An Empirical Study of Adaptive Kernel Density Estimation in Detecting Distributional Overlap

Given data from an observational study or a randomized experiment, the positivity assumption must hold in order to draw causal relations between the treatment and outcome. However, there is shortage of automatic tools that verify compliance with the positivity assumption. We present tools that uses adaptive and standard kernel density estimation...

Visualizing Complexity: Kernel Density Estimation in University Education: Investigating Misconceptions, Challenges, and the Role of Prior Knowledge in Comprehending KDE

This research investigates the improvement of Kernel Density Estimation (KDE) comprehension in a university context via visualization-enhanced teaching. The study tackles KDE misconceptions, the efficacy of visual aids, and the role of previous mathematical and machine learning knowledge. Using a mix of literature review, survey, and...

Floor count from street view imagery using learning-based façade parsing

Street view imagery (SVI) is one of the largest (growing) resources in urban analytics. A global close-up of the urban environment, if you will, which is rich in (untapped) information such as floor count. Floor count is useful in many applications, from improving energy consumption calculations to creation of 3D city models without elevation...

Adaptive particle-aided cubature Kalman filtering for GNSS/INS-based vehicle localization

Accurate vehicle localization is considered to be a key element in future automated driving systems. A network of multiple sensors is employed to deliver information for this localization process. Loosely coupled integration of global navigation satellite systems (GNSS) and inertial navigation systems (INS) data is a common sensor-fusion method...

A data-driven approach for ship-bridge collision candidate detection in bridge waterway

The consequences caused by bridge failures owing to the ship-bridge collision are always severe in terms of loss of life, economy, and environmental consequences to individuals and societies. The previous studies focused on the ship-bridge collision mainly concentrated on passive anti-collision, such as strengthening the bridge structure or...

Tracking traffic congestion and accidents using social media data: A case study of Shanghai

Traffic congestion and accidents take a toll on commuters' daily experiences and society. Locating the venues prone to congestion and accidents and capturing their perception by public members is invaluable for transport policy-makers. However, few previous methods consider user perception toward the accidents and congestion in finding and...

Where does plastic in the ocean come from?: Using the end location to find the likelihood of a possible start location of plastic particles in the ocean

In the ocean resides a large amount of plastic. This has severe environmental consequences for the oceans. To be able to clean up all this plastic the location of the plastic is needed. A lot of times plastic is cleaned up at the source, but to clean up here this location needs to be known. However, what if the start location is not known and...

Extraction of biological parameters of wound-healing processes from time-lapse videos

Experimental data have been extracted from wound-healing time-lapse videos. These data include the detection of the area of the wound and the detection of individual cells. Extracting the area of the wound is done by using a function in Python OpenCV called cv2.findcontours. An improved method to extract the area of the wound is introduced as...

Three-dimensional characterization of grain boundaries in pure nickel by serial sectioning via mechanical polishing

Five macroscopic boundary parameters can be extracted from three-dimensional orientation maps. Serial sectioning, which includes consecutive steps of material removal, and electron backscatter diffraction (EBSD) measurement were employed to extract a stack of two-dimensional sections of a pure nickel sample. The EBSD patterns were collected from...

Bivariate density estimation in an Oriented Cylinder Model

The microstructure of an object of dual phase steel is modelled with an Oriented Cylinder Model, where the martensite grains in the steel object are modelled as oriented cylinders that are randomly distributed within a big block. By cutting this block parallel to the cylinder axes, rectangular visible profiles of the cut cylinders can be...

Maximally Adaptive Nonparametric Importance Sampling

Nowadays, Monte Carlo integration is a popular tool for estimating high-dimensional, complex integrals. Its scope of application can be widened if ways can be found to produce estimates with smaller variance at the same computational cost. Variance reduction techniques aim to accomplish this. In particular, using importance sampling with the so...