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Estimating the relative pose between a camera and a LiDAR holds paramount importance in facilitating complex task execution within multi-agent systems. Nonetheless, current methodologies encounter two primary limitations. First, amid the cross-modal ...

Single-cell RNA sequencing (scRNA-seq) enables a comprehensive analysis of the expression patterns of individual cells in tissue with the resolution of a single cell. However, "dropouts" will lead to an excess of zeros in the scRNA-seq data due to ...

Inside Out 2 (2024) presented a unique set of technical and artistic challenges, requiring careful decisions on retaining elements from the original film while embracing new technologies. As we transitioned from RenderMan’s REYES to the newer RIS ...

Traffic flow prediction has become increasingly important with the rapid development of Intelligent Transportation Systems (ITS) in recent years. Due to the accurate representation of the road network by the graph structure, more and more ...

Recently, the multi-modal fusion of RGB, depth, and semantics has shown great potential in the domain of dense Simultaneous Localization and Mapping (SLAM), as known as dense semantic SLAM. Yet a prerequisite for generating consistent and continuous ...

Adware represents a pervasive threat in the mobile ecosystem, yet its inherent characteristics have been largely overlooked by previous research. This work takes a crucial step towards demystifying Android adware. We present a comprehensive, well-...

The Android ecosystem is significantly challenged by fragmentation, arising from diverse system versions, device specifications, and manufacturer customizations. The growing divergence among devices leads to marked variations in how a given app behaves ...

Motion prediction of surrounding vehicles in complex environments is essential for autonomous vehicle trajectory planning. Accurate motion prediction requires accurately estimating the state information of the surrounding vehicles. For this purpose, a ...

It is challenging to achieve compliant operation in tight interaction tasks, where closed-loop constraints are formed between the robots or between a robot and the environment. Complex dynamic interactions and uncertain parameters degrade the ...

• An RL-based distributed impedance method is proposed for force-position compliance control of robot in tightly interacting tasks, where a closed-chain contact should be maintained between the robots or between the robot and the ...

Determining the limited and compact class acceptance region has become a key bottleneck in classifier design since Open Set Recognition (OSR) requires the classifier to successfully identify those of interest and reject other exceptions. The ...

Recently, deep learning methods that use a combination of convolutional neural networks and Transformers have shown excellent results in both completely supervised and semi-supervised medical image segmentation tasks. This study provides a simple ...

• A simple and effective semi-supervised scheme, based on MobileNet and MobileViT.
• A new cross teaching framework for medical image segmentation.
• This framework performance reaches the level of the state-of-art semi-supervised ...

• Evaluating emergency decision quality from the perspective of public sentiment appeals.
• Through a combined analysis of public dynamic and static sentiment, explores the changes in public sentiment attitude and investigates the impact ...

The increasingly frequent occurrence of emergencies has led to significant losses, both human and economic. It is of the utmost importance to scientifically and effectively formulate emergency decision to prevent and reduce these losses. In this ...

The new radio unlicensed (NR-U) technology is proposed by 3GPP to extend NR to the unlicensed spectrum because of the shortage of the licensed spectrum. Different from the ground and fixed communication equipment-based unlicensed spectrum access ...

The expanding application of Carbon Fiber Reinforced Polymer (CFRP) in industries is drawing increasing attention to energy efficiency improvement and cost reducing during the secondary processing, particularly in milling. Machining parameter ...

In space-air-ground integrated networks (SAGINs), the global energy efficiency (GEE) is a crucial metric for balancing the network throughput and energy consumption, and the maximization of GEE requires the optimizations of both user association and power ...

There are various applications of Cyber-Physical systems (CPSs) that are life-critical where failure or malfunction can result in significant harm to human life, the environment, or substantial economic loss. Therefore, it is important to ensure their ...

As financial markets grow increasingly complex and dynamic, accurately predicting stock price trends becomes crucial for investors and financial analysts. Effectively identifying and selecting the most predictive attributes has become a challenge ...

With the accelerated digital transformation of the national economic activities, the digitization of traditional industries holds significant value in aspects such as gaining insights into business and markets, optimizing operational efficiency, ...

The increasing significance of interdisciplinary research poses a challenge in evaluating its quality and emphasizes the need for academic journals to choose appropriate reviewers for interdisciplinary research. Several studies have focused on the ...

In a federated learning system, it is often the case that the more clients it involves, the less increment of the outcome it achieves. It is thus essential to design a client selection strategy to choose an appropriate subset of the clients to ...