Benefits & drawbacks of different means of interaction for placing objects above a video footage

Public Display Systems (PDS) increasingly have a greater presence in our cities. These systems provide information and advertising specifically tailored to audiences in spaces such as airports, train stations, and shopping centers. A large number of public displays are also being deployed for entertainment reasons. Sometimes designing and prototyping PDS come to be a laborious, complex and a costly task. This dissertation focuses on the design and evaluation of PDS at early development phases with the aim of facilitating low-effort, rapid design and the evaluation of interactive PDS. This study focuses on the IPED Toolkit. This tool proposes the design, prototype, and evaluation of public display systems, replicating real-world scenes in the lab. This research aims at identifying benefits and drawbacks on the use of different means to place overlays/virtual displays above a panoramic video footage, recorded at real-world locations. The means of interaction studied in this work are on the one hand the keyboard and mouse, and on the other hand the tablet with two different techniques of use. To carry out this study, an android application has been developed whose function is to allow users to interact with the IPED Toolkit using the tablet. Additionally, the toolkit has been modified and adapted to tablets by using different web technologies. Finally the users study makes a comparison about the different means of interaction.

Performance of a rapid diagnostic test for the detection of visceral leishmaniasis in a large urban setting

Introduction Rapid diagnostic tests (RDTs) may improve the early detection of visceral leishmaniasis (VL), but their real-world performance requires additional study. Therefore, we evaluated the performance of an rK39-based RDT (Kalazar Detect™) for the detection of VL in an endemic, large urban area. Methods Data were collected from a registry of rK39 RDT performed at 11 emergency care units in Belo Horizonte, Brazil, and from a national database of reportable communicable diseases of the Sistema de Informação de Agravos de Notificação (SINAN). Results The rapid rK39 test was performed in 476 patients, with 114 (23.9%) positive results. The analysis of rK39 RDT performance was based on 381 (80%) cases reported to the SINAN database, of which 145 (38.1%) were confirmed cases. Estimates for sensitivity and specificity were 72.4% (95% CI: 64.6-79%) and 99.6% (95%CI: 97.6-99.9%), respectively. Positive and negative predictive values were estimated at 99.1% (95%CI: 94.9-99.8%) and 85.5% (95%CI: 80.8-89.1%), respectively. In addition, close agreement between the rK39 RDT and indirect immunofluorescence was observed. Conclusions In summary, the rK39 RDT showed a high specificity but only moderate sensitivity. In endemic areas for VL, treatment may be considered in cases with clinical manifestations and a positive rK39 RDT, but those with a negative test should be subjected to further investigation.

Clinical practice guidelines in Portugal : quantitative and qualitative evaluation

RESUMO: Introdução As normas de orientação clínica são ferramentas úteis na translação de conhecimentos desde a investigação para a prática clínica diária. Estratégias ativas de implementação de normas de orientação clínica requerem elevado esforço organizacional e financeiro. Quando os recursos são escassos, as estratégias passivas podem ser a única opção de disseminação. Desde 2011 a Direção Geral da Saúde publicou cento e cinquenta e nove normas de orientação clínica. Nesta Tese é feita uma avaliação do impacto que estratégias de disseminação de normas de orientação clínica têm no padrão de prescrição dos médicos e uma avaliação qualitativa do processo das normas de orientação clínica em Portugal. Métodos: O primeiro artigo é um estudo quasi experimental usando uma série de análises temporais interrompida para comparar os níveis observados e esperados de prescrição de inibidores da ciclooxigenasa-2, antes e depois da publicação da norma de orientação clínica sobre a utilização de anti-inflamatórios não esteroides. O segundo estudo é um artigo de opinião e debate no qual numa primeira parte contextualiza o processo das normas da Direcção Geral da Saúde, na segunda parte aponta virtudes e defeitos no processo e a terceira parte constitui uma contribuição com vista à melhoria do processo. Discussão A produção de normas de orientação clínica requer metodologia rigorosa e complexa. A literatura médica revela que a translação de conhecimento é uma tarefa árdua. Estratégias de implementação ativas requerem recursos financeiros e organizacionais sólidos. Estratégias de implementação passivas podem representar uma solução aceitável se os recursos financeiros e organizacionais escasseiam. Pouco é conhecido sobre a eficácia destas estratégias fora do contexto de investigação. Com esta Tese pretendo contribuir para a clarificação desta resposta, outros países e instituições podem ver utilidade nesta informação, bem como pretendo contribuir para a discussão e melhoria do processo das normas de orientação clínica em Portugal. ------------------ ABSTRACT: Introduction Clinical practice guidelines can help address the failure to translate research findings into clinical practice. Active clinical practice guidelines implementation strategies require active efforts from organizations and are resource and financially demanding. Passive implementation strategies may represent the only option if resources are scarce. Out of research environment, real world efficacy of passive implementation strategies is still undetermined. Since 2011 the Portuguese General Health Directorate published one hundred and fifty nine guidelines. In this Thesis I evaluate the impact of passive dissemination of clinical practice guideline in clinician’s prescription behavior and review, from a qualitative point of view, the Portuguese clinical practice guideline process. Methods The first study is a quasi-experimental study using a retrospective interrupted time-series analysis design to compare the observed and expected prescription of cyclooxygenase-2 before and after the non steroidal antiinflammatory guideline publication. The second study is an opinion and debate article in which I firstly review the General Health Directorate guideline process. The second part states positive and negative aspects in the process and the third part is a contribution aimed at improving the process in the future. Discussion Clinical practice guidelines production demands a rigorous and complex methodology. medical iterature reveals that knowledge translation is a difficult task. Active implementation strategies demand solid financial and organizational resources. Passive implementation strategies may represent an acceptable solution if financial and organizational resources are scarce. Little is known about the efficacy of these strategies out of the research context. With this Thesis I intend to contribute to clarify this question, other countries and institutions with similar conditions may find this information useful, and also to contribute for the discussion and general improvement of national clinical practice guidelines process.

Quadratic programming versus second order con programming in portfolio optimization

Despite the extensive literature in finding new models to replace the Markowitz model or trying to increase the accuracy of its input estimations, there is less studies about the impact on the results of using different optimization algorithms. This paper aims to add some research to this field by comparing the performance of two optimization algorithms in drawing the Markowitz Efficient Frontier and in real world investment strategies. Second order cone programming is a faster algorithm, appears to be more efficient, but is impossible to assert which algorithm is better. Quadratic Programming often shows superior performance in real investment strategies.

A multi-criteria decision support system for a routing problem in waste collection

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Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

An evolutionary multi-objective optimization system for earthworks

Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

An integrated system for human action recognition from video using hidden Markov model

In this paper, we present an integrated system for real-time automatic detection of human actions from video. The proposed approach uses the boundary of humans as the main feature for recognizing actions. Background subtraction is performed using Gaussian mixture model. Then, features are extracted from silhouettes and Vector Quantization is used to map features into symbols (bag of words approach). Finally, actions are detected using the Hidden Markov Model. The proposed system was validated using a newly collected real- world dataset. The obtained results show that the system is capable of achieving robust human detection, in both indoor and outdoor environments. Moreover, promising classification results were achieved when detecting two basic human actions: walking and sitting.

On the impact of overlapping access points in detecting node encounters

Data traces, consisting of logs about the use of mobile and wireless networks, have been used to study the statistics of encounters between mobile nodes, in an attempt to predict the performance of opportunistic networks. Understanding the role and potential of mobile devices as relaying nodes in message dissemination and delivery depends on the knowledge about patterns and number of encounters among nodes. Data traces about the use of WiFi networks are widely available and can be used to extract large datasets of encounters between nodes. However, these logs only capture indirect encounters between nodes, and the resulting encounters datasets might not realistically represent the spatial and temporal behaviour of nodes. This paper addresses the impact of overlapping between the coverage areas of different Access Points of WiFi networks in extracting encounters datasets from the usage logs. Simulation and real-world experimental results show that indirect encounter traces extracted directly from these logs strongly underestimate the opportunities for direct node-to- node message exchange in opportunistic networks.

Cost-effective and lightweight mobile units for MixAR: A comparative trial among different setups

Cultural heritage has arousing the interest of the general public (e.g. tourists), resulting in the increasing number of visitations to archaeological sites. However, many buildings and monuments are severely damaged or completely destroyed, which doesn’t allow to get a full experience of “travelling in time”. Over the years, several Augmented Reality (AR) approaches were proposed to overcome these issues by providing three-dimensional visualization of reconstructed ancient structures in situ. However, most of these systems were made available through heavy and expensive technological bundles. Alternatively, MixAR intends to be a lightweight and cost-effective Mixed Reality system which aims to provide the visualization of virtual ancient buildings reconstructions in situ, properly superimposed and aligned with real-world ruins. This paper proposes and compares different AR mobile units setups to be used in the MixAR system, with low-cost and lightweight requirements in mind, providing different levels of immersion. It was propounded four different mobile units, based on: a laptop computer, a single-board computer (SBC), a tablet and a smartphone, which underwent a set of tests to evaluate their performances. The results show that mobile units based on laptop computer and SBC reached a good overall performance while mobile units based on tablet and smartphone did not meet such a satisfactory result even though they are acceptable for the intended use.

MixAR mobile prototype: visualizing virtually reconstructed ancient structures in situ

Archeology and related areas have a special interest on cultural heritage sites since they provide valuable information about past civilizations. However, the ancient buildings present in these sites are commonly found in an advanced state of degradation which difficult the professional/expert analysis. Virtual reconstructions of such buildings aim to provide a digital insight of how these historical places could have been in ancient times. Moreover, the visualization of such models has been explored by some Augmented Reality (AR) systems capable of providing support to experts. Their compelling and appealing environments have also been applied to promote the social and cultural participation of general public. The existing AR solutions regarding this thematic rarely explore the potential of realism, due to the following lacks: the exploration of mixed environments is usually only supported for indoors or outdoors, not both in the same system; the adaptation of the illumination conditions to the reconstructed structures is rarely addressed causing a decrease of credibility. MixAR [1] is a system concerned with those challenges, aiming to provide the visualization of virtual buildings augmented upon real ruins, allowing soft transitions among its interiors and exteriors and using relighting techniques for a faithful interior illumination, while the user freely moves in a given cultural heritage site, carrying a mobile unit. Regarding the focus of this paper, we intend to report the current state of MixAR mobile unit prototype, which allows visualizing virtual buildings – properly aligned with real-world structures – based on user's location, during outdoor navigation. In order to evaluate the prototype performance, a set of tests were made using virtual models with different complexities.

Task clustering on ETL systems – A pattern-oriented approach

Usually, data warehousing populating processes are data-oriented workflows composed by dozens of granular tasks that are responsible for the integration of data coming from different data sources. Specific subset of these tasks can be grouped on a collection together with their relationships in order to form higher- level constructs. Increasing task granularity allows for the generalization of processes, simplifying their views and providing methods to carry out expertise to new applications. Well-proven practices can be used to describe general solutions that use basic skeletons configured and instantiated according to a set of specific integration requirements. Patterns can be applied to ETL processes aiming to simplify not only a possible conceptual representation but also to reduce the gap that often exists between two design perspectives. In this paper, we demonstrate the feasibility and effectiveness of an ETL pattern-based approach using task clustering, analyzing a real world ETL scenario through the definitions of two commonly used clusters of tasks: a data lookup cluster and a data conciliation and integration cluster.

Distance perception in immersive environments: the role of photorealism

Immersive environments (IE) are being increasingly used in order to perform psychophysical experiments. The versatility in terms of stimuli presentation and control and the less time-consuming procedures are their greatest strengths. However, to ensure that IE results can be generalized to real world scenarios we must first provide evidence that performance in IE is quantitatively indistinguishable from performance in real-world. Our goal was to perceptually validate distance perception for CAVE-like IEs. Participants performed a Frontal Matching Distance Task (Durgin & Li, 2011) in three different conditions: real-world scenario (RWS); photorealistic IE (IEPH) and non-photorealistic IE (IENPH). Underestimation of distance was found across all the conditions, with a significant difference between the three conditions (Wilks’ Lambda = .38, F(2,134)= 110.8, p<.01, significant pairwise differences with p<.01). We found a mean error of 2.3 meters for the RWS, 5 meters for the IEPH, and of 6 meters for the IENPH in a pooled data set of 5 participants. Results indicate that while having a photorealistic IE with perspective and stereoscopic depth cues might not be enough to elicit a real-world performance in distance judgment tasks, nevertheless this type of environment minimizes the discrepancy between simulation and real-world when compared with non-photorealistic IEs.

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.