Managing big data experiments on smartphones

The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. Next generation smartphone applications are expected to be much larger-scale and complex, demanding that these undergo evaluation and testing under different real-world datasets, devices and conditions. In this paper, we present an architecture for managing such large-scale data management experiments on real smartphones. We particularly present the building blocks of our architecture that encompassed smartphone sensor data collected by the crowd and organized in our big data repository. The given datasets can then be replayed on our testbed comprising of real and simulated smartphones accessible to developers through a web-based interface. We present the applicability of our architecture through a case study that involves the evaluation of individual components that are part of a complex indoor positioning system for smartphones, coined Anyplace, which we have developed over the years. The given study shows how our architecture allows us to derive novel insights into the performance of our algorithms and applications, by simplifying the management of large-scale data on smartphones

A linked data approach to publishing complex scientific workflows

Past data management practices in many fields of natural science, including climate research, have focused primarily on the final research output - the research publication - with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. Data were often regarded merely as an adjunct to the publication, rather than a scientific resource in their own right. In this paper, we attempt to address the issues of capturing and publishing detailed workflows associated with the climate/research datasets held by the Climatic Research Unit (CRU) at the University of East Anglia. To this end, we present a customisable approach to exposing climate research workflows for the effective re-use of the associated data, through the adoption of linked-data principles, existing widely adopted citation techniques (Digital Object Identifier) and data exchange mechanisms (Open Archives Initiative Object Reuse and Exchange)

Application of a portable FTIR for measuring on-road emissions

The objective of this work was the development of an onroad in-vehicle emissions measurement technique utilizing a relatively new, commercial, portable Fourier Transform Infra-Red (FTIR) Spectrometer capable of identifying and measuring (at approximately 3 second intervals) up to 51 different compounds. The FTIR was installed in a medium class EURO1 spark ignition passenger vehicle in order to measure on-road emissions. The vehicle was also instrumented to allow the logging of engine speed, road speed, global position, throttle position, air-fuel ratio, air flow and fuel flow in addition to engine, exhaust and catalyst temperatures. This instrumentation allowed the calculation of massbased emissions from the volume-based concentrations measured by the FTIR. To validate the FTIR data, the instrument was used to measure emissions from an engine subjected to a real-world drive cycle using an AC dynamometer. Standard analyzers were operated simultaneously for comparison with the FTIR and the standard analyzer results showed that most pollutants (NOx, CO2, CO) were within ~10% of a standard analyzer during steady state conditions and within 20% during transients. The exception to this was total HC which was generally 50% or less than actual total HC, but this was due to the limited number of hydrocarbons measured by the FTIR. In addition to the regulated emissions, five toxic hydrocarbon species were analyzed and found to be sensitive to cold starts in varying proportions. Finally, FTIR data was compared to results from a commercially available on-road measurement system (Horiba OBS- 1000), and there was good agreement

Open Science in Software Engineering

Open science describes the movement of making any research artefact available to the public and includes, but is not limited to, open access, open data, and open source. While open science is becoming generally accepted as a norm in other scientific disciplines, in software engineering, we are still struggling in adapting open science to the particularities of our discipline, rendering progress in our scientific community cumbersome. In this chapter, we reflect upon the essentials in open science for software engineering including what open science is, why we should engage in it, and how we should do it. We particularly draw from our experiences made as conference chairs implementing open science initiatives and as researchers actively engaging in open science to critically discuss challenges and pitfalls, and to address more advanced topics such as how and under which conditions to share preprints, what infrastructure and licence model to cover, or how do it within the limitations of different reviewing models, such as double-blind reviewing. Our hope is to help establishing a common ground and to contribute to make open science a norm also in software engineering.Comment: Camera-Ready Version of a Chapter published in the book on Contemporary Empirical Methods in Software Engineering; fixed layout issue with side-note

Service Implementation Framework in Manufacturing Firms: A Case Study

The culture and the operational methods of service management have become a formidable competitive weapon even for manufacturing firms. The term "service factory" has been proposed for identifying that particular integration of products and services, achieved by the excellent manufacturing firm, where "service is a multidimensional concept". The creation of a service factory necessarily implies a radical change in the operational and organizational characteristics of the firm. In order to support manufacturing firms in adopting a service strategy, it is relevant on the one hand to identify the bundle of services which have to be provided for the customers and, on the other hand, to understand the implications for firm management model. As regards the first point, the paper proposes a framework which classifies the services along with two dimensions: Timedimension and target-dimension. The proposed framework is of interest for manufacturing firms because it allows a better recognition of services that are more perceptible for the customers. In the second part of the paper, authors discuss the implications of a service strategy adoption on the management model of manufacturing firms. In order to carry out this analysis, authors propose a model that combines four service dimensions with three decision-making categories (Organization, Methodologies and Technologies). In the end, the proposed framework has been applied in a sample of Italian hot water heater manufacturers and a case study analysis has been carried out

Development of methodologies for validating the quality of a novel fluid flow sensor

During the internship required for the Master's degree in Biomedical Engineering, conducted at Riedel Communications, a systematic review of the literature was developed in order to gain a greater understanding of methods for validating the quality of sensors, with a main focus on calibrations. A second assignment involved calibrating the fluid flow sensor (FFS) developed by Riedel. Throughout this dissertation, the work carried out during the internship will be described, as well as its background and objectives. Riedel Communications is developing a scientifically precise and high-quality system for acquiring 3D navigation data. The idea was born out of the need to obtain analytical data that better reflects the movement of a surfer relative to the water. A fluid flow sensor (FFS) is integrated into the system, and its implementation in hostile environments and measurement without interfering with an athlete's performance are the biggest challenges. In order to ensure consistency and reduce errors, all instruments should be calibrated to ensure they are performing in accordance with known standards. Based on the high consistency and repeatability of the experimental results, the fluid flow sensor displayed a high-quality performance. Therefore, the internship was a success because it served as a valuable resource for the company's work, and all activities were successfully completed.Durante o estágio do Mestrado em Engenharia Biomédica, realizado na Riedel Communications, foi desenvolvida uma revisão sistemática da literatura a fim de se obter uma maior compreensão dos métodos de validação da qualidade de sensores, sendo que a calibração foi o foco principal. Num segundo trabalho, procedeu-se exatamente à calibração do sensor de fluxo desenvolvido pela Riedel. Ao longo deste relatório, será descrito o trabalho realizado durante o estágio, bem como os seus objetivos. A Riedel Communications está a desenvolver um sistema cientificamente preciso e de alta qualidade para a aquisição de dados de navegação 3D. A ideia nasceu da necessidade de obter dados analíticos que reflitam melhor o movimento de um surfista em relação à água. Um sensor de fluxo de fluido (FFS) está integrado no sistema, e a sua implementação em ambientes hostis e medição sem interferir com o desempenho de um atleta são os maiores desafios. A fim de assegurar a consistência e reduzir erros, todos os instrumentos devem ser calibrados para garantir que o seu desempenho está de acordo com as normas conhecidas. Com base na elevada consistência e repetibilidade dos resultados das experiências efetuadas, pode-se dizer que o sensor de fluxo de fluido apresentou um desempenho de alta qualidade. Portanto, o estágio foi um sucesso pois serviu como um recurso valioso para o trabalho da empresa, e todas as atividades foram concluídas com sucesso