ppxscal/embedding_network huggingface dataset:
Challenging the Paradigms on Up-Stream B2B E-Commerce?
Authors: Niels Christian Juul, Kim Viborg Andersen, Sara Korzen-Bohr
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 7 - Volume 7 (2004)

Based on a survey (N=392) of adoption of B2B e-commerce within the up-stream part of the Danish grocery sector value chain, this paper shows that technical-rational arguments and organizational readiness hold explanatory strength for adoption whereas the power and market perspective fails to explain adoption of e-commerce. Also, we found that factors that can explain e-commerce adoption fail to explain any pattern in the adoption data for the Web-EDI subset of ecommerce. Further on, the paper calls for a careful examination on how we design future studies. The paper suggests that rather than just replicating variables from previous generations of B2B e-commerce, focus should be directed towards a new set of variables forexplaining the uptake of XML-based e-commerce.
Navigation of a Mobile System with Parametrically Uncertain State Vector
Authors: S. A. Gusarin, V. A. Pogorelov
Venue: Automation and Remote Control (2003)

Navigation of a mobile system with parametrically uncertain state vector is studied. The required navigation accuracy is attained through orientation control of the gyrostabilized platform and identification of the parameters of the model of the platform drift. A wide range of functionals that depend on the a posteriori distribution density can be used as the optimization criteria since the solution is general. In the numerical example, the Shannon criterion is used as the optimization criterion.
Three Hardware Implementations for the Binary Modular Exponentiation: Sequential, Parallel and Systolic
Authors: Nadia Nedjah, Luiza de Macedo Mourelle
Venue: Proceedings of the 15th Symposium on Computer Architecture and High Performance Computing (2003)

Modular exponentiation is the cornerstone computation performed in public-key cryptographysystems such as the RSA cryptosystem. The operation is time consuming for large operands. This paper describes the characteristics of three architectures designed to implement modular exponentiation using the fast binary method: the first FPGA prototype has a sequentialarchitecture, the second has a parallel architecture and the third has a systolic array-based architecture. The paper compares the three prototypes using the time × area classic factor. All three prototypes implement the modular multiplication using the popular Montgomery algorithm.
Margin-based local regression for adaptive filtering
Authors: Yiming Yang, Bryan Kisiel
Venue: Proceedings of the twelfth international conference on Information and knowledge management (2003)

Adaptive information filtering is an open challenge in information retrieval. One of the tough issues is the optimization of decision thresholds over time, based on partial relevance feedback on the system-retrieved documents in chronological order. We developed a new approach, namely margin-based local regression, that automatically adjusts the thresholds based on a sliding window over the truly positive examples for which the system predicted "yes" with respect to a particular class, and a second sliding window over the other documents being processed by the system. Using the means of the scores of the documents in the two windows, we monitor the temporal drifting of the margin that is a function of both the current classification model and the threshold calibration strategy, and that suggests the bounds for the optimal threshold at a given time. Examining this approach together with a Rocchio-style classifier on the TREC 2001 and TREC 2002 benchmark data sets in adaptive filtering, we obtained significant improvements in performance (measured using Fβ=0.5) over the baseline system that did not adapt the threshold over time, and the best result ever reported on the TREC 2002 benchmark corpus for adaptive filtering evaluations. These empirical results suggest that it is important to use both system-accepted and system-rejected documents to optimize thresholds instead of just using system-accepted documents alone, as well as to make the thresholding function temporally sensitive to the shifting centroids of on-topic and off-topic documents.
Closed-form expressions of some stochastic adapting equations for nonlinear adaptive activation function neurons
Authors: Simone Fiori
Venue: Neural Computation (2003)

In recent work, we introduced nonlinear adaptive activation function (FAN) artificial neuron models, which learn their activation functions in an unsupervised way by information-theoretic adapting rules. We also applied networks of these neurons to some blind signal processing problems, such as independent component analysis and blind deconvolution. The aim of this letter is to study some fundamental aspects of FAN units' learning by investigating the properties of the associated learning differential equation systems.
Simplified simulation methods for polyphase brushless DC motors
Authors: J. Figueroa, C. Brocart, J. Cros, P. Viarouge
Venue: Mathematics and Computers in Simulation (2003)

This paper presents a simulation method for brushless DC motors. The purpose of this method is to provide a solution to the initial design process, where the simulation speed is important due to the numerous variables that have to be considered. The method requires a reduced number of parameters in order to simplify it and to facilitate the design process. It is applicable to polyphase motors regardless of its connection or phase number. The simulation method can simulate the phase current control system or a DC bus current feedback system. The later control system is widely used in low-cost brushless DC motors. The simulation method is based upon the average value modelling of the inverter leg, at the PWM scale, in different modulation conditions, modelling almost all the inverter structures with transistors as active elements. The experimental results from a seven-phase brushless DC motor with one uncontrolled phase validate the modelling method. The comparison of the average torque, the current, voltage and torque waveforms in several operating conditions shows that the simulation method can predict the comportment of a brushless DC motor without an excessive computational burden, so it can be readily used as a design tool for this kind of motor.
Closed formulas for the numbers of small independent sets and matchings and an extremal problem for trees
Authors: Charles Delorme, Odile Favaron, Dieter Rautenbach
Venue: Discrete Applied Mathematics (2003)

We derive closed formulas for the numbers of independent sets of size at most 4 and matchings of size at most 3 in graphs without small cycles that depend only on the degree sequence and the products of the degrees of adjacent vertices.As a related problem we describe an algorithm that determines a tree of given degree sequence that maximizes the sum of the products of the degrees of adjacent vertices.
A Knowledge Scoring Engine (KSE) for Real-Time Knowledge Base Generation Used in Intelligent Tutoring Systems
Authors: Mark T. Jodlowski, Stephanie M. Doane
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 5 - Volume 5 (2004)

This paper provides a detailed account of a tool developed to facilitate the development of individual computational cognitive models to be used in intelligent tutoring systems (ITS). A generic tool that we will call the Knowledge Scoring Engine (KSE) reads eye tracking and human performance data in real-time, parses the data into discrete events, and uses a knowledge inference generator to build and update student knowledge bases. Student knowledge bases are generated by interpreting actions in real-time based on the context in which the actions take place. The knowledge bases generated by KSE are used by ADAPT, a comprehension-based framework construction-integration model of pilot action planning. This paper provides a detailed description of KSE, the current ADAPT architecture, how theADAPT model interacts with KSE, and the potential for future developments.
Finite Element Approximations to the Discrete Spectrum of the Schrödinger Operator with the Coulomb Potential
Authors: Weiying Zheng, Lung-an Ying
Venue: SIAM Journal on Numerical Analysis (2004)

In the present paper, the authors consider the Schrödinger operator H with the Coulomb potential defined in R3m, where m is a positive integer. Both bounded domain approximations to multielectron systems and finite element approximations to the helium system are analyzed. The spectrum of H becomes completely discrete when confined to bounded domains. The error estimate of the bounded domain approximation to the discrete spectrum of H is obtained. Since numerical solution is difficult for a higher-dimensional problem of dimension more than three, the finite element analyses in this paper are restricted to the S-state of the helium atom. The authors transform the six-dimensional Schrödinger equation of the helium S-state into a three-dimensional form. Optimal error estimates for the finite element approximation to the three-dimensional equation, for all eigenvalues and eigenfunctions of the three-dimensional equation, are obtained by means of local regularization. Numerical results are shown in the last section.
Expected Number of Distinct Part Sizes in a Random Integer Composition
Authors: P. Hitczenko, G. Stengle
Venue: Combinatorics, Probability and Computing (2000)

An asymptotics, as n &rarr; &infin;, for the expected number of distinct part sizes in a random composition of an integer n is obtained.
Regexpcount, a symbolic package for counting problems on regular expressions and words
Authors: Pierre Nicodème
Venue: Fundamenta Informaticae (2002)

In previous work [10], we considered algorithms related to the statistics of matches with words and regular expressions in texts generated by Bernoulli or Markov sources. In this work these algorithms are extended for two purposes: to determine the statistics of simultaneous counting of different motifs, and to compute the waiting time for the first match with a motif in a model which may be constrained. This extension also handles matches with errors. The package is fully implemented and gives access to high and low level commands. We also consider an example corresponding to a practical biological problem: getting the statistics for the number of matches of words of size 8 in a genome (a Markovian sequence), knowing that an (overrepresented DNA protecting) pattern named Chi occurs a given number of times.
Multiresolution Estimates of Classification Complexity
Authors: Sameer Singh
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)

Abstract--In this paper, we study two measures of classification complexity based on feature space partitioning: "purity" and "neighborhood separability." The new measures of complexity are compared with probabilistic distance measures and a number of other nonparametric estimates of classification complexity on a total of 10 databases from the University of Calfornia, Irvine, (UCI) repository.
Heuristic QoS Routing Based on Possibility Distribution and Soft Computing
Authors: Jiuchuan Hu, Hongke Zhang, Sidong Zhang
Venue: Proceedings of the 2003 International Conference on Computer Networks and Mobile Computing (2003)

The quality of service (QoS) is often degraded by the inefficient management of networks service resources since the QoS routing decisions are often forced to base on the imprecisestate information of the resources. The impreciseness are introduced by the dynamic changes of networks and the non-negligible delay in forwarding the state messages. By managing the possibility distribution of the imprecise state information with soft computing, we proposea heuristic QoS routing algorithm in this paper. The simulation results show that the algorithm can keep the QoS levels stable and routing robust. Therefore, the algorithm can be also used in the ad hoc network, wireless networks, etc. whose resource state is dominant relatively.
Concurrent MIN-MAX simulation
Authors: Ernst Ulrich, Karen Panetta Lentz, Stephen Demba, Rahul Razdan
Venue: Proceedings of the conference on European design automation (1991)

Parametric process variations, which are inherent in the manufacture of complex digital circuits, can cause variations in the timing characteristics of a digital device. These device timing variations can cause catastrophic failures to the intended logical operation of the whole design. Min-Max Timing Simulation is a simulation technique which is well suited to verify that a given design functions correctly, even under the influence of parametric process variations. Unfortunately, in the past, Min-Max Timing Simulation has been very expensive in simulation CPU time and in the amount of memory consumed. We present a technique, Concurrent Min-Max Simulation(CMMS), which employs the techniques developed in Concurrent Fault Simulation, to elegantly solve the Min-Max Timing simulation problem.
A K-NN Associated Fuzzy Evidential Reasoning Classifier with Adaptive Neighbor Selection
Authors: Hongwei Zhu, Otman Basir
Venue: Proceedings of the Third IEEE International Conference on Data Mining (2003)

The paper presents a fuzzy evidential reasoning algorithmin light of the Dempster-Shafer evidence theory andthe K-nearest neighbor algorithm for pattern classification.Given an input pattern to be classified, each of its K nearestneighbors is viewed as an evidence source, in terms ofa fuzzy evidence structure. The distance between the inputpattern and each of its K nearest neighbors is usedfor mass determination while the contextual information ofthe nearest neighbor in the training sample space is formulatedby a fuzzy set in determining a fuzzy focal element.Therefore, pooling evidence provided by neighbors is realizedby a fuzzy evidential reasoning, where feature selectionis further considered through ranking and adaptive combinationof neighbors. A fast implementation scheme of thefuzzy evidential reasoning is also developed. Experimentalresults of classifying multi-channel remote sensing imageshave shown that the proposed approach outperforms the K-nearestneighbor (K-NN) algorithm [1], the fuzzy K-nearestneighbor (F-KNN) algorithm [2], the evidence-theoretic K-nearestneighbor (E-KNN) algorithm [3], and the fuzzy ex-tendedversion of E-KNN (FE-KNN) [4], in terms of theclassification accuracy and insensitivity to the number Kof nearest neighbors.
The role of computer science in undergraduate bioinformatics education
Authors: Debra T. Burhans, Gary R. Skuse
Venue: Proceedings of the 35th SIGCSE technical symposium on Computer science education (2004)

The successful implementation of educational programs in bioinformatics presents many challenges. The interdisciplinary nature of bioinformatics requires close cooperation between computer scientists and biologists despite inescapable differences in the ways in which members of these professions think. It is clear that the development of quality curricula for bioinformatics must draw upon the expertise of both disciplines. In addition, biologists and computer scientists can benefit from opportunities to carry out interdisciplinary research with one another. This paper examines the role of computer science in undergraduate bioinformatics education from the perspectives of two bioinformatics program directors. Their respective programs exemplify two substantively different approaches to undergraduate education in bioinformatics due to the fact that they are at markedly different institutions. One institution is a large, technical university, offering both undergraduate and graduate degrees in bioinformatics while the other is a small, Jesuit liberal arts college with an undergraduate program in bioinformatics. Despite these differences there is considerable overlap with respect to the role of computer science. This paper discusses the ways in which computer science has been integrated into these two undergraduate bioinformatics programs, compares alternative approaches, and presents some of the inherent challenges.
Self-manifestation of composite multimedia objects to satisfy security constraints
Authors: Vijayalakshmi Atluri, Nabil Adam, Ahmed Gomaa, Igg Adiwijaya
Venue: Proceedings of the 2003 ACM symposium on Applied computing (2003)

A composite multimedia object (cmo) is comprised of different media components such as text, video, audio and image, with a variety of constraints that must be adhered to. These constraints include synchronization and spatial relationships between components, as well as the confidentiality and integrity requirements on each component. While spatial and synchronization constraints are to preserve the semantics of the cmo, the security (confidentiality and integrity) constraints are to represent the access control policies and fidelity requirements. A subject (user) requesting access for a cmo may not possess the required credentials to meet the confidentiality constraints, or his computer system the desired capabilities to meet the integrity constraints. This necessitates modification to the original cmo.In this paper, we present a self-manifestation approach in which composite multimedia objects automatically manifest themselves to cater to the subjects' credentials, and the capabilities of their computer systems. We accomplish this in two steps. First, we present a logical model which is an enhanced Petri Net model, called multimedia color-time Petri net (MMCTPN) to represent the components as well as the constraints of the cmo. We then demonstrate how MMCTPN lends itself to automatic manifestation of the cmo when subject's credentials and capabilities activate it. Second, we show how the Petri net behavior can be implemented using the Synchronized Multimedia Integration Language (SMIL): SMIL, which is an extension of XML, supports specification of synchronization of the multimedia components and facilitates automatic rendering. When credentials are specified with digital certificates in some XML format, our system automatically modifies the SMIL document to satisfy the security constraints. We avoid multiple certificate verifications at the component sources by generating a single security token, when multiple credentials are required to view a component.
Corporate Governance, Takeovers, and Top-Management Compensation: Theory and Evidence
Authors: Richard M. Cyert, Sok-Hyon Kang, Praveen Kumar
Venue: Management Science (2002)

We examine, both theoretically and empirically, top-management compensation in the presence of agency conflicts when shareholders have delegated governance responsibilities to a self-interested Board of Directors (BOD). We develop a theoretical framework that explicitly incorporates the BOD as a strategic player, models the negotiation process between the CEO and the BOD in designing CEO compensation, and considers the impact of potential takeovers by large shareholders monitoring the CEO-BOD negotiations. In equilibrium, internal governance by the BOD and external takeover threats by a large shareholder act as substitutes in imposing managerial control, especially in constraining management's profligacy in awarding equity-based compensation to itself. The model emphasizes factors in the design of compensation contracts that are rarely considered in the literature, such as equity ownership of the largest outside shareholder and the firm's bankruptcy risk. It also provides new perspectives on factors that are often considered in the literature, such as firm size, firm performance, equity ownership of the BOD, and BOD structure. Our empirical tests lend considerable support for our theoretical predictions. Equity ownership of the largest external shareholder, that of the BOD, and the default risk, are strongly negatively related to the size of CEO equity compensation. Consistent with the theoretical model, these factors do not significantly influence the growth of fixed (or non-performance-related) compensation. We also find that the equity ownership of the BOD is more important in managerial compensation control than other BOD related variables, such as BOD size or the proportion of outside directors.
Exploiting uniqueness in query optimization
Authors: G. N. Paulley, Per-Åke Larson
Venue: Proceedings of the 1993 conference of the Centre for Advanced Studies on Collaborative research: distributed computing - Volume 2 (1993)

Consider an SQL query that specifies duplicate elimination via a DISTINCT clause. Because duplicate elimination often requires an expensive sort of the query result, it is often worthwhile to identify situations where the DISTINCT clause is unnecessary, to avoid the sort altogether. We prove a necessary and sufficient condition for deciding if a query requires duplicate elimination. The condition exploits knowledge about keys, table constraints, and query predicates. Because the condition cannot always be tested efficiently, we offer a practical algorithm that tests a simpler, sufficient condition. We consider applications of this condition for various types of queries, and show that we can exploit this condition in both relational and nonrelational database systems.
Fault-Tolerant Deployment of Embedded Software for Cost-Sensitive Real-Time Feedback-Control Applications
Authors: Claudio Pinello, Luca P. Carloni, Alberto L. Sangiovanni-Vincentelli
Venue: Proceedings of the conference on Design, automation and test in Europe - Volume 2 (2004)

Designing cost-sensitive real-time control systems for safety-critical applications requires a careful analysis of the cost/coverage trade-offs of fault-tolerant solutions. This further complicates the difficult task of deploying the embedded software that implements the control algorithms on the execution platform that is often distributed around the plant (as it is typical, for instance, in automotive applications). We propose a synthesis-based design methodology that relieves the designers from the burden of specifying detailed mechanisms for addressing platform faults, while involving them in the definition of the overall fault-tolerance strategy. Thus, they can focus on addressing plant faults within their control algorithms, selecting the best components for the execution platform, and de.ning an accurate fault model. Our approach is centered on a new model of computation, Fault Tolerant Data Flows (FTDF), that enables the integration of formal validation techniques.