A review of vision-based road detection technology for unmanned vehicles

With the development of unmanned vehicle technology, unmanned vehicles have played a huge role in logistics transportation, emergency rescue and disaster relief, etc., so the research on unmanned vehicles is becoming more and more important. Road detection is an important part of environmental perception and an important factor in the...

Open Experimental Data-Sets to Reveal Behavioural Insights of High-Deck Coach Evacuations

Numerous evacuation performance data for the utilization in evacuation modelling and simulations have been established for the conventional/widely studied scenarios, such as building evacuation scenarios. However, such data are typically scarce for a new scenario in literature — evacuation from high-deck coaches. This paper fulfills this gap...

Probability and distribution of green water events and pressures

This article proposes a method to quantify, first, the probability of occurrence of green water and, second, the expected maximum pressures during green water events using their statistical distribution for ships at forward speed. A large green water data set which represents 1945 hours of continuous sailing on full scale with different sea...

Multi-class Road User Detection with 3+1D Radar in the View-of-Delft Dataset

Next-generation automotive radars provide elevation data in addition to range-, azimuth- and Doppler velocity. In this experimental study, we apply a state-of-the-art object detector (PointPillars), previously used for LiDAR 3D data, to such 3+1D radar data (where 1D refers to Doppler). In ablation studies, we first explore the benefits of...

Teaching data analysis for building performance simulation – Series: Building simulation and calculation tools in teaching

Abstract The Erasmus+ project, entitled ?Digital Erasmus ? a roadmap to using building performance simulation to achieve resilient design? (DesRes), seeks to transform the learning experience of students in built environment disciplines using a continuous digital learning cycle. Three universities play a part in this project: Graz University of...

Working towards an AI-­based clustering of airports, in the effort of improving humanitarian disaster preparedness

In the past few years, the frequency of onset natural disaster has been rising, causing significant damage to communities and infrastructure around the world. When it happens, airports in the region affected have to rapidly adjust and evolve from serving regular passengers to becoming a humanitarian hub, that handles a massive surge in both...

Disaster Risk Analysis of a Power Grid Network

This research introduces a method for using global data sets to conduct a flood risk and cascading failures analysis in countries where high-quality data does not exist. As the goal is to support policy-making on a national level, an impacts analysis is additionally proposed to provide a systematic way of comparing system performance against...

Machine Learning for Software Refactoring: a Large-Scale Empirical Study

Refactorings tackle the challenge of architectural degradation of object-oriented software projects by improving its internal structure without changing the behavior. Refactorings improve software quality and maintainability if applied correctly. However, identifying refactoring opportunities is a challenging problem for developers and...

Data Generation Methods for Multi-Label Images of LEGO Bricks

Data collection and annotation have proven to be a bottleneck for computer vision applications. When faced with the task of data creation, alternative methods to traditional data collection should be considered, as time and cost may be reduced signif- icantly. We introduce three novel datasets for multi- label classification purposes on LEGO...

Extreme value analysis of complex wave systems

The design of offshore and coastal hydraulic structures is very much dependent on the hydraulic boundary conditions, such as significant wave height, mean wave period and wave direction, among other parameters. A proper design value of these parameters is required during the design process, based on the corresponding safety philosophy and the...

PLADE: A Plane-Based Descriptor for Point Cloud Registration with Small Overlap

Traditional point cloud registration methods require large overlap between scans, which imposes strict constraints on data acquisition. To facilitate registration, users have to carefully position scanners to ensure sufficient overlap. In this article, we propose to use high-level structural information (i.e., plane/line features and their...

Exploring Sources of Uncertainty in Steric Sea-Level Change Estimates

Recent studies disagree about the contribution of variations in temperature and salinity of the oceans—steric change—to the observed sea-level change. This article explores two sources of uncertainty to both global mean and regional steric sea-level trends. First, we analyze the influence of different temperature and salinity data sets on the...

Designing and Evaluating Rebalancing Algorithms for Payment Channel Networks

Payment Channel Networks(PCN) utilize payment channels with an established link capacity between two nodes to route transactions over multiple links to carry out transactions. Such transactions can support a blockchain due to the transactions happening off-chain, i.e., not requiring any information to be published to a ledger. PCNs can help aid...

The influence of the interaction characteristics on the movement dynamics of pedestrians

One of the fundamental properties of pedestrian simulation models is their capability to predict the future movement dynamics of pedestrians depending on the current state of the pedestrian traffic flow, more specically the walking behaviour of neighbouring pedestrians. This paper investigates the influence of the interaction characteristics on...

Remarks on learning hybrid Bayesian networks from data for medical research

In this thesis, we learn the structure of a hybrid Bayesian network (mixed continuous and discrete) for a small data set and learn the parameters. We segment the learning process in distinct steps and evaluate the possible options for each step. After a short introduction into the theory of Bayesian networks, we cover the topics: data...

Re-assessment and update of bulk longshore sediment transport formulas

Longshore sediment transport (LST) is one of the main drivers of beach morphology. Bulk LST formulas are routinely used in coastal management/engineering studies to assess LST rates and gradients. Over 50 years of research has resulted in several bulk LST formulas that have been tested with varying levels of rigor. In this study, the predictive...

OPERATIONAL TECHNIQUES FOR FORECASTING TROPICAL CYCLONE INTENSITY AND MOVEMENT

PART 1-INTRODUCTION AND BACKGROUND INFORMATION Chapter 2- tropical cyclone climatology PART Il - TRACK FORECASTING METHODS Chapter 3 - empirical techniques Chapter 4 - Statistical techniques