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603 results on '"Guo, Hongliang"'

151. Experimental Investigation on Mixed Combustion Characteristics of Coal, Tobacco Straw, and Cinder in an Energy-Saving Bake Process

Author

Jingyu Ran, Li Zhang, Guo Hongliang, Yunfei Yan, Zhongqing Yang, Ting Zhao, and Fulei Xu

Subjects
020209 energy, Energy Engineering and Power Technology, 02 engineering and technology, 010501 environmental sciences, Combustion, 01 natural sciences, law.invention, Geochemistry and Petrology, law, 0202 electrical engineering, electronic engineering, information engineering, Coal, 0105 earth and related environmental sciences, Waste management, Renewable Energy, Sustainability and the Environment, business.industry, Mechanical Engineering, technology, industry, and agriculture, food and beverages, Straw, Cinder, Ignition system, Fuel Technology, Scientific method, Environmental science, business, Energy (signal processing)
Abstract

In view of high-energy consumption, high baking cost, and serious pollution emission during the baking process of tobacco leaves, thermogravimetric analysis is employed to investigate the combustion characteristics of coal, tobacco straw, and cinder. Analyzing thermogravimetric-derivative of thermogravimetric (TG-DTG) characteristics of samples with different blending ratios and based on the ignition temperature and burnout temperature, the combustion characteristics of the samples are obtained. Compared with the individual combustion of coal, the blending ratio of the optimal positive effect is obtained. It is illustrated that different blending ratios of coal, tobacco straw, and cinder result in different effects between promotion and inhibition. Tobacco straw is beneficial to burn on fire but adverse to keep combustion of fixed carbon. Compared with the TG and DTG characteristics in different blending ratios of coal, tobacco straw, and corresponding combustion characteristic parameter, it is illustrated that the best blending ratio of tobacco straw is 40%. According to the TG and DTG characteristics of different blending ratios of coal, cinder, and corresponding combustion characteristic parameter, it is shown that the more blending ratio of cinder, the more adverse effect to fixed carbon burning. The composite fuels with 40% tobacco straw, 10% coal cinder, and 50% coal have two obvious advantages. On the one hand, it can maintain quick burning and the volatile combustion of the tobacco straw at low-temperature stage. On the other hand, it can keep continuous combustion of the fixed carbon in coal at high-temperature stage.

Published
2020
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152. Degradation analyses of GaInP/GaAs/Ge solar cells irradiated by 70 keV and 150 keV protons by current-voltage curves under various intensities of light

Author

Wu Yiyong, Sun Qiang, Xiao Jingdong, Guo Hongliang, Yu Hui, Guo Bin, and Shi Linfeng

Subjects
010302 applied physics, Nuclear and High Energy Physics, Materials science, Photoluminescence, integumentary system, Silicon, business.industry, Open-circuit voltage, chemistry.chemical_element, 02 engineering and technology, 021001 nanoscience & nanotechnology, 01 natural sciences, law.invention, chemistry, law, 0103 physical sciences, Solar cell, Optoelectronics, Degradation (geology), Quantum efficiency, Solar simulator, Irradiation, 0210 nano-technology, business, Instrumentation
Abstract

Low energy protons damage GaInP/GaAs/Ge solar cells seriously. Traditional degradation researches require many supplementary tests, such as quantum efficiency (QE) or photoluminescence (PL). In this paper, we would establish a method that could analysis degradation of solar cells without any other equipment except a solar simulator. A voltage-current analysis technique under various intensities (X) of light was developed to study the degradation mechanisms of proton-irradiated GaInP/GaAs/Ge solar cells. Sum of ideality factor of every sub-cell Σni could be calculated from the change of open circuit voltage (Voc) with light intensities in multi-junction solar cells. The change of ideality factor shows significant increase of Shockley-Read-Hall (SRH) recombination after 70 keV and 150 keV protons irradiation. Shunt resistance Rsh increases with intensities, which is different from silicon solar cells. The change of Rsh with light intensities was used to describe the current mismatch among the sub-cells in the multijunction solar cell. After irradiation, the current mismatch becomes larger. The relative degradation rate is different under different intensities of light. The max-power degradation tends to be smaller at high intensities.

Published
2018
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153. External quantum efficiency artifacts in partial-irradiated GaInP/GaAs/Ge solar cells by protons and electrons

Author

Wang Jie, Wu Yiyong, Xiao Jingdong, Sun Qiang, Guo Bin, Guo Hongliang, and Yu Hui

Subjects
010302 applied physics, Materials science, 02 engineering and technology, Electron, 021001 nanoscience & nanotechnology, 01 natural sciences, General Energy, Radiation degradation, 0103 physical sciences, Quantum efficiency, Irradiation, Atomic physics, 0210 nano-technology, Safety, Risk, Reliability and Quality
Published
2018
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160. E-LOAM: LiDAR Odometry and Mapping With Expanded Local Structural Information

Author

Guo, Hongliang, Zhu, Jiankang, and Chen, Yunping

Abstract

This paper investigates the real time LiDAR odometry and mapping (LOAM) problem in unstructured environments. We propose E-LOAM (LOAM with Expanded Local Structural Information), a paradigm which expands the pre-extracted geometric information with local point cloud information around the geometric feature points. State-of-the-art approaches usually extract pointed geometric features as the only correspondence primitives for point cloud scan-to-scan and scan-to-map registration. We argue that, in unstructured environments, sometimes, the extracted geometric features are too sparse for adequate point cloud registration. Therefore, E-LOAM expands the ‘pointed’ geometric correspondence primitives with the point clouds around them, i.e., the local point clouds in the voxel around the feature point. The local point clouds, approximated by a multivariate normal distribution, offer additional local structural information, on top of the pointed geometric information. Additionally, to enrich the sparse geometric features, we make use of the intensity information of point clouds, and extract the places with high intensity variations as additional feature points. Experimental results with the KITTI dataset show the efficacy of E-LOAM, when compared with state of the arts. We further implement E-LOAM on a real robot platform, and evaluate E-LOAM with in-field tests.

Published
2023
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161. Deep Reinforcement Learning for UAV Routing in the Presence of Multiple Charging Stations

Author

Fan, Mingfeng, Wu, Yaoxin, Liao, Tianjun, Cao, Zhiguang, Guo, Hongliang, Sartoretti, Guillaume, and Wu, Guohua

Abstract

Deploying Unmanned Aerial Vehicles (UAVs) for traffic monitoring has been a hotspot given their flexibility and broader view. However, a UAV is usually constrained by battery capacity due to limited payload. On the other hand, the development of wireless charging technology has allowed UAVs to replenish energy from charging stations.In this paper, we study a UAV routing problem in the presence of multiple charging stations (URPMCS) with the objective of minimizing the total distance traveled by the UAV during traffic monitoring. We present a deep reinforcement learning based method, where a multi-head heterogeneous attention mechanism is designed to facilitate learning a policy that automatically and sequentially constructs the route, while taking the energy consumption into account. In our method, two types of attentions are leveraged to learn the relations between monitoring targets and charging station nodes, adopting an encoder-decoder-like policy network. Moreover, we also employ a curriculum learning strategy to enhance generalization to different numbers of charging stations. Computational results show that our method outperforms conventional algorithms with higher solution quality (except for exact methods such as Gurobi) and shorter runtime in general, and also exhibits strong generalized performance on problem instances with different distributions and sizes.

Published
2023
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172. Abstract 4611: A multicenter clinical study of stool DNA test of methylated syndecan-2 for colorectal cancer detection

Author

Wang, Jianping, primary, Liu, Side, additional, Wang, Hui, additional, Zheng, Lei, additional, Zhou, Changchun, additional, Li, Guoxin, additional, Huang, Rongkang, additional, Wang, Huaiming, additional, Li, Chujun, additional, Fan, Xinjuan, additional, Fu, Xinhui, additional, Wang, Xinying, additional, Guo, Hongliang, additional, Guan, Jie, additional, Sun, Yanlai, additional, Song, Xilin, additional, Li, Zengjun, additional, Mu, Dianbin, additional, Sun, Jujie, additional, Liu, Xianglin, additional, Qi, Yan, additional, Niu, Feng, additional, Chen, Chunhua, additional, Wu, Xiaolin, additional, Wang, Xianshu, additional, Song, Xianrang, additional, and Zou, Hongzhi, additional

Published
2020
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184. Apatinib in the treatment of non-operable or advanced gastric cancer: Evidence of efficacy and safety in a real-world study.

Author

Xing, Ligang, primary, Cao, Wei, additional, Cui, Gang, additional, Zhang, Huanhu, additional, Shi, Yiran, additional, Wei, Xin, additional, Dong, Yuting, additional, Guo, Chengye, additional, Wang, Bingping, additional, Zhang, Shu, additional, Zou, Zhiqiang, additional, Zhang, Zizhi, additional, Sun, Yahong, additional, Yu, Guohua, additional, Guo, Hongliang, additional, Wang, Deyou, additional, Meng, Qi, additional, Li, Changzheng, additional, Wang, Xixun, additional, and Yu, Jinming, additional

Published
2019
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186. Modified admittance control for maneuverable human-powered augmentation lower exoskeleton systems

Author

Abusabah I. A. Ahmed, Abubakr R. Abdalla, Guo Hongliang, and Hong Cheng

Subjects
0209 industrial biotechnology, Admittance, Computer science, Dynamics (mechanics), 020207 software engineering, 02 engineering and technology, Scatterplot smoothing, Motion control, Field (computer science), Exoskeleton, 020901 industrial engineering & automation, Control theory, 0202 electrical engineering, electronic engineering, information engineering, Trajectory
Abstract

On-line motion control in coupled human-exoskeleton system is still rich research field and represents a step towards fully autonomous, safe and intelligent navigation. Admittance Controller (AC) can successfully handle the changing dynamic during flat terrain walking in coupled human-exoskeleton systems. Trajectory correction technique transforms the interaction force exerted on the exoskeleton to appropriate intended joint flexion angles through dynamic visco-elastic model. Further, Modified AC (MAC) is developed to handle stairs transition case by applying LOcally WEighted Scatterplot Smoothing (LOWESS). We proposed Admittance Controller (AC) for on-line motion control. We demonstrate our proposed control strategy on one degree-of-freedom (1-DOF) platform first, to prove it is efficiency then can be extend to the Human power Augmentation Lower Exoskeleton (HUALEX). The experimental results show that the proposed motion control strategy can minimize the interaction dynamics with less interaction force between the pilot and the exoskeleton.

Published
2017
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190. Prognostic Factors for Primary Localized Gastrointestinal Stromal Tumors After Radical Resection: Shandong Gastrointestinal Surgery Study Group, Study 1201.

Author

Zhang, Xiaoqian, Ning, Liang, Hu, Yulong, Zhao, Shanfeng, Li, Zequn, Li, Leping, Dai, Yong, Jiang, Lixin, Wang, Ailiang, Chu, Xianqun, Li, Yuming, Yang, Daogui, Lu, Chunlei, Yao, Linguo, Cui, Gang, Lin, Huizhong, Chen, Gang, Cui, Qing, Guo, Hongliang, and Zhang, Huanhu

Abstract

Background: Most previous risk-prediction models for gastrointestinal stromal tumors (GISTs) were based on Western populations. In the current study, we collected data from 23 hospitals in Shandong Province, China, and used the data to examine prognostic factors in Chinese patients and establish a new recurrence-free survival (RFS) prediction model. Methods: Records were analyzed for 5285 GIST patients. Independent prognostic factors were identified using Cox models. Receiver operating characteristic curve analysis was used to compare a novel RFS prediction model with current risk-prediction models. Results: Overall, 4216 patients met the inclusion criteria and 3363 completed follow-up. One-, 3-, and 5-year RFS was 94.6% (95% confidence interval [CI] 93.8–95.4), 85.9% (95% CI 84.7–87.1), and 78.8% (95% CI 77.0–80.6), respectively. Sex, tumor location, size, mitotic count, and rupture were independent prognostic factors. A new prognostic index (PI) was developed: PI = 0.000 (if female) + 0.270 (if male) + 0.000 (if gastric GIST) + 0.350 (if non-gastric GIST) + 0.000 (if no tumor rupture) + 1.259 (if tumor rupture) + 0.000 (tumor mitotic count < 6 per 50 high-power fields [HPFs]) + 1.442 (tumor mitotic count between 6 and 10 per 50 HPFs) + 2.026 (tumor mitotic count > 10 per 50 HPFs) + 0.096 × tumor size (cm). Model-predicted 1-, 3-, and 5-year RFS was S(12, X) = 0.9926exp(PI), S(36, X) = 0.9739exp(PI) and S(60, X) = 0.9471exp(PI), respectively. Conclusions: Sex, tumor location, size, mitotic count, and rupture were independently prognostic for GIST recurrence. Our RFS prediction model is effective for Chinese GIST patients. [ABSTRACT FROM AUTHOR]

Published
2020
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200. Treatment of refinery wastewater: Current status and prospects.

Author

Guo, Hongliang, Qin, Qing, Hu, Mingzhe, Chang, Jo-Shu, and Lee, Duu-Jong

Subjects
WASTEWATER treatment, ARTIFICIAL intelligence, PETROLEUM refining, PETROLEUM refineries, PETROLEUM technology
Abstract

The continuous increase in petroleum refining wastewater production poses a significant challenge to protecting the water environment. The comprehensive review of petroleum refining wastewater treatment processes, particularly on the cutting-edge treatment technologies, treatment efficiency, and pollutant degradation mechanisms, must be provided. This article offers such a review for filling up the literature gap. The current technologies, including the traditional pre-treatments, primary, secondary, and tertiary treatments, the combined treatments, and the wetland treatment processes, were discussed in detail. The challenges encountered in current practice, with the future research needs to overcome the challenges, were then outlined. The emerging research trend including the use of artificial intelligence technology for enhancing the petroleum refining wastewater treatment performance was also highlighted. • The current status of petroleum refining wastewater treatment was reviewed. • Traditional and the latest combined processes and their principles were summarized. • Challenges and perspectives for petroleum refining wastewater treatment were highlighted. • The use of tools such as AI on problem solutions is discussed. [ABSTRACT FROM AUTHOR]

Published
2024
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