Inductive knowledge graph completion (KGC) aims to infer the missing relation for a set of newly-coming entities that never appeared in the training set. Such a setting is more in line with reality, as real-world KGs are constantly evolving and introducing new knowledge. Recent studies have shown promising results using message passing over subgraphs to embed newly-coming entities for inductive KGC. However, the inductive capability of these methods is usually limited by two key issues. (i) KGC always suffers from data sparsity, and the situation is even exacerbated in inductive KGC where new entities often have few or no connections to the original KG. (ii) Cold-start problem. It is over coarse-grained for accurate KG reasoning to generate representations for new entities by gathering the local information from few neighbors. To this end, we propose a novel iNfOmax RelAtion Network, namely NORAN, for inductive KG completion. It aims to mine latent relation patterns for inductive KG completion. Specifically, by centering on relations, NORAN provides a hyper view towards KG modeling, where the correlations between relations can be naturally captured as entity-independent logical evidence to conduct inductive KGC. Extensive experiment results on five benchmarks show that our framework substantially outperforms the state-of-the-art KGC methods.

In the conceptual design and early embodiment design stages, an effective kinematic prototype can assist in detecting design errors, minimizing unnecessary parameter modifications, and optimizing subsequent resource deployment. Existing methods for creating prototypes, such as 2D sketches, 3D modelling, or analysis software, have their advantages in precise modelling and simulation . However, there is a lack of an efficient approach that can achieve both rapid 3D kinematic idea generation and early on-site interactive verification. To address these challenges, this research proposes a Mixed Reality (MR)-enhanced kinematic prototyping approach for articulated products to enable the rapid generation of 3D kinematic concepts, movement preview, and early interactions with users or the actual workspace. The proposed approach facilitates the quick and rough construction of geometry and kinematic structures through intuitive hand gestures and interactive movement preview within the MR environment. The usability of the proposed approach was evaluated by a comparison experiment with traditional sketch and CAD tools involving eight participants. It is verified that our proposed MR kinematic prototyping system could accelerate the kinematic prototype generation process, improve the user’s kinematic understanding, and facilitate on-site interactive verification in advance.

The rapid development and implementation of smart, connected products (SCPs) in the engineering field has triggered a promising manufacturing paradigm of servitization, i.e. smart product-service systems (Smart PSS). As a complex solution bundle in both system and product level, its engineering change management differs from the existing ones mainly in two aspects. Firstly, massive in-context stakeholder-generated/product-sensed data during usage stage can be leveraged to enable its success in a data-driven manner. Secondly, the digitalized services, consisting of both hardware and software solutions, can also be changed in a more flexible way other than the physical components alone. Nevertheless, scarcely any work reports on how to conduct engineering change in such context, let alone a systematic approach to support the automatic generation of its change prediction or recommendation. Aiming to fill these gaps, this work proposes an occurrence-based design structure matrix (DSM) approach together with a three-way based cost-sensitive learning approach for automatic engineering change management in the Smart PSS environment. This informatics-based research, as an explorative study, overcomes the subjectivity and tedious assessment of the experts in the conventional approaches, and can offer useful guidelines to the manufacturing companies for managing their engineering changes for product-service innovation process.