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Demonstrative learning in virtual reality (VR) is a pivotal learning strategy for knowledge transfer for embodied agents. While existing studies have extensively explored agents’ knowledge transfer through self-demonstrative learning (SDL) or teacher-...

The next point of interest (POI) recommendation task recommends POIs to users that they may be interested in next time based on their historical trajectories. This task holds value for both users and businesses. However, it has consistently faced the ...

The impact of benevolence-based trust on knowledge transfer is understudied in Bangladesh's NGO sector, which is home to more NGOs than any other nation in the world (with a comparable geographic size). The study aims to examine the effects of ...

A nudge is a concept from Behavioral Economics and Psychology that refers to any small change or intervention designed to influence people's behavior predictably, without restricting their options or significantly altering their incentives. The research ...

Knowledge transfer from a source to a target domain is vital for whole slide image classification, given the limited dataset size due to high annotation costs. However, domain shift and task discrepancy between datasets can impede this process. To ...

Compared to the in-air case, underwater depth estimation has its own challenges. For instance, acquiring high-quality training datasets with groundtruth poses difficulties due to sensor limitations in aquatic environments. Additionally, the ...

Source free domain adaptation (SFDA) aims to transfer the model trained on labeled source domain to unlabeled target domain without accessing source data. Recent SFDA methods predominantly rely on self-training, which supervise the model with ...

This work utilizes advanced reinforcement learning techniques to optimize the docking process of unmanned surface vessels (USVs) in challenging maritime environments. The proposed methodology accounts for fluctuating environmental conditions, such as wind,...

Federated Distillation (FD) is a novel and promising distributed machine learning paradigm, where knowledge distillation is leveraged to facilitate a more efficient and flexible cross-device knowledge transfer in federated learning. By optimizing ...

This paper emphasizes the significance of employing methodological approaches rooted in participatory design to facilitate intergenerational collaboration in an age range less studied (generations X to Y) in developing a web-based newsroom for ...

With the widespread accessibility of the Internet, individuals can effortlessly access health-related information from online social platforms. However, the veracity of such health-related content is often questionable, posing a significant ...

Research on university – industry collaboration ideologies, operations and activities for improvement of effective cooperation in industry 4.0 era. Utilizing over 65 years of experience on effective collaboration, inc. advisory notes, experiences, proven ...

German companies are currently facing challenges like the Demographic Change. Due to the retirement of many long-standing employees, companies risk losing tacit experimental know-how. This specific type of knowledge is difficult to capture and ...

Knowledge Amalgamation (KA), aiming to transfer knowledge from multiple well-trained teacher networks to a multi-talented and compact student, is gaining attention due to its crucial role in resource-constrained scenarios. Previous literature on ...

Knowledge Transfer is one of the essential principles in education. The teacher’s knowledge is encoded through speech and writing and transmitted to the student. The student then decodes the transmitted information according to individual capabilities ...

The aim of our research is the enhancement of decision support methods grounded in statistical quality control. In our study we combine machine learning classifiers, and explanatory algorithms (XAI) with the Six Sigma practice to automate the ...

Radio-Frequency (RF) based human activity recognition (HAR) enables many attractive applications such as smart home, health monitoring, and virtual reality (VR). Among multiple RF sensors, mmWave radar is emerging as a new trend due to its fine-grained ...

Single-image dehazing is an essential but challenging computer vision problem. Due to the lack of nonhomogeneous haze datasets, most existing image dehazing methods are only applicable to homogeneous rather than nonhomogeneous dehazing tasks. In ...

This study investigates the effects of the alliance network structural properties on corporate social responsibility (CSR) knowledge transfer in the interfirm network context. Alliances and partnerships allow firms to access valuable CSR knowledge. ...

How local industrial clusters realize industrial upgrading in the development process of embedded global value chain is the central topic. To explore how industrial clusters achieve the enhancement of their innovation capability and value chains when ...