Informing the Design of Direct-Touch Tabletops
Tables provide a large and natural interface for supporting direct manipulation of visual content for human-to-human interactions. Such surfaces also support collaboration, coordination, and parallel problem solving. However, the direct-touch table metaphor also presents considerable challenges, including the need for input methods that transcend traditional mouse- and keyboard-based designs. In this paper, we've designed, implemented, and studied a variety of tabletop user interfaces, interaction techniques, and usage scenarios

title: Under My Finger: Human Factors in Pushing and Rotating Documents Across the Table
abstract: When passing a document to someone across a table, the person passing the document often rotates it to face the receiver. In this paper, we present the results of a user evaluation of three Push-and-Rotate schemes that offer different underlying control semantics for how an electronic document can automatically rotate as it is pushed across an interactive tabletop surface. The effects of document size are also discussed.

title: Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays
abstract: Recent advances in sensing technology have enabled a new generation of tabletop displays that can sense multiple points of input from several users simultaneously. However, apart from a few demonstration techniques [17], current user interfaces do not take advantage of this increased input bandwidth. We present a variety of multifinger and whole hand gestural interaction techniques for these displays that leverage and extend the types of actions that people perform when interacting on real physical tabletops. Apart from gestural input techniques, we also explore interaction and visualization techniques for supporting shared spaces, awareness, and privacy. These techniques are demonstrated within a prototype room furniture layout application, called RoomPlanner.

title: Participatory design of an orientation aid for amnesics
abstract: We present the participatory design and evaluation of an orientation aid for individuals who have anterograde amnesia. Our design team included six amnesics who have extreme difficulty storing new memories. We describe the methods we used to enable the participation of individuals with such severe cognitive impairments. Through this process, we have conceived, designed, and developed the OrientingTool, a software application for Personal Digital Assistants that can be used by amnesics to orient themselves when feeling lost or disoriented. Two complementary studies were conducted to evaluate the effectiveness of this tool in ecologically valid contexts. Our findings suggest that the OrientingTool can improve an amnesic's independence and confidence in managing situations when disoriented, and that participatory design may be productively used with participants who have significant cognitive disabilities.

title: Question-driven classification of retrieved documents
abstract: Many existing information access systems deliver ranked lists of documents in response to users' queries. Some systems also endeavour to represent some of the various types of relationships that can exist between documents. However, few systems provide effective mechanisms to help users discover useful information within the set of retrieved documents. In this paper, we present a question-driven approach to delivering retrieved documents in an attempt to organize them in a way that is closer to the user's mental representation of the expected answer. In our proposed approach, retrieved documents are dynamically classified into categories; an appropriate classification scheme is selected by a user on the basis of his own understanding of the information need. Experimental results show that users are more satisfied with such a directed categorization than with a list of retrieved documents.

title: Dynamic resource allocation via video content and short-term traffic statistics
abstract: Dynamic resource allocation is critical in the transmission of VBR video. Our study shows that content is one of the major factors that controls the bandwidth of the video bit-stream, yet content alone may not be sufficient in predicting future traffic and in determining how much resource to request. A new framework of traffic prediction is proposed, taking into account both content features and available short-term bandwidth statistics.

title: Data hiding in binary image for authentication and annotation
abstract: This paper proposes a new method to embed data in binary images, including scanned text, figures, and signatures. The method manipulates "flippable" pixels to enforce specific block-based relationship in order to embed a significant amount of data without causing noticeable artifacts. Shuffling is applied before embedding to equalize the uneven embedding capacity from region to region. The hidden data can be extracted without using the original image, and can also be accurately extracted after high quality printing and scanning with the help of a few registration marks. The proposed data embedding method can be used to detect unauthorized use of a digitized signature, and annotate or authenticate binary documents. The paper also presents analysis and discussions on robustness and security issues.

title: Supervised probabilistic principal component analysis
abstract: Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When labels of data are available, e.g., in a classification or regression task, PCA is however not able to use this information. The problem is more interesting if only part of the input data are labeled, i.e., in a semi-supervised setting. In this paper we propose a supervised PCA model called SPPCA and a semi-supervised PCA model called S2PPCA, both of which are extensions of a probabilistic PCA model. The proposed models are able to incorporate the label information into the projection phase, and can naturally handle multiple outputs (i.e., in multi-task learning problems). We derive an efficient EM learning algorithm for both models, and also provide theoretical justifications of the model behaviors. SPPCA and S2PPCA are compared with other supervised projection methods on various learning tasks, and show not only promising performance but also good scalability.

title: Encoded bitmap indexing for data warehouses
abstract: Complex query types, huge data volumes, and very high read/update ratios make the indexing techniques designed and tuned for traditional database systems unsuitable for data warehouses (DW). We propose an encoded bitmap indexing for DWs which improves the performance of known bitmap indexing in the case of large cardinality domains. A performance analysis and theorems which identify properties of good encodings for better performance are presented. We compare encoded bitmap indexing with related techniques, such as bit slicing, projection-, dynamic-, and range-based indexing.