Journal of Infrastructure Intelligence and Resilience最新文献_第7页

Random bridge generator as a platform for developing computer vision-based structural inspection algorithms 将随机桥梁生成器作为开发基于计算机视觉的结构检测算法的平台

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-06-01 Epub Date: 2024-04-17 DOI: 10.1016/j.iintel.2024.100098

Haojia Cheng , Wenhao Chai , Jiabao Hu , Wenhao Ruan , Mingyu Shi , Hyunjun Kim , Yifan Cao , Yasutaka Narazaki

{"title":"Random bridge generator as a platform for developing computer vision-based structural inspection algorithms","authors":"Haojia Cheng , Wenhao Chai , Jiabao Hu , Wenhao Ruan , Mingyu Shi , Hyunjun Kim , Yifan Cao , Yasutaka Narazaki","doi":"10.1016/j.iintel.2024.100098","DOIUrl":"10.1016/j.iintel.2024.100098","url":null,"abstract":"<div><p>Recent advances in computer vision algorithms have transformed the bridge visual inspection process. Those algorithms typically require large amounts of annotated data, which is lacking for generic bridge inspection scenarios. To address this challenge efficiently, this research designs, develops, and demonstrates a platform that can provide synthetic datasets and testing environments, termed Random Bridge Generator (RBG). The RBG produces photo-realistic 3D synthetic environments of six types of bridges randomly, automatically, and procedurally. Following relevant standards and design practice, the RBG creates random cross-sectional shapes, converts those shapes into bridge components, and assembles the components into bridges. The effectiveness of the RBG is demonstrated by producing a dataset (RBG Dataset) containing 10,753 images with pixel-wise annotations, rendered in 250 different synthetic environments. Significant diversity of the photo-realistic bridge inspection environments has been achieved, while all structural components strictly conform to the definitions derived from structural engineering documents. The use of the RBG dataset has been demonstrated by training a deep semantic segmentation algorithm with 101 convolutional layers, showing successful segmentation results for both major and minor structural components. The developed RBG is expected to enhance the level of automation in bridge visual inspection process. The Python code for RBG is made public at: <span>https://github.com/chenghaojia2323/Random-Bridge-Generator.git</span><svg><path></path></svg>.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 2","pages":"Article 100098"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991524000173/pdfft?md5=58700757be314ae33cab0ac0f3e2707a&pid=1-s2.0-S2772991524000173-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140769493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An integrated model for selecting bridge structural systems using quality function deployment and analytical hierarchy process 利用质量功能部署和层次分析法选择桥梁结构系统的综合模型

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-06-01 Epub Date: 2024-04-03 DOI: 10.1016/j.iintel.2024.100096

Saleh Abu Dabous , Mohammad AL Ayoub , Mohammed Alsharqawi , Fatma Hosny

{"title":"An integrated model for selecting bridge structural systems using quality function deployment and analytical hierarchy process","authors":"Saleh Abu Dabous , Mohammad AL Ayoub , Mohammed Alsharqawi , Fatma Hosny","doi":"10.1016/j.iintel.2024.100096","DOIUrl":"https://doi.org/10.1016/j.iintel.2024.100096","url":null,"abstract":"<div><p>Selecting an efficient structural system during the conceptual design of bridge projects is an essential requirement for the project’s success and fulfilling stakeholders’ expectations. This process involves evaluating a broad range of objective and subjective requirements based on multiple technical criteria. Despite its importance, current literature lacks a structured methodology for assisting designers in the selection process of the bridge structural system. Therefore, this research aims to develop a selection model to facilitate the decision-making process, helping evaluate different bridge structural systems during the conceptual design phase. The primary goal is to choose the most optimal design that aligns with both the client’s needs and technical specifications. The proposed methodology begins by identifying client needs and finding their relative importance using an Analytic Hierarchy Process (AHP) questionnaire, followed by determining the technical requirements in bridge conceptual design. A Quality Function Deployment (QFD) model is developed to evaluate bridge structural systems. The main advantage of integrating QFD and AHP is that it reduces the inconsistency and uncertainty in the QFD inputs. The methodology is implemented in a real case study of a bridge project in the United Arab Emirates (UAE), demonstrating improved results in structural system selection compared to traditional methods. While this research focused on the conceptual design phase of bridge projects, future work could extend to other phases of design.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 2","pages":"Article 100096"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277299152400015X/pdfft?md5=5327916e8e089d3f85d321248f271b98&pid=1-s2.0-S277299152400015X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140638600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blockchain empowerment in construction supply chains: Enhancing efficiency and sustainability for an infrastructure development 建筑供应链中的区块链赋能：提高基础设施开发的效率和可持续性

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-03-01 Epub Date: 2023-11-07 DOI: 10.1016/j.iintel.2023.100065

Ahsan Waqar, Abdul Mateen Khan, Idris Othman

{"title":"Blockchain empowerment in construction supply chains: Enhancing efficiency and sustainability for an infrastructure development","authors":"Ahsan Waqar, Abdul Mateen Khan, Idris Othman","doi":"10.1016/j.iintel.2023.100065","DOIUrl":"10.1016/j.iintel.2023.100065","url":null,"abstract":"<div><p>The construction sector is now experiencing a significant transformation, primarily motivated by the need to enhance operational efficiency and promote sustainable practices. The emergence of blockchain technology has been seen as a disruptive factor that has the potential to fundamentally transform the field of supply chain management within the construction industry. Nevertheless, the extent to which this technology has revolutionized the sector has yet to be extensively investigated. The primary objective of this study is to address the existing research void by examining the impact of blockchain technology on enhancing the capabilities of building supply chains. This study employs a thorough examination of empirical case studies and a survey conducted among 136 industry professionals to explore the many functions of blockchain technology in augmenting efficiency, transparency, and traceability within building supply chains. The significant constructs were found having impact on blockchain implementation for construction supply chains are, Transparency and Traceability (<em>β</em> = 0.202, <em>ρ</em> = 0.000, <em>t</em> = 42.560), Smart Contracts for Automation (<em>β</em> = 0.232, <em>ρ</em> = 0.000, <em>t</em> = 62.596), Quality Assurance and Compliance (<em>β</em> = 0.230, <em>ρ</em> = 0.000, <em>t</em> = 64.704), Dispute Resolution and Accountability (<em>β</em> = 0.235, <em>ρ</em> = 0.000, <em>t</em> = 79.533), Supplier Management and Verification (<em>β</em> = 0.251, <em>ρ</em> = 0.000, t = 49.404).</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 1","pages":"Article 100065"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991523000403/pdfft?md5=53901e856e1ac3e651bf0fde6657918e&pid=1-s2.0-S2772991523000403-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135509941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ecological network analysis and optimization of resilience and efficiency for electric power systems design 生态网络分析和优化电力系统设计的弹性和效率

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-03-01 Epub Date: 2024-01-10 DOI: 10.1016/j.iintel.2024.100083

Bharadwaj Somu , Enrico Zio

{"title":"Ecological network analysis and optimization of resilience and efficiency for electric power systems design","authors":"Bharadwaj Somu , Enrico Zio","doi":"10.1016/j.iintel.2024.100083","DOIUrl":"10.1016/j.iintel.2024.100083","url":null,"abstract":"<div><p>The simultaneous increase in natural disasters and human dependence on critical infrastructures for essential services such as water, electricity, etc., places ever-increasing demands on the reliable, safe, resilient design and operation of these infrastructures, with a trade-off between continuity of supply (safety and resilience) and quality of supply (reliability and efficiency) at limited cost. With this in mind, a new methodology for the analysis of electric power systems inspired by natural ecosystems is proposed here and applied to representative systems from literature. Information theory is used to quantify the results of the ecological network analysis (ENA) performed. The analysis shows that electric power systems are more efficient than reliable and vulnerable to disasters. A flow matrix is constructed from the available IEEE systems data, quantified and analyzed using information theory, and finally validated by contingency analysis and SCOPF analysis. The original network configurations are compared to random generated topologies. Comparisons are also made with ENA-inspired configurations. The latter show significantly fewer violations in each contingency scenario compared to the original configurations, further supporting the use of ENA to balance power system efficiency and resilience. Thus, ENA can be used to develop power systems with balanced efficiency and resilience.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 1","pages":"Article 100083"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991524000021/pdfft?md5=6a7c5da757d015787dd1f073a57fa8a3&pid=1-s2.0-S2772991524000021-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139456019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying and estimating causal effects of bridge failures from observational data 从观测数据中识别和估计桥梁故障的因果效应

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-03-01 Epub Date: 2023-12-13 DOI: 10.1016/j.iintel.2023.100068

Aybike Özyüksel Çiftçioğlu , M.Z. Naser

引用次数: 0

Control of seismic induced response of wind turbines using KDamper 利用 KDamper 控制风力涡轮机的地震诱导响应

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-03-01 Epub Date: 2024-01-03 DOI: 10.1016/j.iintel.2024.100082

Haoran Zuo , Xunyi Pan , Kaiming Bi , Hong Hao

{"title":"Control of seismic induced response of wind turbines using KDamper","authors":"Haoran Zuo , Xunyi Pan , Kaiming Bi , Hong Hao","doi":"10.1016/j.iintel.2024.100082","DOIUrl":"10.1016/j.iintel.2024.100082","url":null,"abstract":"<div><p>Earthquake-induced vibrations of wind turbines may compromise structural serviceability and safety. Most previous studies adopted passive control devices to mitigate the seismic responses of wind turbines. However, their control effectiveness is heavily dependent on the mass ratio between control devices and wind turbines, and they were typically housed at the tower top or within the nacelle. The restricted space within the hollow tower and the nacelle imposes considerable challenges for the implementation of such devices, rendering the application of large-scale control devices unfeasible for structural vibration control of wind turbines. To this end, this paper integrates a negative stiffness element within a conventional tuned mass damper (TMD), termed KDamper, to mitigate vibrations of wind turbine towers under seismic loads. Specifically, the widely used NREL 5 MW wind turbine is selected as a prototype structure and its tower is modelled as a multiple-degree-of-freedom system. Then KDamper is incorporated into the developed model and its parameters are optimized based on the <em>H</em><sub>2</sub> criterion. Subsequently, the control effectiveness of KDamper is investigated and compared with TMD in the frequency domain, and the control performances in terms of the effectiveness and robustness of KDamper are further examined under a series of earthquake records. Results show that KDamper has superior control effectiveness and robustness than TMD, indicating it has considerable potential for application in improving wind turbine performances against earthquake hazards.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 1","pages":"Article 100082"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277299152400001X/pdfft?md5=ebed026d6d0a94994b7a061c881d41de&pid=1-s2.0-S277299152400001X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139395547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implications of 5G rollout on post-earthquake functionality of regional telecommunication infrastructure 推出 5G 对地区电信基础设施震后功能的影响

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-03-01 Epub Date: 2024-01-21 DOI: 10.1016/j.iintel.2024.100084

Ao Du

{"title":"Implications of 5G rollout on post-earthquake functionality of regional telecommunication infrastructure","authors":"Ao Du","doi":"10.1016/j.iintel.2024.100084","DOIUrl":"https://doi.org/10.1016/j.iintel.2024.100084","url":null,"abstract":"<div><p>Telecommunication infrastructure (TI) is becoming increasingly vital in modern society, where information exchange is needed in almost all aspects of the built environment, business operations, and people's daily lives. The ongoing 5G rollout will lead to a paradigm shift in regional TI deployment landscape, with increased seismic hazard exposure particularly due to the densely deployed small cells. As TI is known to be vulnerable to seismic hazard impacts yet necessary for post-earthquake emergency response, this study carries out a pioneering effort in quantifying the post-earthquake TI failures and functionality to better support risk mitigation decision-making. We propose a novel seismic risk assessment framework for regional 5G TI, by holistically integrating regional seismic hazard analysis, infrastructure seismic exposure data, electric power infrastructure seismic fragility modeling and network connectivity analysis, as well as wireless TI functionality modeling. The proposed framework is evaluated based on a hypothetical regional infrastructure testbed located in Memphis, Tennessee, subjected to several earthquake scenarios. From a reference heterogeneous 5G TI deployment scenario, the results indicate that significant performance degradation of 5G TI is expected especially after major earthquake events. Enabled by the proposed framework, we further compared the efficacy of several risk mitigation strategies and pertinent implications are provided.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 1","pages":"Article 100084"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991524000033/pdfft?md5=08f1505d87bec07c525c7b0327c6ffa2&pid=1-s2.0-S2772991524000033-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139694829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recent advances in wireless sensor networks for structural health monitoring of civil infrastructure 用于土木基础设施结构健康监测的无线传感器网络的最新进展

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-03-01 Epub Date: 2023-11-11 DOI: 10.1016/j.iintel.2023.100066

Xiao Yu , Yuguang Fu , Jian Li , Jianxiao Mao , Tu Hoang , Hao Wang

{"title":"Recent advances in wireless sensor networks for structural health monitoring of civil infrastructure","authors":"Xiao Yu , Yuguang Fu , Jian Li , Jianxiao Mao , Tu Hoang , Hao Wang","doi":"10.1016/j.iintel.2023.100066","DOIUrl":"10.1016/j.iintel.2023.100066","url":null,"abstract":"<div><p>Wireless Smart Sensor Networks (WSSN) have seen significant advancements in recent years. They act as a core part of structural health monitoring (SHM) systems by facilitating efficient measurement, assessment, and hence maintenance of civil infrastructure. This paper presents the latest technology developments of WSSN in the last ten years, including ones for a single sensor node and those for a network of nodes. Focus is placed on critical aspects of such advancements, including event-triggered sensing, multimeric sensing, edge/cloud computing, time synchronization, real-time data acquisition, decentralized data processing, and long-term reliability. In addition, full-scale applications and demonstrations of WSSN in SHM are also summarized. Finally, the remaining challenges and future research directions of WSSN are discussed to promote the further development and applications.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 1","pages":"Article 100066"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991523000415/pdfft?md5=93bc70290b7195e2b1eb2cae5826cce6&pid=1-s2.0-S2772991523000415-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135671193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-modal deep fusion for bridge condition assessment 基于多模态深度融合的桥梁状态评估

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-11-01 Epub Date: 2023-10-02 DOI: 10.1016/j.iintel.2023.100061

Mozhgan Momtaz , Tianshu Li , Devin K. Harris , David Lattanzi

{"title":"Multi-modal deep fusion for bridge condition assessment","authors":"Mozhgan Momtaz , Tianshu Li , Devin K. Harris , David Lattanzi","doi":"10.1016/j.iintel.2023.100061","DOIUrl":"https://doi.org/10.1016/j.iintel.2023.100061","url":null,"abstract":"<div><p>Bridge condition rating is a challenging task as it largely depends on the experience-level of the manual inspection and therefore is prone to human errors. The inspection report often consists of a collection of images and sequences of sentences (text) explaining the condition of the considered bridge. In a routine manual bridge inspection, an inspector collects a set of images and textual descriptions of bridge components and assigns an overall condition rating (ranging between 0 and 9) based on the collected information. Unfortunately, this method of bridge inspection has been shown to yield inconsistent condition ratings that correlate with inspector experience. To improve the consistency among image-text inspection data and further predict the accordant condition ratings, this study first provides a collective image-text dataset, extracted from the collection of bridge inspection reports from the Virginia Department of Transportation. Using this dataset, we have developed novel deep learning-base methods for an automatic bridge condition rating prediction based on data fusion between the textual and visual data from the collected report sets.</p><p>Our proposed multi modal deep fusion approach constructs visual and textual representations for images and sentences separately using appropriate encoding functions, and then fuses representations of images and text to enhance the multi-modal prediction performance of the assigned condition ratings. Moreover, we study interpretations of the deployed deep models using saliency maps to identify parts of the image-text inputs that are essential in condition rating predictions. The findings of this study point to potential improvements by leveraging consistent image-text inspection data collection as well as leveraging the proposed deep fusion model to improve the bridge condition prediction rating from both visual and textual reports.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"2 4","pages":"Article 100061"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49891238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying potentially dangerous areas of frost heaving and surfacing of the buried oil pipeline 识别潜在的冻胀危险区域和埋地输油管道的地表

Journal of Infrastructure Intelligence and Resilience Pub Date : 2023-11-01 Epub Date: 2023-09-09 DOI: 10.1016/j.iintel.2023.100054

Alla Yu. Vladova , Yury R. Vladov

{"title":"Identifying potentially dangerous areas of frost heaving and surfacing of the buried oil pipeline","authors":"Alla Yu. Vladova , Yury R. Vladov","doi":"10.1016/j.iintel.2023.100054","DOIUrl":"https://doi.org/10.1016/j.iintel.2023.100054","url":null,"abstract":"<div><p>This scientific study aims to automatically identify potentially dangerous areas of frost heaving and surfacing of a buried oil pipeline using the geological description of soil profile. The geological description of soil profile along the proposed route of a pipeline entails the study and identification of various layers of soil to determine the soil's suitability for pipeline installation and support. Enriching the geological description of soils in the first stage was achieved by creating a family of parameters that characterize the presence of water in two states and the interaction of the buried oil pipeline with soil layers. In the second stage, missed and erroneous soil parameters were restored by searching for similar patterns along the route of the pipeline using the enriched geological description of soil profile. Afterward, the selected areas of frost heaving and surfacing were ranked by potential danger in the third stage. The algorithm developed was shown to reduce the risk of damage to the oil pipeline and enrich the geological description of soil profile without additional field works. The results of the study allowed for the allocation of potentially dangerous areas where frost heaving and surfacing occur. The methodology described in the study can be applied in the midstream segment of the oil and gas industry to minimize the risk of pipeline damage.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"2 4","pages":"Article 100054"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49891239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0