ppxscal/embedding_network huggingface dataset:
A Printing Workflow Recommendation Tool--Exploiting Correlations between Highly Sparse Case Logs
Authors: Ming Zhong, Tong Sun
Venue: Proceedings of the 5th International Conference on Machine Learning and Applications (2006)

As a user preference prediction mechanism, recommendation techniques have been widely used to support personalized information filtering in current e-commerce applications. We build a recommendation tool into the existing Xerox printing workflow configuration system in order to provide new users with a number of solutions that are possibly of their interests. Such solution recommendations can significantly improve the system efficiency and accuracy by reducing workflow generation overhead and helping users quickly identify their needs. In our work, the main challenge is the high sparsity inherent to our application data -- most fields have missing values due to a customer's lack of background or uncertainty on their specific needs. We address this problem by using Latent Semantic Indexing (LSI) to merge original sparse data records into dense and semantic records. The generated dense data are then grouped into clusters based on their correlations. These clusters, together with their user patterns and representative workflows, are used to support efficient online workflow recommendation. Our implemented tool is able to achieve 83% accuracy on a dataset of 4569 case logs with 91% average sparseness.
Support Vector Machines for Computer Assisted Diagnostic Neuropathology
Authors: Muhammad S. Hassan, Peter J. Bentley, Malcolm Galloway
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

This work describes research towards computerassisted diagnostic neuropathology using support vector machines. The system processes digital photomicrographs in three phases: image preprocessing, feature extraction and classification. Compactness, fractal dimensions and co-occurrence matrices were used to generate a feature vector and then three different kernels were used for support vector machine classification. The results showed an increase in the system's performance when a combination of features was used rather than a single feature, with best results obtained for combination of all three features. Despite limited data, the results were promising, suggesting that this approach is worth exploring further.
Cognitive strategies in dynamic modeling: case studies of opportunities taken and missed
Authors: Steven J. Stratford, Joseph S. Krajcik, Elliot Soloway
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

New technologies offer new opportunities for engaging students in performances of higher-level thinking [Perkins 1985; Salomon, Perkins & Globerson 1991]. The increasing presence of sophisticated computers in classrooms, their expanding computational power, and advances in software interface design [Jackson, Stratford, Krajcik, & Soloway in press] bring opportunities closer to every student, and make it possible for them to engage in more sophisticated and technology-intensive activities such as dynamic modeling. Computer-based dynamic modeling has long been recognized as a scientific activity that promotes deep system analysis, careful cause-and-effect reasoning, and synthesis, along with articulating explanations about phenomena and testing and debugging. With the development of dynamic modeling environments for learners, we're investigating the extent to which students who construct dynamic models take advantage of those opportunities for cognitive engagement. Technology can play a supportive role in helping learners accomplish unfamiliar or cognitively difficult tasks [Guzdial 1995; Jackson et al. in press]. In this paper we present two case studies of pairs of students who, while creating models of their own design, engaged in a range of cognitive activities. The cases we present represent students in the middle range of abilities and performance: they did not struggle as they created their model, nor was what they produced exemplary.
Classification of Petroleum Well Drilling Operations Using Support Vector Machine (SVM)
Authors: Adriane B. S. Serapiao, Rogerio M. Tavares, Jose Ricardo P. Mendes, Ivan R. Guilherme
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)

During the petroleum well drilling operation many mechanical and hydraulic parameters are monitored by an instrumentation system installed in the rig called a mud-logging system. These sensors, distributed in the rig, monitor different operation parameters such as weight on the hook and drillstring rotation. These measurements are known as mud-logging records and allow the online following of all the drilling process with well monitoring purposes. However, in most of the cases, these data are stored without taking advantage of all their potential. On the other hand, to make use of the mud-logging data, an analysis and interpretationt is required. That is not an easy task because of the large volume of information involved. This paper presents a Support Vector Machine (SVM) used to automatically classify the drilling operation stages through the analysis of some mud-logging parameters. In order to validate the results of SVM technique, it was compared to a classification elaborated by a Petroleum Engineering expert.
A Semantic Overlay for Self- Peer-to-Peer Publish/Subscribe
Authors: E. Anceaume, M. Gradinariu, A. K. Datta, G. Simon, A. Virgillito
Venue: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (2006)

Publish/Subscribe systems provide a useful platform for delivering data (events) from publishers to subscribers in an anonymous fashion in distributed networks. In this paper, we promote a novel design principle for self-. dynamic and reliable content-based publish/subscribe systems and perform a comparative analysis of its probabilistic and deterministic implementations. More specifically, we present a generic content-based publish/subscribe system, called DPS (Dynamic Publish/Subscribe). DPS combines classical content-based filtering with self-. (self-organizing, selfconfiguring, and self-healing) subscription-driven clustering of subscribers. DPS gracefully adapts to failures and changes in the system while achieving scalable events delivery. DPS includes a variety of fault-tolerant deterministic and probabilistic content-based publication/subscription schemes. These schemes are targeted toward scalability, and aim at reducing and distributing the number of messages exchanged. Reliability and scalability of our system are shown through analytical and experimental evaluation.
Halton Sequences Avoid the Origin
Authors: Art B. Owen
Venue: SIAM Review (2006)

The nth point of the Halton sequence in [0,1]d is shown to have components whose product is larger than Cn-1, where C > 0 depends on d. This property makes the Halton sequence very well suited to quasi-Monte Carlo (QMC) integration of some singular functions that become unbounded as the argument approaches the origin. The Halton sequence avoids a similarly shaped (though differently sized) region around every corner of the unit cube, making it suitable for functions with singularities at all corners. Convergence rates are established for QMC integration based on two assumptions: a growth condition on the integrand, and a measure of how the sample points avoid the boundary. In some settings the error is O(n-1 + epsilon), while in others the error diverges to infinity. Star discrepancy does not suffice to distinguish the cases.
Crash failure detection in asynchronous agent communication languages
Authors: Nicola Dragoni, Mauro Gaspari
Venue: Autonomous Agents and Multi-Agent Systems (2006)

Agent Communication Languages (ACLs) have been developed to provide a way for agents to communicate with each other supporting cooperation in Multi-Agent Systems (MAS). In the past few years many ACLs have been proposed for MAS and new standards are emerging such as the ACL developed by the Foundation for Intelligent Physical Agents (FIPA). Despite these efforts, an important issue in the research on ACLs is still open and concerns how these languages should deal with failures of agents in asynchronous MAS. The Fault Tolerant Agent Communication Language ( $$\mathbb{FT}$$ - $$\mathbb{ACL}$$ ) presented in this paper addresses this issue dealing with crash failures of agents. $$\mathbb{FT}$$ - $$\mathbb{ACL}$$ provides high-level communication primitives which support a fault-tolerant anonymous interaction protocol designed for open MAS. We present a formal semantics for $$\mathbb{FT}$$ - $$\mathbb{ACL}$$ and a formal specification of the underlying agent architecture. This formal framework allows us to prove that the ACL satisfies a set of well defined knowledge-level programming requirements. To illustrate the language features we show how $$\mathbb{FT}$$ - $$\mathbb{ACL}$$ can be effectively used to write high-level executable specifications of fault tolerant protocols, such as the Contract Net one.
A new fine-grained evolutionary algorithm based on cellular learning automata
Authors: Reza Rastegar, Mohammad Reza Meybodi, Arash Hariri
Venue: International Journal of Hybrid Intelligent Systems (2006)

In this paper a new evolutionary algorithm, called the CLA-EC (Cellular Learning Automata Based Evolutionary Computing), is proposed. This algorithm is a combination of evolutionary algorithms and the Cellular Learning Automata (CLA). In the CLA-EC each genome string in the population is assigned to one cell of the CLA, which is equipped with a set of learning automata. Actions selected by the learning automata of a cell determine the genome string for that cell. Based on a local rule, a reinforcement signal vector is generated and given to the set of learning automata residing in the cell. Each learning automaton in the cell updates its internal structure according to a learning algorithm and the received signal vector. The processes of action selection and updating the internal structures of learning automata are repeated until a predetermined criterion is met. To show the efficiency of the proposed model, to solve several optimization problems including real valued function optimization and data clustering problems.
Fast Composition Planning of OWL-S Services and Application
Authors: Matthias Klusch, Andreas Gerber
Venue: Proceedings of the European Conference on Web Services (2006)

In this paper, we present the implementation, evaluation, and application of our OWL-S service composition planner OWLS-XPlan. Medical services described in OWL-S 1.1 and ontologies are converted to initial state and goal descriptions in PDDL 2.1, which are then used by the fast heuristic FF planner XPlan for generating an execution complete composition plan. Results of experimental evaluation of XPlan shows its top performance compared with other selected AI planners. OWLS-XPlan is used in an agent based mobile e-Health system for emergency medical assistance planning tasks.
Experience report on software product line evolution due to market reposition
Authors: Samuel A. Ajila, Antonio J. Bailetti, Razvan T. Dumitrescu
Venue: Proceedings of the 2004 workshop on Quantitative techniques for software agile process (2004)

This paper presents the result of a study on the changes that occurred in the product line of a telecommunication equipments supplier because of the top management decision to change the product line's target market. The study examines six years of data and identifies potential relationships between changes in the product line and changes in the company's customer, inner context, and product layers. Some of the key findings are: (i) Sales are negatively related to product line growth and positively related to design turnover and the number of designers assigned to the product line. (ii) There is no relationship between the size of the code added to the product line and the number of designers required to develop and test it. (iii) There is a positive relationship between designer turnover and impact of change. (iv) The market downturn has an explicit impact on software development activities.
Soft Benchmarks-Based Application Performance Prediction Using a Minimum Training Set
Authors: Farrukh Nadeem, Muhammad Murtaza Yousaf, Radu Prodan, Thomas Fahringer
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

Application execution time prediction is of key importance in making decisions about efficient usage of Grid resources. Grid services lack support of a generic application execution time prediction service due to environment specific solutions provided by the existing prediction techniques. To remedy this, we present a generic and comprehensive system to provide execution time predictions of applications on different Grid-sites. Our system is based on a two layered training phase to minimize the training effort, which is our first main contribution. The training phase is driven by a novel experimental design. We also introduce a mechanism of sharing performance measurements across the Grid, on the basis of soft benchmarks, which is our second contribution. Both of these phases support our prediction engine to serve robust predictions. Experiments from the prototype implementation are shown to demonstrate the effectiveness of our proposed system.
An Approach to Estimate Domain of Attraction for Nonlinear Control Systems
Authors: Der-Cherng Liaw, Ching-Hung Lee
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

this paper, we present the results of estimation of domain of attraction for nonlinear control systems. The theoretical results of [[9]] is modified and a computational methods to enlarge the domain of attraction for nonlinear control systems is proposed. By the way, we have computational algorithms to estimate the attraction region for locally stable nonlinear systems in uncontrolled version. It is achieved by the construction of Lyapunov function for the nonlinear systems. Numerical results are given to demonstrate the applications.
Seamless design: Impedance mismatch revisited
Authors: P. G. Cherkasova, B. A. Novikov
Venue: Programming and Computing Software (2006)

A pattern for information system implementation is proposed. The pattern is based on the commonly accepted object-oriented methodologies of design and development oriented toward widely used imperative programming languages. At the same time, this pattern makes it possible to fully use the power of declarative possibilities of the DBMS query language. The presented estimations demonstrate much higher performance of the applications obtained compared to those created by means of commonly accepted techniques.
Technology for Medical Education, Research, and Disease Screening by Exploitation of Biomarkers in a Large Collection of Uterine Cervix Images
Authors: L. Rodney Long, Sameer Antani, Jose Jeronimo, Mark Schiffman, Mike Bopf, Leif Neve, Carl Cornwell, Scott R. Budihas, George R. Thoma
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

The Communications Engineering Branch of the National Library of Medicine is collaborating with the National Cancer Institute (NCI) in developing applications for medical education, research, and disease screening for precancer detection in the uterine cervix. These applications include (1) expert marking/labeling of tissue regions, (2) Web viewing/ interpretation of histology images, (3) image database/retrieval, and (4) training/testing in clinical image interpretation. Initial NCI studies have been conducted in expert cervicography marking and histology evaluation. We are working toward making cervix images searchable by content-based image retrieval (CBIR). Image pre-processing to remove specular reflection artifacts has achieved 90% success (120 images). Similar results have been obtained for automated location of cervix regions, using Gaussian Mixture Modeling (GMM) with Lab color and one geometric feature. We describe initial classification experiments to discriminate clinically significant tissue, using RGB, HSV, Lab, and YCbCr color models, texture measures, and GMM, Fuzzy C-means, and deterministic annealing algorithms.
Facial Action Coding Using Multiple Visual Cues and a Hierarchy of Particle Filters
Authors: Joel C. McCall, Mohan M. Trivedi
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

In this paper we present a framework for tracking nonrigid facial landmarks by combining various visual cues at multiple levels of detail. Using a probabilistic framework consisting of a hierarchy of particle filters, we are able to track individual facial landmarks using multiple visual cues at the local level, as well as tracking results at more coarse level of detail. This allows for the fusion of global and local cues in an efficient and robust manner. Testing is performed by tracking and classifying facial action codes obtained from the Cohn-Kanade AU-Coded Facial Expression Database.
Predictor@Home: A "Protein Structure Prediction Supercomputer' Based on Global Computing
Authors: Michela Taufer, Chahm An Andreas Kerstens, Charles L. Brooks III
Venue: IEEE Transactions on Parallel and Distributed Systems (2006)

Predicting the structure of a protein from its amino acid sequence is a complex process, the understanding of which could be used to gain new insight into the nature of protein functions or provide targets for structure-based design of drugs to treat new and existing diseases. While protein structures can be accurately modeled using computational methods based on all-atom physics-based force fields including implicit solvation, these methods require extensive sampling of native-like protein conformations for successful prediction and, consequently, they are often limited by inadequate computing power. To address this problem, we developed Predictor@Home, a "structure prediction supercomputer” powered by the Berkeley Open Infrastructure for Network Computing (BOINC) framework and based on the global computing paradigm (i.e., volunteered computing resources interconnected to the Internet and owned by the public). In this paper, we describe the protocol we employed for protein structure prediction and its integration into a global computing architecture based on public resources. We show how Predictor@Home significantly improved our ability to predict protein structures by increasing our sampling capacity by one to two orders of magnitude.
Tuning IMS LD for Implementing a Collaborative Lifelong Learning Scenario
Authors: Davinia Hernandez-Leo, Eloy D. Villasclaras-Fernandez, Juan I. Asensio-Perez, Yannis A. Dimitriadis, Miguel L. Bote-Lorenzo, Jose A. Marcos-Garcia
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

This paper describes an approach for modeling and implementing a collaborative learning situation, which is part of a real lifelong learning scenario in astronomy. We adopt and slightly adjust IMS Learning Design for computationally representing the script so that collaborative tools can be satisfactorily employed. We use Collage editor, which enables the re-use of general structures proposed by Collaborative Learning Flow Patterns, for authoring the script and Gridcole system for executing it. The paper also shows the log-files produced by the employed tools. The teacher can use these log-files to monitor the evolution of the process for evaluation and regulation purposes.
Anisotropy-based robust performance analysis of finite horizon linear discrete time varying systems
Authors: I. G. Vladimirov, P. Diamond, P. Kloeden
Venue: Automation and Remote Control (2006)

We consider a problem of robust performance analysis of linear discrete time varying systems on a bounded time interval. The system is represented in the state-space form. It is driven by a random input disturbance with imprecisely known probability distribution; this distributional uncertainty is described in terms of entropy. The worst-case performance of the system is quantified by its a-anisotropic norm. Computing the anisotropic norm is reduced to solving a set of difference Riccati and Lyapunov equations and a special form equation.
User-generated content in mobile multimedia: empirical evidence from user studies
Authors: I. Koskinen
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

This paper presents evidence from two studies on the use of mobile multimedia. Mobile image has more than 1000 multimedia messages collected from a pilot in 1999-2001. Radiolinja has more than 4000 messages from a multimedia messaging (MMS) pilot in summer 2002. In Radiolinja, it was found that 32% of messages were a part of an interaction chain such as question-answer pairs, greetings, or stories. Thus, approximately 50% of traffic in the network arose from interactional needs rather than from individual, unattached messages. After the practice phase, fluctuations in use are largely explained by interactional reasons. This paper suggests that user-generated content is a key element in the success of mobile multimedia.
Specification of a framework for the anonymous use of privileges
Authors: Vicente Benjumea, Javier Lopez, Jose M. Troya
Venue: Telematics and Informatics (2006)

In this paper we have defined an open framework to support open distributed applications where anonymous transactions based on user privileges play an important role. The goal of the framework is to provide a basis to the application level, and is presented from an open and general perspective where many different implementation schemes can fit. Moreover, we have presented a set of requirements that implementation schemes must fulfill to conform a fully anonymous privilege system, which guarantees to supported applications that anonymity will be preserved in remote transactions. Finally, we present an application scenario using the services provided by the framework in order to better show the possibilities of what this type of systems offers.
Building Scalable and High Efficient Java Multimedia Collaboration
Authors: Wenjun Wu, Tao Huang, Geoffrey Fox
Venue: Proceedings of the International Symposium on Collaborative Technologies and Systems (2006)

Java Media Framework (JMF) is platform-independent multimedia programming framework which enables easy and fast development of collaborative applications. This paper describes our work on building a high efficient multimedia collaboration system using JMF. We introduce a new rendering approach to optimize the performance of JMF and add screen capturing capability as well as new codecs. Based on this enhanced framework, a high efficient and platform-independent conferencing client named Global-MMCS AVPortlet is developed. The performance evaluation shows that it outperforms other well-known video collaboration tools.