Denoising and Chaotic Feature Extraction of Electrocardial Signals for Driver Fatigue Detection by Kolmogorov Entropy

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Yongxiang Jiang ◽  
Shijie Guo ◽  
Sanpeng Deng
Keyword(s):  
Delay Time ◽  
Detection Method ◽  
Subjective Evaluation ◽  
Nonlinear Dynamic System ◽  
Strong Relationship ◽  
Second Phase ◽  
Kolmogorov Entropy ◽  
Driver Fatigue ◽  
Sampling Points ◽  
Actual Use

This paper proposes a detection method of driver fatigue by use of electrocardial signals. First, lifting wavelet transform (LWT) was used to reduce signal noise and its effect was confirmed by applying it to the denoising of a white-noise-mixed Lorenz signal. Second, phase space reconstruction was conducted for extracting chaotic features of the measured electrocardial signals. The phase diagrams show fractal geometry features even under a strong noise background. Finally, Kolmogorov entropy, which is a factor reflecting the uncertainty in and the chaotic level of a nonlinear dynamic system, was used as an indicator of driver fatigue. The effectiveness of Kolmogorov entropy in the judgment of driver fatigue was confirmed by comparison with a semantic differential (SD) subjective evaluation experiment. It was demonstrated that Kolmogorov entropy has a strong relationship with driver fatigue. It decreases when fatigue occurs. Furthermore, the influences of delay time and sampling points on Kolmogorov entropy were investigated, since the two factors are important to the actual use of the proposed detection method. Delay time may have significant influence on fatigue determination, but sampling points are relatively inconsequential. This result indicates that real-time detection can be realized by selecting a reasonably small number of sampling points.

scholarly journals A Real-time Driver Fatigue Detection Method Based on Two-Stage Convolutional Neural Network

2020 ◽  
Vol 53 (2) ◽  
pp. 15374-15379
Author(s):  
Hu He ◽  
Xiaoyong Zhang ◽  
Fu Jiang ◽  
Chenglong Wang ◽  
Yingze Yang ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Real Time ◽  
Detection Method ◽  
Driver Fatigue ◽  
Two Stage ◽  
Fatigue Detection

scholarly journals Polar stratospheric cloud observations by MIPAS on ENVISAT: detection method, validation and analysis of the northern hemisphere winter 2002/2003

2005 ◽  
Vol 5 (3) ◽  
pp. 679-692 ◽  
Author(s):  
R. Spang ◽  
J. J. Remedios ◽  
L. J. Kramer ◽  
L. R. Poole ◽  
M. D. Fromm ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Detection Method ◽  
Michelson Interferometer ◽  
The Arctic ◽  
Spectral Signature ◽  
Winter Period ◽  
Second Phase ◽  
Good Correspondence ◽  
Hemisphere Winter ◽  
Northern Hemisphere Winter

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on ENVISAT has made extensive measurements of polar stratospheric clouds (PSCs) in the northern hemisphere winter 2002/2003. A PSC detection method based on a ratio of radiances (the cloud index) has been implemented for MIPAS and is validated in this study with respect to ground-based lidar and space borne occultation measurements. A very good correspondence in PSC sighting and cloud altitude between MIPAS detections and those of other instruments is found for cloud index values of less than four. Comparisons with data from the Stratospheric Aerosol and Gas Experiment (SAGE) III are used to further show that the sensitivity of the MIPAS detection method for this threshold value of cloud index is approximately equivalent to an extinction limit of 10-3km-1 at 1022nm, a wavelength used by solar occultation experiments. The MIPAS cloud index data are subsequently used to examine, for the first time with any technique, the evolution of PSCs throughout the Arctic polar vortex up to a latitude close to 90° north on a near-daily basis. We find that the winter of 2002/2003 is characterised by three phases of very different PSC activity. First, an unusual, extremely cold phase in the first three weeks of December resulted in high PSC occurrence rates. This was followed by a second phase of only moderate PSC activity from 5-13 January, separated from the first phase by a minor warming event. Finally there was a third phase from February to the end of March where only sporadic and mostly weak PSC events took place. The composition of PSCs during the winter period has also been examined, exploiting in particular an infra-red spectral signature which is probably characteristic of NAT. The MIPAS observations show the presence of these particles on a number of occasions in December but very rarely in January. The PSC type differentiation from MIPAS indicates that future comparisons of PSC observations with microphysical and denitrification models might be revealing about aspects of solid particle existence and location.

scholarly journals External Resources and Economic Growth: An Empirical Analysis of South Asian Countries

2018 ◽  
Vol 21 (2) ◽  
pp. 1-17
Author(s):  
Imtiaz Arif ◽  
Lubna Khan ◽  
Syed Ali Raza
Keyword(s):  
Economic Growth ◽  
South Asian ◽  
Panel Cointegration ◽  
Strong Relationship ◽  
Vital Role ◽  
Second Phase ◽  
Asian Countries ◽  
Causality Test ◽  
External Resources ◽  
The Individual

Abstract This study aims to investigate the role of three important external resources on the economic growth of leading South Asian countries. A sample of four countries is studied from 1983 to 2014. Empirical analyses are carried out in two phases. First, we have checked the combined effect using CD test, CIPS, Pedroni, and Westerlund panel cointegration, pooled mean group (PMG) framework and Heterogeneous non-causality test. In the second phase, we compared the regional and country-wise estimations using ARDL bound testing, stability test, and Granger causality. Results suggest that remittances play a vital role in the economic growth of selected South Asian countries, whereas, imports and foreign direct investment found to be insignificant. Also, while evaluating the same model for the individual countries using the ARDL estimations also reveal that remittances significantly contribute to the economies of Pakistan and Sri Lanka and imports found to be negatively related with economic growth in the same economies. However, imports showed a strong relationship with the economic growth of Bangladesh. Thus, this paper has drawn some insights for the policymakers.

scholarly journals FACTORS AFFECTING THE USE OF 4G SERVICES: THE CASE OF VIETNAM

2019 ◽  
pp. 61-74
Author(s):  
Binh Tran Duy ◽  
Tran Huu Ai
Keyword(s):  
Technology Adoption ◽  
Service Quality ◽  
High Speed ◽  
Perceived Value ◽  
Strong Relationship ◽  
Service Users ◽  
Factors Affecting ◽  
Value Perception ◽  
Actual Use ◽  
The Impact

4G services open the door for conversation and data communications by means of high-speed mobile connection. However, the actual use of the 4G speeds is still below expectations. Therefore, it is important to understand the interaction of factors involved in the adoption of this technology. Previous studies have shown that such variables as convenience, efficient service quality and variety of services, perceived value and price are important factors in the course of 4G technology adoption. In this study, the authors examine the impact of these factors on own sample of the 4G service users. Our research results demonstrate that: 1) price, convenience and varied services are important predictors of value perception; 2) there is a relationship between diversity of services and the sense of value mediated by convenience and 3) perceived value has a strong relationship with the intention to buy.

scholarly journals Quality Control in Dental Cone-Beam Computed Tomography

2021 ◽  
Vol 11 (17) ◽  
pp. 8162
Author(s):  
Jin-Feng Huang ◽  
Xiao-Zhao Chen ◽  
Hong Wang
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Detection Method ◽  
Subjective Evaluation ◽  
Safety Information ◽  
Evaluation Methods ◽  
Cone Beam ◽  
Dose Area Product ◽  
Effective Manner ◽  
Area Product

Poor medical equipment may lead to misdiagnosis and missed diagnosis by doctors, leading to medical accidents. Given the differences in imaging methods, the performance determination method for conventional computed tomography (CT) does not apply to dental cone-beam computed tomography (CBCT). Therefore, a detection method that is more suitable for the characteristics of dental CBCT and more convenient for on-site operation in hospitals needs to be urgently developed. Hence, this study aimed to design a robust and convenient detection method to control the quality of dental CBCT, grasp the safety information of the equipment in a timely and effective manner, discover and evaluate equipment risks, and take reasonable and necessary countermeasures, thereby, reducing the risk of medical malpractice. This study adopted dose-area product to measure dose parameters and used objective quantitative evaluation methods instead of subjective evaluation methods for spatial resolution, contrast-to-noise ratio index, and uniformity. The dental CBCT of 10 dental hospitals and clinics were tested, and the findings revealed that the testing methods used had good accuracy and applicability.

Recognition System for Fatigue Facial Expression of Driver

2014 ◽  
Vol 644-650 ◽  
pp. 4174-4177
Author(s):  
Xue Mei Wang ◽  
Jia Jun Zhang
Keyword(s):  
Facial Expression ◽  
Image Recognition ◽  
Detection Method ◽  
Recognition Rate ◽  
Recognition System ◽  
Attention Mechanism ◽  
Experimental Results ◽  
Feature Points ◽  
Driver Fatigue ◽  
Recognition Model

In order to improve the accuracy of recognition system for fatigue facial expression of driver, driver fatigue expression of this paper, the detection method for key feature points in the fatigue facial expression image of driver is applied in the paper to establish a fatigue expression image recognition model based on attention mechanism. Experimental results show that the algorithm can improve the recognition rate of driver's expression image, so as to record fatigue expression image of driver more accurate.

IncNSA: Detecting communities incrementally from time-evolving networks based on node similarity

2020 ◽  
Vol 31 (07) ◽  
pp. 2050094
Author(s):  
Xing Su ◽  
Jianjun Cheng ◽  
Haijuan Yang ◽  
Mingwei Leng ◽  
Wenbo Zhang ◽  
...  
Keyword(s):  
Real World ◽  
Detection Method ◽  
Dynamic Networks ◽  
Second Phase ◽  
World Systems ◽  
Evolving Networks ◽  
The Third ◽  
Third Phase ◽  
Node Similarity ◽  
Over Time

Many real-world systems can be abstracted as networks. As those systems always change dynamically in nature, the corresponding networks also evolve over time in general, and detecting communities from such time-evolving networks has become a critical task. In this paper, we propose an incremental detection method, which can stably detect high-quality community structures from time-evolving networks. When the network evolves from the previous snapshot to the current one, the proposed method only considers the community affiliations of partial nodes efficiently, which are either newborn nodes or some active nodes from the previous snapshot. Thus, the first phase of our method is determining active nodes that should be reassigned due to the change of their community affiliations in the evolution. Then, we construct subgraphs for these nodes to obtain the preliminary communities in the second phase. Finally, the final result can be obtained through optimizing the primary communities in the third phase. To test its performance, extensive experiments are conducted on both some synthetic networks and some real-world dynamic networks, the results show that our method can detect satisfactory community structure from each of snapshot graphs efficiently and steadily, and outperforms the competitors significantly.

scholarly journals Face Recognition Based on Viola-Jones Face Detection Method and Principle Component Analysis (PCA)

2018 ◽  
pp. 52-59
Keyword(s):  
Face Recognition ◽  
Image Recognition ◽  
Detection Method ◽  
Principal Component ◽  
Component Analysis ◽  
Face Image ◽  
Important Research ◽  
Research Fields ◽  
Actual Use ◽  
Pca Method

Face recognition is one of the most important research fields of the last two decades. This is due to the actual use of this technology in automatic detection and monitoring systems. Face attribute and features recognition from images is still a challenge. In this paper, face image recognition is proposed upon local face image rather than focusing on the whole image recognition by applying preprocessing techniques and Viola-Jones method. Principal Component Analysis (PCA) method is used in order to extract the needed features. Experiments show satisfied and more accurate results achieved by the proposed system comparing to the existing systems.

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