289 resultados para Computational-linguistic domain


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The structures and thermodynamic properties of methyl derivatives of ammonia–borane (BH3NH3, AB) have been studied with the frameworks of density functional theory and second-order Møller–Plesset perturbation theory. It is found that, with respect to pure AB, methyl ammonia–boranes show higher complexation energies and lower reaction enthalpies for the release of H2, together with a slight increment of the activation barrier. These results indicate that the methyl substitution can enhance the reversibility of the system and prevent the formation of BH3/NH3, but no enhancement of the release rate of H2 can be expected.

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The sidewall additions of diazomethane to (n, n), n = 3–10 armchair single-walled carbon nanotubes (SWCNTs) on two different orientations of C–C bonds have been studied using the ONIOM(B3LYP/6-31G(d):PM3) approach. The binding energies of SWCNTs complexes with CH2N2, CH2 and their transition-state structures were computed at the B3LYP/6-31G(d) level. The effects of diameters of armchair SWCNTs on their binding energies were studied. Relative reactivities of all the SWCNTs and their complexes based on their frontier orbital energies gaps are reported.

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This paper investigates engaging experienced birders, as volunteer citizen scientists, to analyze large recorded audio datasets gathered through environmental acoustic monitoring. Although audio data is straightforward to gather, automated analysis remains a challenging task; the existing expertise, local knowledge and motivation of the birder community can complement computational approaches and provide distinct benefits. We explored both the culture and practice of birders, and paradigms for interacting with recorded audio data. A variety of candidate design elements were tested with birders. This study contributes an understanding of how virtual interactions and practices can be developed to complement existing practices of experienced birders in the physical world. In so doing this study contributes a new approach to engagement in e-science. Whereas most citizen science projects task lay participants with discrete real world or artificial activities, sometimes using extrinsic motivators, this approach builds on existing intrinsically satisfying practices.

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This thesis makes several contributions towards improved methods for encoding structure in computational models of word meaning. New methods are proposed and evaluated which address the requirement of being able to easily encode linguistic structural features within a computational representation while retaining the ability to scale to large volumes of textual data. Various methods are implemented and evaluated on a range of evaluation tasks to demonstrate the effectiveness of the proposed methods.

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The application of different EMS current thresholds on muscle activates not only the muscle but also peripheral sensory axons that send proprioceptive and pain signals to the cerebral cortex. A 32-channel time-domain fNIRS instrument was employed to map regional cortical activities under varied EMS current intensities applied on the right wrist extensor muscle. Eight healthy volunteers underwent four EMS at different current thresholds based on their individual maximal tolerated intensity (MTI), i.e., 10 % < 50 % < 100 % < over 100 % MTI. Time courses of the absolute oxygenated and deoxygenated hemoglobin concentrations primarily over the bilateral sensorimotor cortical (SMC) regions were extrapolated, and cortical activation maps were determined by general linear model using the NIRS-SPM software. The stimulation-induced wrist extension paradigm significantly increased activation of the contralateral SMC region according to the EMS intensities, while the ipsilateral SMC region showed no significant changes. This could be due in part to a nociceptive response to the higher EMS current intensities and result also from increased sensorimotor integration in these cortical regions.

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We present a tool for automatic analysis of computational indistinguishability between two strings of information. This is designed as a generic tool for proving cryptographic security based on a formalism that provides computational soundness preservation. The tool has been implemented and tested successfully with several cryptographic schemes.

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Many successful query expansion techniques ignore information about the term dependencies that exist within natural language. However, researchers have recently demonstrated that consistent and significant improvements in retrieval effectiveness can be achieved by explicitly modelling term dependencies within the query expansion process. This has created an increased interest in dependency-based models. State-of-the-art dependency-based approaches primarily model term associations known within structural linguistics as syntagmatic associations, which are formed when terms co-occur together more often than by chance. However, structural linguistics proposes that the meaning of a word is also dependent on its paradigmatic associations, which are formed between words that can substitute for each other without effecting the acceptability of a sentence. Given the reliance on word meanings when a user formulates their query, our approach takes the novel step of modelling both syntagmatic and paradigmatic associations within the query expansion process based on the (pseudo) relevant documents returned in web search. The results demonstrate that this approach can provide significant improvements in web re- trieval effectiveness when compared to a strong benchmark retrieval system.

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Uncooperative iris identification systems at a distance suffer from poor resolution of the acquired iris images, which significantly degrades iris recognition performance. Super-resolution techniques have been employed to enhance the resolution of iris images and improve the recognition performance. However, most existing super-resolution approaches proposed for the iris biometric super-resolve pixel intensity values, rather than the actual features used for recognition. This paper thoroughly investigates transferring super-resolution of iris images from the intensity domain to the feature domain. By directly super-resolving only the features essential for recognition, and by incorporating domain specific information from iris models, improved recognition performance compared to pixel domain super-resolution can be achieved. A framework for applying super-resolution to nonlinear features in the feature-domain is proposed. Based on this framework, a novel feature-domain super-resolution approach for the iris biometric employing 2D Gabor phase-quadrant features is proposed. The approach is shown to outperform its pixel domain counterpart, as well as other feature domain super-resolution approaches and fusion techniques.

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Chlamydia trachomatis is a bacterial pathogen responsible for one of the most prevalent sexually transmitted infections worldwide. Its unique development cycle has limited our understanding of its pathogenic mechanisms. However, CtHtrA has recently been identified as a potential C. trachomatis virulence factor. CtHtrA is a tightly regulated quality control protein with a monomeric structural unit comprised of a chymotrypsin-like protease domain and two PDZ domains. Activation of proteolytic activity relies on the C-terminus of the substrate allosterically binding to the PDZ1 domain, which triggers subsequent conformational change and oligomerization of the protein into 24-mers enabling proteolysis. This activation is mediated by a cascade of precise structural arrangements, but the specific CtHtrA residues and structural elements required to facilitate activation are unknown. Using in vitro analysis guided by homology modeling, we show that the mutation of residues Arg362 and Arg224, predicted to disrupt the interaction between the CtHtrA PDZ1 domain and loop L3, and between loop L3 and loop LD, respectively, are critical for the activation of proteolytic activity. We also demonstrate that mutation to residues Arg299 and Lys160, predicted to disrupt PDZ1 domain interactions with protease loop LC and strand β5, are also able to influence proteolysis, implying their involvement in the CtHtrA mechanism of activation. This is the first investigation of protease loop LC and strand β5 with respect to their potential interactions with the PDZ1 domain. Given their high level of conservation in bacterial HtrA, these structural elements may be equally significant in the activation mechanism of DegP and other HtrA family members.

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Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

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ForscherInnen aus Sozial- und Geisteswissenschaften interessieren sich seit nunmehr einem Jahrzehnt für Blogs, Online-Tagebücher und Online-Journale. Auch wenn die Zuwachsrate der Blogosphäre seit der Blütezeit des Bloggens in den 2000ern stagniert, bleiben Blogs doch eines der bedeutendsten Genres der internetgestützten Kommunikation. Tatsächlich ist nach der Massenabwanderung zu Facebook, Twitter und anderen erst in jüngerer Zeit entstandenen Kommunikationsmitteln eine etwas kleinere, aber umso stärker etablierte Blogosphäre von engagierten und eingeschworenen Teilnehmenden übriggeblieben. Blogs werden mittlerweile als Teil einer institutionellen, persönlichen und Gruppen-Kommunikationstrategie akzeptiert. In Stil und Inhalt liegen sie zwischen den statischeren Informationen auf konventionellen Websites und den ständig aktualisierten Facebook- und Twitter-Newsfeeds. Blogs ermöglichen es ihren AutorInnen (und deren KommentatorInnen), bestimmte Themen im Umfang von einigen hundert bis zu einigen tausend Wörtern zu durchdenken, in kürzeren Posts ins Detail zu gehen und ggf. intensiver durchdachte Texte anderswo zu publizieren. Zudem sind sie auch ein sehr flexibles Medium: Bilder, Audio-, Video- sowie andere Materialien können mühelos eingefügt werden - und natürlich auch das grundlegende Instrument des Bloggens: Hyperlinks.

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This paper illustrates the use of finite element (FE) technique to investigate the behaviour of laminated glass (LG) panels under blast loads. Two and three dimensional (2D and 3D) modelling approaches available in LS-DYNA FE code to model LG panels are presented. Results from the FE analysis for mid-span deflection and principal stresses compared well with those from large deflection plate theory. The FE models are further validated using the results from a free field blast test on a LG panel. It is evident that both 2D and 3D LG models predict the experimental results with reasonable accuracy. The 3D LG models give slightly more accurate results but require considerably more computational time compared to the 2D LG models.

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Currently, finite element analyses are usually done by means of commercial software tools. Accuracy of analysis and computational time are two important factors in efficiency of these tools. This paper studies the effective parameters in computational time and accuracy of finite element analyses performed by ANSYS and provides the guidelines for the users of this software whenever they us this software for study on deformation of orthopedic bone plates or study on similar cases. It is not a fundamental scientific study and only shares the findings of the authors about structural analysis by means of ANSYS workbench. It gives an idea to the readers about improving the performance of the software and avoiding the traps. The solutions provided in this paper are not the only possible solutions of the problems and in similar cases there are other solutions which are not given in this paper. The parameters of solution method, material model, geometric model, mesh configuration, number of the analysis steps, program controlled parameters and computer settings are discussed through thoroughly in this paper.

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This paper evaluates the efficiency of a number of popular corpus-based distributional models in performing discovery on very large document sets, including online collections. Literature-based discovery is the process of identifying previously unknown connections from text, often published literature, that could lead to the development of new techniques or technologies. Literature-based discovery has attracted growing research interest ever since Swanson's serendipitous discovery of the therapeutic effects of fish oil on Raynaud's disease in 1986. The successful application of distributional models in automating the identification of indirect associations underpinning literature-based discovery has been heavily demonstrated in the medical domain. However, we wish to investigate the computational complexity of distributional models for literature-based discovery on much larger document collections, as they may provide computationally tractable solutions to tasks including, predicting future disruptive innovations. In this paper we perform a computational complexity analysis on four successful corpus-based distributional models to evaluate their fit for such tasks. Our results indicate that corpus-based distributional models that store their representations in fixed dimensions provide superior efficiency on literature-based discovery tasks.

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Construction works are project-based and interdisciplinary. Many construction management (CM) problems are ill defined. The knowledge required to address such problems is not readily available and mostly tacit in nature. Moreover, the researchers, especially the students in the higher education, often face difficulty in defining the research problem, adopting an appropriate research process and methodology for designing and validating their research. This paper describes a ‘Horseshoe’ research process approach and its application to address a research problem of extracting construction-relevant information from a building information model (BIM). It describes the different steps of the process for understanding a problem, formulating appropriate research question/s, defining different research tasks, including a methodology for developing, implementing and validating the research. It is argued that a structure research approach and the use of mixed research methods would provide a sound basis for research design and validation in order to make contribution to existing knowledge.