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An accurate characterization of the substrate is a prerequisite of color management in print. The use of standard ICC profiles in prepress leaves it to the printer to match the fixed substrate characteristics contained in these profiles. This triggers the interest in methods to predict, if a given ink, press and paper combination complies with a given characterization. We present an approach to compare physical and optical characteristics of papers in order to achieve such a prediction of compliance by classification methods. For economical and ecological reasons it is preferable to test paper without printing it. We therefore propose non-destructive methods. [ABSTRACT FROM AUTHOR]

The work presented in this paper shows the way to generate colored paper mosaics using computer graphics techniques. Following two tasks need to be done to generate colored paper mosaic. The first one is to generate colored paper tile and the other one is to arrange the tile. Voronoi Diagram and Random Point Displacement have been used in this paper to come up with the shape of the tile. And, energy value that the tile has depending on its location is the factor to determine the best positioning of the tile. This paper focuses on representing the overlap among tiles, maintenance of the edge of input image, and various shapes of tiles in the final output image by solving two tasks mentioned above. [ABSTRACT FROM AUTHOR]

In this paper we propose a novel personalized paper search system using the relevance among user's queried keywords and user's behaviors on a searched paper list. The proposed system builds user's individual relevance network from analyzing the appearance frequencies of keywords in the searched papers. The relevance network is personalized by providing weights to the appearance frequencies of keywords according to users' behaviors on the searched list, such as "downloading," "opening," and "no-action." In the experimental section, we demonstrate our method using 100 faculties' search information in the University of Suwon. [ABSTRACT FROM AUTHOR]

We propose Focused Page Rank (FPR) algorithm adaptation for the problem of scientific papers ranking. FPR is based on the Focused Surfer model, where the probability to follow the reference in a paper is proportional to its citation count. Evaluation on Citeseer autonomous digital library content showed that proposed model is a tradeoff between traditional citation count and basic Page Rank (PR). In contrast to basic Page Rank, proposed Focused Surfer model suffers less from the "outbound links" problem. We believe that FPR algorithm is closer to reality because highly cited papers are more visible and tend to attract more citations in future. This is in accordance with the one of the most significant principles of Scientometrics. No need for lexical analysis of the domain corpus and simplicity of implementation are among the strong points of the proposed model and make the proposed ranking technique attractive for academia digital libraries. [ABSTRACT FROM AUTHOR]

In digital libraries, much of the reading activity is still done on printed copies of documents. We show how digital pen and paper technologies can be used to support readers by automatically creating interactive paper versions of digital documents during the printing process that enable users to activate embedded hyperlinks to other documents and services from printed versions. The approach uses a special printer driver that allows information about hyperlinks to be extracted and stored at print time. Users can then activate hyperlinks in the printed document with a digital pen. [ABSTRACT FROM AUTHOR]

The goal of this chapter is to help authors recognize and avoid a set of pitfalls that recur in many rejected information visualization papers, using a chronological model of the research process. Selecting a target paper type in the initial stage can avert an inappropriate choice of validation methods. Pitfalls involving the design of a visual encoding may occur during the middle stages of a project. In a later stage when the bulk of the research is finished and the paper writeup begins, the possible pitfalls are strategic choices for the content and structure of the paper as a whole, tactical problems localized to specific sections, and unconvincing ways to present the results. Final-stage pitfalls of writing style can be checked after a full paper draft exists, and the last set of problems pertain to submission. [ABSTRACT FROM AUTHOR]

With the use of computers, paper questionnaires are being replaced by electronic questionnaires. The formats of traditional paper questionnaires have been found to affect a subject΄s rating. Consequently, the transition from paper to electronic format can subtly change results. The research presented begins to determine how electronic questionnaire formats change subjective ratings. For formats where subjects used a flow chart to arrive at their rating, starting at the worst and middle ratings of the flow charts were the most accurate but subjects took slightly more time to arrive at their answers. Except for the electronic paper format, starting at the worst rating was the most preferred. The paper and electronic paper versions had the worst accuracy. Therefore, for flowchart type of questionnaires, flowcharts should start at the worst rating and work their way up to better ratings. [ABSTRACT FROM AUTHOR]

This chapter describes a study on the haptic discrimination of different types of plain paper. The experiment is designed to replicate features of a `banknote΄ scenario in which it may be possible to identify a counterfeit on the basis of only a few seconds contact. Multidimensional scaling (MDS) techniques are used to investigate the perceptual dimensions involved in the discrimination task. A related study of tactile perceptual space is summarised in Appendix 1. [ABSTRACT FROM AUTHOR]

Recently, collaborative tagging has become more and more popular in the Web2.0 community, since tags in these Web2.0 systems reflect the specific content features of the resources. This paper presents a recommender for scientific literatures based on semantic concept similarity computed from the collaborative tags. User profiles and item profiles are presented by these semantic concepts, and neighbor users are selected using collaborative filtering. Then, content-based filtering approach is used to generate recommendation list from the papers these neighbor users tagged. The evaluation is carried out on a dataset crawled from CiteULike, with satisfied experiment results. [ABSTRACT FROM AUTHOR]