ppxscal/embedding_network huggingface dataset:
Answering queries using views: A survey
Authors: Alon Y. Halevy
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2001)

The problem of answering queries using views is to find efficient methods of answering a query using a set of previously defined materialized views over the database, rather than accessing the database relations. The problem has recently received significant attention because of its relevance to a wide variety of data management problems. In query optimization, finding a rewriting of a query using a set of materialized views can yield a more efficient query execution plan. To support the separation of the logical and physical views of data, a storage schema can be described using views over the logical schema. As a result, finding a query execution plan that accesses the storage amounts to solving the problem of answering queries using views. Finally, the problem arises in data integration systems, where data sources can be described as precomputed views over a mediated schema. This article surveys the state of the art on the problem of answering queries using views, and synthesizes the disparate works into a coherent framework. We describe the different applications of the problem, the algorithms proposed to solve it and the relevant theoretical results.
Flight String Models for Aircraft Fleeting and Routing
Authors: Cynthia Barnhart, Natashia L. Boland, Lloyd W. Clarke, Ellis L. Johnson, George L. Nemhauser, Rajesh G. Shenoi
Venue: Transportation Science (1998)

Given a schedule of flight legs to be flown by an airline, the fleet assignment problem is to determine the minimum cost assignment of flights to aircraft types, called fleets, such that each scheduled flight is assigned to exactly one fleet, and the resulting assignment is feasible to fly given a limited number of aircraft in each fleet. Then the airline must determine a sequence of flights, or routes, to be flown by individual aircraft such that assigned flights are included in exactly one route, and all aircraft can be maintained as necessary. This is referred to as the aircraft routing problem. In this paper, we present a single model and solution approach to solve simultaneously the fleet assignment and aircraft routing problems. Our approach is robust in that it can capture costs associated with aircraft connections and complicating constraints such as maintenance requirements. By setting the number of fleets to one, our approach can be used to solve the aircraft routing problem alone. We show how to extend our model and solution approach to solve aircraft routing problems with additional constraints requiring equal aircraft utilization. With data provided by airlines, we provide computational results for the combined fleet assignment and aircraft routing problems without equal utilization requirements and for aircraft routing problems requiring equal aircraft utilization.
A framework for studying substitution
Authors: Härmel Nestra
Venue: Acta Cybernetica (2002)

This paper describes a framework for handling bound variable renaming and substitution mathematically rigorously with the aim at the same time to stay as close as possible to human intuitive preconception about the phenomena, so that proofs could be deduced from intuitive motivations more directly than in the case of standard approaches.The theory is developed for general multi-sorted term algebras with variable binding. Therefore, the results hold for a wide class of term calculi such as the λ-calculus, first-order predicate logic, the abstract syntax of programming languages etc.
Computational complexity of optimization and crude range testing: a new approach motivated by fuzzy optimization
Authors: G. William Walster, Vladik Kreinovich
Venue: Fuzzy Sets and Systems (2003)

It is often important to test whether the maximum maxB f of a given function f on a given set B is smaller than a given number C. This "crude range testing" (CRT) problem is one of the most important problems in the practical application of interval analysis. Empirical evidence shows that the larger the difference C - maxB f, the easier the test. In general, the fewer global maxima, the easier the test; and finally, the further away global maxima are from each other, the easier the test. Using standard complexity theory to explain these empirical observations fails because the compared CRT problems are all NP-hard. In this paper the analysis of fuzzy optimization is used to formalize the relative complexity of different CRT problems. This new CRT-specific relative complexity provides a new and "robust" theoretical explanation for the above empirical observations. The explanation is robust because CRT relative complexity takes numerical inaccuracy into consideration. The new explanation is important because it is a more reliable guide than empirical observations to developers of new solutions to the CRT problem.
A computational algorithm for handling the special uniques problem
Authors: M. J. Elliot, A. M. Manning, R. W. Ford
Venue: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (2002)

Many organizations require detailed individual-level information, much of which has been collected under guarantees of confidentiality. However, simple anonymization procedures, i.e. removing names and addresses, are insufficient for this to be ensured. The records belonging to certain individuals have a high probability of being identified (as their contents, or attributes, are unusual) and therefore have the potential to be recognized spontaneously - such records are referred to as special uniques. Consider, for example, a sixteen-year-old widow in a population survey. Confidentiality of a given dataset cannot be enabled until all special unique records are identified and either disguised or removed. However, to the knowledge of the authors, no exhaustive automated analysis of this nature has been conducted due to the demanding levels of computation and data storage that are required. This paper introduces a new algorithm that locates 'risky' records in discrete data by first identifying all unique attribute sets (up to a user-specified maximum size) and secondly by grading the 'risk' of each record by considering the number and distribution of unique attribute sets within each record. Empirical tests indicate that the algorithm is highly effective at picking out 'risky' records from large samples of data.
Efficient filtering of XML documents with XPath expressions
Authors: C.-Y. Chan, P. Felber, M. Garofalakis, R. Rastogi
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2002)

The publish/subscribe paradigm is a popular model for allowing publishers (i.e., data generators) to selectively disseminate data to a large number of widely dispersed subscribers (i.e., data consumers) who have registered their interest in specific information items. Early publish/subscribe systems have typically relied on simple subscription mechanisms, such as keyword or &rdquo;bag of words&rdquo; matching, or simple comparison predicates on attribute values. The emergence of XML as a standard for information exchange on the Internet has led to an increased interest in using more expressive subscription mechanisms (e.g., based on XPath expressions) that exploit both the structure and the content of published XML documents. Given the increased complexity of these new data-filtering mechanisms, the problem of effectively identifying the subscription profiles that match an incoming XML document poses a difficult and important research challenge. In this paper, we propose a novel index structure, termed XTrie, that supports the efficient filtering of XML documents based on XPath expressions. Our XTrie index structure offers several novel features that, we believe, make it especially attractive for large-scale publish/subscribe systems. First, XTrie is designed to support effective filtering based on complex XPath expressions (as opposed to simple, single-path specifications). Second, our XTrie structure and algorithms are designed to support both ordered and unordered matching of XML data. Third, by indexing on sequences of elements organized in a trie structure and using a sophisticated matching algorithm, XTrie is able to both reduce the number of unnecessary index probes as well as avoid redundant matchings, thereby providing extremely efficient filtering. Our experimental results over a wide range of XML document and XPath expression workloads demonstrate that our XTrie index structure outperforms earlier approaches by wide margins.
On the Relation Between Option and Stock Prices: A Convex Optimization Approach
Authors: Dimitris Bertsimas, Ioana Popescu
Venue: Operations Research (2002)

The idea of investigating the relation of option and stock prices based just on the no-arbitrage assumption, but without assuming any model for the underlying price dynamics, has a long history in the financial economics literature. We introduce convex and, in particular semidefinite optimization methods, duality, and complexity theory to shed new light on this relation. For the single stock problem, given moments of the prices of the underlying assets, we show that we can find best-possible bounds on option prices with general payoff functions efficiently, either algorithmically (solving a semidefinite optimization problem) or in closed form. Conversely, given observable option prices, we provide best-possible bounds on moments of the prices of the underlying assets, as well as on the prices of other options on the same asset by solving linear optimization problems. For options that are affected by multiple stocks either directly (the payoff of the option depends on multiple stocks) or indirectly (we have information on correlations between stock prices), we find nonoptimal bounds using convex optimization methods. However, we show that it is NP-hard to find best possible bounds in multiple dimensions. We extend our results to incorporate transactions costs.
The role of abduction in chance discovery
Authors: Akinori Abe
Venue: New Generation Computing (2003)

Recently, researches on discovery science and knowledge discovery have been carried out in various fields. Basically they are types of learning that learn tendencies from the sets of data of the same or similar categories. In this sense, discovery is to discover the tendencies. As a result, they cannot predict the events that are different from the trend. On the other hand, abduction is thought of as an explanatory reasoning. Indeed, abduction is a reasoning to generate hypotheses to explain an observation. However, the original meaning of abduction was to discover new things that cannot be known in a simple way. In this paper, abduction is defined using the original definition that discovers something that cannot be easily predicted. Then, this paper shows a role of abduction that can suggest or foresee the events that are different from the trend. In fact, Abductive Analogical Reasoning that can generate new hypotheses is adopted to solve the problem.
Error estimates for the discrete inversion of hysteresis and creep operators
Authors: Pavel Krejčí, Klaus Kuhnen
Venue: Mathematics and Computers in Simulation (2003)

The accuracy of a numerical scheme for real-time inverse control of piezoelectric actuators taking into account both hysteresis and creep effects is analyzed with respect to the time step and the memory discretization parameter. It is shown that the error is of the first-order for Lipschitz continuous inputs.
Review of "Highly parallel computations: Algorithms and applications" by M.P. Bekakos, WIT press 2001
Venue: Ubiquity (2002)

How scientists will use "metacomputational" facilities to solve complex problems.
Randomized approximations of the constraint satisfaction problem
Authors: Hoong Chuin Lau, Osamu Watanabe
Venue: Nordic Journal of Computing (1996)

We consider the Weighted Constraint Satisfaction Problem (W-CSP) which is a fundamental problem in Artificial Intelligence and a generalization of important combinatorial problems such as MAX CUT and MAX SAT. In this paper, we prove non-approximability properties of W-CSP and give improved approximations of W-CSP via randomized rounding of linear programming and semidefinite programming relaxations. Our algorithms are simple to implement and experiments show that they are run-time efficient.
Too Much of a Good Thing? Product Proliferation and Organizational Failure
Authors: William P. Barnett, John Freeman
Venue: Organization Science (2001)

When organizations make important changes, such as introducing products based on new technologies, they may gain strategic advantages but they also experience disruptions. We argue that these disruptions are especially strong when organizations introduce multiple products simultaneously, leading to a temporary increase in the hazard of organizational failure. To test this hypothesis, we study the effects of new product introduction on the survival of U.S. semiconductor manufacturers. We find that having a large number of products--especially innovative products--lowers organizational mortality rates, but that mortality rates increase because of the simultaneous introduction of multiple products. This hazard is substantial, amounting to an increase in the market exit rate of over 40% for the "average" case of simultaneous product innovation. These results are robust in models that control for a wide variety of other factors. Our findings call into question the idea that organizations can overcome disruptions from structural inertia by introducing multiple products simultaneously.
Networks of SMEs as virtual web organizations: an experimental program aimed at supporting SMEs in depressed areas of Italy
Authors: Roberto Tononi, Gianfrancesco Amorosi
Venue: Managing virtual web organizations in the 21st century: issues and challenges (2002)

ENEA, the Italian public institution for research on energy, new technologies and environment, is conducting a program aimed at supporting networks of small-medium enterprises (SMEs) in depressed regions of Italy.The program focuses on the experimentation of a business model for these networks and on the introduction of advanced tools and methods, mostly of concurrent engineering. The business model, developed within the program, has the basic features of a virtual Web organization.This chapter illustrates the organizational and functional model that has been defined in the framework of a cooperation between ENEA and the SMEs involved in the research program.
Bounding the efforts on congestion optimization for physical synthesis
Authors: Davide Pandini, Lawrence T. Pileggi, Andrzej J. Strojwas
Venue: Proceedings of the 13th ACM Great Lakes symposium on VLSI (2003)

In this era of Deep Sub-Micron (DSM) technologies, interconnects are becoming increasingly important as their effects strongly impact the integrated circuit (IC) functionality and performance. Moreover, logic block size is no longer determined exclusively by total cell area, and is often limited by wiring resources, yet synthesis optimization objectives are focused on minimizing the number and size of library cells. Methodologies that incorporate congestion within the logic synthesis have been proposed in the past. However, in [15] and [16] it was demonstrated that predicting the true congestion prior to layout is not possible, since different layout regions can have very different routing demands, and the effectiveness of any congestion minimization approach can only be evaluated after routing is completed within the assigned die size. In these works, congestion minimization efforts at the synthesis level are controlled by means of a global weighting factor in the technology mapping cost function. Nevertheless, due to the lack of accurate congestion models, during logic synthesis it is not possible to estimate a priori which values of the congestion minimization factor will yield a congestion-free synthesized netlist. In this paper, we derive practical bounds, which limit the search space for an optimal congestion minimization factor that produces a routable netlist within fixed floorplan constraints. Although we believe that a top-down single-pass congestion-aware logic synthesis is not going to work in general, the bounds obtained in this work can be used in a practical and robust congestion minimization methodology, which can be implemented into any commercial design flow.
A theory of may testing for actors
Authors: Prasannaa Thati, Reza Ziaei, Gul Agha
Venue: Proceedings of the IFIP TC6/WG6.1 Fifth International Conference on Formal Methods for Open Object-Based Distributed Systems V (2002)

The Actor model and π-calculus have served as the basis of a large body of research on concurrency. We represent the Actor model as a typed asynchronous π-calculus, called Aπ. The type system imposes a certain discipline on the use of names to capture actor properties such as uniqueness and persistence. We investigate the notion of may testing in Aπ and give a trace based characterization of it. Such a characterization simplifies reasoning about actor configurations as it does not involve quantification over all environments. We compare our characterization with that of asynchronous π-calculus, and highlight the differences that arise due to actor properties.
Development of a "Technology based business" course
Authors: Kumoli Ramakrishnan, Srinivasan Ragothaman
Venue: Journal of Computing Sciences in Colleges (2002)

University students are likely to be inadequately equipped for the world that confronts them after graduation from traditional programs, unless systematic exposure to these new and emerging developments is ensured. Given the rapid and continuous evolution of models and methods, we are unable to rely of traditional textbooks and lecture based courses. Providing a hybrid electronic business course, with a high degree of technology integration and requiring them to design and implement an online business would provide the motivation and the vehicle for educating themselves about business.This paper discusses the experience of a small Midwestern University responding to developments related to the pervasive role of technology and e-Business. A pilot technology based business course (capped at 24 students), was developed and taught by a multi-disciplinary team of three tenured faculty members. Participants analyzed real world e-commerce cases to learn about business and technology issues. Student teams (mix of MIS and other functional areas, as well as graduate /senior undergraduate) developed new business ventures (including a comprehensive business plan and a working web-site) as part of the requirements. Given the level of 'real world' interest in e-Businesses, the course proved exciting, fast paced, and current. We provide an in-depth analysis of the course development and implementation process, curriculum issues and pedagogies used. Results of the student survey covering student reactions to team exercises, web projects, computer cases and other issues are presented along with statistical analysis of survey data. The faculty members will teach it again, in response to student and administration requests.
On-line knowledge- and rule-based video classification system for video indexing and dissemination
Authors: Wensheng Zhou, Son Dao, C.-C. Jay Kuo
Venue: Information Systems (2002)

Current information and communication technologies provide the infrastructure to transport bits anywhere, but do not indicate how to easily and precisely access and/or route information at the semantic level. To facilitate intelligent access to the rich multimedia data over the Internet, we develop an on-line knowledge- and rule-based video classification system that supports automatic "indexing" and "filtering" based on the semantic concept hierarchy. This paper investigates the use of video and audio content analysis, feature extraction and clustering techniques for further video semantic concept classification. A supervised rule-based video classification system is proposed using video automatic segmentation, annotation and summarization techniques for seamless information browsing and updating. In the proposed system, a real-time scene-change detection proxy performs an initial video-structuring process by splitting a video clip into scenes. Motional, visual and audio features are extracted in real-time for every detected scene by using on-line feature-extraction proxies. Higher semantics are then derived through a joint use of low-level features along with classification rules in the knowledge base. Classification rules are derived through a supervised learning process that relies on some representative samples from each semantic category. An indexing and filtering process can now be built using the semantic concept hierarchy to personalize multimedia data based on users' interests. In real-time filtering, multiple video streams are blocked, combined, or sent to certain channels depending on whether or not the video streams are matched with the user's profile. We have extensively experimented and evaluated the classification and filtering techniques using basketball sports video data. In particular, in our experiment, the basketball video structure is examined and categorized into different classes according to distinct motional, visual and audio characteristics features by a rule-based classifier. The concept hierarchy describing the motional/visual/audio feature descriptors and their statistical relationships are reported in this paper along with detailed experimental results using on-line sports videos.
A subspace cascadic multigrid method for mortar elements
Authors: D. Braess, P. Deuflhard, K. Lipnikov
Venue: Computing (2002)

A cascadic multigrid (CMG) method for elliptic problems with strong material jumps is proposed and analyzed. Non-matching grids at interfaces between subdomains are allowed and treated by mortar elements. The arising saddle point problems are solved by a subspace confined conjugate gradient method as smoother for the CMG. Details of algorithmic realization including adaptivity are elaborated. Numerical results illustrate the efficiency of the new subspace CMG algorithm.
Mean-Risk Trade-Offs in Inductive Expert Systems
Authors: Vijay S. Mookerjee, Michael V. Mannino
Venue: Information Systems Research (2000)

Notably absent in previous research on inductive expert systems is the study of meanrisk trade-offs. Such trade-offs may be significant when there are asymmetries such as unequal classification costs, and uncertainties in classification and information acquisition costs. The objective of this research is to developmodels to evaluate mean-risk trade-offs in value-based inductive approaches. We develop a combined mean-risk measure and incorporate it into the Risk-Based induction algorithm. The mean-risk measure has desirable theoretical properties (consistency and separability) and is supported by empirical results on decision making under risk. Simulation results using the Risk-Based algorithm demonstrate: (i) an order of magnitude performance difference between mean-based and risk-based algorithms and (ii) an increase in the performance difference between these algorithms as either risk aversion, uncertainty, or asymmetry increases given modest thresholds of the other two factors.