Search
Search Results
-
DQMMBSC: design of an augmented deep Q-learning model for mining optimisation in IIoT via hybrid-bioinspired blockchain shards and contextual consensus
Single-chained blockchains are highly secure but cannot be scaled to larger IIoT (Internet of Industrial Things) network scenarios due to storage...
-
How to measure interdisciplinary research? A systemic design for the model of measurement
Interdisciplinarity is a polysemous concept with multiple, reasoned and intuitive, interpretations across scholars and policy-makers. Historically,...
-
Are reviewer scores consistent with citations?
Academic evaluation is a critical component of research, with the interaction between quantitative and qualitative assessments becoming a prominent...
-
An enhanced energy and distance based optimized clustering and dynamic adaptive cluster-based routing in software defined vehicular network
Software-Defined Vehicular Networks (SDVN) have been established to facilitate secure and adaptable vehicle communication within the dynamic...
-
SIM-GCN: similarity graph convolutional networks for charges prediction
In recent years, the analysis of legal judgments and the prediction of outcomes based on case factual descriptions have become hot research topics in...
-
From PARIS to LE-PARIS: toward patent response automation with recommender systems and collaborative large language models
In patent prosecution, timely and effective responses to Office Actions (OAs) are crucial for securing patents. However, past automation and...
-
-
Hierarchical adaptive evolution framework for privacy-preserving data publishing
The growing need for data publication and the escalating concerns regarding data privacy have led to a surge in interest in Privacy-Preserving Data...
-
From informal to formal: scientific knowledge role transition prediction
Comprehending the patterns of knowledge evolution benefits funding agencies, policymakers, and researchers in develo** creative ideas. We introduce...
-
HyperMatch: long-form text matching via hypergraph convolutional networks
Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer...
-
Anomaly analytics in data-driven machine learning applications
Machine learning is used widely to create a range of prediction or classification models. The quality of the machine learning (ML) models depends not...
-
The cost of open access: comparing public projects’ budgets and article processing charges expenditure
Open Access (OA) publication often entails payment of Article processing charges (APCs), particularly in the so-called Hybrid and Gold journals. The...
-
Linguistic perspectives in deciphering citation function classification
Understanding citations within their context is a complex task in information science, critical for bibliometric analysis. The study of citation...
-
Temporal analysis of computational economics: a topic modeling approach
This study offers a comprehensive investigation into the thematic evolution within computational economics over the past two decades, leveraging...
-
De-confounding representation learning for counterfactual inference on continuous treatment via generative adversarial network
Counterfactual inference for continuous rather than binary treatment variables is more common in real-world causal inference tasks. While there are...
-
Exploring the potential of Easy Language for enhancing website sustainability
Sustainable design principles have become increasingly important in website development, mainly focusing on reducing carbon emissions and energy...
-
Systematizing modeler experience (MX) in model-driven engineering success stories
Modeling is often associated with complex and heavy tooling, leading to a negative perception among practitioners. However, alternative paradigms,...
-
A novel PLS technique for secure ESM based MIMO systems
Multiple-input multiple-output systems with spatial modulation has evolved into an energy efficient and less complex wireless transmission system due...
-
Gradient-based explanation for non-linear non-parametric dimensionality reduction
Dimensionality reduction (DR) is a popular technique that shows great results to analyze high-dimensional data. Generally, DR is used to produce...
