Search results for "11"

Context–content systems of random variables : The Contextuality-by-Default theory

2016

Abstract This paper provides a systematic yet accessible presentation of the Contextuality-by-Default theory. The consideration is confined to finite systems of categorical random variables, which allows us to focus on the basics of the theory without using full-scale measure-theoretic language. Contextuality-by-Default is a theory of random variables identified by their contents and their contexts, so that two variables have a joint distribution if and only if they share a context. Intuitively, the content of a random variable is the entity the random variable measures or responds to, while the context is formed by the conditions under which these measurements or responses are obtained. A …

Can back-projection fully resolve polarity indeterminacy of independent component analysis in study of event-related potential?

2011

a b s t r a c t In the study of event-related potentials (ERPs) using independent component analysis (ICA), it is a traditional way to project the extracted ERP component back to electrodes for correcting its scaling (magnitude and polarity) indeterminacy. However, ICA tends to be locally optimized in practice, and then, the back-projection of a component estimated by the ICA can possibly not fully correct its polarity at every electrode. We demonstrate this phenomenon from the view of the theoretical analysis and numerical simulations and suggest checking and modifying the abnormal polarity of the projected component in the electrode field before further analysis. Moreover, when several co…

Selection of the Proper Revenue and Pricing Model for SaaS

2014

Recent research on software revenue and pricing models has revealed important ways in which firms can benefit from software renting. However, it is still unclear how SaaS providers select a proper revenue and pricing model to make their services attractive for customers. Based on 32 interviews with software professionals from four case firms, this study reveals how different factors impacted on the selection of a revenue and pricing model. It can be concluded that customers’ needs were the main driving force to the selection of the most appropriate pricing and revenue model in the market. peerReviewed

Social Collaborative Viewpoint Regression with Explainable Recommendations

2017

A recommendation is called explainable if it not only predicts a numerical rating for an item, but also generates explanations for users' preferences. Most existing methods for explainable recommendation apply topic models to analyze user reviews to provide descriptions along with the recommendations they produce. So far, such methods have neglected user opinions and influences from social relations as a source of information for recommendations, even though these are known to improve the rating prediction. In this paper, we propose a latent variable model, called social collaborative viewpoint regression (sCVR), for predicting item ratings based on user opinions and social relations. To th…

Convolutional neural networks in skin cancer detection using spatial and spectral domain

2019

Skin cancers are world wide deathly health problem, where significant life and cost savings could be achieved if detection of cancer can be done in early phase. Hypespectral imaging is prominent tool for non-invasive screening. In this study we compare how use of both spectral and spatial domain increase classification performance of convolutional neural networks. We compare five different neural network architectures for real patient data. Our models gain same or slightly better positive predictive value as clinicians. Towards more general and reliable model more data is needed and collection of training data should be systematic. peerReviewed

CSI with games and an emphasis on TDD and unit testing

2012

Human-technology choreographies

2014

Bodily movements have traditionally had mostly instrumental value in interaction design. However, movements can also be given a central role in understanding behaviour and in designing technology for humans. This workshop is aiming at taking a fresh, movement-oriented look at the design and evaluation of technology in a wide variety of contexts.

A Novel Model for Cybersecurity Economics and Analysis

2017

In recent times, major cybersecurity breaches and cyber fraud had huge negative impact on victim organisations. The biggest impact made on major areas of business activities. Majority of organisations facing cybersecurity adversity and advanced threats suffers from huge financial and reputation loss. The current security technologies, policies and processes are providing necessary capabilities and cybersecurity mechanism to solve cyber threats and risks. However, current solutions are not providing required mechanism for decision making on impact of cybersecurity breaches and fraud. In this paper, we are reporting initial findings and proposing conceptual solution. The paper is aiming to pr…

Internet Adoption at the User Level: Empirical Evidence from The Gambia

2014

The unified theory of acceptance and use of technology (UTAUT) are used to investigate technology adoption. However, its application in Sub-Saharan Africa is rare and barely extended to the validation phase. In this paper, we introduce six new moderating factors for UTAUT core determinants and two other direct determinants of Internet adoption. The objective of this approach is to identify relevant elements of Internet adoption at the user level in The Gambia. Moderating factors are interacting terms used when the relationship between independent and dependent variable is weak, inconsistent or non-existent. A case study research design was employed and the data were gathered in Autumn of 20…

Online anomaly detection using dimensionality reduction techniques for HTTP log analysis

2015

Modern web services face an increasing number of new threats. Logs are collected from almost all web servers, and for this reason analyzing them is beneficial when trying to prevent intrusions. Intrusive behavior often differs from the normal web traffic. This paper proposes a framework to find abnormal behavior from these logs. We compare random projection, principal component analysis and diffusion map for anomaly detection. In addition, the framework has online capabilities. The first two methods have intuitive extensions while diffusion map uses the Nyström extension. This fast out-of-sample extension enables real-time analysis of web server traffic. The framework is demonstrated using …