scholarly journals Estimate a Flexible Link’s Shape by the Use of Strain Gauge Sensors

ISRN Robotics ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
M. H. Korayem ◽  
A. M. Shafei ◽  
F. Absalan
Keyword(s):  
Wheatstone Bridge ◽  
Curvature Function ◽  
Flexible Link ◽  
Data Logger ◽  
Precision Data ◽  
Interpolation Technique ◽  
Finite Set ◽  
High Precision Data ◽  
Continuous Curvature

This paper presents a method for estimating the flexible link’s shape by finite number of sensors. The position and orientation of flexible link are expressed as a function of curvature of the link. An interpolation technique gives this continuous curvature function from a finite set of the Wheatstone bridge made with strain gauges. For interpolation we can use different functions to find better way for estimation of link’s shape. Comparison between different types of function can show us best corresponding with nature of the link. Our case study is a single flexible link robot. A high-precision data logger is used as data acquisition instrument.

scholarly journals MICROVEGA (MICRO VESSEL FOR GEODETICS APPLICATION): A MARINE DRONE FOR THE ACQUISITION OF BATHYMETRIC DATA FOR GIS APPLICATIONS

2015 ◽  
Vol XL-5/W5 ◽  
pp. 123-130 ◽  
Author(s):  
F. Giordano ◽  
G. Mattei ◽  
C. Parente ◽  
F. Peluso ◽  
R. Santamaria
Keyword(s):  
3D Models ◽  
Precision Data ◽  
Typical Application ◽  
Bathymetric Data ◽  
Research Fields ◽  
Gis Applications ◽  
First Case ◽  
High Precision Data ◽  
Unmanned Surface Vessel

Bathymetric data are fundamental to produce navigational chart and sea-floor 3D models. They can be collected using different techniques and sensors on board of a variety of platforms, such as satellite, aircraft, ship and drone. The MicroVEGA drone is an Open Prototype of Autonomous Unmanned Surface Vessel (AUSV) conceived, designed and built to operate in the coastal areas (0-20 meters of depth), where a traditional boat is poorly manoeuvrable. It is equipped with a series of sensors to acquire the morpho-bathymetric high precision data. In this paper we presents the result of the first case study, a bathymetric survey carried out at Sorrento Marina Grande. This survey is a typical application case of this technology; the Open Prototype MicroVega has an interdisciplinary breath and it is going to be applied to various research fields. In future, it will expect to do new knowledge, new survey strategies and an industrial prototype in fiberglass.

scholarly journals Study of the Natural Heritage Condition of the Kursiu Nerija National Park Using Lidar Technology (Case Study of Agila Dune)

2019 ◽  
Vol 10 ◽  
pp. 36-42
Author(s):  
Deimante Pankauskyte ◽  
Jolanta Valciukiene ◽  
Indrius Kuklys ◽  
Lina Kukliene
Keyword(s):  
Cross Section ◽  
Cross Sections ◽  
National Park ◽  
Large Scale ◽  
Precision Data ◽  
Protective Measures ◽  
Current State ◽  
The Status ◽  
High Precision Data

Analysis of the condition of the Agila dune is presented in this Article. The analysis is based on data collected during accurate geodetic measurements using LIDAR technology. The current state of the Agila dune was compared to the data of the previous year's LIDAR points in order to ensure the reliability and value of the research. In the course of the study, eleven cross sections were compared by height differences with previous year‘s measurements. The condition of the Agila dune was found to be the worst in three cross sections. First cross section‘s erosion measured at 13,98 meters, erosion in the fifth cross section – 9.90 meters, and erosion in the eighth cross section - 11.34 meters. The main reasons for the deterioration of the natural values of the Kursiu Nerija National Park are climate, wind, high visitor flows and the persistent failure to carry out comprehensive research. Therefore, in order to preserve these unique natural values, it is important to collect large-scale and high-precision data on the status of these values, to systematize, analyze and take appropriate protective measures.

scholarly journals Deep learning-aided high-precision data detection for massive MU-MIMO systems

2021 ◽  
Vol 336 ◽  
pp. 04007
Author(s):  
Sen Yang ◽  
Zerun Li ◽  
Jinhui Wei ◽  
Zuocheng Xing
Keyword(s):  
Mimo Systems ◽  
Detection Algorithm ◽  
Iterative Detection ◽  
Data Detection ◽  
Wireless System ◽  
Precision Data ◽  
Efficient Detection ◽  
High Precision Data ◽  
Complexity Cost ◽  
Iteration Parameters

The data detector for future wireless system needs to achieve high throughput and low bit error rate (BER) with low computational complexity. In this paper, we propose a deep neural networks (DNNs) learning aided iterative detection algorithm. We first propose a convex optimization-based method for calculating the efficient detection of iterative soft output data, and then propose a method for adjusting the iteration parameters using the powerful data driven by DNNs, which achieves fast convergence and strong robustness. The results show that the proposed method can achieve the same performance as the known algorithm at a lower computation complexity cost.

scholarly journals NATURAL INFLATION, PLANCK SCALE PHYSICS AND OSCILLATING PRIMORDIAL SPECTRUM

2005 ◽  
Vol 14 (08) ◽  
pp. 1347-1364 ◽  
Author(s):  
XIULIAN WANG ◽  
BO FENG ◽  
MINGZHE LI ◽  
XUE-LEI CHEN ◽  
XINMIN ZHANG
Keyword(s):  
Power Spectrum ◽  
Cosmic Microwave Background ◽  
High Frequency ◽  
Large Scale ◽  
Planck Scale ◽  
Microwave Background ◽  
Precision Data ◽  
Inflation Model ◽  
High Precision Data ◽  
Planck Scale Physics

In the "natural inflation" model, the inflaton potential is periodic. We show that Planck scale physics may induce corrections to the inflaton potential, which is also periodic with a greater frequency. Such high frequency corrections produce oscillating features in the primordial fluctuation power spectrum, which are not entirely excluded by the current observations and may be detectable in high precision data of cosmic microwave background (CMB) anisotropy and large scale structure (LSS) observations.

A Reinforcement Learning - Great-Deluge Hyper-Heuristic for Examination Timetabling

2010 ◽  
Vol 1 (1) ◽  
pp. 39-59 ◽  
Author(s):  
Ender Özcan ◽  
Mustafa Misir ◽  
Gabriela Ochoa ◽  
Edmund K. Burke
Keyword(s):  
Reinforcement Learning ◽  
Complete Solution ◽  
Examination Timetabling ◽  
Low Level ◽  
Termination Criteria ◽  
Candidate Solution ◽  
Wide Range ◽  
Finite Set ◽  
Different Characteristics

Hyper-heuristics can be identified as methodologies that search the space generated by a finite set of low level heuristics for solving search problems. An iterative hyper-heuristic framework can be thought of as requiring a single candidate solution and multiple perturbation low level heuristics. An initially generated complete solution goes through two successive processes (heuristic selection and move acceptance) until a set of termination criteria is satisfied. A motivating goal of hyper-heuristic research is to create automated techniques that are applicable to a wide range of problems with different characteristics. Some previous studies show that different combinations of heuristic selection and move acceptance as hyper-heuristic components might yield different performances. This study investigates whether learning heuristic selection can improve the performance of a great deluge based hyper-heuristic using an examination timetabling problem as a case study.

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