18669821
Managing computing resources in intranets: an electronic commerce perspective
Abstract Intra-organizational networks (intranets) are increasingly being developed for information sharing and collaborative work in geographically dispersed organizations. However, organizations are increasingly realizing that having an intranet in itself may not provide expected increase in productivity and benefits. Intranet resources have to be managed appropriately and with organizational goals in mind for intranets to be a meaningful part of organizational environment. In this paper we provide a framework to manage the resources in the intranets using the concepts of electronic commerce. Specifically, we propose the creation of an electronic organizational unit, intranet Resource Management Unit (iRMU), that manages user requests using a dynamic priority pricing approach. The iRMU integrates a dynamic priority pricing approach with the concepts of topology management, security management, and software-agents based service construction to create a comprehensive resource management environment. The contribution of this paper is to provide a framework that integrates existing technological base with economic pricing approaches to create an economics-embedded intranet resource management approach.
166893960
Priority pricing of integrated services networks
30721210
Economic analysis of consumer purchase intentions in electronic and traditional retail channels: competitive and strategic implications
We develop a multiattribute economic model to analyze consumer behavior for traditional and electronic channels based on consumers' risk profiles and risk-neutral or risk-averse. We then conduct comparative analyses of consumer purchase decisions to derive strategies for different channels. We study the attitudinal and economic factors that lead to specific purchase decisions under different combinations of price, delivery time, and product customization. We develop theoretical propositions concerning consumer channel switching behavior, incentives to consumers, and pricing strategies for different channels. We also use simulations to gain insights for cases where analytical model becomes intractable.
7914809
Predicting Bidders' Willingness to Pay in Online Multiunit Ascending Auctions: Analytical and Empirical Insights
We develop a real-time estimation approach to predict bidders' maximum willingness to pay in a multiunit ascending uniform-price and discriminatory-price (Yankee) online auction. Our two-stage approach begins with a bidder classification step, which is followed by an analytical prediction model. The classification model identifies bidders as either adopting a myopic best-response (MBR) bidding strategy or a non-MBR strategy. We then use a generalized bid-inversion function to estimate the willingness to pay for MBR bidders. We empirically validate our two-stage approach using data from two popular online auction sites. Our joint classification-and-prediction approach outperforms two other naive prediction strategies that draw random valuations between a bidder's current bid and the known market upper bound. Our prediction results indicate that, on average, our estimates are within 2% of bidders' revealed willingness to pay for Yankee and uniform-price multiunit auctions. We discuss how our results can facilitate mechanism-design changes such as dynamic-bid increments and dynamic buy-it-now prices.
17233820
IT-enabled transparent electronic markets: the case of the air travel industry
The electronic market hypothesis predicts that by reducing coordination costs, information technology (IT) will shift industrial organization from hierarchical to market-based forms of economic activity. While academic researchers and practitioners have witnessed these shifts with the advent of the Internet, there is little understanding about the process and the underlying forces that drive them. In this paper, we provide an in-depth analysis of the air travel industry, which has recently experienced significant IT-driven transformations. We conclude that, together with IT, pro-competitive laws and the information-intensive nature of air travel products have triggered competition for consumers with transparent market mechanisms, which is leading to the emergence of more transparent electronic markets in the air travel industry.
57631
Insights and analyses of online auctions
14792710
Enabling analysts in managed services for CRM analytics
Data analytics tools and frameworks abound, yet rapid deployment of analytics solutions that deliver actionable insights from business data remains a challenge. The primary reason is that on-field practitioners are required to be both technically proficient and knowledgeable about the business. The recent abundance of unstructured business data has thrown up new opportunities for analytics, but has also multiplied the deployment challenge, since interpretation of concepts derived from textual sources require a deep understanding of the business. In such a scenario, a managed service for analytics comes up as the best alternative. A managed analytics service is centered around a business analyst who acts as a liaison between the business and the technology. This calls for new tools that assist the analyst to be efficient in the tasks that she needs to execute. Also, the analytics needs to be repeatable, in that the delivered insights should not depend heavily on the expertise of specific analysts. These factors lead us to identify new areas that open up for KDD research in terms of 'time-to-insight' and repeatability for these analysts. We present our analytics framework in the form of a managed service offering for CRM analytics. We describe different analyst-centric tools using a case study from real-life engagements and demonstrate their effectiveness.
6504247
Hardware Diagnosis as Program Debugging
Horn clauses provide a useful framework for writing executable structural representations for digital circuits. This paper discusses how these representations can be used to diagnose faulty circuits using algorithmic program debugging techniques developed by Shapiro. The sound theoretical basis of these techniques is one of the major advantages of this approach. This framework also provides a new perspective on some of the hardware diagnosis techniques suggested in the literature.
18770378
A new model for the recovery of cylindrical structures from medical image data
We introduce a novel analytic model formulation for recovering cylindrical structures (e.g., blood vessels) from segmented 3-D medical image data. Unlike all previous formulations, our model is capable of describing a cylinder with an arbitrary spine (a space curve based on cubic B-splines) and arbitrary cross section which is guaranteed to be orthogonal to the spine. Given this expressiveness, we are able to provide a second order continuous approximation to the centerline of nearly any tubular object. This information may be used for such tasks as a reformatting of the original image data in order to visually detect stenoses or aneurysms. In addition, the cross-section parameter values of our model may aid in automatically isolating these regions. We maintain a relatively simple cross-section function to make this detection straightforward (note that any cross-section function is possible). To describe fine detail in the data, we employ local finite element deformations from the model surface. Thus we are able to recover gross geometric approximations as well as quantify characteristics of the object such as its surface area. We apply our model to the recovery of both a healthy and diseased aorta from segmented CT acquisitions.
7664269
Management of Conflicting Obligations in Self-Protecting Policy-Based Systems
Policy-based management of business systems is increasingly becoming the norm for autonomic computing since these systems can adapt to the changing needs and increasing complexity of the underlying organizations or enterprises. One of the vital characteristics of these systems is self-protection, ie., the ability to secure information and resources, by anticipating, detecting, identifying and protecting against any form of unauthorised access and permitting all authorised accesses based on the users' roles and pre-established policies. In this paper, we focus on one aspect of self-protecting autonomous systems, which is, how to automatically enforce privacy policies related to data handling, for compliance and auditing purposes. The automatic management of privacy sensitive information based on enterprise policies that are driven by a combination of user preferences, internal objectives and external regulations is a key aspect to any enterprise to prevent misuse of this information. These policies extend beyond simple authorization rules, and also mandate obligations to be enforced under certain conditions. One issue in the automatic enforcement of obligations is the presence of conflicts among different obligations which mandate different actions on the same resource, based on different conditions in which the resource is accessed. In this paper we propose algorithms for detecting and resolving conflicts among obligations in both static and runtime environments. We then briefly describe our prototype obligation management system with the conflict resolution module that achieves the automated enforcement of obligations for data-handling based on privacy policies
116973756
Surface and volumetric segmentation of complex 3-D objects using parametric shape models
The problem of part definition, description, and decomposition is central to the shape recognition systems. In this dissertation, we develop an integrated framework for segmenting dense range data of complex 3-D scenes into their constituent parts in terms of surface and volumetric primitives. Unlike previous approaches, we use geometric properties derived from surface, as well as volumetric models, to recover structured descriptions of complex objects without a priori domain knowledge or stored models. 
To recover shape descriptions, we use bi-quadric models for surface representation and superquadric models for object-centered volumetric representation. The surface segmentation uses a novel approach of searching for the best piecewise description of the image in terms of bi-quadric (z = f(x, y)) models. It is used to generate the region adjacency graphs, to localize surface discontinuities, and to derive global shape properties of the surfaces. A superquadric model is recovered for the entire data set and residuals are computed to evaluate the fit. The goodness-of-fit value based on the inside-outside function, and the mean-squared distance of data from the model provide quantitative evaluation of the model. The qualitative evaluation criteria check the local consistency of the model in the form of residual maps of overestimated and underestimated data regions. 
The control structure invokes the models in a systematic manner, evaluates the intermediate descriptions, and integrates them to achieve final segmentation. Superquadric and bi-quadric models are recovered in parallel to incorporate the best of the coarse-to-fine and fine-to-coarse segmentation strategies. The model evaluation criteria determine the dimensionality of the scene, and decide whether to terminate the procedure, or selectively refine the segmentation by following a global-to-local part segmentation approach. The control module generates hypotheses about superquadric models at clusters of underestimated data and performs controlled extrapolation of the part-model by shrinking the global model. As the global model shrinks and the local models grow, they are evaluated and tested for termination or further segmentation. 
We present results on real range images of scenes of varying complexity, including objects with occluding parts, and scenes where surface segmentation is not sufficient to guide the volumetric segmentation. We analyze the issue of segmentation of complex scenes thoroughly by studying the effect of missing data on volumetric model recovery, generating object-centered descriptions, and presenting a complete set of criteria for the evaluation of the superquadric models. We conclude by discussing the applications of our approach in data reduction, 3-D object recognition, geometric modeling, automatic model generation, object manipulation, and active vision.