期刊：
Advances in Civil Engineering,2023年2023 ISSN：1687-8086
通讯作者：
Wang, YK
作者机构：
[Wang, YK; Wang, Yukui; Zhang, Dan] Hunan City Univ, Hunan Engn Res Ctr Dev & Applicat Ceramsite Concre, Yiyang 413099, Peoples R China.;[Yan, Shijun] Hunan City Univ, Coll Mech & Elect Engn, Yiyang 413000, Peoples R China.;[Zhang, Dan] Hunan City Univ, Key Lab Green Bldg & Intelligent Construct Higher, Yiyang 413000, Peoples R China.;[Hu, Zhangqi] Hunan City Univ, Coll Civil Engn, Yiyang 413099, Peoples R China.
通讯机构：
[Wang, YK ] H;Hunan City Univ, Hunan Engn Res Ctr Dev & Applicat Ceramsite Concre, Yiyang 413099, Peoples R China.
关键词：
Introduction;Materials and Methods;Results;Discussion;Conclusion;Abstract;Data Availability;Additional Points;Ethical Approval;Consent;Disclosure;Conflicts of Interests;Authors’ Contributions;Funding Statement;Acknowledgements;Acknowledgments;Supplementary Materials;Reference;Dataset Description;Dataset Files;Abstract;Introduction;Introduction and Materials;Introduction and Methods;Materials;Materials and Methods;Methods;Results;Discussion;Results and Discussion;Discussion and Conclusion;Results and Conclusion;Conclusion;Conclusions;Data Availability;Additional Points;Ethical Approval;Consent;Disclosure;Conflicts of Interest;Authors’ Contributions;Funding Statement;Acknowledgements;Supplementary Materials;References;Appendix;Abbreviations;Preliminaries;Introduction and Preliminaries;Notation;Proof of Theorem;Proofs;Analysis of Results;Examples;Numerical Example;Applications;Numerical Simulation;Model;Model Formulation;Systematic Palaeontology;Nomenclatural Acts;Taxonomic Implications;Experimental;Synthesis;Overview;Characterization;Background;Experimental;Theories;Calculations;Model Verification;Model Implementation;Geographic location;Study Area;Geological setting;Data Collection;Field Testing;Data and Sampling;Dataset;Literature Review;Related Works;Related Work;System Model;Methods and Data;Experimental Results;Results and Analysis;Evaluation;Implementation;Case Presentation;Case Report;Search Terms;Case Description;Case Series;Background;Limitations;Additional Points;Case;Case 1;Case 2 etc.;Concern Details;Retraction Details;Copyright;Related Articles
摘要：
The research group utilized the estimation model of energy consumption capacity for reinforced concrete components without axial force to assess the energy consumption capacity of 92-reinforced concrete components from the PEER database, which were subjected to axial force and bending. The study also examined the impact of design parameters, including longitudinal reinforcement ratio, transverse reinforcement ratio, axial compression ratio, and shear-span ratio, on the estimation results. The research findings revealed that when applying the estimation model of energy consumption capacity for reinforced concrete components without axial force to calculate the energy consumption capacity of reinforced concrete components with axial force, there was a significant deviation rate in the estimation of cumulative energy consumption. The relationship between the deviation rate of cumulative energy consumption and longitudinal reinforcement ratio, axial compression ratio, and shear-span ratio remained unclear. However, a more apparent linear relationship was observed with the transverse reinforcement ratio. By conducting a quantitative analysis of the transverse reinforcement ratio, the researchers proposed an modified estimation model of energy consumption capacity for reinforced concrete components with axial force. Nonetheless, the accuracy of the modified estimation model was found to be high within the range of 0–250,000 kN mm of cumulative energy consumption. For cumulative energy consumption exceeding 250,000 kN mm, further experimental and theoretical research is still required to enhance the reliability of the modified estimation model.
期刊：
International Journal of Global Energy Issues,2023年45(1):26-41https://doi.org/10.1504/IJGEI.2023.127663 ISSN：0954-7118
作者机构：
1. Architecture and Urban Planning School, Hunan City University, Yi Yang 413000, China;2. College of Architecture, Hunan University, Chang Sha 410082, China
摘要：
In order to solve the problem of low recall rate and accuracy of traditional methods, a green building benefit grading and evaluation method based on improved FPA algorithm was proposed. Firstly, the index system of green building benefit grading and evaluation is constructed, and the economic incremental benefit, social incremental benefit and environmental incremental benefit of green building are calculated according to the index system. Then, based on the incremental benefit calculation results, the green building benefit grading evaluation function is constructed. Finally, the improved FPA algorithm is used to optimise the objective function, so as to obtain the optimal solution and complete the green building benefit grading evaluation. The experimental results show that the evaluation results of economic, social and environmental benefits of the proposed method are consistent with the actual situation. The highest recall rate is 95%, and the average accuracy is 93%.
作者机构：
[Xiuxiu Yue; Yitong Yang; Qin Liang; Ruiren Tang; Xiangzhi Song] College of Chemistry & Chemical Engineering, Central South University, Changsha, 410083, China;College of Materials & Chemical Engineering, Hunan City University, Yiyang, 413000, China;[Fengpei Qi] College of Chemistry & Chemical Engineering, Central South University, Changsha, 410083, China<&wdkj&>College of Materials & Chemical Engineering, Hunan City University, Yiyang, 413000, China
通讯机构：
[Ruiren Tang; Xiangzhi Song] C;College of Chemistry & Chemical Engineering, Central South University, Changsha, 410083, China
摘要：
This study examines the impact of confirmatory psychology (CP) on the e-commerce (EC) platform purchasing of sporting products by consumers. The evolution of network communication technologies has produced EC. This study used literature and mathematical statistics to assess the consumption data of sports products purchased by consumers who purchase sports products. By descriptive analysis, variables such as CP are partitioned into dimensions, and hypotheses regarding the relationship between variables are formulated. The study found significant positive associations (P< 0.01) between normative conformity and customers' purchase intentions and between informational conformity and consumers' buying intentions. The interaction variable significantly benefits purchase intent (coefficient standard = 0.045, P< 0.001). Interaction elements showed a statistically significant positive impact on purchase intent (coefficient standard = 0.18, P <0.001). The study has theoretical ramifications that contribute to the body of knowledge. Moreover, the practical consequences of this research are essential for improving the EC platform offerings.
作者机构：
[杨京渝; 罗隆福] School of Electrical & Information Engineering, Hunan University, Changsha;410000, China;[阳同光; 彭丽; 田飞扬] Key Laboratory Energy Monitoring and Edge Computing for Smart City of Hunan Province, Hunan City University, Yiyang;413000, China;[杨京渝] 410000, China<&wdkj&>Key Laboratory Energy Monitoring and Edge Computing for Smart City of Hunan Province, Hunan City University, Yiyang
通讯机构：
[Luo, L.] S;School of Electrical & Information Engineering, China
期刊：
Energy Science & Engineering,2023年11(1):192-205 ISSN：2050-0505
通讯作者：
Changqing Chen<&wdkj&>Yali Wang<&wdkj&>Changqing Chen Changqing Chen Changqing Chen<&wdkj&>Yali Wang Yali Wang Yali Wang
作者机构：
[Chen, Qing Chang; Huang, Liang Zhi] Hunan City Univ, Coll Elect & Informat Engn, Yiyang, Peoples R China.;[Chen, Qing Chang; Zhou, Kui] Hunan Bridge Technol Co LTD, Changsha, Peoples R China.;[Wang, Yali] Changsha Univ Sci & Technol, Sch Econ & Management, Changsha, Peoples R China.;[Wang, Yali] Changsha Univ Sci & Technol, Changsha 410076, Hunan, Peoples R China.;[Chen, Qing Chang] Hunan City Coll, Yiyang 413000, Hunan, Peoples R China.
通讯机构：
[Changqing Chen; Changqing Chen Changqing Chen Changqing Chen] C;[Yali Wang; Yali Wang Yali Wang Yali Wang] S;College of Electrical and Information Engineering, Hunan City University, Yiyang, China<&wdkj&>Hunan Bridge Technology Co., LTD., Changsha, China<&wdkj&>School of Economics and Management, Changsha University of Science and Technology, Changsha, China
关键词：
energy storage;frequency regulation;model predictive control;recovery of SOC;wind farm
摘要：
To further improve the frequency regulation stability of wind farm, and optimize the state of charge (SOC) basepoint, charge and discharge rate and recovery capacity of energy storage. In an isolated, off-grid state, a two-layer optimization method is proposed, taking into account the frequency regulation reliability and SOC adaptive adjustment of the wind storage. In the upper layer, the model predictive control theory is adopted to optimize the energy-storage frequency regulation output power with the goal of minimizing the wind storage frequency regulation power deviation. While solving the problem of low-frequency regulation reliability of wind farm, the SOC recovery basepoint and frequency regulation power of energy storage are optimized. At the SOC optimization layer, based on the upper SOC recovery basis point, we propose a dynamic recovery method for energy-storage SOC that considers both the SOC recovery demand and grid-bearing capacity, to determine the energy-storage recovery power. By determining the frequency regulation or recovery power, we propose a calculation method to optimize the energy-storage charge and discharge coefficients as per the SOC for avoiding excessive charging and discharging. The simulation results show that, under continuous disturbance, the root-mean-square deviations of the proposed method is 80.13% and 62.63% lower than those of the fixed K and SOC methods, respectively. Furthermore, the proposed method exhibits the best SOC maintenance effect.
摘要：
This review provides an overview of the current trends and prospects of the extraction and separation analysis techniques for phenolic compounds in honey in 2012-2022 years. The classification, chemical structures, physicochemical, and bioactive properties of phenolic compounds in honey were comprehensively analyzed. The recent sample preparation techniques for extracting and separating the phenolic compounds from honey were discussed. The advantages and disadvantages of different extraction and separation analyses were also analyzed and compared. According to recent literatures, solid phase extraction and liquid-liquid extraction, two traditional sample preparation techniques, are still widely used for extracting phenolic compounds from honey samples. Various improved microscale extraction methods, such as solid phase microextraction and liquid-liquid microextraction, and sub-technologies can be applied considering the recovery rates, costs, solvent consumption, and environmental impacts. This review will provide insights into the extraction and separation analysis of phenolic compounds, and foster the development and utilization of active components in honey.
摘要：
Positron Emission Tomography (PET) holds substantial promise in biomedical research and clinical diagnostics. Nonetheless, PET imaging's constraints, typified by deficient sampling and considerable noise interference, often result in the production of inferior quality reconstructed images. These shortcomings can potentially undermine the clinical utility of the modality. To address this issue, this study introduces a novel image reconstruction algorithm underpinned by Bayesian theory that incorporates the total variation model and the median root prior (MRP) algorithm. The iterative resolution process of the algorithm comprises two stages. Initially, the MRP algorithm is employed for image reconstruction. Subsequently, the total variation model is applied to attenuate noise within the reconstructed image. Simulation outcomes reveal that the proposed algorithm effectively mitigates Poisson noise while preserving critical image details, such as edges. When contrasted with traditional reconstruction algorithms, the proposed approach enhances both the precision and reliability of PET imaging markedly. Thus, the algorithm carries significant potential for clinical application and could substantially improve the quality of PET imaging.
摘要：
To maximize improving the tracking wind power output plan and the service life of energy storage systems (ESS), a control strategy is proposed for ESS to track wind power planning output based on model prediction and two-layer fuzzy control. First, based on model predictive control, a model with deviations of grid-connected power from the planned output and the minimum deviation of the remaining capacity of the ESS from the ideal value is established as the target. Then, when the grid-connected power exceeds the allowable deviation band of tracking, the weight coefficients in the objective function are adjusted by introducing the first layer of fuzzy control rules, combining the state of charge (SOC) of the ESS with the dynamic tracking demand of the planned value of wind power. When the grid-connected power is within the tracking allowable deviation band, the second layer of fuzzy control rules is used to correct the charging and discharging power of the ESS to improve its ability to track the future planned deviation while not crossing the limit. By repeatedly correcting the charging and discharging power of the ESS, its safe operation and the multitasking execution of the wind power plan output tracking target are ensured. Finally, taking actual data from a wind farm as an example, tests on a simulation platform of a combined wind-storage power generation system verify the feasibility and superiority of the proposed control strategy.
摘要：
Background and objective: Traditional disease diagnosis is usually performed by experienced physicians, but misdiagnosis or missed diagnosis still exists. Exploring the relationship between changes in the cor-pus callosum and multiple brain infarcts requires extracting corpus callosum features from brain image data, which requires addressing three key issues. (1) automation, (2) completeness, and (3) accuracy. Residual learning can facilitate network training, Bi-Directional Convolutional L STM (BDC-L STM) can ex-ploit interlayer spatial dependencies, and HDC can expand the receptive domain without losing resolu-tion.Methods: In this paper, we propose a segmentation method by combining BDC-LSTM and U-Net to seg-ment the corpus callosum from multiple angles of brain images based on computed tomography (CT) and magnetic resonance imaging (MRI) in which two types of sequence, namely T2-weighted imaging as well as the Fluid Attenuated Inversion Recovery (Flair), were utilized. The two-dimensional slice sequences are segmented in the cross-sectional plane, and the segmentation results are combined to obtain the final re-sults. Encoding, BDC-LSTM, and decoding include convolutional neural networks. The coding part uses asymmetric convolutional layers of different sizes and dilated convolutions to get multi-slice information and extend the convolutional layers' perceptual field.Results: This paper uses BDC-LSTM between the encoding and decoding parts of the algorithm. On the image segmentation of the brain in multiple cerebral infarcts dataset, accuracy rates of 0.876, 0.881, 0.887, and 0.912 were attained for the intersection of union (IOU), dice similarity coefficient (DS), sensitivity (SE), and predictive positivity value (PPV). The experimental findings demonstrate that the algorithm out-performs its rivals in accuracy.Conclusion: This paper obtained segmentation results for three images using three models, ConvLSTM, Pyramid-L STM, and BDC-L STM, and compared them to verify that BDC-LSTM is the best method to per-form the segmentation task for faster and more accurate detection of 3D medical images. We improve the convolutional neural network segmentation method to obtain medical images with high segmenta-tion accuracy by solving the over-segmentation problem.& COPY; 2023 Elsevier B.V. All rights reserved.
作者机构：
[Li, Wanting; Huang, Zhiliang; Peng, Li; Yang, Jingyu; Yang, Tongguang] Hunan City Univ, Key Lab Smart City Energy Sensing & Edge Comp Huna, Yiyang 413000, Peoples R China.
通讯机构：
[Li, WT ] H;Hunan City Univ, Key Lab Smart City Energy Sensing & Edge Comp Huna, Yiyang 413000, Peoples R China.
摘要：
To improve the short-term wind power output prediction accuracy and overcome the model prediction instability problem, we propose a combined prediction model based on variational modal decomposition (VMD) combined with the improved whale algorithm (GSWOA) to optimize the long short-term memory network (LSTM) short-term wind power. First, VMD is utilized to decompose the wind power input sequence into modal components of different complexities, and the components are reconstructed into subcomponents with typical characteristics through approximate entropy, which reduces the computational scale of non-smooth sequence analysis. Second, the GSWOA is used to optimize the main influencing parameters of the LSTM model in order to obtain the weights and thresholds under the optimal LSTM model and to use the reconstructed individual subsequences. Finally, the actual data from two wind farms in Xinjiang and Northeast China are taken to verify the generalizability of the proposed model. The comparative analysis of the prediction results under different scenarios demonstrates that the improved model shows higher performance than the original model. (c) 2023 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
