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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

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 10,   Pages 1267-1286 doi: 10.1007/s11709-022-0842-0

Abstract: Gradient Boosting (GB) technique was developed and evaluated in combination with three different optimization

Keywords： 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

Frontiers of Structural and Civil Engineering   Pages 1310-1325 doi: 10.1007/s11709-023-0997-3

Abstract: compressive strength test, this study combines five novel metaheuristic algorithms with extreme gradient boostingThe results indicated that the squirrel search algorithm-extreme gradient boosting (SSA-XGB) yielded

Keywords： sustainable concrete     fly ash     slay     extreme gradient boosting technique     squirrel search algorithm    

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

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 12,   Pages 1937-1948 doi: 10.1007/s11705-023-2353-5

Abstract: 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.

Keywords： 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

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 5,   Pages 525-535 doi: 10.1007/s11705-022-2232-5

Abstract: 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.

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

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Periodically varied initial offset boosting behaviors in a memristive system with cosine memductance Regular Papers

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

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 12,   Pages 1706-1716 doi: 10.1631/FITEE.1900360

Abstract: Nonlinear and one-dimensional initial offset boosting behaviors, which are triggered by not only theof coexisting attractors with different positions and topological structures are revealed along the boosting

Keywords： Initial offset boosting     Memristive system     Memductance     Line equilibrium set    

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

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 11, doi: 10.1007/s11783-023-1735-8

Abstract:

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

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

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The influence of social media on stock volatility

Xianjiao WU, Xiaolin WANG, Shudong MA, Qiang YE

Frontiers of Engineering Management 2017, Volume 4, Issue 2,   Pages 201-211 doi: 10.15302/J-FEM-2017018

Abstract: 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.

Keywords： stock volatility     social data     sentiment analysis     boosting algorithm    

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SPT based determination of undrained shear strength: Regression models and machine learning

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 1,   Pages 185-198 doi: 10.1007/s11709-019-0591-x

Abstract: simple and multiple linear regression models, three machine learning algorithms, random forest, gradient boosting

Keywords： undrained shear strength     linear regression     random forest     gradient boosting     machine learning     standard    

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Boosting the direct conversion of NHHCO electrolyte to syngas on Ag/Zn zeolitic imidazolate framework

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 9,   Pages 1196-1207 doi: 10.1007/s11705-022-2289-1

Abstract: zeolitic imidazolate framework derived nitrogen carbon catalysts, which were used for the first time for boosting

Keywords： Ag catalyst     zeolitic imidazolate framework     CO2 electroreduction     ammonium bicarbonate electrolyte     syngas    

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

Fu-xiang LU,Jun HUANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 10,   Pages 817-828 doi: 10.1631/FITEE.1500070

Abstract: In the first stage, for each of possible detector/descriptor pairs, adaptive boosting classifiers are

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

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Application of machine learning technique for predicting and evaluating chloride ingress in concrete

Van Quan TRAN; Van Loi GIAP; Dinh Phien VU; Riya Catherine GEORGE; Lanh Si HO

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 9,   Pages 1153-1169 doi: 10.1007/s11709-022-0830-4

Abstract: research aims at predicting the chloride content in concrete using three hybrid models of gradient boosting

Keywords： gradient boosting     random forest     chloride content     concrete     sensitivity analysis.    

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Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

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

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 7,   Pages 928-945 doi: 10.1007/s11709-022-0837-x

Abstract: predicted from mix design and curing age by a machine learning (ML) technique named the Extreme Gradient BoostingK-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Trees (DTR), Random Forest (RF), Gradient Boosting

Keywords： self-compacting concrete     machine learning techniques     particle swarm optimization     extreme gradient boosting    

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Initial-condition-switched boosting extreme multistability and mechanism analysis in a memcapacitive Research Articles

Bei Chen, Quan Xu, Mo Chen, Huagan Wu, Bocheng Bao,mervinbao@126.com

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 11,   Pages 1517-1531 doi: 10.1631/FITEE.2000622

Abstract: has seized scientists’ attention due to its rich diversity of dynamical behaviors and great flexibility in engineering applications. In this paper, a four-dimensional (4D) is built using four linear circuit elements and one nonlinear charge-controlled memcapacitor with a cosine inverse memcapacitance. The 4D possesses a line equilibrium set, and its stability periodically evolves with the initial condition of the memcapacitor. The 4D exhibits due to the periodically evolving stability. Complex dynamical behaviors of period doubling/halving bifurcations, chaos crisis, and initial-condition-switched coexisting attractors are revealed by bifurcation diagrams, Lyapunov exponents, and phase portraits. Thereafter, a reconstructed system is derived via integral transformation to reveal the forming mechanism of the in the . Finally, an implementation circuit is designed for the reconstructed system, and Power SIMulation (PSIM) simulations are executed to confirm the validity of the numerical analysis.

Keywords： 超级多稳定性；初值切换调控；忆容振荡器；机理分析    

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Engineering Dual Oxygen Simultaneously Modified Boron Nitride for Boosting Adsorptive Desulfurization Article

罗静, 魏延臣, 巢艳红, 王超, 李宏平, 熊君, 华明清, 李华明, 朱文帅

Engineering 2022, Volume 14, Issue 7,   Pages 86-93 doi: 10.1016/j.eng.2020.08.030

Abstract:

Oxygen atoms usually co-exist in the lattice of hexagonal boron nitride (h-BN). The understanding of interactions between the oxygen atoms and the adsorbate, however, is still ambiguous on improving adsorptive desulfurization performance. Herein, simultaneously oxygen atom-scale interior substitution and edge hydroxylation in BN structure were constructed via a polymer-based synthetic strategy. Experimental results indicated that the dual oxygen modified BN (BN–2O) exhibited an impressively increased adsorptive capacity about 12% higher than that of the edge hydroxylated BN (BN–OH) fabricated via a traditional method. The dibenzothiophene (DBT) was investigated to undergo multi-molecular layer type coverage on the BN–2O uneven surface via π–π interaction, which was enhanced by the increased oxygen doping at the edges of BN–2O. The density functional theory calculations also unveiled that the oxygen atoms confined in BN interior structure could polarize the adsorbate, thereby resulting in a dipole interaction between the adsorbate and BN–2O. This effect endowed BN–2O with the ability to selectively adsorb DBT from the aromatic-rich fuel, thereafter leading to an impressive prospect for the adsorptive desulfurization performance of the fuel. The adsorptive result was in good accordance with Freundlich and pseudo-second-order adsorption kinetics model results. Therefore, the designing of a polymer-based strategy could be also extended to other heteroatom doping systems to enhance adsorptive performance.
 

Keywords： Polymer-based synthetic strategy     Interior substitution BN     Oxygen doping     Adsorptive desulfurization    

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Scalable Core–Sheath Yarn for Boosting Solar Interfacial Desalination through Engineering Controllable Article

Xingfang Xiao, Luqi Pan, Tao Chen, Manyu Wang, Lipei Ren, Bei Chen, Yingao Wang, Qian Zhang, Weilin Xu

Engineering 2023, Volume 30, Issue 11,   Pages 153-160 doi: 10.1016/j.eng.2023.03.015

Abstract:

Tailoring water supply to achieve confined heating has proven to be an effective strategy for boosting

Keywords： Interfacial solar desalination     Photothermal yarn     Tunable water supply     Core–sheath yarn     Salt clogging    

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Title Author Date Type Operation

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

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

Journal Article

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

Journal Article

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

Journal Article

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

Journal Article

Periodically varied initial offset boosting behaviors in a memristive system with cosine memductance

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

Journal Article

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

Journal Article

The influence of social media on stock volatility

Xianjiao WU, Xiaolin WANG, Shudong MA, Qiang YE

Journal Article

SPT based determination of undrained shear strength: Regression models and machine learning

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

Journal Article

Boosting the direct conversion of NHHCO electrolyte to syngas on Ag/Zn zeolitic imidazolate framework

Journal Article

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

Fu-xiang LU,Jun HUANG

Journal Article

Application of machine learning technique for predicting and evaluating chloride ingress in concrete

Van Quan TRAN; Van Loi GIAP; Dinh Phien VU; Riya Catherine GEORGE; Lanh Si HO

Journal Article

Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

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

Journal Article

Initial-condition-switched boosting extreme multistability and mechanism analysis in a memcapacitive

Bei Chen, Quan Xu, Mo Chen, Huagan Wu, Bocheng Bao,mervinbao@126.com

Journal Article

Engineering Dual Oxygen Simultaneously Modified Boron Nitride for Boosting Adsorptive Desulfurization

罗静, 魏延臣, 巢艳红, 王超, 李宏平, 熊君, 华明清, 李华明, 朱文帅

Journal Article

Scalable Core–Sheath Yarn for Boosting Solar Interfacial Desalination through Engineering Controllable

Xingfang Xiao, Luqi Pan, Tao Chen, Manyu Wang, Lipei Ren, Bei Chen, Yingao Wang, Qian Zhang, Weilin Xu

Journal Article