The Homeodomain Resource: sequences, structures, DNA binding sites and genomic information

The Homeodomain Resource is an annotated collection of non-redundant protein sequences, three-dimensional structures and genomic information for the homeodomain protein family. Release 3.0 contains 795 full-length homeodomain-containing sequences, 32 experimentally-derived structures and 143 homeo­box loci implicated in human genetic disorders. Entries are fully hyperlinked to facilitate easy retrieval of the original records from source databases. A simple search engine with a graphical user interface is provided to query the component databases and assemble customized data sets. A new feature for this release is the addition of DNA recognition sites for all human homeodomain proteins described in the literature. The Homeodomain Resource is freely available through the World Wide Web at http://genome.nhgri.nih.gov/homeodomain.

Metodologia para aquisição de sinal elétrico e tratamento de dados em reômetros servo controlados.

A ciência na qual se estuda a deformação de um fluido no qual é aplicada uma tensão de cisalhamento é conhecida como reologia e o equipamento utilizado para a realização dos ensaios é chamado de reômetro. Devido a impraticabilidade de uso de reômetros comerciais, diversos pesquisadores desenvolveram reômetros capazes de analisar suspensões de macropartículas, baseados nos mesmos princípios de funcionamento dos equipamentos já existentes. Em alguns casos, a medição do torque do motor é realizada pela aquisição da tensão, uma vez que esta é proporcional ao torque. Entretanto, para melhor compreensão do resultado e para evitar a possibilidade de conclusões precipitadas, vê-se necessária correta interpretação do sinal elétrico, precisando avaliar qual frequência do sinal é relevante para o ensaio e, também, qual a melhor taxa de amostragem. Além da aquisição, para que o ensaio reológico seja realizado com precisão, é indispensável ótimo controle da taxa ou tensão do motor e uma alternativa é a utilização de um servomotor e um servoconversor. No caso desse ser comercial é essencial saber configurá-lo. Para facilitar o usuário leigo, alguns pesquisadores desenvolveram softwares para controle do equipamento e análise dos dados. Assim, o presente trabalho tem como objetivo propor uma metodologia para compreender o sinal aquisitado de um reômetro servo controlado e desenvolvimento do software de análise para o tratamento dos dados obtidos a partir de ensaios reológicos. Verificou-se a melhor configuração do servocontrolador, a melhor taxa de amostragem, de no mínimo 20 amostras/segundo, e, também, desenvolveu-se um filtro digital passa-baixa do tipo FIR para remover a frequência indesejada. Além disso, foi desenvolvido um software utilizando uma rotina em Matlab e uma interface gráfica do usuário (Graphical User Interface - GUI), para o pós-processamento dos dados para auxiliar o usuário leigo no tratamento e interpretação do resultado, que se mostrou eficaz.

OrientatUA: Mobile Application to guide visual disabled people at the University of Alicante

This paper shows an iOS application to guide visual disabled people in the campus of the University of Alicante by voice indications. The user interface is adapted to visual disabled people, using a bigger visual typography and a bigger area for the tactile buttons. Moreover, the application provides voice indications when users touch any of the elements in the interface, telling them where they are and how they can reach destination.

An authoring tool for decision support systems in context questions of ecological knowledge

Decision support systems (DSS) support business or organizational decision-making activities, which require the access to information that is internally stored in databases or data warehouses, and externally in the Web accessed by Information Retrieval (IR) or Question Answering (QA) systems. Graphical interfaces to query these sources of information ease to constrain dynamically query formulation based on user selections, but they present a lack of flexibility in query formulation, since the expressivity power is reduced to the user interface design. Natural language interfaces (NLI) are expected as the optimal solution. However, especially for non-expert users, a real natural communication is the most difficult to realize effectively. In this paper, we propose an NLI that improves the interaction between the user and the DSS by means of referencing previous questions or their answers (i.e. anaphora such as the pronoun reference in “What traits are affected by them?”), or by eliding parts of the question (i.e. ellipsis such as “And to glume colour?” after the question “Tell me the QTLs related to awn colour in wheat”). Moreover, in order to overcome one of the main problems of NLIs about the difficulty to adapt an NLI to a new domain, our proposal is based on ontologies that are obtained semi-automatically from a framework that allows the integration of internal and external, structured and unstructured information. Therefore, our proposal can interface with databases, data warehouses, QA and IR systems. Because of the high NL ambiguity of the resolution process, our proposal is presented as an authoring tool that helps the user to query efficiently in natural language. Finally, our proposal is tested on a DSS case scenario about Biotechnology and Agriculture, whose knowledge base is the CEREALAB database as internal structured data, and the Web (e.g. PubMed) as external unstructured information.

Advances in camera trap data management tools: Towards collaborative development and integration with GIS

Camera traps have become a widely used technique for conducting biological inventories, generating a large number of database records of great interest. The main aim of this paper is to describe a new free and open source software (FOSS), developed to facilitate the management of camera-trapped data which originated from a protected Mediterranean area (SE Spain). In the last decade, some other useful alternatives have been proposed, but ours focuses especially on a collaborative undertaking and on the importance of spatial information underpinning common camera trap studies. This FOSS application, namely, “Camera Trap Manager” (CTM), has been designed to expedite the processing of pictures on the .NET platform. CTM has a very intuitive user interface, automatic extraction of some image metadata (date, time, moon phase, location, temperature, atmospheric pressure, among others), analytical (Geographical Information Systems, statistics, charts, among others), and reporting capabilities (ESRI Shapefiles, Microsoft Excel Spreadsheets, PDF reports, among others). Using this application, we have achieved a very simple management, fast analysis, and a significant reduction of costs. While we were able to classify an average of 55 pictures per hour manually, CTM has made it possible to process over 1000 photographs per hour, consequently retrieving a greater amount of data.

The use of computers in literature searching and related reference activities in libraries : papers presented at the 1975 Clinic on Library Applications of Data Processing, April 27-30, 1975 /

Includes bibliographical references.

Two NextGen Air Safety Tools: An ADS-B Equipped UAV and a Wake Turbulence Estimator

Thesis (Master's)--University of Washington, 2016-06

Using the R package Shiny to create web applications that facilitate quantitative gene expression analysis

Thesis (Master's)--University of Washington, 2016-06

The design and implementation of a repository for the management of spatial data integrity constraints

This paper reviews the key features of an environment to support domain users in spatial information system (SIS) development. It presents a full design and prototype implementation of a repository system for the storage and management of metadata, focusing on a subset of spatial data integrity constraint classes. The system is designed to support spatial system development and customization by users within the domain that the system will operate.

A case study in specification and implementation testing

Achieving consistency between a specification and its implementation is an important part of software development In previous work, we have presented a method and tool support for testing a formal specification using animation and then verifying an implementation of that specification. The method is based on a testgraph, which provides a partial model of the application under test. The testgraph is used in combination with an animator to generate test sequences for testing the formal specification. The same testgraph is used during testing to execute those same sequences on the implementation and to ensure that the implementation conforms to the specification. So far, the method and its tool support have been applied to software components that can be accessed through an application programmer interface (API). In this paper, we use an industrially-based case study to discuss the problems associated with applying the method to a software system with a graphical user interface (GUI). In particular, the lack of a standardised interface, as well as controllability and observability problems, make it difficult to automate the testing of the implementation. The method can still be applied, but the amount of testing that can be carried on the implementation is limited by the manual effort involved.

Architectural design in object-z

We present a process for introducing an object-oriented architecture into an abstract functional specification written in Object-Z. Since the design is derived from the specification, correctness concerns are addressed as pan of the design process. We base our approach on refactoring rules that apply to class structure, and use the rules to implement design patterns. As a motivating example, we introduce a user-interface design that follows the model-view-controller paradigm into an existing specification.

Using the Amazon metric to construct an image database based on what people do, not what they say

Current image database metadata schemas require users to adopt a specific text-based vocabulary. Text-based metadata is good for searching but not for browsing. Existing image-based search facilities, on the other hand, are highly specialised and so suffer similar problems. Wexelblat's semantic dimensional spatial visualisation schemas go some way towards addressing this problem by making both searching and browsing more accessible to the user in a single interface. But the question of how and what initial metadata to enter a database remains. Different people see different things in an image and will organise a collection in equally diverse ways. However, we can find some similarity across groups of users regardless of their reasoning. For example, a search on Amazon.com returns other products also, based on an averaging of how users navigate the database. In this paper, we report on applying this concept to a set of images for which we have visualised them using traditional methods and the Amazon.com method. We report on the findings of this comparative investigation in a case study setting involving a group of randomly selected participants. We conclude with the recommendation that in combination, the traditional and averaging methods would provide an enhancement to current database visualisation, searching, and browsing facilities.

Efficient Data Management with Applications to IoT

The Internet of Things (IoT) consists of a worldwide “network of networks,” composed by billions of interconnected heterogeneous devices denoted as things or “Smart Objects” (SOs). Significant research efforts have been dedicated to port the experience gained in the design of the Internet to the IoT, with the goal of maximizing interoperability, using the Internet Protocol (IP) and designing specific protocols like the Constrained Application Protocol (CoAP), which have been widely accepted as drivers for the effective evolution of the IoT. This first wave of standardization can be considered successfully concluded and we can assume that communication with and between SOs is no longer an issue. At this time, to favor the widespread adoption of the IoT, it is crucial to provide mechanisms that facilitate IoT data management and the development of services enabling a real interaction with things. Several reference IoT scenarios have real-time or predictable latency requirements, dealing with billions of device collecting and sending an enormous quantity of data. These features create a new need for architectures specifically designed to handle this scenario, hear denoted as “Big Stream”. In this thesis a new Big Stream Listener-based Graph architecture is proposed. Another important step, is to build more applications around the Web model, bringing about the Web of Things (WoT). As several IoT testbeds have been focused on evaluating lower-layer communication aspects, this thesis proposes a new WoT Testbed aiming at allowing developers to work with a high level of abstraction, without worrying about low-level details. Finally, an innovative SOs-driven User Interface (UI) generation paradigm for mobile applications in heterogeneous IoT networks is proposed, to simplify interactions between users and things.

Visual data mining: integrating machine learning with information visualization

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.

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.