scholarly journals Intelligent Analysis of Abnormal Vehicle Behavior Based on a Digital Twin

2021 ◽  
Vol 26 (5) ◽  
pp. 587-597
Author(s):  
Lin Li ◽  
Zeyu Hu ◽  
Xubo Yang
Keyword(s):  
Feature Matching ◽  
Secondary Analysis ◽  
Abnormal Behavior ◽  
Analysis Framework ◽  
Surveillance Videos ◽  
Digital Twin ◽  
Detection Systems ◽  
Analysis Process ◽  
Intelligent Analysis ◽  
Set Up

AbstractAnalyzing a vehicle’s abnormal behavior in surveillance videos is a challenging field, mainly due to the wide variety of anomaly cases and the complexity of surveillance videos. In this study, a novel intelligent vehicle behavior analysis framework based on a digital twin is proposed. First, detecting vehicles based on deep learning is implemented, and Kalman filtering and feature matching are used to track vehicles. Subsequently, the tracked vehicle is mapped to a digital-twin virtual scene developed in the Unity game engine, and each vehicle’s behavior is tested according to the customized detection conditions set up in the scene. The stored behavior data can be used to reconstruct the scene again in Unity for a secondary analysis. The experimental results using real videos from traffic cameras illustrate that the detection rate of the proposed framework is close to that of the state-of-the-art abnormal event detection systems. In addition, the implementation and analysis process show the usability, generalization, and effectiveness of the proposed framework.

Study on Intelligent Analysis of the Causes of SMT Solder Joint Defects Based on Fuzzy Neural Network

2011 ◽  
Vol 189-193 ◽  
pp. 3257-3261
Author(s):  
Chun Yue Huang ◽  
He Geng Wei ◽  
Tian Ming Li ◽  
De Jin Yan
Keyword(s):  
Neural Network ◽  
Solder Joint ◽  
Membership Function ◽  
Fuzzy Neural Network ◽  
Evaluation Model ◽  
Training Samples ◽  
Intelligent Analysis ◽  
Fuzzy Neural ◽  
Input Variables ◽  
Set Up

By determining membership function of the input parameters and selecting defuzzification method, the evaluation model which can be used to intelligent analyzing the causes of SMT solder joint defects was set up. The fuzzy neural network was trained by using the output variables of the training samples from intelligent discrimination as the input variables of training samples of fuzzy neural network. The fuzzy neural network was tested by using the output variables of the testing samples from intelligent discrimination as the input variables of testing samples of fuzzy neural network. The results show that by using the evaluation model the cause of SMT solder joint defects can be analyzed intelligently and the results of intelligently analysis are reasonable, the evaluation model can be used practically.

scholarly journals Machine Learning and Artificial Intelligence in Online Fake Transaction Alerting

2015 ◽  
Vol 3 (2) ◽  
pp. 115-126 ◽  
Author(s):  
Naresh Babu Bynagari
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Fraud Detection ◽  
Learning Ability ◽  
The Core ◽  
The Past ◽  
Music Selection ◽  
Intelligent Analysis ◽  
Set Up ◽  
Detection Mechanisms

Artificial Intelligence (AI) is one of the most promising and intriguing innovations of modernity. Its potential is virtually unlimited, from smart music selection in personal gadgets to intelligent analysis of big data and real-time fraud detection and aversion. At the core of the AI philosophy lies an assumption that once a computer system is provided with enough data, it can learn based on that input. The more data is provided, the more sophisticated its learning ability becomes. This feature has acquired the name "machine learning" (ML). The opportunities explored with ML are plentiful today, and one of them is an ability to set up an evolving security system learning from the past cyber-fraud experiences and developing more rigorous fraud detection mechanisms. Read on to learn more about ML, the types and magnitude of fraud evidenced in modern banking, e-commerce, and healthcare, and how ML has become an innovative, timely, and efficient fraud prevention technology.

scholarly journals Filleting sharp edges of multi-partitioned volume finite element meshes

2015 ◽  
Vol 32 (1) ◽  
pp. 129-154
Author(s):  
Ruding Lou ◽  
Jean-Philippe Pernot ◽  
Franca Giannini ◽  
Philippe Veron ◽  
Bianca Falcidieno
Keyword(s):  
Finite Element ◽  
Semantic Information ◽  
Tetrahedral Mesh ◽  
Content Type ◽  
Analysis Process ◽  
Cad Modelling ◽  
Cad Models ◽  
Sharp Edges ◽  
Set Up ◽  
New Framework

Purpose – The purpose of this paper is to set up a new framework to enable direct modifications of volume meshes enriched with semantic information associated to multiple partitions. An instance of filleting operator is prototyped under this framework and presented in the paper. Design/methodology/approach – In this paper, a generic mesh modification operator has been designed and a new instance of this operator for filleting finite element (FE) sharp edges of tetrahedral multi-partitioned meshes is also pro-posed. The filleting operator works in two main steps. The outer skin of the tetrahedral mesh is first deformed to round user-specified sharp edges while satisfying constraints relative to the shape of the so-called Virtual Group Boundaries. Then, in the filleting area, the positions of the inner nodes are relaxed to improve the aspect ratio of the mesh elements. Findings – The classical mainstream methodology for product behaviour optimization involves the repetition of four steps: CAD modelling, meshing of CAD models, enrichment of models with FE simulation semantics and FEA. This paper highlights how this methodology could be simplified by two steps: simulation model modification and FEA. The authors set up a new framework to enable direct modifications of volume meshes enriched with semantic information associated to multiple partitions and the corresponding fillet operator is devised. Research limitations/implications – The proposed framework shows only a paradigm of direct modifications of semantic enriched meshes. It could be further more improved by adding or changing the modules inside. The fillet operator does not take into account the exact radius imposed by user. With this proposed fillet operator the mesh element density may not be enough high to obtain wished smoothness. Originality/value – This paper fulfils an identified industry need to speed up the product behaviour analysis process by directly modifying the simulation semantic enriched meshes.

Introducing the Digital Twin publishing platform

Digital Twin ◽  
2021 ◽  
Vol 1 ◽  
pp. 1
Author(s):  
Fei Tao ◽  
Qinglin Qi ◽  
Ang Liu
Keyword(s):  
Scientific Research ◽  
Engineering Applications ◽  
Digital Twin ◽  
Open Research ◽  
Set Up

Professor Fei Tao from Beihang University initiated Digital Twin (ISSN 2752-5783), the first open research publishing platform dedicated to digital twin technologies and applications. It is published by F1000, part of the Taylor & Francis Group and sponsored by Beihang University. Digital Twin has been set up to accommodate the outputs of scientific research and engineering applications that are related to digital twin.

scholarly journals Digital Twin for Monitoring Ergonomics during Manufacturing Production

2020 ◽  
Vol 10 (21) ◽  
pp. 7758
Author(s):  
Alessandro Greco ◽  
Mario Caterino ◽  
Marcello Fera ◽  
Salvatore Gerbino
Keyword(s):  
Decision Making ◽  
Decision Making Process ◽  
Methodological Framework ◽  
Production Lines ◽  
Work Activities ◽  
Digital Twin ◽  
Set Up ◽  
Operational Issues ◽  
Smart Factories

Within the era of smart factories, concerning the ergonomics related to production processes, the Digital Twin (DT) is the key to set up novel models for monitoring the performance of manual work activities, which are able to provide results in near real time and to support the decision-making process for improving the working conditions. This paper aims to propose a methodological framework that, by implementing a human DT, and supports the monitoring and the decision making regarding the ergonomics performances of manual production lines. A case study, carried out in a laboratory, is presented for demonstrating the applicability and the effectiveness of the proposed framework. The results show how it is possible to identify the operational issues of a manual workstation and how it is possible to propose and test improving solutions.

Electrochemiluminescence detection for development of immunoassays and DNA probe assays for clinical diagnostics

1991 ◽  
Vol 37 (9) ◽  
pp. 1534-1539 ◽  
Author(s):  
G F Blackburn ◽  
H P Shah ◽  
J H Kenten ◽  
J Leland ◽  
R A Kamin ◽  
...  
Keyword(s):  
Small Molecules ◽  
Dynamic Range ◽  
New Technology ◽  
Clinical Diagnostics ◽  
Reaction Products ◽  
Large Molecules ◽  
Detection Systems ◽  
Highly Sensitive ◽  
Polymerase Chain ◽  
Set Up

Abstract Electrochemiluminescence (ECL) has been developed as a highly sensitive process in which reactive species are generated from stable precursors (i.e., the ECL-active label) at the surface of an electrode. This new technology has many distinct advantages over other detection systems: no radioisotopes are used; detection limits for label are extremely low (200 fmol/L); the dynamic range for label quantification extends over six orders of magnitude; the labels are extremely stable compared with those of most other chemiluminescent systems; the labels, small molecules (approximately 1000 Da), can be used to label haptens or large molecules, and multiple labels can be coupled to proteins or oligonucleotides without affecting immunoreactivity, solubility, or ability to hybridize; because the chemiluminescence is initiated electrochemically, selectivity of bound and unbound fractions can be based on the ability of labeled species to access the electrode surface, so that both separation and nonseparation assays can be set up; and measurement is simple and rapid, requiring only a few seconds. We illustrate ECL in nonseparation immunoassays for digoxin and thyrotropin and in separation immunoassays for carcinoembryonic antigen and alpha-fetoprotein. The application of ECL for detection of polymerase chain reaction products is described and exemplified by quantifying the HIV1 gag gene.

Obstacle Detection System Based on Stereo Vision and a Structured Light

2012 ◽  
Vol 424-425 ◽  
pp. 1070-1074
Author(s):  
Kai Peng ◽  
Xing Lin Zhou ◽  
Ji Guang Liu
Keyword(s):  
Stereo Vision ◽  
Feature Matching ◽  
Detection System ◽  
High Reliability ◽  
Structured Light ◽  
Obstacle Detection ◽  
High Precision Measurement ◽  
Vision Sensors ◽  
Set Up ◽  
Device Guidance

Obstacle detection is a crucial issue for pilotless device guidance function and it has to be performed with high reliability to avoid any potential collision with the front object. The vision-based obstacle detection systems are regarded perfect for this purpose because they require little on all kind of condition. In this paper, an obstacle detection system using stereo vision sensors and structured light is developed. This system realizes rapid feature matching and high precision measurement distance with the help of structured light, avoiding the time-consuming of the initial corresponding pairs. After the initial detection, the system executes the tracking light strip algorithm for the obstacles. The proposed system can detect a front obstacle in vision field and obtain the size of obstacle. The proposed obstacle detection system is set up and its performance is verified experimentally

scholarly journals Contextualising the Research Process: Using Interviewer Notes in the Secondary Analysis of Qualitative Data

2015 ◽  
Author(s):  
John Goodwin ◽  
Henrietta O'Connor
Keyword(s):  
Qualitative Data ◽  
Secondary Analysis ◽  
Research Process ◽  
Research Project ◽  
Analysis Process ◽  
The 1960S ◽  
Insight Into ◽  
Youth Transitions

In this paper we argue that for the secondary analysis of qualitative data to be effective, researchers need to subject any accompanying interviewer notes to the secondary analysis process. The secondary analysis of interviewer notes can provide important insight into the research process and the attitudes, experiences, and expectations of those collecting the data. Such information is essential if meaningful analyses are to be offered. Using interviewer notes from a little known research project on youth transitions form the 1960s, this paper explores how the interviewers’ experiences of the research process and their perceptions are documented in the interviewer notes.

scholarly journals Developing a Digital Twin and Digital Thread Framework for an ‘Industry 4.0’ Shipyard

2020 ◽  
Author(s):  
Toh Yen Pang ◽  
Juan D. Pelaez Restrepo ◽  
Ben Cheng ◽  
Alim Yasin ◽  
Hailey Lim ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Physical World ◽  
Digital Twin ◽  
Behavior Simulation ◽  
Industrial Operations ◽  
Current Design ◽  
Organizational Architecture ◽  
And Performance ◽  
Set Up ◽  
Processing And Storage

This paper provides an overview of the current state-of-the-art digital twin and digital thread technology in industrial operations. Both are transformational technologies that have the advantage of improving the efficiency of current design and manufacturing. Digital twin is an important element of the Industry 4.0 digitalization process; however, the huge amount of data that are generated and collected by digital twin offer challenges in handling, processing and storage. The paper aims to report on the development of a new framework that combines the digital twin and digital thread for better data management in order to drive innovation, improve the production process and performance, and to ensure continuity and traceability of information. The digital twin/thread framework incorporated behavior simulation and physical control components, in which these two components rely on the connectivity between the twin and thread for information flow and exchange to drive innovation. The twin/thread framework encompasses specifications that include organizational architecture layout, security, user access, cloud computing set-up, and hardware and software requirements. It is envisaged that the framework will be applicable to enhancing optimization of operational processes and traceability of information in the physical world, especially in Industry Shipyard 4.0.

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