935 resultados para User Interface (UI) Software-as-a-Service


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This thesis introduces the L1 Adaptive Control Toolbox, a set of tools implemented in Matlab that aid in the design process of an L1 adaptive controller and enable the user to construct simulations of the closed-loop system to verify its performance. Following a brief review of the existing theory on L1 adaptive controllers, the interface of the toolbox is presented, including a description of the functions accessible to the user. Two novel algorithms for determining the required sampling period of a piecewise constant adaptive law are presented and their implementation in the toolbox is discussed. The detailed description of the structure of the toolbox is provided as well as a discussion of the implementation of the creation of simulations. Finally, the graphical user interface is presented and described in detail, including the graphical design tools provided for the development of the filter C(s). The thesis closes with suggestions for further improvement of the toolbox.

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Relatório de Estágio para a obtenção do grau de Mestre na área de Educação e Comunicação Multimédia

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A collaboration between dot.rural at the University of Aberdeen and the iSchool at Northumbria University, POWkist is a pilot-study exploring potential usages of currently available linked datasets within the cultural heritage domain. Many privately-held family history collections (shoebox archives) remain vulnerable unless a sustainable, affordable and accessible model of citizen-archivist digital preservation can be offered. Citizen-historians have used the web as a platform to preserve cultural heritage, however with no accessible or sustainable model these digital footprints have been ad hoc and rarely connected to broader historical research. Similarly, current approaches to connecting material on the web by exploiting linked datasets do not take into account the data characteristics of the cultural heritage domain. Funded by Semantic Media, the POWKist project is investigating how best to capture, curate, connect and present the contents of citizen-historians’ shoebox archives in an accessible and sustainable online collection. Using the Curios platform - an open-source digital archive - we have digitised a collection relating to a prisoner of war during WWII (1939-1945). Following a series of user group workshops, POWkist is now connecting these ‘made digital’ items with the broader web using a semantic technology model and identifying appropriate linked datasets of relevant content such as DBPedia (an archived linked dataset of Wikipedia) and Ordnance Survey Open Data. We are analysing the characteristics of cultural heritage linked datasets, so that these materials are better visualised, contextualised and presented in an attractive and comprehensive user interface. Our paper will consider the issues we have identified, the solutions we are developing and include a demonstration of our work-in-progress.

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The traditional process of filling the medicine trays and dispensing the medicines to the patients in the hospitals is manually done by reading the printed paper medicinechart. This process can be very strenuous and error-prone, given the number of sub-tasksinvolved in the entire workflow and the dynamic nature of the work environment.Therefore, efforts are being made to digitalise the medication dispensation process byintroducing a mobile application called Smart Dosing application. The introduction ofthe Smart Dosing application into hospital workflow raises security concerns and callsfor security requirement analysis. This thesis is written as a part of the smart medication management project at EmbeddedSystems Laboratory, A˚bo Akademi University. The project aims at digitising the medicine dispensation process by integrating information from various health systems, and making them available through the Smart Dosing application. This application is intended to be used on a tablet computer which will be incorporated on the medicine tray. The smart medication management system include the medicine tray, the tablet device, and the medicine cups with the cup holders. Introducing the Smart Dosing application should not interfere with the existing process carried out by the nurses, and it should result in minimum modifications to the tray design and the workflow. The re-designing of the tray would include integrating the device running the application into the tray in a manner that the users find it convenient and make less errors while using it. The main objective of this thesis is to enhance the security of the hospital medicine dispensation process by ensuring the security of the Smart Dosing application at various levels. The methods used for writing this thesis was to analyse how the tray design, and the application user interface design can help prevent errors and what secure technology choices have to be made before starting the development of the next prototype of the Smart Dosing application. The thesis first understands the context of the use of the application, the end-users and their needs, and the errors made in everyday medication dispensation workflow by continuous discussions with the nursing researchers. The thesis then gains insight to the vulnerabilities, threats and risks of using mobile application in hospital medication dispensation process. The resulting list of security requirements was made by analysing the previously built prototype of the Smart Dosing application, continuous interactive discussions with the nursing researchers, and an exhaustive state-of-the-art study on security risks of using mobile applications in hospital context. The thesis also uses Octave Allegro method to make the readers understand the likelihood and impact of threats, and what steps should be taken to prevent or fix them. The security requirements obtained, as a result, are a starting point for the developers of the next iteration of the prototype for the Smart Dosing application.

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Background: Research suggests that forensic mental health services and staff can play an important role in the recognition and intervention with attachment-related behaviours to promote engagement and recovery. There is a lack of literature exploring whether the attachment needs of forensic service-users are recognised and, associations between attachment style and factors predictive of recovery. Aims: This study aimed to examine the extent to which service-users and keyworkers agree about service-users’ attachment and to identify whether attachment was associated with service attachment, working alliance, ward climate and recovery. Methods: Twenty-two service-users from low and medium secure forensic services, completed questionnaire measures of their attachment style, service attachment, working alliance, ward climate and experiences of recovery. Nineteen keyworkers completed measures of the service-users attachment style and working alliance. Results: There was strong agreement between service-users and staff for attachment anxiety (ICC=0.71) but poor agreement for attachment avoidance (ICC=0.39). Service attachment was associated with more positive perceptions of staff support (r=0.49) and avoidant attachment was associated with lower ratings of recovery (r=-0.51). Correlations between attachment style and service attachment, working alliance and ward climate were small and non-significant. Conclusions: A focus on staff training to support recognition of the nature and impact of avoidant attachment styles is indicated. The findings suggest that interventions to enhance staff - service-user relationships may be important for service attachment and indeed promotion of a recovery focused orientation amongst service-users high in avoidant attachment may improve wellbeing and outcomes.

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Los sistemas fotovoltaicos son fuentes emergentes de energías renovables que generan electricidad a partir de la radiación solar. El monitoreo de los sistemas fotovoltaicos aislados proporciona información necesaria que permite a sus propietarios mantener, operar y controlar estos sistemas, reduciendo los costes de operación y evitando indeseadas interrupciones en el suministro eléctrico de zonas aisladas. En este artículo, se propone el desarrollo de una plataforma para el monitoreo de sistemas fotovoltaicos aislados en el Ecuador con el objetivo fundamental de desarrollar una solución escalable, basada en el uso de software libre, en el empleo de sensores de bajo consumo y en el desarrollo de servicios web en la modalidad ‘Software as a Service’ (SaaS) para el procesamiento, gestión y publicación de información registrada y la creación de un innovador centro de control solar fotovoltaico en el Ecuador.

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Automation technologies are widely acclaimed to have the potential to significantly reduce energy consumption and energy-related costs in buildings. However, despite the abundance of commercially available technologies, automation in domestic environments keep on meeting commercial failures. The main reason for this is the development process that is used to build the automation applications, which tend to focus more on technical aspects rather than on the needs and limitations of the users. An instance of this problem is the complex and poorly designed home automation front-ends that deter customers from investing in a home automation product. On the other hand, developing a usable and interactive interface is a complicated task for developers due to the multidisciplinary challenges that need to be identified and solved. In this context, the current research work investigates the different design problems associated with developing a home automation interface as well as the existing design solutions that are applied to these problems. The Qualitative Data Analysis approach was used for collecting data from research papers and the open coding process was used to cluster the findings. From the analysis of the data collected, requirements for designing the interface were derived. A home energy management functionality for a Web-based home automation front-end was developed as a proof-of-concept and a user evaluation was used to assess the usability of the interface. The results of the evaluation showed that this holistic approach to designing interfaces improved its usability which increases the chances of its commercial success.

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Annotation Pro - a description of techniques, methods implemented in the tool, as well as the list of all built in functionalities and features of the user interface, and usage tips.

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Sequences of timestamped events are currently being generated across nearly every domain of data analytics, from e-commerce web logging to electronic health records used by doctors and medical researchers. Every day, this data type is reviewed by humans who apply statistical tests, hoping to learn everything they can about how these processes work, why they break, and how they can be improved upon. To further uncover how these processes work the way they do, researchers often compare two groups, or cohorts, of event sequences to find the differences and similarities between outcomes and processes. With temporal event sequence data, this task is complex because of the variety of ways single events and sequences of events can differ between the two cohorts of records: the structure of the event sequences (e.g., event order, co-occurring events, or frequencies of events), the attributes about the events and records (e.g., gender of a patient), or metrics about the timestamps themselves (e.g., duration of an event). Running statistical tests to cover all these cases and determining which results are significant becomes cumbersome. Current visual analytics tools for comparing groups of event sequences emphasize a purely statistical or purely visual approach for comparison. Visual analytics tools leverage humans' ability to easily see patterns and anomalies that they were not expecting, but is limited by uncertainty in findings. Statistical tools emphasize finding significant differences in the data, but often requires researchers have a concrete question and doesn't facilitate more general exploration of the data. Combining visual analytics tools with statistical methods leverages the benefits of both approaches for quicker and easier insight discovery. Integrating statistics into a visualization tool presents many challenges on the frontend (e.g., displaying the results of many different metrics concisely) and in the backend (e.g., scalability challenges with running various metrics on multi-dimensional data at once). I begin by exploring the problem of comparing cohorts of event sequences and understanding the questions that analysts commonly ask in this task. From there, I demonstrate that combining automated statistics with an interactive user interface amplifies the benefits of both types of tools, thereby enabling analysts to conduct quicker and easier data exploration, hypothesis generation, and insight discovery. The direct contributions of this dissertation are: (1) a taxonomy of metrics for comparing cohorts of temporal event sequences, (2) a statistical framework for exploratory data analysis with a method I refer to as high-volume hypothesis testing (HVHT), (3) a family of visualizations and guidelines for interaction techniques that are useful for understanding and parsing the results, and (4) a user study, five long-term case studies, and five short-term case studies which demonstrate the utility and impact of these methods in various domains: four in the medical domain, one in web log analysis, two in education, and one each in social networks, sports analytics, and security. My dissertation contributes an understanding of how cohorts of temporal event sequences are commonly compared and the difficulties associated with applying and parsing the results of these metrics. It also contributes a set of visualizations, algorithms, and design guidelines for balancing automated statistics with user-driven analysis to guide users to significant, distinguishing features between cohorts. This work opens avenues for future research in comparing two or more groups of temporal event sequences, opening traditional machine learning and data mining techniques to user interaction, and extending the principles found in this dissertation to data types beyond temporal event sequences.

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This article will address the main technical aspects that facilitate the use and growth of computer technology in the cloud, which go hand in hand with the emergence of more and better services on the Internet and technological development of the broadband. Finally, we know what is the impact that the cloud computing technologies in the automation of information units.

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The petrochemical industry has as objective obtain, from crude oil, some products with a higher commercial value and a bigger industrial utility for energy purposes. These industrial processes are complex, commonly operating with large production volume and in restricted operation conditions. The operation control in optimized and stable conditions is important to keep obtained products quality and the industrial plant safety. Currently, industrial network has been attained evidence when there is a need to make the process control in a distributed way. The Foundation Fieldbus protocol for industrial network, for its interoperability feature and its user interface organized in simple configuration blocks, has great notoriety among industrial automation network group. This present work puts together some benefits brought by industrial network technology to petrochemical industrial processes inherent complexity. For this, a dynamic reconfiguration system for intelligent strategies (artificial neural networks, for example) based on the protocol user application layer is proposed which might allow different applications use in a particular process, without operators intervention and with necessary guarantees for the proper plant functioning

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In this work, spoke about the importance of image compression for the industry, it is known that processing and image storage is always a challenge in petrobrás to optimize the storage time and store a maximum number of images and data. We present an interactive system for processing and storing images in the wavelet domain and an interface for digital image processing. The proposal is based on the Peano function and wavelet transform in 1D. The storage system aims to optimize the computational space, both for storage and for transmission of images. Being necessary to the application of the Peano function to linearize the images and the 1D wavelet transform to decompose it. These applications allow you to extract relevant information for the storage of an image with a lower computational cost and with a very small margin of error when comparing the images, original and processed, ie, there is little loss of quality when applying the processing system presented . The results obtained from the information extracted from the images are displayed in a graphical interface. It is through the graphical user interface that the user uses the files to view and analyze the results of the programs directly on the computer screen without the worry of dealing with the source code. The graphical user interface, programs for image processing via Peano Function and Wavelet Transform 1D, were developed in Java language, allowing a direct exchange of information between them and the user

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The International Space Station (ISS) requires a substantial amount of potable water for use by the crew. The economic and logistic limitations of transporting the vast amount of water required onboard the ISS necessitate onboard recovery and reuse of the aqueous waste streams. Various treatment technologies are employed within the ISS water processor to render the waste water potable, including filtration, ion exchange, adsorption, and catalytic wet oxidation. The ion exchange resins and adsorption media are combined in multifiltration beds for removal of ionic and organic compounds. A mathematical model (MFBMODEL™) designed to predict the performance of a multifiltration (MF) bed was developed. MFBMODEL consists of ion exchange models for describing the behavior of the different resin types in a MF bed (e.g., mixed bed, strong acid cation, strong base anion, and weak base anion exchange resins) and an adsorption model capable of predicting the performance of the adsorbents in a MF bed. Multicomponent ion exchange ii equilibrium models that incorporate the water formation reaction, electroneutrality condition, and degree of ionization of weak acids and bases for mixed bed, strong acid cation, strong base anion, and weak base anion exchange resins were developed and verified. The equilibrium models developed use a tanks-inseries approach that allows for consideration of variable influent concentrations. The adsorption modeling approach was developed in related studies and application within the MFBMODEL framework was demonstrated in the Appendix to this study. MFBMODEL consists of a graphical user interface programmed in Visual Basic and Fortran computational routines. This dissertation shows MF bed modeling results in which the model is verified for a surrogate of the ISS waste shower and handwash stream. In addition, a multicomponent ion exchange model that incorporates mass transfer effects was developed, which is capable of describing the performance of strong acid cation (SAC) and strong base anion (SBA) exchange resins, but not including reaction effects. This dissertation presents results showing the mass transfer model's capability to predict the performance of binary and multicomponent column data for SAC and SBA exchange resins. The ion exchange equilibrium and mass transfer models developed in this study are also applicable to terrestrial water treatment systems. They could be applied for removal of cations and anions from groundwater (e.g., hardness, nitrate, perchlorate) and from industrial process waters (e.g. boiler water, ultrapure water in the semiconductor industry).

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In this thesis, a machine learning approach was used to develop a predictive model for residual methanol concentration in industrial formalin produced at the Akzo Nobel factory in Kristinehamn, Sweden. The MATLABTM computational environment supplemented with the Statistics and Machine LearningTM toolbox from the MathWorks were used to test various machine learning algorithms on the formalin production data from Akzo Nobel. As a result, the Gaussian Process Regression algorithm was found to provide the best results and was used to create the predictive model. The model was compiled to a stand-alone application with a graphical user interface using the MATLAB CompilerTM.

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To distinguish the components of NMR signals from hydrated materials and to monitor their evolution after the addition of water to the powders, during the first two days of hydration. To implement the 3 Tau Model in a MATLAB script, called 3TM, provided with a Graphical User Interface (GUI), to easily use the 3 Tau Model with NMRD profiles. The 3 Tau Model, developed a few years ago is used for interpreting the dispersion (NMRD profiles, dependence on the Larmor frequency) of the longitudinal relaxation times, for liquids confined in porous media. This model describes the molecular dynamics of confined molecules by introducing three characteristic correlation times and additional outputs.