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Beyond bag of latent topics: spatial pyramid matching for scene category recognition

Fu-xiang LU,Jun HUANG

《信息与电子工程前沿（英文）》 2015年 第16卷 第10期   页码 817-828 doi: 10.1631/FITEE.1500070

摘要： We propose a heterogeneous, mid-level feature based method for recognizing natural scene categories. The proposed feature introduces spatial information among the latent topics by means of spatial pyramid, while the latent topics are obtained by using probabilistic latent semantic analysis (pLSA) based on the bag-of-words representation. The proposed feature always performs better than standard pLSA because the performance of pLSA is adversely affected in many cases due to the loss of spatial information. By combining various interest point detectors and local region descriptors used in the bag-of-words model, the proposed feature can make further improvement for diverse scene category recognition tasks. We also propose a two-stage framework for multi-class classification. In the first stage, for each of possible detector/descriptor pairs, adaptive boosting classifiers are employed to select the most discriminative topics and further compute posterior probabilities of an unknown image from those selected topics. The second stage uses the prod-max rule to combine information coming from multiple sources and assigns the unknown image to the scene category with the highest ‘final’ posterior probability. Experimental results on three benchmark scene datasets show that the proposed method exceeds most state-of-the-art methods.

关键词： Scene category recognition     Probabilistic latent semantic analysis     Bag-of-words     Adaptive boosting    

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Predicting shear strength of slender beams without reinforcement using hybrid gradient boosting trees

Thuy-Anh NGUYEN; Hai-Bang LY; Van Quan TRAN

《结构与土木工程前沿（英文）》 2022年 第16卷 第10期   页码 1267-1286 doi: 10.1007/s11709-022-0842-0

摘要： Shear failure of slender reinforced concrete beams without stirrups has surely been a complicated occurrence that has proven challenging to adequately understand. The primary purpose of this work is to develop machine learning models capable of reliably predicting the shear strength of non-shear-reinforced slender beams (SB). A database encompassing 1118 experimental findings from the relevant literature was compiled, containing eight distinct factors. Gradient Boosting (GB) technique was developed and evaluated in combination with three different optimization algorithms, namely Particle Swarm Optimization (PSO), Random Annealing Optimization (RA), and Simulated Annealing Optimization (SA). The findings suggested that GB-SA could deliver strong prediction results and effectively generalizes the connection between the input and output variables. Shap values and two-dimensional PDP analysis were then carried out. Engineers may use the findings in this work to define beam's geometrical components and material used to achieve the desired shear strength of SB without reinforcement.

关键词： slender beam     shear strength     gradient boosting     optimization algorithms    

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and optimization design of sustainable concrete based on squirrel search algorithm-extreme gradient boosting

《结构与土木工程前沿（英文）》   页码 1310-1325 doi: 10.1007/s11709-023-0997-3

摘要： Concrete is the most commonly used construction material. However, its production leads to high carbon dioxide (CO2) emissions and energy consumption. Therefore, developing waste-substitutable concrete components is necessary. Improving the sustainability and greenness of concrete is the focus of this research. In this regard, 899 data points were collected from existing studies where cement, slag, fly ash, superplasticizer, coarse aggregate, and fine aggregate were considered potential influential factors. The complex relationship between influential factors and concrete compressive strength makes the prediction and estimation of compressive strength difficult. Instead of the traditional compressive strength test, this study combines five novel metaheuristic algorithms with extreme gradient boosting (XGB) to predict the compressive strength of green concrete based on fly ash and blast furnace slag. The intelligent prediction models were assessed using the root mean square error (RMSE), coefficient of determination (R2), mean absolute error (MAE), and variance accounted for (VAF). The results indicated that the squirrel search algorithm-extreme gradient boosting (SSA-XGB) yielded the best overall prediction performance with R2 values of 0.9930 and 0.9576, VAF values of 99.30 and 95.79, MAE values of 0.52 and 2.50, RMSE of 1.34 and 3.31 for the training and testing sets, respectively. The remaining five prediction methods yield promising results. Therefore, the developed hybrid XGB model can be introduced as an accurate and fast technique for the performance prediction of green concrete. Finally, the developed SSA-XGB considered the effects of all the input factors on the compressive strength. The ability of the model to predict the performance of concrete with unknown proportions can play a significant role in accelerating the development and application of sustainable concrete and furthering a sustainable economy.

关键词： sustainable concrete     fly ash     slay     extreme gradient boosting technique     squirrel search algorithm     parametric analysis    

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Photoreduction adjusted surface oxygen vacancy of BiMoO for boosting photocatalytic redox performance

《化学科学与工程前沿（英文）》 2023年 第17卷 第12期   页码 1937-1948 doi: 10.1007/s11705-023-2353-5

摘要： In this study, Bi2MoO6 with adjustable rich oxygen vacancies was prepared by a novel and simple solvothermal-photoreduction method which might be suitable for a large-scale production. The experiment results show that Bi2MoO6 with rich oxygen vacancies is an excellent photocatalyst. The photocatalytic ability of BMO-10 is 0.3 and 3.5 times higher than that of the pristine Bi2MoO6 for Rhodamine B degradation and Cr(VI) reduction, respectively. The results display that the band energy of the samples with oxygen vacancies was narrowed and the light absorption was broadened. Meanwhile, the efficiency of photogenerated electron-holes was increased and the separation and transfer speed of photogenerated carriers were improved. Therefore, this work provides a convenient and efficient method to prepare potential adjustable oxygen vacancy based photocatalysts to eliminate the pollution of dyes and Cr(VI) in water.

关键词： Bi2MoO6     oxygen vacancies     photoreduction     Cr(VI)     RhB    

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Floret-like Fe–N nanoparticle-embedded porous carbon superstructures from a Fe-covalent triazine polymer boosting

《化学科学与工程前沿（英文）》 2023年 第17卷 第5期   页码 525-535 doi: 10.1007/s11705-022-2232-5

摘要： Fe–Nx nanoparticles-embedded porous carbons with a desirable superstructure have attracted immense attention as promising catalysts for electrochemical oxygen reduction reaction. Herein, we employed Fe-coordinated covalent triazine polymer for the fabrication of Fe–Nx nanoparticle-embedded porous carbon nanoflorets (Fe/N@CNFs) employing a hypersaline-confinement-conversion strategy. Presence of tailored N types within the covalent triazine polymer interwork in high proportions contributes to the generation of Fe/N coordination and subsequent Fe–Nx nanoparticles. Owing to the utilization of NaCl crystals, the resultant Fe/N@CNF-800 which was generated by pyrolysis at 800 °C showed nanoflower structure and large specific surface area, which remarkably suppressed the agglomeration of high catalytic active sites. As expect, the Fe/N@CNF-800 exhibited unexpected oxygen reduction reaction catalytic performance with an ultrahigh half-wave potential (0.89 V vs. reversible hydrogen electrode), a dominant 4e– transfer approach and great cycle stability (> 92% after 100000 s). As a demonstration, the Fe/N-PCNF-800-assembled zinc–air battery delivered a high open circuit voltage of 1.51 V, a maximum peak power density of 164 mW·cm–2, as well as eminent rate performance, surpassing those of commercial Pt/C. This contribution offers a valuable avenue to exploit efficient metal nanoparticles-based carbon catalysts towards energy-related electrocatalytic reactions and beyond.

关键词： Fe–Nx nanoparticles     hypersaline-confinement conversion     floret-like carbon     covalent triazine polymers     oxygen reduction reaction    

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Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

Yue ZHAO, Feng GAO, Qiao SUN, Yunpeng YIN

《机械工程前沿（英文）》 2021年 第16卷 第2期   页码 271-284 doi: 10.1007/s11465-020-0623-1

摘要： Legged robots have potential advantages in mobility compared with wheeled robots in outdoor environments. The knowledge of various ground properties and adaptive locomotion based on different surface materials plays an important role in improving the stability of legged robots. A terrain classification and adaptive locomotion method for a hexapod robot named Qingzhui is proposed in this paper. First, a force-based terrain classification method is suggested. Ground contact force is calculated by collecting joint torques and inertial measurement unit information. Ground substrates are classified with the feature vector extracted from the collected data using the support vector machine algorithm. Then, an adaptive locomotion on different ground properties is proposed. The dynamic alternating tripod trotting gait is developed to control the robot, and the parameters of active compliance control change with the terrain. Finally, the method is integrated on a hexapod robot and tested by real experiments. Our method is shown effective for the hexapod robot to walk on concrete, wood, grass, and foam. The strategies and experimental results can be a valuable reference for other legged robots applied in outdoor environments.

关键词： terrain classification     hexapod robot     legged robot     adaptive locomotion     gait control    

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余弦忆导忆阻系统周期变化初值位移调控行为 Regular Papers

Mo CHEN, Xue REN, Hua-gan WU, Quan XU, Bo-cheng BAO

《信息与电子工程前沿（英文）》 2019年 第20卷 第12期   页码 1706-1716 doi: 10.1631/FITEE.1900360

摘要： 利用一种新型余弦忆导理想忆阻，构造一个四维忆阻系统。由于忆导函数特殊的非线性，忆阻系统具有沿忆阻内部状态变量坐标轴分布的线平衡点集(0, 0, 0, δ)，且平衡点集稳定性随δ变化而周期性演化。数值仿真揭示了忆阻系统非线性、一维的初值位移调控行为，它不仅可由忆阻状态初值触发，也可由其他两个系统状态初值引发。特别地，在位移调控路线上，可以观测到多种具有不同位置和拓扑结构的共存吸引子。通过PSIM电路仿真对该特殊动力学特性进行了验证。

关键词： 初值位移调控；忆阻系统；忆导；线平衡点集    

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Conservation and adaptive-reuse of historical industrial building in China in the post-industrial era

WANG Jianguo, JIANG Nan

《结构与土木工程前沿（英文）》 2007年 第1卷 第4期   页码 474-480 doi: 10.1007/s11709-007-0064-5

摘要： The conservation and adaptive-reuse of historical industrial building is one of the most important issues to be solved in today s urban development and construction in China. In this paper, the necessity and academic meaning of the conservation and adaptive-reuse of historical industrial building were discussed by reviewing its development rend both at home and abroad, and the basic contents of the implementation of the conservation and adaptive-reuse of historical industrial building in China with specific cases provided were analyzed. It is the central task for China to put forward the restructuring and design methods, assessment principles and relevant core technical specifications based on the empirical researches on the historical industrial building and site.

关键词： historical industrial     industrial building     implementation     adaptive-reuse     empirical    

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An adaptive sliding mode control technology for weld seam tracking

Jie LIU,Youmin HU,Bo WU,Kaibo ZHOU,Mingfeng GE

《机械工程前沿（英文）》 2015年 第10卷 第1期   页码 95-101 doi: 10.1007/s11465-015-0332-3

摘要：

A novel adaptive sliding mode control algorithm is derived to deal with seam tracking control problem of welding robotic manipulator, during the process of large-scale structure component welding. The proposed algorithm does not require the precise dynamic model, and is more practical. Its robustness is verified by the Lyapunov stability theory. The analytical results show that the proposed algorithm enables better high-precision tracking performance with chattering-free than traditional sliding mode control algorithm under various disturbances.

关键词： weld seam tracking     welding robotic manipulator     adaptive control     sliding mode control    

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Machine learning enabled prediction and process optimization of VFA production from riboflavin-mediated sludge fermentation

《环境科学与工程前沿（英文）》 2023年 第17卷 第11期 doi: 10.1007/s11783-023-1735-8

摘要：

● Data-driven approach was used to simulate VFA production from WAS fermentation.

关键词： Machine learning     Volatile fatty acids     Riboflavin     Waste activated sludge     eXtreme Gradient Boosting    

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A model reference adaptive control based method for actuator delay estimation in real-time testing

Cheng CHEN, James M. RICLES

《结构与土木工程前沿（英文）》 2010年 第4卷 第3期   页码 277-286 doi: 10.1007/s11709-010-0072-8

摘要： Real-time testing provides a viable experimental technique to evaluate the performance of structural systems subjected to dynamic loading. Servo-hydraulic actuators are often utilized to apply calculated displacements from an integration algorithm to the experimental structures in a real-time manner. The compensation of actuator delay is therefore critical to achieve stable and reliable experimental results. The advances in compensation methods based on adaptive control theory enable researchers to accommodate variable actuator delay and achieve good actuator control for real-time tests. However, these adaptive methods all require time duration for actuator delay adaptation. Experiments show that a good actuator delay estimate can help optimize the performance of the adaptive compensation methods. The rate of adaptation also requires that a good actuator delay estimate be acquired especially for the tests where the peak structural response might occur at the beginning of the tests. This paper presents a model reference adaptive control based method to identify the parameter of a simplified discrete model for servo-hydraulic dynamics and the resulting compensation method. Simulations are conducted using both numerical analysis and experimental results to evaluate the effectiveness of the proposed estimation method.

关键词： real-time testing     actuator delay     compensation     adaptive control     MIT rule     discrete transfer function    

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Obstacle-circumventing adaptive control of a four-wheeled mobile robot subjected to motion uncertainties

《机械工程前沿（英文）》 2023年 第18卷 第3期 doi: 10.1007/s11465-023-0753-3

摘要： To achieve the collision-free trajectory tracking of the four-wheeled mobile robot (FMR), existing methods resolve the tracking control and obstacle avoidance separately. Guaranteeing the synergistic robustness and smooth navigation of mobile robots subjected to motion uncertainties in a dynamic environment using this non-cooperative processing method is difficult. To address this challenge, this paper proposes an obstacle-circumventing adaptive control (OCAC) framework. Specifically, a novel anti-disturbance terminal slide mode control with adaptive gains is formulated, incorporating specified control laws for different stages. This formulation guarantees rapid convergence and simultaneous chattering elimination. By introducing sub-target points, a new sub-target dynamic tracking regression obstacle avoidance strategy is presented to transfer the obstacle avoidance problem into a dynamic tracking one, thereby reducing the burden of local path searching while ensuring system stability during obstacle circumvention. Comparative experiments demonstrate that the proposed OCAC method can strengthen the convergence and obstacle avoidance efficiency of the concerned FMR system.

关键词： four-wheeled mobile robot     obstacle-circumventing adaptive control     adaptive anti-disturbance terminal sliding mode control     sub-target dynamic tracking regression obstacle avoidance    

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Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based

Jian Wu,Yang Yan,Yulong Liu,Yahui Liu,

《工程（英文）》 doi: 10.1016/j.eng.2023.07.018

摘要： The forward design of trajectory planning strategies requires preset trajectory optimization functions, resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits. In addition, owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios, it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters. Therefore, an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed. First, numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset. Subsequently, a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory. Furthermore, a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function, and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed. Finally, the proposed strategy is verified based on real driving scenarios. The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the “emergency degree” of obstacle avoidance and the state of the vehicle. Moreover, this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories, effectively improving the adaptability and acceptability of trajectories in driving scenarios.

关键词： Obstacle avoidance trajectory planning     Inverse reinforcement theory     Anthropomorphic     Adaptive driving scenarios    

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The influence of social media on stock volatility

Xianjiao WU, Xiaolin WANG, Shudong MA, Qiang YE

《工程管理前沿（英文）》 2017年 第4卷 第2期   页码 201-211 doi: 10.15302/J-FEM-2017018

摘要： This study explores the influence of social media on stock volatility and builds a feature model with an intelligence algorithm using social media data from Xueqiu.com in China, Sina Finance and Economics, Sina Microblog, and Oriental Fortune. We find that the effect of social factors, such as increased attention to a stock’s volatility, is more significant than public sentiment. A prediction model is introduced based on social factors and public sentiment to predict stock volatility. Our findings indicate that the influence of social media data on the next day’s volatility is more significant but declines over time.

关键词： stock volatility     social data     sentiment analysis     boosting algorithm    

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Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing

Reza TEIMOURI, Hamed SOHRABPOOR

《机械工程前沿（英文）》 2013年 第8卷 第4期   页码 429-442 doi: 10.1007/s11465-013-0277-3

摘要：

Electrochemical machining process (ECM) is increasing its importance due to some of the specific advantages which can be exploited during machining operation. The process offers several special privileges such as higher machining rate, better accuracy and control, and wider range of materials that can be machined. Contribution of too many predominate parameters in the process, makes its prediction and selection of optimal values really complex, especially while the process is programmized for machining of hard materials. In the present work in order to investigate effects of electrolyte concentration, electrolyte flow rate, applied voltage and feed rate on material removal rate (MRR) and surface roughness (SR) the adaptive neuro-fuzzy inference systems (ANFIS) have been used for creation predictive models based on experimental observations. Then the ANFIS 3D surfaces have been plotted for analyzing effects of process parameters on MRR and SR. Finally, the cuckoo optimization algorithm (COA) was used for selection solutions in which the process reaches maximum material removal rate and minimum surface roughness simultaneously. Results indicated that the ANFIS technique has superiority in modeling of MRR and SR with high prediction accuracy. Also, results obtained while applying of COA have been compared with those derived from confirmatory experiments which validate the applicability and suitability of the proposed techniques in enhancing the performance of ECM process.

关键词： electrochemical machining process (ECM)     modeling     adaptive neuro-fuzzy inference system (ANFIS)     optimization     cuckoo optimization algorithm (COA)    

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标题 作者 时间 类型 操作

Beyond bag of latent topics: spatial pyramid matching for scene category recognition

Fu-xiang LU,Jun HUANG

期刊论文

Predicting shear strength of slender beams without reinforcement using hybrid gradient boosting trees

Thuy-Anh NGUYEN; Hai-Bang LY; Van Quan TRAN

期刊论文

and optimization design of sustainable concrete based on squirrel search algorithm-extreme gradient boosting

期刊论文

Photoreduction adjusted surface oxygen vacancy of BiMoO for boosting photocatalytic redox performance

期刊论文

Floret-like Fe–N nanoparticle-embedded porous carbon superstructures from a Fe-covalent triazine polymer boosting

期刊论文

Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

Yue ZHAO, Feng GAO, Qiao SUN, Yunpeng YIN

期刊论文

余弦忆导忆阻系统周期变化初值位移调控行为

Mo CHEN, Xue REN, Hua-gan WU, Quan XU, Bo-cheng BAO

期刊论文

Conservation and adaptive-reuse of historical industrial building in China in the post-industrial era

WANG Jianguo, JIANG Nan

期刊论文

An adaptive sliding mode control technology for weld seam tracking

Jie LIU,Youmin HU,Bo WU,Kaibo ZHOU,Mingfeng GE

期刊论文

Machine learning enabled prediction and process optimization of VFA production from riboflavin-mediated sludge fermentation

期刊论文

A model reference adaptive control based method for actuator delay estimation in real-time testing

Cheng CHEN, James M. RICLES

期刊论文

Obstacle-circumventing adaptive control of a four-wheeled mobile robot subjected to motion uncertainties

期刊论文

Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based

Jian Wu,Yang Yan,Yulong Liu,Yahui Liu,

期刊论文

The influence of social media on stock volatility

Xianjiao WU, Xiaolin WANG, Shudong MA, Qiang YE

期刊论文

Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing

Reza TEIMOURI, Hamed SOHRABPOOR

期刊论文