相关论文: NOSTROMO: Lessons learned, conclusions and way for…

This research investigates flight delay trends by examining factors such as departure time, airline, and airport. It employs regression machine learning methods to predict the contributions of various sources to delays. Time-series models,…

This paper deals with the challenge of modeling the performance of planned ultrabroadband access networks while maintaining technological neutrality and accuracy in measurable quality. We highlight the importance of such modeling also for…

Traffic Management in Advanced Aerial Mobility (AAM) inherits many elements of conventional Air Traffic Management (ATM), but brings new complexities and challenges of its own. One of its ways of guaranteeing separation is the use of…

Unsupervised machine learning is the training of an artificial intelligence system using information that is neither classified nor labeled, with a view to modeling the underlying structure or distribution in a dataset. Since unsupervised…

Flight delays are a significant challenge in the aviation industry, causing major financial and operational disruptions. To improve passenger experience and reduce revenue loss, flight delay prediction models must be both precise and…

Reliable benchmarking is essential for progress in intelligent traffic control research. While microscopic traffic simulators such as SUMO enable detailed modelling of individual vehicle interactions, many published control studies still…

Semaphores are a widely used and foundational synchronization and coordination construct used for shared memory multithreaded programming. They are a keystone concept, in the sense that most other synchronization constructs can be…

Programmable data plane technology enables the systematic reconfiguration of the low-level processing steps applied to network packets and is a key driver in realizing the next generation of network services and applications. This survey…

Parameter-efficient fine-tuning (PEFT) in multimodal tracking reveals a concerning trend where recent performance gains are often achieved at the cost of inflated parameter budgets, which fundamentally erodes PEFT's efficiency promise. In…

There have been recent efforts to move to population-based structural health monitoring (PBSHM) systems. One area of PBSHM which has been recognised for potential development is the use of multi-task learning (MTL); algorithms which differ…

This document was prepared as part of the MT-LAB research centre. The research centre studies the Modelling of Information Technology and is a VKR Centre of Excellence funded for five years by the VILLUM Foundation. You can read more about…

Microservices are quite widely impacting on the software industry in recent years. Rapid evolution and continuous deployment represent specific benefits of microservice-based systems, but they may have a significant impact on non-functional…

Wind power generation plays a crucial role in transitioning away from fossil fuel-dependent energy sources, contributing significantly to the mitigation of climate change. Monitoring and evaluating the aerodynamics of large wind turbine…

This paper provides a tutorial discussion on path analysis structure with concept of structural equation modelling (SEM). The paper delivers an introduction to path analysis technique and explain to how to deal with analyzing the data with…

The objective of this work is to develop an Electronic Medical Record (EMR) data processing tool that confers clinical context to Machine Learning (ML) algorithms for error handling, bias mitigation and interpretability. We present…

Traffic assignment (TA) is crucial in optimizing transportation systems and consists in efficiently assigning routes to a collection of trips. Existing TA algorithms often do not adequately consider real-time traffic conditions, resulting…

Motion forecasting has become an increasingly critical component of autonomous robotic systems. Onboard compute budgets typically limit the accuracy of real-time systems. In this work we propose methods of improving motion forecasting…

Model Driven Engineering (MDE) has been widely applied in software development, aiming to facilitate the coordination among various stakeholders. Such a methodology allows for a more efficient and effective development process.…

To use libraries of observed stellar spectra, one needs to know the atmospheric parameters of the stars associated to those spectra. It is, however, hard to know what are the real levels of precision and accuracy of these parameters. To…

Aircraft trajectory prediction requires the determination of the atmospheric properties (pressure, temperature, and density) encountered by the aircraft during its flight. This is accomplished by employing a tabulated prediction published…