Veronica Liesaputra

Seeking information in realistic books: a user study

There are opposing views on whether readers gain any advantage from using a computer model of a 3D physical book. There is enough evidence, both anecdotal and from formal user studies, to suggest that the usual HTML or PDF presentation of documents is not always the most convenient, or the most comfortable, for the reader. On the other hand it is quite clear that while 3D book models have been prototyped and demonstrated, none are in routine use in todays digital libraries. And how do 3D book models compare with actual books? This paper reports on a user study designed to compare the performance of a practical Realistic Book implementation with conventional formats (HTML and PDF) and with physical books. It also evaluates the annotation features that the implementation provides.

Creating and Reading Realistic Electronic Books

A digital library project aims to combine the look and feel of physical books with the advantages of online documents such as hyperlinks and multimedia. A lightweight open source implementation enables highly responsive page turning and works within standard Web browsers.

Realistic electronic books

We describe a software book model that emulates a range of properties associated with physical books-analog page turning, visual location cues, bookmarks and annotations-and, furthermore, incorporates many advantages of digital environments-hyperlinks, multimedia, full-text search, automatic identification of synonyms, cross-referencing of key terms with an online encyclopedia, and an automatically generated back-of-the-book index. Usability studies were conducted to compare performance using these books for various reading tasks with HTML, PDF and physical books. Participants completed the tasks more efficiently with the new interface without any loss in accuracy; they also preferred it.

Computer graphics techniques for modeling page turning

Turning the page is a mechanical part of the cognitive act of reading that we do literally unthinkingly. Interest in realistic book models for digital libraries and other online documents is growing. Yet, actually producing a computer graphics implementation for modeling page turning is a challenging undertaking. There are many possible foundations: two-dimensional models that use reflection and rotation; geometrical models using cylinders or cones; mass-spring models that simulate the mechanical properties of paper at varying degrees of fidelity; and finite-element models that directly compute the actual forces within a piece of paper. Even the simplest methods are not trivial, and the more sophisticated ones involve detailed physical and mathematical models. The variety, intricacy, and complexity of possible ways of simulating this fundamental act of reading is virtually unknown. This article surveys computer graphics models for page turning. It combines a tutorial introduction that covers the range of possibilities and complexities with a mathematical synopsis of each model in sufficient detail to serve as a basis for implementation. Illustrations are included, which are generated through our implementations of each model. The techniques presented include geometric methods (both two- and three-dimensional), mass-spring models with varying degrees of accuracy and complexity, and finite-element models. We include a detailed comparison of experimentally determined computation time and subjective visual fidelity for all the methods discussed. The simpler techniques support convincing real-time implementations on ordinary workstations. We also address the question of whether such techniques are worthwhile in practice by describing results from a user study that compared the performance of a page-turning book model with HTML and PDF presentations of the same material—and with physical books. This demonstrates that the book model has many advantages over conventional document formats.

Searching in a book

Information has no value unless it is accessible. With physical books, most people rely on the table of contents and subject index to find what they want. But what if they are reading a book in a digital library and have access to a full-text search tool?. The paper describes a search interface to Realistic Books, and investigates the influence of document format and search result presentation on information finding. We compare searching in Realistic Books with searching in HTML and PDF files, and with physical books.

Efficient Process Model Discovery Using Maximal Pattern Mining

In recent years, process mining has become one of the most important and promising areas of research in the field of business process management as it helps businesses understand, analyze, and improve their business processes. In particular, several proposed techniques and algorithms have been proposed to discover and construct process models from workflow execution logs i.e., event logs. With the existing techniques, mined models can be built based on analyzing the relationship between any two events seen in event logs. Being restricted by that, they can only handle special cases of routing constructs and often produce unsound models that do not cover all of the traces seen in the log. In this paper, we propose a novel technique for process discovery using Maximal Pattern Mining MPM where we construct patterns based on the whole sequence of events seen on the traces--ensuring the soundness of the mined models. Our MPM technique can handle loops of any length, duplicate tasks, non-free choice constructs, and long distance dependencies. Our evaluation shows that it consistently achieves better precision, replay fitness and efficiency than the existing techniques.

Variant Map Construction to Detect Symmetric Properties of Genomes on 2D Distributions

Visualization Methods have played a key role in the Human Genome Project. After further development in other international projects such as ENCODE, larger numbers of Genome Databases are established and mass Genomewide gene expression measurements are developed. In current situation, it is necessary to shift targets in computational cell biology from collecting sequential data to making higher-level interpretation and exploring efficient content-based retrieval mechanism for genomes. Mammalian genomes encode thousands of large non-coding RNAs (lncRNAs), many of which regulate gene expression, interact with chromatin regulatory complexes, and are thought to play a role in localizing these complexes to target loci across the genome. Using higher dimensional visualization tools, their complex interactive properties could be organized as different visual maps. The Variant Map Construction VMC as an emerging scheme is systematically proposed in this paper to apply multiple maps that uses four Meta symbols as same as DNA or RNA representations. System architecture of key components and core mechanism on the VMC are described. Key modules, relevant equations and their I/O parameters are discussed. Using the VMC system, two DNA data sets of multiple real sequences are tested to show their visible properties in higher levels of intrinsic relationships among relevant DNA sequences in 2D maps. Visual results are briefly analyzed to explore their intrinsic properties and symmetric characteristics on relevant genome sequences under 2D maps of the Variant Map Construction. A set of sample 2D maps are included and their characteristics are illustrated under various controllable environment.

Lightweight realistic books: the greenstone connection

Realistic physically-based computer models of page-turning have been around for years, but are rarely deployed in practice except as eye-catching demos. This demo shows a connection from the Greenstone digital library system to a lightweight Macromedia Flash-based page turning mechanism that allows books in certain styles of collection to be automatically presented using animated page-turning. The system is reactive: it opens books quicker than Adobe Acrobat does and responds instantly to the user’s mouse gestures. It capitalizes on a particular style of structural metadata shared by many Greenstone collections, and uses metadata to enhance browsing the library’s contents. There are opposing views on whether readers may gain any advantage from using a 3D physical book model. There is enough evidence, both anecdotal and from formal user studies, to suggest that the usual (HTML or PDF) presentation of documents is not always the most convenient, or the most comfortable, for the reader. On the other hand it is quite clear that while 3D physical book models have been prototyped and demonstrated, none are in routine use in today’s DLs. Given the remarkable historical success of the book form, and the fact that the superiority of HTML or PDF presentation is at least questionable, why are physical book models not more widely available in practical digital libraries? We suggest that the answer is not because of any proven drawbacks, but is purely technological. Chu et al. [1] add a realistic book representation to Greenstone. However, although it makes an eye-catching demo the system is not used for actual reading, for several reasons: special “turning the pages” software must be installed on the reader’s computer; the system does not have access to external metadata such as cover images or internal metadata such as section breaks; and it is painfully slow. No doubt these could be ameliorated by improved implementations. However, informal observations of people using digital library collections in many different countries and environments is that even PDF readers are too slow, mainly because of the start-up delay. A different approach is called for if page turning is to be deployed in practice.

An evaluation on models for particle filtering for resident tracking in a smart home using binary sensors

Localization and tracking 1 are key components to enable personalized service in smart homes such as lifestyle support, energy management, and safety. To locate a person in a smart home, various sensors are installed. In this work, sensor data from only non Wifi-based devices and sensors such as PIR, pressure mat etc. are considered. The Particle filter has been adopted by many works because it has more advantages, e.g. accuracy, robustness, and efficiency, over the other techniques e.g. Kalman filter. Thus, we aim to analyze a set of motion models including random walk, random waypoint and Gaussian Markov model to find how applicable they are for an indoor setting and how they affect the accuracy of particle filter for indoor location estimation. We also analyze a set of sensor models. The result shows that the chosen motion models are applicable for an indoor environment if their parameters are adjusted properly. Random based models are more appropriate in this setting. However, information, such as behavior, activity, and location etc., should be considered to improve motion models. The accuracy of the particle filter is influenced by both motion and sensor models and their parameters such as walking speeds and degree of randomness, etc. Thus, the inaccurate prediction is produced if an improper model and its parameters are used and it is very difficult to correct. In addition, improper sensor models can cause each particle to be weighted incorrectly. Therefore, the estimation is not accurate.

A Framework for Evaluating Anti Spammer Systems for Twitter

Despite several benefits to modern communities and businesses, Twitter has attracted many spammers that have overwhelmed legitimate users with unwanted and disruptive advertising and fake information. Detecting spammers is always challenging because of the huge volume of data that needs to be analyzed while spammers continue to learn and adapt to avoid being detected by anti-spammer systems. Several spam classification systems are proposed that use various features extracted from the content and user’s information from their Tweets. Nevertheless, no comprehensive study has been done to compare and evaluate the effectiveness and efficiency of these systems. It is not known what the best anti-spammer system is and why. This paper proposes an evaluation framework that allows researchers, developers, and practitioners to access existing user-based and content-based features, implement their own features, and evaluate the performance of their systems against other systems. Our framework helps identify the most effective and efficient spammer detection features, evaluate the impact of using different numbers of recent tweets, and therefore obtaining a faster and more accurate classifier model.