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Ramana Babu, B.
- Statistically Efficient Control Scheme for Undersea Surveillance for Sonar Ranging and Detection
Authors
1 Department of Computer Science and Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
Source
Indian Journal of Automation and Artificial Intelligence, Vol 4, No 1 (2017), Pagination: 1-9Abstract
Background/Objectives: Altered Gain Extended Kalman Filter (MGEKF) created by Song and Speyer was ended up being reasonable calculation for edges of just uninvolved target following applications in air. As of late, roughly changed increases are exhibited, which are numerically steady and precise. In this paper, this enhanced MGEKF calculation is investigated for submerged applications with a few adjustments.
Methods/Statistical Analysis: In submerged, the clamor in the estimations is high, turning rate of the stages is low and speed of the stages is additionally low when contrasted and the rockets in air.
Findings: These attributes of the stage are considered in detail and the calculation is changed appropriately to track applications in submerged. Monte-Carlo mimicked comes about for two regular situations are exhibited with the end goal of clarification.
Application/Improvements: From the outcomes it is watched that this calculation is particularly reasonable for this nonlinear edges just latent target following.
Keywords
Estimation, Sonar, Kalman Filter, Simulation, Modified Gain, Angles-Only Target Tracking.Full Text
References
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- RFA:Reanalyze Requests for ADMINSHIP over the Wikipedia
Authors
1 Department of Computer Science and Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
2 Department of Computer Science and Engineering, Avanthi Institute of Engineering & Technology, KOTABHOGAPURAM, Andhra Pradesh 535006, IN
3 Department of Computer Science and Engineering, Andhra University College of Engineering (A), Visakhapatnam, IN
4 Department of Computer Science and Engineering, AVANTHI Institute of Engineering & Technology, NARSIPATNAM, Andhra Pradesh, IN
Source
Indian Journal of Automation and Artificial Intelligence, Vol 4, No 1 (2017), Pagination: 1-8Abstract
Objectives: Requests for ADMINSHIP (RFA) within Wikipedia are primarily focused on the impact of the relationship between ADMINSHIP candidates and voters on RFA success. Very few studies, however, have investigated how candidates’ contributions may predict their success in the RFA process.
Methods/Statistical Analysis: In this examination, we look at the effect of substance and social commitments and in addition add up to commitments made by ADMINSHIP hopefuls on the group's general choice in the matter of whether to elevate the possibility to head.
Findings: We also assess the influence of clarity of contribution on RFA success. To do so, we collected data on 754 RFA cases and used logistic regression to test four hypotheses.
Application/Improvements: Our results highlight the important role that user contribution behaviors and activity history have on the user’s success in the RFA process. The outcomes additionally propose that residency and number of RFA endeavors assume a part in the RFA procedure. Our discoveries have suggestions for hypothesis and practice.
Keywords
Requests for ADMINSHIP (RFA), Content Contribution, Administrators, Trust, Wikipedia, Social Contribution.Full Text
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