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  • SAGE Publications  (6)
  • 1
    Online Resource
    Online Resource
    Effect of tunneled and nontunneled peripherally inserted central catheter placement: A randomized controlled trial
    SAGE Publications ; 2020
    In:  The Journal of Vascular Access Vol. 21, No. 4 ( 2020-07), p. 511-519
    Details
    In: The Journal of Vascular Access, SAGE Publications, Vol. 21, No. 4 ( 2020-07), p. 511-519
    Abstract: To compare the effect of tunneled and nontunneled peripherally inserted central catheter placement under B-mode ultrasound. Methods: A single center, randomized, controlled, nonblinded, prospective trial was conducted in Guangzhou, China, between July 2018 and May 2019. A total of 174 participants were randomized to the experimental group (tunneled peripherally inserted central catheter) or the control group (nontunneled peripherally inserted central catheter) and were followed until extubation. Basic characteristics, peripherally inserted central catheter characteristics, the incidence of complications, and the costs of peripherally inserted central catheter placement and maintenance were collected. Data were analyzed by intention-to-treat. Results: A total of 168 of the participants had successful peripherally inserted central catheter placements (85/87, 97.7% in the experimental group and 83/87, 95.4% in the control group, P = 0.682). Compared to the control group, the experimental group had a lower incidence of complications during the placement (18.4% vs 32.2%, P = 0.036), a lower incidence of wound oozing (27.6% vs 57.5%, P  〈  0.001), a lower incidence of medical adhesive–related skin injury (9.2% vs 25.3%, P = 0.005), a lower incidence of venous thrombosis (1.1% vs 9.2%, P = 0.034), a lower incidence of catheter dislodgement (1.1% vs 9.2%, P = 0.034), and lower costs of peripherally inserted central catheter maintenance at 1, 2, and 3 months ( P  〈  0.05). Conclusion: Tunneled peripherally inserted central catheter may be recommended for good effectiveness.
    Type of Medium: Online Resource
    ISSN: 1129-7298 , 1724-6032
    URL: Article
    DOI: 10.1177/1129729819888120
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2020
    detail.hit.zdb_id: 2079292-X
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    Online Resource
  • 2
    Online Resource
    Online Resource
    A time-reversal assisted probabilistic fusion strategy for damage localization in plate-like structures using Lamb waves
    SAGE Publications ; 2023
    In:  Structural Health Monitoring
    Details
    In: Structural Health Monitoring, SAGE Publications
    Abstract: Precise damage identification and quantification is of great significance to ensure structural performance and provide early-warning for safety maintenance. In this research, a time-reversal assisted probabilistic strategy is developed to accurately localize damage via baseline-free manner in plate-like structures by fusing damage prediction data obtained from the elliptical trajectory location method (ETLM) and reconstruction algorithm for probabilistic inspection of defects (RAPID) algorithm. Damage features, including time difference for ETLM and correlation coefficient index (CCI) for RAPID algorithm, are extracted from the time-reversal focusing signal using the Hilbert transform (HT). To make full use of the damage-related information contained in the time-reversal focusing signals and improve the localizing accuracy, a decision-level data fusion based on Bayesian inference is proposed to fuse damage features and reconstruct damage information. A series of numerical and experimental studies, including different configurations of damage cases and transducer distributions, were conducted to investigate the performances of the proposed time-reversal assisted probabilistic method on damage localization. Results shows that the proposed method could successfully achieve accurate damage localization via baseline-free manner and significantly reduce the damage artifacts compared to traditional methods.
    Type of Medium: Online Resource
    ISSN: 1475-9217 , 1741-3168
    URL: Article
    DOI: 10.1177/14759217221151040
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2101420-6
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  • 3
    Online Resource
    Online Resource
    An innovative deep neural network–based approach for internal cavity detection of timber columns using percussion sound
    SAGE Publications ; 2022
    In:  Structural Health Monitoring Vol. 21, No. 3 ( 2022-05), p. 1251-1265
    Details
    In: Structural Health Monitoring, SAGE Publications, Vol. 21, No. 3 ( 2022-05), p. 1251-1265
    Abstract: Timber structures have been a dominant form of construction throughout most of history and continued to serve as a widely used staple of civil infrastructure in the modern era. As a natural material, wood is prone to termite damages, which often cause internal cavities for timber structures. Since internal cavities are invisible and greatly weaken structural load-bearing capacity, an effective method to timber internal cavity detection is of great importance to ensure structural safety. This article proposes an innovative deep neural network (DNN)–based approach for internal cavity detection of timber columns using percussion sound. The influence mechanism of percussion sound with the volume change of internal cavity was studied through theoretical and numerical analysis. A series of percussion tests on timber column specimens with different cavity volumes and environmental variations were conducted to validate the feasibility of the proposed DNN-based approach. Experimental results show high accuracy and generality for cavity severity identification regardless of percussion location, column section shape, and environmental effects, implying great potentials of the proposed approach as a fast tool for determining internal cavity of timber structures in field applications.
    Type of Medium: Online Resource
    ISSN: 1475-9217 , 1741-3168
    URL: Article
    DOI: 10.1177/14759217211028524
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 2101420-6
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  • 4
    Online Resource
    Online Resource
    Bayesian Network-Based Service Context Recognition Model
    SAGE Publications ; 2009
    In:  International Journal of Distributed Sensor Networks Vol. 5, No. 1 ( 2009-01-01), p. 80-80
    Details
    In: International Journal of Distributed Sensor Networks, SAGE Publications, Vol. 5, No. 1 ( 2009-01-01), p. 80-80
    Abstract: Service context refers to the environmental information which influences the service execution. The processing of service context information is the foundation of the future intelligent telecommunication services in the ubiquitous convergent network. As the complexity and variability of the real world, there exists a large number of uncertain service context information, such as the imprecise information collected by sensors, data noise, and inaccurate location by different location technologies. Hence, it is crucial to recognize the correct service context environment based on unreliable context information. In recent years, context computing and context-awareness have become a major topic of research in an ubiquitous computing field. Ontology technology is often used to support context modeling and reasoning. And the probability theory, especially the Bayesian network, is adopted to deal with uncertainty. However, much of the existing relevant research work mainly concentrated on the modeling and reasoning of context information. But the way to construct and evolve the service context recognition model supporting uncertain reasoning effectively and systematically has not involved. In addition, most of the relative work is only the qualitative analysis, and lacks the quantitative performance analysis and experimental verification. What is more, the research on how to apply context-awareness technology to the telecommunication field and support the intelligence and individualization of the service is scarce. In this article, we combine context-awareness technology with telecommunication service network, and discuss the mechanism of service intelligence in ubiquitous convergent network environment. Then a construction method of the service context recognition model based on the Bayesian Network is put forward. The process of constructing the Bayesian network-based service context recognition model is mainly divided into the following steps: First, according to different service requirements and scenarios, the specific context problem domain should be specified; second, constructing the service context recognition model, which includes the determination of the topology structure and the node probability distribution of Bayesian network; third, when the preliminary Bayesian network-based service context recognition model is constructed, it could be initially applied to the practical system to do the clustering or causality analysis; and last, when the model cannot satisfy the need, the model update should be performed based on the feedback information of the evaluation step and the newly-generated plentiful sample data. This approach has been applied to intelligent access adaptation processing of call service in the office environment. The experimental results show that this approach can strengthen the intelligence of service and compensate for restrictions of certain reasoning.
    Type of Medium: Online Resource
    ISSN: 1550-1477 , 1550-1477
    URL: Article
    DOI: 10.1080/15501320802571830
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2009
    detail.hit.zdb_id: 2192922-1
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  • 5
    Online Resource
    Online Resource
    A novel intelligent inspection robot with deep stereo vision for three-dimensional concrete damage detection and quantification
    SAGE Publications ; 2022
    In:  Structural Health Monitoring Vol. 21, No. 3 ( 2022-05), p. 788-802
    Details
    In: Structural Health Monitoring, SAGE Publications, Vol. 21, No. 3 ( 2022-05), p. 788-802
    Abstract: Crack assessment of reinforced concrete structures using stereo cameras is a potential way for increasing the efficiency and safety of infrastructure maintenance routines. However, existing damage methods for reinforced concrete structures are based on the segmentation of two-dimensional planes without consideration to the actual size of concrete damage. Furthermore, on-site structural monitoring requires the installation of a large number of contact-based sensing devices, resulting in the potentially excessive consumption of time and financial resources. Therefore, a new vision-based damage assessment method for reinforced concrete structures using a novel intelligent inspection robot with Internet of things–enabled data communication system is proposed in this article. In the first part of this article, the data acquisition system of the inspection robot and the algorithm for three-dimensional structural reconstruction using a stereo camera is discussed. The discussion is followed by a description of the method for crack quantification based on a new proposed deep-learning technique. Finally, to accomplish damage localization, the quantified concrete damage with actual size information is projected onto a three-dimensional surface point cloud reconstruction of the inspected structure. To verify the proposed method, a reinforced concrete column that has undergone cyclic loading failure is used as an inspection subject. The validation experiment demonstrated the ability of the proposed system to segment, localize, and quantify the damage in three-dimensional space with high accuracy.
    Type of Medium: Online Resource
    ISSN: 1475-9217 , 1741-3168
    URL: Article
    DOI: 10.1177/14759217211010238
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 2101420-6
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  • 6
    Online Resource
    Online Resource
    Aurora-A Regulates Progression and Metastasis of Colorectal Cancer by Promoting Slug Activity
    SAGE Publications ; 2017
    In:  Technology in Cancer Research & Treatment Vol. 16, No. 6 ( 2017-12), p. 766-775
    Details
    In: Technology in Cancer Research & Treatment, SAGE Publications, Vol. 16, No. 6 ( 2017-12), p. 766-775
    Type of Medium: Online Resource
    ISSN: 1533-0346 , 1533-0338
    URL: Article
    DOI: 10.1177/1533034616682172
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2017
    detail.hit.zdb_id: 2146365-7
    detail.hit.zdb_id: 2220436-2
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