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Article ; Online: Reduce the occurrence of “road rage” and ensure the safety of self-driving travel passengers

Zhang Yujin

E3S Web of Conferences, Vol 251, p

2021 Volume 03074

Abstract: With the rapid growth of car ownership today, choosing self-driving travel has become the first choice for many people. At the same time, we should pay attention to the safety issues in the process of self-driving travel. The “road rage” emotions of self- ...

Abstract	With the rapid growth of car ownership today, choosing self-driving travel has become the first choice for many people. At the same time, we should pay attention to the safety issues in the process of self-driving travel. The “road rage” emotions of self-driving drivers during the driving process pose a threat to the safety of the individual driver and the passengers in the car. Based on the traffic-oriented intelligent terminal and system platform, this article explores ways to reduce the emotion of “road rage” from the perspective of management and control. The methods discussed in this article can also help reduce environmental pollution and ensure travel safety.
Keywords	Environmental sciences ; GE1-350
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	EDP Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Feature-Trajectory-Smoothed High-Speed Model for Video Anomaly Detection.

Sun, Li / Wang, Zhiguo / Zhang, Yujin / Wang, Guijin

Sensors (Basel, Switzerland)

2023 Volume 23, Issue 3

Abstract: High-speed detection of abnormal frames in surveillance videos is essential for security. This paper proposes a new video anomaly-detection model, namely, feature trajectory-smoothed long short-term memory (FTS-LSTM). This model trains an LSTM ... ...

Abstract	High-speed detection of abnormal frames in surveillance videos is essential for security. This paper proposes a new video anomaly-detection model, namely, feature trajectory-smoothed long short-term memory (FTS-LSTM). This model trains an LSTM autoencoder network to generate future frames on normal video streams, and uses the FTS detector and generation error (GE) detector to detect anomalies on testing video streams. FTS loss is a new indicator in the anomaly-detection area. In the training stage, the model applies a feature trajectory smoothness (FTS) loss to constrain the LSTM layer. This loss enables the LSTM layer to learn the temporal regularity of video streams more precisely. In the detection stage, the model utilizes the FTS loss and the GE loss as two detectors to detect anomalies. By cascading the FTS detector and the GE detector to detect anomalies, the model achieves a high speed and competitive anomaly-detection performance on multiple datasets.
Language	English
Publishing date	2023-02-02
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s23031612
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Variable Rate Point Cloud Geometry Compression Method.

Zhuang, Lehui / Tian, Jin / Zhang, Yujin / Fang, Zhijun

Sensors (Basel, Switzerland)

2023 Volume 23, Issue 12

Abstract: With the development of 3D sensors technology, 3D point cloud is widely used in industrial scenes due to their high accuracy, which promotes the development of point cloud compression technology. Learned point cloud compression has attracted much ... ...

Abstract	With the development of 3D sensors technology, 3D point cloud is widely used in industrial scenes due to their high accuracy, which promotes the development of point cloud compression technology. Learned point cloud compression has attracted much attention for its excellent rate distortion performance. However, there is a one-to-one correspondence between the model and the compression rate in these methods. To achieve compression at different rates, a large number of models need to be trained, which increases the training time and storage space. To address this problem, a variable rate point cloud compression method is proposed, which enables the adjustment of the compression rate by the hyperparameter in a single model. To address the narrow rate range problem that occurs when the traditional rate distortion loss is jointly optimized for variable rate models, a rate expansion method based on contrastive learning is proposed to expands the bit rate range of the model. To improve the visualization effect of the reconstructed point cloud, a boundary learning method is introduced to improve the classification ability of the boundary points through boundary optimization and enhance the overall model performance. The experimental results show that the proposed method achieves variable rate compression with a large bit rate range while ensuring the model performance. The proposed method outperforms G-PCC, achieving more than 70% BD-Rate against G-PCC, and performs about, as well as the learned methods at high bit rates.
MeSH term(s)	Physical Phenomena ; Data Compression ; Industry ; Learning ; Technology
Language	English
Publishing date	2023-06-09
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s23125474
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Article ; Online: Nutrient release and antioxidant properties of functional sesame paste formulated with flaxseed during in vitro digestion

Zhang, Yujin / Hou, Lixia / Wang, Xuede

International Journal of Food Science & Technology. 2023 Jan., v. 58, no. 1 p.334-342

2023

Abstract: This study aimed to investigate the structure, fatty acids and protein release and antioxidant activities of sesame paste (SP) formulated with flaxseed during in vitro gastrointestinal digestion and compared with SP and flaxseed paste (FP). The ratio of ... ...

Abstract	This study aimed to investigate the structure, fatty acids and protein release and antioxidant activities of sesame paste (SP) formulated with flaxseed during in vitro gastrointestinal digestion and compared with SP and flaxseed paste (FP). The ratio of n‐3/n‐6 polyunsaturated fatty acid of flaxseed–sesame paste (FSP) was 0.26, which was significantly higher than that of SP (0.01). After digestion, SP contained the most abundant free linoleic acid, while the highest concentration of free linolenic acid was detected in FP. Interestingly, more soluble peptides with a molecular weight lower than 14.4 kDa were distributed in FP after gastric digestion. Meanwhile, after intestinal digestion, the hydrophilic fractions of FP showed the highest DPPH radical scavenging capacity, while the hydrophilic fractions of FP were the lowest than SP and FSP. These findings suggested that SP formulated with flaxseed as a functional ingredient could be a feasible way to increase the nutritional value of SP.
Keywords	antioxidants ; digestion ; hydrophilicity ; ingredients ; intestines ; linoleic acid ; linolenic acid ; linseed ; molecular weight ; nutritive value ; peptides ; technology
Language	English
Dates of publication	2023-01
Size	p. 334-342.
Publishing place	John Wiley & Sons, Ltd
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	883561-5
ISSN	0950-5423
ISSN	0950-5423
DOI	10.1111/ijfs.15807
Database	NAL-Catalogue (AGRICOLA)

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Z 2121: Show issues

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Article ; Online: Predicting Two-Photon Absorption Spectra of Octupolar Molecules: A Deep-Learning Approach Based Exclusively on Molecular Structures.

Fu, Haoqing / Zhang, Mengna / Leng, Jiancai / Hu, Wei / Zhu, Tong / Zhang, Yujin

The journal of physical chemistry. A

2024 Volume 128, Issue 2, Page(s) 431–438

Abstract: Octupolar molecules possessing a strong two-photon response are vital for numerous advanced applications. However, accurately predicting their two-photon absorption (TPA) spectra requires high-precision quantum chemical calculations, which are ... ...

Abstract	Octupolar molecules possessing a strong two-photon response are vital for numerous advanced applications. However, accurately predicting their two-photon absorption (TPA) spectra requires high-precision quantum chemical calculations, which are computationally expensive due to repeated simulations of molecular excited-state properties. To address this challenge, we introduce a deep learning approach capable of rapidly and accurately forecasting TPA spectra for octupolar molecules. By leveraging the geometric structure as an initial descriptor, we employ a graph neural network to predict the maximum two-photon transition wavelength and cross-section. Our model demonstrates a mean absolute percentage error of less than 4% compared to time-dependent density-functional theory calculations, effectively reproducing experimental observations. Notably, this deep learning technique is nearly 100 000 times faster than comparable quantum calculations, making it an efficient and cost-effective tool for simulating TPA properties of octupolar molecules. Furthermore, this method holds great promise for the high-throughput screening of exceptional TPA materials.
Language	English
Publishing date	2024-01-08
Publishing country	United States
Document type	Journal Article
ISSN	1520-5215
ISSN (online)	1520-5215
DOI	10.1021/acs.jpca.3c07324
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Diagnostic value of cervical spine ZOOM-DWI in cervical spondylotic myelopathy.

Li, Jia / Tian, Xiao-Nan / Zhao, Bao-Gen / Wang, Ning / Zhang, Yu-Jin / Zhang, Li

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society

2024 Volume 33, Issue 3, Page(s) 1223–1229

Abstract: Purpose: To investigate the clinical application value of the non-shared incentive diffusion imaging technique (ZOOM-DWI) diagnoses of cervical spondylotic myelopathy (CSM).: Methods: 49 CSM patients who presented from January 2022 to December 2022 ... ...

Abstract	Purpose: To investigate the clinical application value of the non-shared incentive diffusion imaging technique (ZOOM-DWI) diagnoses of cervical spondylotic myelopathy (CSM). Methods: 49 CSM patients who presented from January 2022 to December 2022 were selected as the patient group, and 50 healthy volunteers are recruited as the control group. All subjects underwent conventional MRI and ZOOM-DWI of the cervical spine and neurologic mJOA scores in patients with CSM. The spinal ADC values of segments C2-3, C4-5, C5-6, and C6-7 are measured and analyzed in all subjects, with C5-6 being the most severe level of spinal canal compression in the patient group. In addition, the study also analyzes and compares the relationship between the C5-6 ADC value and mJOA score in the patient group. Results: The mean ADC shows no significantly different levels in the control group. Among the ADC values at each measurement level in the patient group, except for C4-5 and C6-7 segments are not statistically significant, the remaining pair-wise comparisons all show statistically significant differences (F = 24.368, p < 0.001). And these individuals have the highest ADC value at C5-6. The C5-6 ADC value in the patient group is significantly higher compared with the ADC value in the control group (t = 9.414, p < 0.001), with statistical significance. The ADC value at the patient stenosis shows a significant negative correlation with the mJOA score (r = -0.493, p < 0.001). Conclusion: Cervical ZOOM-DWI can be applied to diagnose CSM, and spinal ADC value can use as reliable imaging data for diagnosing cervical myelopathy.
MeSH term(s)	Humans ; Diffusion Tensor Imaging/methods ; Spondylosis/diagnostic imaging ; Spinal Cord Diseases/diagnostic imaging ; Cervical Vertebrae/diagnostic imaging
Language	English
Publishing date	2024-01-17
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1115375-1
ISSN	1432-0932 ; 0940-6719
ISSN (online)	1432-0932
ISSN	0940-6719
DOI	10.1007/s00586-023-08110-8
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Article ; Online: Theoretical Insights on the Sensing Performance for Newly-synthesized Two-photon Fluorescent N

Jiang, Tengfei / Luan, Ni / Wang, Longping / Leng, Jiancai / Zhang, Yujin

Journal of fluorescence

2023 Volume 33, Issue 5, Page(s) 1949–1959

Abstract: The development of fluorescent probe for hydrazine ( ... ...

Abstract	The development of fluorescent probe for hydrazine (N
Language	English
Publishing date	2023-03-17
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2016892-5
ISSN	1573-4994 ; 1053-0509
ISSN (online)	1573-4994
ISSN	1053-0509
DOI	10.1007/s10895-023-03209-z
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Article ; Online: Identifying of Pure and Defected Ti

Zhang, Fengxiang / Song, Ziyue / Hu, Wei / Zhang, Yujin

Chemistry, an Asian journal

2022 Volume 17, Issue 15, Page(s) e202200416

Abstract: Employing first principles calculations, we systematically investigated the geometrical and electronic structures of pure, titanium defected ( ... ...

Abstract	Employing first principles calculations, we systematically investigated the geometrical and electronic structures of pure, titanium defected (D
Language	English
Publishing date	2022-06-10
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2233006-9
ISSN	1861-471X ; 1861-4728
ISSN (online)	1861-471X
ISSN	1861-4728
DOI	10.1002/asia.202200416
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Article ; Online: Crystallization and Structural Properties of Oleogel-Based Margarine.

Chai, Xiuhang / Zhang, Yujin / Shi, Yifei / Liu, Yuanfa

Molecules (Basel, Switzerland)

2022 Volume 27, Issue 24

Abstract: Interest in oleogel as a promising alternative to traditional hydrogenated vegetable oil has increasingly grown in recent years due to its low content of saturated fatty acids and zero trans fatty acids. This study aimed to develop wax-based margarine to ...

Abstract	Interest in oleogel as a promising alternative to traditional hydrogenated vegetable oil has increasingly grown in recent years due to its low content of saturated fatty acids and zero trans fatty acids. This study aimed to develop wax-based margarine to replace traditional commercial margarine. The wax-based margarine was prepared and compared with commercial margarine in texture, rheology, and microscopic morphology. The possibility of preparing margarine at room temperature (non-quenched) was also explored. The results showed that the hardness of oleogel-based margarine increased as the BW concentration increased. Denser droplets and crystal network structure were observed with the increase in BW content. XRD patterns of oleogel-based margarine with different content BW were quite similar and structurally to the β' form. However, the melting temperature of oleogel-based margarine was over 40 °C at each concentration, which represented a poor mouth-melting characteristic. In addition, the unique, improved physical properties of oleogel-based margarine were obtained with binary mixtures of China lacquer wax (ZLW) and Beeswax (BW), due to the interaction of the ZLW and BW crystal network. The rapid cooling process improved the spreadability of oleogel-based margarine. The margarine prepared by 5% BW50:ZLW50 had similar properties to commercial margarine in texture and melting characteristics (37 °C), which had the potential to replace commercial margarine.
Language	English
Publishing date	2022-12-15
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	1413402-0
ISSN	1420-3049 ; 1431-5165 ; 1420-3049
ISSN (online)	1420-3049
ISSN	1431-5165 ; 1420-3049
DOI	10.3390/molecules27248952
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Article ; Online: Dense Point Cloud Reconstruction by Shape and Pose Features Learning

YANG Yongzhao, ZHANG Yujin, ZHANG Lijun

Jisuanji kexue yu tansuo, Vol 16, Iss 5, Pp 1117-

2022 Volume 1127

Abstract: As one of the methods of high-resolution 3D reconstruction, generating dense 3D point clouds from a single image has always been of high interest in the field of computer vision. In view of most methods focusing on the single feature information of the ... ...

Abstract	As one of the methods of high-resolution 3D reconstruction, generating dense 3D point clouds from a single image has always been of high interest in the field of computer vision. In view of most methods focusing on the single feature information of the target and the large amount of sample data used, the method of a multi-stage reconstruction of dense point cloud network based on feature diversity is proposed, which is composed of the first stage of the 3D reconstruction network and the second stage of the point cloud processing network. The 3D reconstruction network can reconstruct sparse point cloud from a single image based on the fusion of 2D image target shape features and 3D point cloud pose features. The second-stage point cloud processing network extracts global and local features based on sparse point clouds, and increases the density of points by fusing global and local point features to obtain high-resolution dense point clouds. Deep learning fine-tuning technology is used to combine two networks to form an end-to-end network that can generate dense point clouds from a single image. The method in this paper is quantitatively and qualitatively analyzed through a large number of experiments on synthetic and real-world datasets. The results show that the average CD value of this method is 0.00698, and the EMD value is 2823.53. The result is better than some existing methods, and the point cloud reconstruction effect is better.
Keywords	\|3d reconstruction\|dense point cloud\|feature diversity\|multi-stage reconstruction\|fine-tuning ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	004
Language	Chinese
Publishing date	2022-05-01T00:00:00Z
Publisher	Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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