A comparative study of exchange and aggregation models in the B2B e-marketplace

This research seeks to provide an economic framework for understanding two major forms of e-marketplaces: aggregation-oriented vs. exchange-oriented e-marketplaces. By analyzing the marginal benefit per transaction in alternative models, we are able to determine the most suitable B2B e-marketplace for a wide variety of product categories, market conditions, and procurement methods. For example, when companies sell commodities in a fragmented market, the aggregation model is suitable for spot purchasing, and the exchange model works best for systematic purchasing. In addition, the effect of supplier consolidation and information technology-enabled cost reduction on model selection is discussed.     

Analysis of numerical methods for the simulation of deformable models

Simulating deformable objects based on physical laws has become the most popular technique for modeling textiles, skin, or volumetric soft objects like human tissue. The physical model leads to an ordinary differential equation. Recently, several approaches to fast algorithms have been proposed.In this work, more profound numerical background about numerical stiffness is provided. Stiff equations impose stability restrictions on a numerical integrator. Some one-step and multistep methods with adequate stability properties are presented. For an efficient implementation, the inexact Newton method is discussed. Applications to 2D and 3D elasticity problems show that the discussed methods are faster and give higher-quality solutions than the commonly used linearized Euler method.     

A genetic algorithm approach for the cutting stock problem

In this paper, a genetic algorithm approach is developed for solving the rectangular cutting stock problem. The performance measure is the minimization of the waste. Simulation results obtained from the genetic algorithm-based approach are compared with one heuristic based on partial enumeration of all feasible patterns, and another heuristic based on a genetic neuro-nesting approach. Some test problems taken from the literature were used for the experimentation. Finally, the genetic algorithm approach was applied to test problems generated randomly. The simulation results of the proposed approach in terms of solution quality are encouraging when compared to the partial enumeration-based heuristic and the genetic neuro-nesting approach.     

An Experimental and Theoretical Comparison of Model Selection Methods

Machine Learning - We investigate the problem of model selection in the setting of supervised learning of boolean functions from independent random examples. More precisely, we compare methods for...     

Gadolinium-enhanced magnetic resonance angiography of the pelvis in patients with erectile impotence

This study evaluted the potential of contrast-enhanced digital-subtraction magnetic resonance angiography (CE-DS-MRA) for noninvasive angiographic delineation of the arterial supply of the penis in patients with erectile dysfunction. After induction of an erection with prostaglandin E, a three-dimensional fast imaging with steady-state precision (FISP) sequence with TE of 1.8–2 milliseconds, TR of 4.4–5 milliseconds, and flip angle of 40°–60° was used to obtain high-resolution angiograms of the pelvis and penis during the injection of gadolinium diethylenetriaminepentaacetic acid (Gd-DTPA) 0.3 mmol/kg body weight, within 30–50 seconds. DS maximum intensity projections (MIPs) and multiplanar reconstructions (MPRs) were compared with clinical work-up and directional Doppler ultrasound in 11 patients. In all 11 patients (100%), the arterial supply of the penis could be delineated from the aortic bifurcation via the iliac and internal pudendal arteries to the dorsal and deep penile arteries. Of the 22 internal pudendal arteries, 6 (27%) were occluded on CE-DS-MRA and 5 (23%) had stenoses, of which 4 (18%) were greater than 50%. In 7 patients (64%) good correlation between CE-DS-MRA and clinical findings and/or Doppler ultrasound was found; in 2 patients (18%), the correlation was moderate, and in 2 patients (18%) results were discrepant. In 6 patients (55%), MRA provided additional information to the clinical and Doppler ultrasound work-up. CE-DS-MRA can delineate small sessels such as the internal pudendal and penile arteries and thus has the potential to become a noninvasive angiography method in the work-up of erectile impotence. Supported by Siemens Medical Systems, Erlangen; Schering AG, Berlin; and Agfa-Gevaert AG, Leverkusen.     

Cognitive engineering of a new telephone operator workstation using COGNET

Many cognitive engineering methodologies for user-centered design involve modeling procedural knowledge; others deal with domain semantics or conceptual models. COGnitive NEwork of Tasks (COGNET) is a framework for modeling human cognition and decision-making which provides an integrated representation of the knowledge, behavioral actions, strategies and problem solving skills used in a domain or task situation, yielding a powerful cognitive engineering tool. A case study of the design of the user interface for a new telephone operator workstation is presented to illustrate the derivation of the design from the components of the COGNET model. The model does not directly convey any specific feature of the interface design, but rather a formal representation of what the user must do with the resulting interface. This information is then evolved through a set of transformations which systematically move toward design features, in a fully traceable manner.

Relevance to industry

With the increasing prevalence of technical systems in complex work domains, cognitive engineering is necessary in designing the user interface for those systems to promote efficient integration of person and machine. The cognitive engineering methodology presented here addresses that need.     

Context-free languages over infinite alphabets

In this paper we introduce context-free grammars and pushdown automata over infinite alphabets. It is shown that a language is generated by a context-free grammar over an infinite alphabet if and only if it is accepted by a pushdown automaton over an infinite alphabet. Also the generated (accepted) languages possess many of the properties of the ordinary context-free languages: decidability, closure properties, etc.. This provides a substantial evidence for considering context-free grammars and pushdown automata over infinite alphabets as a natural extension of the classical ones. Received November 27, 1995 / March 4, 1997     

An Autonomous Spacecraft Agent Prototype

This paper describes the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. The architecture supports challenging requirements of the autonomous spacecraft domain not usually addressed in mobile robot architectures, including highly reliable autonomous operations over extended time periods in the presence of tight resource constraints, hard deadlines, limited observability, and concurrent activity. A hybrid architecture, NMRA integrates traditional real-time monitoring and control with heterogeneous components for constraint-based planning and scheduling, robust multi-threaded execution, and model-based diagnosis and reconfiguration. Novel features of this integrated architecture include support for robust closed-loop generation and execution of concurrent temporal plans and a hybrid procedural/deductive executive.We implemented a prototype autonomous spacecraft agent within the architecture and successfully demonstrated the prototype in the context of a challenging autonomous mission scenario on a simulated spacecraft. As a result of this success, the integrated architecture has been selected to fly as an autonomy experiment on Deep Space One (DS-1), the first flight of NASA';s New Millennium Program (NMP), which will launch in 1998. It will be the first AI system to autonomously control an actual spacecraft.     

Rapid Anisotropic Diffusion Using Space-Variant Vision

Many computer and robot vision applications require multi-scale image analysis. Classically, this has been accomplished through the use of a linear scale-space, which is constructed by convolution of visual input with Gaussian kernels of varying size (scale). This has been shown to be equivalent to the solution of a linear diffusion equation on an infinite domain, as the Gaussian is the Green's function of such a system (Koenderink, 1984). Recently, much work has been focused on the use of a variable conductance function resulting in anisotropic diffusion described by a nonlinear partial differential equation (PDE). The use of anisotropic diffusion with a conductance coefficient which is a decreasing function of the gradient magnitude has been shown to enhance edges, while decreasing some types of noise (Perona and Malik, 1987). Unfortunately, the solution of the anisotropic diffusion equation requires the numerical integration of a nonlinear PDE which is a costly process when carried out on a uniform mesh such as a typical image. In this paper we show that the complex log transformation, variants of which are universally used in mammalian retino-cortical systems, allows the nonlinear diffusion equation to be integrated at exponentially enhanced rates due to the nonuniform mesh spacing inherent in the log domain. The enhanced integration rates, coupled with the intrinsic compression of the complex log transformation, yields a speed increase of between two and three orders of magnitude, providing a means of performing rapid image enhancement using anisotropic diffusion.     

Conjectural Equilibrium in Multiagent Learning

Learning in a multiagent environment is complicated by the fact that as other agents learn, the environment effectively changes. Moreover, other agents' actions are often not directly observable, and the actions taken by the learning agent can strongly bias which range of behaviors are encountered. We define the concept of a conjectural equilibrium, where all agents' expectations are realized, and each agent responds optimally to its expectations. We present a generic multiagent exchange situation, in which competitive behavior constitutes a conjectural equilibrium. We then introduce an agent that executes a more sophisticated strategic learning strategy, building a model of the response of other agents. We find that the system reliably converges to a conjectural equilibrium, but that the final result achieved is highly sensitive to initial belief. In essence, the strategic learner's actions tend to fulfill its expectations. Depending on the starting point, the agent may be better or worse off than had it not attempted to learn a model of the other agents at all.