Search results for "Information Systems"

On the Generalizability of Programs Synthesized by Grammar-Guided Genetic Programming

2021

Grammar-guided Genetic Programming is a common approach for program synthesis where the user’s intent is given by a set of input/output examples. For use in real-world software development, the generated programs must work on previously unseen test cases too. Therefore, we study in this work the generalizability of programs synthesized by grammar-guided GP with lexicase selection. As benchmark, we analyze proportionate and tournament selection too. We find that especially for program synthesis problems with a low output cardinality (e.g., a Boolean output) lexicase selection overfits the training cases and does not generalize well to unseen test cases. An analysis using common software metr…

A Framework for Component Reuse in a Metamodelling-Based Software Development

2001

Exploring the Role of Informants in Interpretive Case Study Research in IS

2011

Interpretive case study research constitutes an important and increasing part of the information systems (IS) knowledge base (Walsham, 1993; Myers, 1997; Pare and Elam, 1997; Walsham, 2006). Interpretive case studies can be distinguished from positivist case study research (Benbasat et al., 1987; Lee, 1989; Dube and Pare, 2003) by the focus on close interaction between researcher and participants throughout the case study process, viewing the case members as active participants in the construction of the case narrative (Boland, 1985; Guba and Lincoln, 1989; Kvale, 2002). However, while the interpretivist perspective ascribes an active role to the case study informants, in practice the exten…

A reflective characterisation of occasional user

2017

This work revisits established user classifications and aims to characterise a historically unspecified user category, the Occasional User (OU). Three user categories, novice, intermediate and expert, have dominated the work of user interface (UI) designers, researchers and educators for decades. These categories were created to conceptualise user's needs, strategies and goals around the 80s. Since then, UI paradigm shifts, such as direct manipulation and touch, along with other advances in technology, gave new access to people with little computer knowledge. This fact produced a diversification of the existing user categories not observed in the literature review of traditional classificat…

WiseNET - smart camera network interacting with a semantic model

2016

This paper presents an innovative concept for a distributed system that combines a smart camera network with semantic reasoning. The proposed system is context sensitive and combines the information extracted by the smart camera with logic rules and knowledge of what the camera observes, building information and events that may occurred. The proposed system is a justification for the use of smart cameras, and it can improve the classical visual sensor networks (VSN) and enhance the standard computer vision approach. The main application of our system is smart building management, where we specifically focus on increasing the services of the building users.

Achieving agility and quality in product development -an empirical study of hardware startups

2020

Context: Startups aim at scaling their business, often by developing innovative products with limited human and financial resources. The development of software products in the startup context is known as opportunistic, agility-driven, and with high tolerance for technical debt. The special context of hardware startups calls for a better understanding of state-of-the-practice of hardware startups’ activities. Objective: This study aimed to identify whether and how startups can achieve product quality while maintaining focus on agility. Method: We conducted an exploratory study with 13 hardware startups, collecting data through semi-structured interviews and analysis of documentation. We pro…

Diversity in search strategies for ensemble feature selection

2005

Ensembles of learnt models constitute one of the main current directions in machine learning and data mining. Ensembles allow us to achieve higher accuracy, which is often not achievable with single models. It was shown theoretically and experimentally that in order for an ensemble to be effective, it should consist of base classifiers that have diversity in their predictions. One technique, which proved to be effective for constructing an ensemble of diverse base classifiers, is the use of different feature subsets, or so-called ensemble feature selection. Many ensemble feature selection strategies incorporate diversity as an objective in the search for the best collection of feature subse…

Problematic internet use prior to and during the COVID-19 pandemic

2021

The health and socio-economic challenges arising from the COVID-19 pandemic have led to greater reliance on the internet to meet basic needs and responsibilities. Greater engagement in online activities may have negative mental and physical health consequences for some vulnerable individuals, particularly under mandatory self-isolation or ‘lockdown’ conditions. The present study investigated whether changes in levels of involvement in online activities during the COVID-19 pandemic (i.e., watching TV series,online sexual activities, video games, social networks, gambling, online shopping, and instant messaging) were associated with problematic internet use, as well as whether certain psychol…

Improving big-data automotive applications performance through adaptive resource allocation

2019

In automotive applications, connected vehicles (CVs) can collect various information (external temperature, speed, location, etc.) and send them to a central infrastructure for exploitation in a wide range of applications: Eco-Driving, fleet management, environmental monitoring, etc. Such applications are known to generate a massive volume of data that is processed in real or near real time (i.e., data streams) depending on the target application requirements. To handle this data volume, big data architectures, based on stream computing paradigm, are usually adopted. Within this paradigm, data are continuously processed by a set of operators (elementary operations) instances. Further, a str…

Terrain data compression using wavelet-tiled pyramids for online 3D terrain visualization

2013

Last years have witnessed the widespread use of online terrain visualization applications. However, the significant improvements achieved in sensing technologies have allowed an increasing size of the terrain databases. These increasing sizes represent a serious drawback when terrain data must be transmitted and rendered at interactive rates. In this paper, we propose a novel wavelet-tiled pyramid for compressing terrain data that replaces the traditional multiresolution pyramid usually used in wavelet compression schemes. The new wavelet-tiled pyramid modifies the wavelet analysis and synthesis processes, allowing an efficient transmission and reconstruction of terrain data in those applic…