Search results for "Data Science"
showing 10 items of 495 documents
In Search of Evidence for Model-Driven Development Claims: An Experiment on Quality, Effort, Productivity and Satisfaction
2015
Context: Model-Driven Development (MDD) is a paradigm that prescribes building conceptual models that abstractly represent the system and generating code from these models through transformation rules. The literature is rife with claims about the benefits of MDD, but they are hardly supported by evidences. Objective: This experimental investigation aims to verify some of the most cited benefits of MDD. Method: We run an experiment on a small set of classes using student subjects to compare the quality, effort, productivity and satisfaction of traditional development and MDD. The experiment participants built two web applications from scratch, one where the developers implement the code by h…
Editorial for PCCP themed issue "Developments in Density Functional Theory''
2016
This issue provides an overview of the state-of-the-art of DFT, ranging from mathematical and software developments, via topics in chemical bonding theory, to all kinds of molecular and material properties. Through this issue, we also celebrate the enormous contributions that Evert Jan Baerends has made to this field.
Implementing a Face Recognition System for Media Companies
2018
During the past few years face recognition technologies have greatly benefited from the huge progress in machine learning and now have achieved precision rates that are even comparable with humans. This allows us to apply face recognition technologies more effectively for a number of practical problems in various businesses like media monitoring, security, advertising, entertainment that we previously were not able to do due to low precision rates of existing face recognition technologies. In this paper we discuss how to build a face recognition system for media companies and share our experience gained from implementing one for Latvian national news agency LETA. Our contribution is: which …
Relevance of Big Data for Business and Management. Exploratory Insights (Part I)
2018
Abstract Over the last few decades Big Data has impetuously penetrated almost every domain of human interest/action and it has (more or less consciously) become a ubiquitous presence of day to day life. The main questions this exploratory paper seeks to address (throughout its two parts) are the following: What is the (actual) impact of Big Data on Business & Management and How can businesses (through their management) leverage the potential of Big Data to their benefit? A gradual, step by step approach (based on literature review and a variety of secondary data) will guide the paper in search for answers to the abovementioned questions: starting with a concise history of the topic Big …
Uso de indicadores bibliométricos para el análisis de temas emergentes y su evolución: spin-offs como caso de estudio
2018
[ES] Las spin-offs constituyen una de las áreas de investigación más atractivas, ya que están asociadas con fenómenos como el emprendimiento, la innovación y la transferencia del conocimiento. El presente estudio muestra que la selección y el uso de indicadores bibliométricos permite identificar y caracterizar el desarrollo y la difusión de temas de investigación emergentes como el analizado. Los principales aspectos observados en relación con el desarrollo de la investigación sobre las spin-offs son que se produce un auge en el número de publicaciones después de un largo período de latencia y la marcada naturaleza multidisciplinar del área. El presente enfoque ha analizado la evolución de …
Standards not that standard
2015
There is a general assent on the key role of standards in Synthetic Biology. In two consecutive letters to this journal, suggestions on the assembly methods for the Registry of standard biological parts have been described. We fully agree with those authors on the need of a more flexible building strategy and we highlight in the present work two major functional challenges standardization efforts have to deal with: the need of both universal and orthogonal behaviors. We provide experimental data that clearly indicate that such engineering requirements should not be taken for granted in Synthetic Biology. Electronic supplementary material The online version of this article (doi:10.1186/s1303…
Two Half-Truths Make a Whole? On Bias in Self-Reports and Tracking Data
2019
The pervasive use of mobile information technologies brings new patterns of media usage, but also challenges to the measurement of media exposure. Researchers wishing to, for example, understand the nature of selective exposure on algorithmically driven platforms need to precisely attribute individuals’ exposure to specific content. Prior research has used tracking data to show that survey-based self-reports of media exposure are critically unreliable. So far, however, little effort has been invested into assessing the specific biases of tracking methods themselves. Using data from a multimethod study, we show that tracking data from mobile devices is linked to systematic distortions in sel…
CorCast: A Distributed Architecture for Bayesian Epidemic Nowcasting and its Application to District-Level SARS-CoV-2 Infection Numbers in Germany
2021
Timely information on current infection numbers during an epidemic is of crucial importance for decision makers in politics, medicine, and businesses. As information about local infection risk can guide public policy as well as individual behavior, such as the wearing of personal protective equipment or voluntary social distancing, statistical models providing such insights should be transparent and reproducible as well as accurate. Fulfilling these requirements is drastically complicated by the large amounts of data generated during exponential growth of infection numbers, and by the complexity of common inference pipelines. Here, we present CorCast – a stable and scalable distributed arch…
Methods to Use Big Wearable Heart Rate Data for Estimation of Physical Activity in Population Level
2015
Technologies for wearable health monitoring are becoming increasingly popular and affordable. As a result, large-scale health databases from a large number of individuals are becoming available. However, analysis of these databases requires special methodology to transform available parameters into more generic ones and to manage such non-balanced data characteristics as biases and sampling issues. In this paper, we introduce a methodology for studying physical activity from big wearable heart rate (HR) data on about 5 000 working-age individuals, each measured only for a few days. Physical activity was assessed by oxygen consumption (VO2) calculated from measured HR data using a neural net…
The Conceptualisation and Measurement of Mega Sport Event Legacies
2007
This paper focuses on the legacy of mega sport events. First, the concept of legacy is defined before the problems of measuring and forecasting legacy are discussed. Benchmarking and the use of macro data do not correctly reveal legacy. Hence a bottom-up approach is introduced which identifies the event legacy by evaluation of ‘soft’ and ‘hard’ event-related changes in a host city. These changes are defined as ‘event-structures’ (infrastructure, knowledge, image, emotions, networks, culture). Many of them change the quality of location factors of the host city in the long-term. The benefits/costs through the transformation of the host city are the legacy of a mega sport event. Here a partic…