Search results for "Data science"

From user-generated data to data-driven innovation: A research agenda to understand user privacy in digital markets

2021

Abstract In recent years, strategies focused on data-driven innovation (DDI) have led to the emergence and development of new products and business models in the digital market. However, these advances have given rise to the development of sophisticated strategies for data management, predicting user behavior, or analyzing their actions. Accordingly, the large-scale analysis of user-generated data (UGD) has led to the emergence of user privacy concerns about how companies manage user data. Although there are some studies on data security, privacy protection, and data-driven strategies, a systematic review on the subject that would focus on both UGD and DDI as main concepts is lacking. There…

Identifying relevant segments of AI applications adopters : Expanding the UTAUT2’s variables

2021

Artificial intelligence (AI) is a future-defining technology, and AI applications are becoming mainstream in the developed world. Many consumers are adopting and using AI-based apps, devices, and services in their everyday lives. However, research examining consumer behavior in using AI apps is scant. We examine critical factors in AI app adoption by extending and validating a well-established unified theory of adoption and use of technology, UTAUT2. We also explore the possibility of unobserved heterogeneity in consumers’ behavior, including potentially relevant segments of AI app adopters. To augment the knowledge of end users’ engagement and relevant segments, we have added two new antec…

Collaborative body sensor networks: Taxonomy and open challenges

2018

International audience; Single Body Sensor Networks (BSNs) have gained a lot of interest during the past few years. However, the need to monitor the activity of many individuals to assess the group status and take action accordingly has created a new research domain called Collaborative Body Sensor Network (CBSN). In such a new field, understanding CBSN's concept and challenges over the roots requires investigation to allow the development of suitable algorithms and protocols. Although there are many research studies in BSN, CBSN is still in its early phases and studies around it are very few. In this paper, we define and taxonomize CBSN, describe its architecture, and discuss its applicati…

Information Abstraction from Crises Related Tweets Using Recurrent Neural Network

2016

Social media has become an important open communication medium during crises. The information shared about a crisis in social media is massive, complex, informal and heterogeneous, which makes extracting useful information a difficult task. This paper presents a first step towards an approach for information extraction from large Twitter data. In brief, we propose a Recurrent Neural Network based model for text generation able to produce a unique text capturing the general consensus of a large collection of twitter messages. The generated text is able to capture information about different crises from tens of thousand of tweets summarized only in a 2000 characters text.

An omics perspective to the molecular mechanisms of anticancer metallo-drugs in the computational microscope era

2017

Introduction: Metallo-drugs have attracted enormous interest for cancer treatment. The achievements of this drug-type are summarized by the success story of cisplatin. That being said, there have been many drawbacks with its clinical use, which prompted decades worth of research efforts to move towards safer and more effective agents, either containing platinum or different metals. Areas covered: In this review, the authors provide an atomistic picture of the molecular mechanisms involving selected metallo-drugs from structural and molecular simulation studies. They also provide an omics perspective, pointing out many unsettled aspects of the most relevant families of metallo-drugs at an ep…

Dades massives i estadística: La perspectiva d'un estadístic

2014

Les dades massives (big data) representen un recurs sense precedents per a afrontar reptes científics, econòmics i socials, però també incrementen la possibilitat de traure conclusions enganyoses. Per exemple, l’ús d’enfocaments basats exclusivament en dades i que es despreocupen de comprendre el fenomen en estudi, que s’orienten a un objectiu esmunyedís i canviant, que no tenen en compte problemes determinants en la recopilació de dades, que resumeixen o «cuinen» inadequadament les dades i que confonen el soroll amb el senyal. Repassarem alguns casos reeixits i il·lustrarem com poden ajudar els principis de l’estadística a obtenir una informació més fiable de les dades. També abordarem els…

Introduction and Technical Survey: Protein Aggregation and Fibrillogenesis

2012

In this chapter we provided the overall background to the subject of protein aggregation and fibrillogenesis in amyloidogenesis, with introduction and brief discussion of the various topics that are included with the coming chapters. The division of the book into basic science and clinical science sections enables correlation of the topics to be made. The many proteins and peptides that have currently been found to undergo fibrillogenesis are tabulated. A broad technical survey is made, to indicate the vast array of techniques currently available to study aspects of protein oligomerization, aggregation and fibrillogenesis. These are split into three groups and tabulated, as the microscopica…

Measuring Behavior in the Home Cage: Study Design, Applications, Challenges, and Perspectives

2021

Contains fulltext : 239279.pdf (Publisher’s version ) (Open Access) The reproducibility crisis (or replication crisis) in biomedical research is a particularly existential and under-addressed issue in the field of behavioral neuroscience, where, in spite of efforts to standardize testing and assay protocols, several known and unknown sources of confounding environmental factors add to variance. Human interference is a major contributor to variability both within and across laboratories, as well as novelty-induced anxiety. Attempts to reduce human interference and to measure more "natural" behaviors in subjects has led to the development of automated home-cage monitoring systems. These syste…

Track and Workshop Program Chair Messages

2016

Publication and Coauthorship Networks of Hannu Oja

2015

In this paper we review Hannu Oja’s publications and form coauthor networks based on them. Applying community detection methods to the network formed by all of Hannu’s publications shows that his coauthors can be classified into 13 clusters, where two large clusters refer to his methodological research. The network concerning this methodological work is then extended to cover all statistical publications written by Hannu’s coauthors. The analysis of the extended network shows that Hannu’s coauthors do not form a closed community, but Hannu is involved in many different fields of statistics.