953 resultados para computer user


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In our large library of annotated environmental recordings of animal vocalizations, searching annotations by label can return thousands of results. We propose a heat map of aggregated annotation time and frequency bounds, maintaining the shape of the annotations as they appear on the spectrogram. This compactly displays the distribution of annotation bounds for the user's query, and allows them to easily identify unusual annotations. Key to this is allowing zero values on the map to be differentiated from areas where there are single annotations.

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It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of large scale terms and data patterns. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, there has been often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences; yet, how to effectively use large scale patterns remains a hard problem in text mining. To make a breakthrough in this challenging issue, this paper presents an innovative model for relevance feature discovery. It discovers both positive and negative patterns in text documents as higher level features and deploys them over low-level features (terms). It also classifies terms into categories and updates term weights based on their specificity and their distributions in patterns. Substantial experiments using this model on RCV1, TREC topics and Reuters-21578 show that the proposed model significantly outperforms both the state-of-the-art term-based methods and the pattern based methods.

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Videogame control interfaces continue to evolve beyond their traditional roots, with devices encouraging more natural forms of interaction growing in number and pervasiveness. Yet little is known about their true potential for intuitive use. This paper proposes methods to leverage existing intuitive interaction theory for games research, specifically by examining different types of naturally mapped control interfaces for videogames using new measures for previous player experience. Three commercial control devices for a racing game were categorised using an existing typology, according to how the interface maps physical control inputs with the virtual gameplay actions. The devices were then used in a within-groups (n=64) experimental design aimed at measuring differences in intuitive use outcomes. Results from mixed design ANOVA are discussed, along with implications for the field.

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For people with intellectual disabilities, there are significant barriers to inclusion in socially cooperative endeavors. This paper investigates the effectiveness of Stomp, a tangible user interface (TUI) designed to provide new participatory experiences for people with intellectual disability. Results from an observational study reveal the extent to which the Stomp system supports social and physical interaction. The tangible, spatial, and embodied qualities of Stomp result in an experience that does not rely on the acquisition of specific competencies before interaction and engagement can occur.

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This paper addresses two common problems that users of various products and interfaces encounter— over-featured interfaces and product documentation. Over-featured interfaces are seen as a problem as they can confuse and over-complicate everyday interactions. Researchers also often claim that users do not read product documentation, although they are often exhorted to ‘RTFM’(read the field manual).We conducted two sets of studies with users which looked at the issues of both manuals and excess features with common domestic and personal products. The quantitative set was a series of questionnaires administered to 170 people over 7 years. The qualitative set consisted of two 6-month longitudinal studies based on diaries and interviews with a total of 15 participants. We found that manuals are not read by the majority of people, and most do not use all the features of the products that they own and use regularly. Men are more likely to do both than women, and younger people are less likely to use manuals than middle-aged and older ones. More educated people are also less likely to read manuals. Over-featuring and being forced to consult manuals also appears to cause negative emotional experiences. Implications of these findings are discussed.

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Intramedullary nailing is the standard fixation method for displaced diaphyseal fractures of the tibia. An optimal nail design should both facilitate insertion and anatomically fit the bone geometry at its final position in order to reduce the risk of stress fractures and malalignments. Due to the nonexistence of suitable commercial software, we developed a software tool for the automated fit assessment of nail designs. Furthermore, we demonstrated that an optimised nail, which fits better at the final position, is also easier to insert. Three-dimensional models of two nail designs and 20 tibiae were used. The fitting was quantified in terms of surface area, maximum distance, sum of surface areas and sum of maximum distances by which the nail was protruding into the cortex. The software was programmed to insert the nail into the bone model and to quantify the fit at defined increment levels. On average, the misfit during the insertion in terms of the four fitting parameters was smaller for the Expert Tibial Nail Proximal bend (476.3 mm2, 1.5 mm, 2029.8 mm2, 6.5 mm) than the Expert Tibial Nail (736.7 mm2, 2.2 mm, 2491.4 mm2, 8.0 mm). The differences were statistically significant (p ≤ 0.05). The software could be used by nail implant manufacturers for the purpose of implant design validation.

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This report was produced in partial fulfillment of contract ICT-2007-216676 (ECRYPT II), sponsored by the European Commission through the ICT Programme. The information in this paper is provided as is, and no warranty is given or implied that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability. We present a short overview of the recent results on the five finalists for NIST's SHA-3 competition. The next five chapters treat each one of the finalists.

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Rove n Rave ™ is a website designed and created for, and with, people with an intellectual disability. Its aim is to provide them with a user-friendly online platform where they can share opinions and experiences, and where they can find reviews which will help them to choose a place to visit themselves. During the development process, input on design requirements was gathered from a group of people with an intellectual disability and the disability service provider. This group then tested the product and provided further feedback on improving the website. It was found that the choice of wording, icons, pictures, colours and some functions significantly affected the users' ability to understand the content of the website. This demonstrated that a partnership between the developer and the user is essential when designing and delivering products or services for people with an intellectual disability.

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Multidimensional data are getting increasing attention from researchers for creating better recommender systems in recent years. Additional metadata provides algorithms with more details for better understanding the interaction between users and items. While neighbourhood-based Collaborative Filtering (CF) approaches and latent factor models tackle this task in various ways effectively, they only utilize different partial structures of data. In this paper, we seek to delve into different types of relations in data and to understand the interaction between users and items more holistically. We propose a generic multidimensional CF fusion approach for top-N item recommendations. The proposed approach is capable of incorporating not only localized relations of user-user and item-item but also latent interaction between all dimensions of the data. Experimental results show significant improvements by the proposed approach in terms of recommendation accuracy.

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This study constructs performance prediction models to estimate the end-user perceived video quality on mobile devices for the latest video encoding techniques –VP9 and H.265. Both subjective and objective video quality assessments were carried out for collecting data and selecting the most desirable predictors. Using statistical regression, two models were generated to achieve 94.5% and 91.5% of prediction accuracies respectively, depending on whether the predictor derived from the objective assessment is involved. These proposed models can be directly used by media industries for video quality estimation, and will ultimately help them to ensure a positive end-user quality of experience on future mobile devices after the adaptation of the latest video encoding technologies.

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The worldwide installed base of enterprise resource planning (ERP) systems has increased rapidly over the past 10 years now comprising tens of thousands of installations in large- and medium-sized organizations and millions of licensed users. Similar to traditional information systems (IS), ERP systems must be maintained and upgraded. It is therefore not surprising that ERP maintenance activities have become the largest budget provision in the IS departments of many ERP-using organizations. Yet, there has been limited study of ERP maintenance activities. Are they simply instances of traditional software maintenance activities to which traditional software maintenance research findings can be generalized? Or are they fundamentally different, such that new research, specific to ERP maintenance, is required to help alleviate the ERP maintenance burden? This paper reports a case study of a large organization that implemented ERP (an SAP system) more than three years ago. From the case study and data collected, we observe the following distinctions of ERP maintenance: (1) the ERP-using organization, in addition to addressing internally originated change-requests, also implements maintenance introduced by the vendor; (2) requests for user-support concerning the ERP system behavior, function and training constitute a main part of ERP maintenance activity; and (3) similar to the in-house software environment, enhancement is the major maintenance activity in the ERP environment, encompassing almost 64% of the total change-request effort. In light of these and other findings, we ultimately: (1) propose a clear and precise definition of ERP maintenance; (2) conclude that ERP maintenance cannot be sufficiently described by existing software maintenance taxonomies; and (3) propose a benefits-oriented taxonomy, that better represents ERP maintenance activities. Three salient dimensions (for characterizing requests) incorporated in the proposed ERP maintenance taxonomy are: (1) who is the maintenance source? (2) why is it important to service the request? and (3) what––whether there is any impact of implementing the request on the installed module(s)?