6,625 research outputs found
The effect of water on the dielectric properties of polypropylene/aluminium nitride nanocomposites
No full textA series of aluminium nitride/polypropylene nanocomposites were prepared. Nano aluminium nitride was surface functionalised by silane coupling agents with different hydrolysable groups and the effect of the surface chemistry and preconditioning (i.e., under different relative humidity) on their AC breakdown strength and the DC conductivity was investigated. The effect of water on the nanosilica-based nanocomposites have been studied by many researchers and the dramatically decreased AC breakdown strength and DC resistivity for wet samples were reported[1, 2]. By contrast, aluminium nitride filler with less hydrophilic sites, hydroxyl groups, was applied in this study. Furthermore, octyl silanes were adopted and the displacement of hydroxyl groups to short carbon chain on the particle surface is expected.The preconditioning results show that the silane functionalisation can effectively reduce the amount of water absorbed during 15 days of immersion in deionized water. The dielectric properties show a high dependency on the sample preconditioning and water content. The DC conductivity of the non-treated aluminium nitride/polypropylene nanocomposites is 2 orders of magnitude higher than the octyl functionalised silane. Similar behaviour was observed on the AC breakdown data. However, the difference between systems treated with silane coupling agent with different hydrolysable groups cannot be seen from the weight monitoring and dielectric properties mentioned above. Although the dielectric results in [3] show the different hydrolysable groups might bring different bonding structure between nanoparticle and silane coupling agents, the interaction with water seems to have less dependency on it.In this study, It can be concluded that the nanoparticle surface chemistry is very important in determining the macroscopic properties, especially in a humid environment. The surface functionalisation by silane coupling agent can effectively minimise the hydrophobicity of nanocomposites.[1] D Qiang, Y Wang, G Chen, and T. Andritsch, "Influence of Water Absorption on Space Charge Behavior of Epoxy Nanocomposites," 2016.[2] I. Hosier, M. Praeger, A. Holt, A. Vaughan, and S. Swingler, "On the effect of functionalizer chain length and water content in polyethylene/silica nanocomposites: Part I—Dielectric properties and breakdown strength," IEEE Transactions on Dielectrics and Electrical Insulation, vol. 24, no. 3, pp. 1698-1707, 2017.[3] X. Wang, T. Andritsch, and G. Chen, "Effect of Surface Functionalization on the Dielectric Properties of Polypropylene Aluminium Nitride Nanocomposites," in 2018 IEEE 2nd International Conference on Dielectrics (ICD), 2018, pp. 1-4: IEEE
Data&code-Right visual field advantage in orientation discrimination based on left field suppression
No full text
All the data corresponds to the paper:
Right visual field advantage in orientation discrimination based on left field suppression
Authors: Xinyu Chen, Liyu Cao and Barbara Haendel</p
XinYu-Chen98/Hybrid-ATL-and-expert-knowledge-for-materials-design: v1.0.0
No full text<p>Source code and data for 'From bulk effective mass to 2D carrier mobility accurate prediction via adversarial transfer learning'</p>
Supplemental Material - Clinical Significance of Pim-1 in Human Cancers: A Meta-analysis of Association with Prognosis and Clinicopathological Characteristics
No full textSupplemental Material for Clinical Significance of Pim-1 in Human Cancers: A Meta-analysis of Association with Prognosis and Clinicopathological Characteristics by Lin Lai, MS, Ge Tian, BS, Xinyu Chen, MS, Renba Liang, MD, Xishan Chen, MD, Yuelan Qin, BS, Kaihua Chen, MD, and Xiaodong Zhu, MD in Cancer Control.</p
Slides | Missing traffic data imputation and pattern discovery with a Bayesian augmented tensor factorization model
No full textSpatiotemporal traffic data, which represent multidimensional time series on considering different spatial locations, are ubiquitous in real-world transportation systems. However, the inevitable missing data problem makes data-driven intelligent transportation systems suffer from the incorrect response. Therefore, imputing missing values is of great importance but challenging as it is not easy to capture spatiotemporal traffic patterns, including explicit and latent features. In this study, we propose an augmented tensor factorization model by incorporating generic forms of domain knowledge from transportation systems. Specifically, we present a fully Bayesian framework for automatically learning parameters of this model using variational Bayes (VB). Relying on the publicly available urban traffic speed data set collected in Guangzhou, China, experiments on two types of missing data scenarios (i.e., random and non-random) demonstrate that the proposed Bayesian augmented tensor factorization (BATF) model achieves best imputation accuracies and outperforms the state-of-the-art baselines (e.g., Bayesian tensor factorization models). Besides, we discover interpretable patterns from the experimentally learned global parameter, biases, and latent factors that indeed conform to the dynamic of traffic states.
If you find this slide is helpful in your research, please consider citing our article:
Xinyu Chen, Zhaocheng He, Yixian Chen, Yuhuan Lu, Jiawei Wang (2019). Missing traffic data imputation and pattern discovery with a Bayesian augmented tensor factorization model. Transportation Research Part C: Emerging Technologies, 104: 66-77. [preprint] [doi] [slide] [data] [Matlab code] [Python code
Visual selective attention_ walking/standing_Singletontask
No full textIn the SelectiveAttentionData folder, the sub-folder [LabrecorderData] include the raw data of all 31 participants.The sub-folder [StimuliData] include the information of stimuli presentation in each trial of all 31 participants.All the data corresponds to the paper:'Differential effects of walking across visual cortical processing stages'Authors: Xinyu Chen, Liyu Cao and Barbara Haendel</div
Supplemental Material - Modeling land-use change using partitioned vector cellular automata while considering urban spatial structure
No full textSupplemental Material for Modeling land-use change using partitioned vector cellular automata while considering urban spatial structure by Jing Yang, Xinyu Zhu, Wei Chen, Yizhong Sun and Jie Zhu in Environment and Planning B: Urban Analytics and City Science</p
Influence of the amount of silane coupling agent on the dielectric properties of AlN/polypropylene nanocomposites
No full textIn this work, four loading amounts of trimethoxy (octyl) silane (C8-M) were used in preparing C8-M treated AlN/polypropylene nanocomposites. Although the thermal gravimetric analysis shows a significant difference in the amount of C8-M grafted on the AlN surface, and a saturation point can be reached as the amount of C8-M added increases, the AC breakdown strengths of composites present virtually identical results. Similar behaviours can be observed in the real and imaginary permittivity from 0.01 Hz to 100 kHz, although the upturns of the imaginary permittivity at low frequency are observed increasing with the amount of C8-M used. Seemingly contradictory to a previously reported work on epoxy with nanosilica, AlN/polypropylene is largely unaffected by the amount of the silane coupling agent applied during the surface treatment
Critical Success Factors in Agile-Based Digital Transformation Projects
No full textDigital transformation (DT) requires organizations to navigate complex technological and organizational changes, often under conditions of uncertainty. While agile methodologies are widely adopted to address the iterative and cross-functional nature of DT, limited attention has been paid to identifying critical success factors (CSFs) from a socio-technical systems (STS) perspective. This study addresses that gap by integrating and prioritizing CSFs as interdependent elements within a layered socio-technical framework. Drawing on a systematic review of 17 empirical and conceptual studies, we adapt Chow and Cao’s agile success model and validate a set of 14 CSFs across five domains—organizational, people, process, technical, and project—through a Delphi-informed Analytic Hierarchy Process (AHP). The findings reveal that organizational and people-related enablers, particularly management commitment, team capability, and organizational environment, carry the greatest weight in agile-based DT contexts. These results inform a three-layered framework—comprising organizational readiness, agile delivery, and project artefacts—which reflects how social, technical, and procedural factors interact systemically. The study contributes both theoretically, by operationalizing STS theory in the agile DT domain, and practically, by providing a prioritized CSF model to guide strategic planning and resource allocation in transformation initiatives
Effect of surface functionalization on the dielectric properties of polypropylene aluminium nitride nanocomposites
No full textPolymer nanocomposites can potentially provide many advantages and the interaction region between polymer and nanoparticles—the so-called interphase is usually considered to be responsible for the change of properties. In this work, nanoaluminium nitride powders with various surface states obtained by three different silane coupling agents (SCA) and an untreated powder, were blended with isotactic polypropylene. AC breakdown strength and dielectric spectroscopy were used to study the effect of different particle surfaces and polymerparticle interphases. The nano-aluminium nitride powder grafted with different organofunctional groups can provide a number of potential interactions with the matrix polymer. The results show that it can not only affect the dispersion state of nanoparticles but will provide different impacts on the dielectric properties of the bulk material. The hydrolysable groups of SCA, notably, can also influence the dielectric properties through altering the surface chemistry of nanoparticles
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