Electroless Ni–P alloys on nanoporous ATO surface of Ti substrate
AbstractFollowed by well-known AAO templates, anodic titanium oxide (ATO) surface with nanoporous structure has gained extensive attraction as implants due to its excellent surface properties. So, the...
View ArticleElectrochemical characteristics and interfacial contact resistance of...
AbstractThe Ni-P/TiN/PTFE (poly tetra fluoroethylene) composite coatings were prepared by electroless plating method on Ti plate, which was used as bipolar plates of proton exchange membrane fuel cells...
View ArticleWear and Corrosive Behaviors of Electroless Ni-LaCl 3 Composites on...
AbstractTi and its alloys, because of its poor wear and oxidation resistance, have seriously restricted its industrial applications in the dry friction conditions. Herein we reported an easy-handling...
View ArticlePreference-Based Resource and Task Allocation in Business Process Automation
AbstractPreference plays an important role in organisational and human decision making as it may be a manifestation of proven practices or of individual working styles. The significance of the notion...
View ArticleExploring Interpretable Predictive Models for Business Processes
AbstractThere has been a growing interest in the literature on the application of deep learning models for predicting business process behaviour, such as the next event in a case, the time for...
View ArticleExploring Interpretability for Predictive Process Analytics
AbstractIn the context of business process management, predictive analytics has been applied to making predictions about the future state of an ongoing business process instance, for example, when will...
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Study on Metallurgically Prepared Copper-Coated Carbon Fibers Reinforced...
AbstractCarbon materials, like carbon fiber, carbon nanotubes and graphene, were widely used as promising reinforcements to strengthen aluminum matrix composites (AMCs). The dispersion of reinforcement...
View ArticleCollective intelligence evolution using ant colony optimization and neural...
AbstractRecently, theory of collective intelligence (CI) evolution is proposed as a meta algorithm toward artificial general intelligence. But the only implementation of the CI algorithm of the theory...
View ArticleEvaluating Fidelity of Explainable Methods for Predictive Process Analytics
AbstractPredictive process analytics focuses on predicting the future states of running instances of a business process. While advanced machine learning techniques have been used to increase the...
View ArticleOverexpression of miR-1298 attenuates myocardial ischemia–reperfusion injury...
AbstractPrevious studies reported that microRNA-1298 was abnormally expressed in the myocardium of rat hearts after hypoxia/normoxia injury. This study aims to investigate the function and specific...
View ArticleSeeing the Forest for the Trees: Group-Oriented Workforce Analytics
AbstractWorkforce analytics brings data-driven methods to organizations for deriving insights from employee-related data and supports decision making. However, it faces an open challenge of lacking the...
View ArticleEvaluating Stability of Post-hoc Explanations for Business Process Predictions
AbstractPredictive process analytics uses advanced machine learning techniques to accurately predict future states of running business processes. Given the complexity of these predictive models,...
View ArticleNo Time to Dice: Learning Execution Contexts from Event Logs for...
AbstractProcess mining enables extracting insights into human resources working in business processes and supports employee management and process improvement. Often, resources from the same...
View ArticleCrop Harvest Forecast via Agronomy-Informed Process Modelling and Predictive...
AbstractReliable and timely forecasts on crop harvest bring significant benefits to agri-food industries by providing valuable input to complex decisions on production planning. Useful predictions on...
View ArticleGenerating Purpose-Driven Explanations: The Case of Process Predictive Model...
AbstractExplainable AI is an emerging branch of data science that focuses on demystifying the complex computation logic of machine learning with an aim to improve the transparency, validity and trust...
View ArticleAn Optimized Flocking Motion with Attention Module for Obstacle Avoidance
AbstractA flocking control algorithm with attention module for obstacle avoidance is proposed, which is based on the classical rules of Reynolds. To enable the self-organized swarm having better...
View ArticleEmergent Morphogenesis for Robot Swarms in 3D Space
AbstractWe consider the problem of robot swarm emergent morphogenesis in 3D space. In this paper, robots are confined in a columnar boundary with tunable radial steepness. They align themselves...
View ArticleThrough the looking glass: evaluating post hoc explanations using transparent...
AbstractModern machine learning methods allow for complex and in-depth analytics, but the predictive models generated by these methods are often highly complex and lack transparency. Explainable...
View ArticleMDF-Net for abnormality detection by fusing X-rays with clinical data
AbstractThis study investigates the effects of including patients’ clinical information on the performance of deep learning (DL) classifiers for disease location in chest X-ray images. Although current...
View ArticleTowards Data-Driven Business Process Redesign Through the Lens of Process...
AbstractProcess mining is widely used for business process analysis, but rarely informs Business Process Redesign (BPR) activities. We review process mining literature and BPR framework to create...
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