ADMIT

To meet the diverse data storage and analysis needs in the Internet of Things era, businesses embrace the lakehouse approach, a hybrid deployment of data lakes and data warehouses on a single platform. Data consumers leverage data mining techniques ...

Link prediction is one of the most essential tasks in data mining. A lot of studies have shown great progress in homogeneous graph. However, besides recommendation system and knowledge graph, little research solves the problem of link prediction in ...

In this paper, we introduce a novel and computationally efficient method for vertex embedding, community detection, and community size determination. Our approach leverages a normalized one-hot graph encoder and a rank-based cluster size measure. ...

Few-shot object detection, which aims to improve the generalization ability of the object detection model with limited data, has gained significant attention. Many existing methods use standard Faster R-CNN as the basic model and add modules to assist ...

The widespread and large-scale distribution of water meter users in China poses a significant challenge to the traditional manual meter reading method in most regions of the country. Rapid and accurate meter reading for a large number of water meters ...

Aiming at the problem that the existing high-value patent recognition methods rely on experts' subjective experience judgment and the patent recognition model cannot fully extract the feature information of the patent text, which leads to the ...

Tuberculosis stands out as a severe and deadly infectious disease globally, characterized by a high incidence rate and mortality. While common tuberculosis screening methods involve diagnosing through CXR images, this approach carries a significant risk ...

Alzheimer’s disease, a prevalent form of dementia, is a progressive, long-term and irreversible neurological disorder. With the growing elderly population, there has been a significant rise in the number of individuals affected by Alzheimer’s disease, ...

Pneumonia is an important threat to human health, and different types of pneumonia have different treatment options, so the prediction and classification of pneumonia are important health issues. In this paper, chest X-ray images are used as data, and ...

The present study elucidates the innovative application of automatic CMT model in gastrointestinal endoscopic image classification tasks, which is an advanced hybrid network based on Transformer.The training process of the CMT model effectively ...

Breast cancer is a prevalent cancer type among women worldwide, which contributes to significant mortality and morbidity rates. Early detection of breast cancer plays a crucial role in improving patients’ chances of survival. In this study, we utilized ...

Contrastive learning has been widely applied in sequential recommendation to improve the recommendation performance. Existing contrastive learning methods focus on adjusting the views number of positive and negative samples to enhance the item ...

This paper introduces a novel approach that combines reversible data hiding (RDH) and encryption-then-compression (ETC) for images. The proposed method involves encrypting the image first, followed by hiding secret information within it. The encrypted ...

Aiming at the problem that cohesion force and internal friction Angle are difficult to be measured as shear strength indexes, correlation analysis and principal component analysis are used to explore the relationship between these two indexes and the ...

As a cornerstone of intelligent transportation systems, traffic flow prediction has garnered extensive research attention. However, traffic flow data exhibits pronounced spatio-temporal dynamics, rendering accurate traffic flow prediction a challenging ...

The filling and solidification method is employed in underground mines to backfill waste materials such as coal gangue, fly ash, and slag into the goaf, aiming to control strata movement and surface subsidence while addressing environmental pollution ...

This paper proposes a classification methodology that combines neighborhood rough set feature selection with the fuzzy k-nearest neighbor algorithm. The method enhances the accuracy by integrating the fuzzy k-nearest neighbor classifier into the well-...

Multi-sensor fusion is essential for 3D object detection in intelligent transportation due to it makes best use of cross-modality information, in which feature-level fusion of millimeter-wave radar and camera has been a hot topic. Existing research ...

Text sentiment analysis is an important task in natural language processing (NLP), which aims to determine people's emotional tendency towards a certain topic or event by analyzing the language and emotion in the text. Aiming at the traditional emotion ...

Network management such as topology discovery and network diagnosis needs to be scanned based on the Internet, and the IPV6 address space is huge and it is difficult to perform global scanning. The existing IPV6 target generation method has a low hit ...

Currently, multi-view deep subspace clustering algorithms have achieved remarkable success. However, existing methods have not yet focused on comprehensive information mining within the deep encoder for clustering performance improvement. To this end, ...

This paper proposes Y-index as the basic index of directed weighted network to measure the importance of nodes in the network. Considering the large number of nodes in most real networks, in order to improve the computing speed, we introduce the Y-...

For multi-objective trajectory planning problem of an unmanned aerial vehicle(UAV) in complex environment, a problem model is constructed based on flight environment information, mission objectives, and flight performance constraints. A multi-objective ...

Particle swarm optimization (PSO), as one of the metaheuristic optimization methods, has the merits of fast convergence, few adjustable parameters and simple searching process, but it also has the disadvantages of easily falling into local optimal and ...

Lung cancer, renowned for having the highest global incidence and mortality rates among all cancers, presents a promising avenue for improving survival rates through early detection and precise diagnosis. However, current diagnostic methods relying on ...

In the face of the information age, the integration of popular financial and computer fields has become a hotspot. Traditional stock prediction algorithms often rely on the experience and skills of financial experts, with unsatisfactory results. To ...

Wordle is a popular puzzle game offered by The New York Times every day, in which players need to guess a five-letter word in six or fewer attempts to solve the puzzle and receive feedback after each guess. Due to its simple and fun rules, it quickly ...

The widespread use of wireless sensor networks has led to an increasing focus on their security. Although access control and other technologies are used to prevent the data from being revealed, many existing authentication key agreement protocols are ...

Applying the BFT consensus mechanism in the IoT edge computing environment effectively solves the problem of data consistency and trustworthiness. However, the existing BFT consensus mechanism needs to pay attention to the impact of the data processing ...

Online news articles contain representative textual content including title, abstract, category and entities, and the clicked news articles by users indicate their interests. Fully exploiting these features is critical for accurate matching between ...