Analysis on lateral vibration characteristics of the deep-sea mining pipe

Linjing Xiao,Qiang Liu 국제구조공학회 2022 Structural Engineering and Mechanics, An Int'l Jou Vol.83 No.6

This paper analyzes the variation law of the pipe lateral vibration characteristics, it was treated as a beam model, and was dispersed into several subunits based on the FEM. The corresponding stiffness and mass matrix of the pipe was deduced by using Hermite interpolation function, and the overall dynamic balance equation was established. The lateral vibration under different pipe lengths, thicknesses and towing speeds are solved by integral method. The results show that the pipe vibration trend decreases first and then increases, and the vibration value at the ore bin is larger than that at the pump set, and the value at the top is the largest, and the least value location can change with the length increase. Increasing length and thickness can reduce lateral vibration value, while increasing speed can increase the value. Neither the thickness nor the towing speed will change the location where the least value occurs. The vibration intensity will increase with the decrease of pipe length and thickness and the increase of towing speed.

친환경혁신의 영향요인 연구: 정보원천 탐색의 조절효과를 포함하여

허림경 ( Xu Linjing ) 국제지역학회 2018 국제지역학회 춘계학술대회 Vol.2018 No.-

Analysis and Research of Magnetorheological Elastomers Piezoresistive Conductivity

Qiang Liu,Linjing Xiao,Qinghui Song,Yamin Fan 한국자기학회 2018 Journal of Magnetics Vol.23 No.3

On the basis of particle structure analysis, this paper studies the conductive mechanism of magnetorheological elastomers (MRE), and verifies the MRE conduction mechanism model based on the combination of tunnel current and conduction current. The piezoelectric characteristic of MRE is analyzed theoretically and the basic theoretical model of piezoelectric is established. A set of MRE piezoelectric characteristic test device has been designed independently. The test device is used to test the resistance values of MRE samples prepared in this experiment. Finally, the test results of each group are analyzed and compared, and the results show that this element can realize the stability test of MRE piezoelectric conductivity. Under different orders of magnitude, the low particle volume content is more sensitive to the conductivity of MRE samples, and the current flowing through the MRE sample shows a significantly non-linear relationship with the voltage applied to the sample.

Inaccuracy and Instability: Challenges of SiC MOSFET Transient Measurement Intruded by Probes

Zheng Zeng,Xin Zhang,Linjing Miao 전력전자학회 2019 ICPE(ISPE)논문집 Vol.2019 No.5

SiC MOSFET is increasingly implemented for high frequency and high power density converters. However, due to the breakneck switching speed of the SiC device and the parasitics of measurement probes, accurate and stable measurements of the transient behavior of SiC MOSFET pose unsolved challenges. In this paper, the inaccuracy and instability of SiC MOSFET caused by measurement probes are highlighted. Besides, mathematical models, interaction mechanisms and influence factors of transient measurement SiC MOSFET intruded by probes are proposed. Concerning the measurement inaccuracy, the bandwidth, rise time and propagation delay of probes and oscilloscope are modeled. Concerning the measurement instability, to understand the interaction mechanism between device and probes, impedance-oriented models of device and probes are proposed. From the perspective of small-signal model, the stability of tested SiC MOSFET influenced by the parasitics of probes are comprehensively modeled. Experimental results are presented to verify the proposed models.

Latent Classes of Circadian Type and Presenteeism and Work-Related Flow Differences Among Clinical Nurses: A Cross-Sectional Study

Xiaofei Kang,Lijuan Yang,Linjing Xu,Yang Yue,Min Ding 대한신경정신의학회 2022 PSYCHIATRY INVESTIGATION Vol.19 No.4

Objective To classify the characteristics of circadian type among clinical nurses and examine their relationships with presenteeism and work-related flow.Methods Using a cross-sectional design, 568 nurses were recruited through convenience sampling in January 2021 from three hospitals in Shandong Province, China. The data were collected using self-report measures, including the 11-item Circadian Type Inventory, Stanford Presenteeism Scale-6, and Work-Related Flow Inventory. Latent class analysis was performed to identify any clustering of circadian types. One-way analysis was performed to compare the differences between presenteeism and work-related flow in different circadian types.Results Four latent classes were identified, including high response class (14.4%), high flexible class (20.1%), high languid class (51.1%), and low response class (14.4%). Regarding presenteeism, the high languid class had higher scores than others. Regarding work-related flow, the scores of high flexible class were higher than those of high languid class, while the differences in all three dimensions were statistically significant.Conclusion Although the shift work mode is not expected to change, nursing managers could use circadian type as a predictive index to select and employ individuals for shift work to enhance work performance and provide sufficient support to staff who are intolerant to shift work.

Use of Word Clustering to Improve Emotion Recognition from Short Text

Shuai Yuan,Huan Huang,Linjing Wu 한국정보과학회 2016 Journal of Computing Science and Engineering Vol.10 No.4

Emotion recognition is an important component of affective computing, and is significant in the implementation of natural and friendly human-computer interaction. An effective approach to recognizing emotion from text is based on a machine learning technique, which deals with emotion recognition as a classification problem. However, in emotion recognition, the texts involved are usually very short, leaving a very large, sparse feature space, which decreases the performance of emotion classification. This paper proposes to resolve the problem of feature sparseness, and largely improve the emotion recognition performance from short texts by doing the following: representing short texts with word cluster features, offering a novel word clustering algorithm, and using a new feature weighting scheme. Emotion classification experiments were performed with different features and weighting schemes on a publicly available dataset. The experimental results suggest that the word cluster features and the proposed weighting scheme can partly resolve problems with feature sparseness and emotion recognition performance.

Main Content Extraction from Web Pages Based on Node Characteristics

Qingtang Liu,Mingbo Shao,Linjing Wu,Gang Zhao,Guilin Fan,Jun Li 한국정보과학회 2017 Journal of Computing Science and Engineering Vol.11 No.2

Main content extraction of web pages is widely used in search engines, web content aggregation and mobile Internet browsing. However, a mass of irrelevant information such as advertisement, irrelevant navigation and trash information is included in web pages. Such irrelevant information reduces the efficiency of web content processing in content-based applications. The purpose of this paper is to propose an automatic main content extraction method of web pages. In this method, we use two indicators to describe characteristics of web pages: text density and hyperlink density. According to continuous distribution of similar content on a page, we use an estimation algorithm to judge if a node is a content node or a noisy node based on characteristics of the node and neighboring nodes. This algorithm enables us to filter advertisement nodes and irrelevant navigation. Experimental results on 10 news websites revealed that our algorithm could achieve a 96.34% average acceptable rate.

Dynamic behavior of lifting pipe with equivalent model under mining vessel heave motion

QingHui Song,HaiYan Jiang,QingJun Song,Linjing Xiao,FangPing Yan 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.5

The lifting pipe is a key component of deep sea mining whose dynamic response directly affects the safety of the lift-ing operation. The objective of this paper was to investigate the effects of heave motion and sailing velocity of mining vessel and the buffer mass on the dynamic response of lifting pipe. First, an equivalent model of the lifting pipe was established, and the natural frequency and dynamic response of the lifting pipe equivalent model were determined with consideration of the wave action by the method of separated variables. Secondly, the reliability of the equivalent model was verified by simulating a 5000 m stepped pipe with OrcaFlex software. Then the dynamic displacement, axial tension, axial stress of the lifting pipe under different sea conditions and sailing velocities were studied, and the main factors affecting the dynamic response of the pipe described. By comparing the simulation results of actual and equivalent models, the equivalent model can be used to analyze the longitudinal vibration characteristics of the lifting pipe. The sailing velocity of the mining vessel has little effect on the dynamic response of the lifting pipe, but the surface wave has a significant effect.

Use of Word Clustering to Improve Emotion Recognition from Short Text

Yuan, Shuai,Huang, Huan,Wu, Linjing Korean Institute of Information Scientists and Eng 2016 Journal of Computing Science and Engineering Vol.10 No.4

Emotion recognition is an important component of affective computing, and is significant in the implementation of natural and friendly human-computer interaction. An effective approach to recognizing emotion from text is based on a machine learning technique, which deals with emotion recognition as a classification problem. However, in emotion recognition, the texts involved are usually very short, leaving a very large, sparse feature space, which decreases the performance of emotion classification. This paper proposes to resolve the problem of feature sparseness, and largely improve the emotion recognition performance from short texts by doing the following: representing short texts with word cluster features, offering a novel word clustering algorithm, and using a new feature weighting scheme. Emotion classification experiments were performed with different features and weighting schemes on a publicly available dataset. The experimental results suggest that the word cluster features and the proposed weighting scheme can partly resolve problems with feature sparseness and emotion recognition performance.

Main Content Extraction from Web Pages Based on Node Characteristics

Liu, Qingtang,Shao, Mingbo,Wu, Linjing,Zhao, Gang,Fan, Guilin,Li, Jun Korean Institute of Information Scientists and Eng 2017 Journal of Computing Science and Engineering Vol.11 No.2

Main content extraction of web pages is widely used in search engines, web content aggregation and mobile Internet browsing. However, a mass of irrelevant information such as advertisement, irrelevant navigation and trash information is included in web pages. Such irrelevant information reduces the efficiency of web content processing in content-based applications. The purpose of this paper is to propose an automatic main content extraction method of web pages. In this method, we use two indicators to describe characteristics of web pages: text density and hyperlink density. According to continuous distribution of similar content on a page, we use an estimation algorithm to judge if a node is a content node or a noisy node based on characteristics of the node and neighboring nodes. This algorithm enables us to filter advertisement nodes and irrelevant navigation. Experimental results on 10 news websites revealed that our algorithm could achieve a 96.34% average acceptable rate.