Independent path‐based process recommendation algorithm for improving biomedical process modelling

Wang, Jiaxing; Tan, Dapeng; Cao, Bin; Fan, Jiulun; Deep, Samundra

doi:10.1049/el.2019.3978

Cited by 9 publications

(3 citation statements)

References 7 publications

(12 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Current recommender systems that deal with biomedical data, target different tasks, such as recommending ontologies to annotate biomedical text [39], model biological processes [40], recommending drugs to target SARS-CoV-2 regarding the COVID-19 pandemic [41], recommending entities of potential interest to specific researchers [12], or even recommending articles to expand existing biomedical datasets [42]. There is also a focus on recommending articles and venues to researchers to limit their search space [43], [44], for instance, by performing keyword-based recommendation [45].…”

Section: Related Workmentioning

confidence: 99%

Biomedical Relation Extraction With Knowledge Graph-Based Recommendations

Sousa

Couto

2022

IEEE J. Biomed. Health Inform.

View full text Add to dashboard Cite

Biomedical Relation Extraction (RE) systems identify and classify relations between biomedical entities to enhance our knowledge of biological and medical processes. Most state-of-the-art systems use deep learning approaches, mainly to target relations between entities of the same type, such as proteins or pharmacological substances. However, these systems are mostly restricted to what they directly identify on the text and ignore specialized domain knowledge bases, such as ontologies, that formalize and integrate biomedical information typically structured as direct acyclic graphs. On the other hand, Knowledge Graph (KG)-based recommendation systems already showed the importance of integrating KGs to add additional features to items. Typical systems have users as people and items that can range from movies to books, which people saw or read and classified according to their satisfaction rate. This work proposes to integrate KGs into biomedical RE through a recommendation model to further improve their range of action. We developed a new RE system, named K-BiOnt, by integrating a baseline state-of-theart deep biomedical RE system with an existing KG-based recommendation state-of-the-art system. Our results show that adding recommendations from KG-based recommendation improves the system's ability to identify true relations that the baseline deep RE model could not extract from the text. The code supporting this system is available at https://github.com/lasigeBioTM/K-BiOnt.

show abstract

Section: Related Workmentioning

confidence: 99%

Biomedical Relation Extraction With Knowledge Graph-Based Recommendations

Sousa

Couto

2022

IEEE J. Biomed. Health Inform.

View full text Add to dashboard Cite

show abstract

“…The method can be used for low/zero speed control for permanent magnet synchronous machines (PMSMs). Tan et al [56][57][58] developed an embedded system of embedded multi-loop parallel processing-measuring integrated controls focusing on the characteristics of high intensity and high impact for sawing as shown in Figure 4. It can effectively restrain the harmonic content of the driving voltage by the linkage control of the loops associated with the sawing process.…”

Section: Processing-measuring Integrated Control Systemmentioning

confidence: 99%

Key Technologies and Development Trends in Advanced Intelligent Sawing Equipments

Wang

Zhang

Tan

2021

Chin. J. Mech. Eng.

Self Cite

View full text Add to dashboard Cite

As a starting point in equipment manufacturing, sawing plays an important role in industrial production. Intelligent manufacturing equipment is an important carrier of intelligent manufacturing technologies. Due to the backwardness of intelligent technology, the comprehensive performance of sawing equipments in China is obviously different from that in foreign countries. State of the art of advanced sawing equipments is investigated along with the technical bottleneck of sawing machine tool manufacturing, and a new industrial scheme of replacing turning-milling by sawing is described. The key technologies of processing-measuring integrated control, multi-body dynamic optimization, the collaborative sawing network framework, the distributed cloud sawing platform, and the self-adapting service method are analyzed; with consideration of the problems of poor processing control stableness, low single machine intelligence level, no on-line processing data service and active flutter suppression of sawing with wide-width and heavy-load working conditions. Suggested directions for further research, industry implementation, and industry-research collaboration are provided.

show abstract

“…The above analysis concluded that the bubble deformation has little effect on particles. With the increase of bubble-wall velocity, the strength of the micro-jet gradually increases until the bubble completely bursts, and at that moment, the maximum of both micro-jet strength and instantaneous speed are reached [58][59][60]. Due to the effect of viscosity and the drag force, the particle velocity drops sharply until it reaches the initial velocity.…”

Section: Bubble Burst Near the Wallmentioning

confidence: 99%

Dynamic Characteristics and Wall Effects of Bubble Bursting in Gas-Liquid-Solid Three-Phase Particle Flow

Wang

et al. 2020

Processes

Self Cite

View full text Add to dashboard Cite

The bubble bursting process existing in the particle flow is a complex gas-liquid-solid three-phase coupling dynamic problem. The bubble bursting mechanism, including dynamic characteristics and wall effects, is not clear. To address the above matters, we present a modeling method for the piecewise linear interface calculation-volume of fluid (PLIC-VOF) based bubble burst. The bubble bursting process near or on the wall is analyzed to reveal the dynamic characteristics of bubble bursting and obtain the effect of a bubble bursting on the surrounding flow field. Then a particle image velocimetry (PIV) based self-developed experimental observation platform is established, and the effectiveness of the proposed method is verified. Research results indicate that, in the high-speed turbulent environment, a large pressure difference existed in the bubble tail, which induces the bubble burst to occur; the distance between the wall and the bubble decreases; the higher the flow velocity is, the less time is acquired for bubble bursting, but when the flow velocity exceeds the critical velocity 50 m/s, more time is needed; the coalescence-burst process of double bubbles increases the bubble bursting time, which causes the acceleration of particle motion to reduce.

show abstract

Independent path‐based process recommendation algorithm for improving biomedical process modelling

Cited by 9 publications

References 7 publications

Biomedical Relation Extraction With Knowledge Graph-Based Recommendations

Biomedical Relation Extraction With Knowledge Graph-Based Recommendations

Key Technologies and Development Trends in Advanced Intelligent Sawing Equipments

Dynamic Characteristics and Wall Effects of Bubble Bursting in Gas-Liquid-Solid Three-Phase Particle Flow

Contact Info

Product

Resources

About