A Simulation Tool for Real-Time Hybrid-Cooperative Positioning Algorithms

2012 ◽  
Vol 3 (3) ◽  
pp. 67-87 ◽  
Author(s):  
Francesco Sottile ◽  
Mauricio A. Caceres ◽  
Maurizio A. Spirito
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Wireless Network ◽  
P2p Network ◽  
Simulation Tool ◽  
Positioning Accuracy ◽  
Cooperative Positioning ◽  
Pseudorange Noise ◽  
High Level ◽  
Improved Accuracy

The authors propose a simulation tool (ST) able to test real-time hybrid GNSS/terrestrial and cooperative positioning algorithms that fuse both pseudorange measurements from satellites and terrestrial range measurements based on radio frequency communication performed between nodes of a wireless network. In particular, the ST simulates devices belonging to a peer-to-peer (P2P) wireless network where peers, equipped also with a GNSS receiver, cooperate among them by exchanging aiding data in order to improve both positioning accuracy and availability. Furthermore, the authors propose a method to increase the robustness of cooperative algorithms based on the estimated position covariance matrix. In particular, the proposed approach assures a faster estimation convergence and improved accuracy while lowering computational complexity and network traffic. Finally, the authors tested the sensitivity of the implemented positioning algorithms through the ST in two different scenarios, first in presence of high level of pseudorange noise and then in presence of a malicious peer in the P2P network.

Analysis of Real-Time Hybrid-Cooperative GNSS-Terrestrial Positioning Algorithms

2014 ◽  
pp. 178-204
Author(s):  
Francesco Sottile ◽  
Zhoubing Xiong ◽  
Claudio Pastrone
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Peer To Peer ◽  
P2p Network ◽  
Simulation Tool ◽  
Positioning Accuracy ◽  
Gnss Receiver ◽  
Hybrid Positioning ◽  
Overall Performance ◽  
Wireless Interface

This chapter analyzes some hybrid and cooperative GNSS-terrestrial positioning algorithms that combine both pseudorange measurements from satellites and terrestrial range measurements based on radio frequency communication to improve both positioning accuracy and availability. A Simulation Tool (ST) is also presented as a viable tool able to test and evaluate the performance of these hybrid positioning algorithms in different scenarios. In particular, the ST simulates devices belonging to a Peer-to-Peer (P2P) wireless network where peers, equipped with a wireless interface and a GNSS receiver, cooperate among them by exchanging positioning aiding data in order to enhance the overall performance. Different hybrid and cooperative algorithms, based on Bayesian and least squares approaches proposed in the literature, have been implemented in the ST and simulated in different simulation scenarios including the vehicular urban one. Moreover, all these algorithms are compared in terms of computational complexity to better understand their feasibility to achieve a real-time implementation. Finally, the sensitivity of the hybrid and cooperative algorithms when pseudorange measurements are affected by large noise and in presence of malicious peers in the P2P network is also assessed by means of the ST.

Cooperative Positioning Based on Hybrid Information

2013 ◽  
Vol 694-697 ◽  
pp. 940-946 ◽  
Author(s):  
Xiang Hui Zeng ◽  
Hong Tao Hou ◽  
Qiang Chang ◽  
Qun Li ◽  
Wei Ping Wang
Keyword(s):  
Wireless Network ◽  
Series Expansion ◽  
Taylor Series ◽  
Taylor Series Expansion ◽  
Least Square ◽  
Positioning Accuracy ◽  
Localization Method ◽  
Cooperative Positioning ◽  
Simulation Results

A new localization method has been proposed to overcome the limitations of systems relying on GPS or other terrestrial infrastructure. This method fuses both pseudorange measurements from GNSS satellites and RSSI-based ranging measurements between peers of a wireless network, and uses improved collaborative subtree algorithm to partition the network. In each collaborative subtree, the nodes’ positions can be computed by using the least square algorithm based on Taylor series expansion-based. Simulation results showed that this method improves both availability and positioning accuracy.

Autonomous framework simulation tools for real-time multimedia streaming over wireless ad-hoc networks

SIMULATION ◽  
2019 ◽  
Vol 96 (2) ◽  
pp. 185-197
Author(s):  
Adel A Ahmed ◽  
Omar Barukab
Keyword(s):  
Real Time ◽  
Wireless Network ◽  
Multimedia Streaming ◽  
Transport Layer ◽  
Simulation Tool ◽  
Simulation Tools ◽  
Streaming Applications ◽  
Network Technologies ◽  
Transport Layer Protocols

Real-time video communication has become one of the most significant applications extensively used by homogeneous/heterogeneous wireless network technologies, such as Wi-Fi, the Internet of things, the wireless sensor network (WSN), 5G, etc. This leads to enhanced deployment of multimedia streaming applications over wireless network technologies. In order to accomplish the optimal performance of real-time multimedia streaming applications over the homogeneous/heterogeneous wireless network, it is therefore necessary to develop a simulation tool-set that effectively measures the quality of service (QoS) for different multimedia streaming applications over transport layer protocols. This paper proposes an autonomous simulation tool (AST) that is entirely independent from the source code of transport layer protocols. Furthermore, the AST is integrated into NS-2 to evaluate the QoS of real-time video streaming over numerous transport layer protocols and it uses new QoS measurement tools to test the video delivery quality based on I-frames to speeds up the assessment of multimedia streaming quality and ensure high accuracy of performance metrics. The simulation results show that using the AST to simulate real-time multimedia stream results in between 13% and 36% higher delivery ratio and 150–250% less cumulative jitter delay compared with using baseline simulation tools. Also, the AST guarantees an optimal QoS performance measurements in terms of the peak signal-to-noise Ratio and visual quality of the received video.

A Highly Efficient and Optimised Simulation Based Multi objective Decision-Making for FMS Control

2018 ◽  
Vol 6 (6) ◽  
pp. 98
Author(s):  
Shreyanshu Parhi ◽  
S. C. Srivastava
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Manufacturing Industry ◽  
Simulation Software ◽  
Shop Floor ◽  
Simulation Tool ◽  
Routing Flexibility ◽  
Decision System ◽  
Multi Objective ◽  
Arena Simulation

Optimized and efficient decision-making systems is the burning topic of research in modern manufacturing industry. The aforesaid statement is validated by the fact that the limitations of traditional decision-making system compresses the length and breadth of multi-objective decision-system application in FMS.  The bright area of FMS with more complexity in control and reduced simpler configuration plays a vital role in decision-making domain. The decision-making process consists of various activities such as collection of data from shop floor; appealing the decision-making activity; evaluation of alternatives and finally execution of best decisions. While studying and identifying a suitable decision-making approach the key critical factors such as decision automation levels, routing flexibility levels and control strategies are also considered. This paper investigates the cordial relation between the system ideality and process response time with various prospective of decision-making approaches responsible for shop-floor control of FMS. These cases are implemented to a real-time FMS problem and it is solved using ARENA simulation tool. ARENA is a simulation software that is used to calculate the industrial problems by creating a virtual shop floor environment. This proposed topology is being validated in real time solution of FMS problems with and without implementation of decision system in ARENA simulation tool. The real-time FMS problem is considered under the case of full routing flexibility. Finally, the comparative analysis of the results is done graphically and conclusion is drawn.

Spatial Interpolators for Intra-Frame Resampling of SAR Videos: A Comparative Study Using Real-Time HD, Medical and Radar Data

2020 ◽  
Vol 15 (2) ◽  
pp. 144-196 ◽  
Author(s):  
Mohammad R. Khosravi ◽  
Sadegh Samadi ◽  
Reza Mohseni
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Video Compression ◽  
Nearest Neighbor ◽  
Radar Data ◽  
Edge Preservation ◽  
Edge Information ◽  
Video Codecs ◽  
Comparative Results ◽  
Interesting Area

Background: Real-time video coding is a very interesting area of research with extensive applications into remote sensing and medical imaging. Many research works and multimedia standards for this purpose have been developed. Some processing ideas in the area are focused on second-step (additional) compression of videos coded by existing standards like MPEG 4.14. Materials and Methods: In this article, an evaluation of some techniques with different complexity orders for video compression problem is performed. All compared techniques are based on interpolation algorithms in spatial domain. In details, the acquired data is according to four different interpolators in terms of computational complexity including fixed weights quartered interpolation (FWQI) technique, Nearest Neighbor (NN), Bi-Linear (BL) and Cubic Cnvolution (CC) interpolators. They are used for the compression of some HD color videos in real-time applications, real frames of video synthetic aperture radar (video SAR or ViSAR) and a high resolution medical sample. Results: Comparative results are also described for three different metrics including two reference- based Quality Assessment (QA) measures and an edge preservation factor to achieve a general perception of various dimensions of the mentioned problem. Conclusion: Comparisons show that there is a decidable trade-off among video codecs in terms of more similarity to a reference, preserving high frequency edge information and having low computational complexity.

scholarly journals Graph-Based Construction of 3D Korean Giwa House Models

Buildings ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 68
Author(s):  
Mankyu Sung
Keyword(s):  
Data Structure ◽  
Computer Graphics ◽  
Real Time ◽  
Texture Image ◽  
Time Rate ◽  
Commercial Software ◽  
Spline Curve ◽  
High Level ◽  
Complicated Part ◽  
Different Parts

This paper proposes a graph-based algorithm for constructing 3D Korean traditional houses automatically using a computer graphics technique. In particular, we target designing the most popular traditional house type, a giwa house, whose roof is covered with a set of Korean traditional roof tiles called giwa. In our approach, we divided the whole design processes into two different parts. At a high level, we propose a special data structure called ‘modeling graphs’. A modeling graph consists of a set of nodes and edges. A node represents a particular component of the house and an edge represents the connection between two components with all associated parameters, including an offset vector between components. Users can easily add/ delete nodes and make them connect by an edge through a few mouse clicks. Once a modeling graph is built, then it is interpreted and rendered on a component-by-component basis by traversing nodes in a procedural way. At a low level, we came up with all the required parameters for constructing the components. Among all the components, the most beautiful but complicated part is the gently curved roof structures. In order to represent the sophisticated roof style, we introduce a spline curve-based modeling technique that is able to create curvy silhouettes of three different roof styles. In this process, rather than just applying a simple texture image onto the roof, which is widely used in commercial software, we actually laid out 3D giwa tiles on the roof seamlessly, which generated more realistic looks. Through many experiments, we verified that the proposed algorithm can model and render the giwa house at a real time rate.

scholarly journals Efficient End-to-End Sentence-Level Lipreading with Temporal Convolutional Networks

2021 ◽  
Vol 11 (15) ◽  
pp. 6975
Author(s):  
Tao Zhang ◽  
Lun He ◽  
Xudong Li ◽  
Guoqing Feng
Keyword(s):  
Performance Improvement ◽  
State Of The Art ◽  
Error Rates ◽  
Convolutional Network ◽  
Convolutional Networks ◽  
Sentence Level ◽  
End To End ◽  
High Level ◽  
Improved Accuracy ◽  
Talking Face

Lipreading aims to recognize sentences being spoken by a talking face. In recent years, the lipreading method has achieved a high level of accuracy on large datasets and made breakthrough progress. However, lipreading is still far from being solved, and existing methods tend to have high error rates on the wild data and have the defects of disappearing training gradient and slow convergence. To overcome these problems, we proposed an efficient end-to-end sentence-level lipreading model, using an encoder based on a 3D convolutional network, ResNet50, Temporal Convolutional Network (TCN), and a CTC objective function as the decoder. More importantly, the proposed architecture incorporates TCN as a feature learner to decode feature. It can partly eliminate the defects of RNN (LSTM, GRU) gradient disappearance and insufficient performance, and this yields notable performance improvement as well as faster convergence. Experiments show that the training and convergence speed are 50% faster than the state-of-the-art method, and improved accuracy by 2.4% on the GRID dataset.

scholarly journals Real-Time High-Level Acute Pain Detection Using a Smartphone and a Wrist-Worn Electrodermal Activity Sensor

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3956
Author(s):  
Youngsun Kong ◽  
Hugo F. Posada-Quintero ◽  
Ki H. Chon
Keyword(s):  
Real Time ◽  
Electrodermal Activity ◽  
Smartphone Application ◽  
Real Time Processing ◽  
Pain Stimulation ◽  
Significant Difference ◽  
Before And After ◽  
Electrical Pulses ◽  
Pain Detection ◽  
High Level

The subjectiveness of pain can lead to inaccurate prescribing of pain medication, which can exacerbate drug addiction and overdose. Given that pain is often experienced in patients’ homes, there is an urgent need for ambulatory devices that can quantify pain in real-time. We implemented three time- and frequency-domain electrodermal activity (EDA) indices in our smartphone application that collects EDA signals using a wrist-worn device. We then evaluated our computational algorithms using thermal grill data from ten subjects. The thermal grill delivered a level of pain that was calibrated for each subject to be 8 out of 10 on a visual analog scale (VAS). Furthermore, we simulated the real-time processing of the smartphone application using a dataset pre-collected from another group of fifteen subjects who underwent pain stimulation using electrical pulses, which elicited a VAS pain score level 7 out of 10. All EDA features showed significant difference between painless and pain segments, termed for the 5-s segments before and after each pain stimulus. Random forest showed the highest accuracy in detecting pain, 81.5%, with 78.9% sensitivity and 84.2% specificity with leave-one-subject-out cross-validation approach. Our results show the potential of a smartphone application to provide near real-time objective pain detection.

scholarly journals Robotic-arm assisted total knee arthroplasty is associated with improved accuracy and patient reported outcomes: a systematic review and meta-analysis

2021 ◽  
Author(s):  
Junren Zhang ◽  
Wofhatwa Solomon Ndou ◽  
Nathan Ng ◽  
Paul Gaston ◽  
Philip M. Simpson ◽  
...  
Keyword(s):  
Learning Curve ◽  
Functional Outcomes ◽  
Patient Reported Outcomes ◽  
Meta Analysis ◽  
Robotic Arm ◽  
Component Position ◽  
Positioning Accuracy ◽  
Patient Reported ◽  
Total Knee ◽  
Improved Accuracy

AbstractThis systematic review and meta-analysis were conducted to compare the accuracy of component positioning, alignment and balancing techniques employed, patient-reported outcomes, and complications of robotic-arm assisted total knee arthroplasty (RATKA) with manual TKA (mTKA) and the associated learning curve. Searches of PubMed, Medline and Google Scholar were performed in October 2020 using PRISMA guidelines. Search terms included “robotic”, “knee” and “arthroplasty”. The criteria for inclusion were published clinical research articles reporting the learning curve for RATKA and those comparing the component position accuracy, alignment and balancing techniques, functional outcomes, or complications with mTKA. There were 198 articles identified, following full text screening, 16 studies satisfied the inclusion criteria and reported the learning curve of rTKA (n=5), component positioning accuracy (n=6), alignment and balancing techniques (n=7), functional outcomes (n=7), or complications (n=5). Two studies reported the learning curve using CUSUM analysis to establish an inflexion point for proficiency which ranged from 7 to 11 cases and there was no learning curve for component positioning accuracy. The meta-analysis showed a significantly lower difference between planned component position and implanted component position, and the spread was narrower for RATKA compared with the mTKA group (Femur coronal: mean 1.31, 95% confidence interval (CI) 1.08–1.55, p<0.00001; Tibia coronal: mean 1.56, 95% CI 1.32–1.81, p<0.00001). Three studies reported using different alignment and balancing techniques between mTKA and RATKA, two studies used the same for both group and two studies did not state the methods used in their RATKA groups. RATKA resulted in better Knee Society Score compared to mTKA in the short-to-mid-term follow up (95%CI [− 1.23,  − 0.51], p=0.004). There was no difference in arthrofibrosis, superficial and deep infection, wound dehiscence, or overall complication rates. RATKA demonstrated improved accuracy of component positioning and patient-reported outcomes. The learning curve of RATKA for operating time was between 7 and 11 cases. Future well-powered studies on RATKAs should report on the knee alignment and balancing techniques utilised to enable better comparisons on which techniques maximise patient outcomes.Level of evidence III.

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