scholarly journals An adaptive weighting algorithm for accurate radio tomographic image in the environment with multipath and WiFi interference

2017 ◽  
Vol 13 (1) ◽  
pp. 155014771668382 ◽  
Author(s):  
Manyi Wang ◽  
Zhonglei Wang ◽  
Xiongzhu Bu ◽  
Enjie Ding
Keyword(s):  
Radio Frequency ◽  
Field Experiments ◽  
State Of The Art ◽  
Interference Field ◽  
Multipath Interference ◽  
Adaptive Weighting ◽  
Tomography Image ◽  
Device Free ◽  
Localization Systems ◽  
Interference Problems

Radio frequency device-free localization based on wireless sensor network has proved its feasibility in buildings. With this technique, a target can be located relying on the changes of received signal strengths caused by the moving object. However, the accuracy of many such systems deteriorates seriously in the environment with WiFi and the multipath interference. State-of-the-art methods do not efficiently solve the WiFi and multipath interference problems at the same time. In this article, we propose and evaluate an adaptive weighting radio tomography image algorithm to improve the accuracy of radio frequency device-free localization in the environment with multipath and different intensity of WiFi interference. Field experiments prove that our approach outperforms the state-of-the-art radio frequency device-free localization systems in the environment with multipath and WiFi interference.

scholarly journals Turbulence and Flow–Sediment Interactions in Open-Channel Flows

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3169
Author(s):  
Roberto Gaudio
Keyword(s):  
Open Channel ◽  
Field Experiments ◽  
State Of The Art ◽  
Channel Flows ◽  
Special Issue ◽  
Panoramic View ◽  
Open Channel Flows ◽  
River Hydraulics ◽  
The World ◽  
Computing Skills

The main focus of this Special Issue of Water is the state-of-the-art and recent research on turbulence and flow–sediment interactions in open-channel flows. Our knowledge of river hydraulics is becoming deeper and deeper, thanks to both laboratory/field experiments related to the characteristics of turbulence and their link to the erosion, transport, deposition, and local scouring phenomena. Collaboration among engineers, physicists, and other experts is increasing and furnishing new inter/multidisciplinary perspectives to the research in river hydraulics and fluid mechanics. At the same time, the development of both sophisticated laboratory instrumentation and computing skills is giving rise to excellent experimental–numerical comparative studies. Thus, this Special Issue, with ten papers by researchers from many institutions around the world, aims at offering a modern panoramic view on all the above aspects to the vast audience of river researchers.

scholarly journals Analysis of Working Qualitative Parameters for No-Till Machines

2011 ◽  
Vol 68 (1) ◽  
Author(s):  
Ovidiu RANTA ◽  
Ioan DROCAS ◽  
Sorin STANILA ◽  
Adrian MOLNAR ◽  
Mircea Valentin MUNTEAN ◽  
...  
Keyword(s):  
Field Experiments ◽  
State Of The Art ◽  
Field Conditions ◽  
Laboratory Conditions ◽  
Experimental Teaching ◽  
No Till ◽  
Soil Bin ◽  
Teaching Facility

Autors was designed a system to modify the SPC romanian seeding machine for in order that it can be used for no-till technology. This machine was manufactured with the help of S.C. MECANICA M.A.R.I..U.S. S.A. in Cluj- Napoca and it was used in laboratory conditions in a state of the art soil bin of Hohenheim University, Stuttgart and in laboratory-field conditions. The field experiments were located on a plot of Experimental Teaching Facility of USAMV Cluj-Napoca, on aluviosol molic soil after SRTS – 200, in location Lunca Someşului Mic (Podişul Someşan) .

scholarly journals UWB fastly-tunable 0.5-50 GHz RF transmitter based on integrated photonics

2021 ◽  
Author(s):  
Fabio Falconi ◽  
Claudio Porzi ◽  
Filippo Scotti ◽  
Giovanni Serafino ◽  
Antonio Malacarne ◽  
...  
Keyword(s):  
Power Consumption ◽  
Radio Frequency ◽  
High Precision ◽  
Life Style ◽  
State Of The Art ◽  
Ultra Wideband ◽  
Robot Localization ◽  
Rf Transmitter ◽  
And Control ◽  
Large Tunability

Abstract In the last decade, the interest in software-defined ultra-wideband (UWB) and tunable radio frequency (RF) apparatuses with low size, weight, and power consumption (SWaP), has grown dramatically, pushed by the new 6G vision where, RF equipment shall enable a large number of fundamental applications as UWB communications, robot localization mapping and control and high precision radars, all of them contributing in revolutionizing our life style. Unfortunately, the coexistence of ultra-wideband and software-defined operation, tunability and low SWaP represents a big issue in the current RF technologies. In this article, to the best of our knowledge, the first example of a complete tunable software-defined RF transmitter with low footprint (i.e. on photonic chip) is presented exceeding the state-of-the-art for the extremely large tunability range of 0.5-50 GHz without any parallelization of narrower-band components and with fast tuning (<200micros). This first implementation, represents a breakthrough in microwave photonics.

scholarly journals Visual Navigation for Recovering an AUV by Another AUV in Shallow Water

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1889 ◽  
Author(s):  
Shuang Liu ◽  
Hongli Xu ◽  
Yang Lin ◽  
Lei Gao
Keyword(s):  
Shallow Water ◽  
Pose Estimation ◽  
Field Experiments ◽  
State Of The Art ◽  
Autonomous Underwater Vehicles ◽  
Visual Navigation ◽  
Ambient Light ◽  
Robust Detection ◽  
Novel Method ◽  
Coarse To Fine

Autonomous underwater vehicles (AUVs) play very important roles in underwater missions. However, the reliability of the automated recovery of AUVs has still not been well addressed. We propose a vision-based framework for automatically recovering an AUV by another AUV in shallow water. The proposed framework contains a detection phase for the robust detection of underwater landmarks mounted on the docking station in shallow water and a pose-estimation phase for estimating the pose between AUVs and underwater landmarks. We propose a Laplacian-of-Gaussian-based coarse-to-fine blockwise (LCB) method for the detection of underwater landmarks to overcome ambient light and nonuniform spreading, which are the two main problems in shallow water. We propose a novel method for pose estimation in practical cases where landmarks are broken or covered by biofouling. In the experiments, we show that our proposed LCB method outperforms the state-of-the-art method in terms of remote landmark detection. We then combine our proposed vision-based framework with acoustic sensors in field experiments to demonstrate its effectiveness in the automated recovery of AUVs.

scholarly journals Large-Scale Dataset for Radio Frequency-Based Device-Free Crowd Estimation

Data ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 52 ◽  
Author(s):  
Abdil Kaya ◽  
Stijn Denis ◽  
Ben Bellekens ◽  
Maarten Weyn ◽  
Rafael Berkvens
Keyword(s):  
Control System ◽  
Radio Frequency ◽  
Large Scale ◽  
Reference Data ◽  
Added Value ◽  
Size Estimation ◽  
Music Festival ◽  
Large Scale Dataset ◽  
Access Control System ◽  
Device Free

Organisers of events attracting many people have the important task to ensure the safety of the crowd on their venue premises. Measuring the size of the crowd is a critical first step, but often challenging because of occlusions, noise and the dynamics of the crowd. We have been working on a passive Radio Frequency (RF) sensing technique for crowd size estimation, and we now present three datasets of measurements collected at the Tomorrowland music festival in environments containing thousands of people. All datasets have reference data, either based on payment transactions or an access control system, and we provide an example analysis script. We hope that future analyses can lead to an added value for crowd safety experts.

Field experiments and public policy: festina lente

2020 ◽  
Vol 5 (1) ◽  
pp. 117-124 ◽  
Author(s):  
GLENN W. HARRISON
Keyword(s):  
Public Policy ◽  
Field Experiments ◽  
State Of The Art ◽  
Welfare Effects ◽  
Current State ◽  
To Receive

AbstractThe current state of the art in field experiments does not give me any confidence that we should be assuming that we have anything worth scaling, assuming we really care about the expected welfare of those about to receive the instant intervention. At the very least, we should be honest and explicit about the need for strong priors about the welfare effects of changes in averages of observables to warrant scaling. What we need is a healthy dose of theory and the implied econometrics.

scholarly journals AWR: Adaptive Weighting Regression for 3D Hand Pose Estimation

2020 ◽  
Vol 34 (07) ◽  
pp. 11061-11068 ◽  
Author(s):  
Weiting Huang ◽  
Pengfei Ren ◽  
Jingyu Wang ◽  
Qi Qi ◽  
Haifeng Sun
Keyword(s):  
State Of The Art ◽  
Input Modality ◽  
Hand Pose Estimation ◽  
Adaptive Weighting ◽  
Adaptive Weight ◽  
Joint Coordinates ◽  
Different Types ◽  
Dense Representation ◽  
Discrete Integration ◽  
Hand Pose

In this paper, we propose an adaptive weighting regression (AWR) method to leverage the advantages of both detection-based and regression-based method. Hand joint coordinates are estimated as discrete integration of all pixels in dense representation, guided by adaptive weight maps. This learnable aggregation process introduces both dense and joint supervision that allows end-to-end training and brings adaptability to weight maps, making network more accurate and robust. Comprehensive exploration experiments are conducted to validate the effectiveness and generality of AWR under various experimental settings, especially its usefulness for different types of dense representation and input modality. Our method outperforms other state-of-the-art methods on four publicly available datasets, including NYU, ICVL, MSRA and HANDS 2017 dataset.

scholarly journals Identifying GNSS Signals Based on Their Radio Frequency (RF) Features—A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom Generator

Data ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 18
Author(s):  
Ruben Morales-Ferre ◽  
Wenbo Wang ◽  
Alejandro Sanz-Abia ◽  
Elena-Simona Lohan
Keyword(s):  
Radio Frequency ◽  
Antenna Array ◽  
Classification Accuracy ◽  
State Of The Art ◽  
Data Use ◽  
General Purpose ◽  
Receiver Side ◽  
Raw Data ◽  
Front End ◽  
Signal Type

This is a data descriptor paper for a set of raw GNSS signals collected via roof antennas and Spectracom simulator for general-purpose uses. We give one example of possible data use in the context of Radio Frequency Fingerprinting (RFF) studies for signal-type identification based on front-end hardware characteristics at transmitter or receiver side. Examples are given in this paper of achievable classification accuracy of six of the collected signal classes. The RFF is one of the state-of-the-art, promising methods to identify GNSS transmitters and receivers, and can find future applicability in anti-spoofing and anti-jamming solutions for example. The uses of the provided raw data are not limited to RFF studies, but can extend to uses such as testing GNSS acquisition and tracking, antenna array experiments, and so forth.

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