Purpose This paper aims to conceptualize the digital behavior of startups and investigate the
emerging behaviors about digital strategies of the Italian startup firms enrolled in the Startup …

The wide-ranging applications of large language models (LLMs), especially in safety-critical
domains, necessitate the proper evaluation of the LLM's adversarial robustness. This paper …

Recent years have witnessed a burgeoning interest in federated learning (FL). However, the
contexts in which clients engage in sequential learning remain under-explored. Bridging FL …

PURPOSE: This research was performed to compare Islamic and Western ethical values in
health services management. APPROACH: Whittemore and Knafl's integrative review was …

Supervised classification is a common field of machine learning. However, the existing
classification methods based on deep models are vulnerable to overfitting the noisy labels in …

The annotation of pathological images often introduces label noise, which can lead to
overfitting and notably degrade performance. Recent studies have attempted to address this …

Graph neural networks (GNNs) have been extensively employed in node classification.
Nevertheless, recent studies indicate that GNNs are vulnerable to topological perturbations …

This thesis investigates the phenomenon of self-disclosure and relationship development
through a case study of a group of Malaysian female bloggers known as 'Scarflet Sisters' …

The objective of this paper is to analyze two research tools applied in the social sciences for
quantitative and qualitative studies respectively, namely codebook, or coding scheme, and …