Supporting Ubiquitous IMS-based Teleconferencing Through Discovery and Composition of IMS and Web Components

Natural communication among people happens in flexible ways and is strongly affected by the users’ situation (such as communication tools available, user’s location, and user’s preferences). This situation or context information is seldom used to initiate communication sessions among users. Current communication systems are indifferent about users’ context, often require time consuming manual configurations and often result in conferencing tools not being easily accessible when needed. This leads to lower adoption of innovative communications services. IMS SIP (IP Multimedia Subsystem, Session Initiation Protocol) sessions allow users to access the session from different points of contact (home, office, etc.), however, IMS still requires a prior knowledge of all SIP components that might be used in a SIP session. Furthermore, IMS makes limited use of context information (mainly user-defined availability). To address these issues our research approach combines techniques from pervasive computing with IMS networking principles to facilitate compositions of communication sessions based on users’ context. We propose a platform and APIs for pervasive application development support to allow greater intelligence in IMS applications. We additionally provide mechanisms for IMS applications to apply their intelligence to the configuration of physical devices and web resources used to set up a conference. The innovations proposed in this paper are: (1) A new standard for intelligent IMS-based conferencing applications. (2) Application Development Interfaces (APIs) for a platform for pervasive computing. (3) An architecture for a pervasive IMS platform.

OXPath: A language for scalable data extraction, automation, and crawling on the deep web

The evolution of the web has outpaced itself: A growing wealth of information and increasingly sophisticated interfaces necessitate automated processing, yet existing automation and data extraction technologies have been overwhelmed by this very growth. To address this trend, we identify four key requirements for web data extraction, automation, and (focused) web crawling: (1) interact with sophisticated web application interfaces, (2) precisely capture the relevant data to be extracted, (3) scale with the number of visited pages, and (4) readily embed into existing web technologies. We introduce OXPath as an extension of XPath for interacting with web applications and extracting data thus revealed—matching all the above requirements. OXPath’s page-at-a-time evaluation guarantees memory use independent of the number of visited pages, yet remains polynomial in time. We experimentally validate the theoretical complexity and demonstrate that OXPath’s resource consumption is dominated by page rendering in the underlying browser. With an extensive study of sublanguages and properties of OXPath, we pinpoint the effect of specific features on evaluation performance. Our experiments show that OXPath outperforms existing commercial and academic data extraction tools by a wide margin.     

Pattern-based framework for modularized software development and evolution robustness

Context

Software development is now facing much more challenges than ever before due to the intrinsic high complexity and the increasing demands of the quick-service-ready paradigm.

Objective

As the developers are now called for more quality software systems from the industries, there is insufficient guidance from the methodologies and standards of software engineering that can provide assistance to the rapid development of qualified business software.

Method

In this work, we discuss the advantages of the pattern-based software development. We verify the benefits using a pattern-based software framework called OS2F, and a corresponding system design architecture that is intended for the rapid development of web applications.

Results

The objective of the framework/architecture is that, through software patterns, developers should be able to separate the work of system development from the business rules so as to reduce the problems caused by a developer’s lack of business experiences.

Conclusion

Through a suitable pattern-based software framework, the quality of the product can thus be enhanced, software development time and cost decreased, and software evolution robustness improved.     

The STEP Integration Information Architecture

Traditionally, when the term integration is used to refer to the interoperability of disparate, heterogeneous computer systems, it means the ability to exchange digital data between the systems. For the more sophisticated systems designers, integration may mean shared, distributed databases or a federated database system. Within the development of the STandard for the Exchange of Product model data (STEP — ISO 10303), integration refers to an information architecture composed of conceptual constructs that is independent of implementation considerations.The Integration Information Architecture of STEP is presented and explained. Instead of a flat representation of abstract (i.e., conceptual) data structures, integration within STEP takes place at four different levels:

AML: a modeling language for designing adaptive web applications

Modern WWW methodologies focus on developing context-aware data delivery applications on the Web, but very few proposals provide a conceptual modeling of their adaptation specifications. In this paper, we present AML—Adaptation Modeling Language—to specify complex Adaptive Web Applications at the conceptual level. AML models the adaptation process by using a special workflow involving modeling primitives that execute elementary manipulations. The adaptation considers different and orthogonal components of the context and operates over the selection of the most suitable contents, the organization of the hypertext structure of the response, and the layout of the final pages. The language and its design process are fully implemented in a CASE tool, called FAWIS. Specifically, FAWIS is able to access a Web data source and automatically filter and adapt information delivery on the basis of the context of the client. The tool is able to manage heterogeneous contexts, is easy extensible to new coordinates of adaptation, and can integrate different adaptation requirements solving possible conflicts between them. It allows the designer to define the response that better satisfies the requirements of adaptation for a context.     

Conceptual scheduling model and optimized release scheduling for agile environments

Context

Release scheduling deals with the selection and assignment of deliverable features to a sequence of consecutive product deliveries while several constraints are fulfilled. Although agile software development represents a major approach to software engineering, there is no well-established conceptual definition and sound methodological support of agile release scheduling.

Objective

To propose a solution, we present, (1) a conceptual model for agile scheduling, and (2) a novel multiple knapsack-based optimization model with (3) a branch-and-bound optimization algorithm for agile release scheduling.

Method

To evaluate our model simulations were carried out seven real life and several generated data sets.

Results

The developed algorithm strives to prevent resource overload and resource underload, and mitigates risks of delivery slippage.

Conclusion

The results of the experiment suggest that this approach can provide optimized semi-automatic release schedule generations and more informed and established decisions utilizing what-if-analysis on the fly to tailor the best schedule for the specific project context.     

RFID-initiated workflow control to facilitate patient safety and utilization efficiency in operation theater

Objective

To control the workflow for surgical patients, we in-cooperate radio-frequency identification (RFID) technology to develop a Patient Advancement Monitoring System (PAMS) in operation theater.

Methods

The web-based PAMS is designed to monitor the whole workflow for the handling of surgical patients. The system integrates multiple data entry ports Across the multi-functional surgical teams. Data are entered into the system through RFID, bar code, palm digital assistance (PDA), ultra-mobile personal computer (UMPC), or traditional keyboard at designated checkpoints. Active radio-frequency identification (RFID) tag can initiate data demonstration on the computer screens upon a patient's arrival at any particular checkpoint along the advancement pathway.

Results

The PAMS can manage the progress of operations, patient localization, identity verification, and peri-operative care. The workflow monitoring provides caregivers’ instant information sharing to enhance management efficiency.

Conclusion

RFID-initiate surgical workflow control is valuable to meet the safety, quality, efficiency requirements in operation theater.     

A calendar based Internet content pre-caching agent for small computing devices

We described in earlier publications the principles of a system where Internet content would be pre-cached, based on contextual information obtained from a user’s electronic calendar. The model for such a system envisioned a set of cooperating agents, distributed on a user’s desktop and mobile device, which would be responsible for making decisions on the context and preferences of the user, and downloading the relevant internet content through a land-based broadband connection and storing it on the mobile device. This paper presents and discusses established pre-caching techniques and their suitability for use on mobile information access scenarios. It proceeds in describing the implementation details of an alternative approach, a calendar-based pre-caching system and presents the findings of tests that were made with human subjects on such a system.

Augmenting and structuring user queries to support efficient free-form code search

Source code terms such as method names and variable types are often different from conceptual words mentioned in a search query. This vocabulary mismatch problem can make code search inefficient. In this paper, we present COde voCABUlary (CoCaBu), an approach to resolving the vocabulary mismatch problem when dealing with free-form code search queries. Our approach leverages common developer questions and the associated expert answers to augment user queries with the relevant, but missing, structural code entities in order to improve the performance of matching relevant code examples within large code repositories. To instantiate this approach, we build GitSearch, a code search engine, on top of GitHub and Stack Overflow Q&A data. We evaluate GitSearch in several dimensions to demonstrate that (1) its code search results are correct with respect to user-accepted answers; (2) the results are qualitatively better than those of existing Internet-scale code search engines; (3) our engine is competitive against web search engines, such as Google, in helping users solve programming tasks; and (4) GitSearch provides code examples that are acceptable or interesting to the community as answers for Stack Overflow questions.     

The Berlin Brain-Computer Interface (BBCI) – towards a new communication channel for online control in gaming applications

The investigation of innovative Human-Computer Interfaces (HCI) provides a challenge for future multimedia research and development. Brain-Computer Interfaces (BCI) exploit the ability of human communication and control bypassing the classical neuromuscular communication channels. In general, BCIs offer a possibility of communication for people with severe neuromuscular disorders, such as Amyotrophic Lateral Sclerosis (ALS) or spinal cord injury. Beyond medical applications, a BCI conjunction with exciting multimedia applications, e.g., a dexterity game, could define a new level of control possibilities also for healthy customers decoding information directly from the user’s brain, as reflected in electroencephalographic (EEG) signals which are recorded non-invasively from user’s scalp. This contribution introduces the Berlin Brain–Computer Interface (BBCI) and presents setups where the user is provided with intuitive control strategies in plausible gaming applications that use biofeedback. Yet at its beginning, BBCI thus adds a new dimension in multimedia research by offering the user an additional and independent communication channel based on brain activity only. First successful experiments already yielded inspiring proofs-of-concept. A diversity of multimedia application models, say computer games, and their specific intuitive control strategies, as well as various Virtual Reality (VR) scenarios are now open for BCI research aiming at a further speed up of user adaptation and increase of learning success and transfer bit rates.

Is software “green”? Application development environments and energy efficiency in open source applications

Context

The energy efficiency of IT systems, also referred to as Green IT, is attracting more and more attention. While several researchers have focused on the energy efficiency of hardware and embedded systems, the role of application software in IT energy consumption still needs investigation.

Objective

This paper aims to define a methodology for measuring software energy efficiency and to understand the consequences of abstraction layers and application development environments for the energy efficiency of software applications.

Method

We first develop a measure of energy efficiency that is appropriate for software applications. We then examine how the use of application development environments relates to this measure of energy efficiency for a sample of 63 open source software applications.

Results

Our findings indicate that a greater use of application development environments - specifically, frameworks and external libraries - is more detrimental in terms of energy efficiency for larger applications than for smaller applications. We also find that different functional application types have distinctly different levels of energy efficiency, with text and image editing and gaming applications being the most energy inefficient due to their intense use of the processor.

Conclusion

We conclude that different designs can have a significant impact on the energy efficiency of software applications. We have related the use of software application development environments to software energy efficiency suggesting that there may be a trade-off between development efficiency and energy efficiency. We propose new research to further investigate this topic.     

Autopoiesis, the immune system, and adaptive information filtering

Adaptive information filtering is a challenging and fascinating problem. It requires the adaptation of a representation of a user’s multiple interests to various changes in them. We tackle this dynamic problem with Nootropia, a model inspired by the autopoietic view of the immune system. It is based on a self-organising antibody network that reacts to user feedback in order to define and preserve the user interests. We describe Nootropia in the context of adaptive, content-based document filtering and evaluate it using virtual users. The results demonstrate Nootropia’s ability to adapt to both short-term variations and more radical changes in the user’s interests, and to dynamically control its size and connectivity in the process. Advantages over existing approaches to profile adaptation, such as learning algorithms and evolutionary algorithms are also highlighted.

Designing XML documents from conceptual schemas and workload information

Due to the increase of XML-based applications, XML schema design has become an important task. One approach is to consider conceptual schemas as a basis for generating XML documents compliant to consensual information of specific domains. However, the conversion of conceptual schemas to XML schemas is not a straightforward process and inconvenient design decisions can lead to a poor query processing on XML documents generated. This paper presents a conversion approach which considers data and query workload estimated for XML applications, in order to generate an XML schema from a conceptual schema. Load information is used to produce XML schemas which can respond well to the main queries of an XML application. We evaluate our approach through a case study carried out on a native XML database. The experimental results demonstrate that the XML schemas generated by our methodology contribute to a better query performance than related approaches.

Prompter

Developers often require knowledge beyond the one they possess, which boils down to asking co-workers for help or consulting additional sources of information, such as Application Programming Interfaces (API) documentation, forums, and Q&A websites. However, it requires time and energy to formulate one’s problem, peruse and process the results. We propose a novel approach that, given a context in the Integrated Development Environment (IDE), automatically retrieves pertinent discussions from Stack Overflow, evaluates their relevance using a multi-faceted ranking model, and, if a given confidence threshold is surpassed, notifies the developer. We have implemented our approach in Prompter, an Eclipse plug-in. Prompter was evaluated in two empirical studies. The first study was aimed at evaluatingPrompter’s ranking model and involved 33 participants. The second study was conducted with 12 participants and aimed at evaluating Prompter’s usefulness when supporting developers during development and maintenance tasks. Since Prompter uses “volatile information” crawled from the web, we also replicated Study I after one year to assess the impact of such a “volatility” on recommenders like Prompter. Our results indicate that (i) Prompter recommendations were positively evaluated in 74 % of the cases on average, (ii) Prompter significantly helps developers to improve the correctness of their tasks by 24 % on average, but also (iii) 78 % of the provided recommendations are “volatile” and can change at one year of distance. While Prompter revealed to be effective, our studies also point out issues when building recommenders based on information available on online forums.     

Factor structure of web site creativity

The objective of this study is to develop an instrument measuring user-assessment of web site creativity and then to investigate the impacts of web site creativity on user behavior. A conceptual model for user perception and response to web site creativity was constructed and the initial Web Site Creativity Measurement Instrument was developed, whose construct validity was based on the literature. This instrument was then administered via a survey (N = 289) with satisfactory internal consistency. The results of factor analysis indicated a refined instrument with seven factors (28 items): Aesthetic Appeal, Interactivity, Novelty and Flexibility, Affect, Importance, Commonality and Simplicity, and Personalization, which explained 63% of the total variance. Stepwise regressions further identified important factors in predicting the user’s attitude and behavior towards web site creativity. 62% of the total variance regarding the prediction of the user’s overall preference towards creative web sites was explained by significant factors. Guidelines and checklist for creative web site design were also developed based on the refined instrument.     

Tracking Context Changes through Meta-Learning

The article deals with the problem of learning incrementally (on-line) in domains where the target concepts are context-dependent, so that changes in context can produce more or less radical changes in the associated concepts. In particular, we concentrate on a class of learning tasks where the domain provides explicit clues as to the current context (e.g., attributes with characteristic values). A general two-level learning model is presented that effectively adjusts to changing contexts by trying to detect (via meta-learning) contextual clues and using this information to focus the learning process. Context learning and detection occur during regular on-line learning, without separate training phases for context recognition. Two operational systems based on this model are presented that differ in the underlying learning algorithm and in the way they use contextual information: METAL(B) combines meta-learning with a Bayesian classifier, while METAL(IB) is based on an instance-based learning algorithm. Experiments with synthetic domains as well as a number of real-world problems show that the algorithms are robust in a variety of dimensions, and that meta-learning can produce substantial increases in accuracy over simple object-level learning in situations with changing contexts.