Academic Articles & Research Papers

Electromagnetically Driven Robot for Multipurpose Applications

This paper presents a novel design of a continuum robot driven by electromagnets and springs, offering enhanced precision in multi-degree-of-freedom bending for diverse applications. Traditional continuum robots, while effective in navigati...

Scalable and High-Fidelity Quantum Random Access Memory in Spin-Photon Networks

A quantum random access memory (qRAM) is considered an essential computing unit to enable polynomial speedups in quantum information processing. Proposed implementations include the use of neutral atoms and superconducting circuits to const...

A study on process information-driven cyber threat detection for I&C systems in NPP

The increasing digitalization of Instrumentation and Control (I&C) systems in Nuclear Power Plants (NPPs) has improved operational efficiency while introducing cybersecurity vulnerabilities. Conventional network-based intrusion detection sy...

Improving the trial efficiency of criminal cases with the assistance of artificial intelligence

Abstract This study explores the application of artificial intelligence (AI) in improving the trial efficiency of criminal cases. Using a dataset consisting of 500 criminal case records, including minor, ordinary, and complex cases, we appl...

Advancements in natural language processing: Implications, challenges, and future directions

This research delves into the latest advancements in Natural Language Processing (NLP) and their broader implications, challenges, and future directions. With the ever-increasing volume of text data generated daily from diverse sources, ext...

User‐Based Evaluation of Explainability Techniques for Misogyny Detection in Code‐Mixed Hindi–English

ABSTRACT Although artificial intelligence (AI) models have demonstrated great success and efficiency in automatically countering online hate speech and misogyny, they suffer from a lack of explainability and transparency. Explainable artifi...

Construction of a knowledge graph for the educational statistical indicator system based on large language models

Current statistical work in the field of educational development faces challenges such as low knowledge-retrieval efficiency and high technical barriers to data utilization. This study focuses on the knowledge related to the indicator syste...

Semantic Alignment in Disciplinary Tutoring System: Leveraging Sentence Transformer Technology

In this work, we present a disciplinary e-tutoring system that integrates ONTO-TDM, an ontology designed for teaching domain modeling, with advanced transformer technology. Our primary objective is to enhance semantic similarity tasks withi...

Machine Unlearning: A Perspective, Taxonomy, and Benchmark Evaluation

Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...

Training‐Efficient Personalised Knee Joint Moment Estimation via an Incremental Broad Learning System

ABSTRACT Knee joint moment estimation is a critical component in biomechanical analysis, with profound implications for rehabilitation assessment and the development of assistive devices like exoskeletons. However, existing data‐driven appr...

MFSM: Chinese-English sentence alignment based on multi- feature self-attention mechanism fusion

Bilingual parallel corpora is a very important basic resource in the research field of natural language processing based on statistics. There are cross alignment and empty alignment in Chinese-English bilingual text, it is easy to affect th...

Text Filtering through Multi-Pattern Matching: A Case Study of Wu–Manber–Uy on the Language of Uyghur

Given its generality in applications and its high time-efficiency on big data-sets, in recent years, the technique of text filtering through pattern matching has been attracting increasing attention from the field of information retrieval a...

Label-Guided Data Augmentation for Chinese Named Entity Recognition

Chinese named entity recognition (NER) is a fundamental natural language processing (NLP) task that involves identifying and categorizing entities in text. It plays a crucial role in applications such as information extraction, machine tran...

Construction and practice of an intelligent management system for preoperative anemia based on multidisciplinary collaboration

[Objective] To improve the efficiency and standardization of preoperative anemia diagnosis and treatment by establishing a systematic intelligent management platform for preoperative anemia. [Methods] A multidisciplinary collaborative model...

A natural language processing based technique for sentiment analysis of college english corpus

The college English corpus can help us better master English, but how to obtain the desired information from a large number of English corpus has become the focus of information technology. Based on the natural language processing (NLP) tec...

Natural Language Processing Applications in Business

Increasing dependency of humans on computer-assisted systems has led to researchers focusing on more effective communication technologies that can mimic human interactions as well as understand natural languages and human emotions. The prob...

Digital Transformation and Operational Efficiency in Banking Under Regulatory Solvency Requirements.

Large Language Models in Healthcare and Medical Domain: A Review

The deployment of large language models (LLMs) within the healthcare sector has sparked both enthusiasm and apprehension. These models exhibit the remarkable ability to provide proficient responses to free-text queries, demonstrating a nuan...

The fluency-based semantic network of LLMs differs from humans

Modern Large Language Models (LLMs) exhibit complexity and granularity similar to humans in the field of natural language processing, challenging the boundaries between humans and machines in language understanding and creativity. However, ...

Prioritized replay dueling double DQN for intelligent task scheduling in IoT Fog Cloud computing

Abstract Task scheduling remains a challenge in IoT-Fog-Cloud systems due to dynamic workloads and heterogeneous resources. Ineffective scheduling strategies increase latency, energy consumption, and Service Level Agreement (SLA) violations...