for machining of EN-19 alloy steel using PVD-TiN coated mixed ceramic (Al2O3+TiCN) inserts on a CNC turning centre under wet lubrication conditions. The machining parameters considered in this study include cutting velocity, feed rate and depth of cut. The levels of machining parameters for the experimental investigation are determined using full factorial experiment model and ANOVA is applied to find the effect of machining parameters on surface roughness. Additionally, noise generated during the cutting operation for all set of experiment trials is recorded to determines the relationship between machining conditions and the surface finish

Detection and Identification of Camouflaged Targets using Hyperspectral and LiDAR data

Camouflaging is the process of merging the target with the background with the aim to reduce/delay its detection. It can be done using different materials/methods such as camouflaging nets, paints. Defence applications often require quick detection of camouflaged targets in a dynamic battlefield scenario. Though HSI data may facilitate detection of camouflaged targets but detection gets complicated due to issues (spectral variability, dimensionality). This paper presents a framework for detection of camouflaged target that allows military analysts to coordinate and utilise the expert knowledge for resolving camouflaged targets using remotely sensed data. Desired camouflaged target (set of three chairs as a target under a camouflaging net) has been resolved in three steps: First, hyperspectral data processing helps to detect the locations of potential camouflaged targets. It narrows down the location of the potential camouflaged targets by detecting camouflaging net using Independent component analysis and spectral matching algorithms. Second, detection and identification have been performed using LiDAR point cloud classification and morphological analysis. HSI processing helps to discard the redundant majority of LiDAR point clouds and support detailed analysis of only the minute portion of the point cloud data the system deems relevant. This facilitates extraction of salient features of the potential camouflaged target. Lastly, the decisions obtained have been fused to infer the identity of the desired targets. The experimental results indicate that the proposed approach may be used to successfully resolve camouflaged target assuming some a priori knowledge about the morphology of targets likely to be present.

Engineering of Deinococcus radiodurans R1 for bioprecipitation of uranium from dilute nuclear waste

Genetic engineering of radiation-resistant organisms to recover radionuclides/heavy metals from radioactive wastes is an attractive proposition. We have constructed a Deinococcus radiodurans strain harboring phoN, a gene encoding a nonspecific acid phosphatase, obtained from a local isolate of Salmonella enterica serovar Typhi. The recombinant strain expressed an ~27-kDa active PhoN protein and efficiently precipitated over 90% of the uranium from a 0.8 mM uranyl nitrate solution in 6 h. The engineered strain retained uranium bioprecipitation ability even after exposure to 6 kGy of 60Co gamma rays. The PhoN-expressing D. radiodurans offers an effective and eco-friendly in situ approach to biorecovery of uranium from dilute nuclear waste