Damian Arregui

Knowledge Pump: Supporting the Flow and Use of Knowledge

This chapter proposes an information technology system we call the Knowledge Pump for connecting and supporting electronic repositories and networked communities. Our objectives are two fold. The first is to facilitate getting the right information to the right people in a timely fashion. The second is to map community networks and repository content. These goals are complementary because the community and repository maps help channel the flow of information while the patterns inferred from information flow help refine the maps. By supporting these two elements of distribution and mapping, the Knowledge Pump can foster an environment that encourages the flow, use, and creation of knowledge.

Collaborative document monitoring

In this paper we present a second generation URL monitoring tool which enables the collaborative evaluation of URL content changes. In our implementation, a document monitoring agent works alongside a recommender system. Using information provided by the monitoring agent, the collaborative system alerts users when documents they are monitoring have changed. The monitoring agent provides automatic evaluation of the nature of the change. Users, however, add subjective evaluations; one users effort informs all others monitoring the same URL. Based on these subjective evaluations, the collaborative system can filter the changed URLs, providing customized notifications for each user based on individual preferences. In this paper, we describe the implemented system and usage results.

Rule-Based Transactional Object Migration over a Reflective Middleware

Object migration is an often overlooked topic in distributed object-oriented platforms. Most common solutions provide data serialization and code mobility across several hosts. But existing mechanisms fall short in ensuring consistency when migrating objects, or agents, involved in coordinated interactions with each other, possibly governed by a multi-phase protocol. We propose an object migration scheme addressing this issue, implemented on top of the Coordination Language Facility (CLF). It exploits the particular combination of features in CLF: the resource-based programming paradigm and the communication protocol integrating a negotiation and a transaction phase. We illustrate through examples how our migration mechanism goes beyond classical solutions. It can be fine-tuned to consider different requirements and settings, and thus be adapted to a variety of situations

Local contrast enhancement

We introduce a novel algorithm for local contrast enhancement. The algorithm exploits a background image which is estimated with an edge-preserving filter. The background image controls a gain which enhances important details hidden in underexposed regions of the input image. Our designs for the gain, edge-preserving filter and chrominance recovery avoid artifacts and ensure the superior image quality of our results, as extensively validated by user evaluations. Unlike previous local contrast methods, ours is fully automatic in the sense that it can be directly applied to any input image with no parameter adjustment. This is because we exploit a trainable decision mechanism which classifies images as benefiting from enhancement or otherwise. Finally, a novel windowed TRC mechanism based on monotonic regression ensures that the algorithm takes only 0.3 s to process a 10 MPix image on a 3 GHz Pentium.

Yaka: document notification and delivery across heterogeneous document repositories

Nowadays people have to deal with an increasing amount of information contained in electronic documents available from numerous heterogeneous, widely distributed sources. Keeping up to date with recently published material relevant to a particular topic has become a challenge in itself. The Yaka system aims at facilitating this task by providing notification and delivery services. Yaka relies on a flexible definition of subjects through intelligent wrapping of existing information sources. Users can subscribe to these subjects in order to be notified whenever new relevant documents are published. Yaka augments document notification with document meta-information obtained through a set of integrated linguistic services. From the notification message users can directly request the document content. Yaka then delivers this content, automatically transformed into the appropriate format, through a variety of delivery media. We describe the Yaka functionality, its architecture and how we deployed it within Xerox.

Resource-Based Scripting to Stitch Distributed Components

This paper proposes the Resource-Based Programming paradigm as support for the design, implementation, debugging and tuning of distributed applications. This paradigm considers components as resource managers and expresses the application logic through scriptable transactional resource manipulations. In this paper, we describe the benefits deriving from such a paradigm both from a theoritical and from a practical point of view. We first introduce the resource-based paradigm in itself and the CLF middleware [3] that implements it. We then illustrate through an example application the various advantages of using it in the context of distributed applications.

Addressing scalability issues using the CLF middleware

This article illustrates how to easily address scalability issues within distributed applications built on top of the Coordination Language Facility (CLF) middleware. CLF provides a distributed object computing framework with high expressiveness, flexibility and dynamicity. Our solutions rely on a core set of techniques such as replication, caching and distribution. We decline them along a geographical, a numerical, and an administrative dimension. We illustrate our approach with examples taken from Yaka, an application in the field of knowledge management and document awareness. In the context of this application we show in detail how the coordination model of the CLF and its associated scripting language enable straightforward solutions to various scalability issues.