ppxscal/embedding_network huggingface dataset:
Decision Making in an Agent-based Marketplace
Authors: Maria Joao Viamonte, Isabel Praca, Carlos Ramos, Zita Vale
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior, dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.
Modeling and Analysis of Generalized Slotted-Aloha MAC Protocols in Cooperative, Competitive and Adversarial Environments
Authors: Richard T. B. Ma, Vishal Misra, Dan Rubenstein
Venue: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (2006)

Aloha [1] and its slotted variant [2] are commonly deployed Medium Access Control (MAC) protocols in environments where multiple transmitting devices compete for a medium, yet may have difficulty sensing each other's presence. This paper models and evaluates the throughput that can be achieved in a system where nodes compete for bandwidth using a generalized version of slotted- Aloha protocols. We evaluate the channel utilization and fairness of these types of protocols for a variety of node objectives, including maximizing aggregate throughput of the channel, each node greedily maximizing its own throughput, and attacker nodes that attempt to jam the channel. If all nodes are selfish and greedily attempt to maximize their own throughputs, a situation similar to the traditional Prisoner's Dilemma[3] arises. Our results reveal that under heavy loads, greedy strategies reduce the utilization, and that attackers cannot do much better than attacking during randomly selected slots.
The dynamical inverse problem for a nonlinear Schrodinger equation using boundary control
Authors: M. Tomas-Rodriguez, S. P. Banks
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 3 (2003)

The problem of determining the potential in a nonlinear one-dimensional Schrodinger equation from dynamical boundary observations is considered. The problem will be solved by a combination of a recent approximation technique for nonlinear dynamical systems, which reduces them to sequences of linear, time-varying systems, and the derivation of a spectral theory for these systems.
Artisan bread manufacturing simulation
Authors: Alison R. Kulp
Venue: Proceedings of the 36th conference on Winter simulation (2004)

A large artisan bread company integrated automated elements such as conveyors, laser sensors, weighing devices and slicing machines with manual components such as hand kneading, loaf forming and scoring in a flexible manufacturing line capable of producing over 25 different types of bread in various shapes and sizes. A simulation of this system successfully identified bottlenecks and allowed additional capacity to be obtained. As a result, the company was able to postpone the purchase of a new manufacturing line by six months through the discovery of alternative ways to increase the output of the system. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Context logic as modal logic: completeness and parametric inexpressivity
Authors: Cristiano Calcagno, Philippa Gardner, Uri Zarfaty
Venue: ACM SIGPLAN Notices (2007)

Separation Logic, Ambient Logic and Context Logic are based on a similar style of reasoning about structured data. They each consist of a structural (separating) composition for reasoning about disjoint subdata, and corresponding structural adjoint(s) for reasoning hypothetically about data. We show how to interpret these structural connectives as modalities in Modal Logic and prove completeness results. The structural connectives are essential for describing properties of the underlying data, such as weakest preconditions for Hoare reasoning for Separation and Context Logic, and security properties for Ambient Logic. In fact, we introduced Context Logic to reason about tree update, precisely because the structural connectives of the Ambient Logic did not have enough expressive power. Despite these connectives being essential, first Lozes then Dawar, Gardner and Ghelli proved elimination results for Separation Logic and Ambient Logic (without quantifiers). In this paper, we solve this apparent contradiction. We study parametric inexpressivity results, which demonstrate that the structural connectives are indeed fundamental for this style of reasoning.
Iterative-Improvement-Based Heuristics for Adaptive Scheduling of Tasks Sharing Files on Heterogeneous Master-Slave Environments
Authors: Kamer Kaya Cevdet Aykanat
Venue: IEEE Transactions on Parallel and Distributed Systems (2006)

The scheduling of independent but file-sharing tasks on heterogeneous master-slave platforms has recently found important applications in Grid environments. The scheduling heuristics recently proposed for this problem are all constructive in nature and based on a common greedy criterion which depends on the momentary completion time values of the tasks. We show that this greedy decision criterion has shortcomings in exploiting the file-sharing interaction among tasks since completion time values are inadequate to extract the global view of this interaction. We propose a three-phase scheduling approach which involves initial task assignment, refinement, and execution ordering phases. For the refinement phase, we model the target application as a hypergraph and, with an elegant hypergraph-partitioning-like formulation, we propose using iterative-improvement-based heuristics for refining the task assignments according to two novel objective functions. Unlike the turnaround time, which is the actual schedule cost, the smoothness of proposed objective functions enables the use of iterative-improvement-based heuristics successfully since their effectiveness and efficiency depend on the smoothness of the objective function. Experimental results on a wide range of synthetically generated heterogeneous master-slave frameworks show that the proposed three-phase scheduling approach performs much better than the greedy constructive approach.
Dynamic Asynchronous Aggregate Search for Solving QoS Compositions of Web Services
Authors: Xuan Thang Nguyen, Ryszard Kowalczyk, Khoi Anh Phan
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

There has been recently an increase of interests in Distributed Constraint Satisfaction (DisCSP) algorithms. Most of these algorithms assume that the set of variables and constraints in a DisCSP are completely known and fixed. However, these assumptions do not hold in many open environments where unexpected events and changes can happen. Therefore this issue needs to be addressed in order for a DisCSP algorithm to be practically used in real life applications. Our contribution in this paper is two-fold. Firstly, we present an extended version of the Asynchronous Aggregate Search (AAS), called the Dynamic Asynchronous Aggregate Search (DynAAS) - as a new algorithm for dynamic and uncertain environments. Secondly, we investigate the applicability of DynAAS in the Web service domain and argue that DynAAS is suitable for solving the QoS compositions of Web services. We also carry out the experiments to show the efficiency of our proposed algorithm in solving the QoS composition problem.
An Algorithm for Identification of Reduced-Order Dynamic Models of Gas Turbines
Authors: Xuewu Dai, Tim Breikin, Hong Wang
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Model based approaches show a lot of advantages for fault detection and condition monitoring. Particularly, it is true in employing reduced order models for real-time parameter identification and output prediction of gas turbines. Many algorithms have been developed, but most of them focus on one-step-ahead prediction models and involve complex computation. These algorithms are not acceptable for long-term prediction and real-time condition monitoring. In this paper, an improved gradient method (Dynamic Gradient Descent) is proposed. The idea is to take account of the dependency of prediction errors and calculate the gradient information recursively. Not only low computation expense is achieved, but the non-Gaussian errors can also be overcome when this approach is applied to estimate parameters of a reduced order gas turbine model and to improve longterm prediction.
Signal compression using discrete fractional Fourier transform and set partitioning in hierarchical tree
Authors: C. Vijaya, J. S. Bhat
Venue: Signal Processing (2006)

Signal compression has been characterized as the removal of redundancy and irrelevancy. Fractional Fourier Transform (FRFT), an orthogonal, linear transform, is known to decompose the signal in terms of chirps. In this paper we propose a scheme for signal compression based on the combination of discrete FRFT (DFRFT) and set partitioning in hierarchical tree (SPIHT). The application of the scheme to different types of signals demonstrates significant reduction in bits leading to high signal compression ratio. The results are compared with those obtained with discrete cosine transform (DCT).
Functional Anatomy of Perceptual and Semantic Processing for Odors
Authors: Jean-P. Royet, Olivier Koenig, Marie-C. Gregoire, Luc Cinotti, Frank Lavenne, Didier Le Bars, Nicolas Costes, Michel Vigouroux, Vincent Farget, Gilles Sicard, André Holley, François Mauguière, Dominique Comar, Jean-C. Froment
Venue: Journal of Cognitive Neuroscience (1999)

The functional anatomy of perceptual and semantic processings for odors was studied using positron emission tomography (PET). The first experiment was a pretest in which 71 normal subjects were asked to rate 185 odorants in terms of intensity, familiarity, hedonicity, and comestibility and to name the odorants. This pretest was necessary to select the most appropriate stimuli for the different cognitive tasks of the second experiment. The second one was a PET experiment in which 15 normal subjects were scanned using the water bolus method to measure regional cerebral blood flow (rCBF) during the performance in three conditions. In the first (perceptual) condition, subjects were asked to judge whether an odor was familiar or not. In the second (semantic) condition, subjects had to decide whether an odor corresponded to a comestible item or not. In the third (detection) condition, subjects had to judge whether the perceived stimulus was made of an odor or was just air. It was hypothetized that the three tasks were hierarchically organized from a superficial detection level to a deep semantic level. Odorants were presented with an air-flow olfactometer, which allowed the stimulations to be synchronized with breathing.Subtraction of activation images obtained between familiarity and control judgments revealed that familiarity judgments were mainly associated with the activity of the right orbito-frontal area, the subcallosal gyrus, the left inferior frontal gyrus, the left superior frontal gyrus, and the anterior cingulate (Brodmann's areas 11, 25, 47, 9, and 32, respectively). The comestibility minus familiarity comparison showed that comestibility judgments selectively activated the primary visual areas. In contrast, a decrease in rCBF was observed in these same visual areas for familiarity judgments and in the orbitofrontal area for comestibility judgments. These results suggest that orbito-frontal and visual regions interact in odor processing in a complementary way, depending on the task requirements.
Supporting concept mapping for learning from text
Authors: Sabine Hauser, Matthias Nückles, Alexander Renkl
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

This study examines concept mapping as a follow-up study strategy for learning from text. Based on a task analysis of the sub-tasks learners must accomplish during mapping, we developed the following support measures: Participants (N = 102) either generated a map (1) from scratch (map-generation), (2) from a list of concepts (concepts-provided), (3) from spatially arranged concepts (concepts-arranged), or, alternatively, they (4) studied a worked-out map (worked-out map). The control-group (5) did not engage in mapping. Presenting a worked-out map enhanced learning most effectively. However, constructing a map from scratch was almost equally helpful. In contrast, students in the half-structured conditions (2 and 3) performed no better than the control condition. We concluded that both studying a worked-out map and generating one's own map allowed learners to devote attention to important parts of the learning contents. Half-structured mapping, in contrast, narrowed attention to specific aspects in a dysfunctional way.
An importance sampling method for portfolios of credit risky assets
Authors: William J. Morokoff
Venue: Proceedings of the 36th conference on Winter simulation (2004)

The distribution of possible future losses for a portfolio of credit risky corporate assets, such as bonds or loans, shows strongly asymmetric behavior and a fat tail as the consequence of the limited upside of credit (the promised coupon payment) and substantial downside if the corporation defaults. Because of correlation, it is not possible to fully diversify away this fat tail. Detailed correlation models require Monte Carlo simulation to determine the loss distribution for a credit portfolio. This paper describes an importance sampling method that provides substantial speed up for computing economic capital, the rare event quantile of the loss distribution that must be held in reserve by a lending institution for solvency. The method, based solely on correlation information, provides accuracy in the tail while maintaining suitable performance for statistics related to the center of the distribution. It is also suitable for long/short portfolios.
Search Experiment of Business-Rule by Dynamic Constraint Algebra
Authors: Rui KIMURA, Takayuki SHIGA, Mizuho IWAIHARA
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Although e-commerce is becoming popular, product rules, which describe various conditions such as prices, applicability, and discount conditions are still expressed in natural languages. These rules are difficult to deal with in relational databases because logics are separated from data. There is no system to search on multiple rules, so buyers have to check business rules one by one. In this paper, we take the case of airline tickets, hotel bookings and others as an example, and describe them in dynamic constraint conditions. We also show several queries written in Dynamic Constraint Algebra (DCA), and the result of the Dynamic Constraint Algebra Query Processing Engine can be utilized to present buyers available options, and to check how variables affect prices.
Rotation Forest: A New Classifier Ensemble Method
Authors: Juan J. Rodriguez, Ludmila I. Kuncheva
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

We propose a method for generating classifier ensembles based on feature extraction. To create the training data for a base classifier, the feature set is randomly split into K subsets (K is a parameter of the algorithm) and Principal Component Analysis (PCA) is applied to each subset. All principal components are retained in order to preserve the variability information in the data. Thus, K axis rotations take place to form the new features for a base classifier. The idea of the rotation approach is to encourage simultaneously individual accuracy and diversity within the ensemble. Diversity is promoted through the feature extraction for each base classifier. Decision trees were chosen here because they are sensitive to rotation of the feature axes, hence the name "forest.” Accuracy is sought by keeping all principal components and also using the whole data set to train each base classifier. Using WEKA, we examined the Rotation Forest ensemble on a random selection of 33 benchmark data sets from the UCI repository and compared it with Bagging, AdaBoost, and Random Forest. The results were favorable to Rotation Forest and prompted an investigation into diversity-accuracy landscape of the ensemble models. Diversity-error diagrams revealed that Rotation Forest ensembles construct individual classifiers which are more accurate than these in AdaBoost and Random Forest, and more diverse than these in Bagging, sometimes more accurate as well.
Optimal control of coupled spins in presence of longitudinal and transverse relaxation
Authors: D. Stefanatos, N. Khaneja
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 3 (2003)

Experiments in coherent spectroscopy correspond to control of quantum mechanical ensemble guiding them from initial to final target states. The control inputs (pulse sequences) that accomplish these transformations should be designed to minimize the effects of relaxation and to optimize the sensitivity of the experiments. For example in nuclear magnetic resonance (NMR) spectroscopy, a question of fundamental importance is what is the maximum efficiency of coherence or polarization transfer between two spins in the presence of relaxation. Furthermore what is the optimal pulse sequence which achieves this efficiency? This manuscript extends our previous work in the above problems. Here, we take into account both the longitudinal and the transverse relaxation mechanisms, thus generalizing our previous results, where the former had been neglected.
A Domain Based Prioritized Model forWeb Servers
Authors: Ash Mohammad Abbas, Vibhu Saujanya Sharma, Anoop Jain
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

In this paper, we present a multiple class model for Web servers when the request to be served are prioritized based on domains from which requests are originated. We evaluate the impact of assigning different priorities to different domains for a single server as well as for multiple servers. The main parameters considered for evaluation are the average waiting time and the standing ratio.
Home turf
Authors: Meg McGinity Shannon
Venue: Communications of the ACM (2006)

Service providers are building their networks right to your door---that is, your den, your bedroom, and your kitchen.
Anatomy: simple and effective privacy preservation
Authors: Xiaokui Xiao, Yufei Tao
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

This paper presents a novel technique, anatomy, for publishing sensitive data. Anatomy releases all the quasi-identifier and sensitive values directly in two separate tables. Combined with a grouping mechanism, this approach protects privacy, and captures a large amount of correlation in the microdata. We develop a linear-time algorithm for computing anatomized tables that obey the l-diversity privacy requirement, and minimize the error of reconstructing the microdata. Extensive experiments confirm that our technique allows significantly more effective data analysis than the conventional publication method based on generalization. Specifically, anatomy permits aggregate reasoning with average error below 10%, which is lower than the error obtained from a generalized table by orders of magnitude.
Understanding e-learning continuance intention: An extension of the Technology Acceptance Model
Authors: Juan Carlos Roca, Chao-Min Chiu, Francisco José Martínez
Venue: International Journal of Human-Computer Studies (2006)

Based on the expectancy disconfirmation theory, this study proposes a decomposed technology acceptance model in the context of an e-learning service. In the proposed model, the perceived performance component is decomposed into perceived quality and perceived usability. A sample of 172 respondents took part in this study. The results suggest that users' continuance intention is determined by satisfaction, which in turn is jointly determined by perceived usefulness, information quality, confirmation, service quality, system quality, perceived ease of use and cognitive absorption.
Cycle Embedding on Twisted Cubes
Authors: Sun-Yuan Hsieh, Pei-Yu Yu
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

A graph is pancyclic if it contains cycles of all lengths. A graph G is node-pancyclic if for every node u, G contains cycles C of all lengths such that u is in C. The twisted cube is an alternative to the popular hypercube network. In this paper, we prove that the twisted cube is node-pancyclic.
Managing Large-Scale Workflow Execution from Resource Provisioning to Provenance Tracking: The CyberShake Example
Authors: Ewa Deelman, Scott Callaghan, Edward Field, Hunter Francoeur, Robert Graves, Nitin Gupta, Vipin Gupta, Thomas H. Jordan, Carl Kesselman, Philip Maechling, John Mehringer, Gaurang Mehta, David Okaya, Karan Vahi, Li Zhao
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

This paper discusses the process of building an environment where large-scale, complex, scientific analysis can be scheduled onto a heterogeneous collection of computational and storage resources. The example application is the Southern California Earthquake Center (SCEC) CyberShake project, an analysis designed to compute probabilistic seismic hazard curves for sites in the Los Angeles area. We explain which software tools were used to build to the system, describe their functionality and interactions. We show the results of running the CyberShake analysis that included over 250,000 jobs using resources available through SCEC and the TeraGrid.