877 resultados para Information Visualization Environment


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Over the past few years, archaeology has experienced a rapid development in geophysical prospection and remote sensing techniques. At the same time, the focus of archaeological research has shifted to landscape evelopment and human interaction. To impart the results, new methods and techniques are necessary. Virtual globes such as Google Earth offer fascinating methods of giving interested amateurs the possibility to interactively explore ancient cities and landscapes. Thanks to the increasing usage of GIS in cultural heritage, the implementation of interactive three dimensional learning opportunities becomes less and less tedious, but the non-linear narrative story telling medium demands for a special adaption of the content. This paper summarizes the experience gained during the realization of the “Virtual Cilicia Project” and outlines the future potential of virtual globes in the field of cultural heritage.

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The arrangement of atoms at the surface of a solid accounts for many of its properties: Hardness, chemical activity, corrosion, etc. are dictated by the precise surface structure. Hence, finding it, has a broad range of technical and industrial applications. The ability to solve this problem opens the possibility of designing by computer materials with properties tailored to specific applications. Since the search space grows exponentially with the number of atoms, its solution cannot be achieved for arbitrarily large structures. Presently, a trial and error procedure is used: an expert proposes an structure as a candidate solution and tries a local optimization procedure on it. The solution relaxes to the local minimum in the attractor basin corresponding to the initial point, that might be the one corresponding to the global minimum or not. This procedure is very time consuming and, for reasonably sized surfaces, can take many iterations and much effort from the expert. Here we report on a visualization environment designed to steer this process in an attempt to solve bigger structures and reduce the time needed. The idea is to use an immersive environment to interact with the computation. It has immediate feedback to assess the quality of the proposed structure in order to let the expert explore the space of candidate solutions. The visualization environment is also able to communicate with the de facto local solver used for this problem. The user is then able to send trial structures to the local minimizer and track its progress as they approach the minimum. This allows for simultaneous testing of candidate structures. The system has also proved very useful as an educational tool for the field.

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A novel protein superfamily with over 600 members was discovered by iterative profile searches and analyzed with powerful bioinformatics and information visualization methods. Evidence exists that these proteins generate a radical species by reductive cleavage of S-adenosylmethionine (SAM) through an unusual Fe-S center. The superfamily (named here Radical SAM) provides evidence that radical-based catalysis is important in a number of previously well- studied but unresolved biochemical pathways and reflects an ancient conserved mechanistic approach to difficult chemistries. Radical SAM proteins catalyze diverse reactions, including unusual methylations, isomerization, sulfur insertion, ring formation, anaerobic oxidation and protein radical formation. They function in DNA precursor, vitamin, cofactor, antibiotic and herbicide biosynthesis and in biodegradation pathways. One eukaryotic member is interferon-inducible and is considered a candidate drug target for osteoporosis; another is observed to bind the neuronal Cdk5 activator protein. Five defining members not previously recognized as homologs are lysine 2,3-aminomutase, biotin synthase, lipoic acid synthase and the activating enzymes for pyruvate formate-lyase and anaerobic ribonucleotide reductase. Two functional predictions for unknown proteins are made based on integrating other data types such as motif, domain, operon and biochemical pathway into an organized view of similarity relationships.

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A guide to the European Union’s Environment Policy, with hyperlinks to sources of information within European Sources Online and on external websites

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In this paper, technology is described as involving processes whereby resources are utilised to satisfy human needs or to take advantage of opportunities, to develop practical solutions to problems. This study, set within one type of technology context, information technology, investigated how, through a one semester undergraduate university course, elements of technological processes were made explicit to students. While it was acknowledged in the development and implementation of this course that students needed to learn technical skills, technological skills and knowledge, including design, were seen as vital also, to enable students to think about information technology from a perspective that was not confined and limited to 'technology as hardware and software'. This paper describes how the course, set within a three year program of study, was aimed at helping students to develop their thinking and their knowledge about design processes in an explicit way. An interpretive research approach was used and data sources included a repertory grid 'survey'; student interviews; video recordings of classroom interactions, audio recordings of lectures, observations of classroom interactions made by researchers; and artefacts which included students' journals and portfolios. The development of students' knowledge about design practices is discussed and reflections upon student knowledge development in conjunction with their learning experiences are made. Implications for ensuring explicitness of design practice within information technology contexts are presented, and the need to identify what constitutes design knowledge is argued.

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Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. Most existing systems concentrate either on mining algorithms or on visualization techniques. Though visual methods developed in information visualization have been helpful, for improved understanding of a complex large high-dimensional dataset, there is a need for an effective projection of such a dataset onto a lower-dimension (2D or 3D) manifold. This paper introduces a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualization domain. The framework follows Shneiderman’s mantra to provide an effective user interface. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection methods, such as Generative Topographic Mapping (GTM) and Hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, billboarding, and user interaction facilities, to provide an integrated visual data mining framework. Results on a real life high-dimensional dataset from the chemoinformatics domain are also reported and discussed. Projection results of GTM are analytically compared with the projection results from other traditional projection methods, and it is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework.

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We introduce a flexible visual data mining framework which combines advanced projection algorithms from the machine learning domain and visual techniques developed in the information visualization domain. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection algorithms, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates and billboarding, to provide a visual data mining framework. Results on a real-life chemoinformatics dataset using GTM are promising and have been analytically compared with the results from the traditional projection methods. It is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework. Copyright 2006 ACM.

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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

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This year the School of Library, Documentation and Information is twenty years from its beginning as Unit Library.

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Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated - that is, user actions should be capable of affecting multiple visualizations when desired - use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

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Technological capabilities are built to support different types of collaboration, and this gives the justification to widely observe, how activity environments are influenced by technology. Technology as an enabler can be addressed from different perspectives, other than merely technological. Dynamic, evolving environment is at the same time interesting but also challenging. As a multinational collaboration environment, the maritime surveillance is an good example of time critical and evolving environment, where technological solutions enable new ways of collaboration. Justification for the inspiration to use maritime environment as the baseline for understanding the challenges in creating and maintaining adequate level of situational awareness, derives from the complexity of the collaboration and information sharing environment elements, needed to be taken into account, when analyzing criticalities related to decision making. Situational awareness is an important element supporting decision making, and challenges related to it can also be observed in the maritime environment. This dissertation describes the structures and factors involved in this complex setting, found from the case studies that should be taken into account when trying to understand, how these elements affect the activities. This dissertation focuses on the gray area that is between a life threatening situation and normal everyday activities. From the multinational experimentation series case studies, MNE5 and MNE6 it was possible to observe situations that were not life threatening for the participants themselves, but not also basic every day activities. These case studies provided a unique possibility to see situations, where gaining of situational awareness and decision making are challenged with time critical crisis situations. Unfortunately organizations do not normally take the benefit from the everyday work to prepare themselves for possible emerging crisis situations. This dissertation focuses on creating a conceptual model and a concept that supports organizations – also outside the maritime community – to improve their ability to support gaining of situational awareness from the individual training level, all the way to changes in organizational structures in aiming for better support for decision making from the individual level to the highest decision making level. Quick changes and unpredictability are reality in organizations and organizations do not have the possibility to control all the factors that affect their functioning. Since we cannot be prepared for everything, and predict every crisis, individual activities inside teams and as a part of organizations, need to be supported with guidance, tools and training in order to support acting in challenging situations. In fact the ideology of the conceptual model created, lies especially in the aim of not controlling everything in beforehand, but supporting organizations with concrete procedures to help individuals to react in different, unpredictable situations, instead of focusing on traditional risk prevention and management. Technological capabilities are not automatically solutions for functional challenges; this is why it is justified to broaden the problem area observation from the technological perspective. This dissertation demonstrates that it is possible to support collaboration in a multinational environment with technological solutions, but it requires the recognition of technological limitations and accepting the possible restrictions related to technological innovations. Technology should not be considered value per se, the value of technology should be defined according to the support of activities, including strategic and operational environment evaluation, identification of organizational elements, and taking into account also the social factors and their challenges. Then we are one step closer to providing technological solutions that support the actual activities by taking into account the variables of the activity environment in question. The multidisciplinary view to approach the information sharing and collaboration framework, is derived especially from the complexity of decision making and building of situational awareness, since they are not build or created in vacuity, but in the organizational framework by the people doing it with the technological capabilities, enabled by the organizational structures. Introduced case studies were related to maritime environment, but according to the research results, it is valid to argue, that based on the lessons learned it is possible to create and further develop conceptual model and to create a general concept to support a wider range of organizations in their attempt to gain better level of situational awareness (SA) and to support decision making. To proof the versatile usage of the developed concept, I have introduced the case study findings to the health care environment and reflected the identified elements from the trauma center to the created concept. The main contribution to complete this adventure is the presented situational awareness concept created in the respect to NATO concept structure. This has been done to tackle the challenge of collaboration by focusing on situational awareness in the information sharing context by providing a theoretical ground and understanding, of how these issues should be approached, and how these elements can be generalized and used to support activities in other environments as well. This dissertation research has been a several year evolving process reflecting and affecting presented case studies and this learning experience from the case studies has also affected the goals and research questions of this dissertation. This venture has been written from a retro perspective according to ideology of process modeling and design rationale to present to the reader how this entire journey took place and what where the critical milestones that affected the end result, conceptual model. Support in a challenging information sharing framework can be provided with the right type of combination of tools, procedures and individual effort. This dissertation will provide insights to those with a new approach to war technology for the organizations to gain a better level of awareness and to improve the capabilities in decision making. This dissertation will present, from the war technology starting point, a new approach and possibility for the organizations to create a better level of awareness and support for decision making with the right combination of tools, procedures and individual effort.

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Eye tracking has become a preponderant technique in the evaluation of user interaction and behaviour with study objects in defined contexts. Common eye tracking related data representation techniques offer valuable input regarding user interaction and eye gaze behaviour, namely through fixations and saccades measurement. However, these and other techniques may be insufficient for the representation of acquired data in specific studies, namely because of the complexity of the study object being analysed. This paper intends to contribute with a summary of data representation and information visualization techniques used in data analysis within different contexts (advertising, websites, television news and video games). Additionally, several methodological approaches are presented in this paper, which resulted from several studies developed and under development at CETAC.MEDIA - Communication Sciences and Technologies Research Centre. In the studies described, traditional data representation techniques were insufficient. As a result, new approaches were necessary and therefore, new forms of representing data, based on common techniques were developed with the objective of improving communication and information strategies. In each of these studies, a brief summary of the contribution to their respective area will be presented, as well as the data representation techniques used and some of the acquired results.

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As Terabyte datasets become the norm, the focus has shifted away from our ability to produce and store ever larger amounts of data, onto its utilization. It is becoming increasingly difficult to gain meaningful insights into the data produced. Also many forms of the data we are currently producing cannot easily fit into traditional visualization methods. This paper presents a new and novel visualization technique based on the concept of a Data Forest. Our Data Forest has been designed to be used with vir tual reality (VR) as its presentation method. VR is a natural medium for investigating large datasets. Our approach can easily be adapted to be used in a variety of different ways, from a stand alone single user environment to large multi-user collaborative environments. A test application is presented using multi-dimensional data to demonstrate the concepts involved.

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Recent advances in the control of molecular engineering architectures have allowed unprecedented ability of molecular recognition in biosensing, with a promising impact for clinical diagnosis and environment control. The availability of large amounts of data from electrical, optical, or electrochemical measurements requires, however, sophisticated data treatment in order to optimize sensing performance. In this study, we show how an information visualization system based on projections, referred to as Projection Explorer (PEx), can be used to achieve high performance for biosensors made with nanostructured films containing immobilized antigens. As a proof of concept, various visualizations were obtained with impedance spectroscopy data from an array of sensors whose electrical response could be specific toward a given antibody (analyte) owing to molecular recognition processes. In addition to discussing the distinct methods for projection and normalization of the data, we demonstrate that an excellent distinction can be made between real samples tested positive for Chagas disease and Leishmaniasis, which could not be achieved with conventional statistical methods. Such high performance probably arose from the possibility of treating the data in the whole frequency range. Through a systematic analysis, it was inferred that Sammon`s mapping with standardization to normalize the data gives the best results, where distinction could be made of blood serum samples containing 10(-7) mg/mL of the antibody. The method inherent in PEx and the procedures for analyzing the impedance data are entirely generic and can be extended to optimize any type of sensor or biosensor.