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An Integrated Framework For Staffing And Shift Scheduling In Hospitals, Wael Rashwan Nov 2017

An Integrated Framework For Staffing And Shift Scheduling In Hospitals, Wael Rashwan

Doctoral

Over the years, one of the main concerns confronting hospital management is optimising the staffing and scheduling decisions. Consequences of inappropriate staffing can adversely impact on hospital performance, patient experience and staff satisfaction alike. A comprehensive review of literature (more than 1300 journal articles) is presented in a new taxonomy of three dimensions; problem contextualisation, solution approach, evaluation perspective and uncertainty. Utilising Operations Research methods, solutions can provide a positive contribution in underpinning staffing and scheduling decisions. However, there are still opportunities to integrate decision levels; incorporate practitioners view in solution architectures; consider staff behaviour impact, and offer comprehensive applied …


Vungle Inc. Improves Monetization Using Big-Data Analytics, Bert De Reyck, Ioannis Fragkos, Yael Gruksha-Cockayne, Casey Lichtendahl, Hammond Guerin, Andre Kritzer Oct 2017

Vungle Inc. Improves Monetization Using Big-Data Analytics, Bert De Reyck, Ioannis Fragkos, Yael Gruksha-Cockayne, Casey Lichtendahl, Hammond Guerin, Andre Kritzer

Research Collection Lee Kong Chian School Of Business

The advent of big data has created opportunities for firms to customize their products and services to unprecedented levels of granularity. Using big data to personalize an offering in real time, however, remains a major challenge. In the mobile advertising industry, once a customer enters the network, an ad-serving decision must be made in a matter of milliseconds. In this work, we describe the design and implementation of an ad-serving algorithm that incorporates machine-learning methods to make personalized ad-serving decisions within milliseconds. We developed this algorithm for Vungle Inc., one of the largest global mobile ad networks. Our approach also …


Identification Of Reverse Engineering Candidates Utilizing Machine Learning And Aircraft Cannibalization Data, Marc Banghart Oct 2017

Identification Of Reverse Engineering Candidates Utilizing Machine Learning And Aircraft Cannibalization Data, Marc Banghart

International Journal of Aviation, Aeronautics, and Aerospace

As military aircraft continue to remain in service and age, cannibalization of parts is increasing. Proactive identification of parts that are at high risk for cannibalization will inform engineering processes such as reverse engineering, thus allowing potentially reducing lead time to develop new parts. The research objective was to develop a causal structure that can be used for prediction of when cannibalization actions may occur. Bayesian networks allow encoding of causality between various descriptive features given a data set. The method utilized a tabu search algorithm, identified the underlying causal structure and the associated node probabilities. The method is then …


Developing Computer Vision Technology To Automate Pitch Analysis In Baseball., Mahdi Moalla May 2017

Developing Computer Vision Technology To Automate Pitch Analysis In Baseball., Mahdi Moalla

Electronic Theses and Dissertations

Lokator is a baseball training system designed to document pitch location while teaching pitch command, selection and sequencing. It is composed of a pitching target and a smartphone app. The target is divided into a set of zones to identify the pitch location. The main limitation of the current system is its reliance on the user's feedback. After each throw, the pitcher or the coach needs to identify and report the target's zone that was hit by the ball by just relying on the naked eye. The purpose of this thesis is to investigate the possibility of using computer vision …


Construction Ergonomic Risk And Productivity Assessment Using Mobile Technology And Machine Learning, Nipun Deb Nath May 2017

Construction Ergonomic Risk And Productivity Assessment Using Mobile Technology And Machine Learning, Nipun Deb Nath

MSU Graduate Theses

The construction industry has one of the lowest productivity rates of all industries. To remedy this problem, project managers tend to increase personnel's workload (growing output), or assign more (often insufficiently trained) workers to certain tasks (reducing time). This, however, can expose personnel to work-related musculoskeletal disorders which if sustained over time, lead to health problems and financial loss. This Thesis presents a scientific methodology for collecting time-motion data via smartphone sensors, and analyzing the data for rigorous health and productivity assessment, thus creating new opportunities in research and development within the architecture, engineering, and construction (AEC) domain. In particular, …


Viewability Prediction For Display Advertising, Chong Wang Apr 2017

Viewability Prediction For Display Advertising, Chong Wang

Dissertations

As a massive industry, display advertising delivers advertisers’ marketing messages to attract customers through graphic banners on webpages. Display advertising is also the most essential revenue source of online publishers. Currently, advertisers are charged by user response or ad serving. However, recent studies show that users barely click or convert display ads. Moreover, about half of the ads are actually never seen by users. In this case, advertisers cannot enhance their brand awareness and increase return on investment. Publishers also lose much revenue. Therefore, the ad pricing standards are shifting to a new model: ad impressions are paid if they …


Developing An Innovative Entity Extraction Method For Unstructured Data, Waleed A. Zaghloul, Silvana Trimi Jan 2017

Developing An Innovative Entity Extraction Method For Unstructured Data, Waleed A. Zaghloul, Silvana Trimi

Department of Management: Faculty Publications

The main goal of this study is to build high-precision extractors for entities such as Person and Organization as a good initial seed that can be used for training and learning in machine-learning systems, for the same categories, other categories, and across domains, languages, and applications. The improvement of entities extraction precision also increases the relationships extraction precision, which is particularly important in certain domains (such as intelligence systems, social networking, genetic studies, healthcare, etc.). These increases in precision improve the end users’ experience quality in using the extraction system because it lowers the time that users spend for training …