Learn More
User-centered approaches to design can guide teams towards an understanding of users and aid teams in better posing design problems. This paper investigates the role of user-centered design approaches in design process and outcome within the context of design team projects. The value of interaction with users is examined at several stages throughout the(More)
One of the challenges in accurately applying metrics for life cycle assessment lies in accounting for both irreducible and inherent uncertainties in how a design will perform under real world conditions. This paper presents a preliminary study that compares two strategies, one simulation-based and one set-based, for propagating uncertainty in a system.(More)
When a computer system is hacked, analyzing the root-cause (for example entry-point of penetration) is a diagnostic process. An audit trail, as defined in the National Information Assurance Glossary, is a security-relevant chronological (set of) record(s), and/or destination and source of records that provide evidence of the sequence of activities that have(More)
The goal of this work is to bridge the gap between business decision making and real-time factory data. Beyond real-time data collection, we aim to provide analysis capability to obtain insights from the data and converting the learnings into action-able recommendations. We focus on analyzing device health conditions and propose a data fusion method that(More)
Detection of fraud, waste, and abuse (FWA) is an important yet difficult problem. In this paper, we describe a system to detect suspicious activities in large healthcare claims datasets. Each healthcare dataset is viewed as a heterogeneous network of patients, doctors, pharmacies, and other entities. These networks can be large, with millions of patients,(More)
Behavioral models are at the core of Fault-Detection and Isolation (FDI) and Model-Based Diagnosis (MBD) methods. In some practical applications , however, building and validating such models may not always be possible, or only partially validated models can be obtained. In this paper we present a diagnosis solution when only a partially validated model is(More)
This paper will demonstrate a machine learning application for predicting positive lead conversion events on the Edmunds.com website, an American destination for car shopping. A positive conversion event occurs when a user fills out and submits a lead form interstitial. We used machine learning to identify which users might want to fill out lead forms, and(More)
  • 1