This paper presents an investigation into user intention prediction in two common web-based tasks: crowdsourcing annotation and web search, based on human-mouse interaction information. User experience is gaining importance within the research area of human-centered computing, and is particularly useful for complex, multi-step tasks. To enhance user experience, the computer should be intelligent enough to be able to predict the user intention. For instance, an intelligent agent might be able to anticipate when the user is about to press a button, and helpfully enlarge or highlight it in advance. In this paper, we propose two prediction models on user intention: a classical model that considers only historical mouse activity sequence, and a multimodal model that utilizes mouse interaction signals as well as features extracted from mouse trajectory and clicking events. We evaluate our models and find that they achieve reasonable accuracy. Our preliminary results indicate that we can dynamically learn a multimodal model that can effectively predict a user's next activity from historical activity sequence and mouse interaction signals.

We present PACE, a Personalized, Automatically Calibrating Eye-tracking system that identifies and collects data unobtrusively from user interaction events on standard computing systems without the need for specialized equipment. PACE relies on eye/facial analysis of webcam data based on a set of robust geometric gaze features and a two-layer data validation mechanism to identify good training samples from daily interaction data. The design of the system is founded on an in-depth investigation of the relationship between gaze patterns and interaction cues, and takes into consideration user preferences and habits. The result is an adaptive, data-driven approach that continuously recalibrates, adapts and improves with additional use. Quantitative evaluation on 31 subjects across different interaction behaviors shows that training instances identified by the PACE data collection have higher gaze point-interaction cue consistency than those identified by conventional approaches. An in-situ study using real-life tasks on a diverse set of interactive applications demonstrates that the PACE gaze estimation achieves an average error of 2.56º, which is comparable to state-of-the-art, but without the need for explicit training or calibration. This demonstrates the effectiveness of both the gaze estimation method and the corresponding data collection mechanism.

This paper presents Personalized Affect Detection with Minimal Annotation (PADMA), a user-dependent approach for identifying affective states from spontaneous facial expressions without the need for expert annotation. The conventional approach relies on the use of key frames in recorded affect sequences and requires an expert observer to identify and annotate the frames. It is susceptible to user variability and accommodating individual differences is difficult. The alternative is a user-dependent approach, but it would be prohibitively expensive to collect and annotate data for each user. PADMA uses a novel Association-based Multiple Instance Learning (AMIL) method, which learns a personal facial affect model through expression frequency analysis, and does not need expert input or frame-based annotation. PADMA involves a training/calibration phase in which the user watches short video segments and reports the affect that best describes his/her overall feeling throughout the segment. The most indicative facial gestures are identified and extracted from the facial response video, and the association between gesture and affect labels is determined by the distribution of the gesture over all reported affects. Hence both the geometric deformation and distribution of key facial gestures are specially adapted for each user. We show results that demonstrate the feasibility, effectiveness and extensibility of our approach.

Social signal processing is becoming an important topic in affective computing. In this paper, we focus on an important social interaction in real life, namely, fighting. Fight detection will be useful in public transportation, prisons, bars, or even sport. A robust mechanism in detecting fights from a video will be extremely useful, especially in applications relevant to surveillance systems. Recent research works focus on extracting visual features from high resolution video, leading to computationally expensive systems. In this paper, we propose an approach to detect fights in a natural and robust way based on motion analysis, which is not only intuitive, but also robust. Experimental results show that we can accurately detect fight activities in different video surveillance settings.

Service learning has been gaining attention in recent years. It has been established as an effective method to teach students a variety of concepts that are not easily taught in the classroom, and much effort has gone into making service learning accessible and relevant to computer science students. This paper investigates a popular mode of computing-related service learning -- offshore projects that seek to introduce information and computing technologies (ICTs) into a beneficiary population. Based on multiple years of experience working with ICTs in service learning, the authors examine the impact on students and beneficiaries through several critical questions, and draw conclusions and recommendations on good practices for designing offshore service learning projects for computing students.

This paper presents KID, an interactive app on a smart device, designed to facilitate and encourage young children to learn and practice Chinese characters. It relies on pen dynamics to extract the strokes and map the written character to the proper one. The stroke orientation is also analyzed for ordering and spatial alignment features that pinpoint common errors. A visual pictorial feedback is then provided to motivate children and to arouse their interest. We iterate the prototype design and implementation upon collecting feedback from focus group interviews, from where the system is greeted with positive comments.

Most eye gaze estimation systems rely on explicit calibration, which is inconvenient to the user, limits the amount of possible training data and consequently the performance. Since there is likely a strong correlation between gaze and interaction cues, such as cursor and caret locations, a supervised learning algorithm can learn the complex mapping between gaze features and the gaze point by training on incremental data collected implicitly from normal computer interactions. We develop a set of robust geometric gaze features and a corresponding data validation mechanism that identifies good training data from noisy interaction-informed data collected in real-use scenarios. Based on a study of gaze movement patterns, we apply behavior-informed validation to extract gaze features that correspond with the interaction cue, and data-driven validation provides another level of crosschecking using previous good data. Experimental evaluation shows that the proposed method achieves an average error of 4.06º, and demonstrates the effectiveness of the proposed gaze estimation method and corresponding validation mechanism.

As computer and interaction technologies mature, a much broader range of media is now used for input and output, each of which has its own rich repertoire of techniques, instruments, and cultural heritage. The combination of multiple media can produce novel multimedia human-computer interaction approaches which are more efficient and interesting than traditional single media methods. This paper presents CalliPaint, a system for cross-modal art generation that links together Chinese ink brush calligraphy writing and Chinese landscape painting. We investigate the mapping between the two modalities based on concepts of metaphoric congruence, and implement our findings into a prototype system. A multi-step evaluation experiment with real users suggests that CalliPaint provides a realistic and intuitive experience that allows even novice users to create attractive landscape paintings from writing. Comparison with a general-purpose digital painting software suggests that CalliPaint provides users with a more enjoyable experience. Finally, exhibiting CalliPaint in an open-access location for use by casual users without any training shows that the system is easy to learn.

This article presents the design and development of i*CATch, a construction kit for physical and wearable computing that was designed to be scalable, plug-and-play, and to provide support for iterative and exploratory learning. It consists of a standardized construction interface that can be adapted for a wide range of soft textiles or electronic boards, a set of functional components, and an easy-to-use hybrid text-graphical integrated development environment. The objective was to design an easily usable, manufacturable and extensible construction kit that can be used in a wide range of teaching tasks for a wide variety of student demographic profiles. We present detailed specifications of our construction kit and explain some of the major design decisions. Experiences in using the kit in multiple teaching environments, ranging from elementary school to postgraduate, demonstrate that the design objectives have been achieved.

MelodicBrush is a novel system that connects two ancient art forms: Chinese ink-brush calligraphy and Chinese music. Our system uses vision-based techniques to create a digitized ink-brush calligraphic writing surface with enhanced interaction functionalities. The music generation combines cross-modal stroke-note mapping and statistical language modeling techniques into a hybrid model that generates music as a real-time, auditory response and feedback to the user's calligraphic strokes.

There has been much recent work in wearable computing that is directed at democratization of the field, to make it more accessible to the general public and more easily used by the hobbyist user. As the field becomes more diversified, there has also been a shift away from the highly specialized functionality of earlier applications towards aesthetics, creativity, design and self-expression, as well as a push towards using wearable computing as an outreach tool to broaden interest and exposure in engineering and computing.

In this paper, we propose a novel approach, Cyclic Signature (CS) clustering, to analyze spatial-temporal pattern. CS clustering is based on the calendar regularities of events to analyze spatial-temporal patterns. An experiment, based on a set of reported crime data for a district in Hong Kong, was performed to compare CS clustering against traditional clustering approaches. The results show that CS clustering can provide information which differs greatly from traditional clustering approaches. In addition, the groups created by CS clustering have higher intra-cluster similarities and lower inter-cluster similarities than traditional clustering approaches.

This paper introduces the Multi-modal Interface Framework (MIF). It is a system which allows developers to easily integrate interface devices of multiple modalities, such as voice, hand and finger gestures, and various tangible devices such as game controllers into a multi-modal input system. The integrated devices can then be used to control practically any computer application. The advantages offered by MIF are ease of use, flexibility and support for collaboration. Its design has been validated by applying it to integrate finger gestures, voice, a Wii mote and an iPhone to control applications such as Google Earth and Windows Media Player.

Controlling a team of robots is much more challenging than controlling an individual robot. Users desire high level commands that shield the users from too much detail, and yet still afford the desired precision of control. This project aims to design a method through which a team of robots can be controlled as easily and precisely as an individual robot. A simple language in the form of a set of finger gestures allows the user to give general motion commands to the team of robots. The gestures are supplemented by fine controls such as speed through tangible input gadgets. The gesture-based language has been implemented in a prototype user interface on a multi-touch screen. A number of test applications demonstrate the validity of the design.

Abstract We studied the effectiveness of a new class of context‐dependent term weights for information retrieval. Unlike the traditional term frequency–inverse document frequency (TF–IDF), the new weighting of a term t in a document d depends not only on the occurrence statistics of t alone but also on the terms found within a text window (or “document‐context”) centered on t. We introduce a Boost and Discount (B&D) procedure which utilizes partial relevance information to compute the context‐dependent term weights of query terms according to a logistic regression model. We investigate the effectiveness of the new term weights compared with the context‐independent BM25 weights in the setting of relevance feedback. We performed experiments with title queries of the TREC‐6, ‐7, ‐8, and 2005 collections, comparing the residual Mean Average Precision (MAP) measures obtained using B&D term weights and those obtained by a baseline using BM25 weights. Given either 10 or 20 relevance judgments of the top retrieved documents, using the new term weights yields improvement over the baseline for all collections tested. The MAP obtained with the new weights has relative improvement over the baseline by 3.3 to 15.2%, with statistical significance at the 95% confidence level across all four collections.

The field of wearable computing and e-textiles has recently attracted much interest from the research and general community. Recent developments in this field raises the possibility of e-textile construction kits for hobbyists and novices alike. The unique nature of wearable computing and e-textiles also gives it a lot of potential as an educational computing topic, as it allows students to exercise their creativity and imagination while learning about computing and technology.

Airfreight forwarding is becoming more important with the increase of international trade. For an international company, sometimes, it would have several branches associating with different airports in the same region. When a branch is overloaded, nearby branches of different airports can offer help and share the workload. A framework of agents has been proposed to support collaborative cargo packing for multi-sites in the same region. Besides defining a set of XML message exchange standards in the framework, a core component is the packing module which is supported by RFID tags with information encoded. This paper discusses how to apply First Fit Decreasing and Best Fit Decreasing for packing airfreight cargoes and their preliminary performance.

Advances in textile-friendly electronics devices, smart materials, sophisticated interfaces, and intelligent software have combined to make intelligent garments increasingly practical. This paper introduces Co-eTex, a framework designed to support collaborative development of intelligent garments. It is based on a newly-invented construction platform for eTextiles and Wearable Computing, which was designed to be robust, reliable, easy to construct and to program. It also includes a hybrid graphical-textual programming tool designed for novice programmers to program intelligent behaviour for intelligent garments. We describe the use of Co-eTex in rapidly developing prototypes for a variety of designs of intelligent garments. Based on our experiences in using the Co-eTex, we believe it is a possible direction leading to the development of mass customization or adaptive customization of intelligent garments.

This paper presents a design for a platform of collaborative robots and electronic devices. The platform design is based on the similarity between the type, functionality and characteristics of the robot or device. We categorize the participating devices by functionality rather than by architecture, therefore making it easy to support new robots or devices with similar functions but different architectures. This approach also allows users to develop, implement and port applications quickly and easily. We demonstrate the efficacy and correctness of our platform through a variety of robotic applications ranging from research to teaching.

To address the unique demands and challenges of educational computing, various kinds of environments, including graphics-rich and textual environments, have been proposed for use in introductory courses to provide students with a rich and interesting learning environment. In our experience, students in Grade 7 and younger respond best to the graphics environments while senior high school students prefer a conventional textual programming environment. Clearly, this leaves a gap at Grade 11-13, with students often on the one hand finding the graphics-based environments too limited and on the other finding the textual environments too difficult. In this paper, we propose a text-enhanced graphical programming environment which is innovative and interactive, and designed for junior high students with no programming experience. This environment allows students to design their own creative stories or programs. They build their programs using drag-and-drop iconic blocks, but unlike other, similar icon-based programming languages, they are also presented with the syntax of the actual program they are constructing in real-time. Once a particular icon block has been dropped in the programming area, the syntax statements corresponding to that block is immediately generated and presented to the user. The environment also allows them to modify the code without any limitations. Our results show that our textual-graphical hybrid environment has a positive impact on the learning experience of the students.

As enrollments in engineering and computer science programs around the world have fallen in recent years, those who wish to see this trend reversed take heart from findings that children are more likely to develop an abiding interest in technology if they are exposed to it at an early age [3, 9]. In line with this research, we now see more summer camps and workshops being offered to middle school students with the objective of teaching programming and computer technology [1, 6, 8, 12]. To offer students a stimulating and interesting environment while teaching computing subjects, the learning tools in these camps usually revolve around robots and graphical programming of animations or games. These tools tend to mainly attract youngsters who like robotics or game design. However, we believe that we can improve the diversity of the student pool by introducing other topics. In this paper, we describe our experience in designing and organizing a programming course that focuses on wearable computing, fashion and design for middle school students. We will show that 1) wearable computing is interesting and inspiring to the students, 2) wearable computing motivates both boys and girls to learn technology and computing, which implies that it may be able to increase the potential computer science population, 3) wearable computing can provide a space for students to exercise their creativity while at the same time, teaching them about technology and programming.

Given a set of clusters, we consider an optimization problem which seeks a subset of clusters that maximizes the microaverage F-measure. This optimal value can be used as an evaluation measure of the goodness of clustering. For arbitrarily overlapping clusters, finding the optimal value is NP-hard. We claim that a greedy approximation algorithm yields the global optimal solution for clusters that overlap only by nesting. We present a mathematical proof of this claim by induction. For a family of n clusters containing a total of N objects, this algorithm has an {\rm O}(n;{2}) time complexity and O(N) space complexity.

Spatial analysis plays a key role in crime prevention. Traditional approaches such as clustering can find static patterns but do not consider the change of spatial patterns over time. In this paper, we introduce a new analysis framework, Dynamic Pattern Analysis Framework (DPA Framework) focusing on two types of related dynamic patterns: the displacement or diffusion of spatial patterns over time and the similarity between spatial patterns of different periods. The new framework aims to support cooperative crime prevention in a district of Hong Kong.

Abstract We propose a new optimal clustering effectiveness measure, called CS1, based on a combination of clusters rather than selecting a single optimal cluster as in the traditional MK1 measure. For hierarchical clustering, we present an algorithm to compute CS1, defined by seeking the optimal combinations of disjoint clusters obtained by cutting the hierarchical structure at a certain similarity level. By reformulating the optimization to a 0‐1 linear fractional programming problem, we demonstrate that an exact solution can be obtained by a linear time algorithm. We further discuss how our approach can be generalized to more general problems involving overlapping clusters, and we show how optimal estimates can be obtained by greedy algorithms.

To cope with the continuing growth of the web, improvements should be made to the current brute-force techniques commonly used by robot-driven search engines. We propose a model that strikes a balance between robot and directorybased search engines by expanding the search scope of conventional directories to automatically include related categories. Our model makes use of a knowledge-rich and wellstructured corpus to infer relationships between documents and topic categories. We show that the hyperlink structure of Wikipedia articles can be effectively exploited to identify relations among topic categories. Our experiments show the average recall rate and precision rate achieved are 91% and between 85% and 215% of Google's respectively.

This paper presents a pilot study of query-specific clustering that uses our novel document-context based similarity scores as compared with document similarity scores. Clustering is applied to the top 1000 retrieved documents for a given query. Clustering effectiveness is evaluated based on the MK1 score for TREC-2, TREC-6 and TREC-7 test collections. Encouraging results were obtained whereby document-context clustering produces better MK1 scores than document clustering with a 95% confidence level if precision and recall are equally important.

Similar Web pages of Web sites on the World Wide Web are usually encoded from an underlying structured source, and generated dynamically from a pre-defined template, such as books' information pages in Amazon.com. By giving a set of Web pages from a common Website, it is possible to extract the template by analyzing common patterns between the Web pages. In our work, we developed the CF-EXALG (collaborative finer-EXALG), based on EXALG, to decompose Web pages and finding their common structures. In our system, templates that are used to generate Web pages can be discovered automatically and stored in XML format. Hence, data encoded in Web pages can be easily extracted and the template can be stored for future manipulation. In our preliminary experiments, CF-EXALG has shown to be more accurate and efficient when compared with other similar systems

The ability to interactively and collaboratively configure and re-configure 3D products on the Internet is an important facilitator for e-commerce. We describe the design of such a system, Co-assembler, that enables casual customers to perform limited configurations of 3D products over the Internet. We discuss the technical challenges and outline our solution. We also describe the application of artificial intelligence to assist the customer in configuring the desired product, The system aims to capture customers' needs and convert them into technical specifications, helping to facilitate e-commerce for manufacturing enterprises.

Abstract The monitor concept provides a structured and flexible high‐level programming construct to control concurrent accesses to shared resources. It has been widely used in a concurrent programming environment for implicitly ensuring mutual exclusion and explicitly achieving process synchronization. This paper proposes an extension to the monitor construct for detecting runtime errors in monitor operations. Monitors are studied and classified according to their functional characteristics. A taxonomy of concurrency control faults over a monitor is then defined. The concepts of a monitor event sequence and a monitor state sequence provide a uniform approach to history information recording and fault detection. Rules for detecting various types of faults are defined. Based on these rules, fault‐detection algorithms are developed. A prototypical implementation of the proposed monitor construct with runtime fault detection mechanisms has been developed in Java. We shall briefly report our experience with and the evaluation of the robust monitor prototype. Copyright © 2005 John Wiley & Sons, Ltd.

In recent years, Web services are getting popular. In order to have more reliable services on the Internet, QoS (quality of service) plays an important role. We extend the WSDL with an optional attribute in order to control the level of QoS. The extension enables Web services providers to support partial request satisfaction by a priority attribute controlling the priorities of WSDL requests and the corresponding sub-requests. We have performed a set of experiments to demonstrate the significance of the partial request satisfaction by with a range of values of the priority attribute. The results are interesting and demonstrated the usefulness of the new parameter.

This paper describes an agent framework to support spatial data mining of air pollution data. A Web-based solution, APMF (Air Pollution Mining Framework), is developed to investigate the effect of meteorological and air pollutant elements on air pollution. It makes use of three types of agents: collect agents, coordinate agents and query/mining agents. Query/mining agents interact with the user, receive user queries and mining requests, and deliver the results. Coordinate agents help to prepare the data resources for the querying tasks. Collect agents provide access to a heterogeneous collection of Web sources. In order to standardize data exchanges and query/mining process descriptions, an XML-based language, DQML, is developed. A prototype of the APMF is implemented with a Java servlet and JavaLite.

The concept of mediation has been successfully applied to the development of distributed information systems, where mediators form the middle tier between client applications and data resources, providing valuable abstraction and integration functions. Using XML, common data models and interfaces can be developed for mediators for deployment in Web -based information systems, making such systems easier to develop, to maintain, and to evolve. This paper discusses the design of such an architecture, and its application in retail inventory control in electronic commerce.