A forma do tempo : a timeline interativa como meio de visualização temporal

This thesis takes a theoretical and practical approach to data visualization, focusing in particular on interactive timelines as a means to mapping historical/cultural narratives. It seeks to understand how timelines can efficiently communicate a historical narrative, enhancing the topic’s comprehension whilst relating it to the surrounding context. For this purpose, an interactive timeline on Design in Portugal from 1900 to present, was conceptualized and developed. The research adopted a descriptive methodology. The theoretical framework depicts the basic concepts, models and taxonomies associated to timelines, which derive from the main studies available on the matter. From this, a model for the analysis of three case studies – Idea Line (2002), The Path of Protest (2011) and British History Timeline (2006) – was proposed. The selection criteria shows that they refer to interactive timelines depicting a historical narrative, in addition to being as heterogeneous as possible with respect to the themes presented and conveyed purposes. The comparative analysis produced a set of thoughts, conclusions and principles, subsequently considered and applied in the development of the timeline presented. The results of this study point to the decisive role of visual setup of the time axis and user tasks in the interpretation of information. The effective implementation of the timeline Design in Portugal: from 1900 to present, contributes to the study of timelines as information devices with its own characteristics and capabilities, promotes associated research and theoretical systematization and, on a pragmatic note, helps creating the basis for the gathering, compilation and presentation of relevant information on design in Portugal, providing the academic and professional community with an effective tool for referring and learning

Power Law Behavior and Self-similarity in Modern Industrial Accidents

Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.

An Open Source BI Approach: Concept Proof Tracking Fleet

É possível assistir nos dias de hoje, a um processo tecnológico evolutivo acentuado por toda a parte do globo. No caso das empresas, quer as pequenas, médias ou de grandes dimensões, estão cada vez mais dependentes dos sistemas informatizados para realizar os seus processos de negócio, e consequentemente à geração de informação referente aos negócios e onde, muitas das vezes, os dados não têm qualquer relacionamento entre si. A maioria dos sistemas convencionais informáticos não são projetados para gerir e armazenar informações estratégicas, impossibilitando assim que esta sirva de apoio como recurso estratégico. Portanto, as decisões são tomadas com base na experiência dos administradores, quando poderiam serem baseadas em factos históricos armazenados pelos diversos sistemas. Genericamente, as organizações possuem muitos dados, mas na maioria dos casos extraem pouca informação, o que é um problema em termos de mercados competitivos. Como as organizações procuram evoluir e superar a concorrência nas tomadas de decisão, surge neste contexto o termo Business Intelligence(BI). A GisGeo Information Systems é uma empresa que desenvolve software baseado em SIG (sistemas de informação geográfica) recorrendo a uma filosofia de ferramentas open-source. O seu principal produto baseia-se na localização geográfica dos vários tipos de viaturas, na recolha de dados, e consequentemente a sua análise (quilómetros percorridos, duração de uma viagem entre dois pontos definidos, consumo de combustível, etc.). Neste âmbito surge o tema deste projeto que tem objetivo de dar uma perspetiva diferente aos dados existentes, cruzando os conceitos BI com o sistema implementado na empresa de acordo com a sua filosofia. Neste projeto são abordados alguns dos conceitos mais importantes adjacentes a BI como, por exemplo, modelo dimensional, data Warehouse, o processo ETL e OLAP, seguindo a metodologia de Ralph Kimball. São também estudadas algumas das principais ferramentas open-source existentes no mercado, assim como quais as suas vantagens/desvantagens relativamente entre elas. Em conclusão, é então apresentada a solução desenvolvida de acordo com os critérios enumerados pela empresa como prova de conceito da aplicabilidade da área Business Intelligence ao ramo de Sistemas de informação Geográfica (SIG), recorrendo a uma ferramenta open-source que suporte visualização dos dados através de dashboards.

Psychocentricity and participant profiles: implications for lexical processing among multilinguals

Lexical processing among bilinguals is often affected by complex patterns of individual experience. In this paper we discuss the psychocentric perspective on language representation and processing, which highlights the centrality of individual experience in psycholinguistic experimentation. We discuss applications to the investigation of lexical processing among multilinguals and explore the advantages of using high-density experiments with multilinguals. High density experiments are designed to co-index measures of lexical perception and production, as well as participant profiles. We discuss the challenges associated with the characterization of participant profiles and present a new data visualization technique, that we term Facial Profiles. This technique is based on Chernoff faces developed over 40 years ago. The Facial Profile technique seeks to overcome some of the challenges associated with the use of Chernoff faces, while maintaining the core insight that recoding multivariate data as facial features can engage the human face recognition system and thus enhance our ability to detect and interpret patterns within multivariate datasets. We demonstrate that Facial Profiles can code participant characteristics in lexical processing studies by recoding variables such as reading ability, speaking ability, and listening ability into iconically-related relative sizes of eye, mouth, and ear, respectively. The balance of ability in bilinguals can be captured by creating composite facial profiles or Janus Facial Profiles. We demonstrate the use of Facial Profiles and Janus Facial Profiles in the characterization of participant effects in the study of lexical perception and production.

MapFish. A WebGIS 2.0 Framework: toolkit to build rich client WebGIS

MapFish is an open-source development framework for building webmapping applications. MapFish is based on the OpenLayers API and the Geo extension of Ext library, and extends the Pylons general-purpose web development framework with geo-specific functionnalities. This presentation first describes what the MapFish development framework provides and how it can help developers implement rich web-mapping applications. It then demonstrates through real web-mapping realizations what can be achieved using MapFish : Geo Business Intelligence applications, 2D/3D data visualization, on/off line data edition, advanced vectorial print functionnalities, advanced administration suite to build WebGIS applications from scratch, etc. In particular, the web-mapping application for the UN Refugee Agency (UNHCR) and a Regional Spatial Data Infrastructure will be demonstrated

Clustering quality and topology preservation in fast learning SOMs

The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for data represented in multidimensional input spaces. In this paper, we describe Fast Learning SOM (FLSOM) which adopts a learning algorithm that improves the performance of the standard SOM with respect to the convergence time in the training phase. We show that FLSOM also improves the quality of the map by providing better clustering quality and topology preservation of multidimensional input data. Several tests have been carried out on different multidimensional datasets, which demonstrate better performances of the algorithm in comparison with the original SOM.

Simulated annealing technique for fast learning of SOM networks

The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for multidimensional input datasets. In this paper, we present an application of the simulated annealing procedure to the SOM learning algorithm with the aim to obtain a fast learning and better performances in terms of quantization error. The proposed learning algorithm is called Fast Learning Self-Organized Map, and it does not affect the easiness of the basic learning algorithm of the standard SOM. The proposed learning algorithm also improves the quality of resulting maps by providing better clustering quality and topology preservation of input multi-dimensional data. Several experiments are used to compare the proposed approach with the original algorithm and some of its modification and speed-up techniques.

Assessment of inter-examiner agreement and variability in the manual classification of auditory brainstem response

Abstract Background: The analysis of the Auditory Brainstem Response (ABR) is of fundamental importance to the investigation of the auditory system behaviour, though its interpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analysing the ABR, clinicians are often interested in the identification of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave latency) is a practical tool for the diagnosis of disorders affecting the auditory system. Significant differences in inter-examiner results may lead to completely distinct clinical interpretations of the state of the auditory system. In this context, the aim of this research was to evaluate the inter-examiner agreement and variability in the manual classification of ABR. Methods: A total of 160 ABR data samples were collected, for four different stimulus intensity (80dBHL, 60dBHL, 40dBHL and 20dBHL), from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). Four examiners with expertise in the manual classification of ABR components participated in the study. The Bland-Altman statistical method was employed for the assessment of inter-examiner agreement and variability. The mean, standard deviation and error for the bias, which is the difference between examiners’ annotations, were estimated for each pair of examiners. Scatter plots and histograms were employed for data visualization and analysis. Results: In most comparisons the differences between examiner’s annotations were below 0.1 ms, which is clinically acceptable. In four cases, it was found a large error and standard deviation (>0.1 ms) that indicate the presence of outliers and thus, discrepancies between examiners. Conclusions: Our results quantify the inter-examiner agreement and variability of the manual analysis of ABR data, and they also allows for the determination of different patterns of manual ABR analysis.

Gaussian processes autoencoder for dimensionality reduction

Learning low dimensional manifold from highly nonlinear data of high dimensionality has become increasingly important for discovering intrinsic representation that can be utilized for data visualization and preprocessing. The autoencoder is a powerful dimensionality reduction technique based on minimizing reconstruction error, and it has regained popularity because it has been efficiently used for greedy pretraining of deep neural networks. Compared to Neural Network (NN), the superiority of Gaussian Process (GP) has been shown in model inference, optimization and performance. GP has been successfully applied in nonlinear Dimensionality Reduction (DR) algorithms, such as Gaussian Process Latent Variable Model (GPLVM). In this paper we propose the Gaussian Processes Autoencoder Model (GPAM) for dimensionality reduction by extending the classic NN based autoencoder to GP based autoencoder. More interestingly, the novel model can also be viewed as back constrained GPLVM (BC-GPLVM) where the back constraint smooth function is represented by a GP. Experiments verify the performance of the newly proposed model.

Mobile systems for monitoring Parkinson's disease

A challenge for the clinical management of Parkinson's disease (PD) is the large within- and between-patient variability in symptom profiles as well as the emergence of motor complications which represent a significant source of disability in patients. This thesis deals with the development and evaluation of methods and systems for supporting the management of PD by using repeated measures, consisting of subjective assessments of symptoms and objective assessments of motor function through fine motor tests (spirography and tapping), collected by means of a telemetry touch screen device. One aim of the thesis was to develop methods for objective quantification and analysis of the severity of motor impairments being represented in spiral drawings and tapping results. This was accomplished by first quantifying the digitized movement data with time series analysis and then using them in data-driven modelling for automating the process of assessment of symptom severity. The objective measures were then analysed with respect to subjective assessments of motor conditions. Another aim was to develop a method for providing comparable information content as clinical rating scales by combining subjective and objective measures into composite scores, using time series analysis and data-driven methods. The scores represent six symptom dimensions and an overall test score for reflecting the global health condition of the patient. In addition, the thesis presents the development of a web-based system for providing a visual representation of symptoms over time allowing clinicians to remotely monitor the symptom profiles of their patients. The quality of the methods was assessed by reporting different metrics of validity, reliability and sensitivity to treatment interventions and natural PD progression over time. Results from two studies demonstrated that the methods developed for the fine motor tests had good metrics indicating that they are appropriate to quantitatively and objectively assess the severity of motor impairments of PD patients. The fine motor tests captured different symptoms; spiral drawing impairment and tapping accuracy related to dyskinesias (involuntary movements) whereas tapping speed related to bradykinesia (slowness of movements). A longitudinal data analysis indicated that the six symptom dimensions and the overall test score contained important elements of information of the clinical scales and can be used to measure effects of PD treatment interventions and disease progression. A usability evaluation of the web-based system showed that the information presented in the system was comparable to qualitative clinical observations and the system was recognized as a tool that will assist in the management of patients.

A web-based system for visualizing upper limb motor performance of Parkinson’s disease patients

Objective To design, develop and set up a web-based system for enabling graphical visualization of upper limb motor performance (ULMP) of Parkinson’s disease (PD) patients to clinicians. Background Sixty-five patients diagnosed with advanced PD have used a test battery, implemented in a touch-screen handheld computer, in their home environment settings over the course of a 3-year clinical study. The test items consisted of objective measures of ULMP through a set of upper limb motor tests (finger to tapping and spiral drawings). For the tapping tests, patients were asked to perform alternate tapping of two buttons as fast and accurate as possible, first using the right hand and then the left hand. The test duration was 20 seconds. For the spiral drawing test, patients traced a pre-drawn Archimedes spiral using the dominant hand, and the test was repeated 3 times per test occasion. In total, the study database consisted of symptom assessments during 10079 test occasions. Methods Visualization of ULMP The web-based system is used by two neurologists for assessing the performance of PD patients during motor tests collected over the course of the said study. The system employs animations, scatter plots and time series graphs to visualize the ULMP of patients to the neurologists. The performance during spiral tests is depicted by animating the three spiral drawings, allowing the neurologists to observe real-time accelerations or hesitations and sharp changes during the actual drawing process. The tapping performance is visualized by displaying different types of graphs. Information presented included distribution of taps over the two buttons, horizontal tap distance vs. time, vertical tap distance vs. time, and tapping reaction time over the test length. Assessments Different scales are utilized by the neurologists to assess the observed impairments. For the spiral drawing performance, the neurologists rated firstly the ‘impairment’ using a 0 (no impairment) – 10 (extremely severe) scale, secondly three kinematic properties: ‘drawing speed’, ‘irregularity’ and ‘hesitation’ using a 0 (normal) – 4 (extremely severe) scale, and thirdly the probable ‘cause’ for the said impairment using 3 choices including Tremor, Bradykinesia/Rigidity and Dyskinesia. For the tapping performance, a 0 (normal) – 4 (extremely severe) scale is used for first rating four tapping properties: ‘tapping speed’, ‘accuracy’, ‘fatigue’, ‘arrhythmia’, and then the ‘global tapping severity’ (GTS). To achieve a common basis for assessment, initially one neurologist (DN) performed preliminary ratings by browsing through the database to collect and rate at least 20 samples of each GTS level and at least 33 samples of each ‘cause’ category. These preliminary ratings were then observed by the two neurologists (DN and PG) to be used as templates for rating of tests afterwards. In another track, the system randomly selected one test occasion per patient and visualized its items, that is tapping and spiral drawings, to the two neurologists. Statistical methods Inter-rater agreements were assessed using weighted Kappa coefficient. The internal consistency of properties of tapping and spiral drawing tests were assessed using Cronbach’s α test. One-way ANOVA test followed by Tukey multiple comparisons test was used to test if mean scores of properties of tapping and spiral drawing tests were different among GTS and ‘cause’ categories, respectively. Results When rating tapping graphs, inter-rater agreements (Kappa) were as follows: GTS (0.61), ‘tapping speed’ (0.89), ‘accuracy’ (0.66), ‘fatigue’ (0.57) and ‘arrhythmia’ (0.33). The poor inter-rater agreement when assessing “arrhythmia” may be as a result of observation of different things in the graphs, among the two raters. When rating animated spirals, both raters had very good agreement when assessing severity of spiral drawings, that is, ‘impairment’ (0.85) and irregularity (0.72). However, there were poor agreements between the two raters when assessing ‘cause’ (0.38) and time-information properties like ‘drawing speed’ (0.25) and ‘hesitation’ (0.21). Tapping properties, that is ‘tapping speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’ had satisfactory internal consistency with a Cronbach’s α coefficient of 0.77. In general, the trends of mean scores of tapping properties worsened with increasing levels of GTS. The mean scores of the four properties were significantly different to each other, only at different levels. In contrast from tapping properties, kinematic properties of spirals, that is ‘drawing speed’, ‘irregularity’ and ‘hesitation’ had a questionable consistency among them with a coefficient of 0.66. Bradykinetic spirals were associated with more impaired speed (mean = 83.7 % worse, P < 0.001) and hesitation (mean = 77.8% worse, P < 0.001), compared to dyskinetic spirals. Both these ‘cause’ categories had similar mean scores of ‘impairment’ and ‘irregularity’. Conclusions In contrast from current approaches used in clinical setting for the assessment of PD symptoms, this system enables clinicians to animate easily and realistically the ULMP of patients who at the same time are at their homes. Dynamic access of visualized motor tests may also be useful when observing and evaluating therapy-related complications such as under- and over-medications. In future, we foresee to utilize these manual ratings for developing and validating computer methods for automating the process of assessing ULMP of PD patients.

Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease

Objective: To develop a method for objective quantification of PD motor symptoms related to Off episodes and peak dose dyskinesias, using spiral data gathered by using a touch screen telemetry device. The aim was to objectively characterize predominant motor phenotypes (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Background: A retrospective analysis was conducted on recordings from 65 patients with advanced idiopathic PD from nine different clinics in Sweden, recruited from January 2006 until August 2010. In addition to the patient group, 10 healthy elderly subjects were recruited. Upper limb movement data were collected using a touch screen telemetry device from home environments of the subjects. Measurements with the device were performed four times per day during week-long test periods. On each test occasion, the subjects were asked to trace pre-drawn Archimedean spirals, using the dominant hand. The pre-drawn spiral was shown on the screen of the device. The spiral test was repeated three times per test occasion and they were instructed to complete it within 10 seconds. The device had a sampling rate of 10Hz and measured both position and time-stamps (in milliseconds) of the pen tip. Methods: Four independent raters (FB, DH, AJ and DN) used a web interface that animated the spiral drawings and allowed them to observe different kinematic features during the drawing process and to rate task performance. Initially, a number of kinematic features were assessed including ‘impairment’, ‘speed’, ‘irregularity’ and ‘hesitation’ followed by marking the predominant motor phenotype on a 3-category scale: tremor, bradykinesia and/or choreatic dyskinesia. There were only 2 test occasions for which all the four raters either classified them as tremor or could not identify the motor phenotype. Therefore, the two main motor phenotype categories were bradykinesia and dyskinesia. ‘Impairment’ was rated on a scale from 0 (no impairment) to 10 (extremely severe) whereas ‘speed’, ‘irregularity’ and ‘hesitation’ were rated on a scale from 0 (normal) to 4 (extremely severe). The proposed data-driven method consisted of the following steps. Initially, 28 spatiotemporal features were extracted from the time series signals before being presented to a Multilayer Perceptron (MLP) classifier. The features were based on different kinematic quantities of spirals including radius, angle, speed and velocity with the aim of measuring the severity of involuntary symptoms and discriminate between PD-specific (bradykinesia) and/or treatment-induced symptoms (dyskinesia). A Principal Component Analysis was applied on the features to reduce their dimensions where 4 relevant principal components (PCs) were retained and used as inputs to the MLP classifier. Finally, the MLP classifier mapped these components to the corresponding visually assessed motor phenotype scores for automating the process of scoring the bradykinesia and dyskinesia in PD patients whilst they draw spirals using the touch screen device. For motor phenotype (bradykinesia vs. dyskinesia) classification, the stratified 10-fold cross validation technique was employed. Results: There were good agreements between the four raters when rating the individual kinematic features with intra-class correlation coefficient (ICC) of 0.88 for ‘impairment’, 0.74 for ‘speed’, 0.70 for ‘irregularity’, and moderate agreements when rating ‘hesitation’ with an ICC of 0.49. When assessing the two main motor phenotype categories (bradykinesia or dyskinesia) in animated spirals the agreements between the four raters ranged from fair to moderate. There were good correlations between mean ratings of the four raters on individual kinematic features and computed scores. The MLP classifier classified the motor phenotype that is bradykinesia or dyskinesia with an accuracy of 85% in relation to visual classifications of the four movement disorder specialists. The test-retest reliability of the four PCs across the three spiral test trials was good with Cronbach’s Alpha coefficients of 0.80, 0.82, 0.54 and 0.49, respectively. These results indicate that the computed scores are stable and consistent over time. Significant differences were found between the two groups (patients and healthy elderly subjects) in all the PCs, except for the PC3. Conclusions: The proposed method automatically assessed the severity of unwanted symptoms and could reasonably well discriminate between PD-specific and/or treatment-induced motor symptoms, in relation to visual assessments of movement disorder specialists. The objective assessments could provide a time-effect summary score that could be useful for improving decision-making during symptom evaluation of individualized treatment when the goal is to maximize functional On time for patients while minimizing their Off episodes and troublesome dyskinesias.

Using Web 2.0 applications to deliver innovative services on the internet

The emergence of Web 2.0 has brought about new Web applications being developed. Represented chiefly by Web applications such as YouTube, MySpace, blogs and Google applications, these community-based technologies are changing the way we use the Internet. One interesting result of these innovations is the extensibility of these applications. For example, YouTubepsilas content can be displayed on other Websites and hence, are popularly dasiaextendedpsila to be displayed on individual blogs and other organization Websites. In this paper, we discussed two applications that were a result of extending Google Earth and Google Maps. These two applications illustrate how new solutions can be quickly built from these extensible applications thus suggesting the future of application development, one that is built upon applications rather than object-oriented components.

A hybrid intelligent system and its application to fault detection and diagnosis

This paper proposes a hybrid system that integrates the SOM (Self Organizing Map) neural network, the kMER (kernel-based Maximum Entropy learning Rule) algorithm and the Probabilistic Neural Network (PNN) for data visualization and classification. The rationales of this hybrid SOM-kMER-PNN model are explained, and the applicability of the proposed model is demonstrated using two benchmark data sets and a real-world application to fault detection and diagnosis. The outcomes show that the hybrid system is able to achieve comparable classification rates when compared to those from a number of existing classifiers and, at the same time, to produce meaningful visualization of the data sets.

An Intelligent Human-Computer Interaction System for Decision Support

This paper proposes a novel architecture for
developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be
incorporated into a computerized system and, at the same time, to
preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking
process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first
employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed
approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.