The State of the Art in Real-Time Range Mapping — A Panel Discussion

This paper mainly surveys the state-of-the-art on real-time communicaton in industrial wireless local networks(WLANs), and also identifys the suitable approaches to deal with the real-time requirements in future. Firstly, this paper summarizes the features of industrial WLANs and the challenges it encounters. Then according to the real-time problems of industrial WLAN, the fundamental mechanism of each recent representative resolution is analyzed in detail. Meanwhile, the characteristics and performance of these resolutions are adequately compared. Finally, this paper concludes the current of the research and discusses the future development of industrial WLANs.

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Real-Time Docking Ring Detection Based on the Geometrical Shape for an On-Orbit Spacecraft

Sensors ◽

10.3390/s19235243 ◽

2019 ◽

Vol 19 (23) ◽

pp. 5243

Author(s):

Zhang ◽

Pan ◽

Ma

Keyword(s):

Least Squares ◽

Real Time ◽

Detection Method ◽

State Of The Art ◽

The State ◽

Selection Strategy ◽

Geometrical Shape ◽

Automatic Capture ◽

Rendezvous And Docking ◽

Real Time Application

Docking ring is a circular hatch of spacecraft that allows servicing spacecraft to dock in various space missions. The detection of the ring is greatly beneficial to automatic capture, rendezvous and docking. Based on its geometrical shape, we propose a real-time docking ring detection method for on-orbit spacecraft. Firstly, we extract arcs from the edge mask and classify them into four classes according to edge direction and convexity. By developing the arc selection strategy, we select a combination of arcs possibly belonging to the same ellipse, and then estimate its parameters via the least squares fitting technique. Candidate ellipses are validated according to the fitness of the estimation with the actual edge pixels. The experiments show that our method is superior to the state-of-the-art methods, and can be used in real time application. The method can also be extended to other applications.

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Summary of Panel Discussion “Substrate Issues for Wide Bandgap Semiconductors”

MRS Proceedings ◽

10.1557/proc-339-3 ◽

1994 ◽

Vol 339 ◽

Cited By ~ 2

Author(s):

Max N. Yoder ◽

Peter K. Bachmann

Keyword(s):

State Of The Art ◽

Panel Discussion ◽

Wide Bandgap ◽

The State ◽

Wide Bandgap Semiconductors ◽

Bandgap Semiconductors

The state-of-the-art in each of the major materials (Diamond, SiC and III-nitrides) was discussed with the advantages, disadvantages, and requirements of each enumerated.

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Real-time Arabic scene text detection using fully convolutional neural networks

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v11i2.pp1634-1640 ◽

2021 ◽

Vol 11 (2) ◽

pp. 1634

Author(s):

Rajae Moumen ◽

Raddouane Chiheb ◽

Rdouan Faizi

Keyword(s):

Real Time ◽

Data Augmentation ◽

State Of The Art ◽

Arabic Language ◽

Text Detection ◽

The State ◽

Convolutional Network ◽

Fully Convolutional Network ◽

Scene Text Detection ◽

Scene Text

The aim of this research is to propose a fully convolutional approach to address the problem of real-time scene text detection for Arabic language. Text detection is performed using a two-steps multi-scale approach. The first step uses light-weighted fully convolutional network: TextBlockDetector FCN, an adaptation of VGG-16 to eliminate non-textual elements, localize wide scale text and give text scale estimation. The second step determines narrow scale range of text using fully convolutional network for maximum performance. To evaluate the system, we confront the results of the framework to the results obtained with single VGG-16 fully deployed for text detection in one-shot; in addition to previous results in the state-of-the-art. For training and testing, we initiate a dataset of 575 images manually processed along with data augmentation to enrich training process. The system scores a precision of 0.651 vs 0.64 in the state-of-the-art and a FPS of 24.3 vs 31.7 for a VGG-16 fully deployed.

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Real-Time Communications in Wireless Sensor Networks

Next Generation Mobile Networks and Ubiquitous Computing ◽

10.4018/978-1-60566-250-3.ch008 ◽

2010 ◽

pp. 69-78

Author(s):

Isabelle Augé-Blum ◽

Fei Yang ◽

Thomas Watteyne

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Real Time ◽

State Of The Art ◽

Communication Protocols ◽

The State ◽

Sensor Nodes ◽

Wireless Sensor ◽

Future Trends ◽

Wireless Links

This chapter presents the state-of-the-art of real-time communication in the challenging topic of Wireless Sensor Networks (WSNs). In real-time communication, the duration between the event which initiates the sending of a message, and the instant this message is received must be smaller than a known delay. Because topologies are extremely dynamic and not known priori, this type of constraint is very hard to meet in WSNs. In this chapter, the different communication protocols proposed in the literatures, together with their respective advantages and drawbacks, are discussed. We focus on MAC and routing because they are key layers in real-time communication. As most existing protocols are not suitable under realistic constraints where sensor nodes and wireless links are unreliable, we give, at the end of this chapter, some insights about future trends in designing real-time protocols. We hope to give the reader an overview of recent research works in this complex topic which we consider to be essential in critical applications.

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Programming Interfaces for Realtime and Cloud-Based Computing

Computer Engineering ◽

10.4018/978-1-61350-456-7.ch412 ◽

2012 ◽

pp. 959-975

Author(s):

Gregory Katsaros ◽

Tommaso Cucinotta

Keyword(s):

Quality Of Service ◽

Real Time ◽

State Of The Art ◽

New Products ◽

The State ◽

New Challenges ◽

Real Time Computing ◽

Programming Interfaces ◽

Real Time Application

The appearance of different business roles according to this classification, potentially with differing interests, introduces new challenges with regard to the tools and mechanisms put in place in order to enable the efficient provisioning of services. Security, Quality of Service (QoS) assurance, and real-time capabilities are just a few issues that the providers are trying to tackle and integrate within the new products and services that they offer. In this chapter, we make an overview of the approaches that aim to APIs for real-time computing. In the first part of this chapter, several Real-Time Application Interfaces will be presented and compared. After that, we will document the state-of-the-art regarding the Cloud APIs available and analyze the architecture and the technologies that they support.

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Recent Advances in 3D Human Pose Estimation: From Optimization to Implementation and Beyond

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001422550035 ◽

2022 ◽

Author(s):

Jielu Yan ◽

MingLiang Zhou ◽

Jinli Pan ◽

Meng Yin ◽

Bin Fang

Keyword(s):

Real Time ◽

Pose Estimation ◽

Recent Progress ◽

State Of The Art ◽

The State ◽

Human Pose Estimation ◽

Estimation Techniques ◽

Comprehensive Survey ◽

Human Pose ◽

3D Human Pose Estimation

3D human pose estimation describes estimating 3D articulation structure of a person from an image or a video. The technology has massive potential because it can enable tracking people and analyzing motion in real time. Recently, much research has been conducted to optimize human pose estimation, but few works have focused on reviewing 3D human pose estimation. In this paper, we offer a comprehensive survey of the state-of-the-art methods for 3D human pose estimation, referred to as pose estimation solutions, implementations on images or videos that contain different numbers of people and advanced 3D human pose estimation techniques. Furthermore, different kinds of algorithms are further subdivided into sub-categories and compared in light of different methodologies. To the best of our knowledge, this is the first such comprehensive survey of the recent progress of 3D human pose estimation and will hopefully facilitate the completion, refinement and applications of 3D human pose estimation.

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Networking Based on ZigBee Technology for Wireless Physiological Signals Aquisition

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.263-266.898 ◽

2012 ◽

Vol 263-266 ◽

pp. 898-904

Author(s):

Xiu Ling Liu ◽

Lei Qiao ◽

Xiaoyu Zhu ◽

Haijun Sun ◽

Hong Rui Wang

Keyword(s):

Disease Prevention ◽

Real Time ◽

Monitoring System ◽

Short Distance ◽

State Of The Art ◽

Health Surveillance ◽

The State ◽

Physiological Signals ◽

Real Time Monitoring ◽

Zigbee Technology

This paper introduces a monitoring system for health surveillance with the modern wireless communication.On the basis of predecessors' work, a remote heath monitoring system is designed based on Zigbee and human-computer interacting technology, which uses real-time monitoring in the field of disease prevention and rehabilitation. Every node is introduced and the results show that this system overcomes short distance and inconvenience of the state-of-the-art systems.

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Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering

The Scientific World JOURNAL ◽

10.1155/2015/671360 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11

Author(s):

Yang Yang ◽

Jun Zhang ◽

Kai-quan Cai

Keyword(s):

Real Time ◽

State Of The Art ◽

Air Traffic ◽

The State ◽

Traffic Situation ◽

Trajectory Clustering ◽

The Real ◽

Preliminary Results ◽

Intent Modeling ◽

Terminal Area

Terminal-area aircraft intent inference (T-AII) is a prerequisite to detect and avoid potential aircraft conflict in the terminal airspace. T-AII challenges the state-of-the-art AII approaches due to the uncertainties of air traffic situation, in particular due to the undefined flight routes and frequent maneuvers. In this paper, a novel T-AII approach is introduced to address the limitations by solving the problem with two steps that are intent modeling and intent inference. In the modeling step, an online trajectory clustering procedure is designed for recognizing the real-time available routes in replacing of the missed plan routes. In the inference step, we then present a probabilistic T-AII approach based on the multiple flight attributes to improve the inference performance in maneuvering scenarios. The proposed approach is validated with real radar trajectory and flight attributes data of 34 days collected from Chengdu terminal area in China. Preliminary results show the efficacy of the presented approach.

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Building a Real-Time 2D Lidar Using Deep Learning

Journal of Robotics ◽

10.1155/2021/6652828 ◽

2021 ◽

Vol 2021 ◽

pp. 1-7

Author(s):

Nadim Arubai ◽

Omar Hamdoun ◽

Assef Jafar

Keyword(s):

Deep Learning ◽

Real Time ◽

Obstacle Avoidance ◽

Tilt Angle ◽

State Of The Art ◽

The State ◽

Prediction Problem ◽

Learning Methods ◽

Depth Prediction ◽

Avoidance Problem

Applying deep learning methods, this paper addresses depth prediction problem resulting from single monocular images. A vector of distances is predicted instead of a whole image matrix. A vector-only prediction decreases training overhead and prediction periods and requires less resources (memory, CPU). We propose a module which is more time efficient than the state-of-the-art modules ResNet, VGG, FCRN, and DORN. We enhanced the network results by training it on depth vectors from other levels (we get a new level by changing the Lidar tilt angle). The predicted results give a vector of distances around the robot, which is sufficient for the obstacle avoidance problem and many other applications.

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