Academic Articles & Research Papers

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...

SABER: a multiparental tomato population leveraging wild relative diversity for high-resolution QTL mapping.

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. ...

Understanding the regulatory grammar of sepsis-causing Staphylococcus aureus bacteria using contexualised DNA language models

Abstract To efficiently and accurately understand, detect, and treat sepsis, we require a deep understanding of how its underlying biological systems work. Conventional methods struggle to provide a detailed view of both the functional and ...

«СЛУЖБОВЦІ» В УКРАЇНСЬКИХ ХУДОЖНІХ ПЕРЕКЛАДАХ ПЕРІОДУ 1920-30-Х РОКІВ (на матеріалі скорочених перекладів-переказів Е. Збарської)

Досліджується привнесення до перекладів-переказів Е.Збарської творів Джеймса Олівера Кервуда “Казан” та “Казанів син” іменника “служба” та похідного від нього іменника “службовець”. До тексту перекладу іменник “служба” потрапляє шляхом пара...

Natural language processing for information assurance and security

This research paper explores a promising interface between natural language processing (NLP) and information assurance and security (IAS). More specificall~ it is devoted to possible applications to, and further dedicated development of, th...

Contrasting Spatial Genomic Structure in Two Widespread Grassland Species Across Norway Supports Species‐Specific Seed Sourcing.

Domain-Specific Sentiment Analysis: An Optimized Deep Learning Approach for the Financial Markets

Although different studies are caried out by deep learning models for financial markets sentiment analysis, there is a lack of specific embedding method that regards the domain. Therefore, the goal of this study is to discover what type of ...

Ensembles machine learning for short duration rainfall intensity forecasting

Abstract This study introduces an ensemble machine learning (EML) framework to enhance short-duration rainfall-intensity prediction under limited-data conditions. By integrating multiple base learners within a stacking architecture, the pro...

Automated Encoding of Clinical Documents Based on Natural Language Processing

OBJECTIVE: The aim of this study was to develop a method based on natural language processing (NLP) that automatically maps an entire clinical document to codes with modifiers and to quantitatively evaluate the method. METHODS: An existing ...

Analyzing Brain Tumor Classification Techniques: A Comprehensive Survey

Classification of brain tumour is critical in medical image analysis and diagnosis as it aids in determining the affinity of cases to select treatment paths. This feature underscores the importance of accurate classification of brain tumour...

Development and External Validation of a Machine Learning Model for Automated Feedback Quality Assessment in Chinese Anesthesiology Residency Training

Lifeng Yao, Yijun Chen, Jing Shen, Junge Zhang, Yiwei Zhang, Guojin Liang, Yiqin Ji Department of Anesthesiology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of ChinaCorrespondence: Yijun Chen, De...

Natural language processing: state of the art, current trends and challenges

Specialized Large Language Model for Standardization of Locomotive Maintenance Data

Standardization is one of the key steps to analyze locomotive overhaul data with a focus on reliability-centered maintenance (RCM). However, traditional manual methods encounter challenges such as small sample sizes, non-standardized data f...

Humor and Resistance in Pakistani Corporate Memes

This study aims at investigating how humor is constructed in corporate memes through cognitive mechanisms and how corporate memes are used as a collective voice by Pakistani employees to express discontent with their work culture and organi...

Link Predictions with Bi-Level Routing Attention

Background/Objectives: Knowledge Graphs (KGs) are often incomplete, which can significantly impact the performance of downstream applications. Manual completion of KGs is time-consuming and costly, emphasizing the importance of developing a...

Machine Learning in Computer Vision: A Review

INTRODUCTION: Due to the advancement in the field of Artificial Intelligence (AI), the ability to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is becoming a hot topic due to the direct training of machines...

An empirical study of LLaMA3 quantization: from LLMs to MLLMs

Abstract The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language...

Hyperspectral Methane Plume Segmentation Through Foundation Computer Vision Models

Efficient large-scale monitoring of methane emissions is crucial for sustainable environmental management, necessitating advanced remote sensing techniques that process hyperspectral imagery to provide detailed insights into the Earth&#x201...

Bridging the performance–efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection

Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...