PREGNANCY-RELATED CHURN AND ACCESS TO CARE IN THE CONTEXT OF NARROW NETWORKS IN WASHINGTON STATE

Thesis (Master's)--University of Washington, 2016-03

Understanding churn and its reasons: The GuestU case

In the age of computerisation, entrepreneurs around the world aim to revolutionise their field with ground-breaking ICTs. GuestU is one of those offering mobile application development to small and medium-sized tourism enterprises. To assure the young start-ups steady growth this paper aims to identify reasons for the high customer churn risk. Primary data is used to analyse end-user behaviour and particularly the success of acquisition and activation. Results show troubling download quantities as well as retention rates leading to the recommendations for GuestU to incentivise and guide their customers in increasing promotion for the applications.

Modelagem de churn a partir de registros de solicitações de reparo de clientes

O objetivo deste trabalho é criar um modelo que permita predizer quais clientes possuem tendência a abandonar a empresa (churn) através da base de dados de solicitações de reparo dos clientes de banda larga. Este tema ganha importância à medida que a concorrência neste mercado se acirra e novas tecnologias para acesso à banda larga são disponibilizadas aos clientes. Para este estudo foram utilizadas as bases de dados de solicitações de reparo e de solicitações de desligamento do serviço. O primeiro modelo criado utilizou as variáveis tempo até o reparo e a quantidade de solicitações de reparo. Na busca por um modelo com maior nível de acerto, foi criado um segundo modelo no qual se consideraram as variáveis motivo da reclamação e causa do defeito. O resultados do estudo indicam que as variáveis tempo até o reparo e quantidade de solicitações de reparo influenciam na taxa de solicitações de desligamento, assim como alguns motivos de solicitação de reparo e causa de defeito são mais relevantes para a decisão de desligamento. No entanto, o nível de acerto dos modelos criados é baixo. Portanto, a utilização destes modelos para identificação e abordagem de clientes propensos a solicitar desligamento implica em ajustes no nível de certeza do modelo e consequente redução na quantidade de clientes a serem abordados.

Social-analytics firms churn out world cup visuals

Three weeks into the world's most famous football tournament, you'd be forgiven for thinking those charts, maps and infographics you've been seeing everywhere were some kind of symptom of your World Cup fever. They are actually the result of a strategy shift by marketing teams in the social-media-measurement space, which have been investing more heavily in designers and content that can show off their products in a visual way.

Flow regime transition criteria for two-phase flow at reduced gravity conditions

Flow regime transition criteria are of practical importance for two-phase flow analyses at reduced gravity conditions. Here, flow regime transition criteria which take the friction pressure loss effect into account were studied in detail. Criteria at reduced gravity conditions were developed by extending an existing model with various experimental datasets taken at microgravity conditions showed satisfactory agreement. Sample computations of the model were performed at various gravity conditions, such as 0.196, 1.62, 3.71, and 9.81 m/s2 corresponding to micro-gravity and lunar, Martian and Earth surface gravity, respectively. It was found that the effect of gravity on bubbly-slug and slug-annular (churn) transitions in a two-phase flow system was more pronounced at low liquid flow conditions, whereas the gravity effect could be ignored at high mixture volumetric flux conditions. While for the annular flow transitions due to flow reversal and onset of dropset entrainment, higher superficial gas velocity was obtained at higher gravity level.

Developing a simulator application to test the billing platform in telecom industry

Billing Mediation Platform (BMP) in telecommunication industry is used to process real-time streams of Call Detail Records (CDRs) which can be a massive number a day. The generated records by BMP can be deployed for billing purposes, fraud detection, spam filtering, traffic analysis, and churn forecast. Several of these applications are distinguished by real-time processing requiring low-latency analysis of CDRs. Testing of such a platform carries diverse aspects like stress testing of analytics for scalability and what-if scenarios which require generating of CDRs with realistic volumetric and appropriate properties. The approach of this project is to build user friendly and flexible application which assists the development department to test their billing solution occasionally. These generators projects have been around for a while the only difference are the potions they cover and the purpose they will be used for. This paper proposes to use a simulator application to test the BMPs with simulating CDRs. The Simulated CDRs are modifiable based on the user requirements and represent real world data.

High load transit line passenger transmission and productiveness efficiencies

Performance of urban transit systems may be quantified and assessed using transit capacity and productive capacity in planning, design and operational management activities. Bunker (4) defines important productive performance measures of an individual transit service and transit line, which are extended in this paper to quantify efficiency and operating fashion of transit services and lines. Comparison of a hypothetical bus line’s operation during a morning peak hour and daytime hour demonstrates the usefulness of productiveness efficiency and passenger transmission efficiency, passenger churn and average proportion line length traveled to the operator in understanding their services’ and lines’ productive performance, operating characteristics, and quality of service. Productiveness efficiency can flag potential pass-up activity under high load conditions, as well as ineffective resource deployment. Proportion line length traveled can directly measure operating fashion. These measures can be used to compare between lines/routes and, within a given line, various operating scenarios and time horizons to target improvements. The next research stage is investigating within-line variation using smart card passenger data and field observation of pass-ups. Insights will be used to further develop practical guidance to operators.

High load transit line passenger transmission and productiveness efficiencies

Performance of urban transit systems may be quantified and assessed using transit capacity and productive capacity in planning, design and operational management activities. Bunker (4) defines important productive performance measures of an individual transit service and transit line, which are extended in this paper to quantify efficiency and operating fashion of transit services and lines. Comparison of a hypothetical bus line’s operation during a morning peak hour and daytime hour demonstrates the usefulness of productiveness efficiency and passenger transmission efficiency, passenger churn and average proportion line length traveled to the operator in understanding their services’ and lines’ productive performance, operating characteristics, and quality of service. Productiveness efficiency can flag potential pass-up activity under high load conditions, as well as ineffective resource deployment. Proportion line length traveled can directly measure operating fashion. These measures can be used to compare between lines/routes and, within a given line, various operating scenarios and time horizons to target improvements. The next research stage is investigating within-line variation using smart card passenger data and field observation of pass-ups. Insights will be used to further develop practical guidance to operators.

Security ceremonies : including humans in cryptographic protocols

Whether by using electronic banking, by using credit cards, or by synchronising a mobile telephone via Bluetooth to an in-car system, humans are a critical part in many cryptographic protocols daily. We reduced the gap that exists between the theory and the reality of the security of these cryptographic protocols involving humans, by creating tools and techniques for proofs and implementations of human-followable security. After three human research studies, we present a model for capturing human recognition; we provide a tool for generating values called Computer-HUman Recognisable Nonces (CHURNs); and we provide a model for capturing human perceptible freshness.

A reciprocal collaborative method using relevance feedback and feature importance

In a people-to-people matching systems, filtering is widely applied to find the most suitable matches. The results returned are either too many or only a few when the search is generic or specific respectively. The use of a sophisticated recommendation approach becomes necessary. Traditionally, the object of recommendation is the item which is inanimate. In online dating systems, reciprocal recommendation is required to suggest a partner only when the user and the recommended candidate both are satisfied. In this paper, an innovative reciprocal collaborative method is developed based on the idea of similarity and common neighbors, utilizing the information of relevance feedback and feature importance. Extensive experiments are carried out using data gathered from a real online dating service. Compared to benchmarking methods, our results show the proposed method can achieve noticeable better performance.

A recommendation approach dealing with multiple market segments

A new community and communication type of social networks - online dating - are gaining momentum. With many people joining in the dating network, users become overwhelmed by choices for an ideal partner. A solution to this problem is providing users with partners recommendation based on their interests and activities. Traditional recommendation methods ignore the users’ needs and provide recommendations equally to all users. In this paper, we propose a recommendation approach that employs different recommendation strategies to different groups of members. A segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs. Then a targeted recommendation strategy is applied to each identified segment. Empirical results show that the proposed approach outperforms several existing recommendation methods.

Integrating time forgetting mechanisms into topic-based user interest profiling

The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.