Constructing and validating a scale of employee satisfaction with HRM practices in the healthcare context

The concept of HRM perceptions is a growing interest in the literature, as one of the antecedents of HRM outcomes. Regardless, not only the cognitive aspect of perception is interesting in this field (what you think) but also the affective perspective is of interest (how you feel about it). In this study we propose a scale for assessing satisfaction with the perceptions of the HRM practices. A 24 item Likert-type scale was developed considering literature review, to assess subjects’ satisfaction with Human Resources Practices in a healthcare setting. Talked reflections were held and a survey encompassing all workers from a Hospital was conducted later, with a sample of 922 subjects. Exploratory and Confirmatory Factor Analysis were performed; reliability was tested using Cronbach’s alpha. The scale presents good psychometric properties with alpha values that range from .71 to .91. Exploratory and Confirmatory Factor Analysis demonstrated that the scale presents a very good fit with CFI= 0.94, AGFI= 0.88, and RMSEA= 0.07. The present study represents a first approach in the usage of this scale and despite having a large sample, respondents originate from a single institution. This study presents a pertinent scale towards measuring a seldom explored construct of the worker-organization relationship. The scale is parsimonious and results are promising. There seems to be very little research on how subjects feel about the HRM practices. This construct, very much in line with more recent studies concerning worker perceptions can be especially interesting in the context of the worker-organization relationship.

Estimation Models for the adoption and use of information technology: internet-related technologies at firm level in the Portuguese and European context

Dissertação apresentada como requisito parcial para obtenção do grau de Doutor em Gestão de Informação

CANDi: context-aware node discovery for short-range cooperation

Multi-standard mobile devices are allowing users to enjoy higher data rates with ubiquitous connectivity. However, the benefits gained from multiple interfaces come at an expense—that being higher energy consumption in an era where mobile devices need to be energy compliant. One promising solution is the usage of short-range cooperative communication as an overlay for infrastructure-based networks taking advantage of its context information. However, the node discovery mechanism, which is pivotal to the bearer establishment process, still represents a major burden in terms of the total energy budget. In this paper, we propose a technology agnostic approach towards enhancing the MAC energy ratings by presenting a context-aware node discovery (CANDi) algorithm, which provides a priori knowledge towards the node discovery mechanism by allowing it to search nodes in the near vicinity at the ‘right time and at the right place’. We describe the different beacons required for establishing the cooperation, as well as the context information required, including battery level, modes, location and so on. CANDi uses the long-range network (WiMAX and WiFi) to distribute the context information about cooperative clusters (Ultra-wideband-based) in the vicinity. The searching nodes can use this context in locating the cooperative clusters/nodes, which facilitates the establishing of short-range connections. Analytical and simulation results are obtained, and the energy saving gains are further demonstrated in the laboratory using a customised testbed. CANDi saves up to 50% energy during the node discovery process, while the demonstrative testbed shows up to 75% savings in the total energy budget, thus validating the algorithm, as well as providing viable evidence to support the usage of short-range cooperative communications for energy savings.

A framework for robustness assessment in the context of corroded RC structures

Structural robustness is an emergent concept related to the structural response to damage. At the present time, robustness is not well defined and much controversy still remains around this subject. Even if robustness has seen growing interest as a consequence of catastrophic consequences due to extreme events, the fact is that the concept can also be very useful when considered on more probable exposure scenarios such as deterioration, among others. This paper intends to be a contribution to the definition of structural robustness, especially in the analysis of reinforced concrete structures subjected to corrosion. To achieve this, first of all, several proposed robustness definitions and indicators and misunderstood concepts will be analyzed and compared. From this point and regarding a concept that could be applied to most type of structures and dam-age scenarios, a robustness definition is proposed. To illustrate the proposed concept, an example of corroded reinforced concrete structures will be analyzed using nonlinear analysis numerical methods based on a contin-uum strong discontinuities approach and isotropic damage models for concrete. Finally the robustness of the presented example will be assessed.

Bringing Context Awareness to IoT-Based Wireless Sensor Networks

IEEE International Conference on Pervasive Computing and Communications (PerCom). 23 to 26, Mar, 2015, PhD Forum. Saint Louis, U.S.A..

Students’ reading behavior: digital vs. print preferences in portuguese context

The aim of this paper is to present the main Portuguese results from a multi-national study on reading format preferences and behaviors from undergraduate students from Polytechnic Institute of Porto (Portugal). For this purpose we apply an adaptation of the Academic Reading Questionnaire previously created by Mizrachi (2014). This survey instrument has 14 Likert-style statements regarding the format influence in the students reading behavior, including aspects such as ability to remember, feelings about access convenience, active engagement with the text by highlighting and annotating, and ability to review and concentrate on the text. The importance of the language and dimension of the text to determine the preference format is also inquired. Students are also asked about the electronic device they use to read digital documents. Finally, some demographic and academic data were gathered. The analysis of the results will be contextualized on a review of the literature concerning youngsters reading format preferences. The format (digital or print) in which a text is displayed and read can impact comprehension, which is an important information literacy skill. This is a quite relevant issue for class readings in academic context because it impacts learning. On the other hand, students preferences on reading formats will influence the use of library services. However, literature is not unanimous on this subject. Woody, Daniel and Baker (2010) concluded that the experience of reading is not the same in electronic or print context and that students prefer print books than e-books. This thesis is reinforced by Ji, Michaels and Waterman (2014) which report that among 101 undergraduates the large majority self-reported to read and learn more when they use printed format despite the fact that they prefer electronically supplied readings instead of those supplied in printed form. On the other side, Rockinson-Szapkiw, et al (2013) conducted a study were they demonstrate that e-textbook is as effective for learning as the traditional textbook and that students who choose e-textbook had significantly higher perceived learning than students who chose to use print textbooks.

Information professionals in business context: new professionals, old skills

This communication aims to present some reflections regarding the importance of information in organizational context, especially in business context. The ability to produce and to share expertise and knowledge among its employees is now a key factor in the success of any organization. However, it’s also true that workers are increasingly feeling that too much information can hurt their performance. The existence of skilled professionals able to organize, evaluate, select and disseminate information in organizations appears to be a prerequisite for success. The skills necessary for the formation of a professional devoted to the management of information and knowledge in the context of business organizations will be analysed. Then data collected in two focus group discussion with students from a graduate course in Business Information, from Polytechnic Institute of Porto, Portugal, a will be examined.

Partilha de Pontos de Interesse, Vídeos e Experiências Sensoriais Baseada no Contexto do Utilizador

A evolução tecnológica das últimas décadas na área das Tecnologias da Informação e Comunicação (TIC) contribuiu para a proliferação de fontes de informação e de sistemas de partilha de recursos. As diversas redes sociais são um exemplo paradigmático de sistemas de partilha tanto de informação como de recursos (e.g. audiovisuais). Essa abundância crescente de recursos e fontes aumenta a importância de sistemas capazes de recomendar em tempo útil recursos personalizados, tendo por base o perfil e o contexto do utilizador. O objetivo deste projeto é partilhar e recomendar locais, artigos e vídeos em função do contexto do utilizador assim como proporcionar uma experiência mais rica de reprodução dos vídeos partilhados, simulando as condições de gravação dos vídeos. Este sistema teve como inspiração dois projetos anteriormente desenvolvidos de partilha e recomendação de locais, artigos e vídeos turísticos em função da localização do utilizador. O sistema desenvolvido consiste numa aplicação distribuída composta por um módulo cliente Android, que inclui a interface com o utilizador e o consumo direto de serviços externos de suporte, e um módulo servidor que controla o acesso à base de dados central e inclui o serviço de recomendação baseado no contexto do utilizador. A comunicação entre os módulos cliente e servidor utiliza um protocolo do nível de aplicação dedicado. As recomendações geradas pelo sistema têm por base o perfil de utilizador, informação contextual (posição do utilizador, data e hora atual e velocidade atual do utilizador) e podem ser geradas a pedido do utilizador ou automaticamente, caso sejam encontrados pontos de interesse de grande relevância para o utilizador. Os pontos de interesse recomendados são apresentados com recurso ao Google Maps, incluindo o período de funcionamento, artigos complementares e a reprodução imersiva dos vídeos relacionados. Essa imersão tem em consideração as condições meteorológicas, temporais e espaciais aquando da gravação do vídeo.

Negotiation context analysis in electricity markets

Contextualization is critical in every decision making process. Adequate responses to problems depend not only on the variables with direct influence on the outcomes, but also on a correct contextualization of the problem regarding the surrounding environment. Electricity markets are dynamic environments with increasing complexity, potentiated by the last decades' restructuring process. Dealing with the growing complexity and competitiveness in this sector brought the need for using decision support tools. A solid example is MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), whose players' decisions are supported by another multiagent system – ALBidS (Adaptive Learning strategic Bidding System). ALBidS uses artificial intelligence techniques to endow market players with adaptive learning capabilities that allow them to achieve the best possible results in market negotiations. This paper studies the influence of context awareness in the decision making process of agents acting in electricity markets. A context analysis mechanism is proposed, considering important characteristics of each negotiation period, so that negotiating agents can adapt their acting strategies to different contexts. The main conclusion is that context-dependant responses improve the decision making process. Suiting actions to different contexts allows adapting the behaviour of negotiating entities to different circumstances, resulting in profitable outcomes.

A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives.

Question order and context effects on multi-items scales questions

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

Decision-making process in radiology: the magnetic resonance example in the TA context

Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Michael Decker (Karlsruhe Institute of Technology-ITAS). Other members of the thesis committee are Carlos Alberto da Silva (University of Évora), José Maria de Albuquerque (Institute of Welding and Quality), Lotte Steuten (University of Twente), Mário Forjaz Secca (FCT-UNL) and Nelson Chibeles Martins (FCT-UNL).

Recommendation of Tourism Resources Supported by Crowdsourcing

Context-aware recommendation of personalised tourism resources is possible because of personal mobile devices and powerful data filtering algorithms. The devices contribute with computing capabilities, on board sensors, ubiquitous Internet access and continuous user monitoring, whereas the filtering algorithms provide the ability to match the profile (interests and the context) of the tourist against a large knowledge bases of tourism resources. While, in terms of technology, personal mobile devices can gather user-related information, including the user context and access multiple data sources, the creation and maintenance of an updated knowledge base of tourism-related resources requires a collaborative approach due to the heterogeneity, volume and dynamic nature of the resources. The current PhD thesis aims to contribute to the solution of this problem by adopting a Crowdsourcing approach for the collaborative maintenance of the knowledge base of resources, Trust and Reputation for the validation of uploaded resources as well as publishers, Big Data for user profiling and context-aware filtering algorithms for the personalised recommendation of tourism resources.