This article is concerned with the reputation-aware Kalman-type distributed filtering (RAKTDF) problem for a class of nonlinear bias-corrupted systems (NBCSs) with a dynamical event-triggered mechanism (DETM). First, a representative unknown input, namely the dynamical bias, is introduced, which is ev...

In this paper, the problem of proportional-integral observer (PIO) design is investigated for a class of discrete-time multi-rate systems with multiple sensors, with the sensor sampling periods being allowed to differ from the system updating periods. The facilitation of communication between...

Purpose: This study aims to explore consumers’ perceptions of retailers’ corporate image, focusing on corporate social responsibility, climate change engagement and sustainability initiatives such as the adoption of recyclable packaging and efforts to reduce carbon footprints and CO2 emissions....

Purpose: Airbnb is one of the world's most successful transactional two-sided digital platforms (TTDPs). However, our understanding of users' motivations for using platforms for value co-creation is limited. This study uses affordance theory to examine the relationships between user...

This study examines elderly consumers’ perceptions of the design of AI insurance chatbot services in a phygital context. Drawing on the extended reality technology (ERT) framework and the stimulus–organism–response (SOR) model, it explores the cognitive–affective dynamics shaping chatbot adoption in&#...

Background: Using the Gompertz–Makeham model, we describe associations between age and the probability of mortality in men with adult-onset testosterone deficiency (TD), stratified by testosterone undecanoate (TU) treatment and type 2 diabetes (T2DM). Methods: We analyzed a registry of 737 men&#x...

Mechanical drawing audits are essential to product design and manufacturing but remain labor-intensive and error-prone, particularly when checking tolerances, surface roughness, materials, treatments and assembly requirements. Although computer vision, document understanding, large language models (LLMs), knowledge ...

Deep learning models deployed in industry often rely on large-scale labeled data, where label noise is unavoidable due to imperfect sensing, human annotation errors, and complex operating environments. Such noisy labels can severely degrade model reliability and limit industrial applicability. To...

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