While search is a common need in Virtual Reality (VR) applications, current approaches are cumbersome, often requiring users to type on a mid-air keyboard using controllers in VR or remove VR equipment to search on a computer. We first conducted a ...

Magnetic Resonance Imaging (MRI) is widely used in diagnosing anterior cruciate ligament (ACL) injuries due to its ability to provide detailed image data. However, existing deep learning approaches often overlook additional factors beyond the ...

Logging is crucial in software development for addressing runtime issues but can pose challenges. Logging encompasses four essential sub-tasks: whether to log (Whether), where to log (Position), which log level (Level), and what information to ...

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• We propose ELogger, an end-to-end log statement generation approach.
• We thoroughly evaluate ELogger, finding it significantly outperforms baselines.
• We open source our replication package for further studies.

Real-time indoor crowd counting plays an important role in many applications such as crowd control, resource allocation and advertisement. Current research predominantly relies on camera-based methods. However, computer vision-based solutions raise ...

Compared to a single robot, multi-robot systems (MRS) offer several advantages in complex multi-task scenarios. The overall efficiency of MRS relies heavily on an efficient task allocation and scheduling process. Multi-robot task allocation (MRTA)...

• Shared groups are established to reduce the iterative workload.
• The method allows rapid response to the addition of new unknown tasks.
• The method is validated through simulations and experiments in white body polishing.

This paper deals with a chemotaxis-Navier–Stokes model with indirect signal production involving Dirichlet signal boundary condition in a bounded domain with smooth boundary. A recent literature has asserted that for all reasonably regular initial ...

Large Language Models (LLMs) specialized in code have shown exceptional proficiency across various programming-related tasks, particularly code generation. Nonetheless, due to its nature of pretraining on massive uncritically filtered data, prior studies ...

High-quality data is essential for effective operation and maintenance of wind farms. However, data missing is a persistent issue in the supervisory control and data acquisition (SCADA) system, which seriously affects the data quality. To tackle ...

The task of Extractive Question Answering (EQA) involves identifying correct answer spans in response to provided questions and passages. The emergence of Pretrained Language Models (PLMs) has sparked increased interest in leveraging these models ...

Advancements in information technology have spurred financial innovation, particularly through the development of big data, artificial intelligence, blockchain, and cloud computing. These technologies have merged with traditional finance, leading to the ...

Trip purpose is a meaningful aspect of travel behaviour for the understanding of urban mobility. However, it is non-trivial to automatically obtain trip purposes. On one hand, trip purposes are naturally diverse and complicated, but the available ...

With the development of the information age and the popularization of electronic documents, a large number of electronic documents are generated every day in government agencies, enterprises and institutions, and are used more and more frequently. ...

Cloud computing allows users to execute tasks on virtual machines (VMs) providing flexible and cost-effective services, but bring new risks due to the shared resources among multiple tenants. Malicious tenants have the potential to build side ...

Cloud computing offers cost-effective resource sharing to users, which also brings additional security risks. Malicious neighbors exploit side-channels to steal information from other resource-sharing users’ virtual machine (VM), which are called ...

To improve software development productivity, developers frequently search for projects on open-source communities such as GitHub. However, it is challenging for users to quickly find suitable projects from numerous results due to the overload of project ...

Twin proximal support vector regression, a novel approach, merges twin support vector regression (TSVR) with proximal support vector regression (PSVR) for regression analysis. Classical PSVR and TSVR assume that the data noise follows a ...

• TPSVR-HGN model proposed for heteroscedastic Gaussian noise.
• Adding bias term broadens kernel function selection range in TPSVR-HGN.
• TPSVR-HGN outperforms existing methods across diverse experimental datasets.

Code search plays an important role in enhancing the productivity of software developers. Throughout the years, numerous code search tools have been developed and widely utilized. Many researchers have conducted empirical studies to understand the ...

Under the background of widespread utilization of wind energy, the improvement of power generation efficiency and the reduction of operation and maintenance costs have increased the demand for anomaly detection and localization of wind turbines ...

Precise real-time traffic flow prediction is crucial for route guidance and traffic fine control. With the development of autonomous driving, the mixed traffic flow state composed of Connected Automated Vehicles (CAVs) and Human-driven Vehicles (...

Ensuring the safety and durability of roads and bridges necessitates the accurate identification of spatial-temporal distribution of vehicle loads. This can be achieved using computer vision algorithms, but these require vehicles to be unoccluded,...