ALFRED: an allele frequency database for diverse populations and DNA polymorphisms—an update

ALFRED (the ALelle FREquency Database) is designed to store and disseminate frequencies of alleles at human polymorphic sites for multiple populations, primarily for the population genetics and molecular anthropology communities. Currently ALFRED has information on over 180 polymorphic sites for more than 70 populations. Since our initial release of the database we have focussed on increasing the quantity and quality of data, making reciprocal links between ALFRED and other related databases, and providing useful tools to make the data more comprehensible to the end user. ALFRED is accessible from the Kidd Lab home page (http://info.med.yale.edu/genetics/kkidd/) or from ALFRED directly (http://alfred.med.yale.edu/alfred/index.asp).

The rise and fall of the medical mediated searcher

The relationship between the development of mediated online literature searching and the recruitment of medical librarians to fill positions as online searchers was investigated. The history of database searching by medical librarians was outlined and a content analysis of thirty-five years of job advertisements in MLA News from 1961 through 1996 was summarized. Advertisements for online searchers were examined to test the hypothesis that the growth of mediated online searching was reflected in the recruitment of librarians to fill positions as mediated online searchers in medical libraries. The advent of end-user searching was also traced to determine how this trend affected the demand for mediated online searching and job availability of online searchers. Job advertisements were analyzed to determine what skills were in demand as end-user searching replaced mediated online searching as the norm in medical libraries. Finally, the trend away from mediated online searching to support of other library services was placed in the context of new roles for medical librarians.

Coleta de dados pessoais e paradoxo da privacidade: um estudo entre usuários de aplicativos móveis

Aplicativos móveis de celulares que coletam dados pessoais estão cada vez mais presentes na rotina do cidadão comum. Associado a estas aplicações, há polêmicas sobre riscos de segurança e de invasão de privacidade, que podem se tornar entraves para aceitação destes sistemas por parte dos usuários. Por outro lado, discute-se o Paradoxo da Privacidade, em que os consumidores revelam mais informações pessoais voluntariamente, apesar de declarar que reconhecem os riscos. Há pouco consenso, nas pesquisas acadêmicas, sobre os motivos deste paradoxo ou mesmo se este fenômeno realmente existe. O objetivo desta pesquisa é analisar como a coleta de informações sensíveis influencia a escolha de aplicativos móveis. A metodologia é o estudo de aplicativos disponíveis em lojas virtuais para celulares através de técnicas qualitativas e quantitativas. Os resultados indicam que os produtos mais populares da loja são aqueles que coletam mais dados pessoais. Porém, em uma análise minuciosa, observa-se que aqueles mais buscados também pertencem a empresas de boa reputação e possuem mais funcionalidades, que exigem maior acesso aos dados privativos do celular. Na survey realizada em seguida, nota-se que os consumidores reduzem o uso dos aplicativos quando consideram que o produto coleta dados excessivamente, mas a estratégia para proteger essas informações pode variar. No grupo dos usuários que usam aplicativos que coletam dados excessivamente, conclui-se que o motivo primordial para compartilhar informações pessoais são as funcionalidades. Além disso, esta pesquisa confirma que comparar os dados solicitados pelos aplicativos com a expectativa inicial do consumidor é um constructo complementar para avaliar preocupações com privacidade, ao invés de simplesmente analisar a quantidade de informações coletadas. O processo desta pesquisa também ilustrou que, dependendo do método utilizado para análise, é possível chegar a resultados opostos sobre a ocorrência ou não do paradoxo. Isso pode dar indícios sobre os motivos da falta de consenso sobre o assunto

Radar interferometry techniques for the study of ground subsidence phenomena: a review of practical issues through cases in Spain

Subsidence related to multiple natural and human-induced processes affects an increasing number of areas worldwide. Although this phenomenon may involve surface deformation with 3D displacement components, negative vertical movement, either progressive or episodic, tends to dominate. Over the last decades, differential SAR interferometry (DInSAR) has become a very useful remote sensing tool for accurately measuring the spatial and temporal evolution of surface displacements over broad areas. This work discusses the main advantages and limitations of addressing active subsidence phenomena by means of DInSAR techniques from an end-user point of view. Special attention is paid to the spatial and temporal resolution, the precision of the measurements, and the usefulness of the data. The presented analysis is focused on DInSAR results exploitation of various ground subsidence phenomena (groundwater withdrawal, soil compaction, mining subsidence, evaporite dissolution subsidence, and volcanic deformation) with different displacement patterns in a selection of subsidence areas in Spain. Finally, a cost comparative study is performed for the different techniques applied.

Characterization of rock slopes through slope mass rating using 3D point clouds

Rock mass classification systems are widely used tools for assessing the stability of rock slopes. Their calculation requires the prior quantification of several parameters during conventional fieldwork campaigns, such as the orientation of the discontinuity sets, the main properties of the existing discontinuities and the geo-mechanical characterization of the intact rock mass, which can be time-consuming and an often risky task. Conversely, the use of relatively new remote sensing data for modelling the rock mass surface by means of 3D point clouds is changing the current investigation strategies in different rock slope engineering applications. In this paper, the main practical issues affecting the application of Slope Mass Rating (SMR) for the characterization of rock slopes from 3D point clouds are reviewed, using three case studies from an end-user point of view. To this end, the SMR adjustment factors, which were calculated from different sources of information and processes, using the different softwares, are compared with those calculated using conventional fieldwork data. In the presented analysis, special attention is paid to the differences between the SMR indexes derived from the 3D point cloud and conventional field work approaches, the main factors that determine the quality of the data and some recognized practical issues. Finally, the reliability of Slope Mass Rating for the characterization of rocky slopes is highlighted.

Dynamic multi-resolution spatial object derivation for mobile and WWW applications

Online geographic information systems provide the means to extract a subset of desired spatial information from a larger remote repository. Data retrieved representing real-world geographic phenomena are then manipulated to suit the specific needs of an end-user. Often this extraction requires the derivation of representations of objects specific to a particular resolution or scale from a single original stored version. Currently standard spatial data handling techniques cannot support the multi-resolution representation of such features in a database. In this paper a methodology to store and retrieve versions of spatial objects at, different resolutions with respect to scale using standard database primitives and SQL is presented. The technique involves heavy fragmentation of spatial features that allows dynamic simplification into scale-specific object representations customised to the display resolution of the end-user's device. Experimental results comparing the new approach to traditional R-Tree indexing and external object simplification reveal the former performs notably better for mobile and WWW applications where client-side resources are limited and retrieved data loads are kept relatively small.

The impact of organizational culture and reshaping capabilities on change implementation success: The mediating role of readiness for change

It was hypothesized that employees' perceptions of an organizational culture strong in human relations values and open systems values would be associated with heightened levels of readiness for change which, in turn, would be predictive of change implementation success. Similarly, it was predicted that reshaping capabilities would lead to change implementation success, via its effects on employees' perceptions of readiness for change. Using a temporal research design, these propositions were tested for 67 employees working in a state government department who were about to undergo the implementation of a new end-user computing system in their workplace. Change implementation success was operationalized as user satisfaction and system usage. There was evidence to suggest that employees who perceived strong human relations values in their division at Time 1 reported higher levels of readiness for change at pre-implementation which, in turn, predicted system usage at Time 2. In addition, readiness for change mediated the relationship between reshaping capabilities and system usage. Analyses also revealed that pre-implementation levels of readiness for change exerted a positive main effect on employees' satisfaction with the system's accuracy, user friendliness, and formatting functions at post-implementation. These findings are discussed in terms of their theoretical contribution to the readiness for change literature, and in relation to the practical importance of developing positive change attitudes among employees if change initiatives are to be successful.

Selecting optimal instantiations of data models - Theory and validation of an ex ante approach

The schema of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. Obtaining quickly the appropriate data increases the likelihood that an organization will make good decisions and respond adeptly to challenges. This research presents and validates a methodology for evaluating, ex ante, the relative desirability of alternative instantiations of a model of data. In contrast to prior research, each instantiation is based on a different formal theory. This research theorizes that the instantiation that yields the lowest weighted average query complexity for a representative sample of information requests is the most desirable instantiation for end-user queries. The theory was validated by an experiment that compared end-user performance using an instantiation of a data structure based on the relational model of data with performance using the corresponding instantiation of the data structure based on the object-relational model of data. Complexity was measured using three different Halstead metrics: program length, difficulty, and effort. For a representative sample of queries, the average complexity using each instantiation was calculated. As theorized, end users querying the instantiation with the lower average complexity made fewer semantic errors, i.e., were more effective at composing queries. (c) 2005 Elsevier B.V. All rights reserved.

Toward a business-to-business channel incentives classification scheme

A recent focus on intermediary compensation underscores the need to organize the many complex incentives used by channel practitioners. Employing a grounded theory methodology, a channel incentives classification scheme is induced from 170 unique channel incentives used in 59 high technology suppliers’ channel programs. The incentives are organized into 16 subcategories and 5 major categories: Credible Channel Policies, Market Development Support, Supplemental Contact, High-Powered Incentives, and End-User Encouragements. Each incentive subcategory is discussed as a means of controlling reseller behaviors. Also, the conditions that give rise to the implementation of incentives are investigated through four testable research propositions.

Probabilistic uncertainty in an interoperable framework

This thesis provides an interoperable language for quantifying uncertainty using probability theory. A general introduction to interoperability and uncertainty is given, with particular emphasis on the geospatial domain. Existing interoperable standards used within the geospatial sciences are reviewed, including Geography Markup Language (GML), Observations and Measurements (O&M) and the Web Processing Service (WPS) specifications. The importance of uncertainty in geospatial data is identified and probability theory is examined as a mechanism for quantifying these uncertainties. The Uncertainty Markup Language (UncertML) is presented as a solution to the lack of an interoperable standard for quantifying uncertainty. UncertML is capable of describing uncertainty using statistics, probability distributions or a series of realisations. The capabilities of UncertML are demonstrated through a series of XML examples. This thesis then provides a series of example use cases where UncertML is integrated with existing standards in a variety of applications. The Sensor Observation Service - a service for querying and retrieving sensor-observed data - is extended to provide a standardised method for quantifying the inherent uncertainties in sensor observations. The INTAMAP project demonstrates how UncertML can be used to aid uncertainty propagation using a WPS by allowing UncertML as input and output data. The flexibility of UncertML is demonstrated with an extension to the GML geometry schemas to allow positional uncertainty to be quantified. Further applications and developments of UncertML are discussed.

Modeling geometric rules in object based models:an XML / GML approach

Most object-based approaches to Geographical Information Systems (GIS) have concentrated on the representation of geometric properties of objects in terms of fixed geometry. In our road traffic marking application domain we have a requirement to represent the static locations of the road markings but also enforce the associated regulations, which are typically geometric in nature. For example a give way line of a pedestrian crossing in the UK must be within 1100-3000 mm of the edge of the crossing pattern. In previous studies of the application of spatial rules (often called 'business logic') in GIS emphasis has been placed on the representation of topological constraints and data integrity checks. There is very little GIS literature that describes models for geometric rules, although there are some examples in the Computer Aided Design (CAD) literature. This paper introduces some of the ideas from so called variational CAD models to the GIS application domain, and extends these using a Geography Markup Language (GML) based representation. In our application we have an additional requirement; the geometric rules are often changed and vary from country to country so should be represented in a flexible manner. In this paper we describe an elegant solution to the representation of geometric rules, such as requiring lines to be offset from other objects. The method uses a feature-property model embraced in GML 3.1 and extends the possible relationships in feature collections to permit the application of parameterized geometric constraints to sub features. We show the parametric rule model we have developed and discuss the advantage of using simple parametric expressions in the rule base. We discuss the possibilities and limitations of our approach and relate our data model to GML 3.1. © 2006 Springer-Verlag Berlin Heidelberg.

Inter-organizational co-operation, conflict and change

Relationships between organizations can be characterized by cooperation, conflict, and change. In this dissertation we study cooperation between organizations by investigating how norms in relationships can enhance innovativeness and subsequently impact relationship performance. We do so by incorporating both beneficial aspects of long term relationships as well as “dark side” factors that may decrease innovativeness. This provides a balanced assessment of the factors increasing and decreasing the performance of relationships. Next, we study conflict between organizations by taking a network view on conflict which helps explain why organizations react to conflict. We find stakeholders to have an effect on channel conflict responsiveness. Finally we study change by means of an organization’s ability to successfully add an Internet channel to their distribution system in order to sell its products or services directly to the end-user. We find that an Internet channel is best implemented by organizations that are flexible and we identify several circumstances under which this flexibility is highest.

Automated mapping of environmental variables from a SEIS or SISE perspective

The INTAMAP FP6 project has developed an interoperable framework for real-time automatic mapping of critical environmental variables by extending spatial statistical methods and employing open, web-based, data exchange protocols and visualisation tools. This paper will give an overview of the underlying problem, of the project, and discuss which problems it has solved and which open problems seem to be most relevant to deal with next. The interpolation problem that INTAMAP solves is the generic problem of spatial interpolation of environmental variables without user interaction, based on measurements of e.g. PM10, rainfall or gamma dose rate, at arbitrary locations or over a regular grid covering the area of interest. It deals with problems of varying spatial resolution of measurements, the interpolation of averages over larger areas, and with providing information on the interpolation error to the end-user. In addition, monitoring network optimisation is addressed in a non-automatic context.

An intelligent approach for deploying applications in WSN's

Wireless sensor networks have been identified as one of the key technologies for the 21st century. They consist of tiny devices with limited processing and power capabilities, called motes that can be deployed in large numbers of useful sensing capabilities. Even though, they are flexible and easy to deploy, there are a number of considerations when it comes to their fault tolerance, conserving energy and re-programmability that need to be addressed before we draw any substantial conclusions about the effectiveness of this technology. In order to overcome their limitations, we propose a middleware solution. The proposed scheme is composed based on two main methods. The first method involves the creation of a flexible communication protocol based on technologies such as Mobile Code/Agents and Linda-like tuple spaces. In this way, every node of the wireless sensor network will produce and process data based on what is the best for it but also for the group that it belongs too. The second method incorporates the above protocol in a middleware that will aim to bridge the gap between the application layer and low level constructs such as the physical layer of the wireless sensor network. A fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort towards the deployed applications running in an energy efficient manner inside the network. The proposed scheme is evaluated through a number of trials aiming to test its merits under real time conditions and to identify its effectiveness against other similar approaches. Finally, parameters which determine the characteristics of the proposed scheme are also examined.

Social and organizational impacts of emerging mobile devices:evaluating use

As mobile devices become increasingly diverse and continue to shrink in size and weight, their portability is enhanced but, unfortunately, their usability tends to suffer. Ultimately, the usability of mobile technologies determines their future success in terms of end-user acceptance and, thereafter, adoption and social impact. Widespread acceptance will not, however, be achieved if users’ interaction with mobile technology amounts to a negative experience. Mobile user interfaces need to be designed to meet the functional and sensory needs of users. Social and Organizational Impacts of Emerging Mobile Devices: Evaluating Use focuses on human-computer interaction related to the innovation and research in the design, evaluation, and use of innovative handheld, mobile, and wearable technologies in order to broaden the overall body of knowledge regarding such issues. It aims to provide an international forum for researchers, educators, and practitioners to advance knowledge and practice in all facets of design and evaluation of human interaction with mobile technologies.