Topic modeling is a widely used unsupervised natural language processing (NLP) technique aimed at discovering latent themes within documents. Since traditional methods fall short in capturing contextual meaning, approaches based on large language models (LLMs)—such as BERTopic—hold the potential to...

This paper considers the distributed group target tracking (DGTT) problem under sensors with limited and different field of views (FoVs). Usually, for the tracking of groups, targets within groups are closely spaced and move in a coordinated manner. These groups can split or merge, and the numbers o...

The Traveling Salesman Problem (TSP) is a well-known NP-hard problem that aims to find the optimal tour among cities, visiting each exactly once and returning to the origin. Over the years, many researchers have proposed various approaches to find near-optimal solutions for TSP. This paper proposed...

Reservoir Science (RS) journal represents a significant milestone in the pursuit of energy extraction, energy storage, and the multifarious effects of climate change, which are influenced by the dual factors of global climate variability and energy scarcity. Concurrently, Reservoir Science is dedica...

Roman Urdu sentiment analysis faces significant challenges due to transliteration inconsistencies, informal language usage, and the lack of labeled datasets. This study proposes a novel framework that addresses these challenges by combining advanced data preprocessing techniques and data augmentatio...

The rapid advancement in machine learning and artificial intelligence has significantly enhanced capabilities in multimedia content creation, particularly in the domain of deepfake generation. Deepfakes leverage complex neural networks to create hyper-realistic manipulated audio-visual content, rais...

In cognitive radio networks (CRNs), dynamic spectrum handoff requires efficient path planning to minimize the overhead of frequent channel switching. This paper proposes a polynomial-time approximation algorithm for spectrum handoff scheduling, based on an improved Traveling Salesman Problem (TSP) m...

To address the issues of low solving efficiency and susceptibility to local optima in multi-unmanned aerial vehicle (multi-UAV) task allocation algorithms within urban areas, this study constructs a task allocation model aiming to minimize economic costs for material delivery and reduce the urgency...

Consumer satisfaction in automotive spare parts e-commerce is shaped by multidimensional factors that are difficult to quantify through conventional survey methods. This paper presents an intelligent text mining framework that integrates multiple machine learning and natural language processing tec...

Perovskite solar cells (PSCs) have appeared as an encouraging photovoltaic technology due to their high efficacy and low fabrication cost. However, their stability and scalability are hampered by charge recombination and intricate multilayer architectures. Using HTL-free design, this work explores r...