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Practical Applications of ChatGPT and BERT: Long Text Summarization and Model Feature Ablation Study for Stock Comment Topic Identification 24

Practical Applications of ChatGPT and BERT: Long Text Summar...

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2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence, DEAI 2024

作者： Xu, Mingyan Chen, Hongyu deng, fuwen Liu, Yuan Zhao, Feng Zhang, Yong School of Statistics Shandong Technology and Business University Yantai264000 China School of Hospital Shandong Technology and Business University Yantai264000 China School of Computer Science and Technology Shandong Technology and Business University Yantai264000 China Yantai Key Laboratory of Big Data Modeling and Intelligent Computing School of Computer Science and Technology Shandong Technology and Business University Yantai China School of Information and Electrotic Shandong Technology and Business University Yantai264000 China

ISBN: (纸本)9798400717147

Topic identification of expert stock comments is an important task in the field of finance, which helps investors understand the market dynamics and expert opinions so that they can make more informed investment decisions. The Bidirectional Encoder Representations from Transformers (BERT) model is one of the widely used methods for text topic identification. To improve the identification accuracy and overcome the limitations of the BERT model, two strategies are proposed in this study. First, given the BERT model's input length limitation when dealing with long texts, we used the summaries created by Chat Generative Pre-training Transformer (ChatGPT) as inputs to the model. The generative summarization capability of ChatGPT not only reduces the length of the text effectively but also preserves the key information of the original text, which enables the model to better understand and deal with long texts. Second, we perform multi-layer feature ablation on the BERT model to find the most representative features for text topic identification. The multi-layer features of the BERT model can be more effectively utilized to improve the accuracy of text topic identification. Experiments show that our proposed strategies exhibit excellent performance and provide effective paths to improve the accuracy of stock comment topic identification. © 2024 ACM.

关键词： Ablation

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A model framework for discovering the spatio-temporal usage patterns of public free-floating bike-sharing system

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Transportation Research Part C: Emerging Technologies 2019年 103卷 39-55页

作者： Yuchuan Du fuwen deng Feixiong Liao Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai China Urban Planning Group Eindhoven University of Technology Eindhoven the Netherlands

Public bike-sharing has gained much attention with the tide of sharing economy. Empowered by modern technologies (e.g., GPS devices and smartphone-based APPs), a new generation of free-floating bike-sharing systems has recently become popular. Usage data generated by such systems produce rich information. This study presents a model framework to explore the spatio-temporal usage patterns of free-floating shared bikes using the usage data. The framework includes modules of probability fitting, Random Forest, a cluster-based time-domain analysis, and a visualization toolset. A case study is discussed based on the usage data from Mobike, one of the largest operating bike-sharing systems in Shanghai (China). The daily usage dynamics is modeled using log-normal distributions. Random Forest is adopted to explore the impact of factors on the usage frequency in different districts. It is found that residential area, park & green area, and population size are the top three factors influencing the frequency. Particularly, usage near metro stations is delved using the hierarchical clustering method, resulting in three typical usage modes. Visualization analysis is demonstrated to understand the time-varying flow patterns and the spatial distribution of shared bikes. This study improves our understanding of the usage patterns of this emerging transport mode and provides insights for the promotion and dynamic deployment of the bike-sharing system in urban areas.

关键词： Free-floating Bike-sharing Dynamics Spatial-temporal patterns

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On the scheduling of lifecycle network-level pavement maintenance: modelling and applications

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INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING 2023年第2期24卷

作者： deng, fuwen Jin, Jiandong Chen, Xiaobo Zhao, Feng Shandong Technol & Business Univ Sch Comp Sci & Technol Yantai Peoples R China Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China

Pavement maintenance is a prominent issue in road traffic systems and plays a fundamental role in ensuring the safety, mobility and comfort of road networks worldwide. This paper introduces an innovative approach for scheduling network-level pavement maintenance based on mathematical planning, guided by the principle of lifecycle cost analysis (LCCA). The primary objective is to optimise pavement performance while minimising maintenance costs, ultimately achieving cost-effectiveness. In particular, the method aims to solve the '2W1H' problem (i.e. 'Which', 'When', and 'How'), which implies identifying the specific road sections, determining an appropriate maintenance timeline, and selecting the most effective maintenance treatment for long-term pavement maintenance planning. The proposed method comprises a bi-level optimisation model. The upper layer is a multi-objective optimisation model which concurrently maximising the lifecycle pavement performance while minimising the lifecycle costs;the lower layer evaluates the impact of pavement maintenance operations on travellers' route choice behaviour by employing the user equilibrium problem to determine the change in user cost attributable to a specific maintenance scheduling scheme. A meta-heuristic algorithm is utilised to solve the model and acquire a Pareto front for multi-objective optimisation. Furthermore, we discuss the practical engineering applications under budgetary constraints and pavement performance requirements, followed by the consideration of parameter uncertainties in pavement performance prediction models. The numerical experiments demonstrate that our approach can deliver pavement maintenance scheduling outcomes across various scales of road networks, and highlight the promising potential of our approach for future pavement management endeavours.

关键词： Lifecycle pavement maintenance multi-objective optimisation meta-heuristic algorithm

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Enhancing automated health monitoring of road infrastructure through a hierarchical robust deep learning approach

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STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL 2024年

作者： deng, fuwen Jin, Jiandong Chen, Xiaobo An, Zhiyong Du, Yuchuan Shandong Technol & Business Univ Sch Comp Sci & Technol 191 Mid Binhai Rd Yantai 264005 Shandong Peoples R China Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China Tongji Univ Coll Transportat Engn Shanghai Peoples R China

The life-cycle monitoring of road health conditions is crucial for precise and automated maintenance of road infrastructure. Despite this importance, existing machine vision-based methods for identifying pavement distresses are constrained in their susceptibleness to interference from factors such as shadows. To bridge this gap, the article introduces a novel hierarchical pavement structure monitoring model, which significantly enhances the task's performance. This proposed model integrates a de-shadowing module based on generative adversarial networks and an anchor-free instance segmentation model to provide pixel-level detection results, encompassing distress categories and morphological masks. A large-scale pavement image dataset was constructed, and a generative model was developed to expand pavement shadow samples. Experimental results show that the model achieved an average precision metric of 78.2%, surpassing existing baseline models. The effectiveness of the de-shadowing module was also validated through the significant improvements observed in various evaluation indicators. The proposed method demonstrates superior accuracy and robustness, holding promise for real-world road infrastructure monitoring systems.

关键词： Pavement health monitoring robustness enhancement hierarchical deep learning instance segmentation model

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Understanding the distribution characteristics of bus speed based on geocoded data

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Transportation Research Part C: Emerging Technologies 2017年 82卷 337-357页

作者： Yuchuan Du fuwen deng Feixiong Liao Yuxiong Ji Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai 201804 China Urban Planning Group Eindhoven University of Technology Eindhoven 513 5600 MB The Netherlands

Data-driven traffic management and control has attracted much attention recently. This paper conducts a series of coherent analyses based on geocoded data to understand the distribution characteristics of bus operational speed and to explore the potential applications of speed distributions. First, an original bipartite model is adopted for capturing instantaneous speed where the suspended and moving states are considered separately and a two-component mixed Weibull distribution is used to model the speed distribution in moving states. The mixed Gaussian distribution with variable components is found to be capable of expressing the speed distribution patterns of different road sections. Second, elaborate analyses on the basis of speed distribution modelling are conducted: (i) regression analyses are conducted to explore the correlations between parameters of instantaneous speed distributions and traffic related factors; (ii) a powerful clustering method using Kullback-Leibler divergence as the distance measure is proposed to grade the road sections of a bus route. These results can be utilized in fields such as bus operations management, bus priority signal control and infrastructure transformation aiming to improve the efficiency of bus operations systems.

关键词： Geocoded data Bus operation Speed distribution Finite mixture model Cluster analysis

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VOCs Concentration, SOA Formation Contribution and Festival Effects during Heavy Haze Event: A Case Study in Zhengzhou, Central China

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ATMOSPHERE 2024年第8期15卷 1009页

作者： Yu, Shijie Xue, Chaofang deng, fuwen Xu, Qixiang Zhao, Bingnan Henan Univ Sci & Technol Dept Environm Engn Luoyang 471023 Peoples R China Zhengzhou Univ Inst Environm Sci Zhengzhou 450001 Peoples R China Zhengzhou Univ Sch Ecol & Environm Zhengzhou 450001 Peoples R China

In this study, online ambient volatile organic compounds (VOCs) were collected at an urban site of Zhengzhou in Central China during February 2018. The VOCs characteristics, source contributions and the Chinese New Year (CNY) effects have been investigated. During the sampling period, three haze periods have been identified, with the corresponding VOCs concentrations of (92 +/- 45) ppbv, (62 +/- 18) ppbv and (83 +/- 34) ppbv;in contrast, the concentration during non-haze days was found to be (57 +/- 27) ppbv. In addition, the festival effects of the CNY were investigated, and the concentration of particulate matter precursor decreased significantly. Meanwhile, firework-displaying events were identified, as the emission intensity had been greatly changed. Both potential source contribution function (PSCF) and the concentration weighted trajectory (CWT) models results indicated that short-distance transportation was the main influencing factor of the local VOCs pollution, especially by transport from the northeast. Source contribution results by the positive matrix factorization (PMF) model showed that vehicle exhaust (24%), liquid petroleum gas and natural gas (LPG/NG, 23%), coal combustion (21%), industrial processes (16%) and solvent usages (16%) were the major sources of ambient VOCs. Although industry and solvents have low contribution to the total VOCs, their secondary organic aerosol (SOA) contribution were found to be relatively high, especially in haze-1 and haze-3 periods. The haze-2 period had the lowest secondary organic aerosol potential (SOAp) during the sampling period;this is mainly caused by the reduction of industrial and solvent emissions due to CNY.

关键词： volatile organic compounds (VOCs) heavy haze source apportionment secondary organic aerosols potential (SOAp) Chinese New Year (CNY) festival effects

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Theranostic radionuclides labeled biodegradable microspheres for the treatment of hepatocellular carcinoma with radioembolization

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RADIATION PHYSICS AND CHEMISTRY 2025年 232卷

作者： Pang, fuwen deng, Haihui Peng, Deti He, Jian Zhao, Weicheng Yu, Liqian Chen, Tuantuan Xie, Zonggui Cai, Huawei Chen, Bin Shenzhen Tradit Chinese Med Hosp Dept Intervent Radiol 1 Fuhua Rd Shenzhen 518033 Peoples R China Shenzhen Tradit Chinese Med Hosp Dept Liver Dis Shenzhen 518033 Peoples R China West China Hosp Dept Nucl Med 37 Guoxue Alley Chengdu 610041 Peoples R China

Liver cancer, predominantly hepatocellular carcinoma (HCC), is the third leading cause of cancer-related deaths worldwide. Unfortunately, curative options like surgery and ablation are limited to 20% of cases due to the frequent diagnosis of HCC at intermediate or advanced stages. Taking advantage of the liver's dual blood supply, transarterial radioembolization (TARE) serves as a viable option when surgery is not possible. It entails the therapeutic intra-arterial injection of microspheres containing radioisotopes during hepatic embolization procedures. While TARE using Yttrium-90 (90Y) labeled resin or glass microspheres has demonstrated promising results in HCC treatment, challenges persist, including non-biodegradability impeding re-embolization, high density causing improper occlusion in capillaries, inherent imaging issues, and high costs. Within the dynamic landscape of advancing research in HCC treatment, this article aims to deliver a thorough review of biodegradable microspheres labeled with theranostic radionuclides in the clinical setting for HCC and addresses new developments, presenting the most relevant findings.

关键词： Hepatocellular carcinoma Transarterial radioembolization Theranostic radionuclides Biodegradable microspheres

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Pyrolytic Graphite for an In-Plane Force Study of Diamagnetic Levitation: A Potential Microdetector of Cracks in Magnetic Material

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MICROMACHINES 2023年第6期14卷 1242-1242页

作者： Liu, Runze Yang, Wenjiang Xiang, Hongjun Zhao, Peng deng, fuwen Yan, Juzhuang Beihang Univ Sch Astronaut Beijing 100191 Peoples R China

The diamagnetic levitation technique can be applied in non-destructive testing for identifying cracks and defects in magnetic materials. Pyrolytic graphite is a material that can be leveraged in micromachines due to its no-power diamagnetic levitation on a permanent magnet (PM) array. However, the damping force applied to pyrolytic graphite prevents it from maintaining continuous motion along the PM array. This study investigated the diamagnetic levitation process of pyrolytic graphite on a permanent magnet array from various aspects and drew several important conclusions. Firstly, the intersection points on the permanent magnet array had the lowest potential energy and validated the stable levitation of pyrolytic graphite on these points. Secondly, the force exerted on the pyrolytic graphite during in-plane motion was at the micronewton level. The magnitude of the in-plane force and the stable time of the pyrolytic graphite were related to the size ratio between it and the PM. During the fixed-axis rotation process, the friction coefficient and friction force decreased as the rotational speed decreased. Smaller-sized pyrolytic graphite can be used for magnetic detection, precise positioning and other microdevices. The diamagnetic levitation of pyrolytic graphite can also be used for detecting cracks and defects in magnetic materials. We hope this technique will be used in crack detection, magnetic detection and other micromachines.

关键词： pyrolytic graphite diamagnetic levitation cracks detector in-plane motion fixed-axis rotation

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Advanced Self-Improving Ramp Metering Algorithm based on Multi-Agent Deep Reinforcement Learning

Advanced Self-Improving Ramp Metering Algorithm based on Mul...

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International Conference on Intelligent Transportation

作者： fuwen deng Jiandong Jin Yu Shen Yuchuan Du College of Transportation Engineering Tongji University Shanghai China School of Electronics Engineering and Computer Science Peking University Beijing China

We proposed a novel ramp metering algorithm embedding multi-agent deep reinforcement learning (DRL) techniques, based on the data of loop detectors. A multi-agent DRL framework is adopted to generate proper ramp metering scheme for each ramp meter in real time to improve the operation efficiency of urban freeway with less investment. A simulation platform is developed to simplify the implementation and training of the algorithm. A set of simulation experiments - encompassing both single and multi-ramp scenarios with various traffic demand profiles - are conducted. Comparing with the state-of-the-practice ramp metering methods, the simulation results demonstrate that the proposed DRL-based algorithm outperforms in a comprehensive evaluation index considering mainstream speed at bottleneck and queue size on ramp. The method presents robustness, scalability, and the capability of further improvement by online learning during implementation.

关键词： Traffic control Training Detectors Inference algorithms Optimization Approximation algorithms Machine learning

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Translational levitation of a permanent magnet above the splicing plane of superconducting blocks under zero field cooling and its motion drag

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ENGINEERING RESEARCH EXPRESS 2022年第3期4卷 035052-035052页

作者： Yang, Wenjiang Zhao, Peng Yan, Juzhuang Liu, Zhaoxin Hu, Juntong deng, fuwen Tang, Haibin Beihang Univ Sch Astronaut 37 Xueyuan Rd Beijing Peoples R China Beihang Univ Ningbo Inst Technol Aircraft & Prop Lab Beijing 315100 Peoples R China

Benefited from the combination of Messiner effect and flux pinning, a permanent magnet (PM) can give the self-stable levitation above a bulk superconductor. The phenomenon provides the basic principle of superconductors in wide applications such as HTS maglev trains and superconducting flywheel systems. When the superconductor works under some conditions without the flux pinning (for example zero-field cooling), the PM will show free motion along multi freedoms due to the full diamagnetism of superconductor. This paper investigated the drag characteristics of the PM moved above the diamagnetic plane spliced by superconducting bulks. The spliced diamagnetic plane can get rid of the limitation of the size of the single superconducting bulk, and realize low-drag translational motion levitation in a large area. The article builds a multidimensional levitation force measurement device to measure the vertical force and lateral force of the PM translation when the superconducting plane works at different temperature. It is found that the lateral force distribution in the PM translation shows with alternating peaks and valleys. The increase of the suspending air gap can reduce the lateral force fluctuation and realize low-drag translation. The translational lateral force has the smaller value at the center of a single superconducting block, and can be measured at the level less than 1 mN. The low drag characteristics bring the potential application of superconducting translational levitation in the low gravity ground simulation for attitude and orbit control experiments of satellites.

关键词： superconductor translational levitation low drag

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