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We present the rationale, description, and critique of a first course in image computing that is not a traditional computer vision principles-and-tools course. "Visual Interfaces to Computers" is instead complementary to standard Computer Vision, User Interface, and Graphics courses; in fact, VI:CV::UI:G. It is organized by case studies of working visual systems that use camera input for data or control information in service of higher user goals, such as GUI control, user identification, or automobile steering. Many CV scientific principles and engineering tools are therefore taught, as well as those of psychophysics, AI, and EE, but taught selectively and always within the context of total system design. Course content is derived from conference and journal articles and Ph.D. theses, augmented with video tapes and real-time web site demos. Students do two homework assignments, one to design a "visual combination lock", and one to parse an image into English. They also do a final paper or project of their own choosing, often in teams of two, and often with surprisingly deep results. The course is assisted by a custom C-based tool kit, "XILite", a user-friendly (and comparatively bug-free) modification of Sun's X-windows Image Library for our lab's camera-equipped Sun workstations. The course has been offered twice to a wide audience with good reviews. [ABSTRACT FROM AUTHOR]

This paper presents a vision based technique to identify the unspoken phones using a small camera that is located on the headset of the speaker. The system is based on temporal integration of the video data to generate motion history image (MHI). The paper proposes the use of global features to classify the MHI and compares the use of image moments with Discrete Cosine Transform (DCT). A comparison between Zernike moments (ZM) with DCT indicates that while the accuracy of classification for both techniques is very comparable (96% for ZM and 94% for DCT) when there is no relative motion between the camera and the mouth, ZM is resilient to rotation of the camera and continues to gives good results despite rotation but DCT is sensitive to rotation. Based on the accuracy of the system and its resilience to movement artefacts such as rotation, the authors propose the use of such a system for human computer interface. Such a system could be invaluable when it is important to communicate without making a sound, such as giving passwords when in an open office or in public spaces. [ABSTRACT FROM AUTHOR]

The rapid evolution of Brain-Computer Interface (BCI) technology and the exponential growth of BCI literature during the past 20 years is a consequence of increasing computational power and the achievements of statistical learning theory and machine learning since the 1960s. Despite this rapid scientific progress, the range of successful clinical and societal applications remained limited, with some notable exceptions in the rehabilitation of chronic stroke and first steps towards BCI-based assisted verbal communication in paralysis. In this contribution, we focus on the effects of noninvasive and invasive BCI-based verbal communication on the quality of life (QoL) of patients with amyotrophic lateral sclerosis (ALS) in the locked-in state (LIS) and the completely locked-in state (CLIS). Despite a substantial lack of replicated scientific data, this paper complements the existing methodological knowledge and focuses future investigators' attention on (1) Social determinants of QoL and (2) Brain reorganization and behavior. While it is not documented in controlled studies that the good QoL in these patients is a consequence of BCI-based neurorehabilitation, the proposed determinants of QoL might become the theoretical background needed to develop clinically more useful BCI systems and to evaluate the effects of BCI-based communication on QoL for advanced ALS patients and other forms of severe paralysis. [ABSTRACT FROM AUTHOR]

It is very useful in the human computer interface to quickly and accurately recognize human hand movements in real time. In this paper, we aimed to robustly recognize hand gestures in real time using Convolutional Recurrent Neural Network (CRNN) with pre-processing and overlapping window. The CRNN is a deep learning model that combines Long Short-Term Memory (LSTM) for time-series information classification and Convolutional Neural Network (CNN) for feature extraction. The sensor for hand gesture detection uses Myo-armband, and six hand gestures are recognized and classified, including two grips, three hand signs, and one rest. As the essential pre-processing due to the characteristics of EMG data, the existing Short Time Fourier Transform (STFT), Continuous-time Wavelet Transform (CWT), and newly proposed Scale Average Wavelet Transform (SAWT) are used, and thus, the SAWT showed relatively high accuracy in the stationary environmental test. The CRNN with overlapping window has been proposed that can improve the degradation of real-time prediction accuracy, which is caused by inconsistent start time and hand motion speed when acquiring the EMG signal. In the stationary environmental test, the CRNN model with SAWT and overlapping window showed the highest accuracy of 92.5%. In the real-time environmental test, for all subjects learning, 80% accuracy and 0.99 s time delay were obtained on average, and for individual learning, 91.5% accuracy and 0.32 s time delay were obtained on average. As a result, in both stationary and real-time tests, the CRNN with SAWT and overlapping window showed better performance than the other methods. [ABSTRACT FROM AUTHOR]

The major drivers for complex applications are cost, efficiency, development time, understandability, usability and more importantly the maintainability. Due to their black box nature, complexity of software components is more crucial for component-based systems. This paper discusses various complexity concerns for these systems and reviews a number of complexity metrics for software components and component-based systems. As interfaces are the only source of information to know about the black-box components, this paper proposes a new interface complexity metric for these components. This metric is based on the information available in the interfaces like interface methods and properties. It also discusses the methodology to assign the weight values to these methods and properties to finally evaluate the complexity of the component. This paper validates the proposed metric against standard Weyukar's properties and empirically evaluates the metric for several Java Bean components. Finally a correlation analysis between proposed metrics and several other metrics like performance, customizability and readability is done to validate the metric. [ABSTRACT FROM AUTHOR]

A simple contract contains formalizing preconditions, postconditions, and invariants. A contract describes the services that are provided by an object. In the component world, it is essential to describe correctly what services are provided by the components and how we can use them. Till now, interfaces are specified in IDL, which describes the syntactic aspect of interface. IDL cannot describe the semantic aspects and safety condition of a component that a client and a server must know how to use or implement it. In this paper, we use contracts specifying components and propose an interface specification technique to describe components as a contract(namely, component contract). We regard a component's interface as contract and present which aspect to be specified for providing correct information of the components. This paper defines some definitions and describes operators such as cooperating components, component version, functional requirements, nonfunctional requirements, and performance measurements to specify components, and specifies them using Z scheme. Finally, we apply this interface specification technique to develop an e-commerce system. [ABSTRACT FROM AUTHOR]

Modern shell scripts provide interfaces with rich functionality for system administration. However, it is not easy for end-users to write correct shell scripts; misusing commands may cause unpredictable results. In this paper, we present SmartShell, an automated function-based tool for shell script synthesis, which uses natural language descriptions as input. It can help the computer system to "understand" users' intentions. SmartShell is based on two insights: (1) natural language descriptions for system objects (such as files and processes) and operations can be recognized by natural language processing tools; (2) system-administration tasks are often completed by short shell scripts that can be automatically synthesized from natural language descriptions. SmartShell synthesizes shell scripts in three steps: (1) using natural language processing tools to convert the description of a system-administration task into a syntax tree; (2) using program-synthesis techniques to construct a SmartShell intermediate-language script from the syntax tree; (3) translating the intermediate-language script into a shell script. Experimental results show that SmartShell can successfully synthesize 53.7% of tasks collected from shell-script helping forums. [ABSTRACT FROM AUTHOR]

The Standard Test Interface Language (STIL) is the de-facto standard for transferring test data between the test generation environment and the test equipment. STIL's flexibility and extensibility facilitates its use as the sole input language for automatic test-pattern generation (ATPG). However, STIL format is complex and does not provide support for algorithmic interactive testing which necessitate the use of additional programming languages to do that. In this paper, we propose a new Test Definition Language for Integrated Circuits (TDLIC) based on the Extensible Markup Language (XML). TDLIC is a description language for defining tests of digital ICs in a precise and reusable form. The proposed TDLIC provides a common platform for specifying test data as well as complex test procedures. A case study that includes a validation platform is used to show the full capabilities of TDLIC. The validation platform is an FPGA-based system that emulates the automatic test equipment and a prototype IC with four circuits to be tested. [ABSTRACT FROM AUTHOR]

Besides the tremendous progress in web-related technologies, interfaces to access the web or large information systems have largely stayed at the level of keyword searches and categorical browsing. This paper introduces analogy queries as one of the essential techniques required to bridge the gap between today's interfaces and future interaction paradigms. The intuitive concept of analogies is directly derived from human cognition and communication practices, and is in fact often considered to be the core concept of human cognition. In brief, analogies form abstract relationships between concepts, which can be used to efficiently exchange information and knowledge needs or transmit even complex concepts including important connotations in a strictly human-centred and natural fashion. Building of analogy-enabled information systems opens up a number of interesting scientific challenges, e.g. how does communication using analogies work? How can this process be represented? How can information systems understand what a user provided analogy actually means? How can analogies be discovered? This paper aims at discussing some of these questions and is intended as a corner stone of future research efforts. [ABSTRACT FROM AUTHOR]

The automotive industry is facing a tremendous growth in the engineering of software-in-tensive systems, giving rise to various challenges. To prevent problems related to the fit of new software technologies in vehicles and the manufacturing processes, a well functioning inter-action between the functions for product development and manufacturing is crucial. This is complicated by the fact that the changeable nature of software development causes unprec-edented needs for collaboration and coordination between these two functions. This paper reports on a process assessment that focuses on the interface between the functions for product development and manufacturing in the development and design of software-intensive automotive systems. The main purpose of the study was to identify the key issues for im-provement in the area assessed. The assessment was performed at two Swedish automotive companies where data were collected from documents and in interviews with practitioners. Nine key improvement issues were established ranging from challenges in requirements engi-neering to the need for knowledge transfer between manufacturing and product development. In addition, to increase the understandability of the results and map possible avenues for solution and future research, the paper provides an extensive analysis of each improvement issue in relation to the state-of-the-art. [ABSTRACT FROM AUTHOR]

A better understanding of events many times requires the association and the efficient representation of multi-modal information. A good approach to this important issue is the development of a common platform for converting different modalities (such as images, text, etc.) into the same medium and associating them for efficient processing and understanding. In a previous paper we have presented a Local-Global graph model for the conversion of images into graphs with attributes and then into natural language (NL) text sentences [25]. Here, in this paper we propose the conversion of NL text sentences into graphs and then into Stochastic Petri-nets (SPN) descriptions in order to efficiently offer a model of associating "activities or changes" in multimodal information for events representation and understanding. The selection of the SPN graph model is due to its capability for efficiently representing structural and functional knowledge. Simple illustrative examples are provided for proving the concept proposed here. [ABSTRACT FROM AUTHOR]

A great deal of data on the Web lies in the hidden databases, or the deep Web. Most of the deep Web data is not directly available and can only be accessed through the query interfaces. Current research on deep Web search has focused on crawling the deep Web data via Web interfaces with keywords queries. However, these keywords-based methods have inherent limitations because of the multi-attributes and top-k features of the deep Web. In this paper we propose a novel approach for siphoning structured data with structured queries. Firstly, in order to retrieve all the data non-repeatedly in hidden databases, we model the hidden database as a hierarchy tree. Under this theoretical framework, data retrieving is transformed into the traversing problem in a tree. We also propose techniques to narrow the query space by using heuristic rule, based on mutual information, to guide the traversal process. We conduct extensive experiments over real deep Web sites and controlled databases to illustrate the coverage and efficiency of our techniques. [ABSTRACT FROM AUTHOR]

Facial expression provides an important behavioral measure for studies of emotion, cognitive processes, and social interaction. Facial expression recognition has recently become a promising research area. Its applications include human-computer interfaces, human emotion analysis, and medical care and cure. In this paper, we investigate various feature representation and expression classification schemes to recognize seven different facial expressions, such as happy, neutral, angry, disgust, sad, fear and surprise, in the JAFFE database. Experimental results show that the method of combining 2D-LDA (Linear Discriminant Analysis) and SVM (Support Vector Machine) outperforms others. The recognition rate of this method is 95.71% by using leave-one-out strategy and 94.13% by using cross-validation strategy. It takes only 0.0357 second to process one image of size 256 × 256. [ABSTRACT FROM AUTHOR]

In this paper, a recently developed machine learning algorithm referred to as Extreme Learning Machine (ELM) is used to classify five mental tasks from different subjects using electroencephalogram (EEG) signals available from a well-known database. Performance of ELM is compared in terms of training time and classification accuracy with a Backpropagation Neural Network (BPNN) classifier and also Support Vector Machines (SVMs). For SVMs, the comparisons have been made for both 1-against-1 and 1-against-all methods. Results show that ELM needs an order of magnitude less training time compared with SVMs and two orders of magnitude less compared with BPNN. The classification accuracy of ELM is similar to that of SVMs and BPNN. The study showed that smoothing of the classifiers' outputs can significantly improve their classification accuracies. [ABSTRACT FROM AUTHOR]

As Internet computing becomes a norm in everyday life, web-based learning is acceptable to many people. However, it is a challenge to learn data modeling on the Internet. Not only is it difficult to guide the users through the operations of e-Learning, but also it is hard to measure its effectiveness. This paper presents a methodology of using interactivity of guiding the user through a case study to learn the discipline of stepwise procedure of data modeling. With well documented data modeling theories on the web pages, the user has to answer the question correctly by selecting the right choice step by step to complete a case study. As a result, the user learns the correct way of data modeling through interactive learning on the web. It is very user friendly and effective. In this respect, this paper focuses on the design principles and implementation of the Human-Computer Interface (HCI). We lay down the guidelines for HCI design concept and principles, and evaluate the HCI design of an interactive e-Learning application. [ABSTRACT FROM AUTHOR]

Software architecture has become one of the most active research topics in software engineering in recent years. One of the distinct features of software architecture research is to explicitly study the interconnections (connectors) among system components. In this paper, we show how to formally specify several well-known general connectors in a software architecture methodology called SAM. Related work is discussed and compared. Our results establish the basis for reusing these defined connectors and for building more sophisticated connectors from them. [ABSTRACT FROM AUTHOR]

This paper posits six new factors that impact customers' expectations for next generation internet banking. The factors are innovative interface, integration with social media, money management tools, instant customer service, enhanced convenience, and next generation security. The data was collected from 310 respondents, who currently use internet banking services from leading countries. The results suggest that three factors, namely, integration with social media, money management tools, and enhanced convenience, would significantly affect customers' expectations for next generation internet banking. The results also suggest the role of innovative interface, next generation security, and instant customer support and service in influencing the customers' expectations. The proposed model would be useful for banks and technology providers to not only understand bank customers' expectations, but also to launch innovative marketing strategies to gain competitive advantage, and to craft a unique selling proposition to its customers. [ABSTRACT FROM AUTHOR]

Web Services represent a number of standard technologies and methodologies that allow developers to build applications under the Service-Oriented Computing paradigm. Within these, the WSDL language is used for representing Web Service interfaces, while code-first remains the de facto standard for building such interfaces. Previous studies with contract-first Web Services have shown that avoiding a specific catalog of bad WSDL specification practices, or anti-patterns, can reward Web Service publishers as service understandability and discoverability are considerably improved. In this paper, we study a number of simple and well-known code service refactorings that early reduce anti-pattern occurrences in WSDL documents. This relationship relies upon a statistical correlation between common OO metrics taken on a service's code and the anti-pattern occurrences in the generated WSDL document. We quantify the effects of the refactorings - which directly modify OO metric values and indirectly alter anti-pattern occurrences - on service discovery. All in all, we show that by applying the studied refactorings, anti-patterns are reduced and Web Service discovery is significantly improved. For the experiments, a dataset of real-world Web Services and an academic service registry have been employed. [ABSTRACT FROM AUTHOR]

We never stop finding better ways to communicate with machines. To interact with computers we tried several ways, from punched tape and tape reader to QWERTY keyboards and command lines, from graphic user interface and mouse to multi-touch screens. The way we communicate with computers or devices are getting more direct and easier. In this paper, we give gesture mouse simulation in human-computer interface based on 3 Gear Systems using two Kinect sensors. The Kinect sensor is the perfect device to achieve dynamic gesture tracking and pose recognition. We hope the 3 Gear Systems can work as a mouse, to be more specific, use gestures to do click, double click and scroll. We use Coordinate Converting Matrix and Kalman Filter to reduce the shaking caused by errors and makes the interface create a better user experience. Finally the future of human-computer interface is discussed. [ABSTRACT FROM AUTHOR]

There have been many attempts to design brain-computer interfaces (BCIs) for wheelchair control based on steady state visual evoked potential (SSVEP), event-related desynchronization/synchronization (ERD/ERS) during motor imagery (MI) tasks, P300 evoked potential, and some hybrid signals. However, those BCI systems cannot implement the wheelchair navigation flexibly and effectively. In this paper, we propose a hybrid BCI scheme based on two-class MI and four-class SSVEP tasks. It cannot only provide multi-degree control for its user, but also allow the user implement the different types of commands in parallel. In order for the subject to learn the hybrid mental strategies effectively, we design a visual and auditory cues and feedback-based training paradigm. Furthermore, an algorithm based on entropy of classification probabilities is proposed to detect intentional control (IC) state for hybrid tasks, and ensure that multi-degree control commands are accurately and quickly generated. The experiment results attest to the efficiency and flexibility of the hybrid BCI for wheelchair control in the real-world. [ABSTRACT FROM AUTHOR]

The technology that integrates various types of Web contents to build a new Web application through end-user programming is widely used nowadays. However, the Web contents do not have a uniform interface for accessing the data and computation. Most of the general Web users access information on the Web through applications until now. Hence, designing a uniform and flexible programmatic interface for integration of different Web contents is unavoidable. In this paper, we propose an approach that can be used to analyze Web applications automatically and reuse the information of Web applications through the programmatic interface we designed. Our approach can support the flexible integration of Web applications. Web services and Web feeds. In our experiments, we use a large number of Web pages from diflFerent types of Web applications and achieve the integration by the proposed programmatic interfaces. The experimental results show that our approach brings to the end-users a flexible and user-friendly programming environment. [ABSTRACT FROM AUTHOR]

With the increasing role of computing devices, facilitating natural human computer interaction (HCI) will have a positive impact on their usage and acceptance as a whole. For long time, research on HCI has been restricted to techniques based on the use of keyboard, mouse, etc. Recently, this paradigm has changed. Techniques such as vision, sound, speech recognition allow for much richer form of interaction between the user and machine. The emphasis is to provide a natural form of interface for interaction. Gestures are one of the natural forms of interaction between humans. As gesture commands are found to be natural for humans, the development of gesture control systems for controlling devices have become a popular research topic in recent years. Researchers have proposed different gesture recognition systems which act as an interface for controlling the applications. One of the drawbacks of present gesture recognition systems is application dependence which makes it difficult to transfer one gesture control interface into different applications. This paper focuses on designing a vision-based hand gesture recognition system which is adaptive to different applications thus making the gesture recognition systems to be application adaptive. The designed system comprises different processing steps like detection, segmentation, tracking, recognition, etc. For making the system as application-adaptive, different quantitative and qualitative parameters have been taken into consideration. The quantitative parameters include gesture recognition rate, features extracted and root mean square error of the system while the qualitative parameters include intuitiveness, accuracy, stress/comfort, computational efficiency, user's tolerance, and real-time performance related to the proposed system. These parameters have a vital impact on the performance of the proposed application adaptive hand gesture recognition system. [ABSTRACT FROM AUTHOR]

Today's search interfaces typically offer keyword searches and facets for the retrieval of cultural heritage multimedia objects. Facets, however, are usually based on a static set of metadata fields. This set is often called an indexing profile. Graph-based repositories based on predicates about resources allow for more precise semantics. They offer stronger support for retrieval, and they can be adopted to almost any metadata format. Technically, those predicates may be serialized as RDF triples, but handling a huge amount of objects with numerous predicates puts an unpredictable load on the query engine. In this paper, we present an approach on analysing transition paths in the RDF triples at ingest time and using the results to create facets in the search index. [ABSTRACT FROM AUTHOR]

For the importance of communication between human and machine interface, it would be valuable to develop an implement which has the ability to recognize emotional states. In this paper, we proposed an approach which can deal with the daily dependence and personal dependence in the data of multiple subjects and samples. 30 features were extracted from the physiological signals of subject for three states of emotion. The physiological signals measured were: electrocardiogram (ECG), skin temperature (SKT) and galvanic skin response (GSR). After removing the daily dependence and personal dependence by the statistical technique of MANOVA, six machine learning methods including Bayesian network learning, naive Bayesian classification, SVM, decision tree of C4.5, Logistic model and K-nearest-neighbor (KNN) were implemented to differentiate the emotional states. The results showed that Logistic model gives the best classification accuracy and the statistical technique of MANOVA can significantly improve the performance of all six machine learning methods in emotion recognition system. [ABSTRACT FROM AUTHOR]

The recovery of 3D information of a face from two (or more) images has been extensively studied and many interesting applications have been implemented. This paper proposes a model-based 3D face pose and animation tracker with auto-registration using a binocular EKF kernel for real time application like human computer interface. Compared with previous trackers, this tracker is able to automatically register face model, which eliminates the traditional manual registration process. Another major contribution is to use augmented measurement as a regularization strategy for suppressing variables coupling and over-fitting problem. This work also gives a compact factorized mathematic representation of the tracking kernel, which is easier to implement. Both synthetic and real experimental results show significant advantages of the proposed tracker from the aspects of processing speed and reliability compared with the conventional monocular tracker and Levenberg-Marquardt tracker. [ABSTRACT FROM AUTHOR]

Petascale parallel computers with more than a million processing cores are expected to be available in a couple of years. Although MPI is the dominant programming interface today for large-scale systems that at the highest end already have close to 300,000 processors, a challenging question to both researchers and users is whether MPI will scale to processor and core counts in the millions. In this paper, we examine the issue of scalability of MPI to very large systems. We first examine the MPI specification itself and discuss areas with scalability concerns and how they can be overcome. We then investigate issues that an MPI implementation must address in order to be scalable. To illustrate the issues, we ran a number of simple experiments to measure MPI memory consumption at scale up to 131,072 processes, or 80%, of the IBM Blue Gene/P system at Argonne National Laboratory. Based on the results, we identified nonscalable aspects of the MPI implementation and found ways to tune it to reduce its memory footprint. We also briefly discuss issues in application scalability to large process counts and features of MPI that enable the use of other techniques to alleviate scalability limitations in applications. [ABSTRACT FROM AUTHOR]

Component-based software engineering has recently emerged as a promising solution to the development of system-level software. Unfortunately, current approaches are limited to specific platforms and domains. This lack of generality is particularly problematic as it prevents knowledge sharing and generally drives development costs up. In the past, we have developed a generic approach to component-based software engineering for system-level software called OpenCom. In this paper, we present OpenComL an instantiation of OpenCom to Linux environments and show how it can be profiled to meet a range of system-level software in Linux environments. For this, we demonstrate its application to constructing a programmable router platform and a middleware for parallel environments. [ABSTRACT FROM AUTHOR]

In neuroscience, phase is assumed to contain more important information about the neural activity than amplitude. However, the most exploited feature in electroencephalogram (EEG) based brain computer interface (BCI) is the amplitude change, phase has been largely ignored, and only phase locking values (PLV) has been introduced in EEG classification recently. In this paper, we define phase interval value (PIV) to explore the phase information of EEG from a new perspective and propose a computational model based on the ordered Parallel Factors (PARAFAC) algorithm to extract feature from multi-way PIV data for single trial EEG classification. Application to the motor imagery task demonstrates that PIV is quite effective for EEG classification, providing significant and discriminative features in spatial and spectral dimension. PIV might become an important new tool in the analysis of EEG phase characteristic, and has the great potential use in BCI. [ABSTRACT FROM AUTHOR]

Services as abstractions of functionality have enabled the engineering of systems that support well-defined processes with relative ease. This success leads to aspirations for achieving greater complexity with the service-oriented paradigm. In particular, we address the case where the process definition is tailored differently in each instantiation based on negotiations among stakeholders of a socio-technical context. For such cases the process definition invariably crosscuts the architecture of a process-support system that composes available services. However, use of pre-defined process variations may bias the tailoring effort and thus, act against the original motivation of having a flexible definition. On the other hand, the characteristics of process complexity and tailorability introduce differences between stakeholder understanding of the process activities and their manifestation in tool support. We encounter these issues while developing a service-oriented process-support system for a security Certification and Accreditation (C&A) process. In this paper, we present our approach to effectively separate the C&A process definition from the architecture of its process-support system. We employ ontological modeling techniques to explicitly model the process definition and later expose it as a service to provide weaving rules for dynamically composing the process-support system architecture at runtime. The feasibility of our approach has been demonstrated in the design of a service-oriented architecture for a prototype workbench that supports the Department of Defense Certification and Accreditation Process (DITSCAP). [ABSTRACT FROM AUTHOR]

Face expression recognition is an active area of research with several fields of applications, ranging from emotion recognition for advanced human computer interaction to avatar animation for the movie industry. This paper presents a review of the state-of-the-art emotion recognition based on the visual analysis of facial expressions. We cover the main technical approaches and discuss the issues related to the gathering of data for the validation of the proposed systems. [ABSTRACT FROM AUTHOR]

From an information systems perspective, the assessment of commercial websites can be assessed objectively or subjectively. From a business point of view, they can be assessed quantitatively or qualitatively. This paper describes taxonomy of website assessment approaches and proposes a knowledge-based system approach to evaluate commercial websites effectively. Given a large number of constantly evolving commercial websites on the Internet, our approach shows an efficient way of automatic assessment of commercial websites. [ABSTRACT FROM AUTHOR]

This paper explores intelligent diagnostic support systems as debugging tools for end-users of computing. By analyzing error (fault) behavior of users and fault-diagnostic relationships of these errors, the authors identified patterns that could be exploited to provide electronic diagnostic assistance. This analysis showed that (a) error behavior differs considerably across end-users; and (b) individual end-users tend to make the same errors over time because they have difficulty identifying the causes of their errors. When viewed in light of the literatures on human-computer interface design and human error/diagnostic behavior, this analysis lead to some general conclusions about how diagnostic systems could be designed to provide better advice. Specifically, the empirical results suggest that diagnostic systems with firing rules based solely upon the aggregated behavior of all users will often provide individual users with poor advice. In contrast, diagnostic support systems could be improved by using user-specific data in the knowledge base. Such a deviation from conventional ideas about knowledge-base development seems consistent with other diagnostic situations, such as medical and machine diagnosis. [ABSTRACT FROM AUTHOR]

Recently, connecting thousands of processors via interconnection networks based on multiple (hierarchical) rings has an increased interest. This is due to the large acceptance and success of the Scalable Coherent Interface (SCI) technology. The inherently weak behavior of ring architecture has led interconnection designers to consider various choices to improve the overall network reliability. An interesting choice is to use braided rings instead of the single (basic) rings in the hierarchy. In this paper, we present new formulas for computing K-processor reliability of SCI ring-based hierarchical networks in the context of large-scale multiprocessor systems. The derived formulas are general and applicable to any given systems size consisting of an arbitrary number of levels. The reliability of hierarchical systems based on the basic and braided rings is evaluated and analyzed using the derived formulas. The results show that hierarchical systems based on braided rings significantly improve the reliability of hierarchies constructed of basic rings. The results are general and not limited to systems of SCI rings; the analysis is valid for any type of rings architecture such as token and slotted rings. [ABSTRACT FROM AUTHOR]

Surprising findings showing that many basic rules of social interaction among humans also apply to the interaction of humans with computers[sup 26] have encouraged interface researchers to proclaim a new paradigm in human computer interface design: the social interface. Reeves and Nass' findings have especially given a new impetus to research on anthropomorphic agents, suggesting that furnishing an agent with a human-like interface could be an effective way to enhance agent usability. Little research exists however, to verify this claim. This study seeks to illuminate user responses to an anthropomorphic agent if it is used on a daily basis. It examines the influence of traditional usability variables such as control, understanding, trust, and distraction on the acceptance of an anthropomorphic interface. Kaasinen[sup 8] as well as Wexelblat and Maes[sup 36] emphasize that the acceptance of agents (whether or not they have an anthropomorphic interface) strongly depends on these traditional usability variables. As subject for this study, a commonly used anthropomorphic agent, the Microsoft Office Assistant, was selected. Using a questionnaire that was distributed through email and the World Wide Web as well as on paper, 105 users of the Microsoft Office Suite were asked about their use and acceptance of the Office Assistant. It turned out that the Office Assistant feature was rejected by the majority of the users. As a feature to troubleshoot problems, it was perceived as inefficient. Also, from a "social" perspective, it was rated as not particularly engaging or motivating. Multiple regression analysis revealed that variables influencing the use and the acceptance of the Office Assistant were distraction and trust. Only those users who felt distracted by the assistant and who did not trust in its capability to solve their problems rejected the Office Assistant. It is concluded that to ensure agent usability, its design should emphasize assistance with the... [ABSTRACT FROM AUTHOR]

A speech interface that allows easy access to information on the WWW has the potential to make the browser more friendly and powerful. This paper, thus, presents a working Mandarin speech interface for using unconstrained Mandarin speech to control the WWW browser for conveniently browsing the Chinese Web pages. The interface currently provides speakable commands, bookmarks, and links. The experimental results show that our approach which specially consider the characteristics of the Chinese language is very effective, and very high accuracy can be achieved. [ABSTRACT FROM AUTHOR]

Traditional human-computer interaction devices such as the keyboard and mouse become ineffective for an effective interaction with the virtual environment applications because the 3D applications need a new interaction device. An efficient human interaction with the modern virtual environments requires more natural devices. Among them the "Hand Gesture" human-computer interaction modality has recently become of major interest. The main objective of gesture recognition research is to build a system which can recognize human gestures and utilize them to control an application. One of the drawbacks of present gesture recognition systems is being application-dependent which makes it difficult to transfer one gesture control interface into multiple applications. This paper focuses on designing a hand gesture recognition system which is vocabulary independent as well as adaptable to multiple applications. This makes the proposed system vocabulary independent and application independent. The designed system is comprised of the different processing steps like detection, segmentation, tracking, recognition, etc. Vocabulary independence has been incorporated in the proposed system with the help of a robust gesture mapping module that allows the user for cognitive mapping of different gestures to the same command and vice versa. For performance analysis of the proposed system accuracy, recognition rate and command response time have been compared. These parameters have been considered because they analyze the vital impact on the performance of the proposed vocabulary and application-independent hand gesture recognition system. [ABSTRACT FROM AUTHOR]

Quantum games offer situations where quantum information theory may help in solving or improving games with lack of information. For example, one may rely upon properties of entanglement for showing the superiority of a quantum player who is allowed to use quantum operations against a classical player (penny flipover [5]). Quantum communication properties enter into play in cooperative games (prisoners game, [3], guessing number [10]). An introduction to this field and an overview of important results are proposed in [7, 8]. But games may also help to make notions easier to understand, and new ways of reasoning to apprehend. The objective of this paper is to formalize and study a simple game with qubits using quantum notions of measurement and superposition, while keeping a simple formalism so that knowing quantum mechanics is not necessary to play the game. We generalize Conway's classical octal games to quantum octal games, and we solve the quantum combinatorial game QO.07 by giving a winning strategy for it. A playable version of the studied qubit game is available at the address . [ABSTRACT FROM AUTHOR]

The modularity of web services has left an open problem in composition, a scenario that involves an amalgamation of two or more web services to fulfill a request that no one web service is able to provide. This paper presents a framework for adaptive and dynamic composition of web services, enabling web services to be discovered either statically or dynamically by utilizing a semantic ontology to describe web services and their methods. This novel approach gives greater control on how web services are dynamically discovered by allowing the application developer to specify how matches are made, which goes beyond the present techniques of semantically matching inputs and outputs along with classification taxonomies. We utilize the Composite Capabilities/Preferences Profiles (CC/PP) to adapt the interface and content to be compatible with virtually any device. A proof of concept implementation has been constructed that enables users of any device to dynamically discover context-based services that will be dynamically composed to satisfy a user's request. In addition, we have designed and implemented a UDDI-like registry to support context-based adaptive composition of web services. Existing web services can be easily adapted and new web services can be effortlessly deployed. [ABSTRACT FROM AUTHOR]

Virtual Interface Architecture(VIA) is a light-weight protocol for protected user-level zero-copy communication. In spite of the promised high performance of VIA, previous MPI implementations for GigaNet's cLAN revealed low communication performance. Two main sources of such low performance are the discrepancy in the communication model between MPI and VIA and the multi-threading overhead. In this paper, we propose a new implementation of the Bulk Synchronous Parallel(BSP) programming library for VIA called xBSP to overcome such problems. To the best of our knowledge, xBSP is the first implementation of the BSP library for VIA. xBSP demonstrates that the selection of a proper library is important to exploit the features of light-weight protocols. Intensive use of Remote Direct Memory Access(RDMA) operations leads to high performance close to the native VIA performance with respect to round trip delay and bandwidth. Considering the effects of multi-threading, memory registration, and completion policy on performance, we could obtain an efficient BSP implementation for cLAN, which was confirmed by experimental results. [ABSTRACT FROM AUTHOR]

Existing user-level network interfaces deliver high bandwidth, low latency performance to applications, but are typically unable to support diverse styles of communication and are unsuitable for use in multiprogrammed environments. Often this is because the network abstraction is presented at too high a level, and support for synchronisation is inflexible. In this paper we present a new primitive for in-band synchronisation: the Tripwire. Tripwires provide a flexible, efficient and scalable means for synchronisation that is orthogonal to data transfer. We describe the implementation of a non-coherent distributed shared memory network interface, with Tripwires for synchronisation. This interface provides a low-level communications model with gigabit class bandwidth and very low overhead and latency. We show how it supports a variety of communication styles, including remote procedure call, message passing and streaming. [ABSTRACT FROM AUTHOR]

Most invasive Brain Computer Interfaces (iBCIs) use spike and Local Field Potentials (LFPs) from the motor or parietal cortices to decode movement intentions. It has been debated whether harvesting signals from other brain areas that encode global cognitive variables, such as the allocation of attention and eye movement goals in a variety of spatial reference frames, may improve the outcome of iBCIs. Here, we explore the ability of LFP signals, sampled from the lateral prefrontal cortex (LPFC) of macaque monkeys, to encode eye-movement intention during the pre-movement fixation period of a delayed saccade task. We use spectral dimensionality reduction to examine the spatiotemporal properties of the extracted non-rhythmic broadband activity and explore its usefulness in decoding saccade goals. The dynamics of the broadband signal in low spatial dimensions across the pre-movement fixation period uncovered saccade target separation; its discriminative potential was confirmed using support vector machine classifications. These findings reveal that broadband LFP from the LPFC can be used to decode intended saccade target location during pre-movement periods. We further provide a general workflow that can be implemented in iBCIs and it is relatively robust to the loss of spikes in individual electrodes. [ABSTRACT FROM AUTHOR]

Event-related potentials (ERPs) especially P300 are popular effective features for brain–computer interface (BCI) systems based on electroencephalography (EEG). Traditional ERP-based BCI systems may perform poorly for small training samples, i.e. the undersampling problem. In this study, the ERP classification problem was investigated, in particular, the ERP classification in the high-dimensional setting with the number of features larger than the number of samples was studied. A flexible group sparse discriminative analysis algorithm based on Moreau–Yosida regularization was proposed for alleviating the undersampling problem. An optimization problem with the group sparse criterion was presented, and the optimal solution was proposed by using the regularized optimal scoring method. During the alternating iteration procedure, the feature selection and classification were performed simultaneously. Two P300-based BCI datasets were used to evaluate our proposed new method and compare it with existing standard methods. The experimental results indicated that the features extracted via our proposed method are efficient and provide an overall better P300 classification accuracy compared with several state-of-the-art methods. [ABSTRACT FROM AUTHOR]