Interactive applications of personal situation-aware assistants

Ultraportable mobile computers provide electronic assistance for environments and usage situations, where computer support up to now has not been feasible. For the first time, a true physical and cognitive integration of computer support into the everyday business of the real-world becomes possible, as envisioned in Mark Weiser's concept of “ubiquitous computing” (Weiser, Communication of the ICM 1993, 36 (12): 75–85). However, although Handheld-PC, etc. today; already support a good deal of personal information management and basic access to distributed multimedia information services such as the World-Wide Web, they are still surprisingly difficult to use in “full action”. Specifically, lengthy interaction sequences and the inability to find quickly that important piece of information which is embedded somewhere in the machine, makes using those devices sometimes a very disappointing experience. In this, paper, we outline a new approach to realizing an easy-to-use personal digital assistant systems, based on the concept of Situation Awareness. Using knowledge about task structures, situation dependencies, and task contexts, our concept allows a mobile assistant to proactively provide the right information at the right time and the right place, without intruding upon the users primary task: interacting with reality.     

A framework for designing closed domain virtual assistants

Since its beginning in 1969, the Internet has grown rapidly, especially over the past few years. Companies and organizations store more and more information about themselves on the Internet. Sometimes, that information is not well organized. Other times, the huge volume of available data makes useful information difficult to be found. The result is that users have to waste their time looking for what they want to know using the traditional menu-driven navigation and keyword search that websites provide. This is a critical issue because it decreases users interest about companies. In order to avoid this problem, in this paper we propose a framework for designing virtual assistants, which are, considering first results, an ideal alternative to help users find, not only the information that they are looking for, but also some related information which could be of the highest interest.     

A framework to model and manipulate constraints for over-constrained geographic applications

Geographic applications are often over-constrained because of the stakeholders’ multiple requirements and the various spatial, alphanumeric and temporal constraints to be satisfied. In most cases, solving over-constrained problems is based on the relaxation of some constraints according to values of preferences. This article proposes the modelling and the management of constraints in order to provide a framework to integrate stakeholders in the expression and the relaxation of their constraints. Three families of constraints are defined: static vs. dynamic, intra-entity vs. inter-entities and intra-instance vs. inter-instances. Constraints are modelled from two points of view: system with the complexity in time of the different involved operators and user with stakeholders’ preferences. The methodology of constraints relaxation is based on primitive, complex and derived operations. These operations allow a modification of the constraints in order to provide a relevant solution to a simulation. The developed system was applied to reduce the streaming/floods risks in the territory of Pays de Caux (Seine Maritime, France).     

A neural fuzzy framework for system mapping applications

A novel neural fuzzy (NF) mapping framework is developed in this paper to convert linear systems and a class of nonlinear systems from the crisp-domain to a NF representation. The resulting neural fuzzy system (NFS) is guaranteed to be functionally identical to the original system. Therefore, the proposed mapping technique provides a well-defined prototype for one type of NFS design. The resulting fuzzy reasoning representation facilitates the investigation in linguistic terms into the system operations, whereas the system performance can be further improved by properly incorporating expertise knowledge or by online/offline training via this NF structure. The developed technique is to extend our previously-developed techniques to NF modeling/mapping applications and its effectiveness is demonstrated by simulations using a flexible-link robot.     

A multiobject tracking framework for interactive multimedia applications

Automatic initialization and tracking of multiple people and their body parts is one of the first steps in designing interactive multimedia applications. The key problems in this context are robust detection and tracking of people and their body parts in an unconstrained environment. This paper presents an integrated framework to address detection and tracking of multiple objects in a computationally efficient manner. In particular, a neural network-based face detector was employed to detect faces and compute person specific statistical model for skin color from the face regions. A probabilistic model was proposed to fuse the color and motion information to localize the moving body parts (hands). Multiple hypothesis tracking (MHT) algorithm was adopted to track face and hands. In real world scenes extracted features (face and hands) usually contain spurious measurements that create unconvincing trajectories and needless computations. To deal with this problem a path coherence function was incorporated along with MHT to reduce the number of hypotheses, which in turn reduces the computational cost and improves the structure of trajectories. The performance of the framework was validated using experiments on synthetic and real sequence of images.     

A framework for semiqualitative reasoning in engineering applications

In most cases the models for experimentation, analysis, or design in engineering applications take into account only quantitative knowledge. Sometimes there is a qualitative knowledge that is convenient to consider in order to obtain better conclusions. These qualitative concepts can be labels such as ''high,'' ''very negative,'' ''little acid,'' ''monotonically increasing'' or symbols such as >>, , , etc… Engineers have already used this type of knowledge implicitly in many activities. The framework that we present here lets us express explicitly this knowledge. This work makes the following contributions. First, we identify the most important classes of qualitative concepts in engineering activities. Second, we present a novel methodology to integrate both qualitative and quantitative knowledge. Third, we obtain significant conclusions automatically. It is named semiqualitative reasoning. Qualitative concepts are represented by means of closed real intervals. This approximation is accepted in the area of Artificial Intelligence. A modeling language is specified to represent qualitative and quantitative knowledge of the model. A numeric constraint satisfaction problem is obtained by means of corresponding rules of transformation of the semantics of this language. In order to obtain conclusions, we have developed algorithms that treat the problem in a symbolic and numeric way. The interval conclusions obtained are transformed into qualitative labels through a linguistic interpretation. Finally, the capabilities of this methodology are illustrated on different problems.     

A framework for context-aware self-adaptive mobile applications SPL

Mobile Applications are rapidly emerging as a convenient medium for using a variety of services. Over time and with the high penetration of smartphones in society, self-adaptation has become an essential capability required by mobile application users. In an ideal scenario, an application is required to adjust its behavior according to the current context of its use. This raises the challenge in mobile computing towards the design and development of applications that sense and react to contextual changes to provide a value-added user experience. In its general sense, context information can relate to the environment, the user, or the device status. In this paper, we propose a novel framework for building context aware and adaptive mobile applications. Based on feature modeling and Software Product Lines (SPL) concepts, this framework guides the modeling of adaptability at design time and supports context awareness and adaptability at runtime. In the core of the approach, is a feature meta-model that incorporates, in addition to SPL concepts, application feature priorities to drive the adaptability. A tool, based on that feature model, is presented to model the mobile application features and to derive the SPL members. A mobile framework, built on top of OSGI framework to dynamically adapt the application at runtime is also described.     

A framework for mapping periodic real-time applications onmulticomputers

This short paper presents a framework for periodic execution of task-flow graphs that enables schedulability analysis of the communication requirements. The analysis performs the steps of segmenting messages, assigning the segments to specific links and time intervals, and ordering them within the intervals to generate node switching schedules that provide contention-free message routing at run-time. The analysis is also used to integrate task allocation with message routing using a contention-based objective function. Usefulness of the proposed scheme in ensuring guaranteed communication performance is demonstrated by an appropriate example     

A framework for multiple snakes and its applications

We present a framework for segmentation of multiple objects whose shapes are similar but image qualities are different. Our framework is based on the snake or active contour method, in which a new kind of energy called “group energy” is introduced. The group energy is used to handle the sharing of properties across multiple objects and also to allow contours of objects with good image qualities to be used as reference contours for remaining objects during optimization. In this framework, we also deal with rotations among similar objects by applying group energy after removing the rotation offset. Comprehensive testing has been performed on synthetic and real images, demonstrating that our framework has significantly better performance of segmentation compared to the original (individual) snake.     

A framework for artificial intelligence applications software development

Despite the promise and prominence of artificial intelligence, successful widely-based applications have been rare. Much of previous artificial intelligence work has concentrated on the demonstration of techniques rather than the development of tools that can be used in systems design, analysis and operation. A systematic program of knowledge compilation in artificial intelligence is proposed where extensible function libraries can be used by professionals in various fields and non-programming specialists in developing artificial intelligence applications.     

A general framework for tree-based morphology and its applications to self-dual filtering

This paper presents a tree-based framework for producing self-dual morphological operators, based on a tree-representation complete inf-semilattice (CISL). The idea is to use a self-dual tree transform to map a given image into the above CISL, perform one or more morphological operations there, and map the result back to the image domain using the inverse tree transform. We also present a particular case of this general framework, involving a new tree transform, the Extrema-Watershed Tree (EWT). The operators obtained by using the EWT in the above framework behave like classical morphological operators, but in addition are self-dual. Some application examples are provided: pre-processing for OCR and dust and scratch removal algorithms, and image denoising. We also explore first steps towards obtaining tree transforms that induce a CISL on the image domain as well.     

A scalable WebRTC-based framework for remote video collaboration applications

Multimedia Tools and Applications - Remote video collaboration is common nowadays in conferencing, telehealth and remote teaching applications. To support these low-latency and interactive use...     

A framework for building mobile single and multi-robot applications

The complexity of robot software systems calls for the use of a well-conceived architecture together with programming tools to support it. One common feature of robot architectures is the modular decomposition of systems into simpler and largely independent components. These components implement primitive actions and report events about their state. The robot programming framework proposed here includes a tool (RoboGraph) to program and coordinate the activity (tasks) of these middleware modules. Project developers use the same task programming IDE (RoboGraph) on two different levels. The first is to program tasks that must be executed autonomously by one robot and the second is to program tasks that can include several robots and building elements.Tasks are described using a Signal Interpreted Petri Net (SIPN) editor and stored in an xml file. A dispatcher loads these files and executes the different Petri nets as needed. A monitor that shows the state of all the running nets is very useful for debugging and tracing purposes. The whole system has been used in several applications: A tour-guide robot (GuideBot), a multi-robot surveillance project (WatchBot) and a hospital food and laundry transportation system based on mobile robots.     

A load balancing framework for adaptive and asynchronous applications

We describe the design of a flexible load balancing framework and runtime software system for supporting the development of adaptive applications on distributed-memory parallel computers. The runtime system supports a global namespace, transparent object migration, automatic message forwarding and routing, and automatic load balancing. These features can be used at the discretion of the application developer in order to simplify program development and to eliminate complex bookkeeping associated with mobile data objects. An evaluation of this system in the context of a three-dimensional tetrahedral advancing front parallel mesh generator shows that overall runtime improvements of 15 percent compared to common stop-and-repartition load balancing methods, 30 percent compared to explicit intrusive load balancing methods, and 42 percent compared to no load balancing are possible on large processor configurations. At the same time, the overheads attributable to the runtime system are a fraction of 1 percent of the total runtime. The parallel advancing front method is a coarse-grained and highly adaptive application and therefore exercises all of the features of the runtime system.     

A unified framework for market segmentation and its applications

Market segmentation is a core marketing concept that is conceptually simple to define and understand, but inherently a multi-criteria problem that is hard to measure and computationally difficult in many aspects. This paper reviews the development of market segmentation techniques and identifies the computational issues of the applications of market segmentation. A multidimensional unified framework for market segmentation is proposed based on the relationship among segmentation variables, data measures, and the multi-objective optimization techniques implemented. We conduct an empirical comparison of two prominent methods: a concomitant finite mixture model and a multi-objective evolutionary algorithm. The result shows that the proposed framework helps to understand different segmentation models and solutions and to guide the development of new market segmentation solution techniques.     

A framework for efficient regression tests on database applications

Regression testing is an important software maintenance activity to ensure the integrity of a software after modification. However, most methods and tools developed for software testing today do not work well for database applications; these tools only work well if applications are stateless or tests can be designed in such a way that they do not alter the state. To execute tests for database applications efficiently, the challenge is to control the state of the database during testing and to order the test runs such that expensive database reset operations that bring the database into the right state need to be executed as seldom as possible. This work devises a regression testing framework for database applications so that test runs can be executed in parallel. The goal is to achieve linear speed-up and/or exploit the available resources as well as possible. This problem is challenging because parallel testing needs to consider both load balancing and controlling the state of the database. Experimental results show that test run execution can achieve linear speed-up by using the proposed framework.     

Multimedia framework to support eHealth applications

Limited bandwidth resources lead to a number of challenges especially for eHealth applications, which are communicated over IP and wireless networks. These multimedia services include high-resolution videos and have very large file sizes that require a high level of compression to overcome this limitation. Therefore, there is an acute demand for the research community to provide an efficient multimedia framework to encode medical videos with high quality specifically under the conditions of an error-prone environment. Both an affordable delivery framework and effective coding techniques are extremely desirable for the delivery of high-quality eHealth video applications for transmission over heterogeneous networks and devices. In this paper, we propose and demonstrate a multimedia framework to support eHealth applications, which has an improved coding scheme that uses an SVC-scalable extension of MPEC-4 AVC/H.264. Simulation results show that the proposed scheme achieves a significant improvement in terms of the PSNR-Y gain and reduces the picture quality degradation caused by artifacts and distortions, compared to the existing scheme.     

A personal computer based expert system framework for the design of experiments

In the field of industrial engineering, experimental design play a large role in the manufacturing quality. Knowledge based systems for parameter design will provide the quality engineer with a powerful tool to increase quality. Just as the past ten years saw a movement away from inspection to statistical process control, the future will see a shift from statistical process control to system and parameter design. Improvements in quality will increasingly come from products that are robust in design which will perform well in the very variable environment that is the global market.     

A framework to identify applications of information technology to improve service quality

Abstract

More and more organizations are seeking innovative ways to use information technology (IT) for strategic advantage. One way to gain this competitive edge is by differentiating the services provided to customers. This paper provides a framework to identify areas ripe for the implementation of IT to enhance and improve customer service. The framework is based upon the examination of the existing service delivery system of an organization and how applications of IT might change the interfaces among the various players (customers, employees, etc.) in the service delivery system. Further, examples are presented to illustrate how some organizations have achieved superior service quality by creatively utilizing simple IT tools.