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29 results on '"Hong Zhiming"'

6. Knowledge Distillation-Based Edge-Decision Hierarchies for Interactive Behavior-Aware Planning in Autonomous Driving System

Author

Hong, Zhiming, Lin, Qing, and Hu, Bo

Abstract

Interactive behavior-aware planning benefits from the hierarchical learning process when adapting to dense traffic. However, the difficulty in the Intelligent Transportation System (ITS) is that the autonomous vehicle fails to execute real-time response due to hardly perceiving dynamic objects beyond the visual range. This problem can be tackled by vehicle-road-cloud cooperation that synchronously collects global perception information and makes strategic policy for deployment. Here we propose a hierarchical edge-decision framework, which addresses real-time motion skill that distills from analogical reasoning of spatial-temporal events. The first step is establishing the goal-conditioned motion library from the centralized edge-cloud perception, to compose the belief-based best response with collision avoidance. In addition, a novel perspective of latent space is presented to promote motion rehearsal in the cloud, which could generate prior credible trajectories based on the policy distillation procedure of extracting informative action from thoroughly exploring changing events. Moreover, the two-stage hierarchy decision is developed to boost the efficiency of advanced policy modification, through evaluating the hierarchical judgment matrices considering conditional criteria, thereby constituting an optimum auto-driving motion with vehicle-road-cloud collaborative system. Extensive validation on challenging autonomous driving scenarios outperforms, demonstrating that our edge-decision method significantly promotes adaption to the complex time-varying environment in ITS system in a smooth and sustainable manner.

Published
2024
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9. Clinical efficacy of Shuangshi Tonglin capsules combined with doxycycline hydrochloride in the treatment of male non-gonococcal urethritis (Damp-Heat Pouring Downward type).

Author

Wei Yi, Hong Zhiming, Chen Zilong, Chen Wenshuo, Wang Shengjie, Qiu Junfeng, and Weng Haowei

Subjects
*URETHRITIS, *DOXYCYCLINE, *CHINESE medicine, *XEROSTOMIA, *MALE infertility
Abstract

Objective To observe the clinical efficacy and safety of Shuangshi Tonglin capsules combined with doxycycline hydrochloride in treating male non-gonococcal urethritis (Damp-Heat Pouring Downward type). Methods From March 2022 to March 2023, 104 patients with non-gonococcal urethritis (Damp-Heat Pouring Downward type) were randomly divided into two groups based on block randomization, including the treatment group (n =52) and the control group ( n = 52) . The patients in the control group were orally administrated with doxycycline hydrochloride for 7 days, and the treatment group with Shuangshi Tonglin capsules in combination with doxycycline hydrochloride for 7 days. Both groups of patients were re-examined at the 7th day after stopping the medication. The clinical efficacy of the two groups was observed and compared, as well as the traditional Chinese medicine symptom scores, the time of clinical symptom regression, laboratory test results for the pathogen, and the incidence of adverse reactions. Results The total efficacy rate for the treatment group and the control group was 96. 15% and 84. 62%, respectively, with a significant difference (P <0. 05) . Symptom regression times of the treatment group for frequent urination, urgency, pain, redness and swelling of the urethral opening, itching, and urethral discharge[ (3.12 ±0.38), (3.34 +0.44), (4.12 ±0.68), (4.03 ±0.59), (3.36 ±0.32), and (3.56 ±0.52) days] were all better than those of the control group[ (4.26 ± 0.76), (4.76 ±0.83), (4.89 ±0.89), (5.12 ±0.92), (4.56 ± 0.82), and (4.64 ±0.78) days], with statistical significance (P <0. 05) . Symptom scores of both groups after treatment showed an obvious decrease (P <0.05), and the scores for the treatment group for each symptom [(0.86 ±0.18), (0.94 ± 0.23), (0.79 ±0. 6), (1.01 ±0.27), (0.83 ± 0.20), and (0.97 ±0.25)] were all notably lower than those of the control group[ (1.38 ±0.46), (1.54 ± 0.52), (1.46 ±0.49), (1.50 ± 0.51), (1.44 ± 0.43), and (1.32 ± 0.36)], with a significant difference (P <0. 05) . The pathogen clearance rate of the treatment group was 96. 15%, which was higher than that of in the control group (82. 69%, P <0.05) . The cases with gastrointestinal reactions, headaches, maculopapular rash, and dry mouth in the treatment group were 1, 1, 0, and 1 and the cases in the control group were 1, 2, 2, and 0 cases. The incidence of adverse reactions in the treatment group was 5.77%, which was lower than that in the control group. However, the difference was not statistically significant (P >0.05). Conclusions The combined treatment of Shuangshi Tonglin capsules and doxycycline hydrochloride for male non-gonocoecal urethritis of the Damp-Heat Pouring Downward type can significantly enhance the clinical pathogen clearance rate, effectively improve clinical symptoms and the life quality of patients. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Forecasting NDVI in multiple complex areas using neural network techniques combined feature engineering

Author

Cui Changlu, Lingkui Meng, Hong Zhiming, and Wen Zhang

Subjects
Feature engineering, Artificial neural network, Phenology, Computer science, Climate change, Normalized Difference Vegetation Index, Computer Science Applications, General Earth and Planetary Sciences, sense organs, Time series, Software, Critical variable, Balance of nature, Remote sensing
Abstract

NDVI (Normalized difference vegetation index) is a critical variable for monitoring climate change, studying ecological balance, and exploring the pattern of regional phenology. Traditional neural ...

Published
2020
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13. A remote sensing-based method for drought monitoring using the similarity between drought eigenvectors

Author

Lingkui Meng, Chao Song, Hong Zhiming, Wen Zhang, Cuiying Yue, and Dongying Zhang

Subjects
Index (economics), Land surface temperature, Similarity (network science), Remote sensing (archaeology), medicine, General Earth and Planetary Sciences, Environmental science, medicine.symptom, Vegetation Index, Vegetation (pathology), Eigenvalues and eigenvectors, Remote sensing
Abstract

The land surface temperature (LST) and vegetation growth status are two direct indicators of drought. In this study, we selected the LST index and vegetation index to construct drought eige...

Published
2019
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14. Effect of Novel Combinatorial Nanosuspension of Catechin and Ciprofloxacin on E. coli Induced Prostatitis Rat Model

Author

Wang Quan, Hong Zhiming, Dening Chen, Wenbin Zhou, and Zeng Yangling

Subjects
Rat model, Prostatitis, Catechin, 02 engineering and technology, Pharmacology, 010402 general chemistry, 021001 nanoscience & nanotechnology, medicine.disease, 01 natural sciences, 0104 chemical sciences, Ciprofloxacin, chemistry.chemical_compound, chemistry, medicine, General Materials Science, 0210 nano-technology, medicine.drug
Published
2018
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17. MicroRNA-384 is lowly expressed in human prostate cancer cells and has anti-tumor functions by acting on HOXB7

Author

Zeng Yangling, Wei Fu, Lijing Qi, Wang Quan, and Hong Zhiming

Subjects
0301 basic medicine, Male, Carcinogenesis, Proliferation, Down-Regulation, RM1-950, medicine.disease_cause, 03 medical and health sciences, 0302 clinical medicine, In vivo, Cell Movement, Cell Line, Tumor, LNCaP, medicine, Humans, education, Cancer function, Migration, Cell Proliferation, Pharmacology, Homeodomain Proteins, education.field_of_study, Reporter gene, Homeobox B7, Chemistry, Prostatic Neoplasms, General Medicine, CAP, In vitro, Up-Regulation, Gene Expression Regulation, Neoplastic, MicroRNAs, miR-384, 030104 developmental biology, Cell culture, 030220 oncology & carcinogenesis, Cancer cell, Cancer research, HOXB7, Therapeutics. Pharmacology
Abstract

Objectives In this work, we evaluated the expression of microRNA-384 (miR-384) in human prostate cancer (CAP) cells and its regulatory role on CAP in vitro and in vivo functions. Methods In CAP cell lines, miR-384 expression was evaluated by qRT-PCR. In LNCaP and VCaP cells, lentiviral infection was done to overexpress miR-384. The regulatory effects of miR-384 overexpression on CAP in vitro proliferation and migration, and in vivo tumorigenesis, were evaluated, respectively. The targeting of miR-384 on Homeobox b7 gene (HOXB7), was evaluated by dual-luciferase reporter assay and qRT-PCR. In addition, HOXB7 was upregulated in miR-384-overexpressed CAP cells to evaluate the correlated role of HOXB7 in miR-384-mediated CAP proliferation and migration in vitro. Results MiR-384 was lowly expressed in CAP cell lines. Lentiviral infection induced miR-384 overexpression inhibited CAP in vitro proliferation and migration, and in vivo tumorigenesis. HOXB7 was directly targeted by miR-384 in CAP cells. In miR-384-overexpressed CAP cells, HOXB7 upregulation reversed the effect of miR-384 by promoting CAP in vitro proliferation and migration. Conclusion MiR-384 was downregulated in CAP cells. MiR-384 overexpression suppressed CAP in vitro and in vivo development, possibly via acting through its downstream target gene of HOXB7.

Published
2019

18. SWCTI: Surface Water Content Temperature Index for Assessment of Surface Soil Moisture Status

Author

Linyi Li, Dongying Zhang, Hong Zhiming, Wen Zhang, Lingkui Meng, and Yu Changhui

Subjects
Index (economics), 010504 meteorology & atmospheric sciences, SWCTI, Lag, 0211 other engineering and technologies, Soil science, 02 engineering and technology, lcsh:Chemical technology, 01 natural sciences, Biochemistry, Normalized Difference Vegetation Index, Article, Analytical Chemistry, medicine, lcsh:TP1-1185, Electrical and Electronic Engineering, Instrumentation, Water content, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Moderate Resolution Imaging Spectroradiometer (MODIS), VSWI, Vegetation, SWCI, Atomic and Molecular Physics, and Optics, Loam, Environmental science, Dryness, medicine.symptom, Surface water
Abstract

The vegetation supply water index (VSWI = NDVI/LST) is an effective metric estimating soil moisture in areas with moderate to dense vegetation cover. However, the normalized difference vegetation index (NDVI) exhibits a long water stress lag and the land surface temperature (LST), sensitive to water stress, does not contribute considerably to surface soil moisture monitoring due to the constraints of the mathematical characteristics of VSWI: LST influences VSWI less when LST value is sufficiently high. This paper mathematically analyzes the characteristics of VSWI and proposes a new operational dryness index (surface water content temperature index, SWCTI) for the assessment of surface soil moisture status. SWCTI uses the surface water content index (SWCI), which provides a more accurate estimation of surface soil moisture than that of NDVI, as the numerator and the modified surface temperature, which has a greater influence on SWCTI than that of LST, as the denominator. The validation work includes comparison of SWCTI with in situ soil moisture and other remote sensing indices. The results show SWCTI demonstrates the highest correlation with in situ soil moisture, the highest correlation R = 0.801 is found between SWCTI and the 0&ndash, 5 cm soil moisture in a sandy loam. SWCTI is a functional and effective method that has a great potential in surface soil moisture monitoring.

Published
2018

21. Upscaling of Surface Soil Moisture Using a Deep Learning Model with VIIRS RDR

Author

Hong Zhiming, Lingkui Meng, Wen Zhang, Zhang Dongying, and Wei Huang

Subjects
Visible Infrared Imaging Radiometer Suite, Coefficient of determination, VIIRS, 010504 meteorology & atmospheric sciences, Scale (ratio), Geography, Planning and Development, 0211 other engineering and technologies, lcsh:G1-922, Soil science, 02 engineering and technology, 01 natural sciences, Data assimilation, Earth and Planetary Sciences (miscellaneous), Satellite imagery, Computers in Earth Sciences, Water content, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, deep learning, surface soil moisture, Regression analysis, Geography, Soil water, lcsh:Geography (General)
Abstract

In current upscaling of in situ surface soil moisture practices, commonly used novel statistical or machine learning-based regression models combined with remote sensing data show some advantages in accurately capturing the satellite footprint scale of specific local or regional surface soil moisture. However, the performance of most models is largely determined by the size of the training data and the limited generalization ability to accomplish correlation extraction in regression models, which are unsuitable for larger scale practices. In this paper, a deep learning model was proposed to estimate soil moisture on a national scale. The deep learning model has the advantage of representing nonlinearities and modeling complex relationships from large-scale data. To illustrate the deep learning model for soil moisture estimation, the croplands of China were selected as the study area, and four years of Visible Infrared Imaging Radiometer Suite (VIIRS) raw data records (RDR) were used as input parameters, then the models were trained and soil moisture estimates were obtained. Results demonstrate that the estimated models captured the complex relationship between the remote sensing variables and in situ surface soil moisture with an adjusted coefficient of determination of R ¯ 2 = 0.9875 and a root mean square error (RMSE) of 0.0084 in China. These results were more accurate than the Soil Moisture Active Passive (SMAP) active radar soil moisture products and the Global Land data assimilation system (GLDAS) 0–10 cm depth soil moisture data. Our study suggests that deep learning model have potential for operational applications of upscaling in situ surface soil moisture data at the national scale.

Published
2017

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