ppxscal/embedding_network huggingface dataset:
Theoretical approach to estimate the air rate in a heated medium temperature furnace
Authors: Minea Alina Adriana
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

In order to develop an appropriate mathematical model for a given materials processing system, several idealizations and simplifications were made to make the problem amenable to an analytical solution. A general procedure, which includes considerations of transient versus steady-state transport, number of spatial dimensions needed, neglecting of relatively small effects, idealizations such as isothermal or uniform heat flux conditions, and characterization of material properties, may be adopted to obtain the usual simplifications in analysis. In addition, the simplifications and approximations that lead to a mathematical model also indicate the dominant variables in a problem. This helps in developing efficient physical or experimental models. This paper focuses on the link between basic research on the underlying transport mechanisms and the engineering aspects associated with the process and the system.
Fostering the determinants of knowledge sharing in professional virtual communities
Authors: Ming-Ji James Lin, Shiu-Wan Hung, Chih-Jou Chen
Venue: Computers in Human Behavior (2009)

Professional virtual communities (PVCs), which are formed on the Internet, are expected to serve the needs of members for communication, information, and knowledge sharing. The executives of organizations should consider PVCs as a new innovation or knowledge pool since members share knowledge. However, many PVCs have failed due to members' low willingness to share knowledge with other members. Thus, there is a need to understand and foster the determinants of members' knowledge sharing behavior in PVCs. This study develops an integrated model designed to investigate and explain the relationships between contextual factors, personal perceptions of knowledge sharing, knowledge sharing behavior, and community loyalty. Empirical data was collected from three PVCs and tested using structural equation modeling (SEM) to verify the fit of the hypothetical model. The results show that trust significantly influences knowledge sharing self-efficacy, perceived relative advantage and perceived compatibility, which in turn positively affect knowledge sharing behavior. Furthermore, the study finds that the norm of reciprocity does not significantly affect knowledge sharing behavior. The results of the study can be used to identify the motivation underlying individuals' knowledge sharing behavior in PVCs. By investigating the impacts of contextual factors and personal perceptions on knowledge sharing behavior, the integrated model better explains behavior than other proposed models. This study might help executives of virtual communities and organizations to manage and promote these determinants of knowledge sharing to stimulate members' willingness to share knowledge and enhance their virtual community loyalty. As only little empirical research has been conducted on the impact of knowledge sharing self-efficacy, perceived relative advantage, and perceived compatibility on the individual's knowledge sharing behavior in PVCs, the empirical evidence reported here makes a valuable contribution in this highly important area.
Analytical models for understanding misbehavior and MAC friendliness in CSMA networks
Authors: Zhefu Shi, Cory Beard, Ken Mitchell
Venue: Performance Evaluation (2009)

Nodes using contention-based CSMA protocols are susceptible to the misbehavior of other nodes and also have little flexibility in controlling quality of service. To address the misbehavior problem, continuous-time protocols are proposed. The effects of ''misbehavior'' on the QoS of all nodes in the system caused by changing the cheater's arrival rate and backoff rate are studied. The problem of flexibility in controlling QoS is addressed by introducing the concept of ''MAC friendliness'' where nodes can adjust arrival rates and backoff rates while maintaining a fixed share of the channel. The continuous-time system is modeled using an iterative method and matrix exponential distributions. Collision probabilities are determined both by the channel utilization of the entire system, as well as the actual stage within the backoff process. The model itself is a key contribution because it is accurate over all ranges of traffic loads and models both queueing within nodes and contention for the channel.
Is allowing trading enough? Making secondary markets in spectrum work
Authors: Pietro Crocioni
Venue: Telecommunications Policy (2009)

The debate on spectrum reforms has mostly focused on the choice between a property rights and a commons regime. This article argues that moving to a property right system requires careful attention to details in order to avoid that ''micro'' rather than ''macro'' factors may prevent efficient trades from taking place. It provides a framework to conduct this assessment, identifies a number of possible concerns and puts forward some solutions.
Post-quantum cryptography: lattice signatures
Authors: Johannes Buchmann, Richard Lindner, Markus R&#x00fc;ckert, Michael Schneider
Venue: Computing (2009)

This survey provides a comparative overview of lattice-based signature schemes with respect to security and performance. Furthermore, we explicitly show how to construct a competitive and provably secure Merkle tree signature scheme solely based on worst-case lattice problems.
Explanatory Capabilities in the CREEK Knowledge-Intensive Case-Based Reasoner
Authors: Anders Kofod-Petersen, Jörg Cassens, Agnar Aamodt
Venue: Proceeding of the 2008 conference on Tenth Scandinavian Conference on Artificial Intelligence: SCAI 2008 (2008)

The ability to give explanations for its reasoning and behaviour is a core capability of an intelligent system. There are a number of different goals a user can have towards such explanations. This paper presents how the knowledge intensive case-based reasoning framework CREEK can support some of these different goals in an ambient intelligence setting.
Calibrating Probability Density Forecasts with Multi-objective Search
Authors: Michael Carney, Pádraig Cunningham
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

The two objectives when estimating the conditional density function in a regression problem are to maximise sharpness (the density rewarded to the actual observation), while maintaining calibration (the empirical validity of the probability estimates). In this paper we outline a process of optimisation that maximises both these objectives simultaneously to make better probabilistic predictions.
Plenary lecture V: intelligent systems
Authors: Ioan-Gheorghe Ratiu
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

Many definitions of intelligence exist, but for our purposes we use the following: intelligence is the ability to reach ones objectives. A system is more intelligent if it reaches its objectives faster and easier. This includes the ability to learn to do this. The intelligence of a system is a property of its mind. The mind is the functioning of its brain. Intelligent System (IS) is a system that learns during its existence. (In other words, it learns, for each situation, which response permits it to reach its objectives.) It continually acts, mentally and externally, and by acting reaches its objectives more often than pure chance would indicate. This paper approaches the subject of paradigms for the categories of intelligent systems. First we can look at the term paradigm in its scientific meaning and then we make acquaintance with the main categories of intelligent systems (expert systems, intelligent systems based on genetic algorithms, artificial neuronal systems, fuzzy systems, hybrid intelligent systems). We will see that every system has one or more paradigms, but hybrid intelligent systems combine paradigms because they are made of different technologies.
Probabilistic Similarity Search for Uncertain Time Series
Authors: Johannes Aßfalg, Hans-Peter Kriegel, Peer Kröger, Matthias Renz
Venue: Proceedings of the 21st International Conference on Scientific and Statistical Database Management (2009)

A probabilistic similarity query over uncertain data assigns to each uncertain database object o a probability indicating the likelihood that o meets the query predicate. In this paper, we formalize the notion of uncertain time series and introduce two novel and important types of probabilistic range queries over uncertain time series. Furthermore, we propose an original approximate representation of uncertain time series that can be used to efficiently support both new query types by upper and lower bounding the Euclidean distance.
A methodology to evaluate the aerosol effective radius based on MODIS aerosol products applicable to other satellite platforms
Authors: Omaira E. Garcia, Ana M. Diaz, Francisco J. Exposito, Juan P. Diaz, Maria D. Gelado, Carmen Guirado
Venue: International Journal of Remote Sensing (2009)

A strategy to evaluate the effective radius (r eff) as a function of aerosol retrievals is provided in this work. This methodology is based on the MODerate resolution Imaging Spectroradiometer (MODIS) aerosol products, using the 0.66 and 0.87 µm bands. These data have been studied from February 2000 to December 2005 in a grid situated at Subtropical North-east Atlantic region. To reduce the number of MODIS useful variables a Factorial Analysis by Principal Components has been applied, decreasing the aerosol parameters from 18 to five. With these parameters, backscattering ratios and asymmetry factors at 0.66 and 0.87 µm besides the Ångstrom parameter, a lineal multivariate analysis technique has been applied to find the combination of variables that better evaluate the r eff. The standard error for the predicted value of r eff is ±0.09 µm. The expression obtained here has the advantage that it can be applied to other remote sensors like AVHRR/NOAA, HRV/SPOT, TM/LANDSAT, and so on, with long time series.
Intelligent Process Planning Optimization for Product Cost Estimation
Authors: W. D. Li, S. K. Ong, A. Y. C. Nee, L. Ding, C. A. McMahon
Venue: Proceeding of the 2006 conference on Integrated Intelligent Systems for Engineering Design (2006)

Manufacturing cost is crucial for the economic success of a product, and early and accurate estimation of manufacturing cost can support a designer to evaluate a designed model dynamically and efficiently for making cost-effective decisions. Manufacturing cost estimation is closely related to process planning problems, in which machining operations, machining resources, operation sequences, etc., are selected, determined and optimized. To solve the intractable decision-making issues in process planning with complex machining constraints, three intelligent optimization methods, i.e., Genetic Algorithm (GA), Simulated Annealing (SA) and Tabu Search (TS), have been developed to determine the optimal or near-optimal allocation of machining resources and sequence of machining operations for a process plan simultaneously, and a fuzzy logic-based Analytical Hierarchical Process technique has been applied to evaluate the satisfaction degree of the machining constraints for the process plan. Case studies, which are used to compare the three developed methods, are discussed to highlight their characteristics in the aspects of solution quality, computation efficiency and optimization result robustness.
On the Development of Extended Communication Driven DSS within Dynamic Manufacturing Networks
Authors: Sébastien Kicin, Christoph Gringmuth, Jukka Hemilä
Venue: Proceeding of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges (2008)

The slow progress to date regarding inter-organizational collaborative decision management within manufacturing supply chains is due to a lack of common understanding of this concept, and the difficulty of integrating external requirements of customers and suppliers into opaque internal decision control. In this paper, we focus on the production management of dynamic manufacturing networks that is characterized by non-centralized decision making. We set out to clarify internal decision collaboration concepts based on research and technology led on collaborative work and enterprise modeling techniques, and discuss how IT can support and improve business and managerial decision-making within supply chains. This paper begins with examining the Communication Driven Decision Support System (DSS) concept and its integration within a supply chain point of view. A framework for inter-organizational decision support is then discussed and linked to the traditional Decision Support Systems and the overall Information Management solutions. We conclude that the effectiveness of supply chain collaboration relies upon two factors: the level to which it integrates internal and external decisions at strategic, tactical and operational levels, and the level to which the efforts are aligned to the supply chain settings in terms of the geographical dispersion, the demand pattern, and the product characteristics.
Generating 5-regular planar graphs
Authors: Guoli Ding, Jinko Kanno, Jianning Su
Venue: Journal of Graph Theory (2009)

For k=0, 1, 2, 3, 4, 5, let ${\cal{P}}_{k}$ be the class of k -edge-connected 5-regular planar graphs. In this paper, graph operations are introduced that generate all graphs in each ${\cal{P}}_{k}$. &copy; 2009 Wiley Periodicals, Inc. J Graph Theory 61: 219&ndash;240, 2009
Overcoming the First Hurdle: Why Organizations Do Not Adopt CMMI
Authors: Nazrina Khurshid, Paul L. Bannerman, Mark Staples
Venue: Proceedings of the International Conference on Software Process: Trustworthy Software Development Processes (2009)

This paper further examines why some software development organizations decide not to adopt CMMI by replicating an earlier Australian study in another country. The study examines data collected from the efforts of three consulting firms to sell a CMMI Level 2 program subsidized by the Malaysian government. The most frequently cited reasons for not adopting CMMI were: the program was too costly; the companies were unsure of the benefits; the organization was too small; and/or the organization had other priorities. The Malaysian study extends and generally supports the Australian study (differences were found in the frequency ordering of reasons and two new reason categories had to be introduced). It also adds to our understanding of CMMI adoption decisions. Based on the results, we conclude that to achieve broader impact in practice, software process improvement (SPI) researchers need to develop a stronger cost-benefit analysis for SPI, recognising it as a business investment rather than just a product or process quality improvement technique, and provide flexible entry options to enable more companies of difference sizes to take the adoption leap.
Decision maker friendly approach for pricing software
Authors: Ajay K. Aggarwal, Dinesh S. Dave
Venue: International Journal of Computer Applications in Technology (2009)

Techniques for predicting computer software prices are of interest to researchers. This paper reviews and extends the earlier contributions of the authors to the field. It illustrates a new approach for predicting software prices. The illustrated approach is superior to previous approaches in two ways. First, the authors employ a unique factoring technique based on variable context that makes the final results easy to interpret and use. Second, the authors use variable transformations that have worked successfully in pricing computer hardware. The paper discusses the model construction, accuracy and results and helps decision makers better understand and control software prices.
Simulation Study of CPG Model: Exploring of a Certain Characteristics of Rhythm of Gait Movement on the Intelligent Creature
Authors: Wei Dong, Rubin Wang, Zhikang Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Movement of the intelligent beings is various, which is divided into two major types: the rhythmic movement and the non-rhythmic movement. The generation of the rhythmic movement uncertain is induced by the responding signals of the peripheral neural receivers, but is generated spontaneously by the central pattern generator (CPG). CPG not only can generate the rhythmic movement, but also can change the frequency and pattern of movement. This paper is based on the revised CPG neural network model which has relation with the movement of legs. We carry on a series of computer number analysis and imitation to further elaborate many characteristics of the rhythmic movement. The research results show that three greatest characteristics of the rhythmic movement respectively are: rhythm, coordination and variety. The paper further reveals the biological properties of gait movement on the intelligent beings and the characteristics of various rhythmic movements.
The Distribution of Student Errors Across Schools: An Initial Study
Authors: Rob Weitz, Neil Heffernan, Viswanathan Kodaganallur, David Rosenthal
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

The little previous research comparing student errors across schools indicates that student “bugs” do not transfer --that is, the distribution of students' systematic errors in one school does not significantly match those in other schools. The issue has practical implications as cognitive (or “model-tracing”) tutors rely on the modeling of student errors in order to provide targeted remediation. In this study we examine the responses of students at three schools to a middle-school mathematics problem. We find the same error is the most common error across all schools, and this single error accounts for some half of all incorrect responses at each school. The top five errors are similar across schools and account for some 2/3 of errors at each school. We conclude that in this example, there appears to be considerable overlap of student errors across schools.
User-oriented design and tangible interaction for kindergarten children
Authors: Javier Marco, Eva Cerezo, Sandra Baldasarri, Emanuela Mazzone, Janet C. Read
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

This paper describes a tabletop prototype that allows kindergarten children to take the benefits of the new pedagogical possibilities that tangible interaction and tabletop technologies offer to manipulative learning. After analyzing children's cognitive and psychomotorial skills, we have designed and tuned a prototype game suitable for children aged 3 to 4 years old. Our prototype uniquely combines low cost tangible interaction and tabletop technology with tutored learning. The design has been based on observations of the children using the technology, letting them freely play with the application during three play sessions. These observational sessions informed the design decisions for the game whilst also confirming the children's enjoyment with the prototype.
Comparing Fully and Partially Synthetic Datasets for Statistical Disclosure Control in the German IAB Establishment Panel
Authors: Jörg Drechsler, Stefan Bender, Susanne Rässler
Venue: Transactions on Data Privacy (2008)

For datasets considered for public release, statistical agencies have to face the dilemma of guaranteeing the confidentiality of survey respondents on the one hand and offering sufficiently detailed data for scientific use on the other hand. For that reason a variety of methods that address this problem can be found in the literature. In this paper we discuss the advantages and disadvantages of two approaches that pro-vide disclosure control by generating synthetic datasets: The first, proposed by Rubin [1], generates fully synthetic datasets while the second suggested by Little [2] imputes values only for selected variables that bear a high risk of disclosure. Changing only some variables in general will lead to higher analytical validity. However, the disclosure risk will also increase for partially synthetic data, since true values remain in the data-sets. Thus, agencies willing to release synthetic datasets will have to decide, which of the two methods balances best the trade-off between data utility and disclosure risk for their data. We offer some guidelines to help making this decision. To our knowledge, the two approaches never haven been empirically compared in the literature so far. We apply the two methods to a set of variables from the 1997 wave of the German IAB Establishment Panel and evaluate their quality by comparing results from the original data with results we achieve for the same analyses run on the datasets after the imputation procedures. The results are as expected: In both cases the analytical validity of the synthetic data is high with partially synthetic datasets outperforming fully synthetic datasets in terms of data utility. But this advantage comes at the price of a higher disclosure risk for the partially synthetic data.
A technique for correlating images on head mounted displays with virtual background scenery
Authors: Sanjeeb Nanda, Rick Pray
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

Visual training systems employing high fidelity image generation capabilities have gained immense popularity over the years in a variety of training applications. They offer economy of cost, and precise scenario execution with consistency across unlimited trials. Training systems using head mounted displays (HMD) are a subset of this fast proliferating technology. However, the implementation and use of HMDs poses a number of challenges. A significant one is the problem of correlating the images that are rendered on the HMD's visor in time and space with the background scenery rendered on a projection screen. In this paper we describe a method to solve this problem using Kalman filters, and show the accuracy of its implementation in practice.
Extending MARIE: an N-gram-based SMT decoder
Authors: Josep M. Crego, José B. Mariño
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

In this paper we present several extensions of MARIE, a freely available N-gram-based statistical machine translation (SMT) decoder. The extensions mainly consist of the ability to accept and generate word graphs and the introduction of two new N-gram models in the loglinear combination of feature functions the decoder implements. Additionally, the decoder is enhanced with a caching strategy that reduces the number of N-gram calls improving the overall search efficiency. Experiments are carried out over the Eurpoean Parliament Spanish-English translation task.