Machine Learning as Enabler of Design-to-Robotic-Operation

This essay promotes Artificial Intelligence (AI) via Machine Learning (ML) as a fundamental enabler of technically intelligent built-environments. It does this by detailing ML’s successful application within three deployment domains: (1) Human Activity Recognition, (2) Object as well as Facial-Identity and -Expression Recognition, and (3) Speech...

In Situ  Failure Detection of Electronic Control Units Using Piezoresistive Stress Sensor

Recent advancements in automotive technologies, most notably autonomous driving, demand electronic systems much more complex than those realized in the past. The automotive industry has been forced to adopt advanced consumer electronics to satisfy the demand, and thus it becomes more challenging to assess system reliability while adopting the...

Toward complete oral cavity cancer resection using a handheld diffuse reflectance spectroscopy probe

This ex-vivo study evaluates the feasibility of diffuse reflectance spectroscopy (DRS) for discriminating tumor from healthy tissue, with the aim to develop a technology that can assess resection margins for the presence of tumor cells during oral cavity cancer surgery. Diffuse reflectance spectra were acquired on fresh surgical specimens...

Comparison of Logistic Regression and Bayesian Networks for Risk Prediction of Breast Cancer Recurrence

Purpose. For individualized follow-up, accurate prediction of locoregional recurrence (LRR) and second primary (SP) breast cancer risk is required. Current prediction models employ regression, but with large data sets, machine-learning techniques such as Bayesian Networks (BNs) may be better alternatives. In this study, logistic regression...

DeepEyes: Progressive Visual Analytics for Designing Deep Neural Networks

Deep neural networks are now rivaling human accuracy in several pattern recognition problems. Compared to traditional classifiers, where features are handcrafted, neural networks learn increasingly complex features directly from the data. Instead of handcrafting the features, it is now the network architecture that is manually engineered. The...

On Developing a Driver Identification Methodology Using In-Vehicle Data Recorders

Recently, cutting edge technologies to facilitate data collection have emerged on a large scale. One of the most prominent is the in-vehicle data recorder (IVDR). There are multiple ways to assign the IVDR's data to the different drivers who share the same vehicle. Irrespective of the level of sophistication, all of these technologies still...

Diffuse reflectance spectroscopy as a tool for real-time tissue assessment during colorectal cancer surgery

Colorectal surgery is the standard treatment for patients with colorectal cancer. To overcome two of the main challenges, the circumferential resection margin and postoperative complications, real-time tissue assessment could be of great benefit during surgery. In this ex vivo study, diffuse reflectance spectroscopy (DRS) was used to...

Learning about the opponent in automated bilateral negotiation: A comprehensive survey of opponent modeling techniques

A negotiation between agents is typically an incomplete information game, where the agents initially do not know their opponent’s preferences or strategy. This poses a challenge, as efficient and effective negotiation requires the bidding agent to take the other’s wishes and future behavior into account when deciding on a proposal. Therefore, in...

VizBin: An application for reference-independent visualization and human-augmented binning of metagenomic data

Background: Metagenomics is limited in its ability to link distinct microbial populations to genetic potential due to a current lack of representative isolate genome sequences. Reference-independent approaches, which exploit for example inherent genomic signatures for the clustering of metagenomic fragments (binning), offer the prospect to...

Efficient Multiclass ROC Approximation by Decomposition via Confusion Matrix Perturbation Analysis

Receiver operator characteristic (ROC) analysis has become a standard tool in the design and evaluation of two-class classification problems. It allows for an analysis that incorporates all possible priors, costs, and operating points, which is important in many real problems, where conditions are often nonideal. Extending this to the multiclass...