p2r weblog
Wednesday, September 24, 2003
The goal of the Scarab project is to build an Artifact tracking system that has the following features:

Thursday, September 18, 2003
Omniformat image conversion freeware
OmniFormat is a free document conversion utility which allows dynamic conversion and image manipulation of over 75 file formats including HTML, DOC, XLS, WPD, PDF, JPG, GIF, TIF, PNG, PCX, PPT, PS, TXT, Photo CD, FAX and MPEG. For a full list of supported formats please see our FAQ page.

Wednesday, September 17, 2003
XMLBeans: The easiest way to use XML in Java
XMLBeans is a breakthrough technology from BEA that makes it incredibly easy for developers to access and manipulate XML data and documents in Java. For the first time, developers can gain a familiar and convenient Java object-based view of their XML data without losing access to the richness of the original, native XML structure and schema.

XMLBeans is based on an efficient XML token stream that provides easy navigation of XML data using cursors. This cursor interface is available for any XML document. If you have an XML Schema description of your document, XMLBeans will also provide Java class 'views' of the data. These Java classes enable easy read/write access to XML information and enforce XML Schema constraints. Because these Java views are based on the preserved, underlying XML representation, XMLBeans always maintains full fidelity of the original XML, and no information is ever lost. So instead of having to choose between full access to XML data through time-consuming traditional APIs like SAX and DOM or convenient but incomplete binding schemes, XMLBeans provides the best of both worlds.

Important Note: XMLBeans requires J2SE 1.4

XMLBeans - Overview
XMLBeans is an XML-Java binding tool that uses XML Schema as a basis for generating Java classes to be used to easily access XML instance data. It was designed to provide both easy access to XML information via convenient Java classes as well as complete access to the underlying XML, combining the best of low-level, full access APIs like SAX and DOM with the convenience of Java binding.

Wired 8.04: Why the future doesn't need us.
Our most powerful 21st-century technologies - robotics, genetic engineering, and nanotech - are threatening to make humans an endangered species.

By Bill Joy

Tuesday, September 16, 2003
AARIA Autonomous Agents at Rock Island Arsenal (dead link?)
AARIA (Autonomous Agents at Rock Island Arsenal), is an ARPA-sponsored project designing an autonomous agent based factory scheduler at the Rock Island Arsenal. The project team is headed by Intelligent Automation, Inc. (Rockville, MD) and includes the University of Cincinnati, Industrial Technology Institute, and Flavors Technology, Inc. The agents, programmed in objective-C and running on a network of Pentium based computers under PDO (Portable Distributed Objects), will actively represent each step on the ladder of manufacturing a part: going from the customer, through the sales representative, engineers, manufacturing processes, and finally to the raw materials.

This paper introduces the readers of the Proceedings to an important class of computer based simulation techniques known as Markov chain Monte Carlo (MCMC) methods. General properties characterizing these methods will be discussed, but the main emphasis will be placed on one MCMC method known as the Gibbs sampler. The Gibbs sampler permits one to simulate realizations from complicated stochastic models in high dimensions by making use of the model’s associated full conditional distributions, which will generally have a much simpler and more manageable form. In its most extreme version, the Gibbs sampler reduces the analysis of a complicated multivariate stochastic model to the consideration of that model’s associated univariate full conditional distributions.

A market mechanism is basically driven by a superposition of decisions of many agents optimizing their profit. The macroeconomic price dynamic is a consequence of the cumulated excess demand/supply created on this micro level. The behavior analysis of a small number of agents is well understood through the game theory. In case of a large number of agents one may use the limiting case that an individual agent does not have an influence on the market, which allows the aggregation of agents by statistic methods. In contrast to this restriction, we can omit the assumption of an atomic market structure, if we model the market through a multi-agent approach.
The contribution of the mathematical theory of neural networks to the market price formation is mostly seen on the econometric side: neural networks allow the fitting of high dimensional nonlinear dynamic models. Furthermore, in our opinion, there is a close relationship between economics and the modeling ability of neural networks because a neuron can be interpreted as a simple model of decision making. With this in mind, a neural network models the interaction of many decisions and, hence, can be interpreted as the price formation mechanism of a market.

JGroups - The JGroups Project
JGroups is a toolkit for reliable multicast communication.
(Note that this doesn't necessarily mean IP Multicast, JGroups can also use transports such as TCP).
It can be used to create groups of processes whose members can send messages to each other. The main features include

RAIDb: Redundant Array of Inexpensive Databases
Abstract: Clusters of workstations become more and more popular to power data server applications such as large scale Web sites or e-Commerce applications. There has been much research on scaling the front tiers (web servers and application servers) using clusters, but data-bases usually remain on large dedicated SMP machines. In this paper, we address database performance scalability and high availability using clusters of commodity hardware. Our approach
consists of studying different replication and partitioning strategies to achieve various degree of performance and fault tolerance.
We propose the concept of Redundant Array of Inexpensive Databases (RAIDb). RAIDb is to databases what RAID is to disks. RAIDb aims at providing better performance and fault tolerance
than a single database, at low cost, by combining multiple database instances into an array of databases. Like RAID, we define different RAIDb levels that provide various cost/performance/fault tolerance tradeoffs. RAIDb-0 features full partitioning, RAIDb-1 offers
full replication and RAIDb-2 introduces an intermediate solution called partial replication, in which the user can define the degree of replication of each database table.

We present a Java implementation of RAIDb called Clustered JDBC or C-JDBC. C-JDBC achieves both database performance scalability and high availability at the middleware level without changing existing applications. We show, using the TPC-W benchmark, that RAIDb-2
can offer better performance scalability (up to 25%) than traditional approaches by allowing fine-grain control on replication. Distributing and restricting the replication of frequently written tables to a small set of backends reduces I/O usage and improves CPU utilization of each cluster node.

Monday, September 15, 2003
By James Odell et al.

Agents: Technology and Usage (Part 1)

Agents: Complex Systems (Part 2)

Vizional > Solutions > Adaptive Demand Management: "The Vizional Adaptive Demand Management application performs three major functions: synchronize independent demand, propagate dependent demand upstream, and enable complete order fulfillment. The application's three modules allow companies to intelligently and rapidly analyze, manage and shape customer demand and orders across the entire supply network. The Vizional Adaptive Demand Management application utilizes powerful, adaptive agents distributed across the supply network that monitor real-time demand information, detect variations in demand, coordinate relevant interactions and resolutions, and then dynamically adjust forecasts to the actual consumption signals. This results in an adaptive supply network that continuously synchronizes demand with supply, intelligently realigning plans and processes based on the specific business environment."

The TAC Supply Chain Management Game
Supply chain management is concerned with planning and coordinating the activities of organizations across the supply chain, from raw material procurement to finished goods delivery. In today’s global economy, effective supply chain management is vital to the competitiveness of manufacturing enterprises as it directly impacts their ability to meet changing market demands in a timely and cost effective manner. With annual worldwide supply chain transactions in trillions of dollars, the potential impact of performance improvements is tremendous. While today’s supply chains are essentially static, relying on long-term relationships among key trading partners, more flexible and dynamic practices offer the prospect of better matches between suppliers and customers as market conditions change. Adoption of such practices has however proven elusive, due to the complexity of many supply chain relationships and the difficulty in effectively supporting more dynamic trading practices. TAC SCM was designed to capture many of the challenges involved in supporting dynamic supply chain practices, while keeping the rules of the game simple enough to entice a large number of competitors to submit entries. The game has been designed jointly by a team of researchers from the e-Supply Chain Management Lab at Carnegie Mellon University and the Swedish Institute of Computer Science (SICS).

Towards Agent-Oriented Application Frameworks

Creating intelligence in the supply chain
(Computerworld Singapore - A Computerworld Mid-year Special: Out of the dark , 19 - 25 July 2002)
In the last two decades, the use of IT in the manufacturing sector was about the optimisation of production through systems such as MRP (materials resource planning) and ERP (enterprise resource planning). Over the next five years, the focus is expected to shift to the optimisation of global networks through the use of expert systems."

Agent-Oriented Supply-Chain Management
Abstract. The supply chain is a worldwide network of suppliers, factories, warehouses, distribution centers, and
retailers through which raw materials are acquired, transformed, and delivered to customers. In recent years, a new software architecture for managing the supply chain at the tactical and operational levels has emerged. It views the supply chain as composed of a set of intelligent software agents, each responsible for one or more activities in the supply chain and each interacting with other agents in the planning and execution of their responsibilities. This paper investigates issues and presents solutions for the construction of such an agent-oriented software architecture. The approach relies on the use of an agent building shell, providing generic, reusable, and guaranteed components
and services for communicative-act-based communication, conversational coordination, role-based organization modeling, and others. Using these components, we show two nontrivial agent-based supply-chain architectures able to support complex cooperative work and the management of perturbation caused by stochastic events in the supply chain.

Agent-Based Modeling vs. Equation-Based Modeling:
A Case Study and Users’ Guide

Abstract. In many domains, agent-based system modeling competes with equation-based approaches that identify system variables and evaluate or integrate sets of equations relating these variables. The distinction has been of great interest in a project that applies agent-based modeling to industrial supply networks, since virtually all computer-based modeling of such networks up to this point has used system dynamics, an approach based on ordinary differential
equations (ODE’s). This paper summarizes the domain of supply networks and illustrates how they can be modeled both with agents and with equations. It summarizes the similarities and differences of these two classes of models, and develops criteria for selecting one or the other approach.

Strategic Analytics Inc.
Agent-based (?) simulators for forecasting consumer-based portfolios (primarily financial industry)

Forecast of Business Performance using an Agent-based Model and Its Application to a Decision Tree-Monte Carlo Business Valuation
Only abstract available now .... seems interesting?

A few portals with focus on supply chain management and/or forecasting. Need to look into these and see if there is any value to be found? Some (but not all) seem interesting ...

Tuesday, September 09, 2003
Free Downloads

OptimalJ - Package Structure Analysis Tool


The OptimalJ - Package Structure Analysis Tool is a new tool for analyzing and improving the modular structure of Java programs, leading to product flexibility, comprehensibility and reduced development time.

The Package Structure Analysis Tool takes Java sources as input and:

Visualizes the dependencies between packages and classes with UML class diagrams.
Detects cycles in the dependency graph.
Recovers an intended architectural layering from a polluted implementation.
Suggests which dependencies should be removed to improve the structure.
Allows refactoring of the source model.
Immediately shows the effect of the refactoring on the dependency structure.
Allows source code to be verified against a design model.
Allows the refactoring to be applied to the source code (not in the free edition).
Read more about package design, layering and metrics.

Free Edition

A free edition of the Package Structure Analysis Tool can be downloaded (login required). This edition is fully functional, except that the functionality to refactor the source has been disabled. The download is about 1.3 MB. A full version is part of the OptimalJ suite.

Cool tool to analyze code?

Sunday, September 07, 2003
Hmm, makes more sense to manually include the following line in <head> section of Blogger template:
<base target="_blank">
Should launch links such as this in a new window?

Friday, September 05, 2003
"Restarting" log at http://w1.859.telia.com/~u85917743/weblog/p2rBlogger.html

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