Over the past decades, cloud computing has become a cornerstone of modern infrastructure. Accurate cloud workload prediction is crucial for assessing quality of service and ensuring efficient resource utilization in cloud center. Despite ...

In order to expand the application of truck-drone cooperative delivery in emergency logistics, this paper investigates the multi-depot vehicle routing problem with drones for emergency logistics scheduling. A mixed-integer programming model with ...

Multimedia streaming has become integral to modern living, reshaping entertainment consumption, information access, and global engagement. The ascent of cloud computing, particularly serverless architectures, plays a pivotal role in this ...

Content-Based Image Retrieval (CBIR) is a method for retrieving images based on their content rather than relying on textual descriptions or tags. Over the last decade, Deep Convolutional Neural Networks (D-CNN) based architectures have gained ...

Predictive Business Process Monitoring has gained significant attention in recent years due to its capability to forecast process outcomes and predict the next event within an ongoing process. In the last few years, works have focused on deep ...

Autonomous driving is a crucial area of research and a key focus for industrial advancement, with the advancement of high-level autonomous driving technology depending significantly on creating precise 3D point cloud maps (PCM$\backslash$PCMs) of the driving ...

Poor-quality products and counterfeit tags within the supply chains pose major challenges. Although several approaches have been suggested, they do not address all the challenges. This paper proposes a blockchain-integrated supply chain to tackle ...

In recent years, blockchain technology has emerged as a topic of increasing interest within the field of computer science research. Due to its characteristics of decentralisation, information traceability, and tamper-resistance, it has been widely ...

Under the impetus of mobile edge computing, mobile access networks and the Internet are deeply integrated providing low-latency, high-reliability computing power for service innovation. Due to the limitation of computing power resources, it is ...

Over the past decade, numerous studies have explored virtual machine (VM) placement with diverse objectives, including energy consumption reduction, carbon footprint reduction, migration minimization, mitigation of service level agreement (SLA) ...

Recently, multi-label categorization learning has emerged as a new area of study in machine learning since it offers a multi-dimensional perspective of the multi-dimensional object. To build a multi-label classification (MLC) system that is both ...

Remote data integrity auditing (RDIA) schemes can inspect the integrity of outsourced data. And deduplication improves the utilization of cloud storage space. Therefore, a considerable number of remote data integrity auditing schemes with ...

The recommendation of passenger pickup zones can enhance driver efficiency, improve passenger experience, and optimize urban traffic management. However, current issues such as direct access to sensitive data and lack of data sharing between ...

Federated Learning has received much attention due to its data privacy benefits, but most existing approaches assume that client classes are fixed. Clients may remove old classes and add new ones, leading to catastrophic forgetting of the model. ...

Ensemble clustering integrates all basic clustering results to produce a better clustering result. Existing ensemble clustering methods typically rely on a co-association matrix (CA), which measures the number of occurrences two samples are ...

Timely and accurate extraction of crop planting units plays a crucial role in crop yield estimation, soil management and disaster warning. For small-scale crop cultivation systems, accurate mapping of crop types is challenging due to the presence ...

Despite significant investments in server infrastructure, spam continues to pose several challenges to the email ecosystem. These include ineffective detection and waste of computing resources. The constant need for periodic updates of spam ...

Logical rules enable knowledge graph reasoning in an explicit and interpretable way. Hybrid learning approaches that combine logical rules with representation learning has shown strong capabilities in knowledge graph reasoning tasks by integrating ...

Anomaly detection of multi-time series data during the working process of Internet of Things systems that utilize sensors is one of the key aspects to prevent accidents in industrial information systems. The key challenge is to discover ...${}_{\mathrm{}}$

Securing image transmissions has become critical as the demand for image sharing and storage grows. In some commercial uses, in order to achieve a balance between encryption security and efficiency, some researchers have tried to encrypt only the ...