Proposta de um modelo de dicionário terminológico onomasiológico

The present paper aims at applying a model of bilingual onomasiological terminological dictionary, as proposed by Babini (2001b), for the development of an English-Portuguese and Portuguese-English electronic dictionary of the fundamental Artificial Neural Networks (ANN) terms. This subarea of Artificial Intelligence was chosen due to its use in several technological activities. The onomasiological dictionary is characterized by allowing searches of either lexical or terminological units from its semantic content. Our dictionary model allows two types of search: semasiological and onomasiological. The onomasiological search is made possible by a set of semes or semantic traits that make up the concept of each term in the dictionary.

Herbivores equalize the seedling height growth of three dominant tree species in an African tropical rain forest

Determining the impact of insect herbivores on forest tree seedlings and saplings is difficult without experimentation in the field. Moreover, this impact may be heterogeneous in time and space because of seasonal rainfall and canopy disturbances, or ‘gaps’, which can influence both insect abundance and plant performance. In this study we used fine netting to individually protect seedlings of Microberlinia bisulcata, Tetraberlinia bifoliolata and Tetraberlinia korupensis trees (Fabaceae = Leguminosae) from insects in 41 paired gap-understorey locations across 80 ha of primary rain forest (Korup, Cameroon). For all species, growth in height and leaf numbers was negligible in the understorey, where M. bisulcata had the lowest survival after c. 2 years. In gaps, however, all species responded positively with pronounced above-ground growth across seasons. When exposed to herbivores their seedling height growth was similar, but in the absence of herbivores, M. bisulcata significantly outgrew both Tetraberlinia species and matched their leaf numbers. This result suggests that insect herbivores might play an important role in maintaining species coexistence by mitigating sapling abundance of the more palatable M. bisulcata, which in gaps was eaten the most severely. The higher ratio in static leaf damage of control-to-caged M. bisulcata seedlings in gaps than understorey locations was consistent with the Plant Vigour Hypothesis. This result, however, did not apply to either Tetraberlinia species. For M. bisulcata and T. korupensis, but not T. bifoliolata (the most shade-tolerant species), caging improved relative seedling survival in the understory locations compared to gaps, providing restricted support for the Limiting Resource Model. Approximately 2.25 years after treatments were removed, the caged seedlings were taller and had more leaves than controls in all three species, and the effect remained strongest for M. bisulcata. We conclude that in this community the impact of leaf herbivory on seedling growth in gaps is strong for the dominant M. bisulcata, which coupled to a very low shade-tolerance contributes to limiting its regeneration. However, because gaps are common to most forests, insect herbivores may be having impacts upon functionally similar tree species that are also characterized by low sapling recruitment much more widely than currently appreciated. An implication for the restoration and management of M. bisulcata populations in forests outside of Korup is that physical protection from herbivores of new seedlings where the canopy is opened by gaps, or by harvesting, should substantially increase its subcanopy regeneration, and thus, too, its opportunities for adult recruitment.

Change Detection Memory in Rhesus Monkeys and Humans

Visual short-term memory (VSTM) is the storage of visual information over a brief time period (usually a few seconds or less). Over the past decade, the most popular task for studying VSTM in humans has been the change detection task. In this task, subjects must remember several visual items per trial in order to identify a change following a brief delay interval. Results from change detection tasks have shown that VSTM is limited; humans are only able to accurately hold a few visual items in mind over a brief delay. However, there has been much debate in regard to the structure or cause of these limitations. The two most popular conceptualizations of VSTM limitations in recent years have been the fixed-capacity model and the continuous-resource model. The fixed-capacity model proposes a discrete limit on the total number of visual items that can be stored in VSTM. The continuous-resource model proposes a continuous-resource that can be allocated among many visual items in VSTM, with noise in item memory increasing as the number of items to be remembered increases. While VSTM is far from being completely understood in humans, even less is known about VSTM in non-human animals, including the rhesus monkey (Macaca mulatta). Given that rhesus monkeys are the premier medical model for humans, it is important to understand their VSTM if they are to contribute to understanding human memory. The primary goals of this study were to train and test rhesus monkeys and humans in change detection in order to directly compare VSTM between the two species and explore the possibility that direct species comparison might shed light on the fixed-capacity vs. continuous-resource models of VSTM. The comparative results suggest qualitatively similar VSTM for the two species through converging evidence supporting the continuous-resource model and thereby establish rhesus monkeys as a good system for exploring neurophysiological correlates of VSTM.

Canopy cover mediates interactions between a specialist caterpillar and seedlings of a neotropical tree

1 Light availability may be crucial for understanding dynamics of plant–herbivore interactions in temperate and tropical forest communities. This is because local light availability can influence both tree seedling tolerance and susceptibility to herbivory – yet how they mediate levels of insect herbivory that vary with the density of host population is virtually unknown. Here we tested predictions of three key, non-mutually exclusive hypotheses of plant–herbivore interactions: the Limiting Resource Model (LRM), the Plant Vigour Hypothesis (PVH), and the Janzen-Connell Mechanism (JCM). 2 In an Amazonian forest, we planted Swietenia macrophylla seedlings (c. 5 months old) into natural canopy gaps and the shaded understorey and simulated the damage patterns of the specialist herbivore moth, Steniscadia poliophaea, by clipping seedling leaves. Over the next 8 months, we monitored seedling performance in terms of growth and survivorship and also quantified herbivory to new young leaves on a seasonal basis. 3 In support of the LRM, severe leaf damage (≥ 50%) was lethal for Swietenia macrophylla seedlings in the understorey, but in gaps only reduced seedling growth. In support of the PVH, gap seedlings suffered greater post-simulated herbivory (up to 100% defoliation) by S. poliophaea caterpillars than their understorey counterparts. 4 Adding a novel dimension to the Janzen–Connell hypothesis, we found that early wet season herbivory of seedlings in gaps increased with conspecific adult density within a 125-m radius; whereas in the understorey only those seedlings within 50 m of a Swietenia tree were attacked by caterpillars. 5 Synthesis. These results suggest lepidopterans that need young leaves for food may forage more widely in forests to find seedlings in light-rich canopy gaps. Moths may achieve this successfully by being first attracted to gaps, and then searching within them for suitable hosts. A conceptual model, integrating conspecific adult tree density with light-driven changes in seedling tolerance/vigour and their susceptibility to herbivory and mortality, is presented. Spatial variation in the light available to tree seedlings often affects their tolerance and vigour, which may have important consequences for leaf-chewing insects and the scale of density-dependent herbivory in forests.

Dynamic Unicast: Information-Centric Multi-hop Routing for Mobile Ad-hoc Networks

Abstract Information-centric networking (ICN) offers new perspectives on mobile ad-hoc communication because routing is based on names but not on endpoint identifiers. Since every content object has a unique name and is signed, authentic content can be stored and cached by any node. If connectivity to a content source breaks, it is not necessarily required to build a new path to the same source but content can also be retrieved from a closer node that provides the same content copy. For example, in case of collisions, retransmissions do not need to be performed over the entire path but due to caching only over the link where the collision occurred. Furthermore, multiple requests can be aggregated to improve scalability of wireless multi-hop communication. In this work, we base our investigations on Content-Centric Networking (CCN), which is a popular {ICN} architecture. While related works in wireless {CCN} communication are based on broadcast communication exclusively, we show that this is not needed for efficient mobile ad-hoc communication. With Dynamic Unicast requesters can build unicast paths to content sources after they have been identified via broadcast. We have implemented Dynamic Unicast in CCNx, which provides a reference implementation of the {CCN} concepts, and performed extensive evaluations in diverse mobile scenarios using NS3-DCE, the direct code execution framework for the {NS3} network simulator. Our evaluations show that Dynamic Unicast can result in more efficient communication than broadcast communication, but still supports all {CCN} advantages such as caching, scalability and implicit content discovery.

Enhancing Interaction With Smart Objects Throught Mobile Devices

Interaction with smart objects can be accomplished with different technologies, such as tangible interfaces or touch computing, among others. Some of them require the object to be especially designed to be 'smart', and some other are limited in the variety and complexity of the possible actions. This paper describes a user-smart object interaction model and prototype based on the well known event-condition-action (ECA) reasoning, which can work, to a degree, independently of the intelligence embedded into the smart object. It has been designed for mobile devices to act as mediators between users and smart objects and provides an intuitive means for personalization of object's behavior. When the user is close to an object, this one publishes its 'event & action' capabilities to the user's device. The user may accept the object's module offering, which will enable him to configure and control that object, but also its actions with respect to other elements of the environment or the virtual world. The modular ECA interaction model facilitates the integration of different types of objects in a smart space, giving the user full control of their capabilities and facilitating creative mash-uping to build customized functionalities that combine physical and virtual actions

Towards a lightweight mobile semantic-based approach for enhancing interaction with smart objects

This work describes a semantic extension for a user-smart object interaction model based on the ECA paradigm (Event-Condition-Action). In this approach, smart objects publish their sensing (event) and action capabilities in the cloud and mobile devices are prepared to retrieve them and act as mediators to configure personalized behaviours for the objects. In this paper, the information handled by this interaction system has been shaped according several semantic models that, together with the integration of an embedded ontological and rule-based reasoner, are exploited in order to (i) automatically detect incompatible ECA rules configurations and to (ii) support complex ECA rules definitions and execution. This semantic extension may significantly improve the management of smart spaces populated with numerous smart objects from mobile personal devices, as it facilitates the configuration of coherent ECA rules.

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.

Intelligent agent supported personalization for virtual learning environments

Virtual learning environments (VLEs) are computer-based online learning environments, which provide opportunities for online learners to learn at the time and location of their choosing, whilst allowing interactions and encounters with other online learners, as well as affording access to a wide range of resources. They have the capability of reaching learners in remote areas around the country or across country boundaries at very low cost. Personalized VLEs are those VLEs that provide a set of personalization functionalities, such as personalizing learning plans, learning materials, tests, and are capable of initializing the interaction with learners by providing advice, necessary instant messages, etc., to online learners. One of the major challenges involved in developing personalized VLEs is to achieve effective personalization functionalities, such as personalized content management, learner model, learner plan and adaptive instant interaction. Autonomous intelligent agents provide an important technology for accomplishing personalization in VLEs. A number of agents work collaboratively to enable personalization by recognizing an individual's eLeaming pace and reacting correspondingly. In this research, a personalization model has been developed that demonstrates dynamic eLearning processes; secondly, this study proposes an architecture for PVLE by using intelligent decision-making agents' autonomous, pre-active and proactive behaviors. A prototype system has been developed to demonstrate the implementation of this architecture. Furthemore, a field experiment has been conducted to investigate the performance of the prototype by comparing PVLE eLearning effectiveness with a non-personalized VLE. Data regarding participants' final exam scores were collected and analyzed. The results indicate that intelligent agent technology can be employed to achieve personalization in VLEs, and as a consequence to improve eLeaming effectiveness dramatically.

How innovation can alleviate negative consequences of demanding work contexts:The influence of climate for innovation on organizational outcomes

This study examines climate for innovation as a method by which negative organizational consequences of demanding work may be lessened. It was expected that a climate for innovation would enable employees to develop coping mechanisms or improved work-related processes which counteract negative consequences of work demands. Extending the job demands-resource model (Karasek, 1979), we predicted and found that among the sample of 22,696 respondents from 131 healthcare organizations, organizational climate for innovation alleviated the negative effects of work demands on organizational performance. Thus, this study informs climate theories and guides practitioners' efforts to support the employees. © 2007 The British Psychological Society.

Static and Dynamic Integrated Expert Systems: State of the Art, Problems and Trends

Systemized analysis of trends towards integration and hybridization in contemporary expert systems is conducted, and a particular class of applied expert systems, integrated expert systems, is considered. For this purpose, terminology, classification, and models, proposed by the author, are employed. As examples of integrated expert systems, Russian systems designed in this field and available to the majority of specialists are analyzed.

Using the Simulation Modeling Methods for the Designing Real-Time Integrated Expert Systems

Certain theoretical and methodological problems of designing real-time dynamical expert systems, which belong to the class of the most complex integrated expert systems, are discussed. Primary attention is given to the problems of designing subsystems for modeling the external environment in the case where the environment is represented by complex engineering systems. A specific approach to designing simulation models for complex engineering systems is proposed and examples of the application of this approach based on the G2 (Gensym Corp.) tool system are described.

Leadership and organisational outcomes in healthcare

This research examined to what extent and how leadership is related to organisational outcomes in healthcare. Based on the Job Demands-Resource model, a set of hypotheses was developed, which predicted that the effect of leadership on healthcare outcomes would be mediated by job design, employee engagement, work pressure, opportunity for involvement, and work-life balance. The research focused on the National Health Service (NHS) in England, and examined the relationships between senior leadership, first line supervisory leadership and outcomes. Three years of data (2008 – 2010) were gathered from four data sources: the NHS National Staff Survey, the NHS Inpatient Survey, the NHS Electronic Record, and the NHS Information Centre. The data were drawn from 390 healthcare organisations and over 285,000 staff annually for each of the three years. Parallel mediation regressions modelled both cross sectional and longitudinal designs. The findings revealed strong relationships between senior leadership and supervisor support respectively and job design, engagement, opportunity for involvement, and work-life balance, while senior leadership was also associated with work pressure. Except for job design, there were significant relationships between the mediating variables and the outcomes of patient satisfaction, employee job satisfaction, absenteeism, and turnover. Relative importance analysis showed that senior leadership accounted for significantly more variance in relationships with outcomes than supervisor support in the majority of models tested. Results are discussed in relation to theoretical and practical contributions. They suggest that leadership plays a significant role in organisational outcomes in healthcare and that previous research may have underestimated how influential senior leaders may be in relation to these outcomes. Moreover, the research suggests that leaders in healthcare may influence outcomes by the way they manage the work pressure, engagement, opportunity for involvement and work-life balance of those they lead.

Behavior of Granular Materials Under Triaxial Compression with Pulsating Deviator Stress, HR-131, Special Report

Behavior of granular material subjected to repeated load triaxial compression tests is characterized by a model based on rate process theory. Starting with the Arrhenius equation from chemical kinetics, the relationship of temperature, shear stress, normal stress and volume change to deformation rate is developed. The proposed model equation includes these factors as a product of exponential terms. An empirical relationship between deformation and the cube root of the number of stress applications at constant temperature and normal stress is combined with the rate equation to yield an integrated relationship of temperature, deviator stress, confining pressure and number of deviator stress applications to axial strain. The experimental program consists of 64 repeated load triaxial compression tests, 52 on untreated crushed stone and 12 on the same crushed stone material treated with 4% asphalt cement. Results were analyzed with multiple linear regression techniques and show substantial agreement with the model equations. Experimental results fit the rate equation somewhat better than the integrated equation when all variable quantities are considered. The coefficient of shear temperature gives the activation enthalpy, which is about 4.7 kilocalories/mole for untreated material and 39.4 kilocalories/mole for asphalt-treated material. This indicates the activation enthalpy is about that of the pore fluid. The proportionality coefficient of deviator stress may be used to measure flow unit volume. The volumes thus determined for untreated and asphalt-treated material are not substantially different. This may be coincidental since comparison with flow unit volumes reported by others indicates flow unit volume is related to gradation of untreated material. The flow unit volume of asphalt-treated material may relate to asphalt cement content. The proposed model equations provide a more rational basis for further studies of factors affecting deformation of granular materials under stress similar to that in pavement subjected to transient traffic loads.