PROCESS-ORIENTED KNOWLEDGE DISCOVERY TO SUPPORT PRODUCT DESIGN USING TEXT MINING

Ph.DDOCTOR OF PHILOSOPH

Learning from the past: uncovering design process models using an enriched process mining

Design documents and design project footprints accumulated by corporate IT systems have increasingly become valuable sources of evidence for design information and knowledge management. Identification and extraction of such embedded information and knowledge into a clear and usable format will greatly accelerate continuous learning from past design efforts for competitive product innovation and efficient design process management in future design projects. Different from existing systems, this paper proposes a methodology of learning and extracting useful knowledge using past design project documents from design process perspective based on process mining techniques. A new process mining approach that is able to directly handle textual data is proposed at the first stage of the proposed methodology. The outcome is a hierarchical process model that reveals the actual design process hidden behind a large amount of design documents and enables the connection of various design information from different perspectives. At the second stage, the discovered process model is further refined to learn multi-faceted knowledge patterns by applying a number of statistical analysis methods. The outcomes range from task dependency study from workflow analysis, identification of irregular task execution from performance analysis, cooperation pattern discovery from social net analysis, to evaluation of personal contribution based on role analysis. Relying on the knowledge patterns extracted, lessons and best practices can be uncovered which offer great support to decision makers in managing any future design initiatives. The proposed methodology was tested using an email dataset from a university-hosted multi-year multidisciplinary design project

Maternal positive coparenting and adolescent ego-identity: the chain mediating role of fathers’ marital satisfaction and adolescent peer relationships

IntroductionBased on the ecological systems theory and the family systems theory, this study explores the mechanisms underlying the effects of maternal positive coparenting on adolescent ego-identity.MethodsThis study employed the Maternal Positive Coparenting Scale to assess mothers, the Father Marital Satisfaction Scale to examine fathers, and the Adolescent Peer Relationship Scale, along with the Ego-Identity Scale, to evaluate adolescents. This comprehensive approach involved investigating 522 families, encompassing both parents and adolescents.ResultsThe results obtained indicate a significant positive correlation between maternal positive coparenting and adolescent ego-identity. Peer relationships mediated the relationship between maternal positive coparenting and adolescent ego-identity. Father marital satisfaction mediated the relationship between maternal positive coparenting and adolescent ego-identity insignificantly. Paternal marital satisfaction and adolescent peer relationship have a chain mediating role between maternal positive coparenting and adolescent ego-identity. The study contributes by offering insights from the perspectives of family and peer relationships for further enhancing the development of adolescent ego-identity

Towards Deeply Unified Depth-aware Panoptic Segmentation with Bi-directional Guidance Learning

Depth-aware panoptic segmentation is an emerging topic in computer vision which combines semantic and geometric understanding for more robust scene interpretation. Recent works pursue unified frameworks to tackle this challenge but mostly still treat it as two individual learning tasks, which limits their potential for exploring cross-domain information. We propose a deeply unified framework for depth-aware panoptic segmentation, which performs joint segmentation and depth estimation both in a per-segment manner with identical object queries. To narrow the gap between the two tasks, we further design a geometric query enhancement method, which is able to integrate scene geometry into object queries using latent representations. In addition, we propose a bi-directional guidance learning approach to facilitate cross-task feature learning by taking advantage of their mutual relations. Our method sets the new state of the art for depth-aware panoptic segmentation on both Cityscapes-DVPS and SemKITTI-DVPS datasets. Moreover, our guidance learning approach is shown to deliver performance improvement even under incomplete supervision labels.Comment: to be published in ICCV 202

The pattern of gray matter atrophy in Parkinson’s disease differs in cortical and subcortical regions

Cortical and subcortical gray matter (GM) atrophy may progress differently during the course of Parkinson's disease (PD). We delineated and compared the longitudinal pattern of these PD-related changes

A BAHD acyltransferase contributes to the biosynthesis of both ethyl benzoate and methyl benzoate in the flowers of Lilium oriental hybrid ‘Siberia’

Lily is a popular flower worldwide due to its elegant appearance and pleasant fragrance. Floral volatiles of lily are predominated by monoterpenes and benzenoids. While a number of genes for monoterpene biosynthesis have been characterized, the molecular mechanism underlying floral benzenoid formation in lily remains unclear. Here, we report on the identification and characterization of a novel BAHD acyltransferase gene that contributes to the biosynthesis of two related floral scent benzoate esters, ethyl benzoate and methyl benzoate, in the scented Lilium oriental hybrid ‘Siberia’. The emission of both methyl benzoate and ethyl benzoate in L. ‘Siberia’ was found to be tepal-specific, floral development-regulated and rhythmic. Through transcriptome profiling and bioinformatic analysis, a BAHD acyltransferase gene designated LoAAT1 was identified as the top candidate gene for the production of ethyl benzoate. In vitro enzyme assays and substrate feeding assays provide substantial evidence that LoAAT1 is responsible for the biosynthesis of ethyl benzoate. It was interesting to note that in in vitro enzyme assay, LoAAT1 can also catalyze the formation of methyl benzoate, which is typically formed by the action of benzoic acid methyltransferase (BAMT). The lack of an expressed putative BAMT gene in the flower transcriptome of L. ‘Siberia’, together with biochemical and expression evidence, led us to conclude that LoAAT1 is also responsible for, or at least contributes to, the biosynthesis of the floral scent compound methyl benzoate. This is the first report that a member of the plant BAHD acyltransferase family contributes to the production of both ethyl benzoate and methyl benzoate, presenting a new mechanism for the biosynthesis of benzoate esters

Reactivation of Epstein–Barr virus by a dual-responsive fluorescent EBNA1-targeting agent with Zn2+-chelating function

EBNA1 is the only Epstein–Barr virus (EBV) latent protein responsible for viral genome maintenance and is expressed in all EBV-infected cells. Zn2+ is essential for oligomerization of the functional EBNA1. We constructed an EBNA1 binding peptide with a Zn2+ chelator to create an EBNA1-specific inhibitor (ZRL5P4). ZRL5P4 by itself is sufficient to reactivate EBV from its latent infection. ZRL5P4 is able to emit unique responsive fluorescent signals once it binds with EBNA1 and a Zn2+ ion. ZRL5P4 can selectively disrupt the EBNA1 oligomerization and cause nasopharyngeal carcinoma (NPC) tumor shrinkage, possibly due to EBV lytic induction. Dicer1 seems essential for this lytic reactivation. As can been seen, EBNA1 is likely to maintain NPC cell survival by suppressing viral reactivation