scholarly journals Real-Time Dry Beach Length Monitoring for Tailings Dams Based on Visual Measurement

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Jun Hu ◽  
Shan Hu ◽  
Fei Kang ◽  
Jianhua Zhang
Keyword(s):  
Real Time ◽  
Health Monitoring ◽  
Reliable Method ◽  
High Accuracy ◽  
Experimental Results ◽  
Tailings Dam ◽  
Visual Measurement ◽  
Tailings Dams ◽  
Novel Method ◽  
Length Determination

The length of dry beach is an important factor that influences the safety of tailings dams. However, there still is no accurate and reliable method that can conveniently measure the length of dry beach. In this paper, the authors focus on developing a novel method for dry beach length determination. The proposed method can effectively measure the dry beach length through an ordinary camera and four marking rods placed on the dry beach. Experimental results show that the proposed method can conveniently measure the dry beach length with high accuracy, and therefore it can be adopted as an effective method in tailings dam real-time health monitoring.

scholarly journals High-Accuracy Tracking Using Ultrawideband Signals for Enhanced Safety of Cyclists

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Davide Dardari ◽  
Nicoló Decarli ◽  
Anna Guerra ◽  
Ashraf Al-Rimawi ◽  
Víctor Marín Puchades ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
High Accuracy ◽  
Experimental Results ◽  
Localization Error ◽  
Localization System ◽  
Dynamic Conditions ◽  
The Road ◽  
Road Users

In this paper, an ultrawideband localization system to improve the cyclists’ safety is presented. The architectural solutions proposed consist of tags placed on bikes, whose positions have to be estimated, and anchors, acting as reference nodes, located at intersections and/or on vehicles. The peculiarities of the localization system in terms of accuracy and cost enable its adoption with enhanced risk assessment units situated on the infrastructure/vehicle, depending on the architecture chosen, as well as real-time warning to the road users. Experimental results reveal that the localization error, in both static and dynamic conditions, is below 50 cm in most of the cases.

scholarly journals A Novel Method for the Enhancement of Wi-Fi Security Software System

2019 ◽  
Vol 8 (6) ◽  
pp. 905-909
Keyword(s):  
User Interface ◽  
Real Time ◽  
Fog Computing ◽  
Experimental Results ◽  
Wireless Access ◽  
Software System ◽  
Security Software ◽  
Novel Method ◽  
Current Systems ◽  
System Analyzing

This paper proposes a novel method for enhancing current Wi-Fi security software system analyzing user’s wireless access behavior. The system secures the user from security hazards during the pre-connection, connection, and afterconnection phases. The system can analyze and plot the Wi-Fi environment. The methods of fog computing and sending fake traffic are employed to protect PSK from sniffing. In the post connection phase, it identifies De-auth attack in real time and footmarks the attacker. The software functionalities are implemented and all the malicious entities are displayed on the User Interface (UI). The experimental results have shown that the system has better performance when compared with current systems. The system can be used for the security of Wi-Fi users

Extracting Commonsense Knowledge Using Concepts Properties

2012 ◽  
pp. 341-353
Author(s):  
Eduardo Blanco ◽  
Hakki C. Cankaya ◽  
Dan Moldovan
Keyword(s):  
Semantic Representation ◽  
High Accuracy ◽  
Experimental Results ◽  
Human Interaction ◽  
Semantic Relations ◽  
Commonsense Knowledge ◽  
Novel Method ◽  
Basic Semantic

Commonsense knowledge encompasses facts that people know but do not communicate most of the time. For example, one needs water and soap to take a shower is commonsense. This chapter presents a semantically grounded method for extracting commonsense knowledge. First, commonsense rules are identified, e.g., one cannot see imaginary objects. Second, those rules are combined with a basic semantic representation in order to infer commonsense facts, e.g. one cannot see a flying carpet. Further combinations of semantic relations with inferred commonsense facts are proposed and analyzed. Experimental results show that this novel method is able to extract thousands of commonsense facts with little human interaction and high accuracy.

scholarly journals Prevention of Unintended Appearance in Photos Based on Human Behavior Analysis

Information ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 468
Author(s):  
Yuhi Kaihoko ◽  
Phan Xuan Tan ◽  
Eiji Kamioka
Keyword(s):  
Social Networks ◽  
Dynamic Programming ◽  
Behavior Analysis ◽  
Real Time ◽  
Human Behavior ◽  
Social Problem ◽  
High Accuracy ◽  
Experimental Results ◽  
Surrounding Environment ◽  
Human Behavior Analysis

Nowadays, with smartphones, people can easily take photos, post photos to any social networks, and use the photos for various purposes. This leads to a social problem that unintended appearance in photos may threaten the facial privacy of photographed people. Some solutions to protect facial privacy in photos have already been proposed. However, most of them rely on different techniques to de-identify photos which can be done only by photographers, giving no choice to photographed person. To deal with that, we propose an approach that allows a photographed person to proactively detect whether someone is intentionally/unintentionally trying to take pictures of him. Thereby, he can have appropriate reaction to protect the facial privacy. In this approach, we assume that the photographed person uses a wearable camera to record the surrounding environment in real-time. The skeleton information of likely photographers who are captured in the monitoring video is then extracted and put into the calculation of dynamic programming score which is eventually compared with a threshold for recognition of photo-taking behavior. Experimental results demonstrate that by using the proposed approach, the photo-taking behavior is precisely recognized with high accuracy of 92.5%.

scholarly journals Prevention of Unintended Appearance in Photos Based on Human Behaviors Analysis

2020 ◽  
Author(s):  
Yuhi Kaihoko ◽  
Phan Xuan Tan ◽  
Eiji Kamioka
Keyword(s):  
Social Networks ◽  
Dynamic Programming ◽  
Real Time ◽  
Social Problem ◽  
High Accuracy ◽  
Experimental Results ◽  
Human Behaviors ◽  
Surrounding Environment ◽  
Wearable Camera

Nowadays, with smartphones people can easily take photos, post photos to any social networks and use the photos for some purposes. This leads to a social problem that unintended appearance in photos may threaten the privacy of photographed person. Some solutions to protect facial privacy in photos have already been proposed. However, most of them rely on different techniques to de-identify photos which can be done only by photographers, giving no choice to photographed person. To deal with that, we propose an approach that allows photographed person to proactively detect whether someone is intentionally/unintentionally trying to take pictures of him/her. Thereby, he/she can have appropriate reaction to protect the privacy. In this approach, we assume that the photographed person uses a wearable camera to record the surrounding environment in real-time. The skeleton information of likely photographers who are captured in the monitoring video is then extracted to be put into the calculation of dynamic programming score which is eventually compared with a threshold for recognition of photo-taking behavior. Experimental results demonstrate that by using the proposed approach, the photo-taking behavior is precisely recognized with high accuracy of 92.5%.

P-like controllers with collision avoidance for passive bilateral teleoperation of a UAV

2018 ◽  
Vol 45 (1) ◽  
pp. 152-166 ◽  
Author(s):  
Huiyu Sun ◽  
Guangming Song ◽  
Zhong Wei ◽  
Ying Zhang
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
High Accuracy ◽  
Experimental Results ◽  
Linear Matrix ◽  
Time Varying ◽  
Bilateral Teleoperation ◽  
Content Type ◽  
Teleoperation System ◽  
The Stability

Purpose This paper aims to tele-operate the movement of an unmanned aerial vehicle (UAV) in the obstructed environment with asymmetric time-varying delays. A simple passive proportional velocity errors plus damping injection (P-like) controller is proposed to deal with the asymmetric time-varying delays in the aerial teleoperation system. Design/methodology/approach This paper presents both theoretical and real-time experimental results of the bilateral teleoperation system of a UAV for collision avoidance over the wireless network. First, a position-velocity workspace mapping is used to solve the master-slave kinematic/dynamic dissimilarity. Second, a P-like controller is proposed to ensure the stability of the time-delayed bilateral teleoperation system with asymmetric time-varying delays. The stability is analyzed by the Lyapunov–Krasovskii function and the delay-dependent stability criteria are obtained under linear-matrix-inequalities conditions. Third, a vision-based localization is presented to calibrate the UAV’s pose and provide the relative distance for obstacle avoidance with a high accuracy. Finally, the performance of the teleoperation scheme is evaluated by both human-in-the-loop simulations and real-time experiments where a single UAV flies through the obstructed environment. Findings Experimental results demonstrate that the teleoperation system can maintain passivity and collision avoidance can be achieved with a high accuracy for asymmetric time-varying delays. Moreover, the operator could tele-sense the force reflection to improve the maneuverability in the aerial teleoperation. Originality/value A real-time bilateral teleoperation system of a UAV for collision avoidance is performed in the laboratory. A force and visual interface is designed to provide force and visual feedback of the slave environment to the operator.

Real Time Person Recognition and Attendance Marking Using Holistic Based Approach

2017 ◽  
Vol 7 (7) ◽  
pp. 302
Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
High Accuracy ◽  
Efficient Technique ◽  
Human Face ◽  
Traditional Methods ◽  
Person Recognition ◽  
The Face

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.

scholarly journals Augmented Reality Maintenance Assistant Using YOLOv5

2021 ◽  
Vol 11 (11) ◽  
pp. 4758
Author(s):  
Ana Malta ◽  
Mateus Mendes ◽  
Torres Farinha
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Object Recognition ◽  
Augmented Reality ◽  
Real Time ◽  
Recognition System ◽  
High Accuracy ◽  
Video Streams ◽  
The Neural Network ◽  
Deep Learning Neural Network

Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed.

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

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