A Multi-channel Application Framework for Customer Care Service Using Best-First Search Technique

It has become imperative to find a solution to the dissatisfaction in response by mobile service providers when interacting with their customer care centres. Problems faced with Human to Human Interaction (H2H) between customer care centres and their customers include delayed response time, inconsistent solutions to questions or enquires and lack of dedicated access channels for interaction with customer care centres in some cases. This paper presents a framework and development techniques for a multi-channel application providing Human to System (H2S) interaction for customer care centre of a mobile telecommunication provider. The proposed solution is called Interactive Customer Service Agent (ICSA). Based on single-authoring, it will provide three media of interaction with the customer care centre of a mobile telecommunication operator: voice, phone and web browsing. A mathematical search technique called Best-First Search to generate accurate results in a search environmen

Towards a Reference Architecture for Context-Aware Services

This Chapter describes an infrastructure for multi-modal perceptual systems which aims at developing and realizing computer services that are delivered to humans in an implicit and unobtrusive way. The framework presented here supports the implementation of humancentric context-aware applications providing non-obtrusive assistance to participants in events such as meetings, lectures, conferences and presentations taking place in indoor "smart spaces". We emphasize on the design and implementation of an agent-based framework that supports "pluggable" service logic in the sense that the service developer can concentrate on the service logic independently of the underlying middleware. Furthermore, we give an example of the architecture’s ability to support the cooperation of multiple services in a meeting scenario using an intelligent connector service and a semantic web oriented travel service. The framework was developed as part of the project CHIL (Computers in the Human Interaction Loop). The vision of CHIL was to be able to provide context-aware human centric services which will operate in the background, provide assistance to the participants in the CHIL spaces and undertake tedious tasks in an unobtrusive way. To achieve this, significant effort had to be put in designing efficient context extraction components so that the CHIL system can acquire an accurate perspective of the current state of the CHIL space. However, the CHIL services required a much more sophisticated modelling of the actual event, rather than simple and fluctuating impressions of it. Furthermore, by nature the CHIL spaces are highly dynamic and heterogeneous; people join or leave, sensors fail or are restarted, user devices connect to the network, etc. To manage this diverse infrastructure, sophisticated techniques were necessary that can map all entities present in the CHIL system and provide information to all components which may require it. From these facts, one can easily understand that in addition to highly sophisticated components at an individual level, another mechanism (or a combination of mechanisms) should be present which can handle this infrastructure. The CHIL Reference Architecture for Multi Modal Systems lies in the background, and provides the solid, high performance and robust backbone for the CHIL services. Each individual need is assigned to a specially designed and integrated layer which is docked to the individual component, and provides all the necessary actions to enable the component to be plugged in the CHIL framework

Active Node supporting Context-aware Vertical Handover in Pervasive Computing Environment with Redundant Positioning

A major requirement for pervasive systems is to integrate context-awareness to support heterogeneous networks and device technologies and at the same time support application adaptations to suit user activities. However, current infrastructures for pervasive systems are based on centralized architectures which are focused on context support for service adaptations in response to changes in the computing environment or user mobility. In this paper, we propose a hierarchical architecture based on active nodes, which maximizes the computational capabilities of various nodes within the pervasive computing environment, while efficiently gathering and evaluating context information from the user’s working environment. The migratable active node architecture employs various decision making processes for evaluating a rich set of context information in order to dynamically allocate active nodes in the working environment, perform application adaptations and predict user mobility. The active node also utilizes the Redundant Positioning System to accurately manage user’s mobility. This paper demonstrates the active node capabilities through context-aware vertical handover applications

A paradigm of an interaction context-aware pervasive multimodal multimedia computing system

Communication is a very important aspect of human life; it is communication that helps human beings to connect with each other as individuals and as independent groups. Communication is the fulcrum that drives all human developments in all fields. In informatics, one of the main purposes of the existence of computer is information dissemination – to be able to send and receive information. Humans are quite successful in conveying ideas to one another, and reacting appropriately. This is due to the fact that we share the richness of the language, have a common understanding of how things work and an implicit understanding of everyday situations. When humans communicate with humans, they comprehend the information that is apparent to the current situation, or context, hence increasing the conversational bandwidth. This ability to convey ideas, however, does not transfer when humans interact with computers. On its own, computers do not understand our language, do not understand how the world works and cannot sense information about the current situation. In a typical computing set-up where we have an impoverished typical mechanism for providing computer with information using mouse, keyboard and screen, the end result is we explicitly provide information to computers, producing an effect that is contrary to the promise of transparency and calm technology in Weiser’s vision of ubiquitous computing (Weiser 1991; Weiser and Brown 1996). To reverse this trend, it is imperative that we researchers find ways that will enable computers to have access to context. It is through context-awareness that we can increase the richness of communication in human-computer interaction, through which we can reap the most likely benefit of more useful computational services. Context is a subjective idea as demonstrated by the state-of-the art in which each researcher has his own understanding of the term, which continues to evolve nonetheless. The acquisition of contextual information is essential but it is the end user, however, that will have the final say as to whether the envisioned context is correctly captured/acquired or not. Current literature informs us that some contextual information is already predefined by some researchers from the very beginning – this is correct if the application domain is fixed but is incorrect if we infer that a typical user does different computing tasks on different occasions. With the aim of coming up with more conclusive and inclusive design, we conjecture that what contextual information should be left to the judgment of the end user who is the one that has the knowledge determine which information is important to him and which is not. This leads us to the concept of incremental acquisition of context where context parameters are added, modified or deleted one context parameter at a time. In conjunction with our idea of inclusive context, we broaden the notion of context that it has become context of interaction. Interaction context is the term that is used to refer to the collective context of the user (i.e. user context), of his working environment (i.e. environmental context) and of his computing system (i.e. system context). Logically and mathematically, each of these interaction context elements – user context, environment context and system context – is composed of various parameters that describe the state of the user, of his workplace and his computing resources as he undertakes an activity in accomplishing his computing task, and each of these parameters may evolve over time. For example, user location is a user context parameter and its value will evolve as the user moves from one place to another. The same can be said about noise level as an environment context parameter; its value evolves over time. The same can be said with available bandwidth that continuously evolves which we consider as a system context parameter. To realize the incremental definition of incremental context, we have developed a tool called the virtual machine for incremental interaction context. This tool can be used to add, modify and delete a context parameter on one hand and determine the sensor-based context (i.e. context that is based on parameters whose values are obtained from raw data supplied by sensors) on the other. In order to obtain the full benefit of the richness of interaction context with regards to communication in human-machine interaction, the modality of interaction should not be limited to the traditional use of mouse-keyboard-screen alone. Multimodality allows for a much wider range of modes and forms of communication, selected and adapted to suit the given user’s context of interaction, by which the end user can transmit data to the computer and computer can respond or yield results to the user’s queries. In multimodal communication, the weaknesses of one mode of interaction, with regards to its suitability to a given situation, is compensated by replacing it with another mode of communication that is more suitable to the situation. For example, when the environment becomes disturbingly noisy, using voice may not be the ideal mode to input data; instead, the user may opt for transmitting text or visual information. Multimodality also promotes inclusive informatics as those with a permanent or temporary disability are given the opportunity to use and benefit from information technology advancement. For example, the work on presentation of mathematical expressions to visually-impaired users (Awdé 2009) would not have been made possible without multimodality. With mobile computing within our midst coupled with wireless communication that allows access to information and services, pervasive and adaptive multimodality is more than ever apt to enrich communication in human-computer interaction and in providing the most suitable modes for data input and output in relation to the evolving interaction context. A look back at the state of the art informs us that a great amount of effort was expended in finding the definition of context, in the acquisition of context, in the dissemination of context and the exploitation of context within a system that has a fixed domain of application (e.g. healthcare, education, etc.). Also, another close look tells us that much research efforts on ubiquitous computing were devoted to various application domains (e.g. identifying the user whereabouts, identifying services and tools, etc.) but there is rarely, if ever, an effort made to make multimodality pervasive and accessible to various user situations. In this regard, we come up with a research work that will provide for the missing link. Our work – the paradigm of an interaction context-sensitive pervasive multimodal multimedia computing system is an architectural design that exhibits adaptability to a much larger context called interaction context. It is intelligent and pervasive, meaning it is functional even when the end user is stationary or on the go. It is conceived with two purposes in mind. First, given an instance of interaction context, one which evolves over time, our system determines the optimal modalities that suit such interaction context. By optimal, we mean a selection decision on appropriate multimodality based on the given interaction context, available media devices that support the modalities and user preferences. We designed a mechanism (i.e. a paradigm) that will do this task and simulated its functionality with success. This mechanism employs machine learning (Mitchell 1997; Alpaydin 2004; Hina, Tadj et al. 2006) and uses case-based reasoning with supervised learning (Kolodner 1993; Lajmi, Ghedira et al. 2007). An input to this decision-making component is an instance of interaction context and its output is the optimal modality and its associated media devices that are for activation. This mechanism is continuously monitoring the user’s context of interaction and on behalf of the user continuously adapts accordingly. This adaptation is through dynamic reconfiguration of the pervasive multimodal system’s architecture. Second, given an instance of interaction context and the user’s task and preferences, we designed a mechanism that allows the automatic selection of user’s applications, the preferred suppliers to these applications and the preferred quality of service (QoS) dimensions’ configurations of these suppliers. This mechanism does its task in consultation with computing resources, sensing the available suppliers and possible configuration restrictions within the given computing set-up. Apart from the above-mentioned mechanisms, we also formulated scenarios as to how a computing system must provide the user interface given that we have already identified the optimal modalities that suit the user’s context of interaction. We present possible configurations of unimodal and bimodal interfaces based on the given interaction context as well as user preferences. Our work is different from previous work in that while other systems capture, disseminate and consume context to suit the preferred domain of application, ours captures the interaction context and reconfigures its architecture dynamically in generic fashion in order that the user could continue working on his task anytime, anywhere he wishes regardless of the application domain the user wishes to undertake. In effect, the system that we have designed along with all of its mechanisms, being generic in design, can be adapted or integrated with ease or with very little modification into various computing systems of various domains of applications. Simulations and mathematical formulations were provided to support our ideas and concepts related to the design of the paradigm. An actual program in Java was developed to support our concept of a virtual machine for incremental interaction context

Naval Reserve support to information Operations Warfighting

Since the mid-1990s, the Fleet Information Warfare Center (FIWC) has led the Navy's Information Operations (IO) support to the Fleet. Within the FIWC manning structure, there are in total 36 officer and 84 enlisted Naval Reserve billets that are manned to approximately 75 percent and located in Norfolk and San Diego Naval Reserve Centers. These Naval Reserve Force personnel could provide support to FIWC far and above what they are now contributing specifically in the areas of Computer Network Operations, Psychological Operations, Military Deception and Civil Affairs. Historically personnel conducting IO were primarily reservists and civilians in uniform with regular military officers being by far the minority. The Naval Reserve Force has the personnel to provide skilled IO operators but the lack of an effective manning document and training plans is hindering their opportunity to enhance FIWC's capabilities in lull spectrum IO. This research investigates the skill requirements of personnel in IO to verify that the Naval Reserve Force has the talent base for IO support and the feasibility of their expanded use in IO.http://archive.org/details/navalreservesupp109451098

UBIDEV: a homogeneous service framework for pervasive computing environments

This dissertation studies the heterogeneity problem of pervasive computing system from the viewpoint of an infrastructure aiming to provide a service-oriented application model. From Distributed System passing through mobile computing, pervasive computing is presented as a step forward in ubiquitous availability of services and proliferation of interacting autonomous entities. To better understand the problems related to the heterogeneous and dynamic nature of pervasive computing environments, we need to analyze the structure of a pervasive computing system from its physical and service dimension. The physical dimension describes the physical environment together wit the technology infrastructure that characterizes the interactions and the relations within the environment; the service dimension represents the services (being them software or not) the environment is able to provide [Nor99]. To better separate the constrains and the functionalities of a pervasive computing system, this dissertation classifies it in terms of resources, context, classification, services, coordination and application. UBIDEV, as the key result of this dissertation, introduces a unified model helping the design and the implementation of applications for heterogeneous and dynamic environments. This model is composed of the following concepts: • Resource: all elements of the environment that are manipulated by the application, they are the atomic abstraction unit of the model. • Context: all information coming from the environment that is used by the application to adapts its behavior. Context contains resources and services and defines their role in the application. • Classification: the environment is classified according to the application ontology in order to ground the generic conceptual model of the application to the specific environment. It defines the basic semantic level of interoperability. • Service: the functionalities supported by the system; each service manipulates one or more resources. Applications are defined as a coordination and adaptation of services. • Coordination: all aspects related to service composition and execution as well as the use of the contextual information are captured by the coordination concept. • Application Ontology: represents the viewpoint of the application on the specific context; it defines the high level semantic of resources, services and context. Applying the design paradigm proposed by UBIDEV, allows to describe applications according to a Service Oriented Architecture[Bie02], and to focus on application functionalities rather than their relations with the physical devices. Keywords: pervasive computing, homogenous environment, service-oriented, heterogeneity problem, coordination model, context model, resource management, service management, application interfaces, ontology, semantic services, interaction logic, description logic.Questa dissertazione studia il problema della eterogeneit`a nei sistemi pervasivi proponendo una infrastruttura basata su un modello orientato ai servizi. I sistemi pervasivi sono presentati come un’evoluzione naturale dei sistemi distribuiti, passando attraverso mobile computing, grazie ad una disponibilit`a ubiqua di servizi (sempre, ovunque ed in qualunque modo) e ad loro e con l’ambiente stesso. Al fine di meglio comprendere i problemi legati allintrinseca eterogeneit`a dei sistemi pervasivi, dobbiamo prima descrivere la struttura fondamentale di questi sistemi classificandoli attraverso la loro dimensione fisica e quella dei loro servizi. La dimensione fisica descrive l’ambiente fisico e tutti i dispositivi che fanno parte del contesto della applicazione. La dimensione dei servizi descrive le funzionalit`a (siano esse software o no) che l’ambiente `e in grado di fornire [Nor99]. I sistemi pervasivi vengono cos`ı classificati attraverso una metrica pi `u formale del tipo risorse, contesto, servizi, coordinazione ed applicazione. UBIDEV, come risultato di questa dissertazione, introduce un modello uniforme per la descrizione e lo sviluppo di applicazioni in ambienti dinamici ed eterogenei. Il modello `e composto dai seguenti concetti di base: • Risorse: gli elementi dell’ambiente fisico che fanno parte del modello dellapplicazione. Questi rappresentano l’unit`a di astrazione atomica di tutto il modello UBIDEV. • Contesto: le informazioni sullo stato dell’ambiente che il sistema utilizza per adattare il comportamento dell’applicazione. Il contesto include informazioni legate alle risorse, ai servizi ed alle relazioni che li legano. • Classificazione: l’ambiente viene classificato sulla base di una ontologia che rappresenta il punto di accordo a cui tutti i moduli di sistema fanno riferimento. Questa classificazione rappresenta il modello concettuale dell’applicazione che si riflette sull’intero ambiente. Si definisce cos`ı la semantica di base per tutto il sistema. • Servizi: le funzionalit`a che il sistema `e in grado di fornire; ogni servizio `e descritto in termini di trasformazione di una o pi `u risorse. Le applicazioni sono cos`ı definite in termini di cooperazione tra servizi autonomi. • Coordinazione: tutti gli aspetti legati alla composizione ed alla esecuzione di servizi cos`ı come l’elaborazione dell’informazione contestuale. • Ontologia dell’Applicazione: rappresenta il punto di vista dell’applicazione; definisce la semantica delle risorse, dei servizi e dell’informazione contestuale. Applicando il paradigma proposto da UBIDEV, si possono descrivere applicazioni in accordo con un modello Service-oriented [Bie02] ed, al tempo stesso, ridurre l’applicazione stessa alle sue funzionalit`a di alto livello senza intervenire troppo su come queste funzionalit` a devono essere realizzate dalle singole componenti fisiche

Context awareness in an adaptive personal health assistant

Estágio realizado no INESC-Porto e orientado pelo Eng.º Artur Jorge da Silva RochaTese de mestrado integrado. Engenharia Informátca e Computação. Faculdade de Engenharia. Universidade do Porto. 200